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<p>In this paper, an optimization technique for energy system of smart home coordinated microgrid (SHMG) as a decentralized cluster in power distribution network (PDN) containing distributed energy resources (DERs) provided with Electric vehicles (EVs) is proposed as flexible storage under the scheme of unified scheduling between SHMG and PDN. Based on this, a stochastic energy management problem of interconnected SHMGs and PDNs is formulated, which considers the uncertainties of renewable generation, market clearing prices in electricity markets and DR schedules. For this purpose, a multi-objective cheetah optimization (MOCO) algorithm is developed to optimize the generation schedule of SHMG-PDN resources and startup schedule of EVs and smart home appliances. The goal is to keep the comfort of the smart home (user comfort level, UCL) within reasonable limits by significantly reducing operating costs and peak-to-average ratio (PAR). The research is carried out using two case studies, i.e., a known environment and an uncertain one. The findings reveal that the proposed demand response programs can cut peak loads by about 36–44% in two case studies and remain bounded within a tolerable limit for overall PAR. Then, UCL of the two scenarios are above 60% still, and network losses, voltage profiles have also been improved successfully, which demonstrate again that high effectiveness and optimal performance of SHMG-PDN scheduling scheduling framework is proposed. The study supports building a formal optimization model for jointly scheduling SHMGs and PDNs in the presence of uncertainty, which would achieve better technical performance and user satisfaction.</p>

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Cooperative stochastic energy management of multi smart home microgrids joint with modern distribution network

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月5日

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  • Hossein Shayeghi,
  • Babak Mohamadi,
  • Abdollah Younesi,
  • Sajad Sadr,
  • Pierluigi Siano

摘要

In this paper, an optimization technique for energy system of smart home coordinated microgrid (SHMG) as a decentralized cluster in power distribution network (PDN) containing distributed energy resources (DERs) provided with Electric vehicles (EVs) is proposed as flexible storage under the scheme of unified scheduling between SHMG and PDN. Based on this, a stochastic energy management problem of interconnected SHMGs and PDNs is formulated, which considers the uncertainties of renewable generation, market clearing prices in electricity markets and DR schedules. For this purpose, a multi-objective cheetah optimization (MOCO) algorithm is developed to optimize the generation schedule of SHMG-PDN resources and startup schedule of EVs and smart home appliances. The goal is to keep the comfort of the smart home (user comfort level, UCL) within reasonable limits by significantly reducing operating costs and peak-to-average ratio (PAR). The research is carried out using two case studies, i.e., a known environment and an uncertain one. The findings reveal that the proposed demand response programs can cut peak loads by about 36–44% in two case studies and remain bounded within a tolerable limit for overall PAR. Then, UCL of the two scenarios are above 60% still, and network losses, voltage profiles have also been improved successfully, which demonstrate again that high effectiveness and optimal performance of SHMG-PDN scheduling scheduling framework is proposed. The study supports building a formal optimization model for jointly scheduling SHMGs and PDNs in the presence of uncertainty, which would achieve better technical performance and user satisfaction.