A power grid power limit configuration method considering multiple factors

Abstract

The present invention belongs to the field of power grid operation and control technology, and in particular, relates to a power grid power limit configuration method that comprehensively considers multiple factors. The present invention includes: step 1. determining the installed capacity of conventional units and the installed capacity of new energy units; step 2. obtaining wind, solar, water and load scene data; step 3. taking the system operation state as a constraint condition; step 4. establishing a comprehensive evaluation index for the unit ratio scheme; step 5. establishing a multi-objective optimization model for unit capacity ratio; step 6. solving the multi-objective optimization model based on the whale algorithm; step 7. determining the weight of each evaluation index based on the consistency of subjective and objective attribute values; step 8. calculating the total score of each unit ratio scheme; step 9. determining the limit ratio of new energy units to conventional units. The present invention can improve the reliability and environmental benefits of the unit ratio scheme, provide a technical basis and practical methods for the stable operation of the power grid under the participation of multiple energy sources, reduce the impact of load volatility, and is easy to implement and develop.

Description

Technical Field

[0001] The present invention belongs to the field of power grid operation and control technology, and in particular relates to a power grid power limit configuration method that comprehensively considers multiple factors, specifically a unit output ratio that comprehensively considers multiple factors such as system peak regulation capability, frequency regulation capability, transient stability, and frequency stability. Background Art

[0002] Traditional fossil energy such as coal and oil is non-renewable. Developing new energy, increasing the output of new energy, and strengthening the comprehensive utilization of new energy units and conventional units are the inevitable choices for energy development. On the one hand, due to the random volatility of new energy power generation, the power grid's ability to accept new energy is insufficient; at the same time, the access of new energy units to replace conventional units has changed the operating characteristics of the system and affected the safety of the power grid. There is currently no effective response strategy.

[0003] Optimizing the ratio of the capacity of new energy units and conventional units is an effective means to achieve stable operation of the power grid and an effective support for maximizing the benefits of energy conservation and emission reduction.

[0004] Replacing conventional units with new energy units can effectively improve the economic efficiency of system operation and increase the absorption capacity of renewable energy. As the proportion of new energy access continues to increase, the intermittent, volatile and anti-peak characteristics of wind power have significantly increased the uncertainty of power system operation when large-scale wind power is connected to the grid, bringing new challenges to power system peak regulation.

[0005] The current mainstream thermal power peak-shaving and hydropower peak-shaving technologies at home and abroad can solve this problem better. Pumped storage is to pump water to the upper reservoir during low electricity consumption, convert the surplus electricity into potential energy, and release water to the lower reservoir during peak electricity consumption, converting the stored potential energy back into electricity, thus playing the role of peak-shaving and valley-filling. Therefore, the joint operation of multiple new energy sources and conventional units can not only better promote the consumption of new energy, but also be beneficial to the stability of the power grid.

[0006] When the load of wind power connected to the grid is low, the fluctuation of its power generation load has a low impact on the peak load regulation of the grid. However, when the load of wind power connected to the grid increases to a certain proportion, the grid needs to take pre-control measures for the fluctuation of wind power output. Especially on certain special operating days, when the actual load curve is significantly higher than the predicted curve and the actual wind power curve is significantly lower than the predicted curve, the net load will show a sustained large value of the forecast deviation, and the grid must perform faster and deeper frequency regulation. However, due to the unreasonable power supply ratio in my country at this stage, the grid's regulation means and peak load regulation capacity are insufficient. With the extraordinary development of new energy, the contradiction between peak load regulation and stability of the grid has become increasingly prominent. The large-scale grid connection of new energy units has offset the economic and environmental benefits of some new energy sources and affected the stability of the system.

