CN-122026438-A - Energy storage system optimal configuration method and system for green electricity direct supply scene

CN122026438ACN 122026438 ACN122026438 ACN 122026438ACN-122026438-A

Abstract

The invention relates to an energy storage system optimal configuration method and system for a green electricity direct supply scene, the method comprises the steps of obtaining structural information of a hybrid energy storage system, carrying out optimal solution by adopting a three-dimensional multi-objective optimization model based on capacity, power and site selection, determining an optimal access position of the hybrid energy storage system by using a capacity investment cost of the energy storage system, a voltage sag detection device deployment cost and an electric energy quality loss cost caused by the fact that sensitive load voltage does not reach standards as optimization targets by an upper-layer optimization model, optimizing and determining energy storage capacity and output power configuration by using a lower-layer optimization model by using joint compensation cost and voltage satisfaction indexes of a distributed energy storage and dynamic voltage restorer, and solving the three-dimensional multi-objective optimization model by adopting a self-adaptive particle swarm optimization algorithm. Compared with the prior art, the method and the device can effectively improve the rationality of the access decision of the energy storage system, reduce the configuration cost, and enhance the flexibility and the operation stability of the system in the green electricity direct supply mode.

Inventors

JIANG BENJIAN
WANG YINCHAO
LIU XIN
HAN DONG
SHEN HUI
GU WEN
SHEN JINGJING
ZHANG LITING

Assignees

国网上海市电力公司

Dates

Publication Date: 20260512
Application Date: 20251209

Claims (10)

1. An energy storage system optimal configuration method for a green electricity direct supply scene is characterized by comprising the following steps: Acquiring a power grid topological structure and space-time distribution characteristics of source charges of a hybrid energy storage system, wherein the hybrid energy storage system comprises a hydrogen energy storage unit and an electrochemical energy storage unit which are operated cooperatively; Carrying out optimization solution according to the topological structure and the space-time distribution characteristics of the power grid by adopting a three-dimensional multi-objective optimization model based on capacity, power and site selection, wherein the three-dimensional multi-objective optimization model is divided into an upper-layer optimization model and a lower-layer optimization model, the upper-layer optimization model takes the capacity cost of energy storage equipment, the deployment cost of a voltage sag detection device and the electric energy quality loss cost caused by the fact that the sensitive load voltage does not reach the standard as optimization targets, and determines the optimal access position of a hybrid energy storage system; and solving the three-dimensional multi-objective optimization model by adopting a self-adaptive particle swarm optimization algorithm to obtain an optimization configuration scheme.
2. The energy storage system optimal configuration method for the green electricity direct supply scene according to claim 1 is characterized in that the upper layer optimization model is used for determining an optimal access position of a distributed energy storage system, candidate nodes are primarily screened through an overall sorting method based on power grid topological characteristics and space-time distribution rules of source charges, and an energy storage arrangement scheme with both economy and reliability is determined by comprehensively considering energy storage investment cost and sensitive load voltage crossing performance in combination with typical scene clustering analysis results.
3. The energy storage system optimization configuration method for the green electricity direct supply scene according to claim 1, wherein the expression of the objective function of the upper optimization model is: In the formula, For the objective function of the upper layer optimization model, For the cost of the capacity of the energy storage device, The cost of deploying the device for voltage sag detection, To sensitive the cost of power quality loss caused by the voltage of the load not reaching the standard, , , ,..., Is a node number; And Respectively, are installed at corresponding nodes Is provided.
4. The energy storage system optimizing configuration method for the green electricity direct supply scene according to claim 3, wherein in the calculation process of the capacity cost of the energy storage device, the considered capacity cost and energy consumption of the energy storage device are calculated based on the response behavior of the hybrid energy storage system in the jth voltage sag event, and the corresponding calculation expression is: In the formula, And The capacity and energy consumed by the energy storage device i in j voltage dip events, , The active power and the reactive power output by the energy storage equipment in j times of voltage dip events are shown as n, wherein n is the installation position of the energy storage system; Is the duration of the voltage dip, For the capacity consumed in j slump events, Is the energy dissipated in j voltage dip events.
5. The energy storage system optimal configuration method for the green electricity direct supply scene according to claim 3, wherein the calculation expression of the deployment cost of the voltage sag detection device is as follows: In the formula, The installation cost of the voltage sag detection device i; Is a constant installation cost; Is a layout indicating variable indicating whether or not the voltage sag detection device is installed at the position.
6. The energy storage system optimal configuration method for the green electricity direct supply scene according to claim 3, wherein the calculation expression of the power quality loss cost caused by the fact that the sensitive load voltage does not reach the standard is: In the formula, Is the lower limit of the compliance voltage; Is the voltage cost of the sensitive load g; is the mass cost of the g-th sensitive load node in the transient process; to penalize the nonlinear index.
7. The energy storage system optimizing configuration method for the green electricity direct supply scene according to claim 1, wherein the lower optimizing model is used for determining a capacity configuration ratio of the distributed energy storage system, the capacity, the voltage satisfaction and the compensation cost of the energy storage system are used as multi-objective optimizing functions, the control variables are the energy storage capacity and the power ratio, and an optimal capacity configuration scheme is obtained through global optimizing.
8. The energy storage system optimization configuration method for the green electricity direct supply scene according to claim 7, wherein the expression of the objective function of the lower optimization model is: In the formula, An objective function of the lower layer optimization model; And The BESS and DVR costs of node i, respectively; the voltage satisfaction index is a sensitive load voltage satisfaction index; 、 And For weighting coefficients.
9. The energy storage system optimal configuration method for the green electricity direct supply scene according to claim 1, wherein the particle swarm algorithm adopts an adaptive adjustment strategy for inertia weights in a solving process, increases the inertia weights to enhance global searching capability when particle swarms tend to be concentrated, and decreases the inertia weights to enhance local searching accuracy when the particle swarms tend to be dispersed; the updating expression of the inertia weight is as follows: In the formula, For the ith inertial weight in the kth iteration, In order to adjust the coefficient of the coefficient, For the reference inertial weight in the kth iteration, As an index of particle swarm concentration in the kth iteration, For the aggregation level lower threshold value, Is an upper threshold for aggregation.
10. An energy storage system optimizing configuration system for a green electricity direct supply scene, which is characterized by comprising a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the method according to any one of claims 1 to 9.

