研究目的
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.
研究成果
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.
研究不足
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.
1:Experimental Design and Method Selection:
The study employs a dynamic knapsack algorithm for energy optimization, supported by a fuzzy logic decision maker (FLDM) embedded into an energy management system with multi-agent. The system is simulated using MATLAB/Simulink Environment.
2:Sample Selection and Data Sources:
The system includes three DC loads, one battery block, and a PV array. Load priorities are defined by the user.
3:List of Experimental Equipment and Materials:
Includes PV modules, batteries, a charge controller, an inverter, and DC loads. The battery capacity is 270-Ah, and the PV array power is 560-Wp.
4:Experimental Procedures and Operational Workflow:
The system monitors SOC of batteries and instant energy consumption to decide which loads should be active, using FLDM to manage load suspension or activation.
5:Data Analysis Methods:
The optimization is based on a dynamic knapsack problem model, with the objective function re-evaluated at each sampling step to maximize load units considering existing energy and consumer preferences.
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