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We develop a transmission planning framework for coupled natural gas and electric power systems facing geographically correlated failures. The framework uses a stochastic optimization method incorporating uncertainty in the locations of the geographically correlated failures. We compare the proposed planning framework with the traditional N-k method which plans for geographically uncorrelated failures in terms of improving resilience effectively against geographically correlated failures. The proposed planning framework is illustrated using a small test system, but is scalable to larger system sizes and portable to other coupled-infrastructure contexts. We illustrate how planning for geographically correlated failures can enhance system-wide robustness by reinforcing the network connectivity between supply and demand locations instead of addressing local vulnerability at specific locations when planning for geographically uncorrelated failures. Planning for geographically correlated failures improves system resilience to both geographically correlated and uncorrelated failures significantly, but the converse is not true in our case study. • Propose a planning method for coupled systems with spatially correlated failures. • Planning for correlated failures enhances network connectivity and resilience. • Planning for uncorrelated failures addresses more local vulnerabilities. [ABSTRACT FROM AUTHOR]

Abstract The electricity industry is rapidly changing: costs are increasingly dominated by capital and technology is turning loads into resources. This is similar to the early days of the Internet. Building on rate-structures used in the communications industry, utilities of the future should offer customers a portfolio of service contract options that provide a signal to the utility regarding the type and amount of infrastructure that should be deployed. [ABSTRACT FROM AUTHOR]

This research introduces a detailed techno-economic model to estimate and evaluate the economics of enhanced oil recovery. The model categorizes the cost objects into three main modules: injection, production, and CO 2 recycling. These modules are composed of a number of lower-level sub-modules that represent specific cost objects. The techno-economic model utilizes reservoir simulation inputs and results such as production rate and composition, injection fluid rate and composition, and bottomhole pressure to provide detailed costs and revenue of injection, production, and CO 2 recycling, according to defined scenarios. Although the techno-economic model is a general model that can be applied to any EOR project, we illustrate it here to compare flooding scenarios for a modeled EOR project in Mississippi. Reservoir heterogeneity is the variation of petrophysical properties with space such as porosity, permeability, fluid saturation. This effect is explored for total of 81 cases considering different combinations of Dykstra-Parsons coefficient (VDP) and correlation length. For each case, 25 random realizations of the permeability field were generated and the results of realizations were averaged to provide a statistical representation of the cases. Simulations of three scenarios including Waterflood, Water Alternating Gas, and Surfactant Alternating Gas floods (using a foam model for SAG) were carried out for each realization. The results show that, under assumed cost structure and the selected foam model, on average, SAG is a better and more profitable injection scenario with an oil price of $40/bbl. The economic advantage of SAG, however, declines with greater permeability variation. [ABSTRACT FROM AUTHOR]

Abstract Low electric energy prices in the PJM market are financially threatening some of Pennsylvania's nuclear power plants. An analysis of capacity and energy markets with and without two of Pennsylvania's most economically threatened nuclear power stations suggests that the retirement of these plants will not materially raise energy costs for Pennsylvania ratepayers. In the near term, the pace of investment in efficient generation capacity will be the more important factor affecting the state's electricity costs. [ABSTRACT FROM AUTHOR]

Using large data sets of simulated wind and solar energy production, we create optimal wind, solar and blended (combined wind and solar) portfolios over various spatial and temporal scales, and use portfolio theory to quantify the capacity benefits in various portions of the electric grid in the Eastern United States. We add to the existing literature on portfolio analysis of renewable energy resources by (i) studying the benefits of optimal aggregation over various spatial and temporal scales, (ii) quantifying the capacity benefits of renewable portfolios over space and time, and (iii) analyzing spatial distributions of renewable installations in optimal renewable portfolios. The results indicate that full time availability of wind and blended portfolios are respectively 14 and 17 times larger than full time availability of an individual wind farm and adding solar to wind portfolios increases the availability factor of renewable portfolios by more than 40% in most regions. Further, optimal hourly portfolios provide higher capacity value relative to daily and weekly portfolios. [ABSTRACT FROM AUTHOR]

