CN201716569U - Optimization system of heat and power cogeneration energy system in paper mill - Google Patents

Abstract

The utility model discloses an energy system optimization system for cogeneration of heat and power in a paper mill. The system consists of a data acquisition system, a real-time database, a relational database, a material flow simulation model library, an energy flow simulation model library, an energy flow optimization model library and a man-machine The interactive interface is connected to each other; the system collects the key data of energy consumption through the data acquisition system and stores it in the relational database, and optimizes the data in the relational database by the material flow simulation model library, energy flow simulation model library and energy flow optimization model library. The optimization results are stored in the relational database, and the on-site control systems such as SCADA and DCS are called to automatically optimize the system. The system of the utility model can realize the economical operation of the cogeneration energy system, effectively save energy, reduce operating costs or increase profits.

Description

An optimization system for cogeneration energy system in a paper mill

technical field

The utility model relates to an optimization system for cogeneration energy system of a pulp and paper mill, in particular to an optimization system for cogeneration energy system of large and medium-sized pulp and paper mills with more than or equal to two boilers or two sets of steam turbine generator sets.

Background technique

The paper industry is a resource and energy-consuming industry. With the rapid development of my country's national economy, the consumption of paper products is increasing rapidly, and the market demand is expanding year by year. The paper industry has been listed by the National Development and Reform Commission as one of the nine high-energy-consuming key regulatory industries. The combined heat and power system is an important part of the pulp and paper making enterprise, and its safe and stable operation is the basis for the safe, stable and long-term operation of the enterprise. Usually, a combined heat and power system consists of multiple boilers and steam turbines. Under the condition of meeting the production electricity requirements, the steam produced by the boilers or the steam extracted or exhausted by the steam turbines provide the heat required by the process. Due to the variety of products, production volume, production status, market sales and seasonal changes, etc., the steam consumption and electricity consumption will change accordingly.

Different from the unit units used in large-scale thermal power plants and thermal power plants, the combined heat and power system in papermaking enterprises usually adopts a parent-controlled thermal system. Under actual conditions, most systems are designed with the same pressure level of fresh steam, and all boilers are connected in parallel to the main pipe of the thermal system. The biggest feature of the main pipe thermal system is that the boiler and the steam turbine are independent of each other, that is, the steam generated by a certain boiler is not directly connected to the corresponding steam turbine, but is provided to the steam main pipe together with all the steam of the same level in the system, and then passed through The pipeline transports steam to various steam consuming equipment in the system and external users. Under the structure of parent control, the boiler system and the steam turbine system are only connected by the total steam production of the boiler. Under the condition that the total steam production of the boiler system remains unchanged, the load of the downstream steam turbine will not be affected by the load of a certain upstream boiler. The impact of changes, the simple series relationship between the steam turbine and the boiler of the unit unit is eliminated, and from the perspective of operation optimization, the degree of freedom of the system is increased, thus increasing the operability of the thermal system.

Generally, cogeneration systems need to provide power, electricity, heat, steam and other energy to pulping and papermaking processes. Due to the diversification of products, in order to effectively use energy, it is necessary to rationally use steam of various pressure levels generated in the production process or supply steam of various pressure levels to meet production needs.

Abnormalities in pulp and paper production can affect the operation of cogeneration systems. Usually, thermal power plant engineers are more concerned about whether the production is normal and stable than whether the operation is economical. Due to local changes or abnormal occurrences in pulping and papermaking production, passive adjustments made by engineers usually make the combined heat and power system in an uneconomical operating state. Therefore, how to make the most economical operation of the system has become a top priority under the condition of meeting the changes in steam and power demand caused by changes in process processing volume, product scheme, climate, seasons and other factors.

Utility model content

The purpose of this utility model is to overcome the unscientific manual adjustment of the current cogeneration energy system, change the current uneconomical situation of the system, and provide a large , Cogeneration energy system optimization system for medium-sized pulp and paper mills. Through this system, the economical operation and automatic adjustment of the combined heat and power energy system can be realized.

