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This study discusses important aspects of policy modeling based on a leader-follower game of policymakers. We specifically investigate non-cooperation between policymakers and the jurisdictional sc...

Prosumers, with ability to act both as a supplier and a consumer in a power market, have received considerable attention recently. Possessing with distributed energy resources, their capability to operate in an isolated mode, shielding from the main grid, has also been promoted as a vital option to enhance the power system's resilience. One emerging concern is the prosumer's ability to manipulate the power market as a buyer or as a seller. This study vets the outcomes of a power market in presence of strategic prosumers. We formulate the optimization problem faced by the prosumers in a complementarity problem. We posit a situation in which a strategic prosumer owns a renewable unit with variant output and a dispatchable backup unit, and participates in a competitive market. The prosumer is assumed to maximize its benefit by deciding amount of power to buy from or sell into the main grid, amount of renewable power to forego consumption, and amount of power to produce from backup unit. The model is applied to a case study of the IEEE 24-bus RTS as an illustrative example. We summarize the model properties and findings in three propositions and report distributional impacts of economic rent among conventional suppliers and consumers.

Workplace injury incident rates are commonly reported to change in commensurate with economic situation. Although causal mechanisms, such as new employees, pace of work, and injury reporting behaviors have previously been proposed to explain this phenomenon, there is little empirical evidence supporting this relationship. Using monthly Taiwanese insurance payment data from four main sectors during 2002–2014, this paper examines the relationship by relating major and minor occupational injury to several macroeconomic variables. Regressions based on the first-differenced variables are used to explore how various factors related to the business cycles impact the incidences of major and minor injuries. The analysis is then supplemented with the Granger tests to establish the causality. We conclude that employee fatigue and operational errors that arise from increased working hours and intensified work pace during economic boom times contributed to the injury incidence. In addition, our longitudinal analyses also explain the ways in which firms respond to external demand shocks, thereby further illustrating the mechanism underlying the business cycle and injury incidence.

Sustainability is generally defined as managing the triple bottom line—a process by which companies and governments manage their economic, social, and environmental risks, obligations and opportunities. These three impacts are sometimes referred to as profits, people, and planet. Pursuing sustainability requires these entities to manage products, processes, value chains, and resources in a way that meets the needs of the present without compromising the ability of future generations to meet their own needs (Elkington 1997). On the same basis, the 2030 Agenda for Sustainable Development, adopted by all United Nations (2015), call for a shared set of goals into the future. At its heart are the 17 sustainable development goals (SDGs), an urgent call for action by all countries around the world from an interdisciplinary perspective. Consistent with the goals for pursuing sustainability, the purpose of the book is to provide a holistic review of the state-of-the-art OR/MS research confronting and enhancing sustainability as well as to identify future research directions through bridging differences and assimilating similarities among three domains: (1) Design, Innovation, and Technology, (2) Manufacturing, Logistics, and Value Creation, and (3) Sustainable Natural Resource Management.

We discuss three directions for future research in sustainable natural resource management. These directions are drawn mainly from our research experience and expertise in the energy sector and other natural resource areas. First, we believe that future sustainability and resilience in natural resource management can be enhanced through better utilization of outcomes from process- or physical-based climate change models, such as Global Climate Models. Second, directly related to the electric power sectors is a better harnessing variability and unpredictability via flexibility, transmission, and storage. Third, future natural resource management should consider interdependence of multiple systems, such as power, natural gas, and water systems, through co-optimization of these interdependent systems. We elaborate each of these three future research directions in this chapter.

