There are significant inconsistencies between the various sources of Government data on renewable energy deployment which undermine confidence in claims regarding progress towards 2020 targets and firm control of subsidy costs to the consumer. For example, the government’s Renewable Energy Planning Database (REPD) is the principal source for estimates of progress and probable future cost, but is inconsistent with five other data sources published by government, and also with estimates made by National Grid. What cannot be measured accurately cannot be managed adequately. Government needs to get a grip.
REF’s Renewable Electricity Target Tracker has just been updated using the latest REPD data published by the Department of Business Energy and Industrial Strategy (BEIS). This continues to show a substantial overshoot, of about 40 TWh, 34% above the 110 TWh required to meet the electricity sector share of the 2020 target set in the EU Renewables Directive of 2009. As we have noted in earlier postings, there is no budget for such an overshoot, and if this is allowed to continue unchecked it will produce a major breach of the Levy Control Framework (LCF) cap which is set at £7.6bn a year (2011-12 prices).
Precise estimates of the cost overshoot are difficult to give due to the uncertainty of strike prices awarded in Contracts for Difference, but an overspend of £1.1bn per year (again in 2011-12 prices) as estimated by the National Audit Office in their recent study of the LCF seems to be of the right order of magnitude. We suspect the NAO has been conservative.
Given the importance of renewables deployment in climate policy and of cost control to public acceptance, it is important that the REPD data is as good as possible. BEIS itself remarks that: “It provides BEIS with robust data that is used to track renewable electricity projects as they move through the planning system”. However, internal checks, and cross checks with other sources suggest that this data is in fact far from robust.
We emphasise that this is not a reflection on the consultants employed by BEIS to produce REPD. It is a critical observation on the inadequacy of government oversight of the renewable sector itself. In a free market, where risk and cost are borne by private enterprise this would be of small concern; public funds would not be at risk, and private capital could be relied upon to protect its own interests. However, it is very striking that a sector that has been created by regulation and is almost entirely dependent on subsidy, currently running at £5bn a year and climbing sharply as the NAO study shows, should be so poorly tracked and monitored by government.
To be specific, data on the deployment of renewable electricity generation is listed in at least six different locations within government records:
(i) The Renewables Obligation (RO) register
(ii) The Renewable Energy Guarantees of Origin (REGO) register
(iii) The Climate Change Levy (CCL) register
(iv) The Feed-in Tariff (FiT) register
(v) The Department’s own publication, Energy Trends
(vi) The Renewable Energy Planning Database (REPD).
Each of these sources records unique values; no two are identical in all respects, and the differences can be substantial. This is extremely surprising.
Furthermore, in some important areas, notably the deployment of Solar PV, government’s data is significantly inconsistent with that of National Grid. For example, there is a more than 1 GW difference in the estimated installed capacity of solar PV at the end of March 2016 between BEIS’s Energy Trends data (10.4 GW) and that of National Grid (9.3 GW).
A lack of consistency between data sources is indicative of the weak control that previous administrations have had over the sector and over public spending to provide subsidies. This is not a trivial concern. Let us suppose, as seems increasingly plausible, that the Department’s Renewable Energy Planning Database, nominally its lead data source for forecasting trends, understates operational renewables while its secondary publication Energy Trends does not, then the discrepancy in total installed capacity is approximately 7 GW. Because it is the government’s principal source for monitoring progress, REF’s Renewables Target Tracker uses the REPD data to calculate the probable energy output, and on the basis of that information, we estimate that the UK has consented sufficient capacity to overshoot the target quantity in 2020 by some 34%. However, if we employ the Energy Trends figures for the current operational portion, the overshoot is some 52% (85 TWh). The related subsidy cost overshoot would thus rise very significantly, perhaps by as much as another £1bn, giving a roughly £2bn overshoot. Which of these two figures is closest to being right? Which is government using in its efforts to control costs?
Better record keeping is obviously crucial, both for the purposes of Treasury accounting and for general public accountability. However, government data collection and publication on the energy sector, while substantial in volume and often interesting, has frequently left much to be desired in terms of accuracy and precision, and it does not appear to be improving. Generation data for the vast bulk of the Feed-in Tariff generators is not collected by government, and much is estimated even for the purposes of subsidy payments. There are apparently no plans for the full public release of generation data from sites registered on the new Contracts for Difference system that replaces the Renewables Obligation for new entrants from next year. And, as we have shown above, even the records of installed capacities are plagued with inconsistencies.
We do not underestimate the difficulties faced by the Department of Business Energy and Industrial Strategy in dealing with the renewables sector, which has been overheated by subsidy and is chaotic and poorly documented, but given the importance of this matter, and the fact the renewables industry is the result of a command economy style instruction, it is time government faced up to its responsibilities to measure accurately and contain cost.