Title :
Optimizing economic/environmental dispatch with wind and thermal units
Author :
Al-Awami, A.T. ; Sortomme, E. ; El-Sharkawi, M.A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA
Abstract :
In this paper, the economic/environmental dispatch for a smart grid with wind and thermal units is formulated. The formulation takes into account the stochastic nature of wind power output and the imbalance charges due to the mismatch between the actual and scheduled wind power outputs. Because minimizing the operating cost of thermal and wind units, and minimizing the emissions of thermal units are two conflicting objectives, multi-objective optimization (MOO) technique is used. With MOO, a set of solutions that are optimal in the Pareto sense is identified. An enhanced multi-objective particle swarm optimization (MO-PSO) is proposed to search for the set of Pareto-optimal solutions. The effect of different system conditions on the Pareto-optimal solutions is investigated. These system conditions include load level and different imbalance cost coefficients. Test results show the effectiveness of the proposed technique in identifying the set of Pareto optimal solutions. This technique is an important tool that system operators require in order to operate the grid with high penetration of wind power more efficiently while maintaining emissions within restricted limits.
Keywords :
Pareto optimisation; particle swarm optimisation; power generation dispatch; power generation economics; power generation scheduling; power grids; stochastic processes; thermal power stations; wind power plants; Pareto optimisation; economic-environmental dispatch; multiobjective optimization technique; particle swarm optimization; smart grid; stochastic process; thermal unit; wind power scheduling; Cost function; Environmental economics; Pareto optimization; Power generation economics; Smart grids; Stochastic processes; Stochastic systems; Thermal loading; Wind energy; Wind farms; Economic/environmental Dispatch; Pareto Optimization; Stochastic Optimization; Wind Power Uncertainty;
Conference_Titel :
Power & Energy Society General Meeting, 2009. PES '09. IEEE
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-4241-6
DOI :
10.1109/PES.2009.5275667