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CLNR TeamLiz SidebothamWashing Machine

Learning outcome 1

What are customer's current, emerging and possible future load and generation characteristics?

Learning Outcome 1 will deliver an understanding of customer's current, emerging and possible future load and generation characteristics. This data will enable us to, update the industry’s current understanding of electricity consumption and generation profiles across a representative cross-section of customer and demographic groups. Broadly speaking, these groups include:

  • A group of around 11,000 domestic customers – the majority of these will be regular customers who do not have low-carbon technologies installed in their homes. However, subsets of this group will have one of the following low-carbon technologies installed in their homes: heat pumps, micro–CHP systems, photovoltaic panels or electric-vehicle charging points. For these customers, enhanced monitoring will be undertaken, including voltage and power quality measurements, as well as in-line monitoring of each low-carbon technology device.

  • A group of around 2,400 small commercial customers – the majority of these will be monitored for half-hourly electricity consumption data. For around 150 of these commercial customers, enhanced monitoring of their electricity consumption profiles will be undertaken, including voltage and power quality measurements.

  • A group of around 14,000 industrial and commercial customers and 230 merchant generators where electricity consumption and generation profiles are monitored and recorded on a half-hourly basis.


A detailed test regime has been defined to collect the data for Learning Outcome 1. This data will enable us to update the industry’s current understanding of electricity consumption and generation profiles, and to analyse the impact of low-carbon technologies on these profiles.

The outputs from Learning Outcome 1 will comprise:

  • A new set of load profiles to update ACE49 (Statistical methods for calculating demand and voltage regulation on LV radial distribution systems, 1981). This will enable a distribution network business to improve its planning of the low voltage electricity distribution networks, and so keep the cost of connections and network /reinforcement as low as possible;

  • A new set of generation profiles to update ETR 130 (Application guide for assessing the capacity of networks containing Distributed Generation, 2006)., This will enable a distribution network business to recognise better the contribution that generation makes to the system security of the electricity distribution network, and so keep , general network reinforcement costs as low as possible;

  • A greater understanding, of how future economic, social and technological trends are likely to affect the patterns of the various components of load and generation. This will enable a distribution network business, to forecast more accurately where it will (and will not) need to reinforce the distribution network; and

  • Quantifying the impact on power quality of new disruptive loads such as heat pumps and electric vehicles.

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