IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v287y2021ics0306261921001100.html
   My bibliography  Save this article

Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation

Author

Listed:
  • Mohseni, Soheil
  • Brent, Alan C.
  • Kelly, Scott
  • Browne, Will N.
  • Burmester, Daniel

Abstract

While industrial demand response programmes have long been valued to support the power grid, recent advances in information and communications technology have enabled new opportunities to leverage the potential of responsive loads in less energy-dense end-use sectors. This brings to light the importance of accurately projecting flexible demand-side resources in the long-term investment planning process of micro-grids. This paper introduces a customer comfort-aware, demand response-integrated long-term micro-grid planning optimisation model. The model (1) draws on non-cooperative game theory and the Stackelberg leadership principles to understand and reflect the strategic behaviour of energy utilities, demand response aggregators, and end-consumers, (2) produces optimal trade-offs between power imported from the main grid and available demand response resources, (3) determines the cost-optimal resource allocation for energy infrastructure, including multiple energy storage systems, and (4) provides a level playing field for emerging technologies, such as power-to-gas and vehicle-to-grid interventions. The multi-energy-storage-technology test-case was effectively applied to achieve 100%-renewable energy generation for the town of Ohakune, New Zealand. Numerical simulation results suggest that the proposed incentive-compatible demand-side management market-clearing mechanism is able to estimate the cost-optimal solution for the provision of renewable energy during the planning phase. The cost-optimal system saves ~21% (equating to around US$5.5 m) compared to a business-as-usual approach, where the participation of end-users in demand response programmes is projected by running uniform price demand response auctions. The most salient distinction of the proposed two-stage (wholesale and retail) demand-side management market model is the continual process of trading, with incentive prices unique to each transaction.