The technical solution adopted for the purpose of realizing the utility model: a paper mill cogeneration energy system optimization system is characterized in that it includes:

A data acquisition system used to collect the demand data of various departments for steam and electric energy and store them in the real-time database;

A real-time database for storing and transmitting data collected by the data acquisition system;

A relational database for storing and transmitting data required for optimization and optimized result data;

A material flow simulation model library used to simulate the material flow of the production process stored in the relational database and store the simulation results in the relational database;

The energy flow simulation model library for simulating the energy flow data of the production process stored in the relational database combined with the simulation results of the material flow simulation model library and storing the simulation results in the relational database;

It is used to optimize the energy flow in the production process according to the simulation results of the energy flow simulation model library and feed back the optimization results to the human-computer interaction interface for display and monitoring. At the same time, the optimization results are stored in the relational database so that the on-site monitoring system can extract An energy flow optimization model library that assigns relevant data to relevant set values to optimize system operation;

Human-computer interaction interface for production dispatchers to interact with real-time databases, relational databases and energy flow optimization model libraries;

The data acquisition system is connected to the real-time database; the real-time database is connected to the relational database; the relational database is connected to the energy flow simulation model library, the material flow simulation model library and the human-computer interaction interface; the relational database is also connected to the input device operating state The data is connected to the manual input port of production planning information; the material flow simulation model library is connected to the energy flow simulation model library; the energy flow simulation model library is connected to the energy flow optimization model library; the energy flow optimization model library is connected to human-computer interaction The interfaces are connected with each other; the human-computer interaction interface is also connected with the real-time database.

In order to realize the utility model better, described data acquisition system comprises the SCADA, PLC and DCS system and data acquisition instrument that are arranged on production and life auxiliary workshop; The data that data acquisition instrument gathers is not installed SCADA, PLC, DCS system The demand data for steam and electric energy in some workshops is collected on-site and manually entered into the real-time database.

The power flow optimization model library includes:

The steam turbine system optimization model library of the steam turbine system energy optimization scheme is obtained by establishing an optimization model for the steam turbine system and solving it;

Boiler system optimization model library for boiler system energy optimization scheme obtained by establishing an optimization model for the boiler system and solving it;

The output of the steam turbine system optimization model library is connected to the input of the boiler system optimization model library.

The human-computer interaction interface includes a PC installed in the boiler unit workshop, a PC installed in the steam turbine unit workshop, and a PC in the central control room of the paper mill.

The real-time database collects relevant data from the data acquisition system through Ethernet and stores them.

The working method of the above paper mill cogeneration energy system optimization system includes the following steps:

In the first step, the data acquisition system collects the demand information of various departments for steam and electric energy, and stores it in the real-time database for calling by the relational database and the human-computer interaction client. The relational database reads relevant data from the real-time database according to the demand and stores them in The relational database, order scheduling plan and production maintenance plan are also input and stored in the relational database through the manual input port, which can be called by the energy flow simulation model library, material flow simulation model library and human-computer interaction client;

In the second step, the material flow simulation model library reads relevant data from the relational database for simulation calculation, stores the calculation results in the relational database and transmits them to the energy flow simulation model library; the energy flow simulation model library reads from the relational database Relevant data, combined with the calculation results of the material flow simulation model library to perform simulation calculations, store the calculation results in the relational database and transmit them to the energy flow optimization model library; the steam turbine system optimization model library in the energy flow optimization model library reads the energy flow Simulate the calculation results of the model library, and read the relevant data of the paper mill's related equipment operation status, order scheduling plan, and production maintenance plan from the relational database, and calculate the optimal operation of the steam turbine generator set to obtain the minimum power consumption required by the steam turbine system. The gas volume is stored in the relational database; the boiler optimization model library in the energy flow optimization model library calculates the minimum steam consumption required by the steam turbine system according to the steam turbine system optimization model library, so as to obtain the necessary steam production of the boiler system, and then As an external constraint on the boiler system, combined with the relevant data of the paper mill's related equipment operating status, order scheduling plan, and production maintenance plan in the relational database, the optimal operation calculation of the boiler unit is carried out with the goal of minimizing coal consumption, and the optimization results are calculated stored in a relational database;

In the third step, the human-computer interaction interface reads relevant data from the real-time database and relational database through Ethernet, and displays the calculation results of the energy flow optimization model database and key indicators of energy consumption. At the same time, a printer can be installed to print relevant information; at the same time, SCADA, On-site monitoring systems such as DCS obtain optimization results from relational databases, and can automatically realize the optimization function by assigning relevant set values in AUTO mode.

