Abstract
One of the key challenges to greater renewable electricity supplies is the temporal mismatch between non-dispatchable renewable sources and peaks in electricity demand. In addition, increased electrification coupled with the de-carbonisation of electricity generation is likely to increase the scale of demand peaks. This could force investment in carbon-intensive peaker generation or capital intensive storage capacity as well as additional transmission and distribution network capacity which may then be substantially underutilised. Whilst considerable effort has been devoted to testing a range of demand response interventions to reduce or shift consumption, less attention has been given to the ability of certain appliances to permanently reduce demand at peak through energy efficiency. In this paper, we use a published model of future energy-efficient lighting uptake together with multi-year measured lighting demand data from a sample of residential households to model the potential power (MW) and energy (MWh) reductions of a ‘business as usual’ rate of efficient lighting adoption. Our estimates suggest that whilst lighting comprises ~ 4% of overall New Zealand annual electricity consumption, it comprises up to 12% of evening peak electricity consumption in winter. As a result, we estimate that by 2029, more efficient residential lighting could reduce New Zealand’s total annual demand by 1 TWh and reduce the highest winter evening peaks (at 17:00) by at least 500 MW (9%). The winter evening demand reduction would be roughly equivalent to avoiding the need for additional generation capacity of the scale of New Zealand’s Huntly Power Stations 1–4 (coal/gas) plus the Stratford peaker plant (gas open-cycle) and has clear implications for any electricity system that is intending to transition towards ~ 100% renewable generation at least cost.
Highlights
Electrification and renewable electricity generation are considered to be the two pillars of a low-carbon energy transition (Bull 2001; International Energy Agency 2019; Yuan and Zuo 2011) because an increase in the share of renewable electricity sources has significant scope to reduce energy-related greenhouse gas emissions (Long et al 2011)
By distributing baseline national lighting electricity consumption from a published lighting efficiency uptake model according to the half-hourly demand profiles of a sample of measured residential households, we estimate that 12% of New Zealand’s winter evening peak period electricity demand in 2015 was due to residential lighting even though it only made up 4% of national annual electricity consumption
12.35 9.95 5.46 9.26 regions in New Zealand, these findings indicate the relative contribution of lighting to peak electricity demand
Summary
Electrification and renewable electricity generation are considered to be the two pillars of a low-carbon energy transition (Bull 2001; International Energy Agency 2019; Yuan and Zuo 2011) because an increase in the share of renewable electricity sources has significant scope to reduce energy-related greenhouse gas emissions (Long et al 2011). We quantify the potential effect of energyefficient lighting on reducing annual demand peaks in New Zealand We do this by combining detailed time-ofuse data of residential lighting demand (Anderson et al 2018) with national-level energy demand data (Energy Efficiency and Conservation Authority 2017a) and a published future lighting technology uptake scenario (EnergyConsult PTY LTD 2015). We use data for the year 2015 as it had the maximum number of dwellings reporting data, had the fewest data outages or quality issues and coincides with the first year of the efficient lighting technology uptake model described above Whilst this sample cannot be considered representative of all New Zealand households due to its recruitment methods and focus on family households (Anderson et al 2018), it provides the most detailed data available on the temporal pattern of residential lighting demand in New Zealand. This is likely to mean that our efficiency savings are underestimates
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