Predictive models for power management of a hybrid microgrid — A review

The energy demand of the human civilization is increasing day by day, which has made man to look for alternative sources, considering that the fossil fuels, which are the principal sources of energy, are depleting. In addition, the carbon footprint left over by fossil fuels has a detrimental effect on the earth's environment. This has entailed researchers to focus their attention to environment friendly and renewable energy sources. The primary considerations in this subject viz. solar and wind energy sources pose their own challenges to researchers, an essential component being their stochastic nature. Weather conditions, weather patterns and the site chosen have a direct impact on the effectiveness of the implemented system. A helping hand is extended by nature with the fact that the availability of these two sources is complimentary to one another, assuring a power source in all weather conditions. This has paved way for researchers to converge their studies on Hybrid power systems which employ multiple types of power generators to cater to the demand. A Predictive Power Management scheme which incorporates a forecast of the power generation capability of each generator, the load demand and other site-specific parameters is vital to extract the best of the implemented system. Such a management system, which makes a long term forecast, minimizing errors on the behavioral patterns of wind and solar energy has become a major subject matter of study for researchers across the globe. This paper gives an overview of the power management strategies. Different predictive power management topologies, advantages and challenges are discussed.