Capacity configuration optimization system for power grid side energy storage system

Abstract

The invention relates to the technical field of energy storage system capacity configuration, and particularly discloses a power grid side energy storage system capacity configuration optimization system, which comprises a power grid operation characteristic analysis unit, an energy storage system characteristic analysis unit, a capacity configuration judgment and adjustment unit, a capacity configuration adjustment verification module, a capacity configuration optimization and adjustment module and an early warning terminal. A power grid running state and a power grid side energy storage system running state are monitored and analyzed, a power grid running stability type feedback judgment signal and an energy storage system running state feedback type judgment signal are generated, power grid side energy storage system capacity expansion adjustment operation is carried out accordingly, and finally an adjustment result is verified and optimized and adjusted again. According to the method, the negative influence caused by blind capacity expansion or improper configuration is avoided, the operation reliability, stability and economical efficiency of the power grid are comprehensively improved, and a solid technical support is provided for sustainable development of the intelligent power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage system capacity configuration, and specifically to an optimization system for grid-side energy storage system capacity configuration. Background Art

[0002] With the large-scale grid connection of renewable energy and the rapid development of the power market, the stable operation and efficient dispatching of the power grid are facing unprecedented challenges. Therefore, as a key means to balance supply and demand and optimize resource allocation, the capacity configuration of the grid-side energy storage system has become increasingly prominent and has become an indispensable part to ensure the safe, reliable and economic operation of the power grid.

[0003] Traditional methods for grid-side energy storage system capacity configuration mostly adopt static analysis or simple rule matching, which are difficult to adapt to the complex and changeable characteristics of the power grid operation state, resulting in deviations in the capacity configuration results of the energy storage system and affecting the stable operation and economic benefits of the power grid.

[0004] With the rapid access of renewable energy, the load volatility of the power grid increases, and higher requirements are imposed on the peak shaving and frequency modulation capabilities of the energy storage system. At the same time, the characteristics of the energy storage system itself, such as charge and discharge efficiency, response degree, etc., will also affect the capacity configuration. Existing technologies generally lack a comprehensive evaluation of the power grid operation stability and the characteristics of the energy storage system itself, and it is difficult to achieve precise optimization of the energy storage system capacity configuration.

[0005] In order to solve the above defects, a technical solution is provided now. Summary of the Invention

[0006] The purpose of the present invention is to provide an optimization system for grid-side energy storage system capacity configuration to solve the problems raised in the above background.

[0007] The purpose of the present invention can be achieved by the following technical solutions: An optimization system for grid-side energy storage system capacity configuration includes a server: The server is communicatively connected to a data acquisition unit, a power grid operation characteristic analysis unit, an energy storage system characteristic analysis unit, a capacity configuration determination and adjustment unit, a capacity configuration adjustment verification module, a capacity configuration optimization adjustment module, and an early warning terminal.

[0008] The data acquisition unit is used to collect power grid operation characteristic parameter information and target grid-side energy storage system own characteristic parameter information, and send them to the power grid operation characteristic analysis unit and the energy storage system characteristic analysis unit respectively through the server;

[0009] The power grid operation characteristic analysis unit is used to receive the power grid operation characteristic parameter information, perform power grid operation characteristic determination and analysis processing, generate feedback signals such as low power grid operation stability, medium power grid operation stability, and high power grid operation stability accordingly, and send them all to the capacity configuration determination and adjustment unit;

[0010] The energy storage system characteristic analysis unit is used to receive the information of the characteristic parameters of the target grid-side energy storage system, and perform the analysis and processing of the energy storage system characteristics determination. Accordingly, the low-efficiency operation feedback signal and the high-efficiency operation feedback signal of the energy storage system are generated, and both are sent to the capacity configuration determination and adjustment unit;

[0011] The capacity configuration determination and adjustment unit is used to receive the grid operation stability feedback type determination signal and the energy storage system operation feedback type determination signal and perform the comprehensive data analysis and processing. Accordingly, the low-level capacity configuration requirement determination signal, the intermediate-level capacity configuration requirement determination signal, and the high-level capacity configuration requirement determination signal are generated, and the corresponding adjustment operations are performed according to the corresponding capacity configuration requirement type determination signals;

[0012] The capacity configuration adjustment verification module is used to extract the grid operation parameters of the adjusted capacity configuration on the target grid-side energy storage system for analysis, and thus obtain the comprehensive efficiency evaluation coefficient of the target grid-side energy storage system after the capacity configuration adjustment. Accordingly, the verification analysis of the capacity configuration optimization adjustment plan is performed, and thus the capacity configuration pass signal and the capacity configuration fail signal are obtained;

[0013] The capacity configuration optimization adjustment module is used to receive the capacity configuration fail signal, and perform the re-optimization adjustment operation accordingly. Thus, the re-adjustment signal and the warning reminder signal are generated. The corresponding adjustment operation is performed according to the generated re-adjustment signal. Then, the grid operation parameters of the adjusted energy storage system capacity configuration are extracted again and the operation of the capacity configuration adjustment verification module is repeated. If the capacity configuration passes, the optimization end signal is generated. If the capacity configuration fail signal is generated, the warning reminder signal is generated and sent to the warning terminal for warning operation.