[0007] The traditional power supply ratio strategy method only considers the environmental benefits of renewable energy. The configuration strategy of incorporating a large number of renewable energy units has led to serious wind and power curtailment in the system. The insufficient grid absorption capacity has offset some of the environmental benefits of renewable energy. At the same time, the traditional power supply ratio strategy does not consider the stability of the system. The system is prone to serious overload or the relative amplitude of the unit seriously exceeds the limit after a transient fault occurs, and even the system collapses. Summary of the invention

[0008] In view of the shortcomings of the above-mentioned prior art, the present invention provides a method for configuring the power supply limit of a power grid that comprehensively considers multiple factors. The purpose is to consider multiple factors such as the peak regulation capability, frequency regulation capability, transient stability, and frequency stability, and to improve the system stability of the configuration scheme more effectively and reliably, and to provide a technical basis and a practical method for the power supply limit configuration method that considers multiple factors.

[0009] The technical solution adopted by the present invention to achieve the above-mentioned purpose is:

[0010] A power grid power limit configuration method taking multiple factors into consideration includes the following steps:

[0011] Step 1. Determine the installed capacity of conventional units and the installed capacity of new energy units;

[0012] Step 2. Obtain the scene data of wind, solar, water and electricity;

[0013] Step 3. Take the system operation status as the constraint;

[0014] Step 4. Establish comprehensive evaluation indicators for unit ratio scheme;

[0015] Step 5. Establish a multi-objective optimization model for unit capacity ratio;

[0016] Step 6. Solve the multi-objective optimization model based on the whale algorithm;

[0017] Step 7. Determine the weight of each evaluation index based on the consistency of subjective and objective attribute values;

[0018] Step 8. Calculate the total score of each unit ratio scheme;

[0019] Step 9. Determine the maximum ratio of new energy units to conventional units.

[0020] Furthermore, the installed capacity of conventional units refers to the sum of the rated powers of all generators in a thermal power plant, and the installed capacity of new energy units refers to the sum of the rated powers of various new energy power generation sources such as wind power and photovoltaic power generation.

[0021] Furthermore, the wind, photovoltaic, and hydropower scenario data refer to wind power, photovoltaic, and hydropower output forecast data, load power consumption forecast data, and system frequency operating parameters.

[0022] Furthermore, the establishment of comprehensive evaluation indicators for unit ratio schemes includes:

[0023] (1) Determine the absolute peak-to-valley difference of system load;

[0024] (2) Determine the maximum and minimum frequency values ​​during the period from when the system frequency fluctuates to when the system frequency stabilizes;

[0025] (3) The degree to which the unit deviates from the system inertia center after a fault is used as a transient stability indicator;

[0026] (4) Calculate the variance of the system frequency deviation from the standard frequency;

[0027] The comprehensive evaluation index of the unit ratio scheme is to use the system peak load regulation capability, frequency regulation capability, transient stability, and frequency stability as indicators, and conduct a comprehensive evaluation according to the following formula:

[0028] ΔP1=P max -P min

[0029] Δf m =f max -f min

[0030]

[0031] Among them, ΔP1 is the absolute peak-to-valley difference of load; P max is the maximum value of load fluctuation; P min is the minimum value of load fluctuation; Δf m The difference between the maximum and minimum frequency values ​​during the period from when the system frequency fluctuates to when the system frequency stabilizes; f max Maximum value of system frequency fluctuation; f min The minimum value of system frequency fluctuation; n is the number of sampling points; f0 represents the system frequency deviation, f i is the frequency of the i-th sampling point; f N is the standard frequency; I ts is the total amount of deviations from the system inertia center after the fault; S is the set of all times after the fault; E is the set of all faults; δ i is the power angle of unit i at a certain moment; δ COI is the inertia center of the system at this moment; δ0 is the maximum allowable amplitude of the power angle.

[0032] Furthermore, the establishment of a multi-objective optimization model for unit capacity ratio refers to establishing a mathematical model according to the following formula with the comprehensive optimization of indicators as the goal and the output as the unit ratio:

[0033] minF=(f1,f2,f3,f4)

[0034]

[0035] Among them, f1, f2, f3, and f4 represent the system peak regulation capability, frequency regulation capability, transient stability, and frequency stability respectively; F represents the overall optimality.

