IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v327y2022ics0306261922013186.html
   My bibliography  Save this article

Peer-to-Peer trading with Demand Response using proposed smart bidding strategy

Author

Listed:
  • Kanakadhurga, Dharmaraj
  • Prabaharan, Natarajan

Abstract

The electricity demand is increasing rapidly among residential consumers due to the utilization of many smart appliances. The renewable-based Distributed Generation (DGs) and Electric Vehicles (EV) investment is also rising among residential consumers. Consumers with renewable-based DGs and smart appliances are considered prosumers in this work. The main objective of this work is to reduce the electricity cost of the smart home by scheduling the smart appliances with Demand Response (DR) using Binary Particle Swarm Optimization (BPSO) algorithm and Peer-to-Peer (P2P) trading using a smart bidding strategy. The smart home consists of two prosumers and two consumers with different Distributed Generation (DG) availability, battery, EV, and smart appliances (thermal and electrical loads). The smart appliances are scheduled based on Real-Time Pricing (RTP), DGs and storage devices availability. The available excess power in the prosumers after self-consumption is traded to the neighbouring consumers to reduce the grid dependency. The novelty of this article lies in the trading decision and trading cost determination for P2P trading, which is called the proposed smart bidding strategy in this work. The proposed smart P2P trading algorithm involves the double auction mechanism, where the bidding occurs between the prosumers and consumers based on the supply–demand ratio (SDR) and RTP. The trading cost calculated is beneficial for both prosumers and consumers in reducing their electricity costs. The electricity cost of consumer 1, consumer 2, prosumer 1, and prosumer 2 is reduced by ₹58.073, ₹20.37, ₹51.656, and ₹20.37, respectively, as compared with grid tariff under the category of normal condition. Similarly, the electricity cost of consumer 1, consumer 2, prosumer 1, and prosumer 2 is reduced by ₹63.514, ₹3.208, ₹98.155, and ₹34.049, respectively, as compared with grid tariff under the category of EV uncertainty in both consumer & prosumer premises. The simulation results proved that the proposed smart bidding strategy effectively reduced the electricity cost of the prosumers and consumers under normal and uncertain conditions compared to the grid tariff.

