Energy and CO2 implications of decarbonization strategies for China beyond efficiency: Modeling 2050 maximum renewable resources and accelerated electrification impacts

Energy efficiency has played an important role in helping China achieve its domestic and international energy and climate change mitigation targets, but more significant near-term actions to decarbonize are needed to help China and the world meet the Paris Agreement goals. Accelerating electrification and maximizing supply-side and demand-side renewable adoption are two recent strategies being considered in China, but few bottom-up modeling studies have evaluated the potential near-term impacts of these strategies across multiple sectors. To fill this research gap, we use a bottom-up national end-use model that integrates energy supply and demand systems and conduct scenario analysis to evaluate even lower CO2 emissions strategies and subsequent pathways for China to go beyond cost-effective efficiency and fuel switching. We find that maximizing non-conventional electric and renewable technologies can help China peak its national CO2 emissions as early as 2025, with significant additional CO2 emission reductions on the order of 7 Gt CO2 annually by 2050. Beyond potential CO2 reductions from power sector decarbonization, significant potential lies in fossil fuel displaced by renewable heat in industry. These results suggest accelerating the utilization of non-conventional electric and renewable technologies present additional CO2 reduction opportunities for China, but new policies and strategies are needed to change technology choices in the demand sectors. Managing the pace of electrification in tandem with the pace of decarbonization of the power sector will also be crucial to achieving CO2 reductions from the power sector in a scenario of increased electrification

Strategies for Low Carbon Growth In India: Industry and Non Residential Sectors

This report analyzed the potential for increasing energy efficiency and reducing greenhouse gas emissions (GHGs) in the non-residential building and the industrial sectors in India. The first two sections describe the research and analysis supporting the establishment of baseline energy consumption using a bottom up approach for the non residential sector and for the industry sector respectively. The third section covers the explanation of a modeling framework where GHG emissions are projected according to a baseline scenario and alternative scenarios that account for the implementation of cleaner technology

A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons

With the globally increasing electricity demand, its related uncertainties are on the rise as well. Therefore, a deeper insight of load forecasting techniques for projecting future electricity demands becomes imperative for business entities and policy makers. The electricity demand is governed by a set of different variables or “electricity demand determinants”. These demand determinants depend on forecasting horizons (long term, medium term, and short term), the load aggregation level, climate, and socio-economic activities. In this paper, a review of different electricity demand forecasting methodologies is provided in the context of a group of low and middle income countries. The article presents a comprehensive literature review by tabulating the different demand determinants used in different countries and forecasting the trends and techniques used in these countries. A comparative review of these forecasting methodologies over different time horizons reveals that the time series modeling approach has been extensively used while forecasting for long and medium terms. For short term forecasts, artificial intelligence-based techniques remain prevalent in the literature. Furthermore, a comparative analysis of the demand determinants in these countries indicates a frequent use of determinants like the population, GDP, weather, and load data over different time horizons. Following the analysis, potential research gaps are identified, and recommendations are provided, accordingly

Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors

Energy has a strategic role in the economic and social development of countries. In the last few decades, energy demand has been increasing exponentially across the world, and predicting energy demand has become one of the main concerns in many countries. The residential and commercial sectors constitute about 34.7% of global energy consumption. Anticipating energy demand in these sectors will help governments to supply energy sources and to develop their sustainable energy plans such as using renewable and non-renewable energy potentials for the development of a secure and environmentally friendly energy system. Modeling energy consumption in the residential and commercial sectors enables identification of the influential economic, social, and technological factors, resulting in a secure level of energy supply. In this paper, we forecast residential and commercial energy demands in Iran using three different machine learning methods, including multiple linear regression, logarithmic multiple linear regression methods, and nonlinear autoregressive with exogenous input artificial neural networks. These models are developed based on several factors, including the share of renewable energy sources in final energy consumption, gross domestic production, population, natural gas price, and the electricity price. According to the results of the three machine learning methods applied in our study, by 2040, Iranian residential and commercial energy consumption will be 76.97, 96.42 and 128.09 Mtoe, respectively. Results show that Iran must develop and implement new policies to increase the share of renewable energy supply in final energy consumption.Peer reviewe

Proposal for the implementation of a carbon pricing instrument in the brazilian industry : assessing competitiveness risks and distributive impacts

