General metaheuristic-based methodology for computation and decomposition of LMPs

Abstract

Locational marginal prices (LMPs) are economic signals paramount to the deliberations, policy designs, and planning judgments of most electricity markets. This paper presents a general metaheuristic-based methodology applied in the scope of two subproblems to compute and decompose the LMPs considering the incorporation of a distributed slack bus model in the power flow formulation. The deterministic core of the methodology is governed by a process of sequential setting of maximum number of metaheuristic iterations based on load disharmony indices (LDIs) in the context of the initial subproblem. The metaheuristic crux of the methodology is anchored in a random initialization strategy based on time-traveling parameters in the environment of both subproblems. In the introductory arrangement of the optimization sequence, the chain order of the operating horizon periods is defined based on the LDIs. Due to its notorious merits and the breadth of its applications in power system problems, a particle swarm optimization (PSO) algorithm model is used to solve the mentioned subproblems. For the practical purposes of this paper, in the PSO algorithm model instance the particle coordinates are adopted as time-traveling metaheuristic parameters. Numerical simulations on a 3-bus system and on the IEEE 30-bus test system corroborate the efficiency and adequacy of the proposed methodology.