4.6 Article

Assessing the Value of Demand Response in Microgrids

Journal

SUSTAINABILITY
Volume 13, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/su13115848

Keywords

microgrid; demand response; stochastic programming; energy management; renewable energy

Funding

  1. Bolsas Camoes, IP/Millennium BCP Foundation
  2. European Union through the European Regional Development Fund
  3. Foundation for Science and Technology (FCT) under the ICT (Institute of Earth Sciences) project [UIDB/04683/2020]
  4. Portuguese Funds through the Foundation for Science and Technology (FCT) under the LAETA project [UIDB/50022/2020]
  5. Portuguese Foundation for Science and Technology (FCT) under the CISE Project [UIDB/04131/2020, UIDP/04131/2020]
  6. Fundação para a Ciência e a Tecnologia [UIDP/04131/2020, UIDB/04131/2020] Funding Source: FCT

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This paper presents a computer application to assist in decisions about enhancing sustainability by shifting demand to more convenient periods in a microgrid. The proposed approach customizes a stochastic programming problem to manage uncertainties in decision making. Case studies show opportunities for significant profit enhancements through better bidding and energy consumption decisions.
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.

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