Design optimization of a thermal-storage-based electricity storage for nanogrid applications

M. Caliano, G. Graditi, A. Pontecorvo, M. Valenti
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Abstract

Thermal Energy Storage (TES) systems have shown a high potential for integrating intermittent renewable energy sources into energy systems by assisting with electrification of thermal loads. The aim of this paper is to develop a tool for the simulation and optimal design of a TES-based electricity storage of electricity produced by a photovoltaic system for nanogrid applications. The tool adopts a multi-objective approach with a view to reducing the costs associated with the nanogrid and saving primary energy, while satisfying the end-user multi-energy demand. The simulation/optimization tool is developed by coupling TRNSYS and Matlab softwares with the aim to find the design and operation strategies solutions on the Pareto frontier, and the problem is solved by using genetic algorithms. In the numerical test case, a single-family house of 200 m2 located in Italy is considered as residential end-user, and the winter and summer scenarios are considered for simulations. Results show the functionality of the tool in simulating and optimizing more or less complex energy systems and its effectiveness for providing good balancing solutions for end-users based on economic and energetic priorities.
纳米电网应用中基于热存储的电力存储的设计优化
热能储存(TES)系统通过协助热负荷电气化,显示出将间歇性可再生能源整合到能源系统中的巨大潜力。本文的目的是开发一种工具,用于模拟和优化设计基于tes的纳米电网应用光伏系统产生的电力存储。该工具采用多目标方法,旨在降低与纳米电网相关的成本,节约一次能源,同时满足最终用户的多种能源需求。结合TRNSYS和Matlab软件开发仿真/优化工具,寻找Pareto边界上的设计和运行策略解,并采用遗传算法求解。在数值测试案例中,将位于意大利的200平方米的单户住宅作为住宅最终用户,并考虑冬季和夏季场景进行模拟。结果表明,该工具在模拟和优化或多或少复杂的能源系统方面的功能,以及为最终用户提供基于经济和能源优先级的良好平衡解决方案的有效性。
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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