CN-122000975-A - Hybrid energy storage capacity planning method and related device for low-voltage distribution network

CN122000975ACN 122000975 ACN122000975 ACN 122000975ACN-122000975-A

Abstract

The invention provides a method and a related device for planning hybrid energy storage capacity of a low-voltage power distribution network, and belongs to the technical field of energy storage of low-voltage power distribution networks in power systems. According to the invention, the year-by-year influence of social economic development on energy storage income is fully considered in the energy storage configuration optimization model, so that the actual income level of energy storage in the whole life cycle can be reflected more truly and accurately, the problem of larger income calculation deviation caused by the fact that social economic development factors are not considered in the traditional energy storage capacity planning is effectively solved, meanwhile, the investment return rate calculation and the economic evaluation are carried out on the preliminary energy storage configuration scheme, and the iterative adjustment is carried out on the configuration scheme when the economic requirement is not met, so that the finally obtained energy storage configuration scheme can be ensured to have reliable economic feasibility and engineering floor property, and the rationality and the practicability of the hybrid energy storage capacity planning of the low-voltage distribution network are obviously improved.

Inventors

ZHU JUN
ZHAN RUI
HE RAN
BAI XUE

Assignees

广东电网有限责任公司佛山供电局

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. The method for planning the hybrid energy storage capacity of the low-voltage power distribution network is characterized by comprising the following steps of: for a low-voltage power distribution network area needing to be additionally provided with energy storage, determining the type of the energy storage to be additionally provided, and obtaining energy storage parameters; Based on the power grid parameters and the energy storage parameters of the low-voltage power distribution network area, solving a pre-built energy storage configuration optimization model to obtain a preliminary energy storage configuration scheme, wherein the energy storage configuration optimization model aims at maximizing the difference between energy storage benefits and energy storage cost; And calculating the return on investment of the preliminary energy storage configuration scheme, evaluating the economy, and if the requirement of the economy is not met, adjusting the energy storage parameters and re-solving the energy storage configuration optimization model until the requirement of the economy is met, thereby obtaining the final energy storage configuration scheme.
2. The method for planning hybrid energy storage capacity of a low voltage power distribution network according to claim 1, wherein the mathematical expression of the energy storage configuration optimization model is: ; Wherein F is an objective function, B j is the demand reduction income of the jth month, m is the month number in the planning period, B i is the peak clipping and valley filling income of the ith day, and d is the day in the planning period; The energy storage system is characterized in that the energy storage system is a social development coefficient of the Y-th year, Y is the service life of energy storage, and C is the monthly energy storage cost; The demand reduction benefits are: ; in the formula, The unit price is the basic electricity charge; And The maximum load value of the month before the energy storage is added and the maximum load value of the month after the energy storage is added are respectively the jth month; The peak clipping and valley filling benefits are as follows: ; Wherein t is a time index; The real-time running power of the hybrid energy storage is configured for the ith moment of the ith day; The peak-valley time-of-use electricity price corresponding to the t-th moment; is the interval length of time; the social development coefficients are: ; in the formula, Is the inflation rate; Is the discount rate; The monthly conversion energy storage cost is as follows: ; in the formula, 、 The investment unit price of each kilowatt hour of the storage unit capacity of the storage battery and the super capacitor is respectively; 、 The purchase unit price of each kilowatt of energy stored by the storage battery and the super capacitor is respectively; 、 The operation and maintenance cost of each kilowatt of energy stored by the storage battery and the super capacitor is respectively; And Rated capacities respectively configured for the storage battery and the super capacitor; And And rated power of the storage battery and the super capacitor are respectively configured.
3. The method of claim 2, wherein determining the real-time operating power of the hybrid energy storage using a scene linearization remodeling method comprises: performing linear transformation on a power fluctuation curve of the hybrid energy storage in a typical scene to obtain: ; in the formula, For the real-time running power vector of the hybrid energy storage on the i-th day, The energy storage real-time power vector corresponds to the o-th typical scene; A vector with all elements being 1; 、 Representing coefficients for linearity; Is the remainder; The linear transformation result optimally approximates to the power fluctuation curves of all natural scenes in the same class through a least square method, and the power fluctuation curves of the hybrid energy storage under the natural scenes are obtained; and determining the real-time operation power of the hybrid energy storage based on the power fluctuation curve in the natural scene.
