Resilient day-ahead microgrid energy management with uncertain demand, EVs, storage, and renewables

IF 5.3 Q2 ENGINEERING, ENVIRONMENTAL
Ahmad Niknami , Mohammad Tolou Askari , Meysam Amir Ahmadi , Majid Babaei Nik , Mahmoud Samiei Moghaddam
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引用次数: 0

Abstract

Managing microgrid energy presents a complex challenge due to unpredictable renewable sources, fluctuating demand, and diverse equipment like batteries, distributed generators, and electric vehicles. This paper introduces a novel two-step optimization model, the Robust Day-Ahead Scheduling for Enhanced Resilience, tailored for microgrid operations. The model addresses the integration of electronic generation, uncertain demand patterns, and small-scale renewable resources. Detailed formulations optimize microgrid energy use, including strategic battery usage, efficient electric vehicle charging, balancing device utilization, and distributed generation dispatch. This multi-faceted approach aims to minimize costs over 24 h, including energy loss, power purchases, reduced power usage, generator operation, and battery/EV expenses. Employing a column-and-constraint generation (C&CG) algorithm ensures efficient problem solving. The proposed model achieved a significant reduction in operational costs, outperforming existing methods by at least 8%. Notably, it minimized energy purchases, energy losses, and load shedding while improving voltage stability, showcasing its effectiveness in enhancing microgrid performance and resilience.

具有不确定需求、电动汽车、储能和可再生能源的弹性日前微电网能源管理
由于不可预测的可再生能源、波动的需求以及电池、分布式发电机和电动汽车等多样化的设备,微电网能源管理面临着复杂的挑战。本文介绍了一种专为微电网运行量身定制的新型两步优化模型--"增强弹性的稳健提前调度"。该模型解决了电子发电、不确定需求模式和小型可再生资源的整合问题。详细的公式优化了微电网的能源使用,包括电池的战略性使用、电动汽车的高效充电、平衡装置的利用以及分布式发电调度。这种多方面的方法旨在最大限度地降低 24 小时内的成本,包括能源损耗、电力采购、减少电力使用、发电机运行和电池/电动汽车支出。采用列和约束生成(C&CG)算法可确保高效解决问题。所提出的模型显著降低了运营成本,比现有方法至少高出 8%。值得注意的是,它最大限度地减少了能源采购、能源损耗和甩负荷,同时提高了电压稳定性,展示了其在提高微电网性能和弹性方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cleaner Engineering and Technology
Cleaner Engineering and Technology Engineering-Engineering (miscellaneous)
CiteScore
9.80
自引率
0.00%
发文量
218
审稿时长
21 weeks
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