Suggested Citation

  • Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
    • Handle: RePEc:eee:appene:v:327:y:2022:i:c:s0306261922013186
    DOI: 10.1016/j.apenergy.2022.120061
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922013186
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ullah, Md Habib & Park, Jae-Do, 2022. "DLMP integrated P2P2G energy trading in distribution-level grid-interactive transactive energy systems," Applied Energy, Elsevier, vol. 312(C).
    2. Rodrigues, Daniel L. & Ye, Xianming & Xia, Xiaohua & Zhu, Bing, 2020. "Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community," Applied Energy, Elsevier, vol. 262(C).
    3. 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).
    4. Lu, Renzhi & Bai, Ruichang & Huang, Yuan & Li, Yuting & Jiang, Junhui & Ding, Yuemin, 2021. "Data-driven real-time price-based demand response for industrial facilities energy management," Applied Energy, Elsevier, vol. 283(C).
    5. Li, Zhenpeng & Ma, Tao, 2020. "Peer-to-peer electricity trading in grid-connected residential communities with household distributed photovoltaic," Applied Energy, Elsevier, vol. 278(C).
    6. Khorasany, Mohsen & Shokri Gazafroudi, Amin & Razzaghi, Reza & Morstyn, Thomas & Shafie-khah, Miadreza, 2022. "A framework for participation of prosumers in peer-to-peer energy trading and flexibility markets," Applied Energy, Elsevier, vol. 314(C).
    7. Zheng, Boshen & Wei, Wei & Chen, Yue & Wu, Qiuwei & Mei, Shengwei, 2022. "A peer-to-peer energy trading market embedded with residential shared energy storage units," Applied Energy, Elsevier, vol. 308(C).
    8. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    9. Hlalele, Thabo G. & Zhang, Jiangfeng & Naidoo, Raj M. & Bansal, Ramesh C., 2021. "Multi-objective economic dispatch with residential demand response programme under renewable obligation," Energy, Elsevier, vol. 218(C).
    10. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    11. Filippo Antoniolli, Andrigo & Naspolini, Helena Flávia & de Abreu, João Frederico & Rüther, Ricardo, 2022. "The role and benefits of residential rooftop photovoltaic prosumers in Brazil," Renewable Energy, Elsevier, vol. 187(C), pages 204-222.
    12. Afzalan, Milad & Jazizadeh, Farrokh, 2019. "Residential loads flexibility potential for demand response using energy consumption patterns and user segments," Applied Energy, Elsevier, vol. 254(C).
    13. Mehdinejad, Mehdi & Shayanfar, Heidarali & Mohammadi-Ivatloo, Behnam, 2022. "Peer-to-peer decentralized energy trading framework for retailers and prosumers," Applied Energy, Elsevier, vol. 308(C).
    14. Gholami, M. & Sanjari, M.J., 2021. "Multiobjective energy management in battery-integrated home energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 967-975.
    15. Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
    16. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    17. Jing, Rui & Xie, Mei Na & Wang, Feng Xiang & Chen, Long Xiang, 2020. "Fair P2P energy trading between residential and commercial multi-energy systems enabling integrated demand-side management," Applied Energy, Elsevier, vol. 262(C).
    18. Alejandro Pena-Bello & David Parra & Mario Herberz & Verena Tiefenbeck & Martin K. Patel & Ulf J. J. Hahnel, 2022. "Integration of prosumer peer-to-peer trading decisions into energy community modelling," Nature Energy, Nature, vol. 7(1), pages 74-82, January.
    19. Blonsky, Michael & McKenna, Killian & Maguire, Jeff & Vincent, Tyrone, 2022. "Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods," Applied Energy, Elsevier, vol. 325(C).
    20. Korjani, Saman & Casu, Fabio & Damiano, Alfonso & Pilloni, Virginia & Serpi, Alessandro, 2022. "An online energy management tool for sizing integrated PV-BESS systems for residential prosumers," Applied Energy, Elsevier, vol. 313(C).
    21. An, Jongbaek & Lee, Minhyun & Yeom, Seungkeun & Hong, Taehoon, 2020. "Determining the Peer-to-Peer electricity trading price and strategy for energy prosumers and consumers within a microgrid," Applied Energy, Elsevier, vol. 261(C).
    22. Qi, Ning & Cheng, Lin & Xu, Helin & Wu, Kuihua & Li, XuLiang & Wang, Yanshuo & Liu, Rui, 2020. "Smart meter data-driven evaluation of operational demand response potential of residential air conditioning loads," Applied Energy, Elsevier, vol. 279(C).
    23. Zhang, Heng & Zhang, Shenxi & Hu, Xiao & Cheng, Haozhong & Gu, Qingfa & Du, Mengke, 2022. "Parametric optimization-based peer-to-peer energy trading among commercial buildings considering multiple energy conversion," Applied Energy, Elsevier, vol. 306(PB).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zeng, Yu & Wei, Xuan & Yao, Yuan & Xu, Yinliang & Sun, Hongbin & Kin Victor Chan, Wai & Feng, Wei, 2023. "Determining the pricing and deployment strategy for virtual power plants of peer-to-peer prosumers: A game-theoretic approach," Applied Energy, Elsevier, vol. 345(C).
