Abstract
In the restructured electricity market, microgrid (MG), with the incorporation of smart grid technologies,
distributed energy resources (DERs), a pumped-storage-hydraulic (PSH) unit, and a demand response program
(DRP), is a smarter and more reliable electricity provider. DER consists of gas turbines and renewable energy
sources such as photovoltaic systems and wind turbines. Better bidding strategies, prepared by MG operators,
decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources
(RES). But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate. To
solve these issues, this study suggests non-dominated sorting genetic algorithmII (NSGA-II) for an optimal bidding
strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties
of renewable energy sources. The uncertainty related to solar and wind units is modeled using lognormal and
Weibull probability distributions. TOU-based DRP is used, especially considering the time of outages along with
the time of peak loads and prices, to enhance the reliability of MG and reduce costs and emissions.