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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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/ |
work_keys_str_mv |
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