In Chaps. 4– 6, we treated operational and investment problems from the perspective of power companies. In particular, these firms’ decisions concern generation-capacity expansion and offerings to the electricity market given a particular transmission network. Consequently, the impact of various environmental policies could be examined while taking into account the physical constraints of the network, which are often paramount to the exertion of market power. However, since some environmental policies, e.g., renewable portfolio standards (RPS), aim to incentivize investment in renewable energy (RE) technologies, either expansions to or reinforcements of the transmission grid are necessary. Yet, as discussed in Chap. 1, the restructured nature of the power sector in most OECD countries means that transmission planning is typically conducted by a welfare-maximizing transmission system operator (TSO), whereas generation expansion and operations are carried out by profit-maximizing power companies. Thus, a credible assessment of policy proposals requires a suitable framework that models this distinction between decision makers’ motives directly. Toward that end, we propose a bi-level modeling approach in this chapter in which a TSO at the upper level makes transmission-expansion decisions while constrained by the generators’ decisions at the lower level. After a discussion of the role of the TSO and a survey of the literature, we develop two types of models. Initially, we formulate a benchmark central-planning model that abstracts from the realities of restructured power sectors to provide first-best policy insights stemming from optimal generation and transmission investment in response to the cost of damage from CO\(_2\) emissions. Next, a bi-level modeling approach is taken in which the TSO at the upper level must anticipate the response of industry’s generation-capacity investment and operations. The effectiveness of a carbon tax in inducing socially optimal behavior by industry is investigated. We conclude the chapter with a summary of its content and extensions to the models therein. GAMS codes for implementing the approaches are provided at the end of this chapter.

In many countries and regions, deregulated electricity industries are characterized by oligopolistic ownership structures. Such industries are vulnerable to price manipulation by strategic generating companies. Particularly, a dominant firm, often a large incumbent generator, may exert market power not only in electricity markets but also in related markets such as emission permit markets. This chapter extends the models without any dominant firm in the previous chapter to elaborate on oligopolistic electricity markets subject to cap-and-trade environmental regulation. We first present the framework of the Cournot model based on the Nash equilibrium concept in game theory. A Nash–Cournot equilibrium of the electricity market can be obtained either by a mixed-complementarity problem resulting from each participant’s optimization problem or by an equivalent single quadratic program. Next, we discuss the model of Stackelberg leader–follower oligopoly in the context of electricity markets. The structure of a Stackelberg leader firm with other follower firms that behave a la Cournot is represented by a bi-level problem. It is then recast as a mathematical program with equilibrium constraints, which is further transformed into a mixed-integer quadratic program. The equilibrium outcomes of Cournot and Stackelberg oligopoly under cap-and-trade regulation are illustrated by the numerical examples of three nodes and three firms with ten generating units. We demonstrate how the exercise of market power would have an impact on the electricity price, the permit price, and overall social welfare under different oligopolistic market structures.

Market power in electricity and emission-permit markets in the South-East Europe Regional Electricity Market, which comprises both EU members subject to the EU Emissions Trading System (ETS) and non-EU members exempt from it, affects social welfare and carbon leakage. We examine its impact under three market settings: perfect competition (PC) and two leader-follower versions, in which a leader can exert market power in either the electricity market (S-T) or both the electricity and permit markets (S). Under PC, carbon leakage is equal to 11%-39% of ETS emission reduction depending on the cap stringency. Generally, in S-T, the leader’s capacity withholding results in ETS emissions below and non-ETS emissions above PC levels. However, carbon leakage is lower vis-à-vis PC as the ETS emission reduction offsets the non-ETS emission increase. Finally, in S, the leader’s propensity to lower the permit price increases ETS emissions and exacerbates carbon leakage compared to S-T.

This chapter provides an overview of key features of deregulated power sectors. The major participants in power markets are consumers and suppliers of electricity. Basic information about the behavior of these participants is summarized in the demand and supply functions (curves). We describe how individual participants make their decisions by maximizing consumer or producer surplus. We next show the aggregated outcome of individually heterogenous market participants from two perspectives. First, a market equilibrium is characterized as a result of a decentralized action of each participant. Second, the market equilibrium is expressed as solutions to the centralized maximization of social surplus. We demonstrate that the decentralized equilibrium is equivalent to the solutions to the centralized system if the industry is perfectly competitive without any market failures. An independent system operator (ISO) can be regarded as playing the centralized role to maximize overall social welfare in deregulated power markets, considering the constraints associated with power system operation. In particular, transmission constraints are crucial for the congestion management of power systems. We discuss the basic elements of a physical network and power flows including Kirchhoff’s laws. The last two sections in this chapter provide an overview of two factors that could affect the market outcome in power sectors, namely the incorporation of environmental policies and the market power of suppliers. This chapter serves as a foundation to prepare readers to proceed with subsequent chapters.

