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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Veröffentlicht in: | Sustainability 2021-06, Vol.13 (11), p.5848 |
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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. |
doi_str_mv | 10.3390/su13115848 |
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F.</creator><creatorcontrib>Gomes, Isaías ; Melicio, Rui ; Mendes, Victor M. F.</creatorcontrib><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.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su13115848</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Alternative energy sources ; Case studies ; Decision making ; Demand side management ; Distributed generation ; Electric power demand ; Electric vehicles ; Electricity ; Energy consumption ; Energy industry ; Energy management ; Energy resources ; Energy storage ; Flexibility ; Fuel cells ; Generators ; Heuristic ; Linear programming ; Market prices ; Mathematical programming ; Methods ; Photovoltaics ; R&D ; Research & development ; Stochastic programming ; Storage systems ; Strategic planning ; Sustainability ; Uncertainty ; Wind power</subject><ispartof>Sustainability, 2021-06, Vol.13 (11), p.5848</ispartof><rights>2021 by the authors. 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subjects | Alternative energy sources Case studies Decision making Demand side management Distributed generation Electric power demand Electric vehicles Electricity Energy consumption Energy industry Energy management Energy resources Energy storage Flexibility Fuel cells Generators Heuristic Linear programming Market prices Mathematical programming Methods Photovoltaics R&D Research & development Stochastic programming Storage systems Strategic planning Sustainability Uncertainty Wind power |
title | Assessing the Value of Demand Response in Microgrids |
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