IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v176y2019icp929-939.html
   My bibliography  Save this article

Multiobjective robust fuzzy stochastic approach for sustainable smart grid design

Author

Listed:
  • Tsao, Yu-Chung
  • Thanh, Vo-Van
  • Lu, Jye-Chyi

Abstract

Smart grids are an effective solution for the rapidly increasing power demand. This study attempts to solve the sustainable smart grid design problem, where three indispensable sustainability dimensions, economy, environment, and society, are considered simultaneously. A multiobjective robust fuzzy stochastic programming approach is presented to minimize the economic, environmental and social costs of the network under uncertain scenarios and parameters. The objective is to determine the optimal number, location and capacity of renewable distributed generation units as well as the dynamic electricity pricing and energy resources scheduling in a sustainable smart grid. The proposed method is applied to a Vietnamese power company in the residential sector. The results indicate that demand response with dynamic pricing reduces environmental and social costs by 3%. Moreover, the proposed model efficiently tackles both uncertainties in scenarios and parameters with a total cost lower than other models.

Suggested Citation

  • Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:929-939
    DOI: 10.1016/j.energy.2019.04.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219306711
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.04.047?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. Soares, João & Ghazvini, Mohammad Ali Fotouhi & Borges, Nuno & Vale, Zita, 2017. "Dynamic electricity pricing for electric vehicles using stochastic programming," Energy, Elsevier, vol. 122(C), pages 111-127.
    2. Atabaki, Mohammad Saeid & Aryanpur, Vahid, 2018. "Multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran," Energy, Elsevier, vol. 161(C), pages 493-507.
    3. SoltaniNejad Farsangi, Alireza & Hadayeghparast, Shahrzad & Mehdinejad, Mehdi & Shayanfar, Heidarali, 2018. "A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs," Energy, Elsevier, vol. 160(C), pages 257-274.
    4. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    5. Samimi, Abouzar & Nikzad, Mehdi & Siano, Pierluigi, 2017. "Scenario-based stochastic framework for coupled active and reactive power market in smart distribution systems with demand response programs," Renewable Energy, Elsevier, vol. 109(C), pages 22-40.
    6. Silva, Hendrigo Batista da & Santiago, Leonardo P., 2018. "On the trade-off between real-time pricing and the social acceptability costs of demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1513-1521.
    7. Verbong, Geert P.J. & Beemsterboer, Sjouke & Sengers, Frans, 2013. "Smart grids or smart users? Involving users in developing a low carbon electricity economy," Energy Policy, Elsevier, vol. 52(C), pages 117-125.
    8. Srinivasan, Dipti & Rajgarhia, Sanjana & Radhakrishnan, Bharat Menon & Sharma, Anurag & Khincha, H.P., 2017. "Game-Theory based dynamic pricing strategies for demand side management in smart grids," Energy, Elsevier, vol. 126(C), pages 132-143.
    9. Zhang, X.Y. & Huang, G.H. & Zhu, H. & Li, Y.P., 2017. "A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties," Energy, Elsevier, vol. 123(C), pages 664-676.
    10. Hadayeghparast, Shahrzad & SoltaniNejad Farsangi, Alireza & Shayanfar, Heidarali, 2019. "Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant," Energy, Elsevier, vol. 172(C), pages 630-646.
    11. Abdullah, M.A. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "Sustainable energy system design with distributed renewable resources considering economic, environmental and uncertainty aspects," Renewable Energy, Elsevier, vol. 78(C), pages 165-172.
    12. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    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. Ji, Ling & Zhang, Beibei & Huang, Guohe & Wang, Peng, 2020. "A novel multi-stage fuzzy stochastic programming for electricity system structure optimization and planning with energy-water nexus - A case study of Tianjin, China," Energy, Elsevier, vol. 190(C).
    2. Tsao, Yu-Chung & Beyene, Tsehaye Dedimas & Thanh, Vo-Van & Gebeyehu, Sisay Geremew & Kuo, Tsai-Chi, 2022. "Power distribution network design considering the distributed generations and differential and dynamic pricing," Energy, Elsevier, vol. 241(C).
    3. Wu, Chuanshen & Jiang, Sufan & Gao, Shan & Liu, Yu & Han, Haiteng, 2022. "Charging demand forecasting of electric vehicles considering uncertainties in a microgrid," Energy, Elsevier, vol. 247(C).
    4. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2021. "Sustainable advanced distribution management system design considering differential pricing schemes and carbon emissions," Energy, Elsevier, vol. 219(C).
    5. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward blockchain-based renewable energy microgrid design considering default risk and demand uncertainty," Renewable Energy, Elsevier, vol. 163(C), pages 870-881.
