Optimal Coordinated Energy Management in Active Distribution System with Battery Energy Storage and Price-Responsive Demand

Contemporary distribution networks can be seen with diverse dispatchable and nondispatchable energy resources. The coordinated scheduling of these resources, together provide several technoeconomic social benefits. Since battery storage systems (BESSs) microturbine units (MT units) are capital-intensive, a thorough investigation their under the economic criterion will challenging task while considering dynamic electricity prices uncertainties renewable power generation load demand. This paper proposes comprehensive methodological framework for optimal BESSs MT unit existing resources to maximize daily profit function utility by employing recently explored modified African buffalo optimization algorithm. key attributes proposed methodology comprised mean price-based adaptive embedded within decision mechanism system (DMS) arbitrage DMS keeps track states as priori, thus resulting in an artificial intelligence-based solution technique sequential optimization. Further, novel concept fictitious charges is also restrict counterproductive operational management BESSs. model method demonstrated on 33-bus system, obtained results verify effectiveness methodology.