GR1009485B - Method of integrated zonal exchange - based and nodal flow - based electricity exchange system clearing - Google Patents

Abstract

The invention relates to a method of an electricity exchange system comprising a set of nodes of a physical electricity network, a set of transmission lines interconnecting said network nodes, wherein line energy physical flow is constrained by an upper limit, where energy physical flow is defined as a linear function of nodal energy injections, whereas nodal energy injection is defined as energy injected minus energy absorbed in the respective node, further comprising a group of nodes in arbitrary number of electricity exchange zones, a set of energy exchanges transacted between interconnected electricity exchange zones, a set of supply orders for energy injection in each node, and a set of demand orders for energy absorption in each node, the method is remarkable in that it comprises the steps of setting an electricity exchange zone clearing signal for each electricity exchange zone, establishing cleared supply energy volumes in each node with supply order thresholds < or = the corresponding electricity exchange zone clearing signal, establishing cleared demand energy volumes in each node with demand order thresholds > or = the corresponding electricity exchange zone clearing signal, setting transmission line flows < or = the respective flow limit, establishing energy exchange volumes between electricity exchange zones with direction from an electricity exchange zone with a lower clearing signal to an electricity exchange zone with a higher zone clearing signal, and making electricity exchange zone energy balance of corresponding nodal net energy injections of nodes included within the electricity exchange zone and energy exchanges with all interconnected electricity exchange zones.

Description

COMPLETE TRADING SYSTEM CLEARING METHOD

ELECTRICITY BASED ON ZONE TRANSACTIONS AND NODE FLOWS

OF THE TRANSPORTATION SYSTEM

Description

The technical field of the invention

The present invention relates to a method of clearing a multi-zonal electricity market according to a congestion management approach based on electricity flows in the transmission system, and which (a) is subject to normal constraints and/or disturbance constraints on the physical transmission lines of system - nodal configuration at the physical level - and (b) clears bilateral trade between the interconnected zones of the system - zoning at the commercial level. Furthermore, the invention relates to a system, through which the above clearing method is carried out, for the processing of bids submitted to auctions by electricity market participants for electricity market products, and which system mainly consists of a database , a processor connected to the database, and means for publishing the results of the auction to inform electricity market participants,

Background of the invention

The European Power Exchanges incorporate congestion management procedures in the day-ahead markets that operate by activating two standard models: a model based on transactions, i.e. available transmission capacity, or a model based on electricity flows [2]-[3 ]. The origin and computational framework for the optimal (ie, maximum) utilization of interconnections are different in the two models, although they derive from the same philosophy (security of supply taking into account constraints of the N-1 criterion). These models make a distinction between the concept of commercial transactions and the flows in the physical branches (lines) of the system. According to relevant studies carried out in the region of West-Central Europe (WCE), the model based on flows leads to a significantly higher utilization of the transmission capacity of the interconnections compared to the model based on the available transmission capacity [2], thereby offering the way better electricity trading opportunities while maintaining at least the same level of security of supply. After these studies were completed, the flow-based model was implemented in DKE from May 21, 2015.

Nevertheless, the application of market flow-based coupling presents a "flaw" in the clearing of trades, and more specifically the "non-intuitive trades" referred to in various studies of DKE [2]-[8], The non-intuitive transactions only take place in the electricity market - and not in the rest of the commodity markets due to Kirchhoff's second law, which prescribes the use of Power Transfer Distribution Coefficients (PTRs) to simulate the effect of transactions on the flows of its natural branches systemic. Basically, the flow-based model makes the physical properties of the system visible at the market level. Since many trades simultaneously affect - albeit at different rates and possibly in different directions - the same sector flow, depending on which flow prevails, it is possible to clear a trade from a high-price zone to a low-price zone, so that capacity is freed up in a critical industry to clear a more (economically) efficient trade from low price zones to high price zones. Although non-intuitive transactions effectively alleviate saturations in critical sectors leading to the maximization of social benefit - where Power Exchanges act as transaction intermediaries matching forward and reverse transactions so that available transport resources are optimally used -, these results can be considered undesirable for designers and market participants [9] as they are perceived - perhaps wrongly or unintentionally - as unfair, anti-competitive behavior and as a "price reduction strategy". However, issues of fair "treatment/management" arise from market participants who perceive the electricity market as a commodity market, overlooking the physical properties of the system that cause counter-intuitive transactions.

To deal with this "defect", a heuristic iterative algorithm was developed in DKE, in each iteration of which the reverse transactions associated with negative SKMIs are ignored when calculating the (prevailing) flow in critical and congested branches [3]. This heuristic procedure does not provide guarantees regarding the quality of the result, as it does not necessarily converge to the optimal solution, and does not give an estimate of the "error" of the methodology (i.e. the deviation of the result of the methodology from the optimal economic result) [3] .

In the following paragraphs, the basic conditions related to the flow-based standard model and the transaction-based standard model, as well as the combined model, are presented. The analysis presented here is for one trading period - one hour in European day markets - for presentation purposes. Nevertheless, the generalization of the models to many periods is straightforward.

The basic congestion management models are then presented. In the Standard Flow Model (FSM), the power grid is represented as a network of physical nodes or busbars that are connected by transmission lines or branches, as shown in Figure 1. Due to the physical laws of electricity, the power flows in the branches depend on net energy injection to all nodes, and are limited by physical flow limits of

branches. Power injections and flows are balanced at the node level

but also of the entire system.

In the classic Linear Programming (LP) formulation, the standard node

flow-based model is formulated as follows, with reference to

basic nomenclature listed below, highlighting each

case the corresponding binary variables:

m

subject to the following restrictions:

Limitation of injection supply quantity:

Absorption bid quantity limit:

Line capacity limits:

Net nodal injection and system energy balancing:

where the transmission line power flux, FLi, is defined as

and the net injection at node n, NIn, is defined as

NIn= Xsn- Xdn(8)

Solving the standard flow-based model achieves the following

Results:

1) a clearing value for each node, Ln,

2) the cleared amounts of energy injection Xsn of the counterparts

of injection offers, whose offer price is less than or equal to

respective nodal clearing price,

3) the cleared amounts of energy absorption of Xdns

of corresponding absorption bids, whose bid price is

greater than or equal to the corresponding clearing nodal value,

4) the fluxes of the transmission lines FLi which are less than or equal to

respective flow limits, and

5) energy balancing at the level of each node and its whole

systemic.

Another basic congestion management model is a transaction-based model, where multi-zone electricity markets are represented as a set of interconnected bidding zones. Trading activities result in transactions between interconnected bid zones,

as shown in Figure 2. Injection bids and absorption bids are submitted to the Market Operator who is responsible for each bidding zone. An optimization model is then solved for all bid zones, determining the acceptable and non-acceptable energy quantities of injection bids and absorption bids, along with the clearing values (for each bid zone). Cross-zone energy transactions between interconnected bidding zones must be cleared in a direction from the cheapest bidding zone to the most expensive bidding zone, i.e. intuitively based on the price differences of the respective bidding zones. The optimization problem takes into account that energy injection quantities, energy absorption quantities, and cross-zone transactions must be balanced at the zone and total market level.

In the classic Linear Programming (LP) formulation, the generalized standard transaction-based model is formulated by (1 )-(3) and the following equations:

Upper and lower cross-zone transaction limits:

E

Zonal Energy Balancing:

where the zonal injection Z is defined as

It should be noted that the transaction-based method of clearing the system can be applied to a random set of bid zones, which accumulate subsets of nodes of the overall system.

Solving this transaction-based method achieves:

1) a clearing price for each node, MPZ,

2) the cleared energy injection quantities Xsn of the corresponding injection bids, whose bid price is less than or equal to the corresponding zonal market clearing price,

3) the cleared quantities of energy absorption Xdn of the corresponding absorption offers, whose offer price is greater than or equal to the corresponding zonal market clearing price,

4) the quantities of energy transactions between interconnected bidding zones, EXe, in the direction from a bidding zone with a lower price to a bidding zone with a higher price, and

5) the balancing of energy at the level of the offer zone and at the level of the overall market.

