Multi-Objective Optimal Planning of Coal-Fired Plants Flexibility Retrofits Considering Multi-Technology Options

Retrofitting coal-fired power plants (CPPs) is a way to accommodate ever-increasing variable renewable energy (VRE) in coal-dominated power systems in countries like China and India. Yet, how to retrofit the CPPS cost-effectively is an important issue to address. This paper proposes a multi-objective two-stage planning approach based on the none-dominated sorting genetic algorithm II (NSGA II). It considers both economic and flexibility requirements for the power system. At the planning stage, optimal technical options considering investment constraints and technical constraints are generated. At the operation stage, a mixed-integer linear programming (MILP) based model considering the detailed start-up and shut-down processes of the CPP is established. Then the optimal solution is selected from the Pareto solution set using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Finally, case studies demonstrate the proposed approaches and show the potential of retrofitting CPPs to enhance power system flexibility.