An optimization study on a typical renewable microgrid energy system with energy storage

被引:35
|
作者
Gomes, J. Graca [1 ,2 ]
Xu, H. J. [1 ]
Yang, Q. [1 ]
Zhao, C. Y. [1 ]
机构
[1] Shanghai Jiao Tong Univ, China UK Low Carbon Coll, Shanghai 200240, Peoples R China
[2] Sino Portuguese Ctr New Energy Technol Shanghai C, Shanghai 200335, Peoples R China
基金
中国国家自然科学基金;
关键词
Renewable microgrid; Optimization; Energy storage; Distributed generation; Bayesian artificial neural network; HYBRID; FEASIBILITY; IMPACT;
D O I
10.1016/j.energy.2021.121210
中图分类号
O414.1 [热力学];
学科分类号
摘要
In isolated microgrids and remote regions, the challenge of developing reliable and self-sufficient renewable energy systems is amplified due to the lack of grid flexibility options. One of the leading solutions to increase renewable energy usage in isolated systems is the commission of energy storage. The current study proposes a novel optimization model that sizes the most cost-efficient renewable power capacity mix of an autonomous microgrid supported by storage technologies. The proposed algorithm considers operational, technical and land-use constraints. The problem is formulated using linear programming, is tested and scrutinized with sets of historical weather, load demand and installation prices data, and is modelled hour-by-hour. The method is applied to Corvo, an island in the Azores archipelago, Portugal. The results obtained exhibit that the proposed approach provides the optimal configuration of the renewable-based microgrid with an LCOE (Levelized Cost of electricity) of 0.21 V/kWh, a value lower than a diesel-based alternative, and while ensuring minimum land area occupation. Furthermore, sensitivity analysis is also presented to examine the effect of variables on the LCOE and PC (present cost) of the system. The present study shows that the developed optimal sizing model can improve electricity planning and facilitate energy transition in distributed power systems. (c) 2021 Elsevier Ltd. All rights reserved.
引用
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页数:15
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