In the above-mentioned working method, in the second step, optimizing the operation calculation of the steam turbine generator set or the boiler unit refers to adopting the eTMS program (note: the program has obtained software copyright registration, and the registration number is 2009SR09023) to optimize the steam turbine system model or The boiler system optimization model is solved.

The working principle of the utility model is as follows: the data acquisition system, in addition to collecting various data that need to be monitored and storing them in the real-time database, also obtains optimization information from the relational database and realizes the automatic optimization function in the AUTO mode; the material flow The simulation model library, energy flow simulation model library, and energy flow optimization model library can analyze, optimize and store relevant information in the relational database by calling the data in the real-time database and relational database; the boiler unit PC, steam turbine unit PC, The human-computer interaction interface composed of PCs and other dispatching centers in the paper mill is responsible for displaying and monitoring optimized results, energy consumption and energy efficiency data, and can print out relevant reports with a printer. Data acquisition system, including data acquisition of SCADA, PLC, DCS acquisition systems used in pulp and paper, thermoelectric workshops, water treatment workshops and production auxiliary workshops, offices, dormitories, canteens, etc. On-site related data collection, which stores the collected data in the real-time database; for further processing, part of the data in the real-time database is stored in the relational database at the same time, and information such as order scheduling plan and production maintenance plan is also stored in the relational database Medium; the material flow simulation model library simulates the material flow in the production process through the interaction with the relational database and stores the simulation results in the relational database; the energy flow simulation model library simulates the energy flow in the production process through the interaction with the relational database Carry out simulation and store the simulation results in the relational database; the energy flow optimization model library is based on the energy flow simulation model library, optimizes the energy flow in the production process and feeds back relevant information to the human-machine interface for display , monitoring, and at the same time store the optimization results in the relational database for SCADA, DCS and other on-site monitoring systems to call; for those information that does not need to be analyzed, optimized, and dispatched, it can directly interact with the historical database through the human-computer interaction interface and display it to the user.

The energy flow optimization model is a mathematical programming model established on the basis of the material flow model and energy flow model combined with the operating conditions of energy conversion equipment such as steam turbines and boilers. It achieves the minimum energy consumption of the system under the condition of meeting the energy consumption of process production Maximization or maximization of profit under the premise of constant energy consumption, thereby improving energy efficiency.

The principle of establishing the material flow simulation model is as follows:

Material flow is from the raw material market through raw material procurement (including auxiliary materials and additives, etc.), storage and transportation (including raw materials, auxiliary materials, additives, intermediate products, products and by-products, etc.), processing and product sales (including by-products), etc. to the product market. Evolution. The processing process is the core part of the whole material process, including separation system, mixing system, reaction system, etc. In this process, the total amount of raw materials and the total amount of products, storage and transportation loss, processing loss and waste discharge conform to the law of mass conservation, and its essence is the combination of separation, mixing and reaction processes.

Usually, during the separation and mixing process of materials, the position and size of the equipment do not change with time, as shown in Figure 1, it satisfies:

In the formula, the density ρ of matter at various places is a function of space position and time, m is the mass source in each equipment or process, v _n is the velocity along the normal direction on the surface, that is, the velocity vector v is in the unit of the outer normal direction Projection on a vector n.

According to Gauss' theorem in field theory:

The area integral of (1) can be converted into volume integral, and we can get

The mass conservation equation or continuity equation in differential form can be obtained as:

)可得物料平衡方程：For separation and mixing equipment, we divide the materials into inflow materials (i), outflow materials (j) and source items (

) can obtain the material balance equation:

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; -</span>}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; \&rho;v</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\mathrm{<span\; class="notranslate">\; \&delta;S</span>}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; +</span>}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; \&rho;v</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\mathrm{<span\; class="notranslate">\; \&delta;S</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; l</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}$

