Developing a new optimization framework for power generation expansion planning with the inclusion of renewable energy—A case study of Iran

Abstract

The current paper proposes a new hybrid framework to consider the tangible and intangible factors besides the conventional power generation expansion planning problem. It aims at approximating the results to the real world and determining the long term electricity generation expansion plan of Iran from 2016–2035. In addition, it focuses on promoting the shares of renewable energy resources by utilizing the sustainable development approach. The proposed framework includes two stages. In the first stage, the detailed evaluation of technologies is carried out using a hybrid fuzzy analytic network process and benefits, opportunities and risks analysis. In the second stage, a multi-objective model is developed for the optimization of a generation expansion plan. Two objective functions are considered in the model: maximizing the total preference weight of the plan and minimizing the total costs, which includes investment, operation and maintenance, generation, emission, and unmet demands costs. The applicability and efficiency of the proposed framework are surveyed by applying it for Iran's power industry. The mathematical model is solved using the NSGA-II algorithm and sensitivity analysis is performed for the key parameters. The results show the increasing shares of renewable resources in the planning horizon. Furthermore, it shows that the fossil power plants would play a significant role in the future of Iran's electricity supply. The natural gas combined cycle power plants would be the most preferred alternative among the fossil power plants and would have the most installed capacity share during the planning horizon.