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Contemporary distribution network can be seen with diverse dispatchable andnon-dispatchable energy resources. The coordinated scheduling of thesedispatchable resources with non-dispatchable resources can provide severaltechno-economic and social benefits. Since, battery energy storage systems(BESSs) and microturbine (MT) units are capital intensive, a thoroughinvestigation of their coordinated scheduling on pure economic basis will be aninteresting and challenging task while considering dynamic electricity priceand uncertainty handling of non-dispatchable resources and load demand. Thispaper proposes a new methodology for optimal coordinated scheduling of BESSsand MT units considering existing renewable energy resources and dynamicelectricity price to maximize daily profit function of the utility by employinga recently explored modified African buffalo optimization (MABO) algorithm. Thekey attributes of the proposed methodology are comprised of mean price-basedadaptive scheduling embedded within a decision mechanism system (DMS) tomaximize arbitrage benefits. DMS keeps a track of system states as a-priorithus guides the artificial intelligence based solution technique for sequentialoptimization. This may also reduce the computational burden of complexreal-life engineering optimization problems. Further, a novel concept offictitious charges is proposed to restrict the counterproductive operationalmanagement of BESSs. The application results investigated and compared on abenchmark 33-bus test distribution system highlights the importance of theproposed methodology.

Optimally Coordinated Energy Management Framework for Profit Maximization Considering Dispatchable and Non-Dispatchable Energy Resources