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A novel peak load shaving algorithm via real‐time battery scheduling for residential distributed energy storage systems
Author(s) -
Barzkar Arash,
Hosseini Seyed Mohammad Hassan
Publication year - 2018
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4010
Subject(s) - peaking power plant , photovoltaic system , renewable energy , computer science , grid , load balancing (electrical power) , energy storage , peak demand , scheduling (production processes) , state of charge , distributed generation , demand response , microgrid , automotive engineering , mathematical optimization , reliability engineering , engineering , electricity , power (physics) , battery (electricity) , electrical engineering , mathematics , physics , quantum mechanics , geometry
Summary As population grows and energy consumption increases, generation, transmission, and energy distribution costs also increase. Sudden and unpredicted demand increase at peak periods might lead to failure and even damage the power grid. This is a challenge for stability and reliability of the grid. Peak load shaving is considered as an effective approach while transition from peak load periods. In this paper, peak load shaving is modeled mathematically through storing energy on demand side and solved using optimization method. Using the results obtained from solving the optimization problem, a simple effective algorithm is proposed for peak load shaving via real‐time scheduling of distributed battery storage systems without complicated calculations. All characteristics required for systemic design of peak load shaving for residential, commercial, and industrial loads are presented. This method can be used in the presence of photovoltaic arrays or other renewable or nonrenewable distributed energy resources simultaneously, and it can be adapted to different conditions and demands. Here, real measured data of a residential state, an office building with photovoltaics, a hotel, and a small office are used for simulation, and GAMS is used for analysis.