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. ‎ Manuscript profile

Clean and sustainable renewable energy technology is going to take responsibility of energy supply in electrical power systems. Using renewable sources improve the environment and reduce dependence on oil and other fossil fuels. In distribution power system, utilizing of wind and solar DGs comprises some advantages; consist of loss and emission reduction, and also improvement of voltage profile. So, in expansion planning of distributed generations, improvement of each of these parameters can be the objective of planner. In this paper, a mathematical model for sizing and placement of wind and solar DGs is proposed. The formulation is based on a probabilistic load-generation model. The stochastic nature of the wind and solar resources are considered in the proposed scenario-based model. This mathematical framework is used to minimize total annual loss as an objective function. All the network constraints in different operational conditions are regarded. The model is applied on a typical rural distribution network using GAMS software which illustrated the effectiveness of the model. Manuscript profile