The Transaction-Based Standard Model presented here is referred to as the "Coordinated Net Transmission Capacity Method" in Regulation 2015/1222 of 24 July 2015 of the European Community which lays down guidelines for capacity allocation and congestion management [11 ]. The use of the Standard Model based on Transactions requires the prior calculation of the Available Transmission Capacities (ATC), which define the maximum allowable transaction for each interconnection. The Transmission System Operators of Europe have developed a special methodology using the N-1 criterion for the exogenous calculation of the Net Transmission Capacity (NTC), and subsequently for the calculation of the NTT. It should be emphasized that the classical form of the transaction-based model concerns the maximum allowed transaction only in the interconnections and not in the intra-zone branches. However, the intra-zonal branch flow limits play a critical role in the calculation of the interconnectors' TORs [10], and thus the resulting interconnection TORs indirectly internalize the flow limits of all branches of the system. In contrast, in the Standard Flow-Based Model, the physical constraints of the system components are incorporated directly into the problem formulation. In this sense, for a given solution space where security of supply applies, theoretically the solution space using the TDMs is a subset of this total solution space, while the solution space using the flow-based model is the complete solution space of the problem [2]-[3]-

Both models mentioned above, in addition to the binding constraints regarding energy flow or transaction quantity, lead to price differentiation between nodes or bidding zones, respectively.

A major drawback of the Flow-Based Standard Model, from the market side, is that energy does not necessarily flow from the lowest to the highest nodal price. However, the Trade-Based Standard Model always results in trades from a bid zone with a lower price to a bid zone with a higher price.

Prior Art

In the following, several approaches to solving the unified model based on both nodal flow and zonal transactions, termed the Combined Flow and Transaction Model, are listed.

Vlachos and Biskas [12] have presented a unified intuitive model based on flows and transactions, but with nodal configuration both at the physical level - congestion management in system branches - and at the commercial level - commercial transactions. More specifically, this approach took into account physical trades on individual physical lines, which is not the usual practice in European markets where trades are reported at a cross-zonal level (between interconnected bid zones). The generalization of this nodal/nodal approach to a nodal/zonal approach, as applied to European markets, is however not straightforward, as it requires a different logic of problem formulation and extensive changes in the constitutive complementarity conditions, as will be further developed in the present invention.

There is currently no published scientific literature on the nodal/zone approach, apart from the technical reports of the DKE area, which present the development of internal research taking place towards the application of flow-based intuitive modeling in the intraday market of DKE, with a hybrid configuration of the system as shown in Figure 3: a nodal configuration for managing the congestion of the system branches, and a cross-zonal configuration for commercial transactions. In order to achieve intuitive solutions based on the flows in this context, the so-called "intuitive transaction generation algorithm" is applied in DKE, i.e. an iterative solution technique which is described in detail in the following section.

The DKE approach is based on the use of the Production Allocation Keys (GALs) at the nodal level which are denoted below as GSKz n and which denote the zonal injection distribution coefficient in the internal nodes, i.e. for the calculation of the nodal injections:

NIn= GSKZin- ZIz(13)

According to Regulation 2015/1222 of July 24, 2015 of the European Community which establishes guidelines for the calculation of capacity and congestion management [11], a Generation Allocation Key is defined as "a method of converting a change in net position <1> of a given bidding zone to estimated specific increases or decreases of injection in the common network model", and "the best prediction of the relationship of a change in the net position of a bidding zone to a specific change in generation or load in the common network model" .

Considering standard definitions (1)-(6) of the flow-based model, combined with equations (11) and (13), a Combined Flow and Transaction-Based Model is formulated. The definition of energy flow in lines (7) becomes:

The term PTDFl n<.>GSKz,n practically represents the Power Transfer Distribution Factor of the zonal net injection ZIz into the flow of line l, FLl, which is hereafter denoted as ZPTDFl z. The model is practically a "zone-flow" model, which resembles a standard nodal model, where nodes correspond to bidding zones.

In the DKE approach, the coefficients of the CCPs are exogenous static parameters, e.g. represent a user-defined static distribution of zonal to nodal injection. To this extent, this approach theoretically leads to a sub-optimal solution, as the solution space is determined by the values of the static and user-defined CFP coefficients.

However, the simple Combined Model based on Flows and Transactions can lead to non-intuitive transactions, e.g. trading from a higher price zone to a lower price zone. Next, the theoretical background regarding the presence of non-intuitive transactions is presented. This presence is further explained by analyzing the Karush-Kuhn-Tucker (KKT) conditions of the formulated problem. By first substituting in (14) the term ZIz from equation (11) and then the term FLi from (14) in (4) and (5), the power flow constraints are formulated as follows:

Horizon:

constraints (15), (16) are simplified as follows:

The KKT condition of the EXevariable is configured as follows:

The physical quantity of each transaction results directly from the optimization of the objective function (1) and the power flow constraints (4) and (5). Each physical flow is a conjugate contribution (via δZPTDFl e) of all transactions. Equivalently, each cross-zonal transaction e affects all physical flows, and conversely, all physical flow binding constraints affect condition (20) for each transaction e. In the optimal solution, for each natural flow in a branch l, FLι, at most one of (18) or (19) can be binding, that is, at most one of the quantities Rfii<up>, or Rfl<lo> can be positive. Additionally, each contribution δZPTDFl e, can be positive or negative. The above findings lead to the following:

the second term of (20), which is a sum of products of individual factors, can be either positive or negative. Theoretically, any possible combinations of signs can occur in each product of individual factors,

the first derivative term of (20), which expresses the zonal difference in value between the zone that delivers the energy and the zone that receives the energy, can be either positive or negative,

because of the strict equality condition (20), the complementary variable (cross-zonal trading quantity) of (20), can be of any direction (positive or negative), regardless of the sign of the relative zonal price difference, as described in the last paragraph above.

As the transactions are dependent variables of the problem, their solution is affected by the optimization conditions, which arise from the physical limits—injection, absorption, and physical flows—along with the optimal objective. Therefore, a random mixture of positive/negative δZPTDFi values would result in any transaction quantities matching the optimization conditions of injection, absorption and natural flows. In conclusion, the conditions of the Combined Flows and Transactions Model do not guarantee an intuitive solution for the EXe dependent variables. It should be noted that, depending on the size of the price of each δZPTDFiie , the transaction quantity between two interconnected bid zones may be greater than the physical limits of the corresponding physical branches that join these bid zones, but also in this case the quantity of the transaction is still implicitly limited by the limits of all physical branches of the system.

Then the "algorithm for creating intuitive transactions" which is applied to DKE is presented.

To deal with the "defect" of non-intuitive transactions, a heuristic iterative algorithm has been developed in DKE, which is called the "intuitive transaction creation algorithm", and in each iteration of which they are ignored, when calculating the (prevailing) flow in the critical (congested) branches, the reverse trades which are associated with negative terms δZPTDFl e[3]. In each iteration of this algorithm the following actions are performed:

A combined flow-based and transaction-based optimization problem is solved and all corresponding zonal MPZ clearing values are calculated

B-Then "sensitivity checks" are performed on the resulting solution. In these checks the benefit - economic surplus - of each EX transaction is calculated as follows:

We= Σz(ZIMe,z; MPz; Εξe) (21)

where EXe is the optimal value of the variable EXe (solving the problem in step (a)) in the current iteration of the algorithm. If all payoffs are positive, indicating that all bilateral trades are intuitive, then the iterative algorithm terminates.

C-Otherwise, in case there is at least one transaction with We< 0 (non-intuitive transaction), then the following constraints are formulated for all physical lines (branches) in congestion, which are the subset of "critical branches" or "active branches", ,cl ⊂ l:

- if the branch physical flow constraint is upper bound binding, then (18) is replaced by:

- if the branch physical flow constraint is lower bound binding, then (19) is replaced by:

These modifications applied to the branch flow constraints practically eliminate all terms that ease the congestion of critical (active) branches, thereby setting tighter fictitious physical flow limits on critical branches.

After implementing the intuitive trade generation algorithm, through the enforcement of constraints (22) and (23), the algorithm continues with step (a) and the next iteration is performed. It should be noted that, constraints (22) and (23) imposed during the above iterative process are applied cumulatively, e.g. restrictions which were applied in previous iterations are not ignored / withdrawn in the next iteration.

The flowchart of DKE's intuitive transaction generation iterative algorithm is shown in Figure 4.

This heuristic approach leads to "unsaturated" branches and more specifically to branches that are loaded below their natural capacity, resulting in a sub-optimal solution, in an interior point of the "solution space", which does not lie on the edges of the flow-based constraints polyhedron [3]. However, this technique does not provide guarantees regarding the quality of the result, as it does not necessarily converge to the optimal solution, and it does not give any estimate for the error of the methodology (i.e. the deviation of the result of the methodology from the optimal economic result) [3] ,

The direct consequences of the application of static and pre-determined PRMs are the following: in a flow-based market structure, before the market is cleared the following procedures are carried out by the Transmission System Operators (TSOs), as shown in Figure 5:

1) A "base case" is created which contains an expected network topology for the next day together with expected net positions of all bid zones and corresponding flows in all critical branches, which are called "Critical Network Elements" KSD. This is a first rough assumption, as it is difficult to recover accurate generation forecasts for each node, and especially in a system with high penetration rates of intermittent power, such as wind and PV. The existence of intermittent production is inherently an indication of potential errors in forecasting production, relative to actual (real-time) production. Large-scale changes in uncontrolled generation, such as natural flow wind and hydro, can occur rapidly with changes in weather conditions, and have a significant influence on the geographic distribution of power generation.

