Economic Dispatch of Energy and Reserve in Competitive Markets Using Meta-heuristic Algorithms

This paper proposes a methodology for the economic dispatch of energy and reserve, in which the reserve requirement is obtained endogenously in the optimization process of the energy dispatch. The formulation assumes that the reserve can be offered both by generation units and flexible demands, which is optimized together with the active power dispatch. To solve this problem, we propose the use of an innovative hybrid methodology that integrates traditional linear programming to calculate the optimal power flow nested within a meta-heuristic algorithm, whose control variable is the reserve vector (reserve assigned to each unit). Thus, faults and congestion of the transmission system are taken into account by providing an optimal location of the reserve. In addition, this paper compares two meta-heuristic models: An evolutionary model widely used in various optimization problems, Evolutionary Particle Swarm Optimization (EPSO) and a novel model known as Mean-Variance Mapping Optimization (MVMO).