Improving Renewable Energy Policy Planning and Decision-Making Through MCDM Combined Method

Abstract

Renewable energy (RE) is one of the potential solutions for climate change, energy security and sustainable growth. Considering the reduction of fossil fuels and the resulting environmental problems, the use of renewable energy is very important, and it is expected that the use of renewable energy will play a prominent role in the world's energy portfolio. In this research, the best place to build a combined solar wind power plant is determined among different options, and then a combined energy production system is designed in the desired location, and the proposed plan is examined from a technical and economic point of view. In this research, renewable energy production sources are examined from various aspects. Renewable energy production sources each have advantages and disadvantages, which can be superior to each other according to the area of ​​use. For this purpose, in this research, the AHP algorithm is used to construct the cost function. For each hour of the day and night, a pair matrix is ​​considered, in which the benefits of two power plants are given, and based on the formed matrix, the benefits of each can be Calculated to the other numerically. In the end, the meta-heuristic algorithm is used to choose the right option. The dragonfly algorithm has the ability to be less stuck in the local optimum and to calculate the optimal solution in less time than other meta-heuristic algorithms.