CN-121984046-A - Distributed energy storage optimal configuration method and system for overload management of distribution transformer area

CN121984046ACN 121984046 ACN121984046 ACN 121984046ACN-121984046-A

Abstract

A distributed energy storage optimization configuration method and a system for temporary heavy overload treatment of a distribution transformer area acquire historical load data of the distribution transformer area, reconstruct load data of a day where a temporary heavy overload event is located, form a temporary heavy overload scene by the reconstructed load data, a distribution network topological structure and load access nodes, calculate dynamic weight coefficients of the temporary heavy overload event of each node and voltage sensitivity coefficients of each node in each temporary heavy overload scene, establish voltage deviation penalty costs based on the dynamic weight coefficients and the voltage sensitivity coefficients, form total economic cost by energy storage investment operation and maintenance costs, voltage deviation penalty costs, various relaxation variable penalty costs and external power grid purchase costs, and iteratively solve a distributed energy storage configuration scheme enabling the total economic cost to be minimum under the constraint condition of the distribution network to realize the optimal configuration of the distributed energy storage system for the temporary heavy overload treatment.

Inventors

YANG WEN
CAI DELONG
CAI XIAOFENG
LI YUELONG
FAN JIA
DAI ZHENGZHOU
Tang Congwei
ZHU SHUAI
Yan Shiye
LU MINAN
ZHUANG JUN
WANG QI
WANG DESHUN
ZHANG FEIFEI
GAN LU
GU ZHIJUN

Assignees

国网上海市电力公司
国网上海能源互联网研究院有限公司

Dates

Publication Date: 20260505
Application Date: 20251211

Claims (12)

