Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer

This paper presents a new short-term multi-objective complementary scheduling problem for hydrothermal-renewable power systems (HTRPSs). The economic/emission objectives, different from traditional economic/emission load dispatch problems, consider the on/off status of thermal power units as well as the dispatched load among engaged units as the optimization variables under various complicated nonlinear constraints. To solve the model with hybrid optimization variables, a multi-objective hybrid grey wolf optimization algorithm is proposed, in which continuous and discrete optimization variables are encoded and optimized synchronously. A daily scheduling simulation example of a hybrid power system consisting of cascade hydropower stations, thermal power units, and renewable energy (RE) power plants is studied to test the proposed model and algorithm. The results not only demonstrate that the proposed algorithm can achieve the best Pareto front for economic/emission bi-objectives compared to its competitors, but also confirm that the obtained scheduling schemes are completely within the feasible domain. Moreover, the impact of RE capacity on the power system is analyzed. Results indicate that the joint operation of RE and hydropower stations benefit both the economic and emission objectives, and the operational costs and pollution emissions decrease by 11.9% and 17.4%, respectively, when the RE capacity increases from 50% to 100% in the hybrid system. (C) 2018 Elsevier Ltd. All rights reserved.