• Energy Research
• US close
• Energy Policy close

The goal of electric power deregulation in the United States is to lower electricity costs through market competition and greater consumer choice. This goal raises important questions: exactly what kinds of distributed generation (DG) should energy and environmental policy favor? What level of government is best-suited and/or most capable of governing DG? And what is the range of regulations that would most easily facilitate the competitive success of DG? In response, this article provides a comparative analysis of the electricity generation process with heat recovery created to assess the level of polluting emissions associated with a range of technologies and fuel types. Given the results of this analysis, we evaluate the governance structure responsible for regulating energy and environmental policy in the United States, and outline a regulatory approach that would ensure the use of the DG technologies and fuel sources that would be most beneficial to the environment and public health. Our analysis suggests that only the lowest emitting DG with significant waste heat recovery is even marginally competitive with combined cycle power production when air pollution issues are considered. Thus, we advocate technology-forcing in the specific form of manufacturer-based regulation, which would require, over time, the reduction of emissions from DG units at the point of manufacture as a means of ensuring greater air quality.

The goal of electric power deregulation in the United States is to lower electricity costs through market competition and greater consumer choice. This goal raises important questions: exactly what kinds of distributed generation (DG) should energy and environmental policy favor? What level of government is best-suited and/or most capable of governing DG? And what is the range of regulations that would most easily facilitate the competitive success of DG? In response, this article provides a comparative analysis of the electricity generation process with heat recovery created to assess the level of polluting emissions associated with a range of technologies and fuel types. Given the results of this analysis, we evaluate the governance structure responsible for regulating energy and environmental policy in the United States, and outline a regulatory approach that would ensure the use of the DG technologies and fuel sources that would be most beneficial to the environment and public health. Our analysis suggests that only the lowest emitting DG with significant waste heat recovery is even marginally competitive with combined cycle power production when air pollution issues are considered. Thus, we advocate technology-forcing in the specific form of manufacturer-based regulation, which would require, over time, the reduction of emissions from DG units at the point of manufacture as a means of ensuring greater air quality.

The bulk of rural populations in sub-Saharan Africa have no access to electricity and are under-served by any other form of modern infrastructure. The cost of infrastructure to mainly scattered communities has been perennially cited as largely to blame. This is an undeniable truth, but only part of it. There are in addition, myriads of social, economic and political obstacles that play an unquantified and frequently unrecognized negative role. At the route of the problem lies a subdued role of the would-be recipients who in fact, unlike anybody else, are conversant with their problems. Consequently, a number of products may come as impositions or misplaced priorities. Consumer participation for sustainable development has been articulated at international forums and in publications as being advantageous. In practice however, the concept appears to be generally shunned and even when, occasionally, tried the needs of the consumers are presumed and their roles prescribed. This paper discusses a range of social, economic and political issues that constitute major obstacles to the realisation of sustainable rural development.

The bulk of rural populations in sub-Saharan Africa have no access to electricity and are under-served by any other form of modern infrastructure. The cost of infrastructure to mainly scattered communities has been perennially cited as largely to blame. This is an undeniable truth, but only part of it. There are in addition, myriads of social, economic and political obstacles that play an unquantified and frequently unrecognized negative role. At the route of the problem lies a subdued role of the would-be recipients who in fact, unlike anybody else, are conversant with their problems. Consequently, a number of products may come as impositions or misplaced priorities. Consumer participation for sustainable development has been articulated at international forums and in publications as being advantageous. In practice however, the concept appears to be generally shunned and even when, occasionally, tried the needs of the consumers are presumed and their roles prescribed. This paper discusses a range of social, economic and political issues that constitute major obstacles to the realisation of sustainable rural development.

Climate change is unique among the consequences of fossil fuel burning in its far reaching impact, both spatially and temporally. Earlier studies estimate the aggregated monetized damage due to climate change at 1.5 to 2.0% of world GDP (for 2 × CO2); the OECD would lose 1.0 to 1.5% of GDP; the developing countries 2.0 to 9.0%, according to these estimates. These figures are not comprehensive and highly uncertain. Newer studies increasingly emphasize adaptation, variability, extreme events, other (non-climate change) stress factors and the need for integrated assessment of damages. As a result, differences in impacts between regions and sectors have increased, the market impacts in developed countries tended to fall, and non-market impacts have become increasingly important. Marginal damages are more interesting from a policy point of view. Earlier estimates range from about US$5 to US$125 per tonne of carbon, with most estimates at the lower end of this range. These figures are based on polynomial functions in the level of climate change, but the rate of change may be equally important, as are the speed of adaptation, restoration and value adjustment. Furthermore, future vulnerability to climate change will be different from current vulnerability. On the whole, the market impacts fall (relatively) with economic growth while the non-market impacts rise (relatively) with growth.

