Multi-objective Optimization of Hybrid Microgrid System of Semau Island in Indonesia: Minimising Energy Cost and Carbon Emission Using Evolutionary Computation

The optimisation of the power system to minimise cost-emission has been discussed and discussed in many studies. The early approach to optimisation is trial and error without using systematic and automated tools, resulting in not all solutions being explored. Other than that, optimising using only a single objective is ineffective since it produces one-sided advantages that could lead to disadvantages for the other parameters. Additionally, single-objective optimisation requires several constraints to be set up, which can be problematic if the limits are unfixed or complex. This paper proposes a novelty multi-objective formulation of the optimal power generation problem involving energy cost, emissions, and total voltage violations as objectives using the Evolutionary Algorithm to automate the process. The object used in this project is a Hybrid Microgrid System consisting of Diesel Generators and Solar Photovoltaic Systems with Battery Energy Storage located in Semau Island, Indonesia. This study aims to provide an alternative optimisation method that the grid operator can use to determine the most environmentally friendly and cost-efficient power generation combination in the operation of a hybrid microgrid system and its future development. The optimization on the grid includes 1,620 load flow simulations, indicating that the energy cost ranges from $202.54 to $208.82, and the emissions range from 0.12 to 0.225 tons per hour. These findings suggest that significant accumulations in costs and emissions can occur over extended periods.