  Contemporary distribution network can be seen with diverse dispatchable and
non-dispatchable energy resources. The coordinated scheduling of these
dispatchable resources with non-dispatchable resources can provide several
techno-economic and social benefits. Since, battery energy storage systems
(BESSs) and microturbine (MT) units are capital intensive, a thorough
investigation of their coordinated scheduling on pure economic basis will be an
interesting and challenging task while considering dynamic electricity price
and uncertainty handling of non-dispatchable resources and load demand. This
paper proposes a new methodology for optimal coordinated scheduling of BESSs
and MT units considering existing renewable energy resources and dynamic
electricity price to maximize daily profit function of the utility by employing
a recently explored modified African buffalo optimization (MABO) algorithm. The
key attributes of the proposed methodology are comprised of mean price-based
adaptive scheduling embedded within a decision mechanism system (DMS) to
maximize arbitrage benefits. DMS keeps a track of system states as a-priori
thus guides the artificial intelligence based solution technique for sequential
optimization. This may also reduce the computational burden of complex
real-life engineering optimization problems. Further, a novel concept of
fictitious charges is proposed to restrict the counterproductive operational
management of BESSs. The application results investigated and compared on a
benchmark 33-bus test distribution system highlights the importance of the
proposed methodology.