Climate change is unique among the consequences of fossil fuel burning in its far reaching impact, both spatially and temporally. Earlier studies estimate the aggregated monetized damage due to climate change at 1.5 to 2.0% of world GDP (for 2 × CO2); the OECD would lose 1.0 to 1.5% of GDP; the developing countries 2.0 to 9.0%, according to these estimates. These figures are not comprehensive and highly uncertain. Newer studies increasingly emphasize adaptation, variability, extreme events, other (non-climate change) stress factors and the need for integrated assessment of damages. As a result, differences in impacts between regions and sectors have increased, the market impacts in developed countries tended to fall, and non-market impacts have become increasingly important. Marginal damages are more interesting from a policy point of view. Earlier estimates range from about US$5 to US$125 per tonne of carbon, with most estimates at the lower end of this range. These figures are based on polynomial functions in the level of climate change, but the rate of change may be equally important, as are the speed of adaptation, restoration and value adjustment. Furthermore, future vulnerability to climate change will be different from current vulnerability. On the whole, the market impacts fall (relatively) with economic growth while the non-market impacts rise (relatively) with growth.

Abstract The resilience of social, biophysical, and technological systems is of increasing scholarly and practical import. Guided by scholarship on disaster resilience, environmental inequality, and urban service inequality, we advance the study of “unequal resilience” in a critical infrastructure – the electric grid. We analyze inequality in electricity outage duration at the census block group level using data from the U.S. Census, the U.S. Geological Survey, and a U.S. electrical utility's database of power outages from 2002 to 2004. Our intersectional approach identifies a factor variable of American Indian disadvantage as a correlate of average outage duration – suggesting possible support for an institutional bias hypothesis. However, spatial error regression models demonstrate that unequal resilience within our study area is most consistently explained by proximity to priority assets (i.e., hospitals), average downstream customers affected by outages, and environmental conditions (i.e., the seasonality of outages). These results are consistent with existing research on utilities' response to power outages, and more broadly with the bureaucratic decision rules perspective on service inequalities. We discuss the implications of our findings for future research and energy policy.

Abstract The resilience of social, biophysical, and technological systems is of increasing scholarly and practical import. Guided by scholarship on disaster resilience, environmental inequality, and urban service inequality, we advance the study of “unequal resilience” in a critical infrastructure – the electric grid. We analyze inequality in electricity outage duration at the census block group level using data from the U.S. Census, the U.S. Geological Survey, and a U.S. electrical utility's database of power outages from 2002 to 2004. Our intersectional approach identifies a factor variable of American Indian disadvantage as a correlate of average outage duration – suggesting possible support for an institutional bias hypothesis. However, spatial error regression models demonstrate that unequal resilience within our study area is most consistently explained by proximity to priority assets (i.e., hospitals), average downstream customers affected by outages, and environmental conditions (i.e., the seasonality of outages). These results are consistent with existing research on utilities' response to power outages, and more broadly with the bureaucratic decision rules perspective on service inequalities. We discuss the implications of our findings for future research and energy policy.

A variety of mathematical models have been proposed to characterize and quantify the dependency of electricity supply technology costs on various drivers of technological change. The most prevalent model form, called a learning curve, or experience curve, is a log-linear equation relating the unit cost of a technology to its cumulative installed capacity or electricity generated. This one-factor model is also the most common method used to represent endogenous technical change in large-scale energy-economic models that inform energy planning and policy analysis. A characteristic parameter is the “learning rate,” defined as the fractional reduction in cost for each doubling of cumulative production or capacity. In this paper, a literature review of the learning rates reported for 11 power generation technologies employing an array of fossil fuels, nuclear, and renewable energy sources is presented. The review also includes multi-factor models proposed for some energy technologies, especially two-factor models relating cost to cumulative expenditures for research and development (R&D) as well as the cumulative installed capacity or electricity production of a technology. For all technologies studied, we found substantial variability (as much as an order of magnitude) in reported learning rates across different studies. Such variability is not readily explained by systematic differences in the time intervals, geographic regions, choice of independent variable, or other parameters of each study. This uncertainty in learning rates, together with other limitations of current learning curve formulations, suggests the need for much more careful and systematic examination of the influence of how different factors and assumptions affect policy-relevant outcomes related to the future choice and cost of electricity supply and other energy technologies.