CN-121980897-A - Construction method and device of optical storage equivalent model and electronic equipment

CN121980897ACN 121980897 ACN121980897 ACN 121980897ACN-121980897-A

Abstract

The application discloses a construction method, a construction device and electronic equipment of an optical storage equivalent model, which are applied to an optical storage system, and comprise the steps of determining a second parameter set according to a first parameter set of the optical storage system, which is acquired in advance; determining a simulation step length and an objective function according to the output power of the optical storage system, determining the fitness between the first parameter set and the second parameter set based on the objective function, judging whether the fitness and the current iteration number meet a preset threshold, updating the second parameter set based on the simulation step length if the fitness does not meet the preset threshold or the current iteration number does not meet the preset threshold, and constructing an optical storage equivalent model according to the current second parameter set. According to the application, the core mechanism of the moss optimization algorithm is combined with the requirements of the optical storage joint frequency modulation equivalent modeling, so that the accurate optimization of the equivalent model parameters is realized.

Inventors

CHENG YAN
SUN LIQUN
CAI HE
YANG SONG
WANG NAN
SUN SHUMIN
WANG SHIBAI
Wang Gongrun
GE YU
WANG CHENGLONG
ZHOU GUANGQI
GUAN YIFEI

Assignees

国网山东省电力公司电力科学研究院

Dates

Publication Date: 20260505
Application Date: 20251128

Claims (16)

