Abstract

An optimization model that incorporates demand in the paradigm of smart grids and distributed generation is formulated. The objective is to transform the demand into an active agent that helps minimizing costs incurred by a distribution company for energy purchases and capacity payments, in a cost based marginal pricing scheme, also extrapolated to market based bids. The development of a secondary market for ancillary services offered by demand is proposed, with local intelligence and distributed generation, operating in a similar way to a day ahead market. Existing resources from the demand-side are provided to allow hourly market adjustments. The demand uncertain future is modeled via preference models using discrete choice methods. Portfolios of incentives, tailored to demand needs and preferences, are built. Consumption profiles of users are identified from synthetic curves and real consumption profiles, associated to large customers. NYISO time series data are used to illustrate the mechanism operation. The optimization model may be easily integrated into any management model of a market operator or within electricity distribution and traders. The only requirement for proper incorporation is the use of two-way communications for coordinating with the customers in the smart-grid and distributed generation paradigm.