Abstract
In this work, a power market framework is presented comprised of demand response aggregators (DRAs) trading energy stored in residential batteries. Competition is modeled by a Stackelberg game, with market clearing hourly, which determines each DRAs bidding strategy that will maximize payoff. The magnitude and price of power transactions allowable is controlled by the game’s leader. Dynamic pricing is considered in two forms. As demand updates, dynamic economic dispatch is used to update utility generator dispatch. The marginal electrical price offered by the utility updates each time interval reflecting updated supply and demand (real time pricing). Time-of-use load scheduling through dynamic programing combined with dynamic pricing optimizes load scheduling and reduces total demand in the system. The method schedules utility generation minimizing supply-side operational cost, and in turn, demand-side electricity cost at all times (valley, peak, off-peak) and is thus mutually advantageous.
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Motalleb, M., Branigan, J. & Ghorbani, R. Poster abstract: demand response market considering dynamic pricing. Comput Sci Res Dev 33, 257–258 (2018). https://doi.org/10.1007/s00450-017-0371-6
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DOI: https://doi.org/10.1007/s00450-017-0371-6