Two-stage Operational Planning of a Virtual Power Plant in ‎the Presence of a Demand Response Program

The spread of the smart grid has led to the widespread penetration of small-scale distributed ‎energy resources. Distributed generations (DGs) include conventional small-scale power plants and ‎renewable energies with no pollutant emission. This paper presents two-stage stochastic planning ‎for the participation of a virtual power plant (VPP) in energy and reserve markets in the presence ‎of demand response (DR) programs. The proposed VPP consists of various power generation sources, including wind turbines, ‎photovoltaics (PV),combined heat and power (CHP) units, microturbines, and boilers; power ‎storage sources, including battery storage systems (BSS) and thermal buffer tank (BT); and also ‎energy consumers, including electric vehicles (EV) and end consumers‎.The designed VPP enables participation in these markets by ‎aggregating DERs. Probability distribution functions are applied to generate scenarios based on ‎the existing uncertainties in renewable energy generation, energy price, and consumer demand. ‎The number of possible scenarios is reduced using a scenario reduction technique. Two-stage ‎stochastic planning is proposed to manage the designed VPP. The results suggest that participation ‎in DR programs leads to a considerable increase in optimal operational profit of the VPP. ‎

Keywords:

Demand Response , Virtual power plant , distributed generations , Renewable energies