Suggested Citation

  • Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:appene:v:287:y:2021:i:c:s0306261921001100
    DOI: 10.1016/j.apenergy.2021.116563
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921001100
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.116563?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. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    3. Nerini, Francesco Fuso & Broad, Oliver & Mentis, Dimitris & Welsch, Manuel & Bazilian, Morgan & Howells, Mark, 2016. "A cost comparison of technology approaches for improving access to electricity services," Energy, Elsevier, vol. 95(C), pages 255-265.
    4. Amrollahi, Mohammad Hossein & Bathaee, Seyyed Mohammad Taghi, 2017. "Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response," Applied Energy, Elsevier, vol. 202(C), pages 66-77.
    5. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    6. Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
    7. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
    8. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    9. Esther, B. Priya & Kumar, K. Sathish, 2016. "A survey on residential Demand Side Management architecture, approaches, optimization models and methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 342-351.
    10. Nwulu, Nnamdi I. & Xia, Xiaohua, 2015. "Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs," Energy, Elsevier, vol. 91(C), pages 404-419.
    11. Soshinskaya, Mariya & Crijns-Graus, Wina H.J. & van der Meer, Jos & Guerrero, Josep M., 2014. "Application of a microgrid with renewables for a water treatment plant," Applied Energy, Elsevier, vol. 134(C), pages 20-34.
    12. Hosseinalizadeh, Ramin & Shakouri G, Hamed & Amalnick, Mohsen Sadegh & Taghipour, Peyman, 2016. "Economic sizing of a hybrid (PV–WT–FC) renewable energy system (HRES) for stand-alone usages by an optimization-simulation model: Case study of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 139-150.
    13. Varasteh, Farid & Nazar, Mehrdad Setayesh & Heidari, Alireza & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs," Energy, Elsevier, vol. 172(C), pages 79-105.
    14. Robledo, Carla B. & Oldenbroek, Vincent & Abbruzzese, Francesca & van Wijk, Ad J.M., 2018. "Integrating a hydrogen fuel cell electric vehicle with vehicle-to-grid technology, photovoltaic power and a residential building," Applied Energy, Elsevier, vol. 215(C), pages 615-629.
    15. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2017. "Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation," Applied Energy, Elsevier, vol. 205(C), pages 1244-1259.
    16. Okur, Özge & Voulis, Nina & Heijnen, Petra & Lukszo, Zofia, 2019. "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, Elsevier, vol. 247(C), pages 426-437.
    17. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    18. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2016. "Generation-scheduling-coupled battery sizing of stand-alone hybrid power systems," Energy, Elsevier, vol. 114(C), pages 671-682.
    19. Ihsan, Abbas & Jeppesen, Matthew & Brear, Michael J., 2019. "Impact of demand response on the optimal, techno-economic performance of a hybrid, renewable energy power plant," Applied Energy, Elsevier, vol. 238(C), pages 972-984.
    20. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    21. Chauhan, Anurag & Saini, R.P., 2016. "Techno-economic optimization based approach for energy management of a stand-alone integrated renewable energy system for remote areas of India," Energy, Elsevier, vol. 94(C), pages 138-156.
    22. Hui, Hongxun & Ding, Yi & Shi, Qingxin & Li, Fangxing & Song, Yonghua & Yan, Jinyue, 2020. "5G network-based Internet of Things for demand response in smart grid: A survey on application potential," Applied Energy, Elsevier, vol. 257(C).
    23. Chauhan, Anurag & Saini, R.P., 2017. "Size optimization and demand response of a stand-alone integrated renewable energy system," Energy, Elsevier, vol. 124(C), pages 59-73.
    24. Gazijahani, Farhad Samadi & Salehi, Javad, 2018. "Reliability constrained two-stage optimization of multiple renewable-based microgrids incorporating critical energy peak pricing demand response program using robust optimization approach," Energy, Elsevier, vol. 161(C), pages 999-1015.
    25. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    26. Muhammad Sajjad Ahmad & Muhammad Aamer Mehmood & Huibo Luo & Boxiong Shen & Muhammad Latif & Wan Azlina Wan Ab Karim Ghani & Nuha Abdulhamid Alkhattabi & Akram Ahmed Aloqbi & Ebtihaj Jamaluddin Jambi , 2019. "Pyrolysis and Thermogravimetric Study to Elucidate the Bioenergy Potential of Novel Feedstock Produced on Poor Soils While Keeping the Environmental Sustainability Intact," Sustainability, MDPI, vol. 11(13), pages 1-15, June.
    27. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    28. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    29. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2016. "Optimal design and techno-economic analysis of an autonomous small isolated microgrid aiming at high RES penetration," Energy, Elsevier, vol. 116(P1), pages 364-379.
    30. Nojavan, Sayyad & Majidi, Majid & Esfetanaj, Naser Nourani, 2017. "An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management," Energy, Elsevier, vol. 139(C), pages 89-97.
