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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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    Cited by:

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    2. Ismail, M.S. & Moghavvemi, M. & Mahlia, T.M.I. & Muttaqi, K.M. & Moghavvemi, S., 2015. "Effective utilization of excess energy in standalone hybrid renewable energy systems for improving comfort ability and reducing cost of energy: A review and analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 726-734.
    3. Malik, Ihtisham Abdul & Siyal, Ghamz-e-Ali & Bin Abdullah, Alias & Alam, Arif & Zaman, Khalid & Kyophilavong, Phouphet & Shahbaz, Muhammad & Baloch, Siraj Ullah & Shams, Tauqeer, 2014. "Turn on the lights: Macroeconomic factors affecting renewable energy in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 277-284.
    4. Haro, Pedro & Aracil, Cristina & Vidal-Barrero, Fernando & Ollero, Pedro, 2015. "Balance and saving of GHG emissions in thermochemical biorefineries," Applied Energy, Elsevier, vol. 147(C), pages 444-455.
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    6. Olsen, Stephen B. & McCann, Jennifer H. & Fugate, Grover, 2014. "The State of Rhode Island's pioneering marine spatial plan," Marine Policy, Elsevier, vol. 45(C), pages 26-38.
    7. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Teo, K.T.K., 2016. "Wind energy assessment considering wind speed correlation in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1389-1400.
    8. Chang, Youngho & Fang, Zheng & Li, Yanfei, 2016. "Renewable energy policies in promoting financing and investment among the East Asia Summit countries: Quantitative assessment and policy implications," Energy Policy, Elsevier, vol. 95(C), pages 427-436.
    9. Atalay, Yasemin & Kalfagianni, Agni & Pattberg, Philipp, 2017. "Renewable energy support mechanisms in the Gulf Cooperation Council states: Analyzing the feasibility of feed-in tariffs and auction mechanisms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 723-733.

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