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GSR 2015

40 02 MARKET AND INDUSTRY TRENDS SIDEBAR 4. RENEWABLE ENERGY DATA: DISTRIBUTED CAPACITY AND PRODUCTION Timely, accurate, and accessible data on renewable energy are essential for good policymaking. As deployment of renewable energy technologies increases and their geographical spread widens, the complexity of data collection, verification, and harmonisation also increases. (p See Sidebar 1, GSR 2014.) A problem of data aggregation has long existed for traditional uses of biomass for heating and cooking, and data on direct consumption of biomass have always been estimated. This challenge now extends to modern renewables, and particularly to distributed and small-scale renewable energy installations, which are difficult to track and often are considered insignificant for inclusion in national energy statistics. In the aggregate, distributed small-scale systems can represent a significant share of a renewable technology’s total capacity and generation on a national or even global level. In Germany, for example, where the regulator requires central registration of all solar PV systems and where very detailed data are available, systems below 1 MW accounted for 68% of all solar PV capacity added to the country’s grid in 2014. Due to the rapidly growing number of distributed renewable energy producers worldwide, some account should be made to avoid omitting significant amounts of renewable capacity and generation while ensuring greater accuracy in the aggregate picture. New methods of energy accounting are needed to complete the picture of renewable energy production and consumption. Challenges of accounting for distributed energy production occur mainly in the electricity and heating and cooling sectors (renewable transport fuels, in contrast, typically are produced at larger facilities and are easier to track). Distributed electricity and heating or cooling often are generated on-site for self-use. Except where financial support mechanisms (such as feed-in tariffs) require production accounting, generation data must be estimated based on installed capacity. In many jurisdictions, however, the authorities responsible for energy data collection lack information on the scale of the market, a problem that is particularly acute in developing countries. To overcome these challenges, authorities at the local and national levels are furthering their efforts to improve data surveys and other means of data collection, and international agencies and non-governmental organisations are pursuing innovative approaches to data collection and collaboration. International agencies that long relied solely on official government data have identified differences in accounting methods from country to country and are adjusting their data collection and estimation accordingly. In addition to publishing official national renewable energy statistics, the International Energy Agency (IEA) supplements these statistics with data obtained from multiple non-governmental sources as well as its own estimates, for publication in its annual Medium-Term Renewable Energy Market Report. The International Renewable Energy Agency (IRENA) is improving existing datasets through its Renewable Energy Statistics Questionnaire by collecting detailed data on distributed systems from countries that are able and willing to supply such information. Additional methodological efforts focus on international trade data (extracted from customs and import tax declaration forms) related to solid and liquid biomass fuels and renewable energy equipment, such as solar PV systems. Such information can be used to identify newly installed capacities and to improve renewable energy consumption data. However, international trade codes are harmonised only up to a six-digit level, which is not explicit enough to clearly identify many types of renewable energy carriers or equipment. Additional challenges include the need to convert from the monetary value of the equipment to the respective capacity, and uncertainty around the date of installation and operation of the imported equipment. There is also a potential opportunity to extract renewable energy statistics from broader surveys and datasets. The World Bank is piloting a new multi-tier approach to measuring energy access. The Bank’s methodology includes information on the equipment used to supply electricity and heat for comfort and cooking, which in turn could provide indirect estimates of renewable energy use. For example, the electricity access survey includes data on solar PV systems (e.g., solar lanterns), which make it possible to estimate associated capacity and generation based on assumed size and load hours. In the heating survey, data gathered according to the type of cookstove used could enable estimates of wood consumption based on stove efficiencies. However, extracting renewable energy-specific information from this survey could be labour-intensive and would provide only a partial picture of small-scale renewable installations. Collaboration among organisations and countries can play a significant role in improving data on distributed renewable energy. Points of collaboration include agreements on common methodologies for improving the comparability of datasets, and contributions to freely accessible knowledge portals that bring together data and analysis from multiple sources. Such portals allow for feedback channels that offer the potential to improve data accuracy significantly. Examples include the REN21 Interactive Map (as well as the annual Renewables Global Status Report and regional status reports), which relies on a large network of international contributors, and IRENA’s newly launched REsource portal. The portal currently references only IRENA’s own work, but, in the next phase, it will include the work of multiple trusted renewable energy actors. Overarching initiatives such as the UN Secretary-General’s Sustainable Energy for All also are bringing stakeholders together and improving the understanding of synergies (such as between energy access and small-scale renewable energy systems) in data collection. Source: See Endnote 2 for this section.

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