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A heuristic multi-objective multi-criteria demand response planning in a system with high penetration of wind power generators

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  • Hajibandeh, Neda
  • Shafie-khah, Miadreza
  • Osório, Gerardo J.
  • Aghaei, Jamshid
  • Catalão, João P.S.

Abstract

Integration of wind energy and other renewable energy resources in electrical systems create some challenges due to their uncertain and variable characteristics. In the quest for more flexibility of the electric systems, combination of these endogenous and renewable resources in accordance with strategies of Demand Response (DR) allows an increment/improvement of the demand potential, as well as a more secure, robust, sustainable and economically advantageous operation. This paper proposes a new model for integration of wind power and DR, thus optimizing supply and demand side operations through a price rule Time of Use (TOU), or incentive with Emergency DR Program (EDRP), as well as combining TOU and EDRP together. The problem is modelled using a stochastic Heuristic Multi-Objective Multi-Criteria Decision Making (HMM) method which aims to minimize operation costs and environmental emissions simultaneously, ensuring the security constraints through two-stage stochastic programming, considering various techno-economic indices such as load factor, electricity market prices, Energy Not Supplied (ENS) and Share Weighted Average Lerner Index (SWALI). Comprehensive numerical results indicate that the proposed model is entirely efficient in DR planning and power system operation.

Suggested Citation

  • Hajibandeh, Neda & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "A heuristic multi-objective multi-criteria demand response planning in a system with high penetration of wind power generators," Applied Energy, Elsevier, vol. 212(C), pages 721-732.
  • Handle: RePEc:eee:appene:v:212:y:2018:i:c:p:721-732
    DOI: 10.1016/j.apenergy.2017.12.076
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wang, Ni & Heijnen, Petra W. & Imhof, Pieter J., 2020. "A multi-actor perspective on multi-objective regional energy system planning," Energy Policy, Elsevier, vol. 143(C).
    2. Jia, Kunqi & Guo, Ge & Xiao, Jucheng & Zhou, Huan & Wang, Zhihua & He, Guangyu, 2019. "Data compression approach for the home energy management system," Applied Energy, Elsevier, vol. 247(C), pages 643-656.
    3. Liang, Zheming & Bian, Desong & Zhang, Xiaohu & Shi, Di & Diao, Ruisheng & Wang, Zhiwei, 2019. "Optimal energy management for commercial buildings considering comprehensive comfort levels in a retail electricity market," Applied Energy, Elsevier, vol. 236(C), pages 916-926.
    4. Shin, Hansol & Kim, Tae Hyun & Kim, Hyoungtae & Lee, Sungwoo & Kim, Wook, 2019. "Environmental shutdown of coal-fired generators for greenhouse gas reduction: A case study of South Korea," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    5. Neda Hajibandeh & Miadreza Shafie-khah & Sobhan Badakhshan & Jamshid Aghaei & Sílvio J. P. S. Mariano & João P. S. Catalão, 2019. "Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme," Energies, MDPI, Open Access Journal, vol. 12(7), pages 1-16, April.
    6. Quanhui Che & Suhua Lou & Yaowu Wu & Xiangcheng Zhang & Xuebin Wang, 2019. "Optimal Scheduling of a Multi-Energy Power System with Multiple Flexible Resources and Large-Scale Wind Power," Energies, MDPI, Open Access Journal, vol. 12(18), pages 1-14, September.
    7. Song, Ziyou & Feng, Shuo & Zhang, Lei & Hu, Zunyan & Hu, Xiaosong & Yao, Rui, 2019. "Economy analysis of second-life battery in wind power systems considering battery degradation in dynamic processes: Real case scenarios," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Gonçalves, Ivo & Gomes, Álvaro & Henggeler Antunes, Carlos, 2019. "Optimizing the management of smart home energy resources under different power cost scenarios," Applied Energy, Elsevier, vol. 242(C), pages 351-363.
    9. Gao, Jianwei & Ma, Zeyang & Guo, Fengjia, 2019. "The influence of demand response on wind-integrated power system considering participation of the demand side," Energy, Elsevier, vol. 178(C), pages 723-738.
    10. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Li, Xinying & Li, Lingwenying, 2019. "Portfolio selection of distributed energy generation projects considering uncertainty and project interaction under different enterprise strategic scenarios," Applied Energy, Elsevier, vol. 236(C), pages 444-464.
    11. Vatanpour, Mohsen & Sadeghi Yazdankhah, Ahmad, 2018. "The impact of energy storage modeling in coordination with wind farm and thermal units on security and reliability in a stochastic unit commitment," Energy, Elsevier, vol. 162(C), pages 476-490.

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