DocumentCode
267477
Title
Stochastic evaluation of aggregator business models — Optimizing wind power integration in distribution networks
Author
Lambert, Quentin ; Sandels, Claes ; Nordstrom, Lars
Author_Institution
Dept. of Ind. Inf. & Control Syst., R. Inst. of Technol., Stockholm, Sweden
fYear
2014
fDate
18-22 Aug. 2014
Firstpage
1
Lastpage
8
Abstract
In order to limit the environmental impact of electricity production, renewable energy sources are expected to expand significantly. The current grid and production structure are not designed to absorb such quantities of intermittent power output and smart grids can provide promising solutions, like demand response. This paper presents the technical advantages of managing flexible demand through Aggregators in a centralized fashion. An optimization model is developed to evaluate the economic benefits induced by adapting instantaneous electricity consumption to renewable generation. The model presented can easily be adapted in a more general context, and tested for different scenarios. Further, a use case related to the Smart Grids project on the Swedish island of Gotland is simulated. The simulation results show that the Aggregator solution is technically feasible, but that the current market design is a barrier for a successful implementation.
Keywords
demand side management; distribution networks; optimisation; wind power plants; aggregator business models; aggregator solution; distribution networks; flexible demand management; instantaneous electricity consumption; optimization model; renewable generation; smart grids; stochastic evaluation; wind power integration optimization; Adaptation models; Biological system modeling; Business; Electricity; Load management; Optimization; Production; Aggregators; Demand Side Management; Distribution Networks; Local Supply/Demand Matching; Wind Power Integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Systems Computation Conference (PSCC), 2014
Conference_Location
Wroclaw
Type
conf
DOI
10.1109/PSCC.2014.7038104
Filename
7038104
Link To Document