2) Then the TSOs define the static CCPs, identify the CSDs, the corresponding faults and Corrective Actions which must be taken into account in advance in the calculation of the capacity (Available Flow Margin). Corrective Action means a measure which is activated by one or more TSOs, either manually or automatically, and relieves or contributes to the relief of physical congestion, e.g. reallocation and/or reverse transaction [13], Corrective Actions can be applied either before or after the error and usually contain reallocation and reverse transaction costs.

3) TSOs define and apply their operational experience in order to adjust the solution space of the flow-based model, reducing the TSOs' RRs, through the "Final Adjustment Price" TTP.

4) The TSOs also define the Flow Confidence Margin (FCR) for each CSD, which is calculated based on a statistical evaluation of the deviations between the flows calculated according to the flow-based method and the actual flows observed.

5) Nodal SCMIs, CCPs and total CSDs are used to calculate zonal SCMIs, e.g. ZPTDFl z in equation (14), together with the corresponding DPRs (potentials) of all KSDs. ΔPR is calculated as follows: RAM = Fmax-FRM-FAV-Fref,

where Fmax the maximum allowable flow in the critical branch, and Fref a reference flow at zero net positions which is obtained by using the calculated table of zonal SCMI from the base case, with a specific generation and consumption forecast for each node, as mentioned in step 1 [13].

6) The TSOs then send the parameters calculated in step 4 to the Market Operators so that the market can be cleared using portfolio based bids/statements submitted by the market participants. The market clearing results consist of the cleared injection/absorption quantities, the cleared transactions between the interconnected zones and the market clearing prices for each zone.

Also, in markets where portfolio bidding is allowed, market participants set their production and consumption schedules - a self-scheduling process - according to the energy traded (bought and/or sold) in each bid zone, and refine these schedules. real-time programs - self-distribution process - according to actual production/consumption conditions. During the self-allocation process, the actual CPMs are set, which are generally different from the forecast CPMs set on the previous day (before the intraday market is resolved).

The mismatch between the statically pre-defined MTPs and the actual MTPs - based on the actual generation/consumption at each node - leads to miscalculations of the flow in the network branches at the pre-day level - relative to the actual flows -, and therefore situations arise where:

A-some line flow constraints are not binding (active) in market clearing results, but may be violated in real operation by taking into account the cleared amounts of energy injection/absorption,

B-while some line flow constraints are binding on market clearing results, they are not binding on actual operation considering the cleared amounts of energy injection/absorption.

Case (A) necessitates the use of pre-defined Corrective Actions in real time - mainly redistribution and reverse trading - in order to deal with violations of the maximum transmission capacity of the transmission lines. These Corrective Actions lead to an overall increased cost - pre-day cost and cost of corrective actions -, or equivalently lower social benefit.

There is no theoretically "right or wrong" methodology for how CCPs are created. However, the choice of CCPs significantly affects the market [13]. CCPs are in fact the largest source of deviations of the applied flow-based model parameterization (zonal SCMIs) and subsequently the market clearing results.

The key element for managing uncertainty in the capacity calculation is the margin of confidence: the Flow Confidence Margin, FAR. The flow may be greater or less than expected, but if the flow is greater, there may be an overload in a DC. In order to reduce the probability of physical overloads to an acceptable level of risk, some capacity of a DCS is withheld from the market as RAP, i.e. the RAP reduces the DPR of a CCD. The PAP for each CSD is based on the historical record of the difference between a CSD's predicted energy flow (which is forecast two days in advance) and the actual flow.

The Final Adjustment Rate (TAP) is used to incorporate operational skills and experience of the operators of a Load Distribution Center (LDC) that cannot be formally calculated in the flow-based system, increasing or (typically) reducing a LDC's ADR. The TTP is introduced to allow a manual adjustment of the DPR.

According to the above, the applied flow-based approach is sub-optimal for three main reasons:

the applied "intuitive trade generation algorithm" leads to "unsaturated" branches and more specifically to branches that are exploited below their natural potential, resulting in a sub-optimal solution at an interior point of the solution space, which does not European markets, which however is not simple, as it requires a different logic of problem formulation as well as extensive changes in the constitutive conditions of complementarity, as described in this invention.

Therefore, the present invention describes a method for creating an integrated model based on both flows and transactions, which simultaneously achieves: (a) intuitive transactions between interconnected bid zones, and (b) maximum flows in critical intra-zone and inter-zone industries, up to their physical carrying capacity limits. The resulting model practically represents two problems which are forced to balance:

a) the first problem aims at maximizing the production/consumption surplus under the respective energy injection/absorption limits,

b) the second problem aims at maximizing the intuitive transactions under the respective limits of the transport capacity of the physical transmission lines of the system.

The model demonstrates a hybrid network configuration: (a) a node-based network for congestion management, defining a physical layer, and (b) a zonal configuration for trading between market participants, defining a commercial layer . The hybrid configuration is fully in line with the current management model applied in Europe, where flow-based modeling - together with a hybrid nodal/zonal configuration - is the preferred congestion management modeling approach under the Capacity Allocation Network Code and of Congestion Management [1] for pre-day and intra-day electricity markets.

Description of the Invention

Therefore with the present invention a technical effect is made in a technical process as mentioned below. The technical process referred to in the invention is the calculation of production and absorption at each node of an electrical network, and the calculation of the phasic energy flow in the branches (electricity transmission lines) of the network to ensure that congestion is managed safely - technically to ensure that the physical loading of the branches of the network is less than or equal to their respective maximum technical limits - under rules that must be satisfied during the parallel process of calculating electricity commercial transactions between the interconnected zones of this network.

The quantities of production and absorption calculated at each node are physical quantities, and determine how the network is charged and operated. However, the way of calculating the physical quantities of electricity must, apart from the physical rules, also follow rules that lie on the dividing line of the polyhedron of flow-based restrictions,

the applied approach uses the static CMPs, which lead to incorrect calculations of the flows in the system branches, necessitating the use of pre-defined Corrective Actions - mainly reallocation and reverse transaction - in order to deal with the violations of the maximum carrying capacity of the lines transport, leading to increased social costs,

the inherent errors in the calculation of the RRs prompt the TSOs to take measures to keep the RR at the pre-day level - and therefore the line flows during actual operation -, through the use of the RR Flow Reliability Margin and the TPP Final Adjustment Price . This is a source of further degradation of the social surplus, as the potential of the branches of the system is not fully exploited. In addition, incorrect CFPs lead to inaccurate zonal clearing prices - resulting from market clearing - which give (a) incorrect economic signals to market participants, and (b) inaccurate congestion income, which does not correspond to actual congestion of the electrical system.

Object of the invention

The present invention aims to provide a solution by which the defects and problems mentioned above are corrected. In this sense, the method according to this invention includes a direct approach to solving cross-zone transactions and nodal injections, which preserve the flow limits of physical transmission lines by mixing flows and transactions in a single clearing model, and aims at the optimal solution of injections, absorptions and transactions which are endogenously delimited by physical limitations, e.g. physical boundaries of energy transfer between system nodes. Therefore, considering:

- the price of injection offers and absorption offers at each node,

- the physical flow limit of each transmission line between connected/adjacent nodes, and

- the technical limitations of the energy production units, if they exist, e.g. the technical maximum and minimum, the rates of change of power output, etc., as continuous convex functions of the corresponding amounts of energy injection,

a method for solving the integrated mixed nodal/zonal model based on both flows and transactions must be found. In order to solve the problem, it is necessary to generalize the nodal/nodal approach to a nodal/zonal approach, as applied to commercial transactions between the interconnected zones of this network.

The effect of the invention on the technical process of managing congestion in an electrical network and calculating natural energy flows is as follows. The hitherto known in the literature methods for calculating the load and managing the congestion of the electric network, under cross-zonal trading rules, result in an incomplete and incorrect calculation of the load of the network branches in the planning stage of the previous day - in relation to the system load in programming time -, and consequently in calculating production and absorption quantities which:

A-in some cases, they cause the technical load limits of certain branches of the network to be exceeded, leading to problematic operation of the network and the unfeasible implementation of the operation planning of the production units, and

B- in some cases during the actual operation of the network they do not take advantage of the maximum possible charging capacity of the network branches for the transfer of electricity between the nodes of the network.

