Multi-objective and multi-criteria decision making for Technoeconomic optimum design of hybrid standalone renewable energy system

The major obstacle in designing of the wind turbine/photovoltaic/battery storage system lies in the task of choosing the most optimum solution while simultaneously considering techno-economic objectives. Consequently, this study provides a distinctive amalgamation of multi-objective multi-perspective and group multi-criteria decision-making methodologies to ascertain collections of Pareto optimum configurations and to weight, rank, and pick up the most desirable optimum solutions that represent best trade-off between conflicting objectives. In this paper, the multi-objective Dragon fly algorithm is developed based on mutation scheme and crossover tactic algorithm is advanced to handle a lack of diversity and poor convergence, while non-dominated sorting and crowding distance strategy is addressed to store the best found optimum solutions in the achieve. Loss of load probability, excess energy, and life cycle cost are conflicting techno-economic objectives solved by multi-objective method. The optimum Pareto front solutions are ranked based on hybrid multi-criteria decision-making method for determining the most favorable solution for the WT/PV/BS system. The experimental outcomes indicated that the developed approach has a distinct performance in constructing a collection of Pareto front solutions in terms of diversity, converge, and convergence. Moreover, it demonstrates outstanding results when compared to well-organized multi-objective optimization methods. The future direction can be accomplished by applying the proposed hybrid sizing methodology for solving gird-connected system along with electric vehicle based on techno-economic scenarios.