1. The distributed energy storage optimal configuration method for temporary heavy overload treatment of the power distribution area is characterized by comprising the following steps of: The method comprises the steps of obtaining historical load data of a distribution transformer area, reconstructing load data of a day where a temporary heavy overload event is located, forming a temporary heavy overload scene by the reconstructed load data, a distribution network topological structure and load access nodes, calculating dynamic weight coefficients of the temporary heavy overload event of each node and voltage sensitivity coefficients of each node in each temporary heavy overload scene, establishing voltage deviation punishment cost based on the dynamic weight coefficients and the voltage sensitivity coefficients, forming total economic cost by energy storage investment operation and maintenance cost, voltage deviation punishment cost, various relaxation variable punishment cost and external power grid electricity purchasing cost, and iteratively solving a distributed energy storage configuration scheme enabling the total economic cost to be minimum under the constraint condition of a power distribution network.
2. The distributed energy storage optimization configuration method for temporary heavy overload management of power distribution area according to claim 1, wherein, And when the current iteration solution is carried out, determining predicted load data of the distribution area, reconstructing the load data of the day where the temporary heavy overload event is located again, forming a predicted heavy overload scene according to the reconstructed load data, the distribution network topological structure and the load access nodes, calculating predicted weight coefficients of the temporary heavy overload event of each node in the predicted heavy overload scene, correcting the voltage sensitivity coefficients according to the deviation of the predicted weight coefficients and the dynamic weight coefficients, updating the voltage deviation penalty cost by utilizing the predicted weight coefficients and the corrected voltage sensitivity coefficients, and ending the iteration when the deviation of the predicted weight coefficients and the dynamic weight coefficients is smaller than a set threshold value to obtain the distributed energy storage optimal configuration scheme for treating the temporary heavy overload of the distribution area.
3. The distributed energy storage optimization configuration method for temporary heavy overload management of power distribution area according to claim 2, wherein, Marking a temporary heavy overload event in the historical load data of the distribution transformer area, and determining the duration of the temporary heavy overload event; The load data of the duration time of the temporary heavy overload event is unchanged, and loads outside the duration time of the temporary heavy overload event all take the load data of the history synchronous normal days to obtain the daily load data after reconstruction.
4. The distributed energy storage optimization configuration method for temporary heavy overload treatment of power distribution area according to claim 3, wherein, Marked as a temporary heavy overload event when the following conditions are simultaneously met: 1) The sudden condition is that the initial moment of the temporary heavy overload event is satisfied for the first time At the previous time When the load apparent power increase of-1 is not less than 30% of the rated capacity of the transformer, The starting time for a temporary heavy overload event is as follows: In the formula, For the moment of initiation of temporary heavy overload event At the previous time The load of-1 is apparent to the power increase, For the moment of initiation of temporary heavy overload event Is used for the load apparent power of the (c), Rated capacity of the transformer for the distribution area; 2) Peak load condition, load apparent power with n or more consecutive time intervals Not less than the rated capacity of the transformer The number of times of the number of times, N is a positive integer greater than 1, and the time interval is more than or equal to 1 hour; 3) A temporary condition that the duration of the temporary heavy overload event should not be greater than 6 hours; 6 In the formula, Duration for temporary heavy overload event; Is the starting time of the temporary heavy overload event; is the end time of the temporary heavy overload event.
5. The distributed energy storage optimization configuration method for temporary heavy overload management of power distribution area according to claim 1, wherein, The dynamic weight coefficient is shown as follows: In the formula, 、、 The start time, end time and duration of the temporary heavy overload event respectively, Indicating time of day The duration of the temporary heavy overload event; Is a node At the moment of time Dynamic weight coefficients of (2); Is a node At the moment of time Is added up to the accumulated heavy overload time; Adjusting a coefficient for the temporary heavy overload time length; Taking the ratio of the average value of the load of the duration of the temporary heavy overload event to the average value of the normal load as the temporary heavy overload multiple in the reconstructed daily load data; And adjusting the coefficient for the temporary heavy overload multiple.
6. The distributed energy storage optimization configuration method for temporary heavy overload treatment of power distribution area according to claim 5, wherein, Based on the dynamic weight coefficient and the voltage sensitivity coefficient, a voltage deviation penalty cost is established as shown in the following formula: In the formula, The cost is penalized for the voltage deviation, The cost is penalized for the deviation of the unit voltage, For the duration of the daily operation of the system, As a total number of nodes, Is that Time node Is used for the voltage of the (c) transformer, Is a node Is used for the voltage sensitivity coefficient of (a).
7. The distributed energy storage optimization configuration method for temporary heavy overload management of power distribution area according to claim 1, wherein, Constructing a relaxation variable penalty cost as shown in the following formula: In the formula, Penalty costs are penalized for the relaxation variable bias, 、、 The relaxation penalty coefficients are voltage, active power and reactive power, respectively; 、 respectively t time node Voltage relaxation variable, active power relaxation variable, reactive power relaxation variable.
8. The distributed energy storage optimization configuration method for temporary heavy overload management of power distribution area according to claim 2, wherein, First, the When the iteration is solved, the ratio of the difference value between the prediction weight coefficient and the dynamic weight coefficient to the dynamic weight coefficient is calculated According to Fitting correction factors for voltage sensitivity coefficients using exponential functions The following formula is shown: 。
9. a distributed energy storage optimization configuration system for temporary heavy overload management in a distribution area, for implementing the method of any one of claims 1 to 8, comprising: The scene generation module is used for acquiring historical load data of the distribution transformer area, reconstructing load data of a day where the temporary overload event is located, and forming a temporary overload scene by the reconstructed load data, the distribution network topological structure and the load access node; The coefficient calculation module is used for calculating the dynamic weight coefficient of the temporary heavy overload event of each node and the voltage sensitivity coefficient of each node in each temporary heavy overload scene; The system comprises an optimization configuration module, an energy storage investment operation and maintenance cost, a voltage deviation punishment cost, various relaxation variable punishment costs and an external power grid electricity purchasing cost, wherein the optimization configuration module is used for establishing a voltage deviation punishment cost based on a dynamic weight coefficient and a voltage sensitivity coefficient, and the total economic cost is formed by the energy storage investment operation and maintenance cost, the voltage deviation punishment cost, the various relaxation variable punishment cost and the external power grid electricity purchasing cost.
10. The distributed energy storage optimization configuration system for temporary heavy overload management in a distribution area according to claim 9, wherein, The optimization configuration module is further used for determining predicted load data of the distribution area based on a distributed energy storage configuration scheme obtained by the current iteration solution when each iteration solution is carried out, reconstructing the load data of the day where the temporary heavy overload event is located again, forming a predicted heavy overload scene according to the reconstructed load data, the distribution network topological structure and the load access node, calculating predicted weight coefficients of the temporary heavy overload event of each node in the predicted heavy overload scene, correcting the voltage sensitivity coefficients according to the deviation of the predicted weight coefficients and the dynamic weight coefficients, updating voltage deviation penalty cost by utilizing the predicted weight coefficients and the corrected voltage sensitivity coefficients, and ending the iteration when the deviation of the predicted weight coefficients and the dynamic weight coefficients is smaller than a set threshold value to obtain the distributed energy storage optimization configuration scheme for temporary heavy overload management of the distribution area.
11. A terminal comprises a processor and a storage medium, and is characterized in that: The storage medium is used for storing instructions; the processor being operative according to the instructions to perform the steps of the method of any one of claims 1-8.
12. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any one of claims 1-8.