The invention achieves calculation of the appropriate amounts of electricity production and absorption, and at the same time the appropriate charging of the network branches, so that the technical limits of the network's charging are not violated during actual operation, and the maximum possible transfer of electricity between the nodes is achieved of the network. The unique economic effect of the invention is that in parallel with the technical process, the overall benefit of the production and absorption quantities at the grid nodes, and of the commercial electricity transactions between grid zones is optimized.

Brief description of the figures

Figure 1 shows the power grid in the Standard Flow-Based Model, where all nodes and transmission lines are considered, as a physical layer.

Figure 2 shows the standard transaction-based model, in which intra-zone lines and nodes are ignored, and only the commercial level of transactions between interconnected bid zones is considered.

Figure 3 presents the integrated nodal/zonal model based on flows and trades, in which both natural and commercial layers are considered in the model conditions, showing the overlapping layers (natural and commercial) in the combined model based on flows and trades.

Figure 4 presents the algorithm for generating intuitive trades which is applied in the area of DKE and is included in the resolution of the European daily markets.

Figure 5 presents the basic design of the current congestion management - flow-based approach -, mainly in Europe, where the resulting defects lead to increased real-time redistribution costs and an overall suboptimal solution for social welfare.

Figure 6 shows the design proposed in this invention, according to which the physical parameters of the SCMI system are not modified, and the calculated flows are correct / accurate, thus leading to an overall optimization of the social welfare for the participants of the market.

Figure 7 illustrates an exemplary system block diagram for operating an electricity market in accordance with the principles of the present invention.

With the present invention, a method is particularly proposed which yields a solution with the following elements:

1) one market clearing price for each bidding zone,

2) the cleared energy injection quantities of the corresponding injection bids, whose bid price is less than or equal to the corresponding zonal market clearing price,

3) the cleared energy absorption quantities of the corresponding absorption offers, whose offer price is greater than or equal to the corresponding zonal market clearing price,

4) the flows of transmission lines which are less than or equal to the corresponding transmission capacity limit,

5) the quantities of energy transactions between bidding zones, directed from a zone with a lower price to a zone with a higher price, 6) the energy balance at the nodal level, which is obtained indirectly through the use of SKMIs and

7) the energy balance at the bidding zone level, according to the cleared transactions between the interconnected bidding zones. The most important features of the solution aimed at by this invention, while achieving the purposes of a mixed hub/zonal market model based on flows as well as transactions, are the following:

1) Static and user-defined CMPs are not used, and no specific static zone injection allocation is required at the internal nodes of a zone.

2) The parameters of the physical system are not modified - there is no elimination of SKMI parameters when calculating the fluxes - i.e. the representation of the physical system remains unchanged.

3) The formulation of the problem constitutes a single integrated model which can be solved in one stage, without requiring any heuristic iterative process (algorithm).

As shown in Figure 6, the solution method provided by this invention leads to:

- optimal solution for the social benefit, without the need to apply financially unprofitable Corrective Actions in order to overcome the inaccuracies of the CCPs, since there are no CCPs in this method,

correct zonal clearing values, which then result in correct economic signals and accurate system congestion income, and

there are no overloads in the network branches - which result from the inaccuracies of the CMPs - in real operation taking into account the cleared amounts of injection and absorption.

According to an initial embodiment of the solution method provided by this invention, the problem of the multi-zone electricity market in which intuitive transactions between interconnected bidding zones take place and which follows a nodal configuration for congestion management based on flows in the natural branches of the transmission system.

According to the invention, a system is thus proposed which processes the offers submitted to auctions by the participants in the electricity market for electricity market products, and which mainly includes the following technical elements:

A-a database that includes model parameters and bid data, and the model parameters and bid data are applied to equations that correspond to an electricity market and include at least one variable to be determined.

B-a processor connected to the database, which simultaneously solves the equations for at least one variable to be determined, and the solution is performed iteratively to determine the at least one variable according to a predetermined objective or criterion, and

C - means for publishing the results of the auction to inform the participants in the electricity market,

D-recursively computing solutions to at least one variable until that variable satisfies a predetermined goal or criterion.

E-determining the results of the auction based on at least one variable that is determined, and

F-sending electronic signals representing the results of the auction for the publication of the results of the auction, and where specifically the above results of the auction are published in an electronic network.

According to another embodiment of the invention, the system for determining the results of an auction carried out for products of an electricity market, advantageously also includes:

A-media for storing the data of model parameters and offers,

B-means for reading model parameters and bid data from said storage media,

C -means for using model parameters and bid data to determine auction results, and

D-media for the publication of the results of the auction.

According to another proposed embodiment of the invention, the above system, where the electricity market constitutes an integrated electricity market or a set of coupled electricity markets, additionally includes at least one of the following, in particular:

a) a number of nodes of a physical electricity network,

b)a plurality of transmission lines connecting said network nodes, where the physical power flow of the line is limited by an upper limit, and where the physical power flow is defined as a linear function of the nodal energy injections and the nodal energy injection is defined as injected energy minus the energy absorbed at the corresponding node,

c) a number of electricity transaction zones which contain an arbitrary number of nodes,

d)a number of energy transactions processed between interconnected zones,<.>

e)a number of offers, for injecting energy into at least one node, and

f) a number of offers, for energy absorption in at least one node,

According to another alternative advantageous embodiment, the superior system further includes one of the following electricity purchase products: electricity, reserve power, and transmission power.

and where this means of publication, performs at least one of the following processes, i.e. to publish solutions of at least one variable in an electronic medium for retrieval by the participants, and to electronically communicate the solution for at least one variable to the participants in the electricity market, where advantageously this corresponding publication includes posting and electronic notification of at least one variable.

According to another embodiment, the above system also includes A-a server connected to a communication network, which serves the electricity market,

B-a plurality of electronic devices coupled to the communication network, which communicate with the server to submit offers for electricity market products,

C- and at least one database coupled to the server, in which the submitted bids, electricity network model parameters and electricity market parameters are stored, and the server simultaneously processes the submitted bids to determine the results of auction.

The above electronic devices of the system include at least one of the following: computer, facsimile, telephone and personal communication device, and/or where the above system server publishes the available results of the auction on the electronic devices, where publication of results is at least one of the following processes: publication on a communication network and electronic transmission.

In a further embodiment according to the invention, this system includes a computer-readable medium having stored sequences of instructions, which include the instructions executed by a processor, and which allows the processor to:

A-to retrieve modeling parameters and multitude of bids submitted for electricity market products,

B-apply the modeling parameters and offers to equations that correspond to an electricity market and include at least one variable that must be determined,

C-solve the equations for at least one variable, where said solving is performed iteratively to determine at least one variable according to a predetermined objective or criterion, and

D-to publish the results of the auction for the information of market participants.

Still according to the invention, this system advantageously includes a computer-readable medium having stored sequences of instructions, which further includes the instructions executed by a processor, and which enables the processor to:

A-to establish a communication link of a market participant with a market operator,

B-to communicate offers of a market participant for electricity market products to the market operator, and

C-to receive the results of the auction from the market participant, which are produced simultaneously.

According to another embodiment, this system includes at least one computer which is advantageously programmed to perform a process for participating in an electricity market in which a server operated by a market operator conducts an auction for electricity market products. energy, according to the following procedure which includes the following steps:

A- transmission of electronic signals to establish a communication link between a computer of a market participant and the server, B- creation of at least one offer for the products of the electricity market, and

C- creation of electronic signals that represent at least one offer which will be sent to the server for submission of at least one offer to be submitted to the auction, while the offers are simultaneously processed to determine the results of the auction, where in particular the process also includes the determination of the results of the auction based on at least one offer and the creation of the electronic signals representing the results of the auction which will be sent by the server to the computer of the market participant.

According to another embodiment of the invention, this system includes at least one computer that is programmed to process the offers submitted by market participants for electricity market products, where this processing advantageously includes the following steps:

A-reception of electronic signals representing the parameters of the electricity market model,

B-receiving electronic signals representing the bids submitted by market participants,

C-applying the parameters of the model of the electricity market and the offers to equations representative of an electricity market which include at least one variable to be determined.

According to another alternative advantageous embodiment, in the above system the settlement calculations or auction results include at least one of the following: scheduled quantities, and/or transaction quantities, and/or clearing prices of the electricity market products and the utilization power flow transfer.

