Dynamic environmental economic dispatch with an enhanced-accuracy probabilistic wind cost model

This paper proposes a dynamic wind-thermal generation scheduling (DWTGS) framework to minimize system generation costs and pollutant emissions. To deal with wind power uncertainty, a new probabilistic wind cost function is introduced, which decomposes wind power uncertainty into several components with varying frequencies. This model not only allows for the use of a more accurate wind power prediction technique in system scheduling, but it also enables the system operator to schedule different thermal units with distinct characteristics to compensate for specific components of uncertainty. This paper also proposes a straightforward procedure for dynamic load dispatch based on power flow, taking into account system constraints and requirements, thereby obtaining more realistic results compared to a large number of previous works in this area. To make the optimization algorithm able to deal with such a complex and high-dimensional optimization problem, a novel heuristic technique is suggested, which is also capable to be readily adapted to other population-based optimization algorithms to improve accuracy. The proposed DWTGS framework is implemented on the IEEE-30 bus test system for performance evaluation. Beneficial information is extracted from the obtained results, and the efficacy of each of the proposed techniques in the optimization procedure is investigated meticulously.