Search

Projections of building electricity consumption are used in multiple fields and for a variety of purposes, from energy utility investment decisions to global climate assessments. Existing approaches to modeling building electricity consumption span a range of structural methodologies, spatial resolutions, and temporal scales, potentially leading to divergent projections. This paper compares how two models with different structures and resolutions respond to a common set of population and climate drivers in the western U.S. The BEND model simulates hourly residential and commercial building electricity consumption at the county scale by weighting the results of simulations of thousands of representative buildings. In contrast, the projected electricity demand in GCAM-USA is determined for each state, year, sector (residential/commercial), and service (e.g., heating, cooling, and others), based on population, income, technology, energy prices, and average annual climate. This paper aggregates the two models’ results to a common resolution: annual residential and commercial building electricity consumption by state. Both models show similar responses to future projected population change and climate change, with population change having the larger impact between the two. Differences are primarily due to how the models capture changes in the aggregate energy efficiency of the building stock as it evolves over time.

Udgivelsesdato: October Climate change response, including the implementation of the Kyoto targets as the first step, calls for technological innovation of future sustainable energy systems. Based on the Danish case, this paper evaluates the type of technological change necessary. During a period of 30 years, Denmark managed to stabilize primary energy supply, and CO2 emissions decreased by 10%, during a period of 20 years. However, after the introduction of the Kyoto Mechanisms, Denmark has changed its strategy. Instead of continuing the domestic CO2 emission controls, Denmark plans to buy CO2 reductions in other countries. Consequently, the innovative technological development has changed. This paper evaluates the character of such change and makes preliminary recommendations for policies to encourage the use of the Kyoto Mechanisms as an acceleration of the necessary technological innovation.

This paper presents an evaluation of energy supply strategies for Egypt’s power sector and identifies prospects to meet rising electricity demand while addressing energy security and low-carbon development issues. We apply the TIMES energy system model to examine Egypt’s energy policy goals as reflected in Egypt’s Vision 2030, and specifically: (a) targeted power generation based on renewable energy under two different scenarios; (b) targeted carbon dioxide (CO2) emissions’ mitigation toward low-carbon society development; and (c) constraints on natural gas production for power generation. The quantitative results from the model suggest a need for diversification from predominantly natural gas to a mix of renewable and conventional energy sources in order to improve energy security, reduce dependency on fossil fuels, and reduce carbon dioxide emissions, with the level of diversification changing with different policy options. Although total energy system cost is projected to increase the effects on fossil-fuel dependency, diversity of energy supply-mix, marginal electricity generation price, and GHG mitigation indicate that it may be wise to target promotion of renewable energy for power generation and develop a low-carbon society.

Major nuclear accidents are typically low-probability–high-consequence events. This paper focuses on weather and sea-level events that might affect the safety of nuclear power plants (NPPs). Flooding risks at Finnish NPP sites have been re-evaluated based on investigations of long-term changes and short-term variations in sea level, which has led to improvements in the protection against extremely high sea water level. Climate change projections indicated that 1000-year return levels of high enthalpy of the air would increase by 13–27% by 2100. However, no clear future trends were projected for the all-year-round probabilities of freezing rain at the NPP sites. Simulations of the spread of hypothetical radioactive releases during two sea-breeze cases, using weather input data at a remarkably high spatial resolution, demonstrated the impacts of coastal meteorological phenomena on atmospheric dispersion. Overviews of various single and combined weather and marine events that could possibly affect normal NPP operation highlighted the need to broaden the scope of future research. Special attention was focused on various aspects of uncertainty. According to the results, a more extreme weather or marine event corresponded to a larger uncertainty in its probability of occurrence in the changing climate.

Climate change will impact renewable resources and electricity demand, usually not jointly considered when designing future decarbonized power systems. This paper assesses how sensitive the Portuguese carbon-neutral power sector is to climate change by 2050 and what are the implications for the formally approved Portuguese Carbon Neutrality Roadmap. The future capacity factors for wind, solar and hydropower and electricity demand response to temperature are estimated for 22 climate projections along the Representative Concentration Pathway 4.5 and 8.5. The eTIMES_PT optimization model is used to assess its combined impact on the cost-optimal configuration of the power sector by 2050. Results show that climate change lowers hydropower generation by 20% (in median terms). Improving spatial and temporal resolution and including future climate patterns, results also in lower cost-effectiveness of solar photovoltaic vis-a-vis the Carbon Neutrality Roadmap. While future climate does not impact onshore wind production, offshore wind power generation is positively affected, being a climate-resilient carbon-neutral option for Portugal. Annual electricity unitary costs at final users (excluding taxes and levies) only increase up to 4% with climate change, but seasonal costs have higher variability. This analysis highlights that climate change affects the cost-optimal annual carbon-neutral power sector and needs to be included in energy planning. info:eu-repo/semantics/publishedVersion

