PROJECT TITLE :

Optimal Battery Sizing in Microgrids Using Probabilistic Unit Commitment

ABSTRACT:

The Stochastic nature of wind power can cause insufficiency of supply in electrical systems. Applying an energy storage system will alleviate the impact of wind power forecast error on Power Systems performance and increase system tolerance against deficiency of provide. This paper tries to investigate a replacement unit commitment (UC) problem based on the value-benefit analysis and here-and-currently (HN) approach for optimal sizing of battery banks (BBs) imicrogrids (MGs) with wind power systems. To resolve this downside, particle swarm optimization is used to minimize the full price and maximize the full benefit. In this paper, twelve eventualities are thought of in the presence of BBs and without them in 2 operating modes: one) stand-alone mode and a couple of) grid-connected mode. Using the HN approach, the uncertainty of wind power is applied as a constraint in these operating modes. The mathematical formulations connected to the HN approach in MGs and its combination in an exceedingly UC drawback are presented intimately for optimal sizing of BBs. Simulation results show that the most effective sizes of BBs and the scheduling of distributed generations would be entirely totally different when the accessibility of wind power is taken into consideration by applying HN approach to the proposed probabilistic UC downside.