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A fuzzy logic embedded energy management software with multi-agent system for a stand-alone PV power plant

DOI:10.1007/s13762-018-2144-6 期刊:International Journal of Environmental Science and Technology 出版年份:2018 更新时间:2025-09-10 09:29:36
摘要: The worst scenario projected for an off-grid photovoltaic power system is the time interval that the solar irradiation amount is in short to supply the load throughout the day, and this situation is resulted in energy deficiency. Nowadays, an off-grid power generating system, which is designed to consider the worst scenario encountered only during a certain period of time, brings through big financial problems in terms of the initial installation costs. This study proposes a smart software to perform energy management considering users’ comfort and their criteria, which are taking some information from the agents communicating with the consumption units wirelessly and the battery agent. All loads and agents in this system are initially defined by the user according to the importance of the consumption loads such as critical, essential, significant, lesser, and insignificant loads. The proposed energy management software includes fuzzy logic-based decision maker to manage load suspension or put the suspended load into effect again according to the state of the sources. The total amount of consumption is kept less than the total existing energy so that the energy to be consumed by the critical loads is always provided. Considering the existing amount of energy and consumer preferences, the total amount of load units is maximized at each sampling step. The proposed system, which is attained without compromising the user comfort, enables more efficient energy consumption. Also, for supplying the critical loads in case of lack of energy is possible.
作者: T. Ozden,S. Kesler,H. I. Okumus
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To propose a smart software for energy management in stand-alone photovoltaic power systems that considers user comfort and criteria, utilizing a fuzzy logic-based decision maker and multi-agent system to manage load suspension and activation based on the state of energy sources.

The proposed multi-agent structured energy optimizer with FLDM for an off-grid PV system effectively manages energy consumption by prioritizing critical loads and postponing less important ones, ensuring energy availability for critical loads even in worst-case scenarios. This approach reduces initial installation costs and enhances system efficiency without compromising user comfort.

The study focuses on simulation results and theoretical validation, with experimental verification mentioned as part of a PhD thesis but not detailed in this paper. The system's performance in varying environmental conditions and scalability for larger systems are not extensively discussed.

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