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6.1 methodology and assumptions The Institute for Sustainable Futures at the University of Technology, Sydney modelled the effects of the Reference scenario and Energy [R]evolution Scenario on jobs in the energy sector.This section provides a simplified overview of how the calculations were performed. A detailed methodology is also available.68 Chapters 2 and 3 contain all the data on how the scenarios were developed.The calculations were made using conservative assumptions wherever possible.The main inputs to the calculations are: For each scenario, namely the Reference (business as usual) and Energy [R]evolution scenario: • The amount of electrical and heating capacity that will be installed each year for each technology, • The primary energy demand for coal, gas, and biomass fuels in the electricity and heating sectors. • The amount of electricity generated per year from nuclear, oil, and diesel. For each technology: • ‘Employment factors’, or the number of jobs per unit of capacity, separated into manufacturing, construction, operation and maintenance, and per unit of primary energy for fuel supply. • For the 2020 and 2030 calculations, a ‘decline factor’ for each technology which reduces the employment factors by a certain percentage per year.This reflects the fact that employment per unit falls as technology prices fall. table 6.1: methodology overview image THE DABANCHENG WIND POWER ALONG THE URUMQI-TURPAN HIGHWAY, XINJIANG PROVINCE, CHINA. HOME TO ONE OF ASIA’S BIGGEST WIND FARMS AND A PIONEER IN THE INDUSTRY XINJIANG’S DABANCHENG IS CURRENTLY ONE OF THE LARGEST WIND FARMS IN CHINA, WITH 100 MEGAWATTS OF INSTALLED POWER GENERATING CAPACITY. For each region: • The percentage of local manufacturing and domestic fuel production in each region, in order to calculate the proportion of manufacturing and fuel production jobs which occur in the region. • The percentage of world trade which originates in each region for coal and gas fuels, and renewable energy traded components. • A “regional job multiplier”, which indicates how labour- intensive economic activity is in that region compared to the OECD.This is used to adjust OECD employment factors where local data is not available. The electrical capacity increase and energy use figures from each scenario are multiplied by the employment factors for each of the technologies, and then adjusted for regional labour intensity and the proportion of fuel or manufacturing which occurs locally.The calculation is summarised in the Table 6.1. A range of data sources are used for the model inputs, including the International Energy Agency, US Energy Information Administration, US National Renewable Energy Laboratory, International Labour Organisation, industry associations for wind, geothermal, solar, nuclear and gas, census data from Australia, Canada, and India, academic literature, and the ISF’s own research. These calculations only take into account direct employment, for example the construction team needed to build a new wind farm. They do not cover indirect employment, for example the extra services provided in a town to accommodate construction teams. The calculations do not include jobs in energy efficiency, although these are likely to be substantial, as the Energy [R]evolution leads to a 40% drop in primary energy demand overall. 6 MANUFACTURING = (FOR LOCAL USE) MANUFACTURING = (FOR EXPORT) CONSTRUCTION = OPERATION & = MAINTENANCE FUEL SUPPLY = (NUCLEAR) FUEL SUPPLY = (COAL, GAS & BIOMASS) HEAT SUPPLY = JOBS IN REGION = EMPLOYMENT FACTOR = AT 2020 OR 2030 MW INSTALLED × PER YEAR IN REGION MW EXPORTED × PER YEAR MW INSTALLED × PER YEAR CUMULATIVE × CAPACITY ELECTRICITY × GENERATION PRIMARY ENERGY × DEMAND + EXPORTS MW INSTALLED × PER YEAR MANUFACTURING + EMPLOYMENT FACTOR ×TECHNOLOGY DECLINE FACTOR(NUMBER OF YEARS AFTER 2010) × % OF LOCAL MANUFACTURING × % OF LOCAL PRODUCTION + FUEL SUPPLY MANUFACTURING × EMPLOYMENT FACTOR MANUFACTURING × EMPLOYMENT FACTOR CONSTRUCTION × EMPLOYMENT FACTOR O&M × EMPLOYMENT FACTOR FUEL EMPLOYMENT × FACTOR FUEL EMPLOYMENT × FACTOR (ALWAYS REGIONAL FOR COAL) EMPLOYMENT FACTOR × FOR HEAT REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER REGIONAL JOB MULTIPLIER CONSTRUCTION + OPERATION & MAINTENANCE (O&M) reference 68 JAY RUTOVITZ AND STEPHEN HARRIS. 2012.CALCULATING GLOBAL ENERGY SECTOR JOBS: 2012 METHODOLOGY. 189 © GP/SIMON LIM future employment | METHODOLOGY AND ASSUMPTIONSPDF Image | SUSTAINABLE WORLD ENERGY OUTLOOK
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