[0014] Further, the specific implementation steps of the grid operation characteristic determination and analysis processing are as follows:

[0015] Obtain the loads at each time point within the unit time period from the grid operation characteristic parameter information. Taking each time point as the abscissa and the load as the ordinate, draw the load curve within the unit time period, and extract the maximum load and the minimum load from it, and mark them respectively as At the same time, calculate the average value of the loads at each time point within the unit time period to obtain the average load, denoted as According to the formula Calculate the grid load peak-valley difference index within the unit time period ;

[0016] Extract the loads at each time point from the load curve within the unit time period, and mark them as , where i represents the number of each time point, i = 1, 2,...., m, and m represents the total number of time point numbers. According to the formula Calculate the standard deviation index of power grid load fluctuation within a unit time period ;

[0017] Extract the loads at two adjacent time points from the load curve within a unit time period, calculate the difference between the loads at two adjacent time points to obtain the load difference between two adjacent time points, and at the same time extract the interval duration corresponding to two adjacent time points. Calculate the ratio of the load difference between two adjacent time points to the interval duration corresponding to two adjacent time points to obtain the load change rate between two adjacent time points. Thus, statistically obtain the load change rates between each two adjacent time points within a unit time period as the load change rates within a unit time period;

[0018] Compare the load change rates within a unit time period with the set reference load change rate threshold. When a certain load change rate within a unit time period is greater than the set reference load change rate threshold, mark this load change rate as an abnormal value, otherwise mark it as a normal value. Thus, statistically obtain the number of normal values and the number of abnormal values of the load change rate within a unit time period, respectively marked as ;

[0019] According to the formula Calculate the power grid load fluctuation coefficient within the set monitoring time period , respectively represent the set reference load peak-valley difference index and reference load fluctuation standard deviation index, and a1, a2, a3, and a4 respectively represent the correction factor coefficients of the load peak-valley difference index, load fluctuation standard deviation index, proportion of the number of abnormal values, and proportion of the number of normal values;

[0020] Obtain the renewable energy power generation power at each time point within a unit time period from the power grid operation parameter information, denoted as , and calculate its average value to obtain the average renewable energy power generation power within a unit time period, denoted as . According to the formula Calculate the renewable energy power generation power fluctuation value within a unit time period ;

[0021] Obtain the power grid load fluctuation coefficient, renewable energy power generation power fluctuation value, voltage deviation, and frequency deviation at each time point within a unit time period from the power grid operation parameter information. According to the formula Calculate the power grid operation stability evaluation coefficient within a unit time period , respectively represent the voltage deviation and frequency deviation, and b1, b2, b3, and b4 respectively represent the weight coefficients of the power grid load fluctuation coefficient, renewable energy power generation power fluctuation value, voltage deviation, and frequency deviation;

[0022] Set the gradient comparison thresholds DT1 and DT2 for the power grid operation stability evaluation coefficient, and compare and analyze the power grid operation stability evaluation coefficient with the preset gradient comparison thresholds DT1 and DT2. Among them, the gradient comparison thresholds DT1 and DT2 increase in a gradient, so DT1 < DT2, and DT2 = x * DT1, where x represents the gradient multiple;

[0023] When the power grid operation stability evaluation coefficient is less than the preset gradient comparison threshold DT1, a low-level feedback signal for power grid operation stability is generated. When the power grid operation stability evaluation coefficient is between the preset gradient comparison thresholds DT1 and DT2, a medium-level feedback signal for power grid operation stability is generated. When the power grid operation stability evaluation coefficient is greater than the preset gradient comparison threshold DT2, a high-level feedback signal for power grid operation stability is generated.

[0024] Furthermore, the specific implementation steps of the energy storage system characteristic determination and analysis processing are as follows:

[0025] Obtain the time points when the target power grid side energy storage system receives each charge and discharge command and the time points when the target power grid side energy storage system starts to charge and discharge after receiving each charge and discharge command within the set monitoring time period, and perform a difference calculation on them to obtain the response duration of each charge and discharge command of the target power grid side energy storage system within the set monitoring time period, and mark it as , where j represents the number of each charge and discharge command, j = 1, 2,...., n, representing the total number of charge and discharge command numbers;

[0026] According to the formula Calculate the corresponding response degree of the target power grid side energy storage system within the set monitoring time period ;

[0027] Obtain the charge and discharge efficiency, self-discharge rate, number of charge and discharge cycles, and response degree of the target power grid side energy storage system per unit time from the information of the target power grid side energy storage system's own characteristic parameters, and mark them as , according to the formula Calculate the operation state determination and evaluation coefficient of the energy storage system per unit time , where c1, c2, c3, and c4 respectively represent the weight coefficients of the charge and discharge efficiency, self-discharge rate, number of charge and discharge cycles, and response degree;

[0028] Set the comparison reference interval rang for the operation state determination and evaluation coefficient of the energy storage system, and compare and analyze the operation state determination and evaluation coefficient with the comparison reference interval rang. When the operation state determination and evaluation coefficient is greater than the maximum value of the comparison reference interval rang, a feedback signal for the efficient operation of the energy storage system is generated. Otherwise, a feedback signal for the inefficient operation of the energy storage system is generated.

