首页> 外文OA文献 >Pumped storage-based standalone photovoltaic power generation system : modeling and techno-economic optimization
【2h】

Pumped storage-based standalone photovoltaic power generation system : modeling and techno-economic optimization

机译:基于抽水蓄能的独立光伏发电系统:建模和技术经济优化

摘要

Standalone renewable energy (RE) systems hold the most promising solution to the electrification of remote areas without utility grid access, while a feasible energy storage is a core part for achieving a continuous and reliable power supply since RE is usually intermittent and weather dependent. In the present study, the pumped hydro storage system is proposed, which is considered as a promising technology for solar energy penetration and particularly for small autonomous systems in remote areas. The mathematical models for the major components are developed, and system reliability and economic criteria are discussed as a benchmark for optimization. The genetic algorithm (GA), along with Pareto optimality concept, is used for the system techno-economic optimization: to maximize power supply reliability and minimize system lifecycle cost simultaneously. The proposed methodology is applied on a real remote inhabited island without power supply. System sizing, simulation and optimization are carried out using single-objective and double-objective GA technique. The performance of the optimal case under zero LPSP is examined. This study demonstrates that the proposed models and optimization algorithm is effective and can be used for other similar studies in the future.
机译:独立的可再生能源(RE)系统是没有公用电网接入的偏远地区电气化的最有希望的解决方案,而可行的能量存储是实现连续和可靠电力供应的核心部分,因为RE通常是间歇性的并且取决于天气。在本研究中,提出了抽水蓄能系统,该系统被认为是一种有前途的太阳能渗透技术,特别是对于偏远地区的小型自治系统。开发了主要组件的数学模型,并讨论了系统可靠性和经济标准,以此作为优化的基准。遗传算法(GA)与帕累托最优概念一起用于系统技术经济优化:最大化电源可靠性并同时最小化系统生命周期成本。所提出的方法应用于没有电源的真正的偏远居住岛屿。使用单目标和双目标遗传算法进行系统规模确定,仿真和优化。考察了在LPSP为零的情况下最优情况的性能。这项研究表明,所提出的模型和优化算法是有效的,并且可以在将来用于其他类似研究。

著录项

  • 作者

    Ma T; Yang HX; Lu L; Peng JQ;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号