According to another alternative with an advantageous implementation, in the above system the publication includes the posting of the solutions of at least one variable of the scheduled quantities, and/or the transaction quantities, and/or the clearing prices of the electricity market products.

According to another further alternative advantageous embodiment, the above system also includes matching the bid data, the scheduled quantities and/or the transaction quantities and/or the clearing prices to power grid positions, where the power grid position represents at least one of the following: a power system bus, a power system node, a power system zone, a group or a random number of buses or nodes or zones, where in addition a market participant submits a bid that includes a set of points defining a price and quantity curve for electricity market products;

wherein the electricity market offers include at least one time period for electricity market products, wherein this process or solving includes performing an optimization or calculation process, wherein the optimization or calculation process includes solving (repeatedly or once) a set necessary variables and conditions included in a set of simultaneous equations, where the process or solution is performed for multiple time intervals, either collectively or individually, and where the process or solution is performed after an acceptable time limit corresponding to the submission new offers and the modification of offers.

This invention also relates to a method for processing bids submitted to auctions by market participants for electricity market products, in particular for implementing the system in accordance with the previous embodiments. According to an embodiment of the invention, this method comprises the following steps:

A-retrieving model parameters and bid data for electricity market products,

B- the application of the parameters of the model and the data of the offers in equations which correspond to an electricity market and include at least one variable that must be determined,

C-the simultaneous solution of the equations for at least one variable, where the solution is performed iteratively to determine at least one variable, and

D- the publication of the results of the auction to inform market participants,

in particular where, advantageously, the above published results include solutions of at least one variable of the quantities and/or clearing prices for the electricity market products.

Also according to an embodiment of the invention, the above method used to conduct an auction for an electricity market, includes the steps:

A-starting a data collection process of the electricity market auction to receive the bids submitted by market participants for electricity market products,

B- receipt of offers regarding electricity market products,

C-end of the data collection process of the electricity market auction, and

D-simultaneous processing of offers to determine the results of the electricity market,

in particular where, this additionally includes the process of validating the offers of the electricity market, in addition specifically the publication of the results of the auction respectively, even more specifically where the publication includes at least one of the following processes:

- publishing the results of the calculation in electronic media, and/or - communicating the results to market participants via electronic communication,

and further where, the published results include public information which is accessible by market participants.

According to the invention in the above method the results via electronic notification include private information, and/or where the electronic notification includes at least one of the following electronic means: electronic mail, text messages and fax.

According to a further embodiment, this method for participating in an auction of an electricity market conducted by a market operator for market participants, comprises the steps of:

A- establishing a communication link between the market participant and the market operator,

B- notification of an offer for electricity market products by the market participant to the market operator, and

C- receiving the results of the auction from the market participant, which are produced at the same time,

where in particular the results of the auction are received via electronic communication, and even more specifically, where this receipt includes: accessing a network location, and receiving the results by entering a password at the network location, and/or where the results of the auction are published in a publicly accessible location.

According to yet another embodiment of the invention in the above method advantageously

A- the settlement calculations, and/or the auction results include at least one of the following: scheduled quantities, and/or transaction quantities, and/or clearing prices of the electricity market products and the use of power flow transmission,

B- where the publication includes the publication of the solutions of at least one variable of the scheduled quantities, and / or the transaction quantities, and / or the clearing prices of the electricity market products,

C- this above method, or even the system, computer or means, further includes the matching of the bid data, the scheduled quantities and / or the transaction quantities and / or the clearing prices to electricity network positions, where the electricity network location represents at least one of the following: a bus of an electricity system, a node of an electricity system, a zone of an electricity system, a group or a random number of busses or nodes or zones;

D- a market participant submits an offer which includes a set of points that define a price and quantity curve for electricity market products,

E- the offers for the purchase of electricity include at least one period of time for products of the purchase of electricity,

F- the process or solution involves carrying out an optimization or calculation process,

G- the optimization or calculation process involves solving (repeatedly or once) a set of necessary variables and conditions included in a set of simultaneous equations,

H- the process or resolution, is performed over multiple time periods, either collectively or individually, and

Th- the procedure or the resolution, is performed after an acceptable time limit which corresponds to the submission of new offers and the modification of the offers.

According to the invention, the method in particular for calculating the loading of the transmission lines of an electric network and managing the congestion of the natural electricity flows of the electric network under the rules of commercial transactions, which is carried out in an electric network consists of:

A- a set of nodes of a physical electrical system,

B- a set of transmission lines connecting the nodes of the system, whose natural energy flow is limited by an upper limit, where said natural energy flow is defined as a linear function of nodal energy injections, where said nodal energy injection is defined as the energy that is injected reduced by the energy that is absorbed at the corresponding node,

C- a group of nodes in a random number of electricity trading zones, D- a set of energy transactions that take place between interconnected electricity trading zones,

E- a set of instructions to inject energy into each node, and

G- a set of energy absorption commands at each node,

where according to a basic embodiment of this invention it advantageously includes the following steps

a- definition of an electricity trading clearing signal, for each electricity trading zone,

b-determining the cleared amounts of energy injection at each node, with injection order limits that are less than or equal to the corresponding clearing signal of the electricity trading zone,

c-determining the cleared amounts of energy absorption at each node, with limits of absorption orders that are greater than or equal to the corresponding clearing signal of the electricity trading zone, d-determining the flows of transmission lines that are less than or equal to the corresponding limit carrying capacity,

e-determining the amounts of energy traded between the electricity trading zones, with a direction from a zone with a lower clearing signal to a zone with a higher clearing signal,

f- determining the energy balance of each electricity trading zone, the corresponding nodal net energy injections of the nodes included within the electricity trading zone, and the energy transactions with all the interconnected electricity trading zones.

The method proposed in this invention combines the standard nodal flow model of the physical level with the intuitive clearing conditions of cross-zonal transactions of the commercial level.

Physical flow constraints are modeled at the nodal level, i.e. with equations (2)-(5) and definitions (7), (8). Instead of the system power balance (6), the zonal power balance equations (11 )-(12) are used. The brief configuration is shown below,

starting with limiting the quantity capacity of supply and demand:

then the line power flow capacity limits:

where the transmission line power flow FL is defined as:

and finally the power balance:

where zonal injection is defined as:

In this sense, the main factors influencing the energy flows are the nodal net injections NIn= Xsn- Xdn. The CMP parameters are not considered, and therefore the nodal net injections are the primary variable of the problem, and the distribution of zonal injections at the internal nodes is solved by the optimization conditions. Additionally, there is no modification (elimination) of the SCMIs, which are consistent with the power flows, and therefore the solution space is not reduced - as in the mentioned DKE intuitive transaction creation algorithm -, and the natural flows can reach up to the natural the limits, i.e. no stricter artificial limits are placed on "critical sectors" through said elimination of specific SCMIs.

Despite introducing the trading variables (24)-(28) into the model, its solution, as a standard GA optimization problem with the objective function (1), cannot guarantee intuitive trading. Furthermore, it may yield surprisingly acceptable or non-acceptable injection/absorption bids with respect to the zonal clearing value MPZorial/shadow value of the constraint (28) These events are theoretically expected and can be further explained by analyzing the KKT conditions of the formulated problem :

A-Transaction variables are dependent variables, as explained in the case of section 2.

B-The KKT optimization conditions indirectly define the nodal values which override the zonal values and determine the optimal solution of Xsn and Xd.

These node values are implicitly configured as follows:

Therefore, injection quantities may be cleared at a zonal price less than their respective bid, or equivalently, absorption quantities may be cleared at a zonal price less than their respective bid. These cases are collectively called oddly acceptable offers. In fact, the GA solution of problem (1), (24)-(28) is the same as the solution of the Flow-Based Standard Model.

In order to achieve a solution with intuitive trade-offs and non-paradoxically cleared amounts of energy injection/absorption, the following conditions must be satisfied:

A-injection and absorption quantities must be cleared, only in case of a positive surplus of their supply in relation to a zonal clearing price, that is:

B-Considering that the transaction EXe can be divided into two directional non-negative quantities EXe= ΕΧe+ - ΕΧ<e->, these directional trade quantities must be cleared only in cases of positive surplus in relation to the difference of the zonal clearing prices, namely:

In an advanced embodiment of the solution method proposed in this invention, the conditions (30)-(33) are formulated as complementarity equations, and are linked to the corresponding variables which determine the market clearing conditions. (24)-(28) are also formulated as complementarity equations specifying the system conditions.

