IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1711-d228632.html
   My bibliography  Save this article

A Day-ahead and Day-in Decision Model Considering the Uncertainty of Multiple Kinds of Demand Response

Author

Listed:
  • Siqing Sheng

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071000, China)

  • Qing Gu

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071000, China)

Abstract

The uncertainty of demand response (DR) will affect the economics of power grid dispatch due to the randomness of participating users’ intentions. According to the different working mechanisms of price-based demand response (PBDR) and incentive-based demand response (IBDR), the uncertainty models of two types of DR were established, respectively. Firstly, the fuzzy variable was used to describe the load change in PBDR, and the robust optimization theory was used to establish the uncertain set of the actual interruption of the interruptible load (IL). Secondly, according to the different acting speed of the two types of DR, they were deployed in the two-stage scheduling model with other output resources; then based on the fuzzy chance constrained programming theory and multi-stage robust optimization theory, the dispatch problem was transformed and solved by the bat algorithm (BA) and the entropy weighting method. Consequently, intraday running costs decrease with increasing confidence of day-ahead, but increase with day-in reliability, and the economics of the model were verified in the improved IEEE33 node system.

Suggested Citation

  • Siqing Sheng & Qing Gu, 2019. "A Day-ahead and Day-in Decision Model Considering the Uncertainty of Multiple Kinds of Demand Response," Energies, MDPI, vol. 12(9), pages 1-26, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1711-:d:228632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1711/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/9/1711/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yajing Gao & Yanping Sun & Xiaodan Wang & Feifan Chen & Ali Ehsan & Hongmei Li & Hong Li, 2017. "Multi-Objective Optimized Aggregation of Demand Side Resources Based on a Self-organizing Map Clustering Algorithm Considering a Multi-Scenario Technique," Energies, MDPI, vol. 10(12), pages 1-20, December.
    2. Smarajit Ghosh & Manvir Kaur & Suman Bhullar & Vinod Karar, 2019. "Hybrid ABC-BAT for Solving Short-Term Hydrothermal Scheduling Problems," Energies, MDPI, vol. 12(3), pages 1-15, February.
    3. Bach Hoang Dinh & Thang Trung Nguyen & Nguyen Vu Quynh & Le Van Dai, 2018. "A Novel Method for Economic Dispatch of Combined Heat and Power Generation," Energies, MDPI, vol. 11(11), pages 1-27, November.
    4. Muhammad Fayaz & DoHyeun Kim, 2018. "Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic," Energies, MDPI, vol. 11(1), pages 1-22, January.
    5. Hui Li & Gengyin Li & Siwei Liu & Yuning Wang & Zhidong Wang & Jiaming Wang & Ning Zhang, 2017. "Research on Optimal Planning of Access Location and Access Capacity of Large-Scale Integrated Wind Power Plants," Energies, MDPI, vol. 10(4), pages 1-13, April.
    6. Jiaxin Lu & Weijun Wang & Yingchao Zhang & Song Cheng, 2017. "Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER," Energies, MDPI, vol. 10(10), pages 1-17, October.
    7. Chenjun Sun & Zengqiang Mi & Hui Ren & Zhipeng Jing & Jinling Lu & David Watts, 2019. "Multi-Dimensional Indexes for the Sustainability Evaluation of an Active Distribution Network," Energies, MDPI, vol. 12(3), pages 1-24, January.
    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. Motta, Vinicius N. & Anjos, Miguel F. & Gendreau, Michel, 2024. "Survey of optimization models for power system operation and expansion planning with demand response," European Journal of Operational Research, Elsevier, vol. 312(2), pages 401-412.
    2. 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).
    3. Ming Tang & Jian Wang & Xiaohua Wang, 2020. "Adaptable Source-Grid Planning for High Penetration of Renewable Energy Integrated System," Energies, MDPI, vol. 13(13), pages 1-26, June.
    4. Tianliang Wang & Xin Jiang & Yang Jin & Dawei Song & Meng Yang & Qingshan Zeng, 2019. "Peaking Compensation Mechanism for Thermal Units and Virtual Peaking Plants Union Promoting Curtailed Wind Power Integration," Energies, MDPI, vol. 12(17), pages 1-20, August.

