Demand-Side Management of Smart Distribution Grids Incorporating Renewable Energy Sources

Gerardo J. Osório, Miadreza Shafie-khah, Mohamed Lotfi, Bernardo J. M. Ferreira-Silva and João P. S. Catalão
Additional contact information
Gerardo J. Osório: C-MAST, University of Beira Interior, Calcada Fonte Lameiro, 6201-001 Covilha, Portugal
Miadreza Shafie-khah: INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
Mohamed Lotfi: INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
Bernardo J. M. Ferreira-Silva: Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
João P. S. Catalão: INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal

Energies, 2019, vol. 12, issue 1, 1-23

Abstract: The integration of renewable energy resources (RES) (such as wind and photovoltaic (PV)) on large or small scales, in addition to small generation units, and individual producers, has led to a large variation in energy production, adding uncertainty to power systems (PS) due to the inherent stochasticity of natural resources. The implementation of demand-side management (DSM) in distribution grids (DGs), enabled by intelligent electrical devices and advanced communication infrastructures, ensures safer and more economical operation, giving more flexibility to the intelligent smart grid (SG), and consequently reducing pollutant emissions. Consumers play an active and key role in modern SG as small producers, using RES or through participation in demand response (DR) programs. In this work, the proposed DSM model follows a two-stage stochastic approach to deal with uncertainties associated with RES (wind and PV) together with demand response aggregators (DRA). Three types of DR strategies offered to consumers are compared. Nine test cases are modeled, simulated, and compared in order to analyze the effects of the different DR strategies. The purpose of this work is to minimize DG operating costs from the Distribution System Operator (DSO) point-of-view, through the analysis of different levels of DRA presence, DR strategies, and price variations.

Keywords: demand response aggregators; demand side management; renewable energy; smart grid; stochastic programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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