Open Access

ARTICLE

Centralized-Distributed Scheduling Strategy of Distribution Network Based on Multi-Temporal Hierarchical Cooperative Game

Guoqing Li, Jianing Li, Kefei Yan, Jing Bian^*

College of Electrical Engineering, Northeast Electric Power University, Jilin, 132011, China

* Corresponding Author: Jing Bian. Email:

(This article belongs to the Special Issue: Emerging Technologies for Future Smart Grids)

Energy Engineering 2025, 122(3), 1113-1136. https://doi.org/10.32604/ee.2025.059558

Received 11 October 2024; Accepted 06 January 2025; Issue published 07 March 2025

Abstract

A centralized-distributed scheduling strategy for distribution networks based on multi-temporal and hierarchical cooperative game is proposed to address the issues of difficult operation control and energy optimization interaction in distribution network transformer areas, as well as the problem of significant photovoltaic curtailment due to the inability to consume photovoltaic power locally. A scheduling architecture combining multi-temporal scales with a three-level decision-making hierarchy is established: the overall approach adopts a centralized-distributed method, analyzing the operational characteristics and interaction relationships of the distribution network center layer, cluster layer, and transformer area layer, providing a “spatial foundation” for subsequent optimization. The optimization process is divided into two stages on the temporal scale: in the first stage, based on forecasted electricity load and demand response characteristics, time-of-use electricity prices are utilized to formulate day-ahead optimization strategies; in the second stage, based on the charging and discharging characteristics of energy storage vehicles and multi-agent cooperative game relationships, rolling electricity prices and optimal interactive energy solutions are determined among clusters and transformer areas using the Nash bargaining theory. Finally, a distributed optimization algorithm using the bisection method is employed to solve the constructed model. Simulation results demonstrate that the proposed optimization strategy can facilitate photovoltaic consumption in the distribution network and enhance grid economy.

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Keywords

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