Capacity optimal configuration of new off-grid wind-solar-storage microgrid system based on flywheel energy storage

WANG Xueshen; SUN Ran; XU Jun; LI Yujie; ZHANG Bin; LIU Chang; LI Wenyan

doi:10.19666/j.rlfd.202407160

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Capacity optimal configuration of new off-grid wind-solar-storage microgrid system based on flywheel energy storage

Thermal Power Generation Vol. 54, Issue 3, Pages: 43-50(2025)

更新时间：2025-09-28

- Capacity optimal configuration of new off-grid wind-solar-storage microgrid system based on flywheel energy storage
- 作者机构：
  
  1. 国网黑龙江省电力有限公司
  2. 华北电力大学能源动力与机械工程学院
  3. 贝肯新能源有限公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202407160
  CLC： TM73
- Published：2025
- 稿件说明：
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WANG Xueshen, SUN Ran, XU Jun, et al. Capacity optimal configuration of new off-grid wind-solar-storage microgrid system based on flywheel energy storage[J]. Thermal Power Generation, 2025, 54(3): 43-50.
DOI：

WANG Xueshen, SUN Ran, XU Jun, et al. Capacity optimal configuration of new off-grid wind-solar-storage microgrid system based on flywheel energy storage[J]. Thermal Power Generation, 2025, 54(3): 43-50. DOI： 10.19666/j.rlfd.202407160.

摘要

基于飞轮储能技术的新型离网型风光储微电网系统，对分布式电源进行容量优化配置研究，建立风力发电机、光伏阵列、储能飞轮和柴油发电机相应的功率输出模型；以经济性和可靠性指标作为目标函数，环保性指标作为约束条件，进行微电网系统容量优化仿真，基于NSGA-Ⅱ改进算法对微电网系统进行多目标双层协调优化，得到基于多目标优化的帕累托最优解；采用TOPSIS方法进行方案决策，最终确定符合微网系统的最优方案。研究得到的数据和结论，对相关领域的工程应用具有指导作用。

Abstract

To address the electricity consumption challenges in remote regions beyond the reach of power grid

a novel off-grid microgrid system integrating wind and solar energy with flywheel storage technology is introduced.Research is conducted on the optimal capacity configuration of distributed power sources

and power output models are developed for wind turbines

photovoltaic arrays

energy storage flywheels

and diesel generators.With economic and reliability indicators as objective functions

and environmental protection indicators as constraints

a capacity optimization simulation for the microgrid system is conducted. By employing the improved NSGA-II algorithm

a multi-objective bi-level coordinated optimization of the microgrid system is performed

resulting in a Pareto optimal solution through multi-objective optimization. The TOPSIS method is utilized for decision-making

ultimately identifying the optimal solution tailored for the microgrid system. The data and conclusions obtained from this study have reference value for engineering applications in related fields.

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