Improved binary PSO for wind-thermal unit commitment considering wind power uncertainity and emission

This paper describes the unit commitment (UC) problem, which aims for the minimization of wind-thermal operating cost and emission cost of thermal units by considering thermal valve point effect and uncertainty of wind power. The uncertainty of wind power is incorporated with the help of Weibull probability density function (PDF), which is used to evaluate the underestimation and overestimation costs of wind power fluctuation. The proposed technique is based on the improved binary particle swarm optimization (IBPSO) and dynamic particle swarm optimization (DPSO). The IBPSO incorporating priority list method is used to decide the units on/off status of the units, whereas DPSO is utilized to solve the economic dispatch subproblem. A modified IEEE 30-bus system incorporating six thermal units and one wind farm is considered to validate the proposed technique.