高渗透率可再生能源接入下考虑网络重构和需求响应的微电网低碳优化调度

高锋阳; 裴淑萍; 查鹏堂; 高建宁; 庄圣贤

doi:doi:10.19912/j.0254-0096.tynxb.2024-1763

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高渗透率可再生能源接入下考虑网络重构和需求响应的微电网低碳优化调度

更新时间：2026-03-06

- 高渗透率可再生能源接入下考虑网络重构和需求响应的微电网低碳优化调度
- Vol. 47, Issue 2, Pages: 310-321(2026)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1763
  CLC： TM73
- Online First：05 March 2026，
  
  Published：05 March 2026
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高锋阳, 裴淑萍, 查鹏堂, et al. 高渗透率可再生能源接入下考虑网络重构和需求响应的微电网低碳优化调度[J]. 2026, 47(2): 310-321.
DOI：

高锋阳, 裴淑萍, 查鹏堂, et al. 高渗透率可再生能源接入下考虑网络重构和需求响应的微电网低碳优化调度[J]. 2026, 47(2): 310-321. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1763.

摘要

针对高渗透率可再生能源接入微电网以及可再生能源提供的电力与负荷需求之间的不平衡

提出考虑网络重构和需求响应的低碳优化调度策略。首先

利用网络重构实现微电网优化运行

有效改善电压偏差

降低总成本

最大限度地减少有功功率损耗

提出苦鱼算法（BFO）构建高渗透率可再生能源接入下微电网低碳优化调度模型。其次

提出一种基于激励需求响应资源和重构方法整合到日前时间框架的微电网调度中

使传统分布式发电的燃料成本和从电网购买电力的成本最小化

使微电网运营利润最大化。最后

采用IEEE 33节点系统进行算例验证

结果表明所提调度策略可有效削弱负荷峰谷差

提升系统运行稳定性、经济性和环保性。

Abstract

To address the imbalance between high penetration of renewable energy in microgrids and the power supply-demand

a low-carbon optimization scheduling strategy considering network reconfiguration and Demand Response （DR） is proposed. Firstly

network reconfiguration is utilized to optimize microgrid operation

effectively improving voltage deviation

reducing total costs

and minimizing active power losses

employing the Bitterling Fish Optimization （BFO） algorithm to construct a low-carbon optimization scheduling model for microgrids with high renewable energy integration. Secondly

an incentive-based demand response scheme and reconfiguration method are integrated into day-ahead scheduling

minimizing fuel costs for traditional distributed generation and the costs for purchasing power from the grid

thus maximizing microgrid operational profits. Finally

the proposed scheduling strategy is validated using the IEEE 33-node system. The results demonstrate that the proposed strategy effectively reduces the load peak-to-valley difference and enhances the stability

economy

and environmental protection performance of the system.

关键词

Keywords

references

EMRANI A, BERRADA A.A comprehensive review on techno-economic assessment of hybrid energy storage systems integrated with renewable energy[J]. Journal of energy storage, 2024, 84: 111010.

孙东磊, 赵龙, 孙凯祺, 等. 新能源接入下配电系统混合储能选址定容优化策略研究[J]. 太阳能学报, 2024, 45(1): 423-432.

孙秋野, 于潇寒, 王靖傲. “双高” 配电系统的挑战与应对措施探讨[J]. 中国电机工程学报, 2024, 44(18): 7115-7136.

SONG Y B, SAHOO S, YANG Y H, et al.Probabilistic risk evaluation of microgrids considering stability and reliability[J]. IEEE transactions on power electronics, 2023, 38(8): 10302-10312.

ASKARZADEH A.A memory-based genetic algorithm for optimization of power generation in a microgrid[J]. IEEE transactions on sustainable energy, 2018, 9(3): 1081-1089.

SHAHEEN M A M, HASANIEN H M, ALKUHAYLI A. A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution[J]. Ain shams engineering journal, 2021, 12(1): 621-630.

HUY P D, RAMACHANDARAMURTHY V K, YONG J Y, et al.Optimal placement, sizing and power factor of distributed generation: a comprehensive study spanning from the planning stage to the operation stage[J]. Energy, 2020, 195: 117011.

