Optimized Operation-Planning of a Microgrid with Renewable Sources and Vehicle to Grid

Asad Waqar, Shaorong Wang, Qasim Kamil Mohsin, Muhammad Zahid

Abstract


The microgrid with renewable sources possess stability issues. During the grid-connected mode, these issues are taken care by the external grid. However in case of islanding, the distributed generators within the microgrid, have to take care of these issues independently. It needs additional backup like diesel generation or battery storage, which increases the overall capital and operation costs. With the intervention of the V2G storage, these costs can be saved to some extent. However similar to the renewable sources like wind and solar, the power from V2G is also fluctuating which may lead the microgrid towards an uneconomical operation. Therefore an extensive operation-planning is needed to deal with these uncertainties, for the microgrid to be economically viable. In this context, the stochastic programming has been applied to achieve the optimum results. The stochastic scenarios for wind speed, solar radiation, V2G power and load fluctuation have been generated using the Markov chain Monte Carlo method. The optimized operation-planning aims to minimize the total net present cost, size of the fixed storage and fossil fuel emissions subject to constraints. The simulations have been performed using Matlab/Simulink, HOMER and Excel. The simulation results show that the V2G technology substantially decrease the total net present cost. Moreover for such a microgrid the total net present cost and fossil fuel emissions conflict with each other.


Keywords


V2G, operational planning, chance constrained programming, Metropolis-Hastings algorithm, microgrid

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DOI: http://doi.org/10.11591/ijeecs.v16.i3.pp401-408

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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