We use a large data set of simulated wind energy production in the United States to quantify the geographic and temporal scaling of energy output variability reduction when multiple sites are aggregated. We add to the existing literature on “geographic smoothing” by (i) quantifying the scaling of geographic smoothing over multiple spatial and temporal scales; (ii) bounding such smoothing through the use of an algorithm that produces minimum-variance sets of wind energy production sites; and (iii) quantifying inherent tradeoffs in optimizing wind energy site selection to minimize output variability along a specific frequency. The number of wind farms required to minimize output variability increases linearly with spatial scale of aggregation, but the scaling factor is small, on the order of 10 - 6 relative to geographic distances. These scaling factors increase by a factor of two as the frequency considered increases by three orders of magnitude (minutes to months). Our analysis indicates that optimizing wind deployment over one particular frequency increases output variability over other frequencies by nearly 30% in some cases. [ABSTRACT FROM AUTHOR]

Combined heat and power (CHP) generates electricity and heat from the same fuel source and can provide these services at higher equivalent conversion efficiency relative to grid-purchased electricity and stand-alone steam production. Previous work has focused on the economic factors and optimal operation strategy that influence the decision to install a single CHP unit. The approach discussed in this paper is to assess the economic potential for CHP in an electricity-market equilibrium framework, accounting for the impact that CHP adoption at scale will have on electricity prices—incremental installations of CHP reduce the demand for grid-provided electricity in some locations, thus reducing wholesale prices in that location. A statistical model of electricity supply and pricing is utilized to estimate locational electricity supply curves that reflect the impact of transmission congestion on locational price formation and location-specific elasticities of supply. The zonal electricity pricing model is coupled with the model of CHP adoption and utilization in commercial buildings for two locations in the PJM power grid. Under a range of operational assumptions and fuel prices, returns to incremental CHP deployment decrease rapidly in both locations for the first 100 MW of building-integrated CHP deployed, although CHP becomes an uneconomical decision only at much higher deployment levels. Although the elasticity of supply is an important determinant of economic potential for CHP, the authors find that in most cases, operating CHP units to follow building thermal demand (versus electrical demand, which would offset peak electricity-demand periods) yields higher returns over a broader range of CHP deployment levels. [ABSTRACT FROM AUTHOR]

For firms developing and managing portfolios of PV assets in utility, commercial, and residential markets the financial performance of the portfolio is a highly relevant business decision factor. Informative metrics are required to quantify the revenue variance of a spatially distributed portfolio of PV assets as well as the individual asset. Financial analysis uses a risk measure known as ‘beta’ to describe the movement of assets relative to a broader portfolio. We define a measure termed the ‘solar beta’ that describes the movement of solar PV revenues at a given site with that of a portfolio of sites. The solar beta incorporates correlation between a site and portfolio, and the volatility of a site relative to the portfolio. We also derive and discuss a method to decompose revenue variance of individual PV assets into components representing price, power, and the interplay among diurnal/seasonal cycles and prevailing weather conditions. This decomposition and the solar beta are illustrated using nine modeled sites following a N–S trend within the PJM Interconnection. We find that revenue variance of a PV asset depends more on diurnal, seasonal, and meteorological fluctuations than on price fluctuations at a particular site. Specifically, the contribution of power variance exceeds the contribution of price variance by roughly a factor of five. Changes in mean market price have a larger effect on revenue variance compared to a proportional change in mean power production. The solar beta was found to be near 1.0 for most sites, indicating strong covariance within the portfolio due in large part to high correlation rather than similar volatility ratios. Lower beta values were found for sites at the perimeters of the study region, due to change in climate regime and population-power consumption cycles, implying portfolio risk reduction when these sites are included. [ABSTRACT FROM AUTHOR]

