Power management and frequency regulation for microgrid and smart grid : a real-time demand response approach

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Date

2014

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Montana State University - Bozeman, College of Engineering

Abstract

Future power systems (known as smart grid) will experience a high penetration level of variable distributed energy resources to bring abundant, affordable, clean, efficient, and reliable electric power to all consumers. However, it might suffer from the uncertain and variable nature of these generations in terms of reliability and especially providing required balancing reserves. In the current power system structure, balancing reserves (provided by spinning and non-spinning power generation units) usually are provided by conventional fossil-fueled power plants. However, such power plants are not the favorite option for the smart grid because of their low efficiency, high amount of emissions, and expensive capital investments on transmission and distribution facilities, to name a few. Providing regulation services in the presence of variable distributed energy resources would be even more difficult for islanded microgrids. The impact and effectiveness of demand response are still not clear at the distribution and transmission levels. In other words, there is no solid research reported in the literature on the evaluation of the impact of DR on power system dynamic performance. In order to address these issues, a real-time demand response approach along with real-time power management (specifically for microgrids) is proposed in this research. The real-time demand response solution is utilized at the transmission (through load-frequency control model) and distribution level (both in the islanded and grid-tied modes) to provide effective and fast regulation services for the stable operation of the power system. Then, multiple real-time power management algorithms for grid-tied and islanded microgrids are proposed to economically and effectively operate microgrids. Extensive dynamic modeling of generation, storage, and load as well as different controller design are considered and developed throughout this research to provide appropriate models and simulation environment to evaluate the effectiveness of the proposed methodologies. Simulation results revealed the effectiveness of the proposed methods in providing balancing reserves and microgrids' economic and stable operation. The proposed tools and approaches can significantly enhance the application of microgrids and demand response in the smart grid era. They will also help to increase the penetration level of variable distributed generation resources in the smart grid.

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