Cluster based Wind-Hydro-Thermal Unit Commitment Using GSA Algorithm

Due to intermittency and random nature of wind power generation over short time period, unit commitment problem becomes more complex. In this paper, wind power forecasting uncertainty is represented by wind scenarios generated using Monte Carlo simulation. The computational burden in stochastic models that require scenario representation is reduced by creating clusters of commitment of units associated with a probability of occurrence from an initial set of large wind scenarios. Gravitational search algorithm (GSA) is applied for solving wind-hydro-thermal coordination problem and a pseudo code based algorithm is suggested to deal with the equality constraints of the problem for accelerating the optimization process. The effectiveness of the proposed algorithms is demonstrated on a test system.