The integral on the left side of the above formula represents the quality of inflow, the integral domain is s ^- (v _n <0), and the integral is a negative number; while the integral on the right represents the quality of outflow, the integral domain is s ⁺ (v _n >0), and the integral is positive number. The chemical reaction of the material needs to meet the mass balance of the components. Even if there is no mass source in the system, the chemical reaction is the reduction of the reactant, which is a negative mass source for the reactant and a positive mass source for the product. Therefore, the continuous The sex equation should be:

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; -</span>}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\mathrm{<span\; class="notranslate">\; \&delta;S</span>}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; +</span>}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}\mathrm{<span\; class="notranslate">\; \&delta;S</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; l</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}$

The simulation model of the material flow is established as above, and the simulation result of the material flow can be obtained by solving the model with the eTMS program.

The establishment principle of the energy flow simulation model is as follows:

Energy is attached to the material through separation, mixing, reaction and other processes to achieve conversion and transmission, utilization, recovery and other processes. In order to more accurately reflect the energy efficiency and energy consumption of each process, we apply the first law of thermodynamics and the second law. Modeling of energy flow.

The energy balance diagram of the process shown in Figure 2, for a process, the sum of the heat Q released from the flow system to the environment during the time from t1 to t2 and the work W done by the system to the outside must be equal to the total energy of the system increase, i.e. energy conservation:

Q+W=ΔH=H ₁ -H ₂

The differential form of the above formula is:

dH=dQ+dW

The total enthalpy of the incoming stream H ₁ =∑H _i , the total enthalpy of the outgoing stream H ₂ =∑H _i , the heat exchanged between the system and the outside world Q=Q _e -Q _i , work W=W _e -W _i ;

∑(H _i -H ₀ )+Q _i +W _i ＝∑(H _e -H ₀ )+Q _e +W _e

(Ex)的计算式为：From the second law of thermodynamics it can be deduced that

(Ex) calculation formula is:

E _X ＝(HH ₀ )-T ₀ (SS ₀ )

Its differential form is:

δE _X ＝dH-T ₀ dS

For any flow process system, the total entropy of the inflow side is always equal to or less than the total entropy of the outflow side, which can be obtained:

$\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}}$

Simultaneously with the energy balance equation, we can get:

$\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}\frac{{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>$

$\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}\frac{{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}$

之和，下表M表示物流； $Q_i(1-\frac{T_0}{T_i})={\left(E_{\mathrm{XH}}\right)}_i$ 为供入体系的全部热量中所含有的

，下标H表示热量；W_i＝(E_XW)_i为供入体系的功相应的

，下标W表示功。出方各项按此归纳可得：In the formula: ∑[(H _i -H ₀ )-T ₀ (S _i -S ₀ )]=∑(E _XM ) _i is the sum of all streams entering the system

The sum, the following table M represents logistics; $Q_i(1-\frac{T_0}{T_i})={\left({\mathrm{E.}}_{\mathrm{XH}}\right)}_i$ is contained in the total heat supplied to the system

, the subscript H means heat; W _i = (E _XW ) _i is the work corresponding to the input system

, the subscript W stands for work. The output items can be summed up according to this:

∑(E _XM ) _i +(E _XH ) _i +(E _XW ) _i ≥∑(E _XM ) _e +(E _XH ) _e +(E _XW ) _e

损耗，即可得

平衡方程：Denote the actual process by D _k

loss, gain

Balance equation:

∑(E _XM ) _i +(E _XH ) _i +(E _XW ) _i ＝∑(E _XM ) _e +(E _XH ) _e +(E _XW ) _e +D _K

As above, the energy flow simulation model can be established, and the result of the energy flow simulation can be obtained by solving the model with the eTMS program.

