Decomposition based multiobjective evolutionary algorithm for PV/Wind/Diesel Hybrid Microgrid System design considering load uncertainty - Bouchekara, Houssem Rafik El-Hana; Javaid, Muhammad Sharjeel; Shaaban, Yusuf Abubakar; Shahriar, Mohammad Shoaib; Ramli, Makbul Anwari Muhammad; Latreche, Yaqoub (Energy reports, 2021)
This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of Yanbu, Saudi Arabia. Designing such a hybrid system with all the renewable and non-renewable sources, storage devices, converters, and loads is a complicated task. A multiobjective approach has been adopted to optimize the microgrid design. Two methodologies are available for solving such multiobjective problems. In the first approach, the problem is transformed into a single objective one (using aggregation, for instance), whereas, the second technique treats objectives simultaneously and independently as adopted in this paper. The proposed approach offers the Pareto front; a set of solutions in one run opening the door of choosing the most suitable solution from the available options based on the experience, expertise and requirement of the designer. This paper presents a novel approach of using Decomposition Based Multiobjective Evolutionary Algorithm (MOEA/D) to optimally design the PV/Wind/Diesel HMS considering load uncertainty. Loss of Power Supply Probability (LPSP) and Cost of Electricity (COE) are considered as the objective functions of the optimization problem. Furthermore, two separate load cases of 5 and 10 houses are tested to verify the robustness of the approach. The obtained results are beneficial in assisting researchers and practitioners in selecting the optimal configuration of the microgrid.