Research on Energy Optimization Scheduling Methods for Systems with Multiple Microgrids in Urban Areas

As an emerging power system architecture, microgrids have garnered widespread attention. Energy optimization scheduling for urban systems with multiple microgrid integrations can ensure the reliability of power supply, achieve optimal energy allocation and utilization, and reduce the overall costs of the multi-microgrid system. This paper proposes an energy optimization scheduling method based on a bi-level optimization model using a CPLEX+PSO hybrid algorithm. The upper level aims to minimize the interaction power and its fluctuations between the multi-microgrid system and the distribution network, while the lower level aims to minimize the overall cost of the multi-microgrid system. Day-ahead scheduling is conducted based on predicted wind and solar load data. Using CPLEX to solve the upper and lower-level functions as a baseline, an evaluation function is introduced to select the optimal particles in the particle swarm algorithm, resulting in the optimal solution for the energy allocation scheme of the multi-microgrid system.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/dtpi61353.2024.10778839
Citations
2
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.34
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article

Research on Energy Optimization Scheduling Methods for Systems with Multiple Microgrids in Urban Areas

Liuming Jing, Zhaozheng Zhou, Mirkomil Melikuziev, Jiayi Guo et al.
2 citations
Power Systems and Renewable Energy
0.34
article

Research on Energy Optimization Scheduling Methods for Systems with Multiple Microgrids in Urban Areas

Liuming Jing, Zhaozheng Zhou, Mirkomil Melikuziev, Jiayi Guo, Han Liu, Feng Teng
article en
2 citations

Abstract

As an emerging power system architecture, microgrids have garnered widespread attention. Energy optimization scheduling for urban systems with multiple microgrid integrations can ensure the reliability of power supply, achieve optimal energy allocation and utilization, and reduce the overall costs of the multi-microgrid system. This paper proposes an energy optimization scheduling method based on a bi-level optimization model using a CPLEX+PSO hybrid algorithm. The upper level aims to minimize the interaction power and its fluctuations between the multi-microgrid system and the distribution network, while the lower level aims to minimize the overall cost of the multi-microgrid system. Day-ahead scheduling is conducted based on predicted wind and solar load data. Using CPLEX to solve the upper and lower-level functions as a baseline, an evaluation function is introduced to select the optimal particles in the particle swarm algorithm, resulting in the optimal solution for the energy allocation scheme of the multi-microgrid system.

North China University of Technology (CN), Tashkent State Technical University named after Islam Karimov (UZ), Fujian Electric Power Survey & Design Institute (CN)
Sustainable cities and communities
Openalex Percentile: Top 33%
Power Systems and Renewable Energy
0.34
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