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Expediting battery investment returns for residential customers utilising spot price-aware local energy exchanges

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  • Ali, Liaqat
  • Azim, M. Imran
  • Peters, Jan
  • Pashajavid, Ehsan

Abstract

This paper presents a local energy exchange mechanism to benefit residential customers and retailers under variable wholesale market spot prices. To do so, a peer-to-peer (P2P) trading-enabled local energy market (LEM) is proposed to facilitate frequent energy transactions among participants. The proposed LEM mechanism considers market operational constraints and maximises electricity cost reductions. Further, the proposed LEM optimises the customers' investment return for battery energy storage systems (BESSs) and minimises retailers’ financial losses during higher spot prices in the wholesale market. Finally, a case study is demonstrated using real-world Australian data in which P2P trading is performed between interested buyers and sellers. Two scenarios with high and low wholesale market spot prices are analysed comprehensively considering five metrics such as solar-to-spot (STS); solar-to-load (STL); forward buy contract (FBC)-to-load (FBC-L); spot-to-load (Short); and FBC-to-spot (Long). The simulation results reveal that the customers reap substantial benefits from the proposed LEM in contrast with business-as-usual (BAU), allowing them to expedite BESS investment returns. Also, the proposed LEM helps a retailer decrease the effect of higher spot prices by reducing its unexpected financial losses while improving self-consumption and self-sufficiency in the local energy network.

Suggested Citation

  • Ali, Liaqat & Azim, M. Imran & Peters, Jan & Pashajavid, Ehsan, 2024. "Expediting battery investment returns for residential customers utilising spot price-aware local energy exchanges," Energy, Elsevier, vol. 306(C).
    • Handle: RePEc:eee:energy:v:306:y:2024:i:c:s0360544224022321
    DOI: 10.1016/j.energy.2024.132458
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    References listed on IDEAS

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    1. Huang, Pei & Lovati, Marco & Zhang, Xingxing & Bales, Chris & Hallbeck, Sven & Becker, Anders & Bergqvist, Henrik & Hedberg, Jan & Maturi, Laura, 2019. "Transforming a residential building cluster into electricity prosumers in Sweden: Optimal design of a coupled PV-heat pump-thermal storage-electric vehicle system," Applied Energy, Elsevier, vol. 255(C).
    2. Haider, Sajjad & Rizvi, Rida e Zahra & Walewski, John & Schegner, Peter, 2022. "Investigating peer-to-peer power transactions for reducing EV induced network congestion," Energy, Elsevier, vol. 254(PB).
    3. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan & Cui, Chuanshi, 2024. "Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi-microgrid system," Energy, Elsevier, vol. 288(C).
    4. Pol Olivella-Rosell & Pau Lloret-Gallego & Íngrid Munné-Collado & Roberto Villafafila-Robles & Andreas Sumper & Stig Ødegaard Ottessen & Jayaprakash Rajasekharan & Bernt A. Bremdal, 2018. "Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level," Energies, MDPI, vol. 11(4), pages 1-19, April.
    5. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Markovska, Natasa & Georghiou, George E., 2022. "Virtual net-billing: A fair energy sharing method for collective self-consumption," Energy, Elsevier, vol. 254(PB).
    6. Niesr, 2024. "National Institute Global Economic Outlook – Summary," National Institute Global Economic Outlook, National Institute of Economic and Social Research, issue 13, pages 4-6.
    7. Neves, Diana & Scott, Ian & Silva, Carlos A., 2020. "Peer-to-peer energy trading potential: An assessment for the residential sector under different technology and tariff availabilities," Energy, Elsevier, vol. 205(C).
    8. Niesr, 2024. "National Institute UK Economic Outlook Summer 2024," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 15, pages 5-6.
    9. Iria, José & Soares, Filipe & Matos, Manuel, 2018. "Optimal supply and demand bidding strategy for an aggregator of small prosumers," Applied Energy, Elsevier, vol. 213(C), pages 658-669.
    10. Esmaeili Aliabadi, Danial & Kaya, Murat & Sahin, Guvenc, 2017. "Competition, risk and learning in electricity markets: An agent-based simulation study," Applied Energy, Elsevier, vol. 195(C), pages 1000-1011.
    11. Mariza P. Oliveira-Roza & Roberto A. Cecílio & David B. S. Teixeira & Michel C. Moreira & André Q. Almeida & Alexandre C. Xavier & Sidney S. Zanetti, 2024. "Rainfall Erosivity over Brazil: A Large National Database," Data, MDPI, vol. 9(10), pages 1-9, October.
    12. Huang, Zhijia & Wang, Fang & Lu, Yuehong & Chen, Xiaofeng & Wu, Qiqi, 2023. "Optimization model for home energy management system of rural dwellings," Energy, Elsevier, vol. 283(C).
    Full references (including those not matched with items on IDEAS)

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