A CMOPSO based multi-objective optimization of renewable energy planning: Case of Turkey. (August 2020) - Deveci, Kaan; Güler, Önder
Abstract: In this paper, a two step multi-objective optimization framework of renewable energy planning is proposed for Turkey. In the first step, optimization process is performed and in the second step a multi-criteria decision making based selection strategy is applied to select a solution from non-dominated solution set. The objectives are selected as minimization of levelized cost of electricity plan and maximization of short term electricity generation from renewable energy resources. The optimization model considers different cases of renewable energy investment expenditures and the optimal use of resource availability according to renewable energy related targets of the country and estimated cost reduction due to technological learning. For optimization purposes, a state-of-the-art metaheuristic Competitive Multi-Objective Particle Swarm Optimizer (CMOPSO) is used. Results reveal that the 2023 targets of Turkey for hydroelectric, and biomass power plants are not optimal with any of the renewable energy investment case. In addition, solar photovoltaics and onshore wind energy should be the most preferred renewable resources. The findings of this paper can help decision makers not only to set optimized and reliable energy-related goals for Turkey but also to estimate the most suitable time for diffusion of offshore wind energy technology which is not currently under operation. Highlights: A multi-objective optimization model for renewable energy planning is developed for Turkey. A new metric is defined by using DM evaluations for selecting a solution from non-dominated set. Selected solutions are projected throughout the planning period for each financial case. The optimality of country specific targets is analyzed by using non-dominated solutions.