Hybrid bio inspired algorithms for the dynamic dispatch of units incorporating wind energy penetration

Abstract

In day to day affair of power system operation power plants ensures hour ahead plans of dispatching the available generations for the power demand in a 24 hour horizon Dispatching the available generation with minimum fuel expenses amongst the generators scheduled for the purpose is called as Economic Dispatch Problem EDP This EDP is simple and most widely used problem in power system operation and control Large literature records this problem static in nature that is the dispatching will be carried out only in an hour assuming the previous and ahead generations are independent of each other But in practice this is just fictitious and use of nothing Thus a Dynamic Economic Dispatch Problem DEDP with ramprate newlineconstraints of generators makes this problem a challenging in day to day operation of power system The advent of renewable energy systems to the existing power system the loads on fossil fuelled power generations has reduced their burdens by throwing some loads to the renewable generations Thus wind power is one amongst the widely used alternative source of energy Thus this research will propose a suitable wind prediction model to give reasonable load sharing to the DEDP In order to do so a bio inspired algorithm named Social Spider Algorithm SSA is utilized such a way that its performance is hybridized with a rebellious operator Also this hybridized SSA is again used along with a convolution neural network to predict the wind power before dispatching the DEDP newline newline