Description

Energy storage system optimal configuration method and system for green electricity direct supply scene Technical Field The invention relates to the technical field of energy storage system configuration, in particular to an energy storage system optimal configuration method and system for a green electricity direct supply scene. Background In recent years, with the wide application of various sensitive load devices based on computer and microprocessor control, the requirements of the power grid on the power quality are continuously improved. In power distribution systems, a large number of non-linear loads, impact loads, and distributed power source accesses raise a variety of power quality problems, wherein voltage sag has become one of the key factors affecting safe and stable operation of power equipment. The existing voltage sag management method mainly comprises the schemes of energy storage technology, constant voltage transformers, solid state switches, inverters, joint compensation and the like. The Dynamic Voltage Restorer (DVR) is used as an effective compensation means for sensitive loads, and has good response characteristics in the process of suppressing sag. However, the compensatory performance of DVRs is limited by their internal energy storage capacity, and it is difficult to cope with voltage sag events of long duration or of greater magnitude. In recent years, with the progress of battery technology and the gradual decrease of cost, distributed energy storage systems have been rapidly developed. The energy storage system has stronger active and reactive power regulation capability, and plays an important role in stabilizing power fluctuation, improving voltage quality and the like. However, the investment cost of the distributed energy storage device is high, and the configuration position and capacity of the distributed energy storage device have significant influence on economy and compensation effects, so how to optimize the site selection and operation strategy of the energy storage system is a key problem for realizing participation in voltage sag control. Research has been conducted on energy storage optimization configuration and control strategies. For example, there are literature proposals for constructing a two-layer multi-objective optimization model and solving by adopting a particle swarm algorithm with the aim of minimizing energy storage investment cost and voltage deviation, research on optimizing the site selection and capacity allocation of an energy storage system from the viewpoint of voltage improvement by a time sequence sensitivity analysis method, and furthermore, an unbalanced power distribution network energy storage sequence configuration method based on voltage sensitivity analysis is also proposed for optimizing the system layout from the viewpoint of improving voltage supporting capability. However, the current research is limited to a single energy storage form or a fixed control strategy, and a systematic method for green electricity direct supply scene, fusion capacity-power-site selection collaborative optimization and joint compensation strategy is not available. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide the energy storage system optimal configuration method and the energy storage system optimal configuration system for the green electricity direct supply scene, which can select reasonable access positions for the energy storage system, reduce capacity configuration requirements, and improve compensation effects through a combined compensation strategy, thereby reducing the overall investment cost of compensation equipment. The aim of the invention can be achieved by the following technical scheme: an energy storage system optimal configuration method for a green electricity direct supply scene comprises the following steps: Acquiring a power grid topological structure and space-time distribution characteristics of source charges of a hybrid energy storage system, wherein the hybrid energy storage system comprises a hydrogen energy storage unit and an electrochemical energy storage unit which are operated cooperatively; Carrying out optimization solution according to the topological structure and the space-time distribution characteristics of the power grid by adopting a three-dimensional multi-objective optimization model based on capacity, power and site selection, wherein the three-dimensional multi-objective optimization model is divided into an upper-layer optimization model and a lower-layer optimization model, the upper-layer optimization model takes the capacity cost of energy storage equipment, the deployment cost of a voltage sag detection device and the electric energy quality loss cost caused by the fact that the sensitive load voltage does not reach the standard as optimization targets, and determines the optimal access position of a hybrid energy storage system; and solving the three-d