    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. Aylin Ece Kayabekir & Zülal Akbay Arama & Gebrail Bekdaş & Sinan Melih Nigdeli & Zong Woo Geem, 2020. "Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications," Sustainability, MDPI, vol. 12(15), pages 1-30, July.
    2. Chih-Ta Tsai & Teketay Mulu Beza & Wei-Bin Wu & Cheng-Chien Kuo, 2019. "Optimal Configuration with Capacity Analysis of a Hybrid Renewable Energy and Storage System for an Island Application," Energies, MDPI, vol. 13(1), pages 1-28, December.
    3. P. M. R. Bento & S. J. P. S. Mariano & M. R. A. Calado & L. A. F. M. Ferreira, 2020. "A Novel Lagrangian Multiplier Update Algorithm for Short-Term Hydro-Thermal Coordination," Energies, MDPI, vol. 13(24), pages 1-19, December.
    4. Xuejun Zheng & Shaorong Wang & Xin Su & Mengmeng Xiao & Zia Ullah & Xin Hu & Chang Ye, 2021. "Real-Time Dynamic Behavior Evaluation of Active Distribution Networks Leveraging Low-Cost PMUs," Energies, MDPI, vol. 14(16), pages 1-20, August.
    5. Saqib Akram & Muhammad Salman Fakhar & Syed Abdul Rahman Kashif & Ghulam Abbas & Nasim Ullah & Alsharef Mohammad & Mohamed Emad Farrag, 2022. "Introducing Adaptive Machine Learning Technique for Solving Short-Term Hydrothermal Scheduling with Prohibited Discharge Zones," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    6. Yuehong Lu & Mohammed Alghassab & Manuel S. Alvarez-Alvarado & Hasan Gunduz & Zafar A. Khan & Muhammad Imran, 2020. "Optimal Distribution of Renewable Energy Systems Considering Aging and Long-Term Weather Effect in Net-Zero Energy Building Design," Sustainability, MDPI, vol. 12(14), pages 1-20, July.
    7. Jin-peng Liu & Yu Tian & Hao Zheng & Tao Yi, 2019. "Research on Dynamic Evolution Simulation and Sustainability Evaluation Model of China’s Power Supply and Demand System," Energies, MDPI, vol. 12(10), pages 1-23, May.
    8. Bartlomiej Kawa & Piotr Borkowski, 2023. "Integration of Machine Learning Solutions in the Building Automation System," Energies, MDPI, vol. 16(11), pages 1-18, June.
    9. Lei Zhang & Ying Yang, 2023. "Towards Sustainable Energy Systems Considering Unexpected Sports Event Management: Integrating Machine Learning and Optimization Algorithms," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    10. Danny Ochoa & Sergio Martinez, 2018. "Proposals for Enhancing Frequency Control in Weak and Isolated Power Systems: Application to the Wind-Diesel Power System of San Cristobal Island-Ecuador," Energies, MDPI, vol. 11(4), pages 1-25, April.
    11. Pascasio, Jethro Daniel A. & Esparcia, Eugene A. & Castro, Michael T. & Ocon, Joey D., 2021. "Comparative assessment of solar photovoltaic-wind hybrid energy systems: A case for Philippine off-grid islands," Renewable Energy, Elsevier, vol. 179(C), pages 1589-1607.
    12. Jingru Huang & Jie Shen & Lu Miao, 2020. "Carbon Emissions Trading and Sustainable Development in China: Empirical Analysis Based on the Coupling Coordination Degree Model," IJERPH, MDPI, vol. 18(1), pages 1-13, December.
    13. Sooyoun Cho & Jeehang Lee & Jumi Baek & Gi-Seok Kim & Seung-Bok Leigh, 2019. "Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach," Energies, MDPI, vol. 12(21), pages 1-23, October.
    14. Yunhai Zhou & Shengkai Guo & Fei Xu & Dai Cui & Weichun Ge & Xiaodong Chen & Bo Gu, 2020. "Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method," Energies, MDPI, vol. 13(7), pages 1-18, April.
    15. Omid Sadeghian & Arash Moradzadeh & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Fausto Pedro Garcia Marquez, 2020. "Generation Units Maintenance in Combined Heat and Power Integrated Systems Using the Mixed Integer Quadratic Programming Approach," Energies, MDPI, vol. 13(11), pages 1-25, June.
    16. Tri-Hai Nguyen & Luong Vuong Nguyen & Jason J. Jung & Israel Edem Agbehadji & Samuel Ofori Frimpong & Richard C. Millham, 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    17. Yan Nie & Guoxing Zhang, 2020. "Indicator system to evaluate the effectiveness and efficiency of China clean power systems," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1381-1401, October.
    18. Chowdhury, Tamal & Chowdhury, Hemal & Miskat, Monirul Islam & Chowdhury, Piyal & Sait, Sadiq M. & Thirugnanasambandam, M. & Saidur, R., 2020. "Developing and evaluating a stand-alone hybrid energy system for Rohingya refugee community in Bangladesh," Energy, Elsevier, vol. 191(C).
    19. Daiva Stanelyte & Neringa Radziukyniene & Virginijus Radziukynas, 2022. "Overview of Demand-Response Services: A Review," Energies, MDPI, vol. 15(5), pages 1-31, February.
    20. Lei, Yu-Tian & Ma, Chao-Qun & Mirza, Nawazish & Ren, Yi-Shuai & Narayan, Seema Wati & Chen, Xun-Qi, 2022. "A renewable energy microgrids trading management platform based on permissioned blockchain," Energy Economics, Elsevier, vol. 115(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:gam:jeners:v:12:y:2019:i:9:p:1711-:d:228632. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.