[0029] Further, the specific implementation steps for comprehensive data analysis and processing are as follows:

[0030] Based on the signal for judging the type of power grid operation stability feedback, establish a set X. Label the low-level feedback signal of power grid operation stability as element a1, the medium-level feedback signal of power grid operation stability as element a2, and the high-level feedback signal of power grid operation stability as element a3. And element a1 ∈ set X, element a2 ∈ set X, element a3 ∈ set X;

[0031] Based on the signal for judging the type of energy storage system operation feedback, establish a set Y. Label the high-efficiency operation feedback signal of the energy storage system as element b1, and the low-efficiency operation feedback signal of the energy storage system as element b2. And element b1 ∈ set Y, element b2 ∈ set Y;

[0032] Perform the union operation on sets X and Y. If X ∪ Y = {a3, b1}, then generate a low-level capacity configuration requirement judgment signal. If X ∪ Y = {a2, b1} or {a2, b2} or {a3, b2}, then generate a medium-level capacity configuration requirement judgment signal. If X ∪ Y = {a1, b2} or {a1, b1}, then generate a high-level capacity configuration requirement judgment signal;

[0033] According to the generated low-level capacity configuration requirement judgment signal, perform a k1-order capacity expansion adjustment on the capacity configuration of the power grid-side energy storage system to meet the power grid operation requirements;

[0034] According to the generated medium-level capacity configuration requirement judgment signal, perform a k2-order capacity expansion adjustment on the capacity configuration of the power grid-side energy storage system to meet the power grid operation requirements;

[0035] According to the generated high-level capacity configuration requirement judgment signal, perform a k3-order capacity expansion adjustment on the capacity configuration of the power grid-side energy storage system to meet the power grid operation requirements.

[0036] Further, extract and analyze the power grid operation parameters of the adjusted capacity configuration on the target power grid-side energy storage system. The specific analysis method is as follows:

[0037] By extracting the grid load power and grid generation power in the adjusted power grid operation parameters of the target power grid-side energy storage system capacity configuration, and respectively labeling them as , according to the formula Calculate the power grid power deficit , and at the same time obtain the maximum discharge power after the capacity expansion adjustment of the target power grid-side energy storage system, denoted as , according to the formula Calculate the power balance satisfaction value after the capacity expansion adjustment of the target power grid-side energy storage system ;

[0038] Obtain the capacity configuration of the target grid-side energy storage system for the adjusted power generation of renewable energy and the actually consumed electricity of renewable energy, which are respectively marked as , and at the same time obtain the renewable energy consumption rate before the capacity expansion adjustment of the target grid-side energy storage system, denoted as . According to the formula , calculate the increased value of renewable energy consumption after the capacity expansion adjustment of the target grid-side energy storage system ;

[0039] . According to the formula , calculate the comprehensive effectiveness evaluation coefficient after the capacity configuration adjustment of the target grid-side energy storage system , where d1 and d2 respectively represent the weight coefficients corresponding to the power balance satisfaction value and the increased value of renewable energy consumption;

[0040] Set the comparison threshold for the comprehensive effectiveness stability evaluation coefficient after the capacity configuration adjustment of the target grid-side energy storage system, and compare and analyze the comprehensive effectiveness evaluation coefficient with the preset comparison threshold. When the comprehensive effectiveness evaluation coefficient is equal to the preset comparison threshold, a capacity configuration pass signal is generated; otherwise, a capacity configuration fail signal is generated.

[0041] Furthermore, perform a re-optimization and adjustment operation. The specific operation steps are as follows:

[0042] By extracting the adjusted grid operation stability evaluation coefficient and the operation state determination evaluation coefficient of the target grid-side energy storage system, according to the formula , calculate the grid comprehensive state determination coefficient , where w1 and w2 respectively represent the weight coefficients of the grid operation stability evaluation coefficient and the operation state determination evaluation coefficient of the energy storage system;

[0043] Set the comparison reference threshold for the grid comprehensive state determination coefficient as . Compare the grid comprehensive state determination coefficient with the preset comparison reference threshold for comparison and analysis. When the grid comprehensive state determination coefficient is greater than or equal to the preset comparison reference threshold , a re-regulation signal is generated; otherwise, a warning reminder signal is generated;

[0044] According to the generated re-regulation signal, perform a capacity expansion adjustment of km + p order on the capacity configuration of the target grid-side energy storage system to make the grid operation stable, where m = 1, 2, 3, and p is the scale parameter unit of the capacity configuration of the target grid-side energy storage system for the second adjustment;

[0045] Extract the adjusted grid-side energy storage system capacity configuration of the target grid's operating parameters again and repeat the operation of the capacity configuration adjustment verification module. If the capacity configuration passes, generate an optimization end signal; if the capacity configuration fails, generate a warning reminder signal.

[0046] Advantages of the present invention:

[0047] Through symbolic calibration, formulaic analysis, and data comparison analysis, the present invention analyzes the load volatility and renewable energy generation volatility in grid operation, thereby determining and analyzing the grid operation stability, generating corresponding grid operation stability feedback signals. At the same time, by analyzing the operating state of the target grid-side energy storage system, the operating state of the target grid-side energy storage system is evaluated, and corresponding operating efficiency feedback signals are generated, providing strong data support for the subsequent determination of the capacity configuration requirements of the target grid-side energy storage system;

[0048] By comprehensively analyzing the grid operation stability type feedback determination signal and the energy storage system operating state feedback type determination signal, and generating corresponding capacity configuration requirement determination signals for expansion adjustment operations, targeted adjustment of the energy storage system capacity configuration is achieved. It can dynamically match the best capacity configuration according to the real-time states of the grid and the energy storage system, realize the collaborative optimization of the energy storage system and the grid, not only meet the diverse needs of the grid for energy storage, but also avoid unnecessary investment waste, and improve the economy of grid operation.

