Optimal battery scheduling in solar-plus-storage grid-connected microgrid for profit and cost efficiency: A use case on an Israeli microgrid

This paper presents an optimal energy management algorithm for solar-plus-storage grid-connected microgrid simulated on a real full-scale small town microgrid test-case, taking into account the daily solar energy generation as well as the electricity demand to ensure that the battery is charged and discharged at the optimal times to balance energy supply and demand. The optimization is performed using dynamic programming and finding the minimum-cost-path, to minimize the total cash-flow. The formulation is utilized with two variations such that two business models are considered, optimizing cost efficiency in both aspects of minimizing cost and maximizing profits, according to the scenario. The first model maximizes self-consumption, and the second model is the case of retail electricity providers. The results are compared to real data from a solar-plus-storage grid-connected microgrid located in Israel, that is currently managed by a rule-based scheduling procedure. The results show that by using the optimal control schedule, the revenue increases up to 8% during the spring and autumn when the weather conditions are typically moderate. In summer and winter, where the climate conditions are more extreme and the demand for energy is at its peak, the full revenue potential can be realized by using the suggested optimal control algorithm, offering an increased profit of up to 30%. Unlike prior studies which are restricted to small use-cases, this paper leverages a unique and private large-scale data-set from a small town, enabling a thorough exploration of the optimization's real-world viability and scalability. Through rigorous simulations, the findings underscore the method's exceptional potential in effectively integrating PV-plus-storage assets and optimizing energy use in power grids.