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Market Optimization of a Cluster of DG-RES, Micro-CHP, Heat Pumps and Energy Storage within Network Constraints: The PowerMatching City Field Test

  • René Kamphuis
  • Bart Roossien
  • Frits Bliek
  • Albert van de Noort
  • Jorgen van de Velden
  • Johan de Wit
  • Marcel Eijgelaar
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 54)

Abstract

The share of renewable energy resources for electricity production, in a distributed setting (DG-RES), increases. The amount of energy transported via the electricity grid by substitution of fossil fuels for mobility applications (electric vehicles) and domestic heating (heat pumps) increases as well. Apart from the volume of electricity also the simultaneity factor increases at all grid levels. This poses unprecedented challenges to capacity management of the electricity infra-structure. A solution for tackling this challenge is using more active distribution networks, intelligent coordination of supply and demand using ICT and using the gas distribution network to mitigate electricity distribution bottlenecks.

In the EU FP6 Energy Program Integral project, a large scale heterogeneous field test has been designed for application of the software agent based PowerMatcher technology. The test is conducted in a suburb of Groningen, Hoogkerk, and entails approximately 30 homes with either a ‘dual fuel’ heating system (electrical heat pump with gas-fired peak-burners) or a micro-CHP. Homes also may have PV. Furthermore, a wind production facility and nodes with electricity chargers for EVs and electricity storage are part of the Virtual Power Plant cluster, constructed in this way.

Domestic heating systems have intrinsic operational flexibility in comfort management through the thermal mass of the dwellings. Furthermore, the field test comfort systems are equipped with possibilities for hot water storage for central heating as well as for tap-water. Finally, having additional gas-fired heating capacity for electrical heat-pumps adds to increasing flexibility by switching the energy source dependent on the status of the electricity grid.

Purpose of the field test is using this flexibility to react to phenomena in the electricity system.

  • From a commercial perspective, the aggregated cluster reacts on small-time scale events like real-time portfolio imbalance, compensation of ramp-up and ramp-down induced phenomena of large generators and compensating for variable output of renewables like PV and Wind. Aim for the latter is to reduce the margin between realization and forecast of a portfolio containing these resources.

  • From a distribution perspective, the total load on the transformer is monitored and coordination also involves diminishing this load during peak periods to improve the utilization of grid components and increase their lifetime.

    An extensive socio-economic study is performed on user perception of the control of these new types of installations. In this paper, the component configuration and set-up of the field-test and the architecture of the ICT-network for coordination are discussed. The test has commenced in December 2009.

Keywords

Heat Pump Electricity Grid Network Constraint Related Party Dual Fuel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. IEEE-PES,2008.
    Hommelberg, M.P.F., van der Velde, B.J., Warmer, C.J., Kamphuis, I.G., Kok, J.K.: A novel architecture for real-time operation of multi-agent based coordination of demand and supply. In: Warmer, C.J., Kamphuis, I.G. (eds.) Local DER Driven Grid Support by Coordinated Operation of Devices, IEEE-PES general Meeting, Pittsburg (2008)Google Scholar
  2. IEEE-NGI,2008.
    Kamphuis, I.G., Kok, J.K., Warmer, C.J., Hommelberg, M.P.F.: Architecture for novel energy infrastructures: Multi-agent based coordination patterns. In: IEEE-NGI, Rotterdam, The Netherlands (November 2008)Google Scholar
  3. AAMAS, 2005.
    Kok, J.K., Warmer, C.J., Kamphuis, I.G.: PowerMatcher: multiagent control in the electricity infrastructure. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents & Multi- Agent Systems AAMAS 2005, ACM, New York (2005); Industrial Track Volume, pp. 75 – 82Google Scholar
  4. SmartGridsSDD, 2008.
    Strategic deployment document for Europe’s Electricity Networks of the future, http://www.smartgrids.eu

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2011

Authors and Affiliations

  • René Kamphuis
    • 1
  • Bart Roossien
    • 1
  • Frits Bliek
    • 2
  • Albert van de Noort
    • 2
  • Jorgen van de Velden
    • 3
  • Johan de Wit
    • 3
  • Marcel Eijgelaar
    • 4
  1. 1.Unit Efficiency and InfrastructureEnergy research Centre of the NetherlandsPettenThe Netherlands
  2. 2.KEMA Gase Consultancy ServicesGroningenThe Netherlands
  3. 3.HumiqGroningenThe Netherlands
  4. 4.EssentDen BoschThe Netherlands

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