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Renewable energy aggregation with intelligent battery controller

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  • Li, Jiaming
  • Guo, Ying
  • Platt, Glenn
  • Ward, John K.

Abstract

Photovoltaic (PV) generation of electricity is an important renewable energy source. One way to increase the value of small-scale renewable generators is to aggregate and control their output so they appear to the wider grid as one larger generator. This paper introduces our Virtual Power Station system which aggregates multiple geographically dispersed small-scale photovoltaic generators together to present to the wider electricity system as a single dispatchable quantity in an energy market. As such a quantity has greater benefit to the wider system than the individual responses of many uncoordinated energy sites, the Virtual Power Station can improve the payback period for renewable energy systems. This paper describes a Virtual Power Station deployment with a diverse range of sites, and PV output, which are then coordinated together with an intelligent battery controller. We also introduce an optimal control strategy that manages the energy storage to allow a firm commitment of output energy from the Virtual Power Station.

Suggested Citation

  • Li, Jiaming & Guo, Ying & Platt, Glenn & Ward, John K., 2013. "Renewable energy aggregation with intelligent battery controller," Renewable Energy, Elsevier, vol. 59(C), pages 220-228.
    • Handle: RePEc:eee:renene:v:59:y:2013:i:c:p:220-228
    DOI: 10.1016/j.renene.2013.03.027
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    References listed on IDEAS

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    1. Joeri Rogelj & David L. McCollum & Andy Reisinger & Malte Meinshausen & Keywan Riahi, 2013. "Probabilistic cost estimates for climate change mitigation," Nature, Nature, vol. 493(7430), pages 79-83, January.
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