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal. [ABSTRACT FROM AUTHOR]

Energy efficiency can be a powerful way to lower energy bills, as well as the external (social) costs associated with energy consumption. Previous experience and research, however, has demonstrated that consumers are often unwilling to make investments in energy efficiency, even when such investments have relatively short payback periods. Because energy efficiency can contribute to correcting negative externalities associated with energy use, subsidies and other programs have been proposed as a way to increase efficiency investments. Thus, under the right circumstances, such subsidies can improve economic efficiency. In this paper, we analyze the economics of energy-efficient space conditioning using data from an actual household in rural Pennsylvania to evaluate ground-source heat pumps (GHP). GHP technology has been advocated as a potentially appealing energy efficiency measure for rural communities. We find that with current subsidies GHP is economically viable for a wide range of electricity prices. We also find, however, that current subsidies are actually greater than those that can be economically justified. Using the efficient level of subsidies reduces, but does not eliminate, the economic case for GHP technology. We also evaluate the economics of efficiency subsidies using an ambitious program in Pennsylvania as a case study. The program, known as the Alternative Energy Investment Act (AEIA), provides subsidies for GHP among other technologies. We find that the substantial federal subsidies for GHP undercut the economic efficiency arguments for the AEIA with respect to GHP. [ABSTRACT FROM AUTHOR]

Abstract: The “smart grid” represents one of the greatest potential advances in electricity delivery infrastructure in the past century. While the technologies that collectively comprise the smart grid have existed for decades, the potential for changing the way that electricity is generated, delivered, utilized and priced is revolutionary. Not surprisingly, many countries have undertaken initiatives to rollout smart grid infrastructure at an aggressive pace. Understanding the fundamental changes that the smart grid is likely to introduce is important for the development of future energy scenarios and the environmental, social and economic implications of these scenarios. Here we present an overview of the emerging smart grid and outline a few implications for the energy modeling community. Specifically, we discuss the potential for the smart grid to act as an enabling technology for renewable energy integration, price-responsive electricity demand, electrified transportation and distributed energy production as examples of how the smart grid may fundamentally change future energy system scenario development. The smart grid is being deployed and implemented much faster than we are able to fully consider its implications, and in some cases public policy has a long way to go before it catches up with the pace of smart grid technology deployment. [Copyright &y& Elsevier]

The price of delivered electricity will rise if generators have to pay for carbon dioxide emissions through an implicit or explicit mechanism. There are two main effects that a substantial price on CO2 emissions would have in the short run (before the generation fleet changes significantly). First, consumers would react to increased price by buying less, described by their price elasticity of demand. Second, a price on CO2 emissions would change the order in which existing generators are economically dispatched, depending on their carbon dioxide emissions and marginal fuel prices. Both the price increase and dispatch changes depend on the mix of generation technologies and fuels in the region available for dispatch, although the consumer response to higher prices is the dominant effect. We estimate that the instantaneous imposition of a price of $35 per metric ton on CO2 emissions would lead to a 10% reduction in CO2 emissions in PJM and MISO at a price elasticity of -0.1. Reductions in ERCOT would be about one-third as large. Thus, a price on CO2 emissions that has been shown in earlier work to stimulate investment in new generation technology also provides significant CO2 reductions before new technology is deployed at large scale. [ABSTRACT FROM AUTHOR]

Current regulatory policy distinguishes transmission investments that have primarily economic benefits from those that primarily enhance reliability. But no such dichotomy exists; congestion and reliability are inter-related in complex ways. Thus, solving the transmission investment problem is more complex than “fixing” merchant transmission; investment in the grid must be treated as a systems problem. [Copyright &y& Elsevier]

Restructuring efforts in the U.S. electric power sector have tried to encourage transmission investment by independent (non-utility) transmission companies, and have promoted various levels of market-based transmission investment. Underlying this shift to "merchant" transmission investment is an assumption that new transmission infrastructure can be classified as providing a congestion-relief benefit or a reliability benefit. In this paper, we demonstrate that this assumption is largely incorrect for meshed interconnections such as electric power networks. We focus on a particular network topology known as the Wheatstone network to show how congestion and reliability can represent tradeoffs. Lines that cause congestion may be justified on reliability grounds. We decompose the congestion and reliability effects of a given network alteration, and demonstrate their dependence through simulations on a 118- bus test network. The true relationship between congestion and reliability depends critically on identifying the relevant range of demand for evaluating any network externalities. [ABSTRACT FROM AUTHOR]

Blind faith is unlikely to produce a free market that is competitive. Substituting markets for traditional regulation is only one choice among many policy instruments to achieve a goal of lower prices; such substitution should not be in itself a goal. [Copyright &y& Elsevier]

An analysis of three recently deregulated markets—California, PJM, and New York—finds that none of them can be regarded as highly competitive, contrary to what conventional measures of market power indicate. Auctions for generation are unlikely to be competitive and costly steps will be needed to mitigate market power, likely eroding any benefits from increased operating efficiency in deregulated markets. Thus, FERC and state legislators need to reexamine the desirability of deregulating the generation portion of the industry. [Copyright &y& Elsevier]

This special issue of Environmental Engineering Science highlights the role of environmental engineering and science (EES) in interdisciplinary efforts to understand and protect food security, water resources, and sustainable energy. It includes articles that present model frameworks, theoretical constructs, as well as practical applications. Case studies provide a global perspective, as well as drawing attention to considerations of racial and ethnic inequalities, human health, and multiscale governance. As the EES community evaluates research efforts for 21st century challenges, food, energy, and water nexus research can provide interdisciplinary ideas for improving natural resource provisioning across the water, food, and energy spectrum. [ABSTRACT FROM AUTHOR]

• We investigated the uncertainty of CO 2 sequestration in depleted Shale-gas. • We solved the profit-maximization for different methane and CO 2 price levels. • We found CO 2 and CH 4 price pairs with equivalent injection or production profit. • As CO 2 price increases, option value and likelihood to delay injection decreases. • As the discount rate grows, value of the option drops. Depleted shale gas reservoirs may be candidates for conversion to injection wells for the long-term geologic storage of CO 2 , but the decision to transition from production to injection depends on economic and policy factors that may be uncertain. This paper aims to comprehend the uncertainty inherent to the underlying assumptions of CO 2 sequestration and their impact on the injection decision. We view and analyze the production to injection transition decision as a kind of options problem, where the owner of a producing well can choose to exercise the option to stop producing natural gas and start injecting CO 2. Our approach integrates a detailed reservoir model for shale-gas production and CO 2 injection in the Marcellus shale formation with a multi-period decision problem under uncertainty in future prices for CO 2 and produced natural gas. With no uncertainty, the modeling framework is able to identify the optimal timing of the transition to CO 2 injection as a function of natural gas prices and a hypothetical CO 2 price. We find that a CO 2 price of approximately $15 per tonne to be needed in order to incentivize a producer to transition to CO 2 injection earlier. If these prices are uncertain, we find that the option to delay CO 2 injection has value even when CO 2 prices are relatively high and natural gas prices are low, although the option value is highly sensitive to the choice of discount rate and the option value to delay injection is generally very low when CO 2 prices are $20/tonne or higher. Our modeling suggests that commitment in carbon pricing regimes is of equal importance to the choice of the price level. [ABSTRACT FROM AUTHOR]

