Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

• A stochastic energy procurement cost function in presence of DRP is proposed.
• The load, price and output power of PV and wind uncertainties are modeled.
• Four case studies are used to assess the effects of ESS and DRP on SEPP.
• Case 4 is considered the effects of ESS and DRP simultaneously.
• The expected energy procurement cost of case 4 is lower than cases 1, 2 and 3.

This paper proposes a stochastic energy procurement problem (SEPP) for large electricity consumer (LEC) with multiple energy procurement sources (EPSs) considering the effects of demand response program (DRP) and energy storage system (ESS). The EPSs contain power market (PM), bilateral contracts (BCs), micro-turbines (MTs), and renewable energy sources (RESs). Moreover, the RESs include photovoltaic (PV) systems and wind-turbines (WT). The ESS and DRP are incorporated in the SEPP by the LEC’s decision-maker to reduce the expected energy procurement cost (EEPC). Meanwhile, the uncertainty models of market price, load and RES output power are considered in the SEPP formulation. The error of forecasting of market price, load, temperature and radiation of PV systems are modeled using the normal distribution for generating the related scenarios. Also, the weibull distribution is used to generate variable wind speed scenarios for WT output power uncertainty modeling. Furthermore, the fast forward selection based on Kantorovich distance approach is used for the scenarios reduction. Finally, the influences of ESS and DRP on EEPC are investigated, and four case studies are used to illustrate the capability of the proposed SEPP. The obtained results demonstrate the efficiency of the proposed stochastic program.