[0049] By extracting and analyzing the grid operation parameters after the capacity configuration adjustment of the target grid-side energy storage system, the comprehensive performance evaluation coefficient after the capacity configuration adjustment of the target grid-side energy storage system is obtained. Based on this, the capacity configuration verification analysis is carried out, and the capacity configuration pass signal and the capacity configuration fail signal are obtained, and then re-optimization and adjustment are carried out to avoid the negative impacts brought by blind expansion or improper configuration, comprehensively improve the reliability, stability, and economy of grid operation, provide solid technical support for the sustainable development of smart grids, and effectively respond to the complex and changeable challenges faced by the grid during the energy transformation process. Description of the Drawings

[0050] The present invention will be further described below with reference to the drawings.

[0051] Figure 1 It is the system block diagram of the present invention. Detailed Embodiments

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0053] Please refer to Figure 1 As shown, the present invention is an optimization system for the capacity configuration of a grid-side energy storage system, including a server, which is communicatively connected to a data acquisition unit, a grid operation characteristic analysis unit, an energy storage system characteristic analysis unit, a capacity configuration determination and adjustment unit, a capacity configuration adjustment verification module, a capacity configuration optimization adjustment module, and an early warning terminal;

[0054] The data acquisition unit is used to collect the grid operation characteristic parameter information and the self-characteristic parameter information of the target grid-side energy storage system, and send them to the grid operation characteristic analysis unit and the energy storage system characteristic analysis unit through the server respectively;

[0055] When the grid operation characteristic analysis unit receives the grid operation characteristic parameter information, it performs grid operation characteristic determination and analysis processing accordingly. The specific operation execution steps are as follows:

[0056] Obtain the load at each time point within a unit time period from the grid operation characteristic parameter information. Taking each time point as the abscissa and the load as the ordinate, draw the load curve within the unit time period, and extract the maximum load and the minimum load from it, which are respectively marked as At the same time, calculate the average value of the loads at each time point within the unit time period to obtain the average load, denoted as According to the formula Calculate the grid load peak-valley difference index within the unit time period;

[0057] Extract the load at each time point from the load curve within the unit time period, and mark it as , where i represents the number of each time point, i = 1, 2,...., m, and m represents the total number of time point numbers. According to the formula Calculate the grid load fluctuation standard deviation index within the unit time period;

[0058] Extract the loads at two adjacent time points from the load curve within a unit time period, calculate the difference between the loads at two adjacent time points to obtain the load difference between two adjacent time points. At the same time, extract the interval duration corresponding to two adjacent time points, and calculate the ratio of the load difference between two adjacent time points to the interval duration corresponding to two adjacent time points to obtain the load change rate between two adjacent time points. Thus, statistically obtain the load change rates between each two adjacent time points within a unit time period as the load change rates within a unit time period;

[0059] Compare the load change rates within a unit time period with the set reference load change rate threshold. When a certain load change rate within a unit time period is greater than the set reference load change rate threshold, record this load change rate as an abnormal value, otherwise record it as a normal value. Thus, statistically obtain the number of normal values and the number of abnormal values of the load change rate within a unit time period, and mark them respectively as ;

[0060] According to the formula Calculate the grid load fluctuation coefficient within the set monitoring time period , respectively represent the set reference load peak-valley difference index and the reference load fluctuation standard deviation index. a1, a2, a3, and a4 respectively represent the correction factor coefficients of the load peak-valley difference index, the load fluctuation standard deviation index, the proportion of the number of abnormal values, and the proportion of the number of normal values. And a1, a2, a3, and a4 are all natural numbers greater than 0. The correction factor coefficients are used to correct the deviations that occur in the formula calculation of each parameter, so as to obtain more accurate parameter data;

[0061] Obtain the renewable energy power generation at each time point within a unit time period from the grid operation parameter information, denoted as , and calculate its average value to obtain the average renewable energy power generation within a unit time period, denoted as . According to the formula Calculate the renewable energy power generation fluctuation value within a unit time period ;

[0062] Obtain the grid load fluctuation coefficient, the renewable energy power generation fluctuation value, the voltage deviation, and the frequency deviation within a unit time period from the grid operation parameter information. According to the formula Calculate the grid operation stability evaluation coefficient within a unit time period , They are represented as voltage deviation and frequency deviation respectively. b1, b2, b3, and b4 are represented as the grid load fluctuation coefficient, the renewable energy power generation fluctuation value, and the weight coefficients of voltage deviation and frequency deviation respectively, and b1 > b2 > b3 > b4. The weight coefficients are used to balance the proportion weights of various data in the formula calculation, so as to promote the accuracy of the calculation results;

[0063] It should be noted that the voltage deviation refers to the value of the degree to which the grid voltage deviates from the reference grid voltage within a unit time period, and the frequency deviation refers to the value of the degree to which the grid voltage deviates from the reference grid frequency within a unit time period. When the voltage deviation and frequency deviation are larger, the power demand for frequency modulation of the power grid and the demand for reactive power regulation are greater, which also indicates that the capacity configuration of the energy storage system needs to be increased; in addition, when the grid load fluctuation coefficient is larger, in order to effectively smooth the load curve, the capacity configuration of the energy storage system also needs to be increased. When the renewable energy power generation fluctuation value is larger, the more surplus electric energy that the energy storage system needs to store and the electric energy that needs to be released when the renewable energy output is insufficient, and the energy storage system needs a larger capacity to suppress the power fluctuation of wind power to ensure the stable operation of the power grid;