These system conditions guarantee that all natural flows will reach their limits. Market conditions guarantee that, in a flow-congested solution, at most one directional trade can be intuitively positive for each trade. Market conditions guarantee that injection and absorption bids will intuitively clear relative to the zonal market clearing price.

The formulation practically represents two basic/major problems which are driven to balance: the first problem aims at maximizing the surplus of injection/absorption under the respective limits of injection/absorption bids while the second problem aims at maximizing the surplus of intuitive trades. In both problems the quantities are subject to limits which are indirectly set by the physical flow limits of the transmission lines. The zonal balance equation balances the two problems:

- providing the zonal clearing values, common to both problems, and - balancing the zonal injections of the first problem with the transaction quantities of the second problem.

According to a further advanced embodiment of the present invention, the settlement conditions of the injection offers are provided, at the node level, in relation to the zonal settlement price of the market to which the node belongs. Clearing of injection bids must ensure the positive surplus of cleared nodal quantities over the zonal market clearing price.

Yet a further embodiment of the present invention provides the clearing conditions of absorption bids, at a node level, relative to the zonal clearing price of the market to which the node belongs. The clearing of absorption bids must ensure the positive surplus of cleared nodal quantities over the zonal market clearing price.

A further advanced embodiment of the present invention provides the clearing conditions for energy injection and absorption, in case of additional linear constraints involving the nodal quantities of energy injection and absorption.

A further preferred embodiment of the present invention provides the immediate conditions for defining intuitive trades, i.e. the quantities of trades that are traded from a zone with a lower price to a zone with a higher price.

More features are defined in the corresponding claims below.

Some exemplary embodiments of this invention are described in detail in conjunction with the accompanying drawings. It is pointed out that the embodiments of this invention and the features thereof can be mutually combined with each other without any contradiction.

Additional preferred embodiments of this invention are presented below.

A main embodiment of the present invention provides the clearing conditions of the injection offers, at the node level, relative to the zonal clearing price of the market to which the node belongs. Clearing of injection bids must ensure the positive surplus of cleared nodal quantities over the zonal market clearing price. In this, the nodal injection clearing condition takes into account the shadow (additional) value of any constraint that sets an upper bound on the injection amount.

Supply quantities are limited directly by the corresponding capacity limits (24), and indirectly by constraints (26)-(27). More specifically, each flow constraint sets an upper bound on the injection quantities as follows:

In the above indirect upper limit definitions the quantities Rfl<up>,Rfl<lo> are interpreted as injection reduction limit values, or equivalently increasing the injection upper limit, in order to relieve congestion.

Taking the marginal supply values as in (24), (34) and (35), the clearing condition for injection quantities is expressed in the following complementarity form:

In a further embodiment of the present invention, the clearing conditions of the absorption bids are provided, at the node level, relative to the zonal clearing price of the market to which the node belongs. The clearing of absorption bids must ensure the positive surplus of cleared nodal quantities over the zonal market clearing price. In this, the nodal absorption clearing condition takes into account the shadow (additional) value of any constraint that sets an upper bound on the amount of absorption.

Demand quantities are limited directly by the corresponding capacity limits (25), and indirectly by constraints (26)-(27). More specifically, each flux constraint sets an upper bound on the absorption quantities as follows:

In the above indirect definitions of the upper limit the quantities Rfl<up>,Rfl<lo> are interpreted as absorption reduction limit values, or equivalently an increase of the upper absorption limit, in order to alleviate the congestion.

Taking the marginal supply values as in (25), (37) and (38), the clearing condition for absorption quantities is expressed in the following complementarity form:

A still further embodiment of this invention provides a generalized extension of said first and second embodiment, i.e. the clearing conditions of energy injection and absorption, in case additional linear constraints involve injection quantities Xsn , absorption quantities Xdn and other variables Xu ie:

where x<T>= [Xs, Xd, Xu] , or equivalent

Each constraint j defines an implicit upper bound on the quantities Xsn and Xdn as follows:

In the above indirect definitions of the upper limit the quantity Rj is interpreted as the limiting value of reducing the injection or absorption, or equivalently increasing the upper limit of injection or absorption, in order to relieve the congestion of the constraint.

Taking the injection threshold values as in (41) and (42), the clearing condition of the injection quantities is expressed in the following complementarity form:

Taking the absorption threshold values as in (43) and (44), the clearing condition of the absorption quantities is expressed in the following complementarity form:

A further embodiment of this invention provides the immediate conditions for the definition of intuitive trades, i.e. trade quantities which are traded from a zone with a lower price to a zone with a higher price.

A transaction EXe is taken as the difference of two directional non-negative quantities EXe= ΕΧ<e+>- ΕΧ<e->, only one of which can be non-zero. Directional trading quantities should be intuitively cleared against the difference of the zonal clearing prices.

For each trading direction, the corresponding variable of the positive price difference PPd is defined as follows:

The conditions dictate that only one of the quantities PPde(z,z') and PPd<->e(z,z') can be positive, while the other will be zero.

Under the definition of which direction makes a zonal price difference positive, the following conditions impose that only the directional trade with PPd ≥ 0 will be cleared, that is, it can have a positive value. Correspondingly the reverse

directional trade with PPd = 0 will be zero.

In summary, conditions (47)-(50) guarantee that the cleared quantity

transaction between two bid zones are intuitively connected to the

price difference of these zones.

For the case in which there are no additional linear constraints

(40) which involve injection and absorption nodal quantities, h

integrated solution method is to solve the following set

conditions:

In case there are additional constraint linears of type (40),

then condition (56) is replaced by:

and condition (57) is replaced by:

According to the invention, the method yields a solution which determines:

1) a market clearing price for each bid/trade zone, 2) the cleared quantities of injection bids, to be injected into each node, whose bid price is less than or equal to the corresponding market clearing price of the zone offers/transactions,

3) the cleared quantities of absorption offers, which are to be absorbed at each node, the offer price of which is greater than or equal to the corresponding market clearance price of the offer/transaction zone,

4) the flows of transmission lines, which are less than or equal to the corresponding transmission capacity limit,

5) the quantities of energy transactions that will be transferred between bidding/trading zones, in the direction from a bidding/trading zone with a lower clearing price to a bidding/trading zone with a higher clearing price,

6) the energy balance at the nodal level, which is obtained indirectly through the use of SCMIs, and

7) the energy balance at the bidding/trading zone level, according to the respective net energy injections to each bidding/trading zone node, and the energy transactions with all interconnected bidding/trading zones.

The method presented here results in a model that is both theoretically and practically efficient at the level of social surplus and cleared intuitive transactions.

The proposed method simultaneously achieves a physically feasible and "commercially" reasonable solution, satisfying the "fairness" and "reasonableness" requirements of designers and market participants at the level of intuitive commercial transactions [9],

The solution method of this invention used herein can therefore be formulated as a mathematical programming problem, e.g. as a Mixed Complementarity Problem, which consists of linear complementarity conditions of the corresponding quantity and price variables, or e.g. as a Quadratic Programming problem, which can be solved either with commercially available solvers or with properly designed solvers/algorithms.

Embodiments of this invention are suitable for clearing electricity markets with a hybrid system configuration, and more specifically a node-based configuration for managing congestion in system branches, and a zonal configuration for trading between interconnected bidding zones , as shown in Figure 3.

The present invention concerns spot bids - as opposed to portfolio bids - by market participants, so it is suitable for markets with rules providing for unit bids - as opposed to portfolio bids Therefore, European markets after being suitably reformed - applying submission unit bids - can directly implement the present invention, highlighting its industrial applicability.

Compared to the traditional "intuitive transaction generation algorithm" implemented in DKE, the model conditions presented here guarantee that all natural flows will be limited to the carrying capacity limits of the respective transmission lines - and not to artificially tighter limits such as happens in the mentioned "intuitive transaction generation algorithm" - and zone injections will be distributed dynamically to internal nodes, in a non-static way. This is the main improvement of the proposed solver method over the currently implemented "intuitive trade generation algorithm" that has been incorporated into the EUPHEMIA solver of the European day markets [14].

1 Basic nomenclature

Indexes and Totals

n Index of system nodes

n(z) Index of system nodes within a bid zone z

z Index of bid zones

e Index of transactions between interconnected bidding zones

e(z, z') Trade from bid zone z to bid zone z'

i Index of transmission lines (branches)

l(n,n') C transmission line (branch) that joins nodes n and n'

Parameters

Qsn, Psn Injection bid amount and price at node n , in MWh and €/MWh, respectively

Qdn, Pdn Absorption bid quantity and price at node n , in MWh and €/MWh, respectively

FL<up>, FL<lo>Upper (positive value) and lower (negative value) limits of available natural flux on line l , in MW, respectively. These limits are also called Available Flow Margin (AFR) in the terminology of flow-based modeling.