[0036] Furthermore, the multi-objective optimization model is solved based on the whale algorithm, including:

[0037] (1) Set the population size and number of iterations;

[0038] Setting the population size and the number of iterations refers to inputting system operation data including conventional generator installed capacity, new energy generator installed capacity, wind, solar, water and load scenario data, and solving the number of iterations;

[0039] (2) Randomly initialize the number of whale populations;

[0040] The random initialization of the number of whale populations refers to the random generation of the output ratio scheme of new energy units and conventional units;

[0041] (3) The whale group currently in the best position for encirclement and capture is the target prey;

[0042] The target prey is the whale group currently in the best capture position, which means updating the position according to the following mathematical expression based on the current best unit ratio scheme:

[0043]

[0044] Where t represents the current iteration number; Indicates the optimal position space of the current whale group individuals; represents the position space of the remaining individuals; || represents the absolute value; represents the coefficient; represents a vector that decreases linearly from 2 to 0 during iteration; Represents the distance between the individual position and the optimal individual; Represents a random number between 0 and 1; M is the maximum number of iterations;

[0045] (4) Whales hunt prey along spiral paths;

[0046] The whale contracts along the spiral path to hunt prey, which means finding the feasible solution of the optimal unit ratio scheme and hunting prey according to the following mathematical expression:

[0047]

[0048] Among them, b is a constant used to define the spiral shape, l is a random number between -1 and 1, and e represents a natural constant;

[0049] (5) After multiple iterations, output a set of non-inferior solutions;

[0050] The multiple iterations refer to outputting a non-inferior solution set, which means repeatedly generating and screening the matching schemes and outputting a feasible solution for the optimal unit matching scheme.

[0051] Furthermore, the extreme ratio of new energy units to conventional units refers to the minimum proportion of conventional units put into the system under the optimal comprehensive evaluation condition.

[0052] Furthermore, the comprehensive evaluation index of the unit ratio scheme is established, including: system peak load regulation capability index, system frequency regulation capability index, system transient stability index and system frequency stability index.

[0053] Furthermore, the system peak load regulation capability index, i.e., the peak-to-valley difference, reflects the flexibility of the system in regulating load;

[0054] The system frequency regulation capability index, i.e., the system frequency regulation fluctuation, is one of the important indicators reflecting the system stability;

[0055] The system transient stability index reflects the degree to which the amplitude of the unit deviates from the system inertia center exceeds the limit after the expected fault occurs;

[0056] The system frequency stability index, that is, the variance of the system frequency deviation from the standard frequency, is one of the important indexes for testing system stability.

[0057] A computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods for configuring power grid power limits taking into account multiple factors are implemented.

[0058] The present invention has the following beneficial effects and advantages:

[0059] The invention comprehensively considers multiple factors of the power grid power limit configuration method, which can improve the reliability and environmental protection benefits of the unit ratio scheme. By considering multiple factors to configure the unit output, the output ratio of new energy units and conventional units can be effectively and reliably configured, providing a technical basis and practical methods for the stable operation of the power grid under the participation of multiple energy sources, thereby reducing the impact of load fluctuations and improving the reliability of the system.

[0060] The method of the present invention is also easy to implement. Based on the original unit configuration, the method of the present invention comprehensively considers multiple factors, so that the unit ratio scheme has a stronger ability to cope with load uncertainty. It is easy to implement from the configuration point of view; at the same time, there are ready-made algorithms for solving each ratio model, and the configuration strategy is also easy to implement.

[0061] The method of the present invention is also characterized by being easy to commercialize. With the increase of new energy units, the development of the configuration method of the present invention is bound to have a greater demand and has a good prospect for commercial development and application.

[0062] The basic idea of ​​the grid power supply limit configuration method that comprehensively considers multiple factors proposed in the present invention is to establish a multi-objective optimization model for unit capacity ratio, and screen out the limit ratios among multiple unit ratio schemes based on multi-objective evaluation indicators, thereby greatly improving the economy of the unit ratio scheme.

