Multi‐objective unit commitment with renewable energy using hybrid approach

During the last few years, greenhouse gas emission especially from electric power generation is a major concern due to the global warming and environmental change, therefore, committing the generating units on minimum cost criterion is shifting toward minimising the cost with minimum emission. Due to the conflicting nature of economic and emission objectives, the generation scheduling becomes a multi‐objective problem. In this study, a weighted sum method is applied to convert multi‐objective problem to a single‐objective problem by linear combination of different objectives as a weighted sum and an efficient hybrid algorithm is presented for aiding unit commitment (UC) decisions in such environments. Due to uncertainty of wind power generation, the UC problem has become complex. To handle uncertainty, scenario generation and reduction techniques are used. The proposed hybrid approach is a combination of weighted improved crazy particle swarm optimisation with pseudo code algorithm, which is enhanced by extended priority list to handle the spinning reserve constraints and a heuristic search algorithm to handle minimum up/down time constraints. Simulation results confirm the potential and effectiveness of proposed approach after comparison with other methods reported in the literature.