Aysegul KahramanOnder BulutEmrah BiyikCuneyt GuzelisGokhan DemirkiranDemirkiran, GokhanGuzelis, CuneytKahraman, AysegulBulut, OnderBiyik, Emrah2025-10-062019978-1-7281-2868-9978172812868910.1109/asyu48272.2019.89464392-s2.0-85078359716http://dx.doi.org/10.1109/asyu48272.2019.8946439https://gcris.yasar.edu.tr/handle/123456789/5744https://doi.org/10.1109/asyu48272.2019.8946439https://doi.org/10.1109/ASYU48272.2019.8946439Microgrids enable the integration of distributed energy resources with high renewable penetration into the main power grid. In this study a microgrid problem that takes into account the stochastic nature of the net load defined as the difference between actual demand and renewable generation is studied. The problem is formulated as a Mixed Integer Linear Stochastic Optimization Programming and is solved under different net load distributions and planning horizons. Numerical results show that increasing variance causes a rise in total system cost for the approach that solves the stochastic problem by ignoring randomness (as in most real-life applications) as well as for the one that solves the problem with the true distribution. It is observed that enlarging the planning horizon also has similar effects.Turkishinfo:eu-repo/semantics/closedAccessMicrogrids, energy systems, optimal control, stochastic programmingOptimal ControlEnergy SystemsMicrogridsStochastic ProgrammingConference Object