Amirali Shahkoomahalli - Department of Electrical Engineering, Aliabad katoul Branch,Islamic Azad University, Aliabad Katoul, Iran
Amangaldi Koochaki - Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
Heidarali Shayanfar - Center of Excellence for Power Systems Automation and Operation, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

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. ‎

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