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Optimal contract pricing of load aggregators for direct load control in smart distribution systems

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Distribution system operators (DSOs) are interested in demand side participation programs as an efficient and secure resource to manage electricity supply and demand. However, it is usually difficult for DSOs… Click to show full abstract

Distribution system operators (DSOs) are interested in demand side participation programs as an efficient and secure resource to manage electricity supply and demand. However, it is usually difficult for DSOs to aggregate demand response of large/small consumers. Thus, in some electricity markets, an entity called an aggregator is defined to aggregate the load response of consumers. In this paper a bilevel scheduling model is proposed to determine the long-term optimal contract price between the DSO and aggregator for executing direct load control in smart distribution systems. The DSO and aggregator are considered as two different agents with individual objectives in the proposed bilevel scheduling model. On the one hand, the aggregator maximizes its profit by bidding load reduction of the large consumers to the DSO by executing a direct load control (DLC) mechanism, and on the other hand, the DSO tries to minimize its overall cost to supply all consumers. The DSO has two options to follow the variation of its consumers' demand: purchasing energy from the electricity market and executing DLC programs. The bilevel programming formulation is transferred into an equivalent single level programming problem using its Karush--Kuhn--Tucker optimality conditions. Moreover, the uncertainties of the electricity market price, demand of consumers, and generation of a wind power plant are modeled via point estimate method. Two typical case studies are implemented to demonstrate the effectiveness of the proposed scheduling model.

Keywords: optimal contract; load control; load; distribution; direct load

Journal Title: Turkish Journal of Electrical Engineering and Computer Sciences
Year Published: 2019

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