Standalone Hybrid Renewable Energy System Optimization Using Linear Programming

Various strategies for optimizing the renewable energy system size exist, and they vary depending on the system design. In this paper, a standalone hybrid renewable energy system composed of a photovoltaic power source, wind turbines, storage, and diesel generators was considered. Linear programming was used to optimize the system in terms of multiple objectives. Bender's decomposition, lexicographic optimization, and epsilon constraint are among the linear programming techniques employed. The main objective function is to keep excess power to a minimum while also keeping unsatisfied demand to a minimum. This paper considers a full-year time span, optimizes household self-consumption, reduces curtailed power, maximizes local use of renewable generated power, lowers operational costs, lowers CO2 emissions, considers multiple renewable energy sources, considers system sizing as an objective, and incorporates the net present worth value of the components into the sizing. The aforementioned objectives and considerations have never been brought together yet in the literature. Furthermore, using a 365-day span is more comprehensive than using a 24-h span, which is typically used to limit the size of the linear programming issue. Therefore, in terms of integrated objectives, cost analysis, considerations, and timeframe, the proposed method is considered one of the most comprehensive. The ability to adjust the feed in limit to the grid and the change in electricity price during the day are also considered in this work.