Stochastic Energy Management of Microgrid with Nodal Pricing

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 eff...

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Main Authors: Dhanapala Prudhviraj, P. B. S. Kiran, Naran M. Pindoriya
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8922949/
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spelling doaj-33538add452641439ba4c6555bada6ce2021-04-23T16:10:43ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202020-01-018110211010.35833/MPCE.2018.0005198922949Stochastic Energy Management of Microgrid with Nodal PricingDhanapala Prudhviraj0P. B. S. Kiran1Naran M. Pindoriya2Indian Institute of Technology Gandhinagar,Department of Electrical Engineering,Gandhinagar,India,382355Indian Institute of Technology Gandhinagar,Department of Electrical Engineering,Gandhinagar,India,382355Indian Institute of Technology Gandhinagar,Department of Electrical Engineering,Gandhinagar,India,382355This 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.https://ieeexplore.ieee.org/document/8922949/Battery energy storage system (BESS)demand response (DR)distributed generationmicrogridmixed integer non-linear programming (MINLP)scheduling
collection DOAJ
language English
format Article
sources DOAJ
author Dhanapala Prudhviraj
P. B. S. Kiran
Naran M. Pindoriya
spellingShingle Dhanapala Prudhviraj
P. B. S. Kiran
Naran M. Pindoriya
Stochastic Energy Management of Microgrid with Nodal Pricing
Journal of Modern Power Systems and Clean Energy
Battery energy storage system (BESS)
demand response (DR)
distributed generation
microgrid
mixed integer non-linear programming (MINLP)
scheduling
author_facet Dhanapala Prudhviraj
P. B. S. Kiran
Naran M. Pindoriya
author_sort Dhanapala Prudhviraj
title Stochastic Energy Management of Microgrid with Nodal Pricing
title_short Stochastic Energy Management of Microgrid with Nodal Pricing
title_full Stochastic Energy Management of Microgrid with Nodal Pricing
title_fullStr Stochastic Energy Management of Microgrid with Nodal Pricing
title_full_unstemmed Stochastic Energy Management of Microgrid with Nodal Pricing
title_sort stochastic energy management of microgrid with nodal pricing
publisher IEEE
series Journal of Modern Power Systems and Clean Energy
issn 2196-5420
publishDate 2020-01-01
description 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.
topic Battery energy storage system (BESS)
demand response (DR)
distributed generation
microgrid
mixed integer non-linear programming (MINLP)
scheduling
url https://ieeexplore.ieee.org/document/8922949/
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