Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed

Abstract

In a generation operating system planning, avoided utility cost (AUC) is customarily implemented to attain the optimal economic benefits in a generating system by taking into account intriguing issues on the energy efficiency, renewable energy sources or conservation programs. In this thesis a new approaches of optimal dispatch of limited energy unit (ODLEU) and demand side management (DSM) using computational intelligence approach is proposed for AUC improvement. Contrary to the conventional approaches, which mainly rely on dispatching of each limited energy unit (LEU) in sequential order, the proposed algorithm comprising with optimization technique is used as an alternative for performing LEU dispatch; which has a tangible impact to improve and increase the AUC value. In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). The AUC is originated from the summation of avoided energy cost, avoided expected cycle cost and avoided capacity cost of the generating system