[0063] The present invention constructs a multi-objective optimization model for unit capacity ratio by considering multiple indicators such as system stability, and finds the minimum ratio scheme for conventional unit output based on the multi-objective comprehensive evaluation ratio scheme. It can more effectively and reliably find the ratio of new energy units to conventional units, and provide a technical basis and practical method for the power grid power limit configuration method considering multiple factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0065] Figure 1 It is the overall flow chart of the present invention;

[0066] Figure 2 It is a comprehensive evaluation index system of the unit ratio scheme of the present invention;

[0067] Figure 3 is the distribution of the non-inferior solution set of indicators 1, 2, and 3 of the present invention in space;

[0068] Figure 4 It is the comprehensive evaluation value of the 8 groups of matching schemes of the present invention. DETAILED DESCRIPTION

[0069] In order to more clearly understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0071] Refer to the following Figure 1-Figure 4 The technical solutions of some embodiments of the present invention are described.

[0072] Example 1

[0073] The present invention provides an embodiment, which is a power grid power limit configuration method that comprehensively considers multiple factors, such as Figure 1 As shown, Figure 1 It can be seen from the process in the figure that the method of the present invention is to find the limit ratio of the minimum output of the conventional unit by comprehensively considering multiple index systems.

[0074] In order to solve the problems in the prior art, the present invention considers multiple factors such as the system's peak-shaving capability, frequency regulation capability, transient stability, and frequency stability, and configures the output ratio of new energy units to conventional units. The complexity of the configuration method of the present invention lies in that, on the one hand, the configuration method must adapt to changes in various operating conditions, such as large fluctuations in new energy sources such as wind and solar power, transient stability when a system failure occurs, and so on. Different operating conditions require that the configured unit ratio can still ensure the stable operation of the system. On the other hand, the configuration method also needs to find the limit ratio for the minimum output of conventional units to meet the operating requirements of a clean and low-carbon power grid. Achieve a limit ratio of units that adapt to various complex conditions.

[0075] The present invention establishes a multi-objective optimization model for unit capacity ratio based on various system operating factors, solves the multi-objective optimization model based on the whale algorithm, and screens out the unit limit ratio scheme based on multi-objective evaluation indicators to achieve stable system operation while minimizing thermal power output, thereby achieving low-carbon operation.

[0076] The present invention specifically comprises the following steps:

[0077] Step 1. Determine the installed capacity of conventional units and the installed capacity of new energy units;

[0078] The conventional installed capacity refers to the sum of the rated powers of all generators in a thermal power plant, and the new energy installed capacity refers to the sum of the rated powers of various new energy sources such as wind power and photovoltaic power generation;

[0079] Step 2. Obtain the scene data of wind, solar, water and electricity;

[0080] The wind, photovoltaic, and water-load scenario data refers to wind power, photovoltaic, and water power output forecast data, load power consumption forecast data, and system frequency and other operating parameters;

[0081] Step 3. Take the system operation status as the constraint;

[0082] The said constraint condition of the system operation status refers to the upper and lower limits of the thermal power unit output, the climbing rate, the output of the new energy unit, the amount of abandoned wind, etc. as constraint conditions.

[0083] Step 4. Establish comprehensive evaluation indicators for unit ratio scheme;

[0084] The establishment of comprehensive evaluation indicators for unit ratio schemes specifically includes:

[0085] (1) Determine the absolute peak-to-valley difference of system load;

[0086] (2) Determine the maximum and minimum frequency values ​​during the period from when the system frequency fluctuates to when the system frequency stabilizes;

[0087] (3) The degree to which the unit deviates from the system inertia center after a fault is used as a transient stability indicator;

[0088] (4) Calculate the variance of the system frequency deviation from the standard frequency.

[0089] The comprehensive evaluation index of the unit ratio scheme is to use the system peak load regulation capability, frequency regulation capability, transient stability, and frequency stability as indicators, and conduct a comprehensive evaluation according to the following formula:

[0090] ΔP1=P max -P min

[0091] Δf m =f max -f min

[0092]

[0093] Among them, ΔP1 is the absolute peak-to-valley difference of load; P max is the maximum value of load fluctuation; P min is the minimum value of load fluctuation; Δf m The difference between the maximum and minimum frequency values ​​during the period from when the system frequency fluctuates to when the system frequency stabilizes; f max Maximum value of system frequency fluctuation; f min The minimum value of system frequency fluctuation; n is the number of sampling points; f0 represents the system frequency deviation, f i is the frequency of the i-th sampling point; f N is the standard frequency; I ts is the total amount of deviations from the system inertia center after the fault; S is the set of all times after the fault; E is the set of all faults; δ i is the power angle of unit i at a certain moment; δ COIis the inertia center of the system at this moment; δ0 is the maximum allowable amplitude of the power angle.