Externalities stemming from greenhouse gas (GHG) emissions may drive a wedge between social and private incentives concerning investment and operations in the power sector. While a central planner who internalizes GHG emissions via a Pigouvian tax to curb consumption may yield a first-best policy, decentralized mechanisms are typically deployed in OECD countries’ power sectors in order to align the incentives of private power companies with those of society. Using a bi-level modeling approach, we develop a framework in which a welfare-maximizing policymaker at the upper level sets the renewable portfolio standard (RPS) target for industry, which takes it as a regulatory parameter at the lower level when making its profit-maximizing capacity-expansion and generation-operation decisions. We demonstrate that even in the case of perfect competition, RPS cannot fully align social and private incentives in mitigation of GHG emissions since consumption is not curbed to the same extent as under the first-best policy. Consequently, “too much” renewable energy (RE) investment takes place. This distortion is less pronounced when power companies behave a la Cournot because the exercise of market power already diminishes consumption, thereby reducing the need for RE investment. We illustrate these principles using case studies based on a stylized network and provide techniques for resolving the bi-level problems. Extensions to these cases are explored in the end-of-chapter exercises with implementation of the problem instances in GAMS.

Economists have long been in favor of deregulating or restructuring the power sector in order to promote competition. One of the motivations for doing so is to make the industry more competitive through which investment decisions, such as generation capacity and transmission expansion, are driven by market signals. The so-called market signals include those provided by environmental and energy market-based instruments, e.g., cap-and-trade (C&T) policy and renewable portfolio standards (RPS). This chapter focuses on generation-capacity investment in the power sector. It first introduces screening-curve analysis, a common approach used by the power industry to gauge which technology is economically more (or less) favorable for given capacity factors. Inferring from existing studies, we then focus on open-loop formulations, assuming that producers simultaneously make investment and operational decisions for two reasons. First, the solutions of open-loop and closed-loop formulations have been shown to be equivalent under perfect competition. Second, a long-run equilibrium under perfect competition market entails the notion of the zero-profit condition unless there are significant entry barriers. Solutions to imperfectly competitive oligopoly formulations based on the concept of subgame perfect equilibrium (SPE) exist, but their implementations are limited to small-scale case studies, mostly theoretical studies with limited applicability to any realistic system. Thus, we present open-loop oligopoly capacity-investment models and compare their solutions to those under perfect competition. The chapter then introduces a Stackelberg leader–follower competition in which one of the firms is designated as the leader who possesses opportunities for investing in new capacity while other firms are price takers and not allowed to invest. The resulting mathematical program with equilibrium constraints (MPEC), with followers’ first-order conditions embedded in the leader’s problem, is then recast into a mixed-integer quadratic program (MIQP). The chapter concludes with discussions on possible extensions, including modeling price-containment policies, e.g., permit-price ceiling and floor, that are currently used by the Regional Greenhouse Gas Initiative (RGGI) in the U.S. and the California C&T program.

Bottom-up power market models based upon economic principles with incorporation of engineering details, such as the transmission grid, and calibrated with real market data are powerful tools for market and policy analysis. This chapter describes a step-by-step process to build a power market model when there is no dominant firm in the market. We begin with a single-area cost-minimization problem when the market under consideration is subject to fixed demand. The chapter then introduces how to reformulate the problem as a social-surplus-maximization problem through parameterized demand curves. This chapter next illustrates a decentralized way of solving the model by formulating it as a complementarity problem. We conclude this chapter by pointing out how the models can be extended to study other energy and environmental policies such as renewable portfolio standards and tradable performance-based standards.

Due to its emitting a significant amount of air pollution emissions relative to the rest of the economy, the power sector in most countries is subject to various forms of regulation in order to reduce or to limit its pollution. The regulation evolves from traditional command-and-control policies such as technology or performance standards based on engineering solutions or best-available technologies earlier to more recent implementations of market-based instruments, including emission tax and cap-and-trade programs. Compared to technology or performance standards, market-based instruments are aligned with firms’ profit-maximization principles in a deregulated market place while facilitating the minimization of the system’s pollution-abatement cost through proper pricing of the pollution externality. This chapter reviews various forms of regulation, discusses regional experiences, and highlights the challenges going forward.

