Grey Wolf Optimization based Energy Management by Generator Rescheduling with Renewable Energy Resources

In deregulated power industry, many participants are playing in the market aiming to get the maximum benefit by selling and buying the energy. The congestion in the transmission line occurs due to increased load demand, the limited capacity of the transmission line and tendency to get the power at a cheaper rate. Power system security and reliability may be at high risk due to intense congestion in the network. Hence, the system operator has to deal the congestion management issues with utmost care. In this paper, energy management approach is applied to relieve the congestion on transmission line by rescheduling of generators with an objective to minimize the rescheduling cost. The Generator Sensitivity Factors(GSF) is incorporated in an optimization model of energy management to determine the number of generators to be rescheduled. The optimized cost of rescheduling of generators is obtained by applying the Grey Wolf Optimization(GWO) Algorithm. The performance of energy management approach with different contingency cases are considered in the analysis on modified IEEE 30 bus system. The power and energy generation, generation cost, energy saving, rescheduling cost for different cases are obtained. The rescheduling of generators are carried out by considering with and without Renewable Energy Source(RES) and it is shown that the rescheduling cost, energy loss and usage of fossil fuel with RES generator is reduced compared to rescheduling of generators without RES generators.