The steps for modeling an optimization model are as follows:

The first step is to determine the initial scale of the energy conversion link optimization problem by obtaining relevant information such as pulping, papermaking, auxiliary workshops, offices, etc. for steam and electric energy according to the relational database;

The second step is to establish a nonlinear programming model for energy system optimization based on cogeneration mode;

The third step is to solve the above optimization model combined with the actual situation of pulp and paper production to obtain an optimal target value and operation plan;

Among them, the optimized mathematical model in the second step can usually be expressed as:

min F(x)

s.t.p(x)≥0

Among them, F(x) is called the objective function, which can be an economic target such as total expenditure, a technical target such as fuel consumption, or an environmental target such as pollution discharge. In the optimal operation problem, because the structure of the system does not change, many expenses such as fixed investment expenses in the total expenditure are constant, and they do not change with the change of the operation plan. When the other expenses change, the total expenditure changes monotonously with the change of fuel consumption, and the goal of the lowest fuel consumption can reflect the situation of the total expenditure. p(x) is a constraint function, which reflects the requirements of the outside world on the system and the relationship between various physical quantities inside the system.

Different from the unit units used in large thermal power plants, the thermal system of parent control is usually used in papermaking enterprises. The biggest feature of the main pipe thermal system is that the boiler and the steam turbine are independent of each other, that is, the steam generated by a certain boiler is not directly connected to the corresponding steam turbine, but is provided to the steam main pipe together with all the steam of the same level in the system, and then passed through The pipeline transports steam to various steam consuming equipment in the system and external users. Under the structure of parent control, the boiler system and the steam turbine system are only connected by the total steam production of the boiler. Under the condition that the total steam production of the boiler system remains unchanged, the load of the downstream steam turbine will not be affected by the load change of an upstream boiler. Impact. From the point of view of operation optimization, the degree of freedom of the system increases, thus increasing the operability of the thermal system. In terms of strategy, the operation optimization problem is regarded as the optimal operation problem of two independent subsystems connected in series, that is, the optimal operation of the boiler system and the steam turbine system.

Optimal Operation of Steam Turbine System

Since the characteristics of various steam turbines show linear characteristics, here we do not consider the start/stop problem of the equipment in the optimal operation, so the research problem can be simplified as a linear programming problem, and the corresponding model can be adopted accordingly, namely

minF(X)=CX

s.t.G(X)<B

x _i ≥ 0

In the formula: X is a continuous variable, C=[c ₁ , c ₂ ,..., c _n ] is a vector of cost coefficients, and our objective function for steam turbines is the minimum total steam consumption, where C is a unit vector. G is the constraint function coefficient matrix, and B is the resource vector.

(1) Objective function

The purpose of optimal scheduling of the steam turbine system is to ensure the minimum total steam consumption of the steam turbine system, so the objective function can be expressed as

$\mathrm{<span\; class="notranslate">\; min</span>}\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; Si</span>}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; Di</span>}$

为n台汽轮机进汽量之和，t/h；

为m台减温减压阀进汽量之和，t/h。目标就是在满足总供电和供热需求的情况下，使总的蒸汽需求量最小。In the formula, S is the total steam demand, t/h;

is the sum of steam intake of n steam turbines, t/h;

It is the sum of steam intake of m temperature reducing and reducing valves, t/h. The goal is to minimize the total steam demand while meeting the total power and heating demand.

(2) Constraint function

The constraint function reflects the requirements of the outside world on the system under actual operating conditions and the relationship between various physical quantities within the system. These constraints roughly include the following types:

(a) Generation constraints

This constraint ensures that the power supply of the thermal system meets the needs of users, that is,

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; P</span>}$

(b) Constraint of external steam supply

Under the determined external steam load in the main pipe of each pressure level, the balance of steam flow in and out should be satisfied, that is,

$\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; in</span>}}<span\; class="notranslate">\; )</span>}_{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; out</span>}}<span\; class="notranslate">\; )</span>}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; load</span>}}$

(c) Device Model Constraints

That is, the characteristics of each steam turbine under actual operating conditions, which reflect the relationship between the steam intake, exhaust steam and power of the steam turbine. Taking the secondary regulation extraction steam turbine as an example, its characteristic equation is shown below.

S _in ＝a ₀ +a ₁ N _i +a ₂ S ₁ +a ₃ S ₂

For once-adjusted extraction steam turbines, extraction backpressure steam turbines, backpressure steam turbines, and condensing steam turbines, the above corresponding regression coefficients are zero, which constitutes the constraint of the equipment model in the optimal scheduling of steam turbine systems.

