Day-ahead scheduling for virtual power plant to participate in energy and spinning reserve markets

In this paper a scheduling model is implemented to determine optimal simultaneous energy and spinning reserve
 SR) procurement. Also optimal bidding strategy, considering wind power plants (WPPs) and storage facilities penetration in
distribution network has been represented. The virtual power plant (VPP) has used mix of available resources to maximize its expected profit by participating in both energy/SR day-ahead markets. The pumped storage plant (PSP) and gridable vehicle units (GVUs) are modeled as storage facilities in the VPP Moreover, consumers can participate in both energy and SR markets using VPP demand response (DR) programs. This paper models uncertainty in available electric power of WPPs, energy and reserve day-ahead market prices and the manner of GVU owners using point estimated method (PEM). The stochastic generation of WPP is covered through allocating desirable SR the proposed method is applied to an 18 busses distribution test system over 24-h period

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