Assessing the effects of power grid expansion on human health externalities

Generation expansion planning is the framework under which power grid capacity expansions are made. Under this framework, mathematical optimization tools are used to determine the type of generation technology to invest in, and when and where these investments should be made in order to minimize market costs such as investment costs, fixed and variable operating & maintenance costs, and fuel costs over a long term planning horizon. Given the current infrastructure and policies, fossil fuels (such as coal, oil, and natural gas) are among the most economical sources of electricity. Thus, under these assumptions, these energy sources dominate the resulting expansion plans. However, fossil fuel combustion creates by-products contributing to ground-level ozone, particulates, and acid rain, which have harmful health implications such as premature death, respiratory-related illnesses, cardiovascular injuries, pulmonary disorders, and autism leading to lost days at school or work on a daily basis. In this research, we formulate a linear program to solve a multi-period generation expansion planning problem minimizing market costs for a centrally dispatched power system. We can then assess the human health externalities of the resulting expansion plan by studying the model output with an Environmental Protection Agency (EPA) screening tool that determines the human health externalities from the electricity sector. Results with and without emission limits and other policies can then be evaluated and compared based on predicted societal costs including human health externalities. This research enables policy makers to directly assess the health implications of power grid expansion decisions by explicitly estimating the total societal costs by quantifying externalities as part of the investment strategy.     

Modeling regional electric power markets and market power

This paper develops a nonlinear, mathematical programming model for estimating production decisions in an open access, regional power market. Our approach allows one to estimate competitive power market equilibrium prices, which in turn offers empirical conclusions about marginal generation facilities, transmission interconnection congestion, and most importantly, load pockets and market power. Sensitivity analyses are conducted by subjecting the model to changes in production costs, peak hour demand, power imports, and transmission interconnection price assumptions. We then consider the issue of a firm's ability to exercise market power and the implications it may have on regional equilibrium power prices. The Louisiana power market is used as a case study for our work. Copyright © 2001 John Wiley & Sons, Ltd.     

Electricity Auctions

This article examines auctions in the electricity industry. We find that the laws of physics that rule power transmission networks defeat ex post productive efficiency: the cheapest combination of generating plants is not always selected, not even in the optimal auction. Furthermore, neither the pay-your-bid nor the uniform-price auction coincides in general with the optimal auction, nor do they yield productive efficiency. Our analysis also sheds light on behavior observed in existing power markets, and leads to policy recommendations. First, producers protected by transmission constraints must see their bids capped in the short run to curb their ability to extract large rents. Second, producers apparently hurt by the unavailability of transmission capacity may benefit from it. Hence, contrary to common wisdom, policy makers cannot rely on them to finance or advocate transmission expansion.     

The impact of renewable energy diffusion on European consumption-based emissions

The amount of carbon embedded in the final consumption of goods and services in a country or region depends on the amount of goods and services consumed and the emission intensity of the production processes along global production chains. A reduction of consumption-based emissions can be achieved from both sides, a reduction in total consumption and a reduction in the emission intensity of the production processes. The power sector is one of the most carbon intensive industries along global production chains and the global deployment of renewable power generation technologies (RPGTs) is one possibility to significantly reduce emissions in this industry. This paper combines three different strands of literature, multi-regional input–output analysis, dynamic energy–economy–environment models and technological change in renewable energy (RE), to model the impact of the global diffusion of renewable energies on European consumption-based emissions. The global diffusion of RE technologies (photovoltaic and wind) depends on the development of technology costs, which are modeled using learning curves. With increasing deployment of renewables within the EU as well as increasing RD&D efforts, the EU can achieve an accelerated costs decrease for these technologies, thus fostering deployment of RPGTs at a global scale through the effect of decreasing costs. This behavior indirectly influences the electricity mix abroad, making it less carbon intensive, so that consumption-based emissions of the EU decrease.     

The path to renewable energy consumption in the European Union through drivers and barriers: A panel vector autoregressive approach

