A robust unit commitment based on GA-PL strategy by applying TOAT and considering emission costs and energy storage systems

The main purpose of unit commitment problem (UCP) is to find the optimal operation cost (OOC) by considering power system constraints. In this paper, an uncertain UCP (UUCP) is proposed in the presence of energy storage systems (ESSs) via applying genetic algorithm-priority list-based (GA-PLB) strategy and considering operational constraints such as power balance, minimum down time (MDT), minimum up time (MUT), and spinning reserve (SR). To find the robust optimal scheduling due to modeling the uncertainty of renewable energy sources (RESs), the Taguchi orthogonal arrays technique (TOAT) is applied. Furthermore, to consider the environmental concerns, the emission produced by thermal power plants is modeled using the emission cost function as a term of the objective function. The proposed model is tested on the standard cases of IEEE 10, and 38 units and the results are reported. The obtained results confirm that the proposed approach can effectively reduce the OOC. One of the main advantages of the proposed method is the reduction in computational burden due to the modeled uncertainties in solving the UUCP compared to the other proposed methods based on iterations while improving the final solutions.