    6. Wang, Jidong & Liu, Jianxin & Li, Chenghao & Zhou, Yue & Wu, Jianzhong, 2020. "Optimal scheduling of gas and electricity consumption in a smart home with a hybrid gas boiler and electric heating system," Energy, Elsevier, vol. 204(C).
    7. Sun, Chenhao & Wang, Xin & Zheng, Yihui, 2020. "An ensemble system to predict the spatiotemporal distribution of energy security weaknesses in transmission networks," Applied Energy, Elsevier, vol. 258(C).
    8. Carlo Bianca, 2022. "On the Modeling of Energy-Multisource Networks by the Thermostatted Kinetic Theory Approach: A Review with Research Perspectives," Energies, MDPI, vol. 15(21), pages 1-22, October.
    9. Parizad, Ali & Hatziadoniu, Konstadinos, 2020. "Security/stability-based Pareto optimal solution for distribution networks planning implementing NSGAII/FDMT," Energy, Elsevier, vol. 192(C).
    10. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    11. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2022. "Efficiency of resilient three-part tariff pricing schemes in residential power markets," Energy, Elsevier, vol. 239(PD).
    12. Tsao, Yu-Chung & Thanh, Vo-Van & Chang, Yi-Ying & Wei, Hsi-Hsien, 2021. "COVID-19: Government subsidy models for sustainable energy supply with disruption risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    13. Huang, Qian & Xu, Jiuping, 2023. "Carbon tax revenue recycling for biomass/coal co-firing using Stackelberg game: A case study of Jiangsu province, China," Energy, Elsevier, vol. 272(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. 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.
    2. Fang, Fang & Yu, Songyuan & Liu, Mingxi, 2020. "An improved Shapley value-based profit allocation method for CHP-VPP," Energy, Elsevier, vol. 213(C).
    3. Khalil Gholami & Behnaz Behi & Ali Arefi & Philip Jennings, 2022. "Grid-Forming Virtual Power Plants: Concepts, Technologies and Advantages," Energies, MDPI, vol. 15(23), pages 1-26, November.
    4. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    5. Sajjad Ali & Imran Khan & Sadaqat Jan & Ghulam Hafeez, 2021. "An Optimization Based Power Usage Scheduling Strategy Using Photovoltaic-Battery System for Demand-Side Management in Smart Grid," Energies, MDPI, vol. 14(8), pages 1-29, April.
    6. Donghai Wang & Qiuhong Zhao, 2020. "A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    7. Nyong-Bassey, Bassey Etim & Giaouris, Damian & Patsios, Charalampos & Papadopoulou, Simira & Papadopoulos, Athanasios I. & Walker, Sara & Voutetakis, Spyros & Seferlis, Panos & Gadoue, Shady, 2020. "Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty," Energy, Elsevier, vol. 193(C).
    8. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    9. Khaled, Oumaima & Minoux, Michel & Mousseau, Vincent & Michel, Stéphane & Ceugniet, Xavier, 2018. "A multi-criteria repair/recovery framework for the tail assignment problem in airlines," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 137-151.
    10. Irawan, Chandra Ade & Jones, Dylan & Hofman, Peter S. & Zhang, Lina, 2023. "Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders," European Journal of Operational Research, Elsevier, vol. 308(2), pages 864-883.
    11. Hashem Omrani & Farzane Adabi & Narges Adabi, 2017. "Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 816-828, July.
    12. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    13. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    14. Jihee Han & KwangSup Shin, 2016. "Evaluation mechanism for structural robustness of supply chain considering disruption propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 135-151, January.
    15. Tsai, Jung-Fa, 2007. "An optimization approach for supply chain management models with quantity discount policy," European Journal of Operational Research, Elsevier, vol. 177(2), pages 982-994, March.
    16. Nock, Destenie & Baker, Erin, 2019. "Holistic multi-criteria decision analysis evaluation of sustainable electric generation portfolios: New England case study," Applied Energy, Elsevier, vol. 242(C), pages 655-673.
    17. Xuejie Bai & Yankui Liu, 2016. "Robust optimization of supply chain network design in fuzzy decision system," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1131-1149, December.
    18. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    19. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    20. Schönlein, Michael & Makuschewitz, Thomas & Wirth, Fabian & Scholz-Reiter, Bernd, 2013. "Measurement and optimization of robust stability of multiclass queueing networks: Applications in dynamic supply chains," European Journal of Operational Research, Elsevier, vol. 229(1), pages 179-189.

    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:energy:v:176:y:2019:i:c:p:929-939. 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.journals.elsevier.com/energy .

    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.