    31. Rezk, Hegazy & Sayed, Enas Taha & Al-Dhaifallah, Mujahed & Obaid, M. & El-Sayed, Abou Hashema M. & Abdelkareem, Mohammad Ali & Olabi, A.G., 2019. "Fuel cell as an effective energy storage in reverse osmosis desalination plant powered by photovoltaic system," Energy, Elsevier, vol. 175(C), pages 423-433.
    32. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    33. Heetae Kim & Jinwoo Bae & Seoin Baek & Donggyun Nam & Hyunsung Cho & Hyun Joon Chang, 2017. "Comparative Analysis between the Government Micro-Grid Plan and Computer Simulation Results Based on Real Data: The Practical Case for a South Korean Island," Sustainability, MDPI, vol. 9(2), pages 1-18, January.
    34. Cardoso, G. & Stadler, M. & Bozchalui, M.C. & Sharma, R. & Marnay, C. & Barbosa-Póvoa, A. & Ferrão, P., 2014. "Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicle driving schedules," Energy, Elsevier, vol. 64(C), pages 17-30.
    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. Wu, Qiong & Xie, Zhun & Ren, Hongbo & Li, Qifen & Yang, Yongwen, 2022. "Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study," Energy, Elsevier, vol. 254(PC).
    2. Abdellatif Soussi & Enrico Zero & Alessandro Bozzi & Roberto Sacile, 2024. "Enhancing Energy Systems and Rural Communities through a System of Systems Approach: A Comprehensive Review," Energies, MDPI, vol. 17(19), pages 1-43, October.
    3. Jann Michael Weinand & Maximilian Hoffmann & Jan Gopfert & Tom Terlouw & Julian Schonau & Patrick Kuckertz & Russell McKenna & Leander Kotzur & Jochen Lin{ss}en & Detlef Stolten, 2022. "Global LCOEs of decentralized off-grid renewable energy systems," Papers 2212.12742, arXiv.org, revised Mar 2023.
    4. Li, Ke & Ye, Ning & Li, Shuzhen & Wang, Haiyang & Zhang, Chenghui, 2023. "Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory," Energy, Elsevier, vol. 273(C).
    5. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2022. "Optimal strategy of electricity and natural gas aggregators in the energy and balance markets," Energy, Elsevier, vol. 257(C).
    6. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    7. Yan, Zhongzhen & Zhu, Xinyuan & Chang, Yiming & Wang, Xianglong & Ye, Zhiwei & Xu, Zhigang & Fars, Ashk, 2023. "Renewable energy effects on energy management based on demand response in microgrids environment," Renewable Energy, Elsevier, vol. 213(C), pages 205-217.
    8. Wang, Yudong & Hu, Junjie, 2023. "Two-stage energy management method of integrated energy system considering pre-transaction behavior of energy service provider and users," Energy, Elsevier, vol. 271(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. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    2. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    3. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    4. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    5. Antonopoulos, Ioannis & Robu, Valentin & Couraud, Benoit & Kirli, Desen & Norbu, Sonam & Kiprakis, Aristides & Flynn, David & Elizondo-Gonzalez, Sergio & Wattam, Steve, 2020. "Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    6. Juan Carlos Oviedo Cepeda & German Osma-Pinto & Robin Roche & Cesar Duarte & Javier Solano & Daniel Hissel, 2020. "Design of a Methodology to Evaluate the Impact of Demand-Side Management in the Planning of Isolated/Islanded Microgrids," Energies, MDPI, vol. 13(13), pages 1-24, July.
    7. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    8. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    9. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    10. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    11. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    12. Alexander Lavrik & Yuri Zhukovskiy & Pavel Tcvetkov, 2021. "Optimizing the Size of Autonomous Hybrid Microgrids with Regard to Load Shifting," Energies, MDPI, vol. 14(16), pages 1-19, August.
    13. Nizami, Sohrab & Tushar, Wayes & Hossain, M.J. & Yuen, Chau & Saha, Tapan & Poor, H. Vincent, 2022. "Transactive energy for low voltage residential networks: A review," Applied Energy, Elsevier, vol. 323(C).
    14. Rajavelu Dharani & Madasamy Balasubramonian & Thanikanti Sudhakar Babu & Benedetto Nastasi, 2021. "Load Shifting and Peak Clipping for Reducing Energy Consumption in an Indian University Campus," Energies, MDPI, vol. 14(3), pages 1-16, January.
    15. Guelpa, Elisa & Verda, Vittorio, 2021. "Demand response and other demand side management techniques for district heating: A review," Energy, Elsevier, vol. 219(C).
    16. Roldán-Blay, Carlos & Escrivá-Escrivá, Guillermo & Roldán-Porta, Carlos, 2019. "Improving the benefits of demand response participation in facilities with distributed energy resources," Energy, Elsevier, vol. 169(C), pages 710-718.
    17. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Tian, Ning & Zhao, Wei, 2023. "Incentive-based demand response strategies for natural gas considering carbon emissions and load volatility," Applied Energy, Elsevier, vol. 348(C).
    18. Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2020. "Reviewing energy system modelling of decentralized energy autonomy," Energy, Elsevier, vol. 203(C).
    19. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
    20. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2021. "Off-Grid Multi-Carrier Microgrid Design Optimisation: The Case of Rakiura–Stewart Island, Aotearoa–New Zealand," Energies, MDPI, vol. 14(20), pages 1-28, October.

    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:287:y:2021:i:c:s0306261921001100. 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.