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Effectiveness of demand response in achieving supply-demand matching in a renewables dominated electricity system: A modelling approach

Author

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  • Balasubramanian, S.
  • Balachandra, P.

Abstract

Globally, electricity systems are undergoing transitions from robust, carbon-intensive, and firm power conventional systems to uncertain, intermittent, and variable renewable energy integrated low carbon systems. These transitioning electricity systems have moved from a situation of “matching available supply with dynamic demand” to “matching dynamic supply with dynamic demand.” These transformations have led to several new challenges - significant mismatch in periods of high supply and high demand, the shift in the method of accessing energy resources for electricity generation from “procure, store and generate when needed” to “generate when available,” continuous struggle to match variable supply with variable demand, and installed capacity redundancy, temporal as well as permanent leading to low plant load factors. Actions on the supply-side alone will not be enough to address these challenges and achieve optimal functioning of the electricity system. We need effective demand-side solutions, too, to manage variations in both supply and demand. In this paper, it is proposed to study the effectiveness of demand-side interventions as potential solutions for managing the variabilities introduced by renewable energy mainstreaming. Towards this, we develop a mixed-integer linear programming model to implement and validate emergency and economic demand response (DR) programs. DR options like load curtailment, short-, medium- and long-term load shifting are considered with both incentive-based and penalty-based pricing strategies to influence consumer participation. The Karnataka electricity system is used as a case study for model implementation and validation. The findings suggest that DR interventions are very effective in moderating variability in electricity demand by chopping the peak loads and topping the valleys. Further, benefits include postponement of installed capacity additions, enhanced utilization of available capacity, and minimization of demand variability.

Suggested Citation

  • Balasubramanian, S. & Balachandra, P., 2021. "Effectiveness of demand response in achieving supply-demand matching in a renewables dominated electricity system: A modelling approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
  • Handle: RePEc:eee:rensus:v:147:y:2021:i:c:s1364032121005323
    DOI: 10.1016/j.rser.2021.111245
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    References listed on IDEAS

    as
    1. Balachandra, P. & Chandru, Vijay, 1999. "Modelling electricity demand with representative load curves," Energy, Elsevier, vol. 24(3), pages 219-230.
    2. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
    3. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
    4. Karunanithi, K. & Saravanan, S. & Prabakar, B.R. & Kannan, S. & Thangaraj, C., 2017. "Integration of Demand and Supply Side Management strategies in Generation Expansion Planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 966-982.
    5. Anjo, João & Neves, Diana & Silva, Carlos & Shivakumar, Abhishek & Howells, Mark, 2018. "Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study," Energy, Elsevier, vol. 165(PA), pages 456-468.
    6. Craparo, E.M. & Sprague, J.G., 2019. "Integrated supply- and demand-side energy management for expeditionary environmental control," Applied Energy, Elsevier, vol. 233, pages 352-366.
    7. Osorio, Sebastian & van Ackere, Ann & Larsen, Erik R., 2017. "Interdependencies in security of electricity supply," Energy, Elsevier, vol. 135(C), pages 598-609.
    8. Mukherji, A. & Das, B. & Majumdar, N. & Nayak, N.C. & Sethi, R.R. & Sharma, B.R., 2009. "Metering of agricultural power supply in West Bengal, India: Who gains and who loses?," Energy Policy, Elsevier, vol. 37(12), pages 5530-5539, December.
    9. Olkkonen, Ville & Ekström, Jussi & Hast, Aira & Syri, Sanna, 2018. "Utilising demand response in the future Finnish energy system with increased shares of baseload nuclear power and variable renewable energy," Energy, Elsevier, vol. 164(C), pages 204-217.
    10. Amrutha, A.A. & Balachandra, P. & Mathirajan, M., 2017. "Role of targeted policies in mainstreaming renewable energy in a resource constrained electricity system: A case study of Karnataka electricity system in India," Energy Policy, Elsevier, vol. 106(C), pages 48-58.
    11. Noor, Sana & Yang, Wentao & Guo, Miao & van Dam, Koen H. & Wang, Xiaonan, 2018. "Energy Demand Side Management within micro-grid networks enhanced by blockchain," Applied Energy, Elsevier, vol. 228(C), pages 1385-1398.
    12. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    13. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    14. Thakur, Jagruti & Chakraborty, Basab, 2016. "Demand side management in developing nations: A mitigating tool for energy imbalance and peak load management," Energy, Elsevier, vol. 114(C), pages 895-912.
    15. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    16. Parra, David & Swierczynski, Maciej & Stroe, Daniel I. & Norman, Stuart.A. & Abdon, Andreas & Worlitschek, Jörg & O’Doherty, Travis & Rodrigues, Lucelia & Gillott, Mark & Zhang, Xiaojin & Bauer, Chris, 2017. "An interdisciplinary review of energy storage for communities: Challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 730-749.
    17. Ikpe, Eka & Torriti, Jacopo, 2018. "A means to an industrialisation end? Demand Side Management in Nigeria," Energy Policy, Elsevier, vol. 115(C), pages 207-215.
    Full references (including those not matched with items on IDEAS)

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