Renewable energy consumption brings sustainable economic growth and pollution reduction. Despite the worldwide increase in renewable energy consumption, global energy-related carbon dioxide emissions are rising and there are still considerable differences in the share of renewable energy consumption in national energy portfolios. These concerns require further effort at the policy level, especially by countries that make extensive use of energy imports. These countries could improve their lack of energy independence by using renewable energy sources and leveraging a few factors to facilitate their transition. This study aims to investigate renewable energy consumption drivers, focusing on the role of socio-technical (rather than economic) aspects such as policy stringency, lobbying, public awareness, and education. We employ a panel vector autoregressive model in first differences to test the complex dynamic relationships among renewable energy consumption, policy stringency, lobbying, public awareness, and education, controlling for variables such as per capita income and import levels, for 12 European Union net energy importing countries. Results show that the positive income effect prevails in the influence of the level of carbon dioxide emissions (negative) on renewable energy consumption, despite the latter being more significant in countries with higher levels of education. Increasing energy needs push traditional sources towards complementarity with renewable energy consumption, implying a positive lobbying effect. Public awareness is not enough to facilitate the transition to renewable energy consumption. By contrast, policy stringency has positive direct and indirect effects on renewable energy consumption, suggesting that the approach adopted by the European Commission in the recent Green Deal is a step in the right direction. Moreover, as shown, policymakers are able, through renewable energy consumption, to generate a decrease in carbon dioxide emissions and electricity production from oil, gas, coal, and nuclear sources in the first instance, but also in net energy imports, even if at a later stage.     

Optimal expenditures on police protection

The object of this paper is to propose an approach for operationalizing Rubin's (Minimizing Harm: a New Crime Policy for modern America, Westview Press, Boulder, CO, 1999) idea that minimizing harm is a solution to the crime policy conundrum. Harm is defined to be the total cost of damages due to crime plus the cost of police protection. Its minimization determines optimal expenditures for protection. This is an appropriate basis for specifying the optimal size of a police force, and provides a term of reference for actual policy decisions. Data for the states of the US are used to make the presentation more concrete and to clarify some of the problems that must be solved in actual applications of the method suggested. This does not eliminate the applicability of the approach to any other country or to the geo-political subdivisions within a country. The results obtained are of interest to policy makers dealing specifically with expenditures for police at local, regional or national levels or, more generally, with similar uses of public or private financial resources.     

The effects of regional trade integration and renewable energy transition on environmental quality: Evidence from South Asian neighbors

Improving environmental quality across South Asia has become one of the utmost important policy agendas of the concerned governments. The susceptibility of the majority of the South Asian countries to multifaceted climate change adversities has motivated the need to identify the factors that can function to ensure environmental sustainability across South Asia. Although several studies have highlighted the importance of globalization and cleaner energy use in tackling the environmental degradaton issues of the South Asian countries, very little is known regarding the impacts of regional trade and renewable energy transition in this regard. Hence, this paper aims to scrutinize the effects of enhancing intra-regional trade integration and undergoing renewable energy transition on per capita carbon dioxide emissions in the context of six South Asian nations between 1990 and 2016. The results from the recently developed cross-sectionally augmented autoregressive distributed lag regression approach, accounting for cross-sectional dependency and slope heterogeneity issues, reveal that facilitating trade among the South Asian neighbors reduces carbon emissions in both the short and long run. Moreover, enhancing the share of renewable energy in the aggregate energy consumption figures is also found to reduce carbon dioxide emissions in both the short and long run. Furthermore, both regional trade integration and renewable energy transition are found to jointly reduce carbon dioxide emissions in South Asia. The results also authenticate the existence of the environmental Kuznets curve hypothesis, while financial development and urbanization are found to boost carbon dioxide emissions only in the long run.     

Policy Capacity and Incapacity in Canada's Federal Government

Abstract

Governments, world-wide, are preoccupied with avoiding policy failure. A high level of policy capacity is considered one indicator of addressing this issue. Canada is typical of most countries where policy-related work tends to be centralized within its national capital city (Ottawa). There have been criticisms that on-the-ground perspectives are not conceded in policy decisions. Given the vast size and the decentralization of power, very little research has been dedicated to policy work conducted in its regions and whether it contributes to strengthening policy capacity. This article employs eight key hypotheses about contribution of Canadian regionally-based federal policy work to policy capacity based upon data derived from a national survey. A structural equation model (LISREL) is used to present the results. We find that regional-based policy work currently does little to enhance policy capacity. Policy work is divided along two distinct functional lines: traditional policy analysis and ‘street-level’ bureaucracy. The more engaging policy analysts belong to formal policy units which are a critical aspect of stronger policy capacity. The second factor contributing to policy capacity were attitudes towards the larger political arena.     

Collective decision making by committee

Implicitly or explicitly, economic decisions always contain elements of compromise. However, the bargaining models of economic theory treat only the two decision maker case with linearly aggregated priorities; i.e. compromise decisions under Pareto optimality and no side payments. Even then the relative importance of the decision makers remains indeterminate. This paper proposes a simplified bargaining model with three new features: (a) it allows multiple participants; (b) it uses optimal voting patterns to combine the policy proposals, rather than the policy priorities, to form those compromise decisions; and (c) it determines the relative power of each participant endogenously. Perhaps more important, the method does not depend on each decision maker knowing the preferences of his colleagues exactly.     