Abstract: Switching from liquid fuels to electricity in the transportation and heating sectors can result in greenhouse gas emissions reductions. These reductions are maximized when electricity-sector carbon emissions are constrained through policy measures. We use a linear optimization, generation expansion/dispatch model to evaluate the impact of increased electricity demand for plug-in electric vehicle charging on the generating portfolio, overall generating fuel mix, and the costs of electricity generation. We apply this model to the PJM Interconnect and ISO-New England Regional Transmission Organization service areas assuming a CO2 pricing scheme that is applied to the electricity sector but does not directly regulate emissions from other sectors. We find that a shift from coal toward natural gas and wind generation is sufficient to achieve a 50% reduction in electricity-sector CO2 emissions while supporting vehicle charging for 25% of the vehicle fleet. The price impacts of these shifts are sensitive to demand side price responsiveness and the capital costs of new wind construction. [Copyright &y& Elsevier]

In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss, and blackout sizes. The first two are purely topological metrics. The blackout size calculation results from a model of cascading failure in power networks. Testing the response of 40 areas within the Eastern U.S. power grid and a standard IEEE test case to a variety of attack/failure vectors indicates that directed attacks result in larger failures using all three vulnerability measures, but the attack-vectors that appear to cause the most damage depend on the measure chosen. While the topological metrics and the power grid model show some similar trends, the vulnerability metrics for individual simulations show only a mild correlation. We conclude that evaluating vulnerability in power networks using purely topological metrics can be misleading. [ABSTRACT FROM AUTHOR]

The authors reject calls for reregulation. An alternative is to solicit offers for long-term contracts that specify fixed and generating prices for each plant. The contracts would specify the number of times a generator could be asked to shut down, as well as the availability and reliability of the unit. Units whose offers are accepted would be paid their fixed offer if they complied with the terms of the contract and their generation offer for each MWh they were asked to supply. [Copyright &y& Elsevier]

Electricity market restructuring is widely seen as having failed. Many of the same groups that pressed for deregulation now find themselves seeking reregulation. But reregulation will reintroduce the flaws and problems that led people to seek deregulation. Further, reregulation will introduce the additional problem of how to value competitive market assets for inclusion in the regulated rate base. [Copyright &y& Elsevier]

Proponents of free markets for electricity assert that minor fixes to the California market and to FERC''s proposed Standard Market Design would generate lower prices. We disagree. Designing a competitive market that remedies the problems seen in California and other restructured markets is difficult; emulating even good ISOs like PJM will not do the job. Each one of the problems can be overcome, but the costs of doing so might make full deregulation unattractive. [Copyright &y& Elsevier]

• Gas shortages at New England generators have accounted for up to ¼ of all failures. • A $3−7/MWh premium could mitigate ∼2 GW of gas shortages using oil dual fuel. • A $7−16/MWh premium could mitigate ∼2 GW of gas shortages using CNG storage. • Battery costs must decrease by 75 % to be competitive with fuel storage for mitigating gas shortages. In the Northeastern United States, natural gas supply constraints have led to periods when gas shortages have caused up to a quarter of all unscheduled power plant outages. Dual fuel oil/gas generators or local gas storage might mitigate gas supply shortages. We use historical power plant operational and availability data to develop a supply curve of the costs required for generators to mitigate fuel shortage failures in New England. Based on 2012–2018 data, we find that the historical fuel shortages at approximately 2 GW worth of gas-fired capacity could be mitigated using on-site fuel storage. For comparison, New England's average reserve margin was 1.7–2.8 GW over our sample period. Oil dual fuel plants would recoup their investment if compensated with a reliability adder of $3−7/MWh during their normal operations, while $7−16/MWh would incentivize using on-site, compressed natural gas storage. We estimate that the capital expenses associated with the fuel storage options would be less expensive than installing battery backup for resource adequacy at current battery prices. [ABSTRACT FROM AUTHOR]

