Transition to Low-Carbon Electric Power: Portfolios, Flexibility, and Option Value.

With the increased focus on responding to climate change by accelerating a transition to a low-carbon energy system, differing views remain on the combination of energy technologies that will best achieve this goal. Identifying technological pathways is complicated by wide uncertainties in economic and technological factors. Analyses that neglect these uncertainties can produce pathways for a low-carbon energy future that are highly granular and specific, but which are based on a particular assumption about future conditions and imply a need to make specific technology commitments over a long period of time. We frame the energy transition problem as the identification of one near-term investment strategy that is flexible across a wide range of possible future costs, followed by many alternative subsequent investment plans, each of which responds to realized future costs to achieve an aggressive emissions reduction target. Using an example of planning a low-carbon power system under uncertainty, we demonstrate the option value of not ruling out some energy technologies in the near term.

Emissions and Health Implications of Pennsylvania's Entry into the Regional Greenhouse Gas Initiative.

The Regional Greenhouse Gas Initiative (RGGI) is a cap-and-trade system targeting CO2 emissions from the electricity sector in the northeastern United States. As a major power producer and carbon emitter, Pennsylvania plans to join RGGI in 2022, which will affect both the carbon market (i.e., RGGI) and the regional electricity market (i.e., PJM). Combining a PJM power system model with a reduced-form model of CO2 emissions abatement from RGGI states that are not in PJM, we find the annual average emissions from power plants in Pennsylvania can be reduced by 40%, 79%, 68%, and 76% for CO2, SO2, NOx, and PM2.5, respectively, during 2022-2030. Then, based on a range of source-specific marginal damage estimates, we find the cumulative monetized health cobenefits to be 17.7 to 40.8 billion USD. However, the reduced emissions and health damages in Pennsylvania are slightly offset by increases in the other states in PJM that do not participate in RGGI. Our study hence highlights the potential cross-state leakage issue that warrants careful consideration in the policy design and implementation process.

Modeled response of ozone to electricity generation emissions in the northeastern United States using three sensitivity techniques.

UNLABELLED: 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 NOx from 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 NOx emissions 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.

Environmental controls of cadmium desorption during CO2 leakage.

Geologic carbon sequestration represents a promising option for carbon mitigation. Injected CO(2), 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 CO(2) 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 CO(2) 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 CO(2) leakage.

Do topological models provide good information about electricity infrastructure vulnerability?

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.

Integrating embedded resources and network analysis to understand food-energy-water nexus in the US.

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.

Short run effects of a price on carbon dioxide emissions from U.S. electric generators.

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 workto stimulate investment in new generation technology also provides significant CO2 reductions before new technology is deployed at large scale.