Environmental policy implications of extreme variations in pollutant stock levels and socioeconomic costs

This paper uses a real options approach to examine the impact of abrupt increases in carbon dioxide emissions and pollutant-related socio-economic costs. It derives optimal investment rules in the form of critical values for both pollutant stock levels and social costs, above which environmental policies should be adopted. Moreover, it determines the optimal emissions abatement level. Our analysis extends the methodology of Pindyck (2000) using jump diffusion processes. We show that if the stock of pollutant is subject to extreme variations and the emissions abatement level is chosen exogenously by the policymaker, then lower levels of the pollutant stock are required to trigger policy adoption. A similar, yet more prominent, effect is observed under the assumption that pollutant-related socio-economic costs and benefits are expected to exhibit abrupt changes. However, different results are obtained when we examine simultaneously the two interrelated decisions, namely, the optimal threshold of emissions abatement and the optimal abatement level. In this case, an increase in the size and/or probability of a jump increases the critical values of both pollutant stock levels and socio-economic costs but leads to higher optimal abatement.     

A scenario-based integrated approach for modeling carbon price risk

Carbon prices are highly dependent on government emission policies and local industrial compositions. When historical data does not exist or limited price data can only be sourced from another country, scenario analysis becomes the only tool for the modelling of future carbon prices. However, various plausible but equally possible scenarios can produce large variations in forecast carbon prices. In a traditional approach of scenario analysis, investment decisions or risk management strategies are proposed and analysed for each given scenario, optimal solutions are determined. However, when the number of scenarios becomes large, it often becomes too complex and intractable to have a clear view on the selection of investment decisions or risk-management strategies because these decisions and strategies are closely linked with each of the many scenarios. In this paper, it is proposed to use a stochastic mean-reversion model to represent future carbon price movements, but this model is calibrated to the forecast carbon prices of all the scenarios. In this approach, a single model is used to capture the underlying uncertainty and expectation of the stochastic carbon prices as projected by all the scenarios, carbon price risk can thus be modeled and analysed without the need for direct references to any specific scenarios. The modelling and management of long-term carbon-price risk are therefore purely dependent on future carbon price levels and volatilities of these scenarios, instead of on the scenarios themselves. Through such an approach, the optimization of investment decisions and risk management solutions can be much simpler because the forecasted carbon prices are the only input data.      

The impact of capacity expansion on the market value of the firm

This paper empirically investigates the impact of capacity expansion decisions on the market value of the firm. Event study methodology is used to estimate the abnormal change in stock prices around capacity expansion decision announcements. On the day of the announcement, the magnitude of the price change is abnormally high, evidenced by a significantly positive mean standardized square of the abnormal change (Beaver's U-statistic). We also analyze factors that we could affect the direction and magnitude of the abnormal change in the stock prices. We find that the change in price on the day of the announcement is positively and significantly related to the real growth rate of the industry, and negatively and significantly related to the variability of demand. A negative relationship between the price change and industry capacity utilization is also found which can have important implications for companies which follow the wait-and-see approach to capacity expansion decisions. We also find management ownership to be a significant predictor in explaining stock price changes around these announcements.     

Federal Water Resources Policy and Decision-Making: Their Formulation Is Essentially a Political Process Conditioned by Government Structure and Needs

A bstract . The effects that politics, government structure , and economic standards have upon federal water resources planning are examined. Water resources policy decisions are treated as a product of political demands which, in turn, are examined as a product of the direct or indirect stakes, or perception thereof, in a policy. Government structure also affects decisions, since it affects political access and, subsequently, power as well as the administrative capacity of government. Economic standards , such as a requirement that water projects contribute to national economic development , arise within a political context. Formulation of federal water resources policy is essentially a political process that is conditioned to some extent by government structure and planning standards such as economic requirements. Thus, recommendations to improve the product of this process must take into account its essential nature. Examples are drawn from the western reclamation and water pollution experiences.     