(d) Adjusting the constraints of the pure condensing steam condition of the extraction steam turbine

That is, the lower boundary of the operating area of the steam turbine in the working condition diagram introduced above. According to its physical meaning, it means that any point in the operating area must meet the requirement of S _i ≥ 0.

(e) Constraints on the minimum steam intake of the low-pressure cylinder

In an extraction regulated steam turbine, if the proportion of regulated extraction steam is high, the steam flow through the low pressure cylinder will be correspondingly reduced. Because when the steam flow rate of the low-pressure cylinder is too low, the heat generated due to frictional blowing loss, etc. will cause the temperature of the low-pressure cylinder to rise a lot, even exceeding the allowable level. Therefore, the low-pressure unit must maintain a minimum flow to make the steam cool the low-pressure unit, so this constraint must be added in the optimal operation calculation. This constraint takes the form:

S _in -S _1i -S _2i -∑S _ij ＞(S _COND ) _min

Among them, S _ij represents the sum of steam extraction volumes used by each section of the steam turbine to heat the regenerator. These steam extraction volumes are generally not directly measured, but need to be obtained through balance calculations.

(f) Maximum steam intake constraint

In actual operation, it is stipulated that the steam intake of the steam turbine cannot exceed the maximum steam intake requirement proposed in the design, that is,

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; in</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; in</span>}}_{\mathrm{<span\; class="notranslate">\; max</span>}}}$

(g) Maximum generating power limitation

In actual operation, the steam turbine can operate under the condition of exceeding the rated power, at this time, the steam turbine is said to be in an overload condition. For the sake of safety, the maximum generating power of the steam turbine must be strictly regulated in the process of operation optimization to ensure the feasibility of the optimal operation scheme in practice. In this example, the maximum generating power is taken as the rated power of the unit, and the corresponding constraint can be written as:

N _i =N _imax

(h) Constrained steam extraction

In order to ensure the normal operation of the steam turbine, the primary steam extraction volume and the secondary steam extraction volume of the steam turbine are not allowed to exceed the specified values, so the extraction steam volume constraint is increased accordingly in the optimal scheduling.

S _1i ≤ (S _1i ) _max

S _2i ≤(S _2i ) _max

(i) Variable constraints

It specifies the value range of variables in the optimization operation calculation, such as

S _1i ≥ 0; S _2i ≥ 0; N _i ≥ 0

So far, the optimal calculation model of the steam turbine system has been established.

Optimal Operation of Boiler Systems

Since the characteristics of various boilers show nonlinear characteristics, here we do not consider the start/stop problem of the equipment in the optimal operation, so the research problem can be simplified as a nonlinear programming problem. After the optimization operation of the steam turbine system is completed, it can be The minimum steam consumption required by the steam turbine system can be obtained, so that the steam production required by the boiler system can be obtained, and this can be used as an external constraint on the boiler system.

(1) Objective function

The goal of boiler system optimization scheduling is to ensure the minimum total fuel consumption of the system under the condition of satisfying the steam production, that is, minB=∑Bi

(2) Constraint function

The constraint function of the boiler system is relatively simple, it includes the following constraints:

(a) Boiler characteristic constraints:

It reflects the relationship between the fuel consumption of each boiler and the variation of evaporation, that is,

B=f(S _i )

${\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; no</span>}}$

(b) Steam load constraints:

It reflects the requirement of the steam turbine system on the steam production of the boiler system, that is,

$\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; o</span>}}$

In the above formula, S _o is the total steam production of the boiler system.

(c) Boiler evaporation constraints

It reflects the allowable operating range of each boiler, and its constraints are:

(S _i ) _min ≤ S _i ≤ (S _i ) _max

In addition, variable constraints, etc. are also included. Accordingly, an optimal calculation model of the boiler system can be established.

First, calculate the minimum steam consumption required by the steam turbine system based on the steam turbine system optimization model, so as to obtain the necessary steam production of the boiler system, as an external constraint on the boiler system, and then use the boiler system optimization model to calculate, use eTMS The optimal scheduling scheme of the energy system can be obtained by solving the program.

Store the above optimized scheduling plan in the relational database and display it on the man-machine interface at the same time. On-site monitoring systems such as SCADA and DCS can obtain the optimization results from the relational database, and assign relevant setting values in AUTO mode to automatically realize the system operation. optimize.

