Stochastic energy management of microgrid with nodal pricing

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dc.contributor.author Prudhviraj, Dhanapala
dc.contributor.author Kiran, P. B. S.
dc.contributor.author Pindoriya, Naran M.
dc.date.accessioned 2019-12-18T12:44:35Z
dc.date.available 2019-12-18T12:44:35Z
dc.date.issued 2019-12
dc.identifier.citation Prudhviraj, Dhanapala; Kiran, P. B. S. and Pindoriya, Naran M., "Stochastic energy management of microgrid with nodal pricing ", Journal of Modern Power Systems and Clean Energy, DOI: 10.35833/MPCE.2018.000519, Dec. 2019. en_US
dc.identifier.isbn Microgrids
dc.identifier.isbn Mathematical model
dc.identifier.isbn Load modeling
dc.identifier.isbn Energy management
dc.identifier.isbn Uncertainty
dc.identifier.isbn Stochastic processes
dc.identifier.isbn Pricing
dc.identifier.isbn battery energy storage system (BESS)
dc.identifier.isbn demand response (DR)
dc.identifier.isbn distributed generation
dc.identifier.isbn microgrid
dc.identifier.isbn mixed integer non-linear programming (MINLP)
dc.identifier.isbn scheduling
dc.identifier.isbn stochastic optimization
dc.identifier.issn 2196-5625
dc.identifier.issn 2196-5420
dc.identifier.uri https://doi.org/10.35833/MPCE.2018.000519
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/5034
dc.description.abstract This paper develops a stochastic framework for the energy management of a microgrid to minimize the energy cost from the grid. It considers the uncertainties in solar photovoltaic (PV) generation, load demand, and electricity price. Furthermore, the opportunity of flexible load demand, i.e., the effect of demand response (DR), on the test system is studied. The uncertainties are modeled by using Monte Carlo simulations and the generated scenarios are reduced to improve the computational tractability. In general, microgrid scheduling is implemented by using substation (source node) price as a reference, but that reference price is not the same at all nodes. Therefore, this paper develops the nodal price based energy management in a microgrid to improve the scheduling accuracy. The stochastic energy management framework is formulated as a mixed integer non-linear programming (MINLP). Four case studies are simulated for a modified 15-node radial distribution network integrated with solar PV and battery energy storage system (BESS) to validate the effectiveness of the energy management framework for a microgrid with nodal pricing.
dc.description.statementofresponsibility by Dhanapala Prudhviraj, P. B. S. Kiran and Naran M. Pindoriya
dc.language.iso en_US en_US
dc.publisher SpringerOpen en_US
dc.title Stochastic energy management of microgrid with nodal pricing en_US
dc.type Article en_US
dc.relation.journal Journal of Modern Power Systems and Clean Energy


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