What is the extent of a real-time electricity market’s pass-through of the marginal cost of CO2 emissions due to a cap-and-trade (C&T) program? This is an important policy question, as an incomplete pass-through would suggest the program’s limited effectiveness in achieving efficient pricing of electricity. To answer the question, we perform a regression analysis of California’s electricity market data for a 65-month period of 01/01/2011–05/31/2016. Based on this newly constructed large sample, we find that the California Independent System Operator’s real-time market prices contain a CO2 premium that closely tracks the marginal cost of CO2 emissions of California’s natural-gas-fired generation units, which are often at margin that determines the power prices. While the CO2 premium provides much needed incentives for renewable energy development, it does little to improve the incentive for natural-gas-fired generation investment in California. Hence, procurement of dispatchable generation capacity via long-term contracts continues to be useful for the state to meet the mandatory criteria for resource adequacy and system reliability.

Two types of emission trading programs are allowed under the US federal Clean Power Plan (CPP): mass-based cap-and-trade (C&T) program, and the performance-based trading program. While a C&T sets a total emission cap for a region, a performance-based program under CPP relies on trading the emission rate credits (ERCs), which represent an equivalent MWh of energy generated or saved with zero associated CO 2 emissions, to reduce emission costs. This paper examines the theoretical properties of the tradable performance-based policy and compares it to a C&T program. We distinguish two kinds of tradable performance-based policy: (1) a regional policy, under which all states are subject to a regional performance-based standard, and (2) a state-by-state policy, under which each state adopts its performance-based policy within a regional power market while trading of ERCs is allowed. Our findings indicate that under a state-by-state policy, power prices across states could be different even without any transmission congestion, reflecting varying stringency of tradable performance-based standards among states within an interconnected market. We also identify a counterintuitive result that even if ERCs trading is allowed under the state-by-state performance policy, the permit prices could diverge. Two models are simulated in our analysis: three-state and the Pennsylvania-Jersey-Maryland (PJM) regional power market. While the three-state example allows us to illustrate the theoretical properties of the policies, the PJM-based simulation allows us to gauge the performance of the policies. Our PJM analysis shows that a C&T policy is the most effective, while the comparison between a regional and state-by-state tradable performance policy is ambiguous.

We propose a new approach to analyze the payoffs of a hybrid capacity option with a daily-varying strike price. We document that the option’s payoffs are less than the capacity payments required to attract customer participation. We also present results useful for designing payoff-neutral options to enhance customer participation in a capacityidding program. Our proposed approach is equally applicable for a transparent analysis of the payoffs of other types of exotic capacity options.

Motivated by diverse residential electricity outage cost estimates and possible hypothetical bias of contingent valuation (CV) survey data, this paper proposes a simple formula for market-based estimation of residential outage costs. Its key finding is that average residential outage cost estimates for the lower 48 states of the US range from US$0.12 to US$0.34 per kWh unserved, below the regional CV-based estimates of US$1.0 to US$4.2 per kWh unserved found by a national study. It makes three contributions to the literature of residential outage cost estimation. First, it obviates collecting and analysing CV survey data for estimating average residential outage costs. Second, its proposed formula has minimal data requirements and is applicable to any city, state, region, or country. Finally, it details the policy implications of our newly found empirics in electricity pricing, resource planning, resource procurement, electricity product differentiation, and performance-based regulation of electricity reliability.

Using a sample of daily market data, we quantify the effect of California's CO 2 cap-and-trade program on the wholesale electricity prices of four interconnected market hubs in the Western U.S.A.: North of Path 15 (NP15) and South of Path 15 (SP15) in California, Mid-Columbia (Mid-C) in the Pacific Northwest, and Palo Verde (PV) in the Desert Southwest. A $1/metric ton increase in California's CO 2 price is estimated to have increased the electricity prices by $0.41/MWh ( p -value p -value p -value = 0.0056) for Mid-C, and $0.15/MWh ( p -value = 0.0925) for PV. These estimates reflect: (a) the NP15 and SP15 sellers’ pricing behavior of fully including the CO 2 price in their intra-state transactions; (b) the Mid-C price's 100% pass-through of the CO 2 price in the Pacific Northwest's hydro export to California; and (c) the statutory obligation of paying the CO 2 emissions cost by California's buyers of the electricity imported from the Desert Southwest. The policy implication is that internalization of CO 2 's externality in the Western U.S.A. requires a cap-and-trade program with a regional scope that encompasses all four hubs, thereby remedying the California program's limited geographic coverage which introduces distortions in neighboring markets.

