Scholarlink

<p>This paper proposes a techno-economic evaluation model for distributed energy resources participating in a joint energy and regulation market. To this end, an installed battery energy storage system (BESS) of MAPNA Co. as well as various electricity consumers are aggregated in a virtual power plant (VPP) framework. A design features and precise models of the installed Lithium iron phosphate (LiFePO4 or LFP) battery modules are taken into account. Besides, the VPP sets up incentive agreement to benefit from the potential of responsive consumers in both energy and regulation services. Within the proposed model, three main types of electricity demand including residential, commercial, and industrial consumers are considered. A 2m + 1 point estimate method (PEM) is applied to model uncertainties arise from stochastic parameters including energy and regulation prices, up/down regulation calling requests, energy losses due to passive balancing process in the installed BESS and different electricity consumer demands. Three different case studies are applied to demonstrate robustness and effectiveness of the proposed scheduling methodology.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Techno-economic evaluation of installed battery energy storage system of MAPNA Co. for providing both energy and regulation provision services

  • 期刊论文

  • 发表日期：

    2026年2月16日

查看全文
  • Ali Shayegan-Rad,
  • Ali Zanganeh,
  • Asghar Aghaei-Rad,
  • Reza Kiani,
  • Mehdi Bashooki

摘要

This paper proposes a techno-economic evaluation model for distributed energy resources participating in a joint energy and regulation market. To this end, an installed battery energy storage system (BESS) of MAPNA Co. as well as various electricity consumers are aggregated in a virtual power plant (VPP) framework. A design features and precise models of the installed Lithium iron phosphate (LiFePO4 or LFP) battery modules are taken into account. Besides, the VPP sets up incentive agreement to benefit from the potential of responsive consumers in both energy and regulation services. Within the proposed model, three main types of electricity demand including residential, commercial, and industrial consumers are considered. A 2m + 1 point estimate method (PEM) is applied to model uncertainties arise from stochastic parameters including energy and regulation prices, up/down regulation calling requests, energy losses due to passive balancing process in the installed BESS and different electricity consumer demands. Three different case studies are applied to demonstrate robustness and effectiveness of the proposed scheduling methodology.