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Storage and Demand Side Management as power generator’s strategic instruments to influence demand and prices

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  • Prüggler, Natalie
  • Prüggler, Wolfgang
  • Wirl, Franz

Abstract

Classic storage utilisation is mainly based on charging/discharging strategies enabling a power generation company to generate revenues by buying electricity in low-price periods and selling it at higher prices. Within this paper another feasible way to gain arbitrage in storage utilisation is considered: Strategically increasing demand disregarding existing market prices. This means, charging electricity for storage is not only bought in low price periods, but in all periods where storage charging could influence demand so that market prices increase. This idea is expanded by focussing on another frequently discussed topic which could serve utilities for the same purpose: Automated Demand Side Management (DSM). By using data from Ontario’s electricity market and applying a particular storage and DSM strategy it is analysed to which extent a non-regulated dominant power generation company could influence hourly demand and corresponding prices. It turns out that both strategies analysed derive additional revenues for the dominant power generation company compared to a Business-as-Usual (BAU) case. The results provide an indicator of potential threats for misuse from particular storage or DSM utilisation. Therefore, especially in countries where DSM and/or storage applications are still in its fledgling stages, appropriate market surveillance has to be guaranteed.

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  • Prüggler, Natalie & Prüggler, Wolfgang & Wirl, Franz, 2011. "Storage and Demand Side Management as power generator’s strategic instruments to influence demand and prices," Energy, Elsevier, vol. 36(11), pages 6308-6317.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:11:p:6308-6317
    DOI: 10.1016/j.energy.2011.09.048
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    References listed on IDEAS

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    3. Azzopardi, Brian & Gabriel-Buenaventura, Alejandro, 2014. "Feasibility assessment for high penetration of distributed photovoltaics based on net demand planning," Energy, Elsevier, vol. 76(C), pages 233-240.
    4. Macedo, M.N.Q. & Galo, J.J.M. & de Almeida, L.A.L. & de C. Lima, A.C., 2015. "Demand side management using artificial neural networks in a smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 128-133.
    5. Warren, Peter, 2014. "A review of demand-side management policy in the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 941-951.
    6. Prüggler, Natalie, 2013. "Economic potential of demand response at household level—Are Central-European market conditions sufficient?," Energy Policy, Elsevier, vol. 60(C), pages 487-498.
    7. Jonathan Muñoz Tabora & Ulisses Carvalho Paixão Júnior & Carlos Eduardo Moreira Rodrigues & Ubiratan Holanda Bezerra & Maria Emília de Lima Tostes & Bruno S. de Albuquerque & Edson Ortiz de Matos & An, 2021. "Hybrid System Assessment in On-Grid and Off-Grid Conditions: A Technical and Economical Approach," Energies, MDPI, vol. 14(17), pages 1-21, August.

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