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

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 stochast...

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Bibliographic Details
Published inEnergies (Basel) Vol. 12; no. 1; p. 143
Main Authors Osório, Gerardo J., Shafie-khah, Miadreza, Lotfi, Mohamed, Ferreira-Silva, Bernardo J. M., Catalão, João P. S.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2019
Subjects
Air pollution
Algorithms
Alternative energy sources
Climate change
Consumption
Customers
demand response aggregators
demand side management
Elasticity of demand
Electric vehicles
Electricity generation
Emissions
Energy industry
Energy management
Energy policy
Energy resources
Energy sources
Environmental impact
Flexibility
Integration
Load
Market prices
Mitigation
Pollutants
Price elasticity
renewable energy
Renewable energy sources
smart grid
stochastic programming
Portugal
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12010143