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Intelligent energy management using powermatcher: Recent results from field deployments and simulation studies

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Author: Kok, J.K. · Roossien, B. · MacDougall, P.A. · Pruissen, O.P. van · Venekamp, G. · Kamphuis, I.G. · Laarakkers, J.A.W. · Warmer, C.
Publisher: IET
Place: London
Source:22nd International Conference and Exhibition on Electricity Distribution, CIRED 2013, 10-13 June 2013, Stockholm, Sweden
IET Conference Publications
Identifier: 500197
doi: doi:10.1049/cp.2013.1251
Article number: 1470
Keywords: Energy · Congestion management · Electrical vehicles · Electricity storages · Intelligent energy management · Large-scale wind power generations · Network operations · Smart Grid technologies · Virtual power plants · Commerce · Distributed power generation · Domestic appliances · Electric energy storage · Electric power transmission networks · Electric utilities · Exhibitions · Heating · Smart power grids · Computer simulation · Energy Efficiency · Energy / Geological Survey Netherlands · Communication & Information · SEM - Service Enabling & Management · TS - Technical Sciences


Response of demand, distributed generation and electricity storage (e.g. vehicle to grid) will be crucial for power systems management in the future smart electricity grid. In this paper, we describe recent results using PowerMatcher a smart grid technology that integrates demand and supply flexibility in the operation of the electricity system through the use of dynamic pricing. Over the last few years, this technology has been researched and developed into a market-ready system, and has been used in a number of successful field deployments. Recent field experiences and simulation studies show the potential of the technology for network operations (e.g. congestion management and black-start support), for market operations (e.g. virtual power plant operations), and integration of large-scale wind power generation. The scalability of the technology, i.e. the ability to perform well under mass-application circumstances, has been demonstrated in a targeted field experiment. This paper gives an overview of the results of two field deployments and three large simulation studies. In these deployments and simulations, demand and supply response from real and simulated electrical vehicles, household appliances and heating systems (heat pumps and micro co-generation) has been successfully coordinated to reach specific smart grid goals.