Compared with the prior art, the main advantages and effects of the utility model are: the utility model applies the "three links" theory to model the entire energy system of the paper mill, and establishes a simulation model of the entire energy flow and material flow. The "three links" analysis method of process energy system is a comprehensive optimization method of process system energy with the goal of global optimization. It is based on the in-depth understanding and description of the energy structure of the process system and the thermodynamic analysis and thermoeconomic on the basis of scientific analysis. The method is supported by modeling and process simulation techniques, and can be used in conjunction with any unit or subsystem optimization techniques (such as mathematical programming, heuristics, artificial intelligence, etc.).

(Yong)流模型，适合过程能量系统的全局优化。The "three links" model believes that the degradation of energy in the entire process occurs gradually in three different functional links, which are divided into energy conversion links, energy utilization links, and energy recovery links according to the evolution process. The "three links" energy structure model summarizes the energy structure and common laws of complex process systems, gives a strict quantitative definition of the energy flow structure model, and establishes a strict energy flow model and

(Yong) Flow models for global optimization of process energy systems.

The "three links" model divides the energy use process in the entire technological process into three links with different functions, namely energy conversion and transmission links, energy process utilization links and energy recovery links. The consumption and depreciation of energy in the whole process occur gradually in three links with different functions. The three links are interconnected and restrict each other.

The energy system of a papermaking enterprise is a typical process energy system, and it is suitable to use the "three links" method to analyze and optimize its energy system globally. Based on the "three links" simulation model, the utility model combines the mathematical programming method with the energy flow simulation model to model the energy system of the papermaking enterprise to optimize the operation and reduce the operation cost. way. Under the conditions of meeting the steam and power demand changes caused by changes in process processing volume, product plans, climate, seasons and other factors, the optimal operation plan can be calculated to achieve the lowest total system operating costs or maximize profits.

Description of drawings

Fig. 1 is the material balance diagram of the technical process in the material flow simulation model;

Fig. 2 is a schematic diagram of technological process energy balance in the energy flow simulation model;

Fig. 3 is a brief structural block diagram of the system of the present utility model;

Fig. 4 is the structural block diagram of the system of the present utility model;

Fig. 5 is the work flowchart of the system of the present utility model;

Fig. 6 is a schematic diagram of physical connection of the system of the present invention.

Detailed ways

The utility model will be further described in detail below in conjunction with the embodiments and accompanying drawings, but the implementation of the utility model is not limited thereto.

The system of the utility model is used to optimize the operation of the energy system of a papermaking enterprise in a cogeneration mode. The energy conversion link of the enterprise includes 4 fluidized bed boilers, 4 condensing steam turbines and a number of temperature and pressure reduction equipment. Tubular thermal system. The working method is as follows:

The first step, as shown in Figures 3 and 5, is to collect the data of each department from the SCADA, PLC, DCS and data acquisition equipment of the pulp and paper production line, thermoelectric workshop, water treatment workshop, office dormitory, canteen and other production and living assistance workshops. Energy related data. The obtained data is stored in the real-time database for calling by the relational database and the human-computer interaction interface. The relational database reads and stores the current energy consumption related data from the real-time database, and predicts the required energy according to the order scheduling plan and production maintenance plan input by the manual input port and stores relevant data for the simulation model library, optimization model library and customers terminal calls.

In the second step, the material flow simulation model library reads relevant data from the relational database for simulation calculation, stores the calculation results in the relational database and transmits them to the energy flow simulation model library; the energy flow simulation model library reads from the relational database Relevant data, combined with the calculation results of the material flow simulation model library to perform simulation calculations, store the calculation results in the relational database and transmit them to the energy flow optimization model library; the steam turbine system optimization model library in the energy flow optimization model library reads the energy flow Simulate the calculation results of the model library, and read the relevant data of the paper mill's related equipment operation status, order scheduling plan, and production maintenance plan from the relational database, and calculate the optimal operation of the steam turbine generator set to obtain the minimum power consumption required by the steam turbine system. The gas volume is stored in the relational database; the boiler optimization model library in the energy flow optimization model library calculates the minimum steam consumption required by the steam turbine system according to the steam turbine system optimization model library, so as to obtain the necessary steam production of the boiler system, and then As an external constraint on the boiler system, combined with the relevant data of the paper mill's related equipment operation status, order scheduling plan, and production maintenance plan in the relational database, the optimal operation calculation of the boiler unit is carried out, and the coal consumption required for the operation of the energy system is calculated. The minimum amount is the objective function, then call the eTMS program to solve it, and store the optimization result in the relational database;