我国可再生能源发电产业区域发展能力评价

正确评估我国各省区可再生能源发电产业的发展能力,是制定产业规划、优化资源配置、促进产业快速发展的前提。论文以区域产业发展理论和可持续发展理论为基础构建了评价指标体系,并运用AHP(层次分析法)对全国各省区的可再生能源发电产业发展能力进行了综合评价。     

碳交易政策下供应链协调决策机制研究

供应链系统中成员企业存在竞争关系,在减排活动中容易相互推卸责任,使供应链系统不能良性发展,因此协调各方利益做到互利双赢十分重要。深入探究了单周期两级供应链的订购与减排决策模型,针对碳交易政策,并结合政府减排技术补贴政策,重点研究了收益共享契约对最优订购量、最优碳减排率以及最大收益的影响。     

Integrated environmental policy instruments driven river water pollution management decision system

Market-based approaches and command and control regulations are the two main tools that policy/decision makers use to implement environmental protection goals; however, these alone have proven to be somewhat ineffective or counterproductive in some cases. Therefore, this study proposes a hybrid environmental policy tool to guide river basin environmental management decisions. The river basin authority and regional Environmental Protection Agency (EPA), as the two leading decision makers, and policy makers and implementers of river basin management, make decisions sequentially in a process similar to a Stackelberg game. This decision making can be mathematically represented using a bi-level optimization model. The proposed model addressed the conflicting equitable resource allocation and economic efficiency objectives to achieve coordinated development of the whole river basin. To verify the model effectiveness, the most considerable pollutant emissions limits and water quality standards were set, and incentive measures (pollution chargers and subsidies) were applied to assess these hybrid instruments' impact on the decision outcomes. The results from a Minjiang river basin case further illustrated that the trade-off between social equity and cost-efficient environmental goals could efficiently achieve, proving that a combination of instruments could be influential in pollution decision-making and delivery of environmental policy. Given the model's proven effectiveness, several proposals are given for solving complex pollution problems that also need to consider the related socioeconomic issues.     

Comparing the forecasting performances of linear models for electricity prices with high RES penetration

We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable energy sources. The accuracy of point and density forecasts is inspected in four main European markets (Germany, Denmark, Italy, and Spain) characterized by different levels of renewable energy power generation. Our results show that the Bayesian vector autoregressive specifications with exogenous variables dominate other multivariate and univariate specifications in terms of both point forecasting and density forecasting.     

Analysis of technology pathway of China's liquid fuel production with consideration of energy supply security and carbon price

Efforts to provide alternative resources and technologies for producing liquid fuel have recently been intensified. Different levels of dependence on oil imports and carbon prices have a significant impact on the composition of the cost-minimizing portfolio of technologies. Considering such factors, how should China plan its future liquid fuel industry? The model for supporting the technology portfolio and capacity configuration that minimizes the total system cost until 2045 is described in this study. The results obtained for different carbon prices and levels of dependence on oil import indicate that the oil-to-liquid fuel (OTL) will remain dominant in China's liquid fuel industry over the next three decades. If the carbon price is low, the coal-to-liquid fuel (CTL) process is competitive. For a high carbon price, the biomass-to-liquid fuel (BTL) technology expands more rapidly. The results also reveal that developing the BTL and CTL can effectively reduce the oil-import dependency; moreover, a high carbon price can lead to the CTL being replaced with the low-carbon technology (e.g., BTL). Improvement in energy raw material conversion and application of CO₂ removal technologies are also effective methods to control carbon emissions for achieving the carbon emission goals and ultimately emission reduction targets.     

考虑延期成本承诺交货时间与产能扩张决策

根据产能与交货时间的关系,构建了延期成本函数。在此基础上,建立以企业利润为目标函数,以承诺交货时间和产能扩张为决策变量的模型。通过模型的分析得到了相互递推的最优承诺交货时间和最优产能扩张关系式,以及联合最优承诺交货时间和产能扩张。最后通过算例分析表明企业利润随着承诺交货时间或产能扩张的增加先增加后减少,两者相比,企业利润受承诺交货时间影响更大。     

Eco‐efficiency: GHG reduction related environmental and economic performance. The case of the companies participating in the EU Emissions Trading Scheme

Empirical findings on eco‐efficiency are still inconsistent. Using survey data based on a sample of 283 European carbon‐intensive companies participating in the EU ETS between 2005 and 2012, this article investigates the causal relationships between the corporate environmental strategy focus, proactive GHG reductions and related environmental and economic performance, while taking into account an important contingent factor: the initial state of technology. The study's findings show that eco‐efficiency was generally not obvious among the companies during the first two trading periods. It furthermore indicates that GHG emissions were generally not reduced cost‐effectively, as companies' intrinsic values were more likely to have influenced carbon reduction related decisions to a greater degree than the economic incentives resulting from the market mechanisms of the ETS. The results not only shed light on firm behavior with regard to technology management but also provide insights for policy makers into how to stimulate more cost‐effective environmental investments. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment