Eco-environmental dispatch of power system with high penetration wind farms considering demand/source side uncertainties

In this paper, a stochastic economic-emission dispatch (EE-D) of a power system with wind farms and flexible loads is proposed. The EE-D is defined as a stochastic multi-objective optimization problem, and a heuristic hybrid multi-objective algorithm is also proposed to solve it. The proposed algorithm is a combination of the lightning search algorithm and multi-objective particle swarm optimization (hLSA-MOPSO). The simulations are conducted in two sections. In the first section, the performance of the proposed algorithm is evaluated by optimizing standard benchmark functions. In the second section, the EE-D problem is solved optimally, considering the impact of uncertainties and the participation of flexible loads, as well as without considering them. Simulations are conducted on a standard 40-unit power system that includes two wind farms. Additionally, a sensitivity analysis is performed to examine the effects of uncertainties and flexible loads on cost and emissions. The sensitivity analysis demonstrates that increasing the penetration rate of wind farms results in reduced costs and emissions. However, it also reveals that the impact of this increase diminishes as the penetration rate continues to rise. Also, the uncertainty analysis reveals that the simultaneous uncertainty of load and wind has the most significant impact on costs and emissions.