CN114050570B - Collaborative regulation and control method and device for source network charge storage system - Google Patents

Abstract

The invention relates to a cooperative regulation and control method and a device for a source network charge storage system, wherein the source network charge storage system comprises new energy power generation equipment, traditional power generation equipment and energy storage equipment, and the method comprises the following steps: acquiring key meteorological parameters of the numerical weather forecast; calculating the similarity between the key meteorological parameters and the typical normal curve, and determining the system operation mode in a first preset time in the future according to the similarity; and performing daily control, intra-daily control and real-time control on the system according to the determined system operation mode, and solving the stability problem of the novel power system containing high-proportion renewable energy sources.

Description

A method and device for coordinated control of source-grid-load-storage system

Technical field

The present invention relates to the technical field of power system control, and in particular to a method and device for coordinated control of a source-grid-load-storage system.

Background technique

In the future, the energy landscape will transform to a clean-dominated, electricity-centered one. Then, a new power system based on electric energy, with multiple energy sources, supply and consumption coordination, will become a trend. In new power systems that contain a high proportion of renewable energy, power generation from renewable energy sources such as wind and solar is greatly affected by meteorological factors. The randomness and volatility of power generation have a greater impact on the power quality and safe and stable operation of the power grid. Through the coordinated interaction of source, grid, load and storage within a power system containing a high proportion of renewable energy, it can not only ensure the stable operation of the power grid, but also improve the new energy consumption capacity, reduce wind and solar power abandonment, reduce the system's new energy external demand capacity, and delay Investment in power grid infrastructure construction, while guiding users to transfer their electricity load from peak hours to low hours through the "demand side response" mechanism and real-time two-way interaction with users.

Contents of the invention

Based on the above situation of the prior art, the purpose of the present invention is to provide a source-grid-load-storage system collaborative control method and device to solve the stability problem of a new power system containing a high proportion of renewable energy.

In order to achieve the above object, according to one aspect of the present invention, a method for coordinated regulation of a source grid load storage system is provided. The source grid load storage system includes new energy power generation equipment, traditional power generation equipment and energy storage equipment. The method includes :

Obtain key meteorological parameters for numerical weather forecasting;

Calculate the similarity between the key meteorological parameters and the typical normal curve, and determine the system operation mode within the first predetermined time in the future based on the similarity;

Perform day-ahead control, intra-day control and real-time control on the system according to the determined system operation mode.

Further, the following formula is used to calculate the similarity between the key meteorological parameters and the typical normal daily curve:

Among them, x _i = [x _i (1), x _i (2)] is the vector composed of irradiance and wind speed in the numerical weather forecast on the forecast day; ξ _i (k) is the difference between the curve x _i on the forecast day and the typical The similarity coefficient of the daily radiation value at the k-th sampling point; |x ₀ (k) _-xi (k)|=Δx _i (k) is the absolute difference between x ₀ and _xi at the k-th sampling point;

It is the first-level minimum difference, which means finding the minimum difference between a point on the curve x _i and x ₀ ; It is the second level minimum difference, which means that based on the minimum difference found in each curve, press i=1,2,... to find the minimum difference of all curves;/> is the second-level maximum difference, which means based on the maximum difference found in each curve, then press i=1,2,... to find the maximum difference of all curves; ρ is the maximum difference coefficient;

r _i is the similarity between the predicted day and the i-th typical normal day, and m represents the similarity coefficient of m sampling points on the comprehensive curve to obtain the similarity;

If the similarity r _i ≥0.8, it is determined to be the normal operating mode;

If the similarity r _i <0.8, the emergency operation mode is determined.

Furthermore, under normal operation of the system, day-ahead controls include:

Set the demand side load to the peak and valley electricity price mode;

Obtain the energy storage charging and discharging power day-ahead planning curve, the new energy power generation day-ahead planning curve and the traditional power supply day-ahead planning curve, and control according to the curves;

Intraday controls include:

Obtain the energy storage peak-shaving and valley-filling charging and discharging power intraday planning curve, the traditional power supply intraday planning curve and the new energy power generation intraday planning curve, and control according to the curves.