    2. Liang, Ziwen & Mu, Longhua, 2024. "Multi-agent low-carbon optimal dispatch of regional integrated energy system based on mixed game theory," Energy, Elsevier, vol. 295(C).
    3. Cui, Shiting & Wu, Jun & Gao, Yao & Zhu, Ruijin, 2023. "A high altitude prosumer energy cooperation framework considering composite energy storage sharing and electric‑oxygen‑hydrogen flexible supply," Applied Energy, Elsevier, vol. 349(C).
    4. Cui, Shiting & Zhu, Ruijin & Wu, Jun, 2024. "A double layer energy cooperation framework for prosumer groups in high altitude areas," Renewable Energy, Elsevier, vol. 224(C).
    5. Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
    6. Meng, Yan & Fan, Shuai & Shen, Yu & Xiao, Jucheng & He, Guangyu & Li, Zuyi, 2023. "Transmission and distribution network-constrained large-scale demand response based on locational customer directrix load for accommodating renewable energy," Applied Energy, Elsevier, vol. 350(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    2. Wang, Juan & Zheng, Junjun & Yu, Liukai & Goh, Mark & Tang, Yunying & Huang, Yongchao, 2023. "Distributed Reputation-Distance iterative auction system for Peer-To-Peer power trading," Applied Energy, Elsevier, vol. 345(C).
    3. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    4. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    5. Zhang, Wen-Yi & Chen, Yue & Wang, Yi & Xu, Yunjian, 2023. "Equilibrium analysis of a peer-to-peer energy trading market with shared energy storage in a power transmission grid," Energy, Elsevier, vol. 274(C).
    6. Schwidtal, J.M. & Piccini, P. & Troncia, M. & Chitchyan, R. & Montakhabi, M. & Francis, C. & Gorbatcheva, A. & Capper, T. & Mustafa, M.A. & Andoni, M. & Robu, V. & Bahloul, M. & Scott, I.J. & Mbavarir, 2023. "Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    7. Maarten Evens & Patricia Ercoli & Alessia Arteconi, 2023. "Blockchain-Enabled Microgrids: Toward Peer-to-Peer Energy Trading and Flexible Demand Management," Energies, MDPI, vol. 16(18), pages 1-24, September.
    8. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    9. Javier Parra-Domínguez & Esteban Sánchez & Ángel Ordóñez, 2023. "The Prosumer: A Systematic Review of the New Paradigm in Energy and Sustainable Development," Sustainability, MDPI, vol. 15(13), pages 1-44, July.
    10. Arnob Das & Susmita Datta Peu & Md. Abdul Mannan Akanda & Abu Reza Md. Towfiqul Islam, 2023. "Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector," Energies, MDPI, vol. 16(5), pages 1-27, February.
    11. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    12. Lee, Minwoo & Han, Changho & Kwon, Soonbum & Kim, Yongchan, 2023. "Energy and cost savings through heat trading between two massive prosumers using solar and ground energy systems connected to district heating networks," Energy, Elsevier, vol. 284(C).
    13. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    14. Roth, Tamara & Utz, Manuel & Baumgarte, Felix & Rieger, Alexander & Sedlmeir, Johannes & Strüker, Jens, 2022. "Electricity powered by blockchain: A review with a European perspective," Applied Energy, Elsevier, vol. 325(C).
    15. Bidan Zhang & Yang Du & Xiaoyang Chen & Eng Gee Lim & Lin Jiang & Ke Yan, 2022. "Potential Benefits for Residential Building with Photovoltaic Battery System Participation in Peer-to-Peer Energy Trading," Energies, MDPI, vol. 15(11), pages 1-21, May.
    16. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
    17. May, Ross & Huang, Pei, 2023. "A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets," Applied Energy, Elsevier, vol. 334(C).
    18. Chang, Soowon & Cho, Junyoung & Heo, Jae & Kang, Junsuk & Kobashi, Takuro, 2022. "Energy infrastructure transitions with PV and EV combined systems using techno-economic analyses for decarbonization in cities," Applied Energy, Elsevier, vol. 319(C).
    19. Wu, Chun & Chen, Xingying & Hua, Haochen & Yu, Kun & Gan, Lei & Shen, Jun & Ding, Yi, 2024. "Peer-to-peer energy trading optimization for community prosumers considering carbon cap-and-trade," Applied Energy, Elsevier, vol. 358(C).
    20. Xu, Yuxin & Gao, Fei, 2024. "A novel higher-order Deffuant–Weisbuch networks model incorporating the Susceptible Infected Recovered framework," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:327:y:2022:i:c:s0306261922013186. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.