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Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

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  • Gyamfi, Samuel
  • Krumdieck, Susan

Abstract

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers' network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response.

Suggested Citation

  • Gyamfi, Samuel & Krumdieck, Susan, 2011. "Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response," Energy Policy, Elsevier, vol. 39(5), pages 2993-3004, May.
    • Handle: RePEc:eee:enepol:v:39:y:2011:i:5:p:2993-3004
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    References listed on IDEAS

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    1. Charles Goldman & Galen Barbose & Joseph Eto, 2002. "California Customer Load Reductions during the Electricity Crisis: Did They Help to Keep the Lights On?," Journal of Industry, Competition and Trade, Springer, vol. 2(1), pages 113-142, June.
    2. Dillman, Don A. & Rosa, Eugene A. & Dillman, Joye J., 1983. "Lifestyle and home energy conservation in the United States: the poor accept lifestyle cutbacks while the wealthy invest in conservation," Journal of Economic Psychology, Elsevier, vol. 3(3-4), pages 299-315, September.
    3. Narayan, Paresh Kumar & Smyth, Russell & Prasad, Arti, 2007. "Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities," Energy Policy, Elsevier, vol. 35(9), pages 4485-4494, September.
    4. Herter, Karen & McAuliffe, Patrick & Rosenfeld, Arthur, 2007. "An exploratory analysis of California residential customer response to critical peak pricing of electricity," Energy, Elsevier, vol. 32(1), pages 25-34.
    5. Wall, Rob & Crosbie, Tracey, 2009. "Potential for reducing electricity demand for lighting in households: An exploratory socio-technical study," Energy Policy, Elsevier, vol. 37(3), pages 1021-1031, March.
    6. Ek, Kristina & Söderholm, Patrik, 2010. "The devil is in the details: Household electricity saving behavior and the role of information," Energy Policy, Elsevier, vol. 38(3), pages 1578-1587, March.
    Full references (including those not matched with items on IDEAS)

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