吕建虎, 郭晓蕊, 梁志峰, 等. 计及负荷调峰容量不确定性的发用双侧协同调峰调度优化[J]. 电网技术, 2025, 49(4): 1337-1346.

刘佳, 唐早, 曾平良, 等. 高比例可再生能源接入下与配电系统分层协同的输电系统自适应规划[J]. 电网技术, 2022, 46(8): 3105-3115.

谭慧娟, 李世明, 郭文鑫, 等. 基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法[J]. 太阳能学报, 2022, 43(5): 468-477.

PAN J S, WANG H J, NGUYEN T T, et al.Dynamic reconfiguration of distribution network based on dynamic optimal period division and multi-group flight slime mould algorithm[J]. Electric power systems research, 2022, 208: 107925.

汪涛, 武传涛, 随权, 等. 计及故障维修与网络重构的灾后配电网综合调度策略[J]. 中国电机工程学报, 2024, 44(5): 1764-1777.

靳攀润, 宋汶秦, 刘永成. 考虑DG不确定性的有源配电网两阶段动态鲁棒重构方法[J]. 太阳能学报, 2024, 45(6): 208-216.

HASANIEN H M, ALSALEH I, ULLAH Z, et al.Probabilistic optimal power flow in power systems with Renewable energy integration using Enhanced walrus optimization algorithm[J]. Ain shams engineering journal, 2024, 15(3): 102663.

李虹, 林兰心, 赵小军. 基于需求侧用户响应分析的电-气-热综合能源系统低碳经济调度[J]. 太阳能学报, 2023, 44(5): 97-105.

廖望, 刘东, 巫宇锋, 等. 考虑源荷不确定性及用户响应行为的电力系统低碳经济调度[J]. 中国电机工程学报, 2024, 44(3): 905-918.

DOU C X, ZHOU X H, ZHANG T F, et al.Economic optimization dispatching strategy of microgrid for promoting photoelectric consumption considering cogeneration and demand response[J]. Journal of modern power systems and clean energy, 2020, 8(3): 557-563.

张玉敏, 杨子震, 叶平峰, 等. 市场环境下考虑配网重构和需求响应的输配协同优化调度[J]. 高电压技术, 2025, 51(6): 2954-2969.

黄鸣宇, 张庆平, 张沈习, 等. 高比例清洁能源接入下计及需求响应的配电网重构[J]. 电力系统保护与控制, 2022, 50(1): 116-123.

MATIN S A A, MANSOURI S A, BAYAT M, et al. A multi-objective bi-level optimization framework for dynamic maintenance planning of active distribution networks in the presence of energy storage systems[J]. Journal of energy storage, 2022, 52: 104762.

AZIZ H, TABRIZIAN M, ANSARIAN M, et al.A three-stage multi-objective optimization framework for day-ahead interaction between microgrids in active distribution networks considering flexible loads and energy storage systems[J]. Journal of energy storage, 2022, 52: 104739.

LIN F J, LIAO J C, ZHANG Y M, et al.Optimal economic dispatch and power generation for microgrid using novel Lagrange multipliers-based method with HIL verification[J]. IEEE systems journal, 2023, 17(3): 4533-4544.

BADRUDEEN T U, ARIYO F K, NWULU N.Voltage stability improvement and power losses reduction through multiple grid contingency supports[J]. Energy exploration & exploitation, 2024, 42(4): 1218-1240.

AHMED D, EBEED M, KAMEL S, et al.An enhanced jellyfish search optimizer for stochastic energy management of multi-microgrids with wind turbines, biomass and PV generation systems considering uncertainty[J]. Scientific reports, 2024, 14: 15558.

MOHAMED M A, KAMEL S, ALRASHED M M, et al.Power flow optimization in distribution networks: estimating optimal distribution generators through pseudo-inverse analysis[J]. Energy reports, 2024, 11: 2935-2970.

ŞEKER A A, GÖZEL T, HOCAOĞLU M H. BIBC matrix modification for network topology changes: reconfiguration problem implementation[J]. Energies, 2021, 14(10): 2738.

ZAREIAN L, RAHEBI J, SHAYEGAN M J.Bitterling fish optimization (BFO) algorithm[J]. Multimedia tools and applications, 2024, 83(31): 75893-75926.

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