2017/05/11 by Adriana Chis, Visa Koivunen, Chis, Adriana +1 · 2 citations
Energy · Engineering · #Computer Science and Game Theory (cs.GT) #Electric Power System Optimization #Energy Efficiency and Management #FOS: Computer and information sciences #FOS: Mathematics #Optimization and Control (math.OC) #Smart Grid Energy Management
paper · pdf · doi:10.48550/arxiv.1705.04118
openalex publication_date 2017/05/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we propose two novel coalitional game theory based optimization\nmethods for minimizing the cost of electricity consumed by households from a\nsmart community. Some households in the community may own renewable energy\nsystems (RESs) conjoined with energy storing systems (ESSs). Some other\nresidences own ESSs only, while the remaining households are simple energy\nconsumers. We first propose a coalitional cost optimization method in which\nRESs and ESSs owners exchange energy and share their renewable energy and\nstorage spaces. We show that by participating in the proposed game these\nhouseholds may considerably reduce their costs in comparison to performing\nindividual cost optimization. We further propose another coalitional\noptimization model in which RESs and ESSs owning households not only share\ntheir resources, but also sell energy to simple energy consuming households. We\nshow that through this energy trade the RESs and ESSs owners can further reduce\ntheir costs, while the simple energy consumers also gain cost savings. The\nmonetary revenues gained by the coalition are distributed among its members\naccording to the Shapley value. Simulation examples show that the proposed\ncoalitional optimization methods may reduce the electricity costs for the RESs\nand ESSs owning households by 20%, while the sole energy consumers may reduce\ntheir costs by 5%.\n