[0094] Step 5. Establish a multi-objective optimization model for unit capacity ratio;

[0095] The establishment of a multi-objective optimization model for unit capacity ratio refers to establishing a mathematical model according to the following formula with the comprehensive optimization of indicators as the goal and the output as the unit ratio:

[0096] minF=(f1,f2,f3,f4)

[0097]

[0098] Among them, f1, f2, f3, and f4 represent the system peak regulation capability, frequency regulation capability, transient stability, and frequency stability respectively; F represents the comprehensive optimality.

[0099] Step 6. Solve the multi-objective optimization model based on the whale algorithm;

[0100] like Figure 1 As shown in , the multi-objective optimization model is solved based on the whale algorithm, specifically including:

[0101] (1) Set the population size and number of iterations;

[0102] The setting of the population size and the number of iterations refers to inputting system operation data including conventional installed capacity, new energy installed capacity, wind, solar, and water load scenario data, and the number of solution iterations.

[0103] (2) Randomly initialize the number of whale populations;

[0104] The randomly initialized whale population refers to randomly generating an output ratio scheme of new energy units and conventional units.

[0105] (3) The whale group currently in the best position for encirclement and capture is the target prey;

[0106] The target prey is the whale group currently in the best capture position, which means updating the position according to the following mathematical expression based on the current best unit ratio scheme:

[0107]

[0108]

[0109] Where t represents the current iteration number; Indicates the optimal position space of the current whale group individuals; represents the position space of the remaining individuals; || represents the absolute value; represents the coefficient; represents a vector that decreases linearly from 2 to 0 during iteration; Represents the distance between the individual position and the optimal individual; Represents a random number between 0 and 1; M is the maximum number of iterations.

[0110] (4) Whales hunt prey along spiral paths;

[0111] The whale contracts along the spiral path to hunt prey, which means finding the feasible solution of the optimal unit ratio scheme and hunting prey according to the following mathematical expression:

[0112]

[0113] Among them, b is a constant used to define the spiral shape, l is a random number between -1 and 1, and e represents a natural constant.

[0114] (5) After multiple iterations, output a set of non-inferior solutions;

[0115] The multiple iterations refer to outputting a non-inferior solution set, which means repeatedly generating and screening the matching schemes and outputting a feasible solution for the optimal unit matching scheme.

[0116] Step 7. Determine the weight of each evaluation index based on the consistency of subjective and objective attribute values;

[0117] Determining the weight of each evaluation index based on the consistency of subjective and objective attribute values ​​means taking into account both the subjectivity and observability of the evaluation, and determining the combined weight according to the following formula:

[0118]

[0119] in, Indicates that the main weights of indicators are determined by using the hierarchical analysis method; represents the objective weight of the indicator determined by the anti-entropy weight method; w i Represents the combined weight determined based on the consistency of subjective and objective attribute values.

[0120] Step 8. Calculate the total score of each unit ratio scheme;

[0121] Step 9. Determine the maximum ratio of new energy units to conventional units.

[0122] The said maximum ratio of new energy units to conventional units means that under the optimal comprehensive evaluation condition, the proportion of conventional units put into the system is the smallest.

[0123] Example 2

[0124] The present invention further provides an embodiment, which is a power grid power limit configuration method that comprehensively considers multiple factors, such as Figure 2 As shown, Figure 2It is a comprehensive evaluation index system for the unit ratio scheme of the present invention.

[0125] In order to ensure that the output ratio of the method of the present invention ensures the minimum output of conventional units while the system operating state is optimal, the present invention establishes four index systems to comprehensively screen out the limit ratio with the minimum output of conventional units, namely, system peak load capacity index, system frequency regulation capacity index, system transient stability index, and system frequency stability index.