After the COP 21 and the adoption of the Paris Agreement in December 2015, the outlook for carbon pricing policies has been widened. During the conference, Brazil has announced a target to reduce its GHG emissions by 37%, compared to 2005 levels, by 2025, and the intention to reduce 43% of such emissions by 2030. However, considering the industrial sector, there are neither details nor precise quantifications. This gap can represent a strategic opportunity to implement carbon pricing instruments (CPI), such as emissions trading schemes (ETS) or carbon taxes, in this sector. Therefore, this thesis aims to assess institutional frameworks for CPI in the Brazilian industry seeking to reduce its domestic vulnerability and international trade exposure. For this purpose, a qualitative and quantitative analysis is carried out taking into account the lessons from a review of the international experience, besides the assessment of the CPI impacts on sectorial policies and the exposure to the risk of carbon leakage scrutinized under different methodologies. Results show that different institutional frameworks are better or worse depending on main objectives and the impacts to be minimized. Considering the reduction of effects on sectorial competitiveness and families purchasing power as main drivers, an EIS covering total industry emissions, distributed considering a free allocation method and grandfathered-based seems to be a more politically-palatable way to implement a CPI in the Brazilian industry.Após a COP 21 e da adoção do Acordo de Paris em dezembro de 2015, as perspectivas para as políticas de precilicação de carbono foram ampliadas. Durante a conferência, o Brasil anunciou a meta de reduzir as emissões de GEE em 37% em relação aos níveis de 2005 até 2025 e a intenção de reduzir 43% até 2030. Considerando o setor industrial, não há detalhes nem quantificações precisas. Essa lacuna pode representar uma oportunidade estratégica para implementar um instrumento de precificação de carbono (IPC), como esquemas de comércio de emissões (ETS) ou tributos sobre carbono, neste setor. Dessa forma, esta tese tem como objetivo avaliar desenhos institucionais para o IPC na indústria brasileira, visando reduzir sua vulnerabilidade interna e exposição ao comércio internacional. Para isso, é realizada uma análise qualitativa e quantitativa levando em conta as lições aprendidas a partir da revisão da experiência internacional, além da avaliação dos impactos doa IPCs nas políticas setoriais e a exposição subsetorial ao risco de vazamento de carbono a partir de diferentes metodologias. Os resultados mostram que diferentes desenhos institucionais são melhores ou piores dependendo de seu objetivo principal e do impacto a ser minimizado. Considerando a redução dos efeitos sobre a competitividade setorial e sobre o poder de compra das famílias como variáveis principais, um ETS cobrindo as emissões totais do setor, distribuído por um método de alocação gratuito e baseado em grandfathe ring parece ser uma maneira mais politicamente aceitável de se implementar um ¡PC na indústria brasileira

Energy End-Use Technologies for the 21st Century. A Report of the World Energy Council

This report makes clear the opportunities and places technology development firmly centre stage in meeting and overcoming the challenges confronting the energy industry and policy makers. Energy End-Use Technologies for the 21st Century makes it crystal clear that technologies deployed in 20 to 50 years will be the result of policy and funding decisions taken now and that we cannot afford to duck these decisions if we are to meet the World Energy Council’s goals of energy availability, accessibility and acceptability

Bridging the Gap Between Energy and Climate Policies in Brazil: Policy Options to Reduce Energy-Related GHG Emissions

Brazil is facing a series of important policy decisions that will determine its energy future over the next several decades, with important implications for the country's economic competitiveness, the well-being of its citizens, and the global climate. The decisions concern the direction of approximately 0.5 trillion U.S. dollars of anticipated investment in energy infrastructure over the next decade -- which can either lock in carbon-intensive infrastructure, or advance Brazil's position as a leader in the low-carbon economy. This report examines Brazil's key energy-related GHG emitting sectors through a climate lens in order to offer recommendations for a more integrated approach that can more effectively reconcile energy and climate needs. It begins with an overview of Brazil's past energy and GHG emissions profiles, current pledges and future trends, and a discussion of the implications for a possible allocation of the remaining global carbon budget. Next, it reviews available scenarios for Brazil's energy-related GHG emissions in order to identify key drivers and results and compare them to a given allocation of the global carbon budget. It then focuses on the top emitting subsectors -- transport, industry, and power generation -- to identify key abatement opportunities. The report concludes with recommendations regarding a portfolio of policies and measures that could achieve both climate and energy objectives