A New Paradigm for Distributed Generation Management Considering the Renewable ‎Energy Uncertainties and Demand Response Resources

Peyman Ghanbari-Mobarakeh, Mohammadreza Moradian

Abstract


In recent decades, the prevalence of microgrids with the resolution of more exploitation of demand-side renewable energy ‎resources ‎has been vastly increased. The advantages of microgrids such as reduction of operation ‎costs, use of clean ‎renewable energy, and improvement in the reliability of the system have assumed ‎significant attention to this ‎subject. In this regard, the optimization of microgrids is an important ‎item, which reinforces the plus sides ‎of microgrid scheme. The demand response programs (DRPs) are ‎practical tools accessible for the operator to ‎facilitate and optimize the management of the grid’s ‎operation and are counted as novel evolutions in ‎modern power systems. Demand response implies ‎that the consumers can have participation in reshaping and correction of the load pattern. These ‎programs can achieve considerable profits from both consumers and the grid point of view such as ‎reduction of load shedding, mitigation of generation cost, smoothing the load curve, alleviation of ‎price fluctuations in electricity markets etc. In this study, a new energy management scheme is ‎proposed in order to obtain the optimized performance of the microgrid in presence of renewable ‎resources. The short-term operational costs are declined by incorporation of incentive-based programs (IBP). The results of the simulations are illustrated through three scenarios ‎to assess the improvements in costs and emissions. The implication of the presence of renewable and ‎demand response resources is investigated in these scenarios. Moreover, the Chicken swarm optimization algorithm is employed to conduct the optimization of the objective function. The results reveal that the suggested scheme is effective and beneficial.


Keywords


Microgrid, uncertainty, energy management system, renewable energy resources, demand response resources.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v9i1.8918.g7578

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