In the current context, climate change has become an unequivocal phenomenon. Although it primarily encompasses change in temperature, nevertheless other weather variables such as rainfall, wind speed, evaporation and humidity can also be affected as a result of climate change. Addressing the impacts of climate change on electricity demand is essential for predicting the future demand. For example, cooling and heating requirements change significantly with respect to climate change that may result to the change in electricity load demand. In this paper, a backward elimination based multiple regression approach is proposed for analyzing the influence of climatic variables on load forecasting. A correlation analysis has been carried out using Pearson’s correlation coefficient to examine the interdependency between different climatic variables in the context of Sydney, one of the most densely populated cities in Australia. Regression based analysis has been performed to examine the relationship between per capita electricity demand and associated climatic variables. ‘Degree Days’ concept has been utilized to determine balance point temperature. Backward elimination based multiple regression is used to exclude non-significant climatic variables and evaluate the sensitivity of significant variables related to the load demand. Average change in future per capita electricity demand has been predicted using the proposed approach for the city of Sydney, Australia. Results indicate that the demand for Sydney will increase by 6% by 2030.

Increasing reliance on uninterrupted electricity supply against emerging threats such as climate change and cyberattacks calls for higher resilience of societies against power disruptions. A better understanding of social and economic impacts during these disruptions would be important for planning of resilience improvements. However, traditional energy system models rarely include these aspects. This paper presents an integrated framework containing a geospatial power system operation model, capable of emulating system component failures and restoration according to environmental conditions, with a link to spatial social and economic values such as population, economic activity, critical services and facilities. The framework was applied for analyzing the effects of uncontrolled and controlled power outages for two windy winter weeks in Finland. This case illustrated how controlled optimization could reduce the societal costs of such outage by shifting power shortage to regions where such costs are lower andin part by shifting the costs to other factors.

Energy systems, which include energy production, conversion, transportation, distribution and utilization, are key infrastructures in modern society. Interactions among energy systems are generally studied under the framework of energy trade. Although such studies have generated important insights, there are limitations. Many distant interactions (e.g. those due to the Fukushima nuclear crisis) are not in the form of trade, but affect energy sustainability. Even when distant interactions are related to energy trade, they are not systematically analyzed. Environmental impacts of trade are often not integrated with economic analysis of trade. In this paper, to identify and fill important knowledge gaps, we apply an integrated framework of telecoupling (socioeconomic and environmental interactions over distances). The framework of telecoupling, which is more comprehensive and cross-disciplinary than the energy trade framework, is a useful theoretical and methodological tool for analyzing distant interactions among coupled human and natural systems (including energy systems). Telecouplings widely exist in energy systems with various forms and link energy sustainability of different countries closely, so we proposed some methods for energy sustainability analysis under the framework of telecoupling. From the aspect of causes, a method is proposed to judge whether the telecoupling driven by economic factors is conducive to energy sustainability. From the aspect of effects, a method is proposed to assess whether an event is conducive to energy sustainability. The telecoupling framework presents opportunities for more profound and comprehensive understanding of energy sustainability.

© 2015 Elsevier Ltd. Both new and existing buildings need to be adapted to climate change, in order to keep providing a comfortable and healthy indoor climate. Preferably, the adaptation measures applied at the building level scale do not require additional energy (i.e. passive measures). Previous studies showed that passive climate change adaptation measures can have a positive effect on thermal comfort in summer and its shoulder seasons in non-air-conditioned residential buildings. In this paper, the effect of these passive climate adaptation measures - applied at building component level - on the cooling and heating energy demand of a terraced house is analyzed using building energy simulations. It is shown that for this particular case the required cooling energy can be limited to a large extent (59-74%) when external solar shading or additional natural ventilation is applied. In addition, it is shown that for a well-insulated terraced house the energy cost for heating is not strongly affected by the application of passive climate change adaptation measures. publisher: Elsevier articletitle: Analysis of the predicted effect of passive climate adaptation measures on energy demand for cooling and heating in a residential building journaltitle: Energy articlelink: http://dx.doi.org/10.1016/j.energy.2015.11.036 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved. ispartof: Energy vol:94 pages:811-820 status: published

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. However, the weather-dependent nature of renewable energy sources often hinders their integration to national grids. Combining different sources to profit from beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity. The method is employed to study the complementarity of wind, solar and hydro resources on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the total temporal complementarity., Comment: Submitted for peer review