4. The method for planning hybrid energy storage capacity of low-voltage distribution network according to claim 3, wherein the method for optimizing the linear transformation result to approximate the power fluctuation curves of all natural scenes in the same class by the least square method comprises the following steps: constructing an optimization problem of linear representation coefficients by taking the minimum sum of squares of all elements of the linear transformation remainder as an optimization target; Converting the optimization problem into an optimal approximate solution problem of a linear equation set; Solving the linear equation set by adopting a weighted recursive least square identification algorithm with forgetting factors to obtain a linear representation coefficient; And determining a linear mapping relation between the typical scene and the natural scene based on the linear representation coefficient obtained by solving so as to realize optimal approximation of power fluctuation curves of all natural scenes in the same class.
5. The method for hybrid energy storage capacity planning of a low voltage power distribution network according to claim 4, wherein the mathematical expression of the weighted recursive least squares identification algorithm with forgetting factors is: ; in the formula, And Linear representation coefficient estimation values at time t and time t-1 respectively; The energy storage real-time power value is t hours in the i-th day of the whole year; Regression vector representing t hours on day i of the year Is a transpose of (2); is a gain matrix; And Covariance matrices at time t and time t-1, respectively; Is a forgetting factor; Is a unit matrix; wherein, the calculation expression of the forgetting factor is as follows: ; in the formula, Forgetting factor for the kth iteration; For the state of charge of the battery at time t, And The lower limit value and the upper limit value of the charge state of the storage battery respectively.
6. A method of planning a hybrid energy storage capacity of a low voltage distribution network according to claim 3, wherein the exemplary scenario is generated by modifying a k-means clustering algorithm to cluster daily load data of a user, and comprises: based on the power user characteristic index, carrying out characteristic dimension reduction processing on the normalized user daily load curve, extracting characteristic indexes reflecting the power consumption behaviors of the user all day and time period, and forming a clustering characteristic data set; Based on the cluster characteristic data set, different cluster numbers are tried, and candidate cluster results corresponding to the different cluster numbers are generated; Carrying out quantitative evaluation on the candidate clustering result by using a validity evaluation index, and selecting the clustering number corresponding to the maximum validity evaluation index to determine the optimal clustering number; and taking a daily load curve corresponding to a clustering center under the optimal clustering number as a typical daily load curve, wherein each typical daily load curve corresponds to one type of typical scene.
7. The method for planning hybrid energy storage capacity of a low voltage power distribution network according to claim 6, wherein the mathematical expression of the effectiveness evaluation index is: ; in the formula, N is the total number of samples subjected to dimension reduction by the main component, k is the clustering number, To spread the traces of the matrix between different classes of samples obtained after dimension reduction, For the trace of the intra-class dispersion matrix corresponding to the s-th power load characteristic, And S is the index number of the power consumer characteristics.
8. The utility model provides a low voltage distribution network hybrid energy storage capacity planning device which characterized in that includes: The energy storage type determining module is used for determining the energy storage type to be additionally installed for a low-voltage power distribution network area needing to additionally install energy storage and obtaining energy storage parameters; The energy storage configuration optimization solving module is used for solving a pre-built energy storage configuration optimization model based on the power grid parameters and the energy storage parameters of the low-voltage power distribution network area to obtain a preliminary energy storage configuration scheme, wherein the energy storage configuration optimization model aims at maximizing the difference between energy storage benefits and energy storage costs; And the energy storage scheme determining module is used for calculating the return on investment of the preliminary energy storage configuration scheme, evaluating the economy, adjusting the energy storage parameters if the requirement of the economy is not met, and re-solving the energy storage configuration optimizing model until the requirement of the economy is met, thereby obtaining the final energy storage configuration scheme.
9. A computer device, the device comprising a processor and a memory: the memory is used for storing a computer program and sending instructions of the computer program to the processor; the processor executes a method for planning hybrid energy storage capacity of a low-voltage distribution network according to the instructions of the computer program.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements a method for planning hybrid energy storage capacity of a low voltage distribution network according to any of claims 1-7.