The incidence of climate change policy is of great interests to economists, policy makers, producers and consumers. Using the daily market data for a 65-month period of 01/01/2011–05/31/2016, this empirical paper documents that the California Independent System Operator’s day-ahead prices have a CO2 premium approximately equal to natural-gas-fired generation’s marginal cost of CO2 emissions. This finding prevails in the six time-of-day periods developed to match the pricing periods used by the state’s local distribution companies and the bilateral trading of wholesale electricity in the Western Interconnection, a large electricity grid serving the western portion of North America and a Mexican state. Our findings suggest that the California cap-and-trade (C&T) program is effective in internalizing CO2 emission costs of the in-state natural-gas-fired generation. However, the program’s economic efficiency is compromised by the unintended consequence of power laundering under inter-regional trading of wholesale electricity. While the program encourages the Pacific Northwest’s hydro export that displaces California’s natural-gas-fired generation, it also induces output increases by non-California coal- and natural-gas-fired generators in the Western Interconnection. Hence, reducing the overall CO2 emissions in the Western Interconnection requires expanding the program’s geographic scope to meaningfully address the global warming problem.

As part of its climate policy, the European Union (EU) aims to reduce greenhouse gas (GHG) emissions levels by 20% by the year 2020 compared to 1990 levels. Although the EU is projected to reach this goal, its achievement of objectives under its Emissions Trading System (ETS) may be delayed by carbon leakage, which is defined as a situation in which the reduction in emissions in the ETS region is partially offset by an increase in carbon emissions in the non-ETS regions. We study the interaction between emissions and hydropower availability in order to estimate the magnitude of carbon leakage in the South-East Europe Regional Electricity Market (SEE-REM) via a bottom-up partial equilibrium framework. We find that 6.3% to 40.5% of the emissions reduction achieved in the ETS part of SEE-REM could be leaked to the non-ETS part depending on the price of allowances. Somewhat surprisingly, greater hydropower availability may increase emissions in the ETS part of SEE-REM. However, carbon leakage might be limited by demand response to higher electricity prices in the non-ETS area of SEE-REM. Such carbon leakage can affect both the competitiveness of producers in ETS member countries on the periphery of the ETS and the achievement of EU targets for CO2 emissions reduction. Meanwhile, higher non-ETS electricity prices imply that the current policy can have undesirable outcomes for consumers in non-ETS countries, while non-ETS producers would experience an increase in their profits due to higher power prices as well as exports. The presence of carbon leakage in SEE-REM suggests that current EU policy might become more effective when it is expanded to cover more countries in the future.

We explore the role of a transmission system operator (TSO) that builds a transmission line to accommodate renewable energy in order to lower emissions as required by government policy. In contrast to central planning, a TSO in a deregulated electricity industry can only indirectly influence outcomes through its choice of the transmission line capacity. Via a bi-level model, we show that this results in less transmission capacity and with limited emissions control in a perfectly competitive industry vis-a-vis a benchmark centrally planned system. A carbon charge on industry that fully accounts for the cost of pollution damage leads to a perfect alignment of incentives and maximised social welfare only under perfect competition. By contrast, a carbon charge may actually lower social welfare under a Cournot oligopoly as the resulting reduction in consumption facilitates the further exercise of market power.

Climate policy has mostly focused on regulating power suppliers. There is a growing interest in exploring regulating emissions from the demand side by incentivizing consumers to reduce their energy consumptions, or to purchase power from cleaner sources through tracking carbon content of power flow in the transmission network. This paper analyzes market outcomes under two approaches: producer-based and demand-based carbon taxes. We formulate each approach as a market equilibrium model. For the consumer-based approach, the analysis assumes that a utility, procuring electricity on behalf of consumers, is subject to the carbon tax. For the producer-based approach, the producers are subject to the carbon tax, and therefore, pay for their emissions. We show that the two approaches are equivalent when the program's coverage is complete. However, when the coverage is incomplete, the consumer-based carbon tax is less effective in pricing carbon emissions owing to the fact that sales to unregulated regions are not subject to the carbon tax. Given that the transaction cost of implementing consumer-based tax is likely to be high, benefit of tracking power flows in order to estimate carbon content or footprint might not be justified even with a full coverage program.