[0064] Set the gradient comparison thresholds DT1 and DT2 of the grid operation stability evaluation coefficient, and compare and analyze the grid operation stability evaluation coefficient with the preset gradient comparison thresholds DT1 and DT2. Among them, the gradient comparison thresholds DT1 and DT2 increase in a gradient, so DT1 < DT2, and DT2 = x * DT1, where x represents the gradient multiple;

[0065] When the grid operation stability evaluation coefficient is less than the preset gradient comparison threshold DT1, a low-level feedback signal of grid operation stability is generated. When the grid operation stability evaluation coefficient is between the preset gradient comparison thresholds DT1 and DT2, a medium-level feedback signal of grid operation stability is generated. When the grid operation stability evaluation coefficient is greater than the preset gradient comparison threshold DT2, a high-level feedback signal of grid operation stability is generated;

[0066] Send the generated low-level feedback signal of grid operation stability, medium-level feedback signal of grid operation stability, and high-level feedback signal of grid operation stability to the capacity configuration determination and adjustment unit;

[0067] When the energy storage system characteristic analysis unit receives the information of the target grid-side energy storage system's own characteristic parameters and conducts characteristic determination analysis and processing based on this, the specific implementation steps are as follows:

[0068] Obtain the time points when the target grid - side energy storage system receives charge - discharge commands each time within the set monitoring time period and the time points when the target grid - side energy storage system starts to charge and discharge after receiving the charge - discharge commands each time, and perform a difference calculation on them to obtain the response duration of each charge - discharge command of the target grid - side energy storage system within the set monitoring time period, and mark it as , where j represents the number of each charge - discharge command, j = 1, 2,...., n, representing the total number of charge - discharge command numbers;

[0069] According to the formula Calculate the corresponding response degree of the target grid - side energy storage system within the set monitoring time period ;

[0070] Obtain the charge - discharge efficiency, self - discharge rate, number of charge - discharge cycles, and response degree of the target grid - side energy storage system per unit time from the information of the target grid - side energy storage system's own characteristic parameters, and mark them as , according to the formula Calculate the operation - state determination and evaluation coefficient of the energy storage system per unit time , where c1, c2, c3, and c4 respectively represent the weight coefficients of the charge - discharge efficiency, self - discharge rate, number of charge - discharge cycles, and response degree, and c1, c2, c3, c4 are all natural numbers greater than 0. The weight coefficients are used to balance the proportion weights of each item of data in the formula calculation, so as to promote the accuracy of the result;

[0071] It should be noted that the charge - discharge efficiency refers to the ratio of the actually effectively utilized energy to the input or output energy during the charging and discharging processes of the energy storage system. The lower the charge - discharge efficiency of the target grid - side energy storage system, the more energy loss there is during the charge - discharge process of the energy storage system. Therefore, to store or provide the same amount of effective electric energy, a larger capacity needs to be configured to make up for the loss; the self - discharge rate refers to the ratio of the natural loss of the energy storage system's own power when the energy storage system does not perform charge - discharge operations. The higher the self - discharge rate of the target grid - side energy storage system, the more energy loss there is during the self - discharge process of the energy storage system. In order to ensure that enough electric energy can be provided to meet the grid demand when needed, a larger - capacity energy storage system needs to be configured; when the number of charge - discharge cycles of the target grid - side energy storage system is more, the capacity of the energy storage system will gradually decay. In order to ensure that the energy demand of the grid can be met throughout the service life, it is necessary to appropriately increase the capacity configuration when the number of cycles is more;

[0072] Set a comparison reference range rang for the operating status determination evaluation coefficient of the energy storage system. Compare and analyze the operating status determination evaluation coefficient with the comparison reference range rang. When the operating status determination evaluation coefficient is greater than the maximum value of the comparison reference range rang, generate a high-efficiency operation feedback signal for the energy storage system; otherwise, generate a low-efficiency operation feedback signal for the energy storage system.

[0073] Send both the generated low-efficiency operation feedback signal and high-efficiency operation feedback signal of the energy storage system to the capacity configuration determination and adjustment unit.

[0074] When the capacity configuration determination and adjustment unit receives the power grid operation stability feedback type determination signal and the energy storage system operation feedback type determination signal and conducts comprehensive data analysis and processing, the specific implementation steps are as follows:

[0075] Establish a set X based on the power grid operation stability feedback type determination signal. Label the power grid operation stability low-level feedback signal as element a1, the power grid operation stability medium-level feedback signal as element a2, and the power grid operation stability high-level feedback signal as element a3. And element a1 ∈ set X, element a2 ∈ set X, element a3 ∈ set X.

[0076] Establish a set Y based on the energy storage system operation feedback type determination signal. Label the high-efficiency operation feedback signal of the energy storage system as element b1 and the low-efficiency operation feedback signal of the energy storage system as element b2. And element b1 ∈ set Y, element b2 ∈ set Y.

[0077] Perform the union operation on sets X and Y. If X ∪ Y = {a3, b1}, generate a low-level capacity configuration requirement determination signal. If X ∪ Y = {a2, b1} or {a2, b2} or {a3, b2}, generate a medium-level capacity configuration requirement determination signal. If X ∪ Y = {a1, b2} or {a1, b1}, generate a high-level capacity configuration requirement determination signal.