ΖΜΜe,z Transaction / zone mapping table, which takes a positive (value = 1) and negative (value = -1) for each transaction e made from / to bid zone z, respectively. All other values of row e of the table are zero.

PTDFi,nTransport Distribution Factor Power of the flow in branch I relative to a nodal injection at node n and an absorption from the reference node of the system. The SKMI matrix satisfies the energy balance at each node, that is, the nodal net energy injection (positive or negative) is equal to the algebraic sum of the energy flows from and to the connected (neighboring) nodes.

ATCe<up>,ATCelo Upper and lower limits (Available Transmission Capacities) for transaction e, in MW, respectively

GSKznGeneration Allocation Key of node h in relation to bidding zone z

Main Variables

XsnAmount of energy injection into node h, in MWh

XdnAmount of energy absorption at node h, in MWh

EXn∈ Amount of transaction e, in MWh

Rsn, RdnComplementary (binary) variable of maximum energy injection and energy absorption constraints at node n, respectively, in €/MWh

lo

Rfl<up>, RF Complementary (binary) variables of upper and lower flow limits of transmission line I, respectively, in €/MW

Rexe<up>, Rexe<lo>Complementary (binary) variables of upper and lower limits of transaction quantity e, respectively, in €/MWh.

2 References

[1] ENTSO=E, Capacity Allocation and Congestion Management Network Code (CACM NC), July 2015. Available at

http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32015R1222&from=EN [2] CWE REM, “CWE Enhanced Flow-Based MC feasibility report”, October 2011. Available at http://www.casc.eu/media/CWE%20FB%20Publications/CWE_FB-MC_feasibility_report_2.0_1910 201 1.pdf.

[3] CWE REM, "CWE enhanced flow-based MC intuitiveness report", October 2013. Available at

https://www.apxgroup.com/wp-content/uploads/2-CWE_FB-MC_intuitiveness_report_October-2013.pdf.

[4] EPEXSPOT, “CWE Flow-Based Market Coupling Forum”, October 2013. Available at https://www.epexspot.com/document/24695/CWE%20FB%20MC%20Market%20Forum% 2C%200ctober%201 0th %2C%20201 3.pdf.

[5] CASC, “Documentation of the CWE FB MC solution as basis for the formal approval request, Annex 16.18 Flow-Based intuitive explained”, August 2014. Available at http://www.casc.eu/media/Annex%201 6_18 %20Flow-Based%20intuitive%20explained.pdf.

[6] CREG, “Position Paper of CWE NRAs on Flow-Based Market Coupling”, March 2015. Available at http://www.cre.fr/en/documents/deliberations/approval/flow-basedmarket-coupling/position- paper-of-cwe-nras-on-flow-based-market-coupling.

[7] European Market Design Working Group, “Flow-Based Market Coupling Status Update”, April 2015. Available at http://publications.elia.be/upload/UG_upload/QEJA90KQLV.pdf.

[8] E-Control, “Documentation of the CWE FB MC solution as basis for the formal approval-request”, May 2014. Available at

http://www.econtrol.at/portal/page/portal/medienbibliothek/statistik/dokumente/pdfs/CWE%20FB%20M C%20Approval%20document.pdf.

[9] CREG, "NRA public consultation on Flow Based Market Coupling, Synthesis of respondents' answers", July 2014. Available at http://www.cre.fr/en/documents/publicconsultations/flow-based-market-coupling -fb-mc-and-its-implementation-in-the-cweregion/read-the-synthesis-of-the-answers-to-the-public-consultation.

[10] ENTSO-E, "Procedures for cross-border transmission capacity assessments", October 2001. Available at https://www.entsoe.eu/fileadmin/user_upload/_library/ntc/entsoe_proceduresCapacityAssessments.pdf.

[11] Commission Regulation (EU) 2015/1222 of 24 July 2015 establishing a guideline on capacity allocation and congestion management. Available at

http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32015R1222&from=EN [12] A.G. Vlachos, P.N. Biskas, “An Integrated Intuitive Exchange- and Flow-Based Market Clearing Model”, IEEE Transactions on Power Systems, vol. 31, no. 5, Sept. 2016.

[13] Methodology and concepts for the Nordic Flow-Based Market Coupling Approach. Available at http://www.fingrid.fi/fi/asiakkaat/asiakasliitteet/S%C3%A4hk%C3%B6markkinat%20ja%20 edunvalvonta/Methodology%20and%20concepts%20for%20the%20Nordic%20Flow-Based%20Market %20Coupling%20Approach.pdf

[14] EPEX Spot, APX, Belpex, Nord Pool Spot, OMIE, GME, and OTE, "EUPHEMIA public description," Oct. 2013. Available at

http://www.apxgroup.com/wp-content/uploads/Euphemia-public-description-Nov-20131.pdf.

Claims (20)