To find a sustainable way of supplying food, energy, and water (FEW) while simultaneously protecting the ecosystem services, it is imperative to build greater understanding on interconnections, feedback, and dependencies in FEW systems. The FEW nexus has developed as a field of study to provide frameworks for such pursuits. Building upon previous work in this paper, we analyze FEW resources through the development of a virtual water trade network using the US network of food and energy flows and their associated virtual water contents. Our main objective is to provide a quantitative estimation of the virtual water embodied in the internal US food and energy transfers and analyze the associated interdependencies of these connections. Three methodological advancements demonstrate the novelty of this work. First, unlike existing FEW virtual water modeling studies, our work separates corn into both food and energy resources accounting for the significant use of corn for ethanol in the United States. Second, we apply recently published water consumption values for energy commodities confirming the variation between previous water footprint studies and these more accurate accounting procedures. Third, we examine network properties of the trade flows furthering FEW nexus literature and showcasing avenues for future research. Our results indicate that accounting for the transfer of corn from the food commodity network to the energy commodity network leads to a virtual water footprint decline of 11% for the cereal grain virtual water network. Additionally, the food trade network shows highly dense and connected properties compared to the energy trade network. Finally, our results indicate that transfers of water footprints between water scarce and water abundant states differ substantially between food and energy virtual water networks. A quantifiable understanding of the water footprint network embodied in the food and energy trade can help in developing policies for promoting conservation and efficiency in the context of the FEW nexus. Unlabelled Image • A method to assess the network structure of embedded water for food and energy is proposed. • We separate corn into both food and energy resources accounting for the significant use of corn for ethanol. • Separating corn leads to a virtual water footprint decline of 11% for the cereal grain virtual water network. • The food network shows highly dense and connected properties compared to the energy network. • This method can be used to assess multiple sustainability priorities simultaneously. [ABSTRACT FROM AUTHOR]

A firm's patent strategy is commonly focused on excluding competition in the domestic market. Foreign patent rights may be sought, but the presumption is that they are valuable for a firm only if it has access to a foreign market through sales, licensing or foreign direct investment. However, in countries that are major manufacturing bases and international exporters, like China and India, a new strategy may be emerging: seeking patents solely to impact competition in external markets. This Article describes this novel use of "global patent chokepoints" and presents empirical evidence that it is actually occurring. It considers patent filings in solar photovoltaics (PV) in China between 2002 and 2007 and demonstrates that the patent filings are responsive to increases in solar PV production by Chinese rivals but not Chinese domestic installation. If this strategy is more widely adopted, pricing and access impacts for important health and sustainability technologies may result. [ABSTRACT FROM AUTHOR]

Electrical generation units (EGUs) are important sources of nitrogen oxides (NOx) that contribute to ozone air pollution. A dynamic management system can anticipate high ozone and dispatch EGU generation on a daily basis to attempt to avoid violations, temporarily scaling back or shutting down EGUs that most influence the high ozone while compensating for that generation elsewhere. Here we investigate the contributions of NOxfrom individual EGUs to high daily ozone, with the goal of informing the design of a dynamic management system. In particular, we illustrate the use of three sensitivity techniques in air quality models—brute force, decoupled direct method (DDM), and higher-order DDM—to quantify the sensitivity of high ozone to NOxemissions from 80 individual EGUs. We model two episodes with high ozone in the region around Pittsburgh, PA, on August 4 and 13, 2005, showing that the contribution of 80 EGUs to 8-hr daily maximum ozone ranges from 1 to >5 ppb at particular locations. At these locations and on the two high ozone days, shutting down power plants roughly 1.5 days before the 8-hr ozone violation causes greater ozone reductions than 1 full day before; however, the benefits of shutting down roughly 2 days before the high ozone are modest compared with 1.5 days. Using DDM, we find that six EGUs are responsible for >65% of the total EGU ozone contribution at locations of interest; in some locations, a single EGU is responsible for most of the contribution. Considering ozone sensitivities for all 80 EGUs, DDM performs well compared with a brute-force simulation with a small normalized mean bias (–0.20), while this bias is reduced when using the higher-order DDM (–0.10). Implications: Dynamic management of electrical generation has the potential to meet daily ozone air quality standards at low cost. We show that dynamic management can be effective at reducing ozone, as EGU contributions are important and as the number of EGUs that contribute to high ozone in a given location is small (<6). For two high ozone days and seven geographic regions, EGUs would best be shut down or their production scaled back roughly 1.5 days before the forecasted exceedance. Including online sensitivity techniques in an air quality forecasting model can provide timely and useful information on which EGUs would be most beneficial to shut down or scale back temporarily. [ABSTRACT FROM PUBLISHER]