[0126] The comprehensive evaluation index of the unit ratio scheme is established, including:

[0127] ① System peak load regulation capability index, that is, the peak-to-valley difference reflects the flexibility of the system in regulating load;

[0128] ② System frequency regulation capability index, that is, system frequency regulation fluctuation is one of the important indicators reflecting system stability;

[0129] ③ System transient stability index, which reflects the amplitude limit of the unit deviating from the system inertia center after the expected fault occurs;

[0130] ④The system frequency stability index, that is, the variance of the system frequency deviation from the standard frequency is one of the important indicators for testing the system stability.

[0131] Example 3

[0132] The present invention further provides an embodiment, which is a power grid power limit configuration method that comprehensively considers multiple factors, such as Figure 3 As shown, Figure 3 It is the distribution of the non-inferior solution set of indicators 1, 2, and 3 of the present invention in space.

[0133] Since a three-dimensional coordinate graph can only reflect the screening results of three indicators at most, the system peak-shaving capability, frequency regulation capability and transient stability are selected to reflect the screening results. The distribution of the non-inferior solution set in space can be clearly seen from the three-dimensional graph.

[0134] Example 4

[0135] The present invention further provides an embodiment, which is a power grid power limit configuration method that comprehensively considers multiple factors, such as Figure 4 As shown, Figure 4 It is the comprehensive evaluation value of the 8 groups of matching schemes of the present invention.

[0136] Taking a 110kv power grid pilot area as an example, the annual load time series is taken from the standard load data of IEEE-RTS, and the peak load is 10MW. By solving the multi-objective planning model, the non-inferior solution set is solved, and the weights of each evaluation index a1, a2, a3, and a4 are determined to be 0.1208, 0.2735, 0.1667, and 0.4390 respectively based on the consistency of subjective and objective attribute values. The comprehensive evaluation values ​​y1, y2, y3, y4, y5, y6, y7, and y8 are 0.6412, 0.9012, 0.7445, 0.8251, 0.0878, 0.6879, 0.1577, and 0.9204 respectively.

[0137] The comprehensive evaluation values ​​of each scheme are sorted from small to large, the larger the better, and the symbol > indicates better than. The initial sorting result is S8>S2>S4>S3>S6>S1>S7>S5.

[0138] It can be seen that the output ratio of conventional units in Scheme S8 is small. Under this scheme, better system stability can be achieved, while ensuring better system peak regulation capability, frequency regulation capability, transient stability, and frequency stability. That is, this scheme is the extreme ratio of grid power supply.

[0139] Example 5

[0140] Based on the same inventive concept, an embodiment of the present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a grid power limit configuration method that comprehensively considers multiple factors as described in Example 1 or 2 or 3 or 4 or 5 are implemented.

[0141] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for configuring power grid power limits by comprehensively considering multiple factors, characterized by: The following steps are involved: Step 1. Determine the installed capacity of conventional generators and the installed capacity of new energy generators; Step 2. Obtain wind, solar, water and load scenario data; Step 3. Take the system operation status as a constraint condition; Step 4. Establish a comprehensive evaluation index for the unit ratio scheme, including: (1) determining the absolute peak-to-valley difference of the system load; (2) determining the maximum and minimum frequencies during the period from the system frequency fluctuation to the system frequency stability; (3) taking the degree of deviation of the unit from the system inertia center after the fault as a transient stability index; (4) calculating the variance of the system frequency deviation from the standard frequency; The establishment of the comprehensive evaluation index for the unit ratio scheme refers to taking the system peak regulation capability, frequency regulation capability, transient stability, and frequency stability as indicators, and comprehensively evaluating according to the following formula: ΔP1=P max -P min Δf m =f max -f min Among them, ΔP1 is the absolute peak-to-valley difference of load; P max is the maximum value of load fluctuation; P min is the minimum value of load fluctuation; Δf m The difference between the maximum and minimum frequency values ​​during the period from when the system frequency fluctuates to when the system frequency stabilizes; f max Maximum value of system frequency fluctuation; f min The minimum value of system frequency fluctuation; n is the number of sampling points; f0 represents the system frequency deviation, f i is the frequency of the i-th sampling point; f N is the standard frequency; I ts is the total amount of deviations from the system inertia center after the fault; S is the set of all times after the fault; E is the set of all faults; δ i is the power angle of unit i at a certain moment; δ COI is the inertia center of the system at this moment; δ0 is the maximum allowable amplitude of the power angle; Step 5. Establish a multi-objective optimization model for unit capacity ratio, which means taking the comprehensive optimal index as the goal and the output as the unit ratio, and establish a mathematical model according to the following formula: minF = (f1, f2, f3, f4) Among them, f1, f2, f3, and f4 represent the system peak-shaving capability, frequency regulation capability, transient stability, and frequency stability, respectively; F represents comprehensive optimality; Step 6. Solve the multi-objective optimization model based on the whale algorithm; Step 7. Determine the weight of each evaluation index based on the consistency of subjective and objective attribute values; Step 8. Calculate the total score of each unit ratio scheme; Step 9. Determine the limit ratio of new energy units to conventional units.

2. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 1 is characterized in that: The installed capacity of conventional units refers to the sum of the rated powers of all generators in a thermal power plant, and the installed capacity of new energy units refers to the sum of the rated powers of wind power and photovoltaic power generation.

3. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 1 is characterized in that: The wind, photovoltaic, and hydropower scenario data refer to wind power, photovoltaic, and hydropower output forecast data, load power consumption forecast data, and system frequency operating parameters.

4. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 1 is characterized in that: The multi-objective optimization model is solved based on the whale algorithm, including: (1) Set the population size and number of iterations; Setting the population size and the number of iterations refers to inputting the installed capacity of conventional generators, the installed capacity of new energy generators, the scene data of wind, solar, water and load, and the number of iterations for solving; (2) Randomly initialize the number of whale populations; The random initialization of the number of whale populations refers to the random generation of the output ratio scheme of new energy units and conventional units; (3) The whale group currently in the best position for encirclement and capture is the target prey; The target prey is the whale group currently in the best capture position, which means updating the position according to the following mathematical expression with the current best unit ratio scheme: Where t represents the current iteration number; Indicates the optimal position space of the current whale group individuals; represents the position space of the remaining individuals; || represents the absolute value; represents the coefficient; represents a vector that decreases linearly from 2 to 0 during iteration; Represents the distance between the individual position and the optimal individual; Represents a random number between 0 and 1; M is the maximum number of iterations; (4) Whales hunt prey along spiral paths; The whale contracts along the spiral path to hunt prey, which means finding the feasible solution of the optimal unit ratio scheme and hunting prey according to the following mathematical expression: Among them, b is a constant used to define the spiral shape, l is a random number between -1 and 1, and e represents a natural constant; (5) After multiple iterations, output a set of non-inferior solutions; The multiple iterations refer to outputting a non-inferior solution set, which means repeatedly generating and screening the matching schemes and outputting a feasible solution for the optimal unit matching scheme.

5. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 1 is characterized in that: The said maximum ratio of new energy units to conventional units means that under the optimal comprehensive evaluation condition, the proportion of conventional units put into the system is the smallest.

6. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 1 is characterized by: The comprehensive evaluation index for the unit ratio scheme is established, including: a system peak load regulation capability index, a system frequency regulation capability index, a system transient stability index, and a system frequency stability index.

7. The method for configuring power grid power limit by comprehensively considering multiple factors according to claim 6 is characterized by: The peak-shaving capability index of the system, i.e. the peak-to-valley difference, reflects the flexibility of the system in regulating load; The system frequency regulation capability index, i.e., the system frequency regulation fluctuation, is one of the important indicators reflecting the system stability; The system transient stability index reflects the degree to which the amplitude of the unit deviates from the system inertia center exceeds the limit after the expected fault occurs; The system frequency stability index, that is, the variance of the system frequency deviation from the standard frequency, is one of the important indexes for testing system stability.

8. A computer storage medium, characterized in that: The computer storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any one of the methods for configuring power grid power limits that comprehensively considers multiple factors according to claims 1-7 are implemented.

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