[0078] Perform a k1-order capacity expansion adjustment on the capacity configuration of the grid-side energy storage system according to the generated low-level capacity configuration requirement determination signal to meet the power grid operation requirements.

[0079] Perform a k2-order capacity expansion adjustment on the capacity configuration of the grid-side energy storage system according to the generated medium-level capacity configuration requirement determination signal to meet the power grid operation requirements.

[0080] Perform a k3-order capacity expansion adjustment on the capacity configuration of the grid-side energy storage system according to the generated high-level capacity configuration requirement determination signal to meet the power grid operation requirements.

[0081] It should be noted that the k1 order < the k2 order < the k3 order, where the order represents the unit of the capacity configuration scale parameter. The specific values and units of the 1st order, k2 order, and k3 order are set by those skilled in the art in specific cases.

[0082] When the capacity configuration adjustment verification module extracts the grid operation parameters of the adjusted capacity configuration on the target grid-side energy storage system for analysis, the specific analysis method is as follows:

[0083] By extracting the grid load power and grid generation power in the adjusted grid operation parameters of the target grid-side energy storage system capacity configuration, and marking them respectively as , according to the formula calculate the grid power deficit , and at the same time obtain the maximum discharge power after the capacity expansion adjustment of the target grid-side energy storage system, denoted as , according to the formula calculate the power balance satisfaction value after the capacity expansion adjustment of the target grid-side energy storage system ;

[0084] Obtain the power generation of renewable energy and the electricity actually consumed by renewable energy in the adjusted capacity configuration of the target grid-side energy storage system, and mark them respectively as , and at the same time obtain the renewable energy consumption rate before the capacity expansion adjustment of the target grid-side energy storage system, denoted as , according to the formula calculate the increased value of renewable energy consumption after the capacity expansion adjustment of the target grid-side energy storage system ;

[0085] According to the formula calculate the comprehensive effectiveness evaluation coefficient after the capacity configuration adjustment of the target grid-side energy storage system , d1 and d2 respectively represent the weight coefficients corresponding to the power balance satisfaction value and the increased value of renewable energy consumption. The weight coefficients are used to balance the proportion weights of various data in the formula calculation, so as to promote the accuracy of the calculation results;

[0086] Set the comparison threshold of the comprehensive effectiveness stability evaluation coefficient after the capacity configuration adjustment of the target grid-side energy storage system, and compare and analyze the comprehensive effectiveness evaluation coefficient with the preset comparison threshold. When the comprehensive effectiveness evaluation coefficient is equal to the preset comparison threshold, a capacity configuration pass signal is generated; otherwise, a capacity configuration fail signal is generated;

[0087] When the capacity configuration optimization adjustment module receives the capacity configuration fail signal and performs re-optimization adjustment operations accordingly, the specific operation steps are as follows:

[0088] By extracting the adjusted power grid operation stability evaluation coefficient and the operation state determination evaluation coefficient of the target power grid side energy storage system, and according to the formula calculate the power grid comprehensive state determination coefficient , where w1 and w2 respectively represent the weight coefficients of the power grid operation stability evaluation coefficient and the operation state determination evaluation coefficient of the energy storage system;

[0089] Set the comparison reference threshold of the power grid comprehensive state determination coefficient to , and compare and analyze the power grid comprehensive state determination coefficient with the preset comparison reference threshold . When the power grid comprehensive state determination coefficient is greater than or equal to the preset comparison reference threshold , a readjustment signal is generated; otherwise, a warning reminder signal is generated;

[0090] According to the generated readjustment signal, perform km + p - order capacity expansion adjustment on the capacity configuration of the target power grid side energy storage system to meet the power grid operation requirements, where m = 1, 2, 3, and p is the scale parameter unit of the capacity configuration of the target power grid side energy storage system for the second adjustment;

[0091] Extract the power grid operation parameters of the capacity configuration of the adjusted target power grid side energy storage system again and repeat the operation of the capacity configuration adjustment verification module. If the capacity configuration passes, an optimization end signal is generated; if the capacity configuration fails, a warning reminder signal is generated.

[0092] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should belong to the protection scope of the present invention.

