Optimal scheduling of uncertain wind energy and demand response in unit commitment using binary grey Wolf optimizer (BGWO)

The uncertain wind energy handling is a vital aspect of modern power system operational planning with considerable wind penetration. The handling of same is a techno-economic constrained procedure considering its effect on energy and reserve scheduling of whole generation mix. This paper presents a dynamic penalty cost based methodology to solve power system resource scheduling problem with uncertain wind energy, thermal units and responsive loads using binary grey wolf optimizer (BGWO). The proposed methodology considers the effect of uncertain wind energy in terms of total rescheduling cost, total energy balancing cost and total reserve cost. The unit commitment procedure is solved using BGWO and the economic dispatch of committed thermal units alongside the wind energy, responsive load scheduling is solved using Lambda iteration technique. In addition, two different levels of wind uncertainty level are considered to examine the variation techno-economic aspects of proposed methodology. The simulation results are presented and discussed with respect to various performance attributes and the same demonstrate the superior performance of proposed dynamic penalty cost models over existing static cost models.