Optimal Day-ahead Energy Scheduling of Battery in Distribution Systems Considering Uncertainty

Abstract

One of the features in the modern smart grid is accommodation of different distributed generation resources and battery energy storage system (BESS). Because the renewable power generation is intermittent and uncertain, the BESS can help regulation of power generation, voltage and even system frequency. This paper explores a short term (24h) energy scheduling of batteries in a power system considering uncertain photovoltaic (PV) power generations and loads. The cost of losses is minimized while both equality and inequality constraints are satisfied. The equality constraints consist of the power flow equations and the energy balance equations for batteries. The inequality constraints comprise the limits of power and energy of batteries. The states (charging and discharging) of batteries are set according to the tariffs of electricity. Due to the uncertainty of PV powers and loads, the problem is solved by two loops: the outer loop is implemented by point-estimation method while the inner loop deals with the 24 h optimal power flow considering deterministic PV generations and loads using the interior-point method. A 33-bus distribution system of 3.454 MW (peak load) was used to show the simulation results. One PV farm (1MW) and six BESS at different buses were considered. The deterministic and stochastic results obtained by the proposed method were discussed and compared.