A Quantum-inspired Binary PSO algorithm for unit commitment with wind farms considering emission reduction

Abstract

To reduce air pollutant emissions, generation scheduling with energy conservation and emission reduction is a kind of inevitable trend. The paper builds the mathematical model for solving unit commitment of power system with wind farms, which contains a bi-objective function considering both cost and emissions and up/down spinning reserve constraints of the system; simultaneously, the article uses a Quantum-inspired Binary PSO (QBPSO) for the regular unit on/off problem and the primal-dual interior point method for economic load dispatch problem. In addition, the paper deploys new heuristic adjusted regulations to ensure the whole algorithm to search the optimal particle in the feasible region. The proposed method is applied to power systems which are composed of up to 40-units with 24-h demand horizon and a certain proportion of wind farms. The simulation results show that considering both cost and emissions can not only guarantee the reliability and efficiency of power generation, but also be coincident with the environment requirements, making the unit commitment results more reasonable.