Assessing the Value of Demand Response in Microgrids
This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic part...
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doaj-0f3f078da9ec4e28bb857ebbc0da53552021-06-01T00:50:32ZengMDPI AGSustainability2071-10502021-05-01135848584810.3390/su13115848Assessing the Value of Demand Response in MicrogridsIsaías Gomes0Rui Melicio1Victor M. F. Mendes2IDMEC, Instituto de Engenharia Mecânica, Universidade de Lisboa, 1049-001 Lisboa, PortugalIDMEC, Instituto de Engenharia Mecânica, Universidade de Lisboa, 1049-001 Lisboa, PortugalCISE, Electromechatronic Systems Research Centre, Universidade da Beira Interior, 6201-001 Covilhã, PortugalThis paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.https://www.mdpi.com/2071-1050/13/11/5848microgriddemand responsestochastic programmingenergy managementrenewable energy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Isaías Gomes Rui Melicio Victor M. F. Mendes |
spellingShingle |
Isaías Gomes Rui Melicio Victor M. F. Mendes Assessing the Value of Demand Response in Microgrids Sustainability microgrid demand response stochastic programming energy management renewable energy |
author_facet |
Isaías Gomes Rui Melicio Victor M. F. Mendes |
author_sort |
Isaías Gomes |
title |
Assessing the Value of Demand Response in Microgrids |
title_short |
Assessing the Value of Demand Response in Microgrids |
title_full |
Assessing the Value of Demand Response in Microgrids |
title_fullStr |
Assessing the Value of Demand Response in Microgrids |
title_full_unstemmed |
Assessing the Value of Demand Response in Microgrids |
title_sort |
assessing the value of demand response in microgrids |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2021-05-01 |
description |
This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid. |
topic |
microgrid demand response stochastic programming energy management renewable energy |
url |
https://www.mdpi.com/2071-1050/13/11/5848 |
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