1. The construction method of the optical storage equivalent model is characterized by being applied to an optical storage system, and comprises the following steps: s102, determining a second parameter set according to a first parameter set of the optical storage system, which is acquired in advance; s104, determining a simulation step length and an objective function according to the output power of the optical storage system, which is acquired in advance; s106, determining the adaptability between the first parameter set and the second parameter set based on the objective function; s108, judging whether the fitness and the current iteration number meet a preset threshold value or not; S110, if the adaptability does not meet a preset threshold value or the current iteration number does not meet the preset threshold value, updating the second parameter set based on the simulation step length, and returning to S106; s112, constructing an optical storage equivalent model according to the current second parameter set.
2. The method for constructing an optical storage equivalent model according to claim 1, wherein S102 comprises: And carrying out random proportion processing on the first parameter set based on a preset proportion relation to generate a second parameter set.
3. The method for constructing an optical storage equivalent model according to claim 2, wherein S102 further comprises: eliminating the dimension difference of the first parameter set and the second parameter set; And unifying the measurement spaces of the first parameter set and the second parameter set.
4. The method for constructing an optical storage equivalent model according to claim 1, wherein S104 comprises: s104-2, determining a simulation step length according to the pre-acquired output power of the optical storage system before and after frequency modulation; s104-4, determining an objective function according to the pre-acquired output power before and after frequency modulation of the optical storage system.
5. The method for constructing an optical storage equivalent model according to claim 4, wherein S104-2 comprises: S104-2-2, pre-acquiring output power of the optical storage system before and after frequency modulation based on a preset time interval; S104-2-4, determining a power difference value according to the output power before and after frequency modulation; S104-2-6, determining a simulation step size according to the power difference value.
6. The method for constructing an optical storage equivalent model according to claim 5, characterized in that S104-4 comprises: S104-4-2, pre-acquiring output power before and after frequency modulation of the optical storage system based on a preset time interval, and determining a power sequence before frequency modulation and a power sequence after frequency modulation; s104-4-4, respectively performing derivative processing on the pre-frequency modulation power sequence and the post-frequency modulation power sequence; S104-4-6, calculating a loss coefficient between the frequency modulated power sequence after derivative processing and the frequency modulated power sequence after derivative processing; S104-4-8, determining a transient loss weight coefficient according to a preset regression coefficient and the loss coefficient; S104-4-10, determining an objective function between the pre-frequency modulation optical storage system and the post-frequency modulation optical storage system according to the transient loss weight coefficient.
7. The method for constructing an optical storage equivalent model according to claim 6, characterized in that S106 comprises: and determining the adaptability between the first parameter set and the second parameter set according to the preset weight, the objective function between the pre-frequency modulation optical storage system and the post-frequency modulation optical storage system, and the first parameter set and the current second parameter set.
8. The method for constructing an optical storage equivalent model according to claim 7, wherein S110 is implemented based on an MGO algorithm, and S110 includes: s110-2, determining a parameter evolution direction of the second parameter set; S110-4, performing global spore diffusion search and cryptobiotic mechanism processing on the second parameter set based on the parameter evolution direction and the simulation step length to obtain a plurality of groups of processed parameter sets; S110-6, calculating the adaptability between each group of processed parameter sets and the first parameter set; S110-8, combining the optimal individual iteration rule of the MGO algorithm, and taking the processed parameter set with the minimum adaptability as a current second parameter set.
9. The method for constructing an optical storage equivalent model according to claim 1, wherein the optical storage system comprises a photovoltaic system and an energy storage system; The first set of parameters includes: The method comprises the steps of reducing a load reserve fitting coefficient of a photovoltaic system, reducing a load self-reserve rate of the photovoltaic system, an upper frequency modulation triggering threshold value of the photovoltaic system, a lower frequency modulation triggering threshold value of the photovoltaic system, an upper frequency modulation dead zone boundary of the photovoltaic system, a lower frequency modulation dead zone boundary of the photovoltaic system, an upper frequency modulation boundary of the photovoltaic system, a lower frequency modulation boundary of the photovoltaic system, a short circuit current coefficient of the photovoltaic system, a left frequency modulation control gain of the photovoltaic system, a right frequency modulation control gain of the photovoltaic system, an upper boundary of an energy storage system starting SOC self-regulating function, a lower boundary of the energy storage system starting SOC self-regulating function, equivalent impedance of a transformer in a photovoltaic system, equivalent impedance of a current collecting line of the transformer in the photovoltaic system and equivalent irradiation intensity of the transformer in the photovoltaic system.
10. The device for constructing the optical storage equivalent model is characterized by comprising the following components: The first construction module is used for determining a second parameter set according to a first parameter set of the optical storage system, which is acquired in advance; The second construction module is used for determining simulation step length and objective function according to the output power of the optical storage system which is acquired in advance; a third building module for determining a fitness between the first set of parameters and the second set of parameters based on the objective function; A fourth construction module, configured to determine whether the fitness and the current iteration number meet a preset threshold; a fifth construction module, configured to update the second parameter set based on the simulation step length if the fitness does not meet a preset threshold or the current iteration number does not meet a preset threshold, and return to S106; And the sixth construction module is used for constructing the optical storage equivalent model according to the current second parameter set.
11. The apparatus for constructing an optical storage equivalent model according to claim 10, wherein the first construction module is further configured to perform random scaling on the first parameter set based on a preset scaling relationship to generate the second parameter set.
12. The device for constructing an optical storage equivalent model according to claim 10, wherein the second construction module is further configured to determine a simulation step size according to pre-acquired output powers before and after frequency modulation of the optical storage system, and determine an objective function according to pre-acquired output powers before and after frequency modulation of the optical storage system.
13. The device for constructing an optical storage equivalent model according to claim 10, characterized in that the third construction module is further configured to determine the fitness between the first parameter set and the second parameter set according to a preset weight, an objective function between the optical storage system before frequency modulation and the optical storage system after frequency modulation, the first parameter set and the current second parameter set.
14. The device for constructing an optical storage equivalent model according to claim 10, wherein the fifth construction module is further configured to determine a parameter evolution direction of the second parameter set, perform global spore diffusion search and saphenous mechanical processing on the second parameter set based on the parameter evolution direction and the simulation step size to obtain a plurality of groups of processed parameter sets, calculate an fitness between each group of processed parameter sets and the first parameter set, and use the processed parameter set with the smallest fitness as a current second parameter set in combination with an optimal individual iteration rule of an MGO algorithm.
15. An electronic device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, the processor executing the machine executable instructions to implement the method of constructing an optical storage equivalent model of any one of claims 1-9.
16. A machine-readable storage medium storing machine-executable instructions which, when invoked and executed by a processor, cause the processor to implement a method of constructing an optical storage equivalence model according to any one of claims 1-9.