Climate change is of great concern for society today. Manufacturing industries and construction account for approximately 20% of global CO2 emissions and, consequently, it is important that this sector investigate options to reduce its CO2 emissions. One option could be to substitute fossil fuels with renewable alternatives. This paper describes a case study in which four future energy market scenarios predicting 2030 were used to analyse whether it would be profitable for a steel plant to produce bio-SNG (bio-synthetic natural gas) in a biomass gasifier and to substitute LPG (liquefied petroleum gas) with bio-SNG as fuel in reheating furnaces. The effects on global CO2 emissions were analysed from a perspective in which biomass is considered a limited resource. The results from the analysis show that investment in a biomass gasifier and fuel conversion would not be profitable in any of the scenarios. Depending on the scenario, the production cost for bio-SNG ranged between 22 and 36 EUR/GJ. Fuel substitution would reduce global CO2 emission if the marginal biomass user is a producer of transportation fuel. However, if the marginal user of biomass is a coal power plant with wood co-firing, the result would be increased global CO2 emissions

The residential sector plays an important role in the energy system of developing countries. In this paper we introduce a bottom up simulation model for household energy use. The model describes energy demand for several end-use functions based on a set of physical drivers, such as floor space and heating degree days. The model also recognizes different population groups: i.e. urban and rural households, each distinguishing five income quintiles. The model is applied to analyze possible future developments of residential energy use in five developing world regions: India, China, South East Asia, South Africa and Brazil. We find that in each of these regions cooking is currently the main end-use function, but that other functions, such as space heating, cooling and appliances become more important. At the same time, energy consumption slowly shifts towards modern fuels. The model also shows that climate policy can reduce residential energy emissions, but could also slow down the energy transition away from traditional fuels in low income classes. (C) 2011 Elsevier Ltd. All rights reserved.

This paper performs a multi-model comparison to assess strategies for adaptation to climate change impacts in hydropower generation in Brazil under two Representative Concentration Pathways. The approach used allows for evaluating the interactions between climate change mitigation and adaptation strategies under low and high impact scenarios through 2050. Climate change impact projections of sixteen General Circulation Models indicate that a global high emissions trajectory scenario would likely yield more severe impacts on hydropower generation than a mitigation scenario. Adaptation modeling suggests that climate change impacts can be compensated by a wide range of alternatives, whose optimality will depend on the level of mitigation effort pursued. Our results show that climate change impacts would lead to even higher emissions in the absence of climate change mitigation policies. On the other hand, mitigation strategies to pursue lower emissions are maintained under climate change impacts, meaning that mitigation strategies are robust when faced with adaptation challenges. Mitigation efforts could yield a more diverse and less carbon intensive mix of technological options for adaptation. When analyzing investment costs to adapt to climate change impacts, in some cases mitigation can lead to a lower total investment level.

The equity implications of alternative climate policy measures are an essential issue to be considered in the design of future international agreements to tackle global warming. This paper specifically analyses the future path of emissions and income distribution and its determinants in different scenarios. Whereas our analysis is driven by tools which are typically applied in the income distribution literature and which have recently been applied to the analysis of CO2 emissions distribution, a new methodological approach is that our study is driven by simulations run with the popular regionalised optimal growth climate change model RICE99 over the 1995-2105 period. We find that the architecture of environmental policies, the implementation of flexible mechanisms and income concentration are key determinants of emissions distribution over time. In particular we find a robust positive relationship between measures of inequalities in the distribution of emissions and income and that their magnitude will essentially depend on technological change. © 2009 Elsevier Ltd. All rights reserved.

There is a broad consensus that the costs of abatement of global climate change can be reduced efficiently through the assignment of quota rights and through international trade in these rights. There is, however, no consensus on whether the initial assignment of emissions permits can affect the Pareto-optimal global level of abatement. This paper provides some insight into the equity–efficiency puzzle. Qualitative results are obtained from a small-scale model; then quantitative evidence of separability is obtained from MERGE, a multiregion integrated assessment model. It is shown that if all the costs of climate change can be expressed in terms of GDP losses, Pareto-efficient abatement strategies are independent of the initial allocation of emissions rights. This is the case sometimes described as ‘market damages’. If, however, different regions assign different values to nonmarket damages such as species losses, different sharing rules may affect the Pareto-optimal level of greenhouse gas abatement. Separability may then be demonstrated only in specific cases (e.g. identical welfare functions or quasi-linearity of preferences or small shares of wealth devoted to abatement).