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Incentive determination of a demand response program for microgrids

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  • Astriani, Yuli
  • Shafiullah, GM
  • Shahnia, Farhad

Abstract

The return on investment for a microgrid can be accelerated if the microgrid can maximize its profits, either by minimizing the cost of energy production or maximizing the revenue from selling electricity to the microgrid customers. This can be achieved by implementing demand response. Under a demand response program, microgrid loads can be re-scheduled from peak to off-peak periods or shaved and shed during peak periods. Moreover, demand response execution may reduce customers’ comfort; thus, the microgrid operator should offer some compensating incentives to the participants. This study has been conducted from a microgrid owner’s perspective, aiming at determining the demand response incentives for its customers which should be feasible for both demand response participants and the microgrid operator. The incentives are derived from the difference between the microgrid’s profits before implementing the demand response program and its projected benefit before implementation. Due to the effects of controlling customers' loads to the customers comfort and economic aspects, the demand response is also optimized to minimize the number of affected loads and customers’ discomfort. The given incentive varies based on the participants' discomfort level and the load’s economic value. The results show that the microgrid operating under the proposed demand response program is able to increase its profits, part of which is allocated to the consumers as an incentive to participate in the program. Furthermore, the results from the sensitivity analysis show that the pay-back period of the participants’ demand response deployment cost is within the project lifetime.

Suggested Citation

  • Astriani, Yuli & Shafiullah, GM & Shahnia, Farhad, 2021. "Incentive determination of a demand response program for microgrids," Applied Energy, Elsevier, vol. 292(C).
  • Handle: RePEc:eee:appene:v:292:y:2021:i:c:s0306261921001598
    DOI: 10.1016/j.apenergy.2021.116624
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    as
    1. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    2. 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.
    3. Li, Kangping & Wang, Fei & Mi, Zengqiang & Fotuhi-Firuzabad, Mahmoud & Duić, Neven & Wang, Tieqiang, 2019. "Capacity and output power estimation approach of individual behind-the-meter distributed photovoltaic system for demand response baseline estimation," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    4. Shahryari, E. & Shayeghi, H. & Mohammadi-ivatloo, B. & Moradzadeh, M., 2018. "An improved incentive-based demand response program in day-ahead and intra-day electricity markets," Energy, Elsevier, vol. 155(C), pages 205-214.
    5. Bullich-Massagué, Eduard & Díaz-González, Francisco & Aragüés-Peñalba, Mònica & Girbau-Llistuella, Francesc & Olivella-Rosell, Pol & Sumper, Andreas, 2018. "Microgrid clustering architectures," Applied Energy, Elsevier, vol. 212(C), pages 340-361.
    6. Zhanle Wang & Raman Paranjape & Zhikun Chen & Kai Zeng, 2019. "Multi-Agent Optimization for Residential Demand Response under Real-Time Pricing," Energies, MDPI, vol. 12(15), pages 1-15, July.
    7. Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang & Rieger, Alexander & Thimmel, Markus, 2018. "One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids," Applied Energy, Elsevier, vol. 210(C), pages 800-814.
    8. Jamal, Taskin & Carter, Craig & Schmidt, Thomas & Shafiullah, G.M. & Calais, Martina & Urmee, Tania, 2019. "An energy flow simulation tool for incorporating short-term PV forecasting in a diesel-PV-battery off-grid power supply system," Applied Energy, Elsevier, vol. 254(C).
    9. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    10. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    11. Pavani Ponnaganti & Jayakrishnan R Pillai & Birgitte Bak‐Jensen, 2018. "Opportunities and challenges of demand response in active distribution networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(1), January.
    12. Ayvazoğluyüksel, Özge & Filik, Ümmühan Başaran, 2018. "Estimation methods of global solar radiation, cell temperature and solar power forecasting: A review and case study in Eskişehir," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 639-653.
    13. Imani, Mahmood Hosseini & Ghadi, M. Jabbari & Ghavidel, Sahand & Li, Li, 2018. "Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 486-499.
    14. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    15. Kane, Laura & Ault, Graham, 2014. "A review and analysis of renewable energy curtailment schemes and Principles of Access: Transitioning towards business as usual," Energy Policy, Elsevier, vol. 72(C), pages 67-77.
    16. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    17. Rahmani-Andebili, Mehdi, 2017. "Stochastic, adaptive, and dynamic control of energy storage systems integrated with renewable energy sources for power loss minimization," Renewable Energy, Elsevier, vol. 113(C), pages 1462-1471.
    18. Bradley, Peter & Leach, Matthew & Torriti, Jacopo, 2013. "A review of the costs and benefits of demand response for electricity in the UK," Energy Policy, Elsevier, vol. 52(C), pages 312-327.
    19. Liu, Zifa & Chen, Yixiao & Zhuo, Ranqun & Jia, Hongjie, 2018. "Energy storage capacity optimization for autonomy microgrid considering CHP and EV scheduling," Applied Energy, Elsevier, vol. 210(C), pages 1113-1125.
    20. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
    21. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
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