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Document Number CLNR-L247

Date Posted 31-Mar 2015

Developing the smarter grid: the role of industrial and commercial and distributed generation customers


This report draws together the key learning from the Customer-Led Network Revolution project with respect to the flexibility services industrial & commercial (I&C) customers and distributed generators (DG) can provide for distribution network operators to help them efficiently manage network constraints and keep future reinforcement costs down for the benefit of all customers. It forms part of a suite of comprehensive suite of high-level project learning outputs which are listed under related documents.


The key findings in relation to our I&C and DG customer research are as follows:

Static demand side response– The April 2010 tariff reform, which led to the introduction of the peak pricing signals in the common distribution charging methodology (CDCM), has had little impact on the behaviour of customer electricity consumption patterns and, four years later, still only about 5% of half-hourly customers see the peak pricing signals in the form of the red/amber/green distribution use of system (DUoS) tariff time bands in their electricity bill. Suppliers put this down to their customers wanting simplicity. The aggregate profile of I&C customers does not actually exhibit a peak in the red time band as it tends to fall away from 16:00 onwards. However, any reduction that this sector can make during this period would serve to offset the residential peak and so it would be useful if energy suppliers could actively promote multi-rate tariffs to this group that mirrored the DUoS time bands.

“On-demand” demand side response – Our I&C DSR trials have shown that there is good potential for providing capacity to address post-fault peak-loading constraints at EHV and HV and there are no major barriers to its use by DNOs in locations where there are sufficient willing and flexible customers located downstream of a network constraint. This will not always be the case but, where it is, we recommend that DSR should be the first choice option for addressing constraints. The key issues to address to enable DSR to be become more prevalent relate to the task of identifying and signing up these customers, at a price that is efficient relative to the counterfactual reinforcement costs, in a market where there is competition with other users of DSR (i.e. National Grid STOR). An arrangement where different parties are able to share DSR resource may create value for all stakeholders and is under development by the ENA DSR sharing group.

This report provides the results of our trials, in which we recruited 17MW of DSR capacity, and describes a simple pricing methodology for setting a ceiling price based upon the counterfactual reinforcement scheme costs, years of scheme deferment, DSR set up and operating costs and the level of assumed DSR reliability. This gives an indicative ceiling price in the region of £17 per kW/yr or £2000 per MWh for a typical use case.

We found that it is easier to procure DSR from standby generation than find a truly flexible load but we also found that reliability from the generation sites was not as good, particularly when it came to availability which was only 50%. This will improve as providers get more used to the idea but it also highlights a need for more research to identify flexible loads. The loads that we used were refrigeration and gas compression – both of which provided 100% availability and 100% utilisation.

Generator voltage support – Operating generation in voltage control mode on a DNO network is an effective means of managing voltage through the control of reactive power. We have successfully trialed this with a 54MW wind farm and such an approach could provide an alternative to generator curtailment under certain circumstances.

Generator contribution to network security– A review of distributed generation profiles from a range of generation types has confirmed the contribution to system security as being appropriate as set out in “ENA ETR130 methodology for assessing the contribution of DG to network security” with the exception of wind turbines which we recommend should be reduced as follows:

Wind farms Persistence Tm (hours)
0.5 2 3 18 24 120 360
ENA ETR 130 28% 25% 24% 14% 11% 0% 0%
CLNR trials 19% 15% 14% 8% 6% 0% 0%

Wind farm F factors: Comparison of ETR 130 figures against CLNR calculations

With respect to the overall methodology for calculating the contribution to security we recommend that a fully probabilistic risk-based planning approach be developed, using information from CLNR test cell 8, to support the “Review of ER P2/6 Working Group” of the Distribution Code Review Panel on the review of ETR 130 methodology for assessing the contribution of DG to network security.

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