Integrated renewable-conventional generation expansion planning using multiobjective framework

This study presents multiperiod multiobjective generation expansion planning (MMGEP) model of power electric system including renewable energy sources (RES). The model optimises simultaneously multiple objectives (i.e. minimisation of total costs, emissions, energy consumption and portfolio investment risk as well as maximisation of system reliability). The mixed-integer linear programming (MILP) is used for the proposed optimisation and an efficient linearisation technique is proposed to convert the non-linear reliability metrics into a set of linear expressions. The proposed solution for multiobjective mathematical programming (MMP) framework includes a hybrid augmented-weighted epsilon constraint and lexicographic optimisation approach to obtain the Pareto optimal or efficient solutions for the MMGEP problem. Finally, fuzzy decision making is implemented to select the most preferred solution among Pareto solutions based on the goals of decision makers (DMs). A synthetic test system including seven types of candidate units is considered here for GEP in a 6-year planning horizon. The effectiveness of the proposed modifications is illustrated in detail.