Table 1 Comparison of steam turbine before and after optimization

Table 2 Comparison before and after boiler optimization

In the third step, the human-computer interaction interface reads relevant data from the real-time database and relational database through Ethernet, and displays the calculation results of the energy flow optimization model database, energy consumption, and key indicators of energy efficiency; the on-site monitoring system (SCADA, DCS, etc.) Relational database obtains optimization information. In AUTO mode, assign values to related settings to realize automatic optimization function. The optimization results are shown in Table 1 and Table 2. At the same time, a printer can be installed to print relevant information.

Through the above optimization, the steam turbine system needs 971.34t/h of steam for actual operation before optimization, and 895.87t/h after optimization, which is 75.47t/h less than the actual operation under the premise of meeting the steam and electric energy requirements of the papermaking process. The coal consumption of the boiler system has changed from 154.72t/h to 138.74t/h, which is 15.98t/h less than the actual operation.

The above-mentioned embodiment is a preferred implementation mode of the present utility model, but the implementation mode of the present utility model is not limited by the above-mentioned embodiment, and any changes, modifications, substitutions and combinations made without departing from the spirit and principle of the present utility model , simplification, all should be equivalent replacement methods, and are all included in the protection scope of the present utility model.

Claims (5)

1. A paper mill cogeneration energy system optimization system, characterized in that it comprises: A data acquisition system used to collect the demand data of various departments for steam and electric energy and store them in the real-time database; A real-time database for storing and transmitting data collected by the data acquisition system; A relational database for storing and transmitting data required for optimization and optimized result data; A material flow simulation model library used to simulate the material flow of the production process stored in the relational database and store the simulation results in the relational database; An energy flow simulation model library for simulating the energy flow data of the production process stored in the relational database combined with the simulation results of the material flow simulation model library and storing the simulation results in the relational database; The energy flow optimization model library used to optimize the energy flow in the production process according to the simulation results of the energy flow simulation model library and feed back relevant information to the human-computer interaction interface for display, monitoring and scheduling prompts; Human-computer interaction interface for production dispatchers to interact with real-time databases, relational databases and energy flow optimization model libraries; The data acquisition system is connected to the real-time database; the real-time database is connected to the relational database; the relational database is connected to the energy flow simulation model library, the material flow simulation model library and the human-computer interaction interface; the relational database is also connected to the input device operating state The data is connected to the manual input port of production planning information; the material flow simulation model library is connected to the energy flow simulation model library; the energy flow simulation model library is connected to the energy flow optimization model library; the energy flow optimization model library is connected to human-computer interaction The interfaces are connected with each other; the human-computer interaction interface is also connected with the real-time database. 2. The paper mill cogeneration energy system optimization system according to claim 1, characterized in that, the data acquisition system includes SCADA, PLC and DCS systems and data acquisition instruments arranged in production and life assistance workshops. 3. The paper mill cogeneration energy system optimization system according to claim 1, wherein the energy flow optimization model library includes: The steam turbine system optimization model library of the steam turbine system energy optimization scheme is obtained by establishing an optimization model for the steam turbine system and solving it; Boiler system optimization model library for boiler system energy optimization scheme obtained by establishing an optimization model for the boiler system and solving it; The output of the steam turbine system optimization model library is connected to the input of the boiler system optimization model library. 4. The paper mill cogeneration energy system optimization system according to claim 1, characterized in that, the human-computer interaction interface includes a PC installed in the boiler unit workshop, a PC installed in the steam turbine workshop, and a paper mill PC in the central control room. 5. The paper mill cogeneration energy system optimization system according to claim 1, characterized in that, the real-time database collects relevant data from the data acquisition system via Ethernet and stores them.

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