PROJECT TITLE:

A Multivariable Optimal Energy Management strategy for Standalone DC Micro grids - 2015

ABSTRACT:

Due to substantial generation and demand fluctuations in standalone inexperienced microgrids, energy management methods are becoming essential for the ability sharing and voltage regulation functions. The classical energy management strategies use the maximum power point tracking (MPPT) algorithms and rely on batteries in case of doable excess or deficit of energy. But, in order to appreciate constant current-constant voltage (IU) charging regime and increase the generation of batteries, energy management methods need being a lot of flexible with the facility curtailment feature. In this paper, a coordinated and multivariable energy management strategy is proposed that employs a wind turbine and a photovoltaic array of a standalone DC microgrid as controllable generators by adjusting the pitch angle and the switching duty cycles. The proposed strategy is developed as an on-line nonlinear model predictive management (NMPC) algorithm. Applying to a sample standalone dc microgrid, the developed controller realizes the IU regime for charging the battery bank. The variable load demands also are shared accurately between generators in proportion to their ratings. Moreover, the DC bus voltage is regulated at intervals a predefined vary, as a style parameter.