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Integrating short-term demand response into long-term investment planning

  • De Jonghe, C.
  • Hobbs, B. F.
  • Belmans, R.

Planning models have been used for many years to optimize generation investments in electric power systems. More recently, these models have been extended in order to treat demand-side management on an equal footing. This paper stresses the importance of integrating short-term demand response to time-varying prices into those investment models. Three different methodologies are suggested to integrate short-term responsiveness into a long-term model assuming that consumer response can be modelled using price-elastic demand and that generators behave competitively. First, numerical results show that considering operational constraints in an investment model results in less inflexible base load capacity and more mid-range capacity that has higher ramp rates. Then, own-price and cross-price elasticities are included in order to incorporate consumers’ willingness to adjust the demand profile in response to price changes. Whereas own-price elasticities account for immediate response to price signals, cross-price elasticities account for shifting loads to other periods. As energy efficiency programs sponsored by governments or utilities also influence the load profile, the interaction of energy efficiency expenditures and demand response is also modelled. In particular, reduced responsiveness to prices can be a side effect when consumers have become more energy efficient. Comparison of model results for a single year optimization with and without demand response shows the peak reduction and valley filling effects of response to real-time prices for an illustrative example with a large amount of wind power injections. Additionally, increasing demand elasticity increases the optimal amount of installed wind power capacity. This suggests that demand-side management can result in environmental benefits not only through reducing energy use, but also by facilitating integration of renewable energy.

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File URL: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe1132.pdf
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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1132.

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Date of creation: 05 Apr 2011
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Handle: RePEc:cam:camdae:1132
Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm

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  1. Maddaloni, Jesse D. & Rowe, Andrew M. & van Kooten, G. Cornelis, 2009. "Wind integration into various generation mixtures," Renewable Energy, Elsevier, vol. 34(3), pages 807-814.
  2. Severin Borenstein, 2005. "The Long-Run Efficiency of Real-Time Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-116.
  3. Gillingham, Kenneth & Newell, Richard G. & Palmer, Karen, 2009. "Energy Efficiency Economics and Policy," Discussion Papers dp-09-13, Resources For the Future.
  4. Burtraw, Dallas & Palmer, Karen, 2005. "Cost-Effectiveness of Renewable Electricity Policies," Discussion Papers dp-05-01, Resources For the Future.
  5. Oikonomou, Vlasis & Rietbergen, Martijn & Patel, Martin, 2007. "An ex-ante evaluation of a White Certificates scheme in The Netherlands: A case study for the household sector," Energy Policy, Elsevier, vol. 35(2), pages 1147-1163, February.
  6. Hobbs, Benjamin F., 1995. "Optimization methods for electric utility resource planning," European Journal of Operational Research, Elsevier, vol. 83(1), pages 1-20, May.
  7. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2009. "Interactions between measures for the support of electricity from renewable energy sources and CO2 mitigation," Energy Policy, Elsevier, vol. 37(11), pages 4743-4752, November.
  8. James Bushnell, 2011. "Building Blocks: Investment in Renewable and Nonrenewable Technologies," RSCAS Working Papers 2011/53, European University Institute.
  9. Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
  10. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
  11. Benjamin F. Hobbs, 1991. "The "Most Value" Test: Economic Evaluation of Electricity Demand-Side Management Considering Customer Value," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 67-92.
  12. Hobbs, Benjamin F. & Nelson, Sushil K., 1989. "Assessing conservation payments: Least-cost, least-rates, or most-value?," The Electricity Journal, Elsevier, vol. 2(6), pages 28-39, July.
  13. van der Weijde, A.H. & Hobbs, B.F., 2011. "Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty," Cambridge Working Papers in Economics 1113, Faculty of Economics, University of Cambridge.
  14. Richard Green & Nicholas Vasilakos, 2011. "The Long-term Impact of Wind Power on Electricity Prices and Generating Capacity," Discussion Papers 11-09, Department of Economics, University of Birmingham.
  15. Lijesen, Mark G., 2007. "The real-time price elasticity of electricity," Energy Economics, Elsevier, vol. 29(2), pages 249-258, March.
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