Using the Envelope Theorem, this paper derives a simple formula for market-based estimation of an average non-residential outage cost. Its key finding is that the 2019 estimate for the US is about US$10 per kWh unserved, below the regional estimates of approximately US$20 to US$40 per kWh unserved previously found by a large national study that uses contingent valuation (CV) survey data. This finding’s policy implication is reductions in marginal-cost-based electricity prices, an electric grid’s need for transmission and generation capacity and demand response resources, a local distribution company’s reliability-related investment, an independent system operator’s cap for wholesale prices, and a regulator’s penalty for reliability deterioration under performance-based regulation.

Incentives for renewable energy based on feed-in-tariffs (FITs) and the renewable portfolio standard (RPS) have succeeded in reducing greenhouse gas (GHG) emissions from the power generation sector. Although numerous countries have adopted a strategy combining both approaches, few studies compare its performance with either the individual FITs or RPS approach. To evaluate the effects of these three policy instruments, this study takes market transactions into account, such as net transfers to the renewable and non-renewable sectors, RPS allocation, and renewable certificate/credit (RECs) exchange. It proposes central planning, bi-level regulation, and regulation under screening as the three market structure scenarios to construct its cases and includes social welfare in the incentive performance index. Further, this study extends to cases of asymmetric information by means of optimal control to reflect market reality for comparison. The numerical examples and counterfactual analyses reach the following conclusions. First, a combined incentive policy performs best when renewable power is in its early stage of development. Second, an integrated incentive policy may neutralize the drastic volatility of FITs or the RPS. Third, the RPS is a favorable approach when the levelized cost of renewable energy is lower than that of non-renewable, while FITs do well when the costs of renewable and non-renewable energy differ slightly. The key policy implication is that along with the reduction in renewable energy generation costs, an RPS and RECs exchange mechanism or combined strategy might be adopted for social welfare benefits, the benefit of the power plants or the TSOs, respectively.

In order to limit climate change from greenhouse gas emissions, governments have introduced renewable portfolio standards (RPS) to incentivise renewable energy production. While the response of industry to exogenous RPS targets has been addressed in the literature, setting RPS targets from a policymaker’s perspective has remained an open question. Using a bi-level model, we prove that the optimal RPS target for a perfectly competitive electricity industry is higher than that for a benchmark centrally planned one. Allowing for market power by the non-renewable energy sector within a deregulated industry lowers the RPS target vis-a-vis perfect competition. Moreover, to our surprise, social welfare under perfect competition with RPS is lower than that when the non-renewable energy sector exercises market power. In effect, by subsidising renewable energy and taxing the non-renewable sector, RPS represents an economic distortion that over-compensates damage from emissions. Thus, perfect competition with RPS results in “too much” renewable energy output, whereas the market power of the non-renewable energy sector mitigates this distortion, albeit at the cost of lower consumer surplus and higher emissions. Hence, ignoring the interaction between RPS requirements and the market structure could lead to sub-optimal RPS targets and substantial welfare losses.

Real-time electricity pricing (RTP) for consumers has long been argued to be key to realize the many envisioned benefits of a smart energy grid. However, there has not been a consensus on how to best implement RTP in an organized, competitive wholesale market with active demand participation. Since most of such markets implement a two-settlement system, with day-ahead electricity price forecasts guiding physical transactions in the next day and real-time ex post prices settling any realtime imbalances, it is a natural idea to let consumers respond to the day-ahead prices. We show in this paper through simulation that naive responsive behaviors to the day-ahead price signals can lead to high price volatility, which will increase not only the risk of system instability, but also the financial risks faced by the consumers. To overcome this issue, we propose a game-theoretic framework in which each consumer solves a multi-armed bandit problem; that is, each consumer learns from the history of the game and attempts to minimize the cumulative regrets. We show through simulation that such a framework leads to drastically reduced volatility on real-time prices and much flatter load curves for the entire grid.

The U.S. Clean Power Plan stipulates a state-specific performance-based CO_2 emission standard and delegates considerable flexibility to the states for using either a tradable performance-based or a mass-based permit program. This paper analyzes these two instruments when they are subject to imperfect competition. We show that while the cross-subsidy inherent in the performance-based instrument might effectively reduce power prices, it could also inflate energy demand, thereby rendering permits scarce. A dominant firm with a relatively clean endowment under the performance-based policy would be able to manipulate the electricity market as well as to lower permit prices, which might worsen market outcomes compared to its mass-based counterpart. On the other hand, the "cross-subsidy" could be the dominant force leading to a higher social welfare if the leader has a relatively dirty endowment.