Costs and environmental concerns associated with fossil fuels have encouraged researchers and eco-friendly organizations to seek an alternative energy source that can help satisfy this rising energy demand in an environmentally friendly and sustainable manner. The proposed work is driven by the need to harness the potential of a clean (nuclear) and inexhaustible renewable energy source, with enhanced reliability and resilience. [ABSTRACT FROM AUTHOR]

Identifying coherent sub-graphs in networks is important in many applications. In power systems, large systems are divided into areas and zones to aid in planning and control applications. But not every partitioning is equally good for all applications; different applications have different goals, or attributes, against which solutions should be evaluated. This paper presents a hybrid method that combines a conventional graph partitioning algorithm with an evolutionary algorithm to partition a power network to optimize a multi-attribute objective function based on electrical distances, cluster sizes, the number of clusters, and cluster connectedness. Results for the IEEE RTS-96 show that clusters produced by this method can be used to identify buses with dynamically coherent voltage angles, without the need for dynamic simulation. Application of the method to the IEEE 118-bus and a 2383-bus case indicates that when a network is well partitioned into zones, intra-zone transactions have less impact on power flows outside of the zone; i.e., good partitioning reduces loop flows. This property is particularly useful for power system applications where ensuring deliverability is important, such as transmission planning or determination of synchronous reserve zones. [ABSTRACT FROM PUBLISHER]

The flow regime of rivers is a complex but important measure of environmental quality and one that can be significantly impacted by conventional hydropower generation. While traditional hydropower scheduling creates a periodicity in downstream flows corresponding to seasonal and daily electricity demand patterns, deregulated electricity markets may provide financial incentives to further alter flows, as utilities respond to hourly market dynamics. This study investigates the potential for deregulated markets to impact both a hydropower utility's revenue stream and downstream flow regimes. Six operating scenarios are explored: (1-2) full-market participation (including real-time energy), with and without flow reregulation; (3) day-ahead market only; and (4-6) run-of-river operations (ROR), with and without flood control and flow reregulation. Results suggest that, relative to a day-ahead-only scenario, the scale of any differences in flow regime resulting from full-market participation is relatively small compared to the additional revenue-generating potential of such a strategy. Implementing a run-of-river policy frequently yields "more natural" flow regimes than the day-ahead only scenario; but, in some cases these improvements are modest, and in others the ROR scenarios exacerbate deviation from unregulated flows. Regardless, the effects of implementing an ROR strategy come at a substantial cost in terms of foregone hydropower revenue. [ABSTRACT FROM AUTHOR]

Geologic carbon sequestration represents a promising option for carbon mitigation. Injected CO2, however, can potentially leak into water systems, increase water acidity, and mobilize metals. This study used column experiments to quantify the effects of environmental controls on cadmium desorption during CO2 leakage in subsurface systems without ambient flow. Results show that fast leakage rates are responsible for earlier and larger amounts of Cd desorption. Long weathering time of Cd laden clay leads to low Cd desorption. Calcite content as low as 10% can mitigate the effect of pH reduction and result in zero Cd desorption. Increasing the salinity of the leaking fluid has a relatively minor effect, primarily due to the offsetting impacts of an increased extent of ion exchange and the decrease in CO2 solubility (and therefore acidity). This work systematically quantifies, for the first time, the effects of environmental controls on Cd desorption and points to key parameters for risk assessment associated with metal mobilization during CO2 leakage. [ABSTRACT FROM AUTHOR]