Further, obtain the energy storage charging and discharging power day-ahead planning curve through the following steps:

Calculate the new energy generation power deficit corresponding to each time interval i within the second predetermined time;

Sort the calculated power deficits from large to small, and select the energy storage and discharge time interval i in order;

Determine whether the new energy generation power deficit reaches the preset energy storage capacity in the selected energy storage discharge time interval i; if so, proceed to the next step; if not, then i=i+1 and return to the previous step;

The energy storage charge and discharge power day-ahead planning curve is obtained according to the following formula:

P _stori =(P _Loadi-Geni >P _stormax )? P _stormax :P _Loadi-Geni

Among them, P _stori is the single point energy storage charging and discharging power in the day-ahead planning curve of energy storage charging and discharging power, P _Loadi-Geni is the difference between the load prediction value of the i-th hour and the new energy equipment power generation prediction value, and P _stormax is the energy storage Maximum charge and discharge power. The load forecast value and the new energy equipment power generation forecast value are obtained through the known load forecast curve and the new energy equipment power generation forecast curve. The value of i is the time interval in which the new energy power generation power deficit reaches the preset energy storage capacity.

Further, the energy storage peak-shaving and valley-filling charge and discharge power intraday planning curve is obtained through the following steps:

Calculate the power deficit at the third predetermined time in the future based on the new energy power generation intraday planning curve and the known load forecast curve;

Determine whether the power deficit reaches the preset charging and discharging power; if so, obtain the energy storage peak-shaving and valley-filling charging and discharging power daily plan curve; if not, adjust according to the new energy power generation intra-day planning curve to obtain the energy storage peak-shaving and filling power. Valley charge and discharge power intraday planning curve.

Further, in the system emergency operation mode, the day-ahead control includes:

Set the demand side load to the full peak price mode;

Obtain the day-ahead planning curve of new energy power generation and the day-ahead planning curve of traditional power supply, and control according to the curves;

Intraday controls include:

Obtain energy storage to suppress new energy fluctuation charging and discharging power intraday planning curve, traditional power supply intraday planning curve and new energy power generation intraday planning curve, and control according to the curves.

Further, according to the following steps, obtain the daily planning curve of energy storage to suppress the fluctuation of new energy charging and discharging power and the daily planning curve of new energy power generation:

Calculate the fluctuation change rate of the new energy equipment at each predetermined time interval in the fourth predetermined time in the future;

Determine whether each fluctuation change rate meets the preset change rate threshold; if so, perform energy storage SOC maintenance based on whether the energy storage SOC meets the stability margin, and obtain the new energy power generation daily planning curve; if not, proceed to the next step;

According to the capacity of the energy storage equipment, the daily planning curve of energy storage to suppress the fluctuation of new energy charging and discharging power at each moment is formulated;

Determine whether the total change rate of energy storage equipment and new energy equipment meets the stable operation requirements of the system; if so, obtain the new energy power generation intraday planning curve; if not, limit the power generation of new energy equipment and obtain the new energy power generation intraday planning curve.

Further, in the system's normal operation mode or emergency operation mode, real-time control includes:

Based on intraday control, corrections are made based on the operating status and operating constraints of the system.

According to the second aspect of the present invention, a source-grid-load-storage system collaborative control device is provided, including a key meteorological parameter acquisition module, a similarity calculation module, a system operation mode determination module, and a control module;

The key meteorological parameter acquisition module is used to obtain key meteorological parameters for numerical weather forecasting;

The similarity calculation module is used to calculate the similarity between the key meteorological parameters and typical normal curves;

The system operation mode determination module is used to determine the system operation mode within a predetermined time in the future based on the similarity;

The control module is used to perform day-ahead control, intra-day control and real-time control of the system according to the determined system operation mode.

According to a third aspect of the present invention, a storage medium is provided. The storage medium stores a computer program. When the computer program is executed by a processor, the method as described in the first aspect of the present invention is implemented.

