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A Two-Layer Optimal Scheduling Strategy for Rural Microgrids Accounting for Flexible Loads

Guo Zhao1,2, Chi Zhang1,2,*, Qiyuan Ren1,2
1 School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, 430068, China
2 Key Laboratory of Solar Energy Efficient Utilization and Energy Storage Operation Control, Hubei University of Technology, Wuhan, 430068, China
* Corresponding Author: Chi Zhang. Email: email

Energy Engineering https://doi.org/10.32604/ee.2024.053130

Received 25 April 2024; Accepted 16 August 2024; Published online 11 September 2024

Abstract

In the context of China’s “double carbon” goals and rural revitalization strategy, the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids. Considering the operational characteristics of rural microgrids and their impact on users, this paper establishes a two-layer scheduling model incorporating flexible loads. The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid, while the lower-layer aims to minimize the total electricity cost for rural users. An Improved Adaptive Genetic Algorithm (IAGA) is proposed to solve the model. Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations, enhance microgrid stability, increase clean energy consumption, and balance microgrid operating costs with user benefits.

Keywords

Double carbon; flexible loads; rural microgrid; clean energy consumption; two-layer scheduling; improved adaptive genetic algorithm
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