The U.S. Clean Power Plan stipulates a state-specific performance-based CO2 emission standard, delegating states with considerable flexibility for using either a tradable performance-based or a mass-based permit program. This paper analyzes these two standards under imperfect competitive. We limit our attention to (1) short-run analyses and (2) a situation in which all states are subject to the same type of standard. We show that while the cross-subsidy inherent in the performance-based standard might effectively reduce power prices, it could also inflate energy consumption. A dominant firm with a relatively clean endowment under the performance-based standard would be able to manipulate the electricity market as well as to elevate permit prices, which might worsen market outcomes compared to its mass-based counterpart. On the other hand, the "cross-subsidy" could be the dominant force leading to a higher social welfare if the leader has a relatively dirty endowment.

We propose a framework for analyzing the long-run effects of climate change on the spatial and temporal distribution of nitrogen oxide (NOx) emissions from the power sector. Elevated ground-level temperatures could increase electricity demand during the ozone season, altering the generation mixes and ultimately changing emissions. A sequence of load forecasting, supply investment and operation, and facility siting models is used to project spatial and temporal distributions of NOx emissions. Under a worse-case scenario with no renewable additions or other interventions, the results indicate that even if total NOx is limited by cap-and-trade policies, climate-warming-induced changes in the timing of pollution emissions can be significant, especially under warmer or high-load conditions. This suggests that a continued reliance on fossil-fuel together with a temperature sensitivity of generation efficiency and peak electricity demands increases the likelihood that emissions will be greater during the warm days when ozone episodes also occur. The paper advances the integrated assessment by identifying ways at which climate-change-derived energy demand can impact generation mixture, operations and local air pollution. The downscaled emissions can be used in regional air quality models such as the Community Multiscale Air Quality (CMAQ) to project changes in tropospheric ozone due to climate change.

We study the strategic behavior in an imperfectly competitive cellulosic biofuel supply chain. An optimization-based supply chain model is used to obtain long-run planning outcomes, based on which we develop market models considering both perfect and imperfect competitions. The equilibrium among stakeholders in the multi-echelon supply chain can be obtained by solving a collection of first-order conditions associated with their profit-maximization problems. For the imperfect competition, the model, additionally, allows firms with significant market share at different segment of the supply chain to exercise market power. We apply the models to an illustrative case study of California.

Climate policy has mostly focused on regulating power suppliers. Suppliers then reduce their greenhouse gas emissions through retrofitting pollution control devices, switching fuels, or alternating energy production processes. There is a growing interest in exploring regulating emissions from the demand side by incentivizing consumers to reduce their energy consumptions or purchase power from cleaner sources through tracking carbon content of power flow in the transmission network. This paper analyzes market outcomes under two approaches: producer-based and demand-based carbon tax. In particular, we formulate each approach as a market equilibrium model. For the consumer-based approach, we assume that a utility that procures electricity on behalf of consumers is subject to the carbon tax. For the producer-based approach, the producers will pay for their emissions. We show that the two approaches are equivalent when the program’s coverage is complete. That is, they produce the same prices, distribution of emissions and the economic rent allocation. However, when the coverage is incomplete, the consumer-based carbon tax is less effective in pricing carbon emissions owing to the fact that sales to unregulated nodes are not subject to the carbon tax. Given that the transaction cost of implementing consumer-based tax is likely to be higher, the benefit of tracking power flows in order to estimating carbon content might not be justified even with a full coverage program.

This paper examines the implications of alternative forms of cap-and-trade regulations on the California electricity market. Specific focus is given to the implementation of a downstream form of regulation known as the first-deliverer policy. Under this policy, importers (i.e., first-deliverers) of electricity into California are responsible for the emissions associated with the power plants from which the power originated, even if those plants are physically located outside of California. We find that, absent strict non-economic barriers to changing import patterns, such policies are extremely vulnerable to reshuffling of import resources. The net impact implies that the first-deliverer policies will be only marginally more effective than a conventional source-based regulation.