To sum up, the present invention provides a method and device for coordinated regulation of a source-grid-load-storage system. The source-grid-load-storage system includes new energy power generation equipment, traditional power generation equipment and energy storage equipment. The method includes the steps of: obtaining Key meteorological parameters of numerical weather forecasting; calculate the similarity between the key meteorological parameters and typical normal curves, and determine the system operation mode within the first predetermined time in the future based on the similarity; perform the system operation according to the determined system operation mode Day-ahead control, intra-day control and real-time control solve the stability problem of new power systems containing a high proportion of renewable energy.

Description of drawings

Figure 1 is a flow chart of a source-grid-load-storage system collaborative control method according to an embodiment of the present invention;

Figure 2 is a flow chart of day-ahead control, intra-day control and real-time control in the normal operation mode of the system;

Figure 3 is a flow chart for obtaining the day-ahead planning curve of energy storage charging and discharging power;

Figure 4 is a flow chart for obtaining the daily planning curve of energy storage peak-shaving and valley-filling charging and discharging power;

Figure 5 is a flow chart of day-ahead control, intra-day control and real-time control in the system emergency operation mode;

Figure 6 is a flow chart for obtaining the daily planning curve of energy storage peak-shaving and valley-filling charging and discharging power.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the specific embodiments and the accompanying drawings. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. Furthermore, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily confusing the concepts of the present invention.

The technical solution of the present invention will be described in detail below with reference to the accompanying drawings. According to an embodiment of the present invention, a coordinated control method for a source grid load storage system is provided. The source grid load storage system includes new energy power generation equipment, traditional power generation equipment and energy storage equipment. The control method is based on weather prediction. Determine the power generation fluctuations of the system's new energy equipment during the future control period. The power generation fluctuations determine the control objectives and control strategies. Different control objectives and control strategies are determined by the operation mode of the system. The flow chart of this method is shown in Figure 1. The method includes the following steps:

S1. Obtain key meteorological parameters for numerical weather forecasting. The fluctuations of key meteorological parameters in numerical weather forecasting are used to map the fluctuations of new energy power generation in the control area and determine the system operation mode within the first predetermined time in the future (for example, 1-3 days). You can choose to have numerical weather forecasts updated daily for the next 3 days with a time resolution of 15 minutes.

S2. Calculate the similarity between the key meteorological parameters and the typical normal curve, and determine the system operation mode within the first predetermined time in the future based on the similarity. The system operation mode is divided into regular operation mode and emergency operation mode according to the different control objectives of the source network, load and storage. Under different operating modes, the control objectives of source-grid-load-storage coordinated regulation of source, grid, load and storage are different for day-ahead, intra-day and real-time control:

Under normal operating mode, the daily curves of key meteorological parameters such as solar irradiance and wind speed are similar to typical normal daily meteorological curves. It has normal power generation capacity and small fluctuations without affecting the stability of the power grid. The goal of coordinated regulation of source, grid, load and storage is to rationally arrange energy storage. The power station's charging and discharging plan and the use of load peak and valley electricity prices guide users to use electricity in an orderly manner to achieve peak shaving and valley filling of new energy, reduce wind and solar abandonment, and increase the proportion of new energy power generation in the system.

In emergency operation mode, key meteorological parameters such as solar irradiance and wind speed have poor correlation with typical normal daily weather curves and fluctuate greatly. The goal of coordinated regulation of source, grid, load and storage is to ensure stable operation of the power grid. The combination of energy storage and new energy is used to suppress the fluctuation of new energy output. In addition, the full-peak electricity price model of the "demand side response" mechanism needs to be used to guide users to reduce electricity consumption to offset the power shortage after suppressing the output of new energy.

In this embodiment, the grayscale method is used to calculate the similarity. The following formula can be used to calculate the similarity between the key meteorological parameters and the typical normal daily curve:

Among them, x _i = [x _i (1), x _i (2)] is the vector composed of irradiance and wind speed in the numerical weather forecast on the forecast day; ξ _i (k) is the difference between the curve x _i on the forecast day and the typical The similarity coefficient of the daily radiation value at the k-th sampling point; |x ₀ (k) _-xi (k)|=Δx _i (k) is the absolute difference between x ₀ and _xi at the k-th sampling point;

It is the first-level minimum difference, which means finding the minimum difference between a point on the curve x _i and x ₀ ; It is the second level minimum difference, which means that based on the minimum difference found in each curve, press i=1,2,... to find the minimum difference of all curves;/> is the second-level maximum difference, which represents the maximum difference found in each curve, and then press i=1,2,... to find the maximum difference of all curves; ρ is the maximum difference coefficient, and the value in this embodiment is 0.5 .

r _i is the similarity between the predicted day and the i-th typical normal day, and m represents the similarity coefficient of m sampling points on the comprehensive curve to obtain the similarity.

If the similarity r _i ≥0.8, it is determined to be the normal operating mode;

If the similarity r _i <0.8, the emergency operation mode is determined.

The typical normal daily curve can be maintained manually, or can be automatically added by on-site operation historical data. After ensuring that the system operates stably in normal operation mode on that day, the system will transfer the key meteorological parameter curves of that day as the typical normal daily curve. Meteorological curve library.

Based on numerical weather forecasts, as well as historical new energy generation power and historical load power, power generation and load forecasting are obtained, such as ultra-short-term 15-minute rolling updates for the next 1 to 4 hours and short-term daily updates for the next 1 to 3 days. The time resolution is 15-minute power generation forecast and load forecast. The load prediction curve and the new energy equipment power generation prediction curve are only used as input data for the control method in this embodiment and will not be described in detail.

S3. Perform day-ahead control, intra-day control and real-time control on the system according to the determined system operation mode. The above control methods are described in detail below.

In the normal operation mode of the system, the flow chart of day-ahead control, intra-day control and real-time control is shown in Figure 2. In the normal operation mode of the system, day-ahead controls include:

Set the demand side load to the peak and valley electricity price mode;

Obtain the energy storage charging and discharging power day-ahead planning curve, the new energy power generation day-ahead planning curve and the traditional power supply day-ahead planning curve, and control according to the curves.

For day-ahead control in normal operation mode, first set the demand side load to the peak and valley electricity price mode. Based on the day-ahead load forecast that takes into account peak and valley electricity prices, the total electricity demand P _Load daily curve in the next 24 hours is obtained (the daily curve is 96 points a day, 15-minute resolution). Based on the results of power generation prediction and load prediction of new energy equipment in the system, the system power deficit P _Load-Gen daily curve is obtained. The optimization goal of energy storage in normal mode is peak shaving and valley filling of the system.

Among them, the new energy power generation day-ahead planning curve and the traditional power supply day-ahead planning curve can be obtained using conventional curve acquisition methods, which will not be described again here. In this embodiment, the energy storage charging and discharging power day-ahead planning curve is obtained through the following steps. The flow chart for obtaining the energy storage charging and discharging power day-ahead planning curve is shown in Figure 3:

S11. Calculate the new energy power generation deficit corresponding to each time interval i within the second predetermined time. When the second predetermined time is, for example, 24 hours, the value of i is 0-96, and the time resolution is 15 minutes. According to the following formula calculate:

P _Load i _-Geni +P _Load i _+1-Geni+1 +P _Load i _+2-Geni+2 +P _Load i _+3-Geni+3

P _Load i _-Geni , P _Load i _+1-Geni+1 , P _Load i _+2-Geni+2 , and P _Load i _+3-Geni+3 represent the load prediction value of each new energy equipment minus the new energy power generation value. There is a shortage of new energy power generation.

S12. Sort the calculated power deficits from large to small, and select the energy storage discharge time interval i in order;

S13. Determine whether the new energy generation power deficit reaches the preset energy storage capacity in the selected energy storage and discharge time interval i. The preset energy storage capacity is, for example, 60% of the energy storage capacity; if so, proceed to the next step; If not, then i=i+1 and return to the previous step;

S14. Obtain the energy storage charge and discharge power day-ahead planning curve according to the following formula:

P _stori =(P _Loadi-Geni >P _stormax )? P _stormax :P _Loadi-Geni

Among them, P _stori is the single point energy storage charging and discharging power in the day-ahead planning curve of energy storage charging and discharging power, P _Loadi-Geni is the difference between the load prediction value of the i-th hour and the new energy equipment power generation prediction value, P _stormax is... , the load prediction value and the new energy equipment power generation prediction value are obtained through the known load prediction curve and the new energy equipment power generation prediction curve. The value of i is the time interval in which the new energy power generation power deficit reaches the preset energy storage capacity. The new energy power generation plan is to calculate the new energy surplus when P _{Gen+stor-Load} > 0 and whether it meets the limit of the regional power grid's external power transmission. If it exceeds the limit, the new energy output will be limited. When the system has traditional power equipment and new energy equipment cannot meet the power demand in the area, P _{Gen+stor-Load} <0, calculate the power generation shortage and reserve situation in the system, and formulate a start-up and shutdown plan for the traditional power supply.

S15. Sort the calculated power deficits from small to large, and select the energy storage discharge time interval i in sequence;

S16. Determine whether the new energy power generation deficit in the selected energy storage discharge time interval i reaches the preset energy storage capacity. The preset energy storage capacity is, for example, 60% of the energy storage capacity. If so, obtain the storage capacity according to the above formula. Can charge and discharge power day-ahead planning curve; if not, if not, then i=i+1, and return to the previous step.

Under normal operation of the system, intraday controls include:

Obtain the energy storage peak-shaving and valley-filling charging and discharging power intraday planning curve, the traditional power supply intraday planning curve and the new energy power generation intraday planning curve, and control according to the curves.

Among them, the traditional power supply intraday planning curve and the new energy power generation intraday planning curve can be obtained using conventional curve acquisition methods, which will not be described again here. In this embodiment, the following steps are used to obtain the daily planning curve of the energy storage peak-shaving and valley-filling charge and discharge power. The flow chart of obtaining the daily planning curve of the energy storage peak-shaving and valley-filling charge and discharge power is as shown in Figure 4:

S21. Calculate the power deficit for the third predetermined time in the future based on the new energy power generation intraday planning curve and the known load prediction curve. In this embodiment, the third predetermined time is 4 hours;

S22. Determine whether the power shortage reaches the preset charging and discharging power; if so, obtain the energy storage peak-shaving and valley-filling charging and discharging power intraday planning curve; if not, adjust according to the new energy power generation intraday planning curve to obtain the energy storage clipping. Peak-filling and valley-filling charge and discharge power intra-day planning curve, that is, if the power shortage reaches the preset charging and discharging power, the energy storage peak-filling and valley-filling charging and discharging power intra-day planning curve is directly used for control. If it is not reached, the new energy power generation intra-day planning curve is used. Take control.

In the system emergency operation mode, the flow chart of day-ahead control, intra-day control and real-time control is shown in Figure 5. In system emergency operation mode, day-ahead controls include:

Set the demand side load to the full peak price mode;

Obtain the new energy power generation day-ahead planning curve and the traditional power supply day-ahead planning curve, and control based on the curves.

In the emergency operation mode of the system, first set the demand side load to the full peak price mode. Based on the day-ahead load forecast that considers the full-peak mode electricity price, the total electricity demand P _Load daily curve in the next 24 hours is obtained. The optimization goal of energy storage in emergency mode is the stability of the system. Therefore, the use of energy storage for peak-shaving and valley-filling optimization is no longer considered in the day-to-day plan, and the day-to-day plan for energy storage is no longer developed. Therefore, it is only necessary to formulate new energy generation plans and traditional power supply start-up and stop plans based on the total power demand P _Load , system backup demand, and external power limit. Based on the results of the day-ahead new energy power generation forecast in the region, the system's new energy fluctuation ΔP _Gt /Δt curve for the next 4 hours is obtained. The optimization goal of energy storage in emergency mode is the stability of the system. Therefore, the daily curve formulation process and algorithm of the energy storage day-ahead charge and discharge plan are as follows:

max|(ΔP _Gi +ΔP _stori )/Δt|<max(ΔP/Δt)

Among them, ΔP _Gi is the Δt interval change value of new energy equipment power generation at time i, ΔP _stori is the Δt interval change value of energy storage equipment at i time, and Δt is the interval time, which is configurable. The point where the power fluctuation of all new energy sources exceeds the limit exceeds the limit by adding energy storage to make the fluctuation meet the system's 15-minute maximum fluctuation change rate requirement. When the fluctuation of new energy meets the requirements, the charging and discharging SOC maintenance of the energy storage power station must be carried out according to the energy storage SOC situation and system operation status, so that the state of charge SOC of the energy storage power station is between 60% and 70%, which is the basis for subsequent systems. Keep enough in case of fluctuations.

In system emergency operation mode, intraday controls include:

Obtain energy storage to suppress new energy fluctuation charging and discharging power intraday planning curve, traditional power supply intraday planning curve and new energy power generation intraday planning curve, and control according to the curves.

Among them, the traditional power supply intraday planning curve and the new energy power generation intraday planning curve can be obtained using conventional curve acquisition methods, which will not be described again here. In this embodiment, the energy storage peak-shaving and valley-filling charge and discharge power intraday planning curve is obtained through the following steps. The flow chart of obtaining the energy storage peak-shaving and valley-filling charge and discharge power intraday planning curve is shown in Figure 6:

S31. Calculate the fluctuation change rate of the new energy equipment at each predetermined time interval in the fourth predetermined time in the future. The fluctuation change rate is ΔP _Gt /Δt, and ΔP _Gt is the change value of the new energy equipment Δt time interval;

S32. Determine whether each fluctuation change rate meets the preset change rate threshold; if so, perform energy storage SOC maintenance based on whether the energy storage SOC meets the stability margin, and obtain the new energy power generation daily planning curve; if not, proceed to the next step. step;

S33. According to the capacity of the energy storage equipment, formulate the daily planning curve of the energy storage to suppress the fluctuation of new energy charging and discharging power at each moment;

S34. Determine whether the total change rate of energy storage equipment and new energy equipment meets the stable operation requirements of the system; if so, obtain the daily planning curve of new energy power generation; if not, obtain the daily planning curve of new energy power generation after limiting the power generation of new energy equipment. .

In the system's normal operation mode or emergency operation mode, real-time control includes:

Based on intraday control, corrections are made based on the operating status and operating constraints of the system. In emergency mode, real-time control is modified based on the intraday plan combined with the current system operating status and operating constraints. The specific corrections are the same as in normal operation mode, but the constraints increase the operating constraints on the 1 to 5 minute change rate of new energy equipment.

Among them, the operational constraints involved include the following aspects:

System stable operation constraints:

1) System external power constraints:

2) Operation constraints of N-1 transformers in the system.

Energy storage equipment operating constraints include:

1)P _char，max ≤P _bess (t)≤0

2)0≤P _bess (t)≤P _dis,max

3)SOC _min ≤ SOC _bess (t) ≤ SOC _max

4)P _ess (t)*Δt+E _cur (t)≤SOC _max *CAP

Among them, P _{char, max} is the maximum charging power of the energy storage device, P _{dis, max} is the maximum discharge power of the energy storage device, SOC _min is the minimum state of charge of the energy storage device, SOC _max is the maximum state of charge of the energy storage device, P _bess ( t) is the real-time planned power value of the energy storage device at time t during the day, SOC _bess (t) is the state of charge of the energy storage device at time t, E _cur (t) is the remaining power of the energy storage device at time t, and CAP is the rated capacity of the energy storage device. , Δt is the real-time planning time resolution of the energy storage device.

New energy equipment operation constraints:

P _min ≤ P _gen (t) ≤ P _max

P _min and P _max are the minimum and maximum power generation capabilities of new energy equipment respectively.

New energy climbing restrictions

According to the second embodiment of the present invention, a source-grid-load-storage system collaborative control device is provided, including a key meteorological parameter acquisition module, a similarity calculation module, a system operation mode determination module, and a control module;

The key meteorological parameter acquisition module is used to obtain key meteorological parameters for numerical weather forecasting;

The similarity calculation module is used to calculate the similarity between the key meteorological parameters and typical normal curves;

The system operation mode determination module is used to determine the system operation mode within a predetermined time in the future based on the similarity;

The control module is used to perform day-ahead control, intra-day control and real-time control of the system according to the determined system operation mode.

The specific process of each module in the device realizing its function is the same as the steps of the fault location method in the first embodiment provided by the present invention, and will not be described again here.

According to a third embodiment of the present invention, a storage medium is provided. The storage medium stores a computer program. When the computer program is executed by a processor, the method as described in the first embodiment of the present invention is implemented.

To sum up, the present invention relates to a method and device for coordinated control of a source-grid-load-storage system. The source-grid-load-storage system includes new energy power generation equipment, traditional power generation equipment and energy storage equipment. The method includes the steps of: obtaining a numerical value. Key meteorological parameters of weather forecast; calculate the similarity between the key meteorological parameters and typical normal curves, and determine the system operation mode within the first predetermined time in the future based on the similarity; perform day-to-day inspection of the system based on the determined system operation mode control, intraday control and real-time control to solve the stability problem of new power systems containing a high proportion of renewable energy.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for implementing the functions specified in one process or processes of the flowchart and/or one block or blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and do not limit the scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: Those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation modes of the invention after reading the present invention, but these changes, modifications or equivalent substitutions are within the protection scope of the pending claims of the invention.

Claims (8)

1. The utility model provides a source net lotus stores up system cooperation regulation and control method, source net lotus stores up system includes new energy power generation facility, traditional power generation facility and energy storage equipment, and its characterized in that, this method includes:

acquiring key meteorological parameters of the numerical weather forecast;

calculating the similarity between the key meteorological parameters and the typical normal curve, and determining the system operation mode in a first preset time in the future according to the similarity;

performing daily control, intra-daily control and real-time control on the system according to the determined system operation mode;

the similarity between the key meteorological parameters and a typical normal day curve is calculated by adopting the following formula:

wherein,the method comprises the steps of (1) predicting a vector formed by irradiance and wind speed in numerical weather forecast of the day; />To predict day of day curve +.>Is at +.>Similarity coefficients of the sampling points; />Is->Sampling Point->And->Is the absolute difference of (2);

for the first order minimum difference, the curve +.>Go up to find a point and a break>Is the smallest difference of (2); />For the second-stage minimum difference, the minimum difference found in each curve is expressed, and the sum is calculated according to +.>=1, 2, … finds the smallest difference of all curves; />For the second-order maximum difference, the maximum difference found in each curve is expressed, and the sum is expressed as +.>=1, 2, … finds the maximum difference for all curves; />Is the maximum difference coefficient;

to predict day and->Similarity of typical normal days, +.>Representing +.>Similarity coefficients of the sampling points to obtain the similarity;

if the similarity isDetermining a normal operation mode;

if the similarity isDetermining an emergency operation mode;

the method comprises the following steps of obtaining an energy storage peak clipping, valley filling and discharging power daily planning curve:

calculating the power shortage of a third preset time in the future according to the new energy power generation daily planning curve and the known load prediction curve;

judging whether the power shortage reaches preset charging and discharging power or not; if yes, obtaining an energy storage peak clipping and valley filling charging and discharging power daily planning curve; and if not, adjusting according to the new energy power generation daily planned curve to obtain the energy storage peak clipping and valley filling charging and discharging power daily planned curve.