Description

Construction method and device of optical storage equivalent model and electronic equipment Technical Field The application relates to the technical field of model construction, in particular to a construction method and device of an optical storage equivalent model and electronic equipment. Background The large-scale clustered optical storage system plays an increasingly important role in practical application of a power distribution network, and one of the key problems of cluster control and cluster adjustment of the power distribution network is the adaptability of cluster equivalent modeling, which relates to the accuracy of a cluster control and cluster adjustment optimization result. The parameter optimization process in the current cluster equivalent modeling does not consider the limiting conditions of an objective function and an optimization function in the model, and influences the optimization accuracy of the cluster control cluster. In order to obtain cluster equivalent modeling which is more suitable for group control group adjustment optimization, the invention provides a construction method, a device and electronic equipment of an adaptive light storage equivalent model, which are beneficial to obtaining more accurate optimization results of the group control group adjustment of a power distribution network and improving the economical efficiency and reliability of the operation of the power distribution network. Disclosure of Invention In view of the above, the application aims to provide a construction method, a construction device and electronic equipment of an adaptive light storage equivalent model, which are beneficial to obtaining more accurate optimization results of group control and group adjustment of a power distribution network and improve the economical efficiency and reliability of the operation of the power distribution network. In a first aspect, the embodiment of the invention provides a construction method of an optical storage equivalent model, which is applied to an optical storage system, and comprises the steps of S102, determining a second parameter set according to a first parameter set of the optical storage system, S104, determining a simulation step length and an objective function according to output power of the optical storage system, S106, determining the fitness between the first parameter set and the second parameter set based on the objective function, S108, judging whether the fitness and the current iteration number meet a preset threshold, S110, updating the second parameter set based on the simulation step length if the fitness does not meet the preset threshold or the current iteration number does not meet the preset threshold, and returning to S106, and S112, constructing the optical storage equivalent model according to the second parameter set. Further, S102 comprises performing random proportion processing on the first parameter set based on a preset proportion relation to generate a second parameter set. Further, S102 also includes eliminating dimension differences of the first parameter set and the second parameter set, and unifying measurement spaces of the first parameter set and the second parameter set. Further, S104 comprises S104-2, determining a simulation step length according to pre-acquired output power before and after frequency modulation of the optical storage system, and S104-4, determining an objective function according to pre-acquired output power before and after frequency modulation of the optical storage system. Further, the step S104-2 comprises the step S104-2-2 of acquiring the output power before and after frequency modulation of the optical storage system in advance based on a preset time interval, the step S104-2-4 of determining a power difference value according to the output power before and after frequency modulation, and the step S104-2-6 of determining a simulation step according to the power difference value. Further, the method comprises the steps of S104-4-2, S104-4-4, calculating loss coefficients between the pre-frequency modulation power sequence and the post-frequency modulation power sequence after the derivative processing, S104-4-8, determining transient loss weight coefficients according to preset regression coefficients and the loss coefficients, and S104-4-10, determining objective functions between the pre-frequency modulation optical storage system and the post-frequency modulation optical storage system according to the transient loss weight coefficients, wherein the pre-frequency modulation power sequence and the post-frequency modulation power sequence are subjected to derivative processing respectively, and the S104-4-6. Further, S106 includes determining a fitness between the first parameter set and the second parameter set according to a preset weight, an objective function between the pre-frequency-modulation optical storage system and the post-frequency-modulation optical storage system, the