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Seasonal relationship of peak demand and energy impacts of energy efficiency measures—a review of evidence in the electric energy efficiency programmes

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Abstract

While energy efficiency programmes traditionally focus on energy savings, there is also a policy interest in their impact on system peak demand. Examples include demand-side management, integrated resource planning and recent developments to integrate energy efficiency into forward capacity markets. However, there is only limited research on the relationship between peak demand impacts and overall energy savings from efficiency measures, although this relationship can have important bearings on efficiency programmes. This paper reviews utility efficiency programmes in nine jurisdictions in North America and analyses how the seasonal peak-energy relationship differs between commercial and industrial (C&I) and residential sectors, among efficiency measures. In terms of the seasonal difference in peak demand impacts, these programmes show that residential lighting and residential water heating can deliver greater peak savings in weekday early evening winter peak periods. By contrast, C&I lighting and residential appliances make higher peak savings in weekday afternoon summer peak periods. A seasonal difference is more significant in lighting, especially residential lighting, than other measures. The evidence from North America also suggests that space cooling in both sectors and C&I lighting may well make greater peak savings relative to non-peak impacts than other measures during summer peak periods, while in winter peak periods, residential lighting can achieve greater peak savings relative to non-peak impacts. This review highlights the significance of regional electricity use patterns along with climatic and regulatory conditions and indicates how further research may contribute to appropriate electricity demand reduction programme design and monitoring regimes in particular regions.

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Notes

  1. Great Britain (GB) is made up of England, Scotland and Wales but does not include the other member nation of the UK, Northern Ireland.

  2. System peak demand period is defined as 4 pm-8 pm of non-holiday weekdays between November and February.

  3. Coincident peak demand is the electricity demand occurring during the system peak demand periods.

  4. Heating, ventilation and air conditioning

  5. Electric energy efficiency programmes in Connecticut, Maryland, Massachusetts, New Hampshire and Rhode Island. Capacity payments for the electric energy efficiency programmes in Vermont are channelled to its natural gas energy efficiency programmes.

  6. Including operational optimisation in some measure categories

  7. Portfolio-level evaluation reports report the energy and peak demand impacts for all of their energy efficiency programmes.

  8. For example, in the conservation and demand management (CDM) programmes funded by Ontario Power Authority, The EM&V Protocols and Requirements 2011–2014 defines the peak demand period differently from before it was introduced.

  9. Net impacts refer to those that can be directly attributed to the programme effects (e.g. discounting free-rider and/or free-driver effects from gross impacts).

  10. Load forecast is based on probability. A ‘50/50’ load forecast means that there is a 50 % chance for the actual load to exceed the forecast.

  11. Diversity factor represents the ratio between the highest simultaneous peak demand reduction for a population of specific equipment and the reduction in connected loads. Coincidence factor is the percentage of the highest simultaneous peak demand reduction coincident with a system peak period.

  12. In the Massachusetts TRM, coincidence factor is defined differently as it is the product of coincidence factor and diversity factor.

  13. Include the California Energy Commission forecasting model utility end-use load profile or other studies. However, their use needs the ‘review and approval through the evaluation planning review process’

  14. Regression analysis can be used to account for weather and other variables.

  15. Used with IPMVP Option B or Option D

  16. Measures constituting more than 1 % of IOU-claimed energy savings

  17. The evaluation for 2009 bridge funding period draws upon the results of 2006–2008 programme evaluation.

  18. Lifetime energy savings refer to the amount of energy savings specific measures can accrue over their operational lifetime.

  19. Not included in Fig. 1

  20. Fuel switching measures such as solar water heating are not considered in this review.

  21. Adjustment factors applied to the connected loads to estimate coincident peak demand impacts in winter peak periods

  22. With the exception of Hawaii

  23. Time-based retail tariffs (e.g. time-of-use tariffs) charge different rates depending on when electricity use occurs. By lowering electricity demand (e.g. through energy efficiency) during high price hours, which are typically system peak hours, customers can reduce the electricity expenditure.

  24. Can only be used for lighting, lighting controls, motors and variable speed drives, process chiller, heating controls, retail display cabinets, and professional refrigerated storage cabinets

  25. Partial measurement, full measurement with sub-metering and full measurement with total building metering

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Acknowledgments

The author was supported by the China Scholarship Council to undertake this research. The author would like to thank Dr. Nick Eyre, Dr. Sarah Darby and two anonymous reviewers for their valuable comments on this paper.

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  1. Environmental Change Institute, University of Oxford, South Parks Road, Oxford, OX1 3QY, UK

    Yingqi Liu

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Correspondence to Yingqi Liu.

Appendix

Appendix

Table 2 PERs of energy efficiency measures in the selected efficiency portfolios and programmes
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Liu, Y. Seasonal relationship of peak demand and energy impacts of energy efficiency measures—a review of evidence in the electric energy efficiency programmes. Energy Efficiency 9, 1015–1035 (2016). https://doi.org/10.1007/s12053-015-9407-6

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