Claims 1. A system for processing bids submitted to auctions by electricity market participants for electricity market products, which includes: A-a database that includes model parameters and bid data, and the model parameters and bid data are applied to equations that correspond to an electricity market and include at least one variable to be determined. B-a processor connected to the database, which simultaneously solves the equations for at least one variable to be determined, and the solution is performed iteratively to determine the at least one variable according to a predetermined objective or criterion, and C - means for the publication of the results of the auction to inform the participants in the electricity market, where means of publication, it is understood that it performs at least one of the following processes: - publishes solutions of at least one variable in an electronic medium for its retrieval by participants, and - electronically communicates the solution for at least one variable to electricity market participants, and/or, where the respective publication includes posting and electronic notification of at least one variable. 2. A system, in particular according to claim 1, for conducting an electricity market auction, comprising: A- a server connected to a communication network, which serves the electricity market, B-a plurality of electronic devices coupled to the communication network, which communicate with the server to submit offers for electricity market products, C- and at least one database coupled to the server, in which the submitted bids, electricity network model parameters and electricity market parameters are stored, and the server simultaneously processes the submitted bids to determine the results of auction. where in particular the above electronic devices of the system include at least one of the following: computer, facsimile, telephone and personal communication device, and/or where the above system server publishes the available results of the auction on the electronic devices, where publication of results constitutes at least one by the following processes: publication on a communication network and electronic transmission. 3. A system, in particular according to one of claims 1 to 7, which is characterized in that it comprises a computer-readable medium having stored sequences of instructions, which also include the instructions executed by a processor, and which allows in the editor: A-to retrieve modeling parameters and multitude of bids submitted for electricity market products, B-apply the modeling parameters and offers to equations that correspond to an electricity market and include at least one variable that must be determined, C-solve the equations for at least one variable, where said solving is performed iteratively to determine at least one variable according to a predetermined objective or criterion, and D-to publish the results of the auction for the information of market participants. 4. A system, in particular according to claims 1 to 7 and/or 8, which is characterized in that it comprises a computer-readable medium having stored sequences of instructions, including the instructions executed by a processor, and the which allows the processor to: A-to establish a communication link of a market participant with a market operator, B-to communicate offers of a market participant for electricity market products to the market operator, and C-to receive the results of the auction from the market participant, which are produced simultaneously. 5. A system, in particular according to one of claims 1 to 4, characterized in that it comprises at least one computer programmed to perform a procedure for participating in an electricity market in which a server operated by a market operator conducts an auction for electricity market products, where the process includes the steps: A- transmission of electronic signals to establish a communication link between a computer of a market participant and the server, B- creating at least one offer for the electricity market products, and C- generating electronic signals representing at least one bid which will be sent to the server for submission of at least one bid to be submitted to the auction, while the bids are simultaneously processed to determine the results of the auction, in particular where the process further includes: determining the results of the auction based on at least one bid and generating the electronic signals representing the results of the auction which will be sent by the server to the market participant's computer. 6. A system, in particular according to one of claims 1 to 5, which is characterized in that it includes at least one computer programmed to process the offers submitted by market participants for electricity market products, where the processing includes the steps: A-reception of electronic signals representing the parameters of the electricity market model, B-receiving electronic signals representing the bids submitted by market participants, C-applying the parameters of the model of the electricity market and the offers to equations representative of an electricity market which include at least one variable to be determined. D-recursively computing solutions to at least one variable until that variable satisfies a predetermined goal or criterion. E-determining the results of the auction based on at least one variable that is determined, and F-sending electronic signals representing the results of the auction for the publication of the results of the auction, in particular where the above auction results are published in an electronic network. 7. A system, in particular according to one of claims 1 to 6, for determining results of an auction carried out for products of an electricity market, which is characterized in that the system includes: A-media for storing the data of model parameters and offers, B-means for reading model parameters and bid data from said storage media, C -means for using model parameters and bid data to determine auction results, and D-media for the publication of the results of the auction. 8. The system according to any one of claims 1 to 7, further A- where the electricity market is an integrated electricity market or a set of coupled electricity markets, additionally comprises at least one of the following: a) a number of nodes of a physical electricity network, b) a number of transmission lines connecting said network nodes, where the physical power flow of the line is limited by an upper limit, and where the physical power flow is defined as a linear function of of nodal energy injections and nodal energy injection is defined as injected energy minus energy absorbed at the corresponding node, c) a number of electricity transaction zones which contain an arbitrary number of nodes, d)a number of energy transactions processed between interconnected zones,<.> e)a number of offers, for injecting energy into at least one node, and f) a number of offers, for energy absorption in at least one node, B- where one of the following electricity market products is included: electricity, reserve power, and transmission power, C- where the settlement calculations or auction results include at least one of the following: scheduled quantities, and / or trading quantities, and / or clearing prices of the electricity market products and the use of power flow transmission, D- where the publication includes the posting of the solutions of at least one variable of the scheduled quantities, and/or the transaction quantities, and/or the clearing prices of the electricity market products, E- where the above system, also includes the matching of bid data, scheduled quantities and / or transaction quantities and / or clearing prices to electricity network positions, where the electricity network position represents at least one of the following: a bus of a power system, a node of a power system, a zone of a power system, a group or a random number of busses or nodes or zones, F-where a market participant submits a bid which includes a set of points defining a price and quantity curve for electricity market products, G- where the offers for the purchase of electricity include at least one period of time for products of the purchase of electricity, H- where this process or solution involves carrying out an optimization or calculation process, Θ- where the optimization or calculation process involves solving (repeatedly or once) a set of necessary variables and conditions included in a set of simultaneous equations, I- where the process or resolution, is performed over multiple periods of time, either collectively or individually, and K- where the procedure or resolution is performed after an acceptable time limit which corresponds to the submission of new offers and the modification of offers. 9. A method for processing bids submitted to auctions by market participants for electricity market products, in particular for implementing the system according to one of claims 1 to 15, characterized in that the method comprises the steps: A-retrieving model parameters and bid data for electricity market products, B- the application of the parameters of the model and the data of the offers in equations which correspond to an electricity market and include at least one variable that must be determined, C-the simultaneous solution of the equations for at least one variable, where the solution is performed iteratively to determine at least one variable, and D- the publication of the results of the auction to inform market participants, in particular where the above published results include solutions of at least one variable of the quantities and/or clearing prices for the electricity market products. 10. A method, in particular according to claim 9, used to conduct an auction for an electricity market, characterized in that the method comprises the steps: A-starting a data collection process of the electricity market auction to receive the bids submitted by market participants for electricity market products, B- receipt of offers regarding electricity market products, C-end of the data collection process of the electricity market auction, and D-simultaneous processing of offers to determine the results of the electricity market, in particular where it also includes a validation process of the electricity market offers, in addition in particular the publication of the results of the auction respectively, in particular where publication includes at least one of the following processes: - publishing the results of the calculation in electronic media, and/or - communicating the results to market participants via electronic communication, and further in particular where published results include public information which is accessible by market participants. 11. The method according to claim 10, wherein the results via electronic notification include private information, and/or wherein the electronic notification includes at least one of the following electronic means: electronic mail, text messages, and facsimile. 12. A method, in particular according to one of claims 9 to 11, for participating in an auction of an electricity market conducted by a market operator for market participants, comprising the steps of: A- establishing a communication link between the market participant and the market operator, B- notification of an offer for electricity market products by the market participant to the market operator, and C- receiving the results of the auction from the market participant, which are produced at the same time, in particular where the results of the auction are received via electronic communication, in particular where this receipt includes: accessing a network location, and receiving the results by entering an access code to the network location, and/or where the results of the auction are published in a publicly accessible location. 13. The method according to one of claims 9 to 12, in particular for realizing the system according to claim 8, characterized in that further A- where the settlement calculations, and/or auction results include at least one of the following: scheduled quantities, and/or trading quantities, and/or clearing prices of electricity market products and the use of power flow transmission, B- where the publication includes the publication of the solutions of at least one variable of the scheduled quantities, and / or the transaction quantities, and / or the clearing prices of the electricity market products, C- where the above method, system, computer or means, further comprises the matching of the bid data, the scheduled quantities and / or the transaction quantities and / or the clearing prices to electricity grid positions, where the electricity grid position represents at least one of the following: a bus of a power system, a node of a power system, a zone of a power system, a group or a random number of busses or nodes or zones, D- where a market participant submits an offer which includes a set of points defining a price and quantity curve for electricity market products, E- where offers for the purchase of electricity include at least one time period for products of the purchase of electricity, F- where the process or solution involves carrying out an optimization or calculation process, G- where the optimization or calculation process involves solving (repeatedly or once) a set of necessary variables and conditions included in a set of simultaneous equations, H- where the process or solution is performed for multiple time intervals, either collectively or individually , and Θ- where the procedure or resolution is performed after an acceptable time limit which corresponds to the submission of new offers and the modification of offers. 14. A method, in particular according to claims 9 to 13, for calculating the loading of the transmission lines of an electric network and managing the congestion of the natural electricity flows of the electric network under trading rules, where the electric network consists of: A- a set of nodes of a physical electrical system, B- a set of transmission lines connecting the nodes of the system, whose natural energy flow is limited by an upper limit, where said natural energy flow is defined as a linear function of nodal energy injections, where said nodal energy injection is defined as the energy that is injected reduced by the energy that is absorbed at the corresponding node, C- a group of nodes in a random number of electricity trading zones, D- a set of energy transactions that take place between interconnected electricity trading zones, E- a set of instructions to inject energy into each node, and G- a set of energy absorption commands at each node, which is characterized in that the above method includes the following steps a- definition of an electricity trading clearing signal, for each electricity trading zone, b-determining the cleared amounts of energy injection at each node, with injection order limits that are less than or equal to the corresponding clearing signal of the electricity trading zone, c-determining the cleared amounts of energy absorption at each node, with limits of absorption orders that are greater than or equal to the corresponding clearing signal of the electricity trading zone, d-determining the flows of transmission lines that are less than or equal to the corresponding limit carrying capacity, e-determining the amounts of energy traded between the electricity trading zones, with a direction from a zone with a lower clearing signal to a zone with a higher clearing signal, f- determining the energy balance of each electricity trading zone, the corresponding nodal net energy injections of the nodes included within the electricity trading zone, and the energy transactions with all the interconnected electricity trading zones. 15. The method according to claim 14, which is characterized in that it includes in the clearing condition of the injection orders only positive terms with respect to the contribution of the nodal injection to the transmission line flows, i.e. positive SKMI with respect to an upper limit of transmission capacity of the transmission line, and negative SKMIs with respect to the lower carrying capacity limit of the transmission line, where the condition for clearing injection orders at node (h) includes at least the following formulation: in particular where in said condition the variable Rsn is defined by the condition Xsn≤ Qsnl Rsn≥ 0 (65) 16. The method according to claim 14 or 15, which is characterized in that it includes in the clearing condition of the nodal absorption orders only positive terms with respect to the contribution of the nodal absorption to the transmission line flows, and consists of positive SKMI with respect with the lower transmission line carrying capacity limit and negative SKMIs with respect to the upper transmission line carrying capacity limit, where the condition for clearing absorption orders at node (h) includes at least the following formulation: in particular where in said condition the variable Rdn is defined by the condition Xdn≤ Qdnl Rdn≥ 0 (67) 17. The method according to claim 14 to 16, characterized in that the variable Rfli<up>is defined by the condition: and the variable Rfl<lo> is defined by the condition: and the variable Rj is defined by the condition: 18. The method according to claim 14 to 17, characterized in that the settlement condition of a cross-zone transaction (e) consists of at least the following formulation: 19. The method according to claim 14 to 18, characterized in that the variable MPZ is defined as the clearing signal of the electricity trading zone, and wherein the energy balance constraint of the zone (g) is defined as follows: 20. The application method according to one of claims 14 to 19, characterized in that said electricity trading system corresponds to an electricity market, wherein said electricity trading zones correspond to bid zones, further wherein said signal clearing correspond to a price, and further where said orders correspond to bids.