Description

Distributed energy storage optimal configuration method and system for overload management of distribution transformer area Technical Field The invention belongs to the technical field of distributed energy storage configuration of distribution networks, and particularly relates to a distributed energy storage optimization configuration method and system for temporary heavy overload treatment of a distribution area. Background With the increase of urban and rural residential electricity demand and the large-scale access of the charging piles of the new energy automobiles and the increase of the in-situ consumption proportion of the distributed photovoltaic, the phenomenon of temporary heavy overload frequently occurs in the distribution area, so that the service lives of equipment such as distribution transformers and circuits are shortened, the power interruption is possibly caused, and the electricity reliability of users is influenced. The traditional temporary heavy overload treatment means (such as line capacity increase, load transfer and temporary load shedding) can play a role in a specific scene, but have the problems of high investment cost, response lag, insufficient flexibility and the like, and the distributed energy storage becomes a key technical direction of temporary heavy overload treatment by virtue of the flexible and controllable characteristic. In the prior art, a great deal of researches on load peak-valley adjustment, new energy output fluctuation stabilization and the like of a distribution area are carried out on distributed energy storage optimization, but few researches are carried out on deep exploration aiming at distributed energy storage optimization configuration under a specific scene of temporary heavy overload, so that the problem that the conventional configuration scheme is difficult to accurately match with randomness and short-term characteristics of the temporary overload and cannot be effectively solved. Disclosure of Invention In order to solve the defects in the prior art, the invention provides the distributed energy storage optimization configuration method and system for the overload management of the distribution area, which fully considers the differential requirements of sensitive load and conventional load of the distribution area on voltage quality, takes account of key factors in aspects such as network topology structure, voltage characteristics, line power supply bearing capacity, energy storage investment operation and maintenance economic cost, charge and discharge operation characteristics of the distribution area, and constructs a distributed energy storage configuration optimization model to realize the distributed energy storage system optimization configuration for temporary heavy overload management. The invention adopts the following technical scheme. The invention provides a distributed energy storage optimization configuration method for temporary heavy overload treatment of a power distribution area, which comprises the following steps: The method comprises the steps of obtaining historical load data of a distribution transformer area, reconstructing load data of a day where a temporary heavy overload event is located, forming a temporary heavy overload scene by the reconstructed load data, a distribution network topological structure and load access nodes, calculating dynamic weight coefficients of the temporary heavy overload event of each node and voltage sensitivity coefficients of each node in each temporary heavy overload scene, establishing voltage deviation punishment cost based on the dynamic weight coefficients and the voltage sensitivity coefficients, forming total economic cost by energy storage investment operation and maintenance cost, voltage deviation punishment cost, various relaxation variable punishment cost and external power grid electricity purchasing cost, and iteratively solving a distributed energy storage configuration scheme enabling the total economic cost to be minimum under the constraint condition of a power distribution network. And when the current iteration solution is carried out, determining predicted load data of the distribution area, reconstructing the load data of the day where the temporary heavy overload event is located again, forming a predicted heavy overload scene according to the reconstructed load data, the distribution network topological structure and the load access nodes, calculating predicted weight coefficients of the temporary heavy overload event of each node in the predicted heavy overload scene, correcting the voltage sensitivity coefficients according to the deviation of the predicted weight coefficients and the dynamic weight coefficients, updating the voltage deviation penalty cost by utilizing the predicted weight coefficients and the corrected voltage sensitivity coefficients, and ending the iteration when the deviation of the predicted weight coefficients and the dynamic weight