2. The method of claim 1, wherein, in normal operation of the system, the day-ahead control comprises:

setting a load on a demand side as a peak-valley electricity price mode;

acquiring an energy storage charging and discharging power day-ahead planning curve, a new energy power generation day-ahead planning curve and a traditional power supply day-ahead planning curve, and controlling according to the curves;

the intra-day control includes:

and acquiring an energy storage peak clipping and valley filling charging and discharging power daily planning curve, a traditional power daily planning curve and a new energy power generation daily planning curve, and controlling according to the curves.

3. The method of claim 2, wherein the stored charge-discharge power pre-day schedule curve is obtained by:

calculating each time interval within the second predetermined timeCorresponding new energy generated power is absent;

sequencing the calculated power deficiency according to the order from big to small, and sequentially selecting the energy storage discharge time interval；

Judging the energy storage discharge time interval selectedWhether the new energy generated power shortage reaches a preset energy storage capacity or not; if yes, the next step is carried out; if no, then->And returning to the previous step;

and obtaining an energy storage charging and discharging power day-ahead planning curve according to the following formula:

wherein,for the single-point energy storage charging and discharging power in the planned curve before the energy storage charging and discharging power day, +.>Is->Difference between load predicted value and new energy equipment power generation predicted value for each hour, +.>The maximum charge and discharge power of the stored energy; the load predicted value and the new energy equipment power generation predicted value are obtained through a known load predicted curve and a new energy equipment power generation predicted curve, < >>The value of (2) is a time interval for enabling the shortage of the generated power of the new energy to reach the preset energy storage capacity.

4. The method of claim 1, wherein the day-ahead control in the emergency mode of operation of the system comprises:

setting the load on the demand side as a full peak price mode;

acquiring a new energy power generation day-ahead planning curve and a traditional power supply day-ahead planning curve, and controlling according to the curves;

the intra-day control includes:

and acquiring an energy storage inhibition new energy fluctuation charge and discharge power daily planning curve, a traditional power daily planning curve and a new energy generation daily planning curve, and controlling according to the curves.

5. The method according to claim 4, wherein the energy storage inhibition new energy fluctuation charge-discharge power intra-day planning curve and the new energy generation intra-day planning curve are obtained according to the steps of:

calculating the fluctuation change rate of each preset time interval in a fourth preset time in the future of the new energy equipment;

judging whether each fluctuation change rate meets a preset change rate threshold value or not; if yes, after maintaining the energy storage SOC according to whether the energy storage SOC meets the stability margin, obtaining a new energy power generation daily planned curve; if not, the next step is carried out;

an intra-day planning curve of the fluctuation charge and discharge power of the new energy is formulated according to the capacity of the energy storage equipment;

judging whether the total change rate of the energy storage equipment and the new energy equipment meets the requirement of stable operation of the system or not; if yes, obtaining a new energy power generation daily planning curve; if not, limiting the new energy equipment to generate electricity, and obtaining a new energy generation daily planned curve.

6. The method according to any one of claims 1-5, wherein the real-time control comprises, in normal operation mode or emergency operation mode of the system:

and (3) correcting the operation state and the operation constraint of the system on the basis of the daily control.

7. A source network charge storage system cooperative regulation and control device, wherein the regulation and control device regulates and controls by using the source network charge storage system cooperative regulation and control method according to any one of claims 1-6, and the device is characterized by comprising a key meteorological parameter acquisition module, a similarity calculation module, a system operation mode determination module and a control module;

the key weather parameter acquisition module is used for acquiring key weather parameters of the numerical weather forecast;

the similarity calculation module is used for calculating the similarity between the key meteorological parameters and the typical normal curve;

the system operation mode determining module is used for determining the system operation mode in the future preset time according to the similarity;

and the control module is used for performing daily front control, daily inner control and real-time control on the system according to the determined system operation mode.

8. A storage medium storing a computer program which, when executed by a processor, implements the method of any one of claims 1-6.