Abstract

Virtual power plants (VPPs) are highly motivated to perform demand response programs as an effective electricity source along with other energy sources. However, scheduling demand response (DR) provided by individual customers will not be an easy task. Therefore, individual responsive customers are planned by a sub-entity in VPP, called VPP demand response aggregator (VPP-DRA). In other words, the VPP-DRA aggregates DR provided including load curtailment (LC) and load shifting (LS) applications by playing a mediator role between individual customers and the distribution system operator (DSO). This chapter develops two different programming approaches to model DR applications in the VPP, namely single level scheduling approach (SLSA) and bi-level scheduling approach (BLSA). In SLSA, DSO imports electricity from the electricity market and schedules individual DRs to meet its demand. However, fair transaction between DSO and VPP-DRA is modeled through the BLSA. In the BLSA, VPP-DRA aggregates individual customers and negotiates with the DSO to determine optimal contract prices for performing DR applications. On the one hand, the VPP-DRA seeks to maximize its obtained profit by offering aggregated DR of the responsive loads to DSO and, on the other hand, the DSO aims to minimize its incurred payments to supply customers. The presented BLSA is converted into a single-level optimization problem by implementing its Karush–Kuhn–Tucker (KKT) optimality conditions. Finally, five different scenarios are used to verify the capability of the proposed models.

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