Description

Hybrid energy storage capacity planning method and related device for low-voltage distribution network Technical Field The invention belongs to the technical field of energy storage of low-voltage distribution networks in power systems, and particularly relates to a method and a related device for planning hybrid energy storage capacity of a low-voltage distribution network. Background In modern power systems, with the wide access of distributed energy sources and the increase of the requirements of users on the quality of electric energy, energy storage technology plays an increasingly important role in power grid operation and planning as an effective regulating means. The energy storage system can stabilize power fluctuation, improve electric energy quality, optimize power grid operation scheduling and the like, and has important significance for improving stability and reliability of a power grid. In a low-voltage distribution network, configuration planning of energy storage is important. The accurate and reasonable energy storage capacity planning can effectively cope with the change of the user load, and the running efficiency and the economic benefit of the power grid are improved. At present, various methods are commonly used for carrying out power grid risk identification and risk analysis, so as to plan the energy storage capacity. In the traditional energy storage capacity planning method, the adopted energy storage full life cycle cost model is mostly simplified, the actual influence of social and economic development factors on energy storage capacity planning cannot be fully considered, and the benefit change of energy storage in the long-term operation process cannot be truly reflected. The energy storage configuration scheme obtained on the basis often has deviation with the economic benefit of actual engineering, and the economic rationality and the floor feasibility of the configuration result are difficult to ensure, so that the actual requirement of the low-voltage power distribution network hybrid energy storage planning cannot be met. Disclosure of Invention Based on the foregoing, it is necessary to provide a hybrid energy storage capacity planning method and related device for a low-voltage power distribution network. In a first aspect, the present invention provides a method for planning hybrid energy storage capacity of a low-voltage power distribution network, including the following steps: for a low-voltage power distribution network area needing to be additionally provided with energy storage, determining the type of the energy storage to be additionally provided, and obtaining energy storage parameters; based on the power grid parameters and the energy storage parameters of the low-voltage power distribution network area, solving a pre-built energy storage configuration optimization model to obtain a preliminary energy storage configuration scheme, wherein the energy storage configuration optimization model aims at maximizing the difference between energy storage benefits and energy storage costs; And calculating the return on investment of the preliminary energy storage configuration scheme, evaluating the economy, and if the requirement of the economy is not met, adjusting the energy storage parameters and re-solving the energy storage configuration optimization model until the requirement of the economy is met, thereby obtaining the final energy storage configuration scheme. Further, the mathematical expression of the energy storage configuration optimization model is: ; Wherein F is an objective function, B j is the demand reduction income of the jth month, m is the month number in the planning period, B i is the peak clipping and valley filling income of the ith day, and d is the day in the planning period; The energy storage system is characterized in that the energy storage system is a social development coefficient of the Y-th year, Y is the service life of energy storage, and C is the monthly energy storage cost; The demand reduction benefits are: ; in the formula, The unit price is the basic electricity charge; And The maximum load value of the month before the energy storage is added and the maximum load value of the month after the energy storage is added are respectively the jth month; The peak clipping and valley filling benefits are as follows: ; Wherein t is a time index; The real-time running power of the hybrid energy storage is configured for the ith moment of the ith day; The peak-valley time-of-use electricity price corresponding to the t-th moment; is the interval length of time; the social development coefficients are: ; in the formula, Is the inflation rate; Is the discount rate; The monthly conversion energy storage cost is as follows: ; in the formula, 、The investment unit price of each kilowatt hour of the storage unit capacity of the storage battery and the super capacitor is respectively;、 The purchase unit price of each kilowatt of energy stor