Sayyad Nojavan

Penetration of renewable energy sources (RESs) in power systems increase all over the world to overcome current challenges, most importantly environmental issues. Beside advantages of RESs, their integration into the power systems have imposed various challenges considering uncertain and intermitted power output. To cope with these challenges, utilizing energy storage systems with renewable energy sources alongside the demand response (DR) programs are considered as reliable solutions. On the other hand, in an uncertain environment, minimizing worst-case cost or regret is counted as an important criterion to evaluate operation of any system under uncertain parameters. Therefore, in this paper, optimal operation of power systems is solved under penetration of wind turbines, hydrogen storage system, and DR programs in an uncertain environment. To guarantee robust operation of the system under the worst-case scenario, a novel stochastic p-robust optimization method (SPROM) is proposed which combines both stochastic programming and robust optimization approaches where minimizes the worst-case cost or regret level. The performance of the developed model is evaluated considering a six-bus test system under two cases as stochastic optimization (SO) and SPROM. Obtained results show that the maximum regret level is reduced considerably using the proposed SPROM comparing with pure stochastic method.