Claims

1. A capacity configuration optimization system for a grid-side energy storage system, comprising a server, wherein the server is communicatively connected to a grid operation characteristic analysis unit, an energy storage system characteristic analysis unit, a capacity configuration determination and adjustment unit, a capacity configuration adjustment verification module, a capacity configuration optimization and adjustment module, and an early warning terminal; characterized in that: The power grid operation characteristic analysis unit is used to receive power grid operation characteristic parameter information, and perform power grid operation characteristic determination and analysis processing, thereby generating a power grid operation stability low feedback signal, a power grid operation stability medium feedback signal and a power grid operation stability high feedback signal, and sending them all to the capacity configuration determination and adjustment unit; The energy storage system characteristic analysis unit is used to receive characteristic parameter information of the target grid-side energy storage system itself, and perform energy storage system characteristic determination and analysis processing, thereby generating an energy storage system inefficient operation feedback signal and an energy storage system efficient operation feedback signal, and sending them to the capacity configuration determination and adjustment unit; The capacity configuration determination and adjustment unit is used to receive the grid operation stability feedback type determination signal and the energy storage system operation feedback type determination signal and perform comprehensive data analysis and processing, thereby generating a low-level capacity configuration demand determination signal, a medium-level capacity configuration demand determination signal and a high-level capacity configuration demand determination signal, and perform corresponding adjustment operations according to the corresponding capacity configuration demand type determination signal; The capacity configuration adjustment verification module is used to extract the grid operation parameters of the adjusted capacity configuration on the target grid-side energy storage system for analysis, thereby obtaining the comprehensive efficiency evaluation coefficient of the target grid-side energy storage system after the capacity configuration is adjusted, and based on this, perform verification analysis on the capacity configuration optimization adjustment plan, thereby obtaining a capacity configuration pass signal and a capacity configuration fail signal; The capacity configuration optimization and adjustment module is used to receive a capacity configuration failure signal, and perform re-optimization and adjustment operations accordingly, thereby generating a readjustment signal and an early warning reminder signal, and performing corresponding adjustment operations according to the generated readjustment signal, and then extracting the adjusted energy storage system capacity configuration product in the power grid operation parameters and repeating the operation of the capacity configuration adjustment verification module. If the capacity configuration passes, an optimization end signal is generated, and if the capacity configuration fails, an early warning reminder signal is generated, and the early warning reminder signal is sent to the early warning terminal for early warning operation.

2. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The specific execution steps of the power grid operation characteristic determination and analysis process are as follows: The load at each time point in a unit time period is obtained from the grid operation characteristic parameter information. The load curve in a unit time period is drawn with each time point as the horizontal coordinate and the load as the vertical coordinate. The maximum load and the minimum load are extracted from the curve and marked as At the same time, the load at each time point in the unit time period is averaged to obtain the average load, which is recorded as , according to the formula Calculate the peak-to-valley difference index of the power grid load within a unit time period ; Extract the load at each time point from the load curve within the unit time period and mark it as , i represents the number of each time point, i=1,2,....,m, m represents the total number of time point numbers, according to the formula Calculate the standard deviation index of power grid load fluctuation within a unit time period ; Extract the loads of two adjacent time points from the load curve within the unit time period, and perform a difference calculation on the loads of the two adjacent time points to obtain the load difference of the two adjacent time points, and extract the interval duration corresponding to the two adjacent time points at the same time, perform a ratio calculation on the load difference of the two adjacent time points and the interval duration corresponding to the two adjacent time points to obtain the load change rate of the two adjacent time points, thereby statistically obtaining the load change rate of each two adjacent time points within the unit time period as each load change rate within the unit time period; The load change rate in a unit time period is compared with the set reference load change rate threshold. When a load change rate in a unit time period is greater than the set reference load change rate threshold, the load change rate is recorded as an abnormal value, otherwise it is recorded as a normal value. The number of normal values ​​and abnormal values ​​of the load change rate in a unit time period are obtained by statistics, which are marked as ; According to the formula Calculate the grid load fluctuation coefficient within the set monitoring time period , They are respectively represented as the set reference load peak-to-valley difference index and reference load fluctuation standard deviation index, and a1, a2, a3 and a4 are respectively represented as the correction factor coefficients of the load peak-to-valley difference index, the load fluctuation standard deviation index, the number of abnormal values ​​and the number of normal values; The renewable energy power generation at each time point in a unit time period is obtained from the grid operation parameter information, which is recorded as , and calculate the average value to obtain the average power of renewable energy generation in a unit time period, which is recorded as , according to the formula Calculate the fluctuation value of renewable energy power generation within a unit time period ; The grid load fluctuation coefficient, renewable energy power generation fluctuation value, voltage deviation and frequency deviation within a unit time period are obtained from the grid operation parameter information. Calculate the grid operation stability assessment coefficient within a unit time period , They are represented by voltage deviation and frequency deviation respectively, b1, b2, b3, b4 are represented by the weight coefficients of grid load fluctuation coefficient, renewable energy power generation power fluctuation value, voltage deviation and frequency deviation respectively; Set the gradient comparison thresholds DT1 and DT2 of the power grid operation stability evaluation coefficient, and compare and analyze the power grid operation stability evaluation coefficient with the preset gradient comparison thresholds DT1 and DT2: When the grid operation stability evaluation coefficient is less than the preset gradient comparison threshold DT1, a low grid operation stability feedback signal is generated; when the grid operation stability evaluation coefficient is between the preset gradient comparison thresholds DT1 and DT2, a medium grid operation stability feedback signal is generated; when the grid operation stability evaluation coefficient is greater than the preset gradient comparison threshold DT2, a high grid operation stability feedback signal is generated.

3. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The specific execution steps of the energy storage system characteristic determination and analysis process are as follows: Obtain the time points at which the target grid-side energy storage system receives the charge and discharge instructions each time within the set monitoring time period and the time points at which the target grid-side energy storage system starts to charge and discharge after receiving the charge and discharge instructions each time, and perform a difference calculation to obtain the response time of each charge and discharge instruction of the target grid-side energy storage system within the set monitoring time period, and mark it as , j represents the number of each charge and discharge instruction, j=1,2,....,n, represents the total number of charge and discharge instruction numbers; According to the formula Calculate the responsiveness of the target grid-side energy storage system within the set monitoring time period ; The charging and discharging efficiency, self-discharge rate, number of charging and discharging cycles and responsiveness of the target grid-side energy storage system in a unit time period are obtained from the characteristic parameter information of the target grid-side energy storage system itself, and are marked as , according to the formula Calculate the evaluation coefficient of the energy storage system's operating status within a unit time period , c1, c2, c3, c4 represent the weight coefficients of charge and discharge efficiency, self-discharge rate, number of charge and discharge cycles, and responsiveness, respectively; A comparison reference interval rang of the operation state judgment evaluation coefficient of the energy storage system is set, and the operation state judgment evaluation coefficient is compared and analyzed with the comparison reference interval rang. When the operation state judgment evaluation coefficient is greater than the maximum value of the comparison reference interval rang, an energy storage system efficient operation feedback signal is generated, otherwise, an energy storage system inefficient operation feedback signal is generated.

4. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The specific execution steps of the data comprehensive analysis and processing are as follows: According to the power grid operation stability feedback type judgment signal, a set X is established, the low power grid operation stability feedback signal is marked as element a1, the medium power grid operation stability feedback signal is marked as element a2, and the high power grid operation stability feedback signal is marked as element a3, and element a1∈set X, element a2∈set X, and element a3∈set X; According to the energy storage system operation feedback type judgment signal, a set Y is established, the energy storage system high-efficiency operation feedback signal is marked as element b1, and the energy storage system low-efficiency operation feedback signal is marked as element b2, and element b1∈set Y, element b2∈set Y; The sets X and Y are processed as a union. If X∪Y={a3, b1}, a low-level capacity configuration demand determination signal is generated. If X∪Y={a2, b1} or {a2, b2} or {a3, b2}, a medium-level capacity configuration demand determination signal is generated. If X∪Y={a1, b2} or {a1, b1}, a high-level capacity configuration demand determination signal is generated. According to the generated low-level capacity configuration demand judgment signal, the capacity configuration of the grid-side energy storage system is adjusted by k1 order to meet the grid operation demand; According to the generated intermediate capacity configuration demand judgment signal, the capacity configuration of the grid-side energy storage system is adjusted by k2 order to meet the grid operation demand; According to the generated advanced capacity configuration demand judgment signal, the capacity configuration of the grid-side energy storage system is adjusted by k3 order to meet the grid operation needs.

5. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The grid operation parameters of the adjusted capacity configuration on the target grid-side energy storage system are extracted and analyzed. The specific analysis method is as follows: By extracting the grid load power and grid generation power configured in the adjusted grid operation parameters by the target grid-side energy storage system capacity, and marking them as , according to the formula Calculate the power shortage of the power grid , and at the same time obtain the maximum discharge power of the target grid-side energy storage system after expansion and adjustment, recorded as , according to the formula Calculate the power balance satisfaction value after the target grid-side energy storage system is expanded and adjusted ; Obtain the target grid-side energy storage system capacity configuration in the adjusted renewable energy generation and the actual renewable energy consumption, marked as , and at the same time obtain the renewable energy consumption rate before the expansion adjustment of the target grid-side energy storage system, recorded as , according to the formula Calculate the renewable energy consumption improvement value after the target grid-side energy storage system expansion adjustment ; According to the formula Calculate the comprehensive performance evaluation coefficient after adjusting the capacity configuration of the target grid-side energy storage system , d1 and d2 represent the weight coefficients corresponding to the power balance satisfaction value and the renewable energy consumption improvement value respectively; A comparison threshold of the comprehensive performance stability evaluation coefficient after the capacity configuration of the target grid-side energy storage system is adjusted is set, and the comprehensive performance evaluation coefficient is compared and analyzed with the preset comparison threshold. When the comprehensive performance evaluation coefficient is equal to the preset comparison threshold, a capacity configuration pass signal is generated, otherwise, a capacity configuration fail signal is generated.

6. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The specific steps of re-optimization and adjustment are as follows: By extracting the adjusted grid operation stability evaluation coefficient and the target grid-side energy storage system operation status evaluation coefficient, according to the formula Calculate the comprehensive state determination coefficient of the power grid , where w1 and w2 represent the weight coefficients of the grid operation stability evaluation coefficient and the energy storage system operation status evaluation coefficient respectively; Set the comparison reference threshold of the power grid comprehensive status determination coefficient to , the comprehensive state determination coefficient of the power grid Compare with preset reference threshold Comparative analysis is performed, when the comprehensive state determination coefficient of the power grid is Greater than or equal to the preset comparison reference threshold If the error is too high, a readjustment signal is generated; otherwise, an early warning signal is generated. According to the generated readjustment signal, the capacity configuration of the target grid-side energy storage system is expanded by km+p to stabilize the grid operation, where m=1, 2, 3, and p is the unit of the scale parameter of the readjusted target grid-side energy storage system capacity configuration; The adjusted target grid-side energy storage system capacity is extracted again and configured in the grid operating parameters and the operation of the capacity configuration adjustment verification module is repeated. If the capacity configuration passes, an optimization end signal is generated; if the capacity configuration fails, an early warning reminder signal is generated.

7. A grid-side energy storage system capacity configuration optimization system according to claim 1, characterized in that: The server is also communicatively connected to a data acquisition unit, which is used to collect grid operation characteristic parameter information and characteristic parameter information of the target grid-side energy storage system itself, and send them to the grid operation characteristic analysis unit and the energy storage system characteristic analysis unit respectively through the server.

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