Alamri, AbdullahAlowaifeer, MaadMeliopoulos, A.P Sakis2020-01-042020-01-042020-01-07978-0-9981331-3-3http://hdl.handle.net/10125/64106This paper presents a mixed integer linear program (MILP) to optimally size power and energy of energy storage systems (ESSs). The sizing model takes into account conventional generation (CG) operation constraints in addition to seasonal and locational wind speed and solar radiation variations, and variable generation (wind turbine systems (WTSs) and solar cell generators (SCGs)) forced outages. Subsequently, the outcomes of the ESS sizing model are inputted to the probabilistic production method (PCC) to assess the reliability of the integrated system. All aforementioned analyses have been applied to a system with different penetration levels. The method is demonstrated with case studies on a system consisting of 10 CG units and VG penetration levels of 20% and 30%. For each penetration level, ESS sizing is computed and then reliability assessment is performed.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalDistributed, Renewable, and Mobile Resourcesenergy storage systemsexpected unserved energyloss of load probabilitymixed integer linear programmingprobabilistic production costing.Conference Paper10.24251/HICSS.2020.364