Climate change threatens all parts of the US electric power system, from electricity generation to distribution. An important dimension of this issue is the impact on electricity demand. While many ...studies have looked at these impacts, few have tried to represent this effect at higher temporal resolutions (such as daily or sub-daily) or to analyze its seasonal aspects. Our study expands on previous work to improve our understanding of how climate change can affect patterns of hourly electricity demand, the differences in these effects over different seasons, and how this in turn could affect the operations of the power system. For this analysis, we combine a linear regression model, a simplified economic dispatch model, and projections from twenty different climate models to analyze how climate change may affect seasonal demand patterns and, consequently, power plants dispatch. We use this method to analyze a case study of the Tennessee Valley Authority (TVA). The results suggest that climate change can result in an average increase in annual electricity consumption in the TVA region of 6% by the end of the century and an increase in the frequency of peak demand values (the maximum quantity of electricity demanded during an hour). However, this increase is not uniformly distributed throughout the year. During summer, total electricity consumption can increase on average by 20% while during winter, it may decrease on average by 6% by the end of the century. Such changes in demand could result in changes in the typical dispatch patterns of TVA’s power plants. Estimated summer time capacity factors would increase (8 to 37% for natural gas and 71 to 84% for coal) and winter time capacity factor decrease (3% to virtually zero for natural gas and 67 to 60% for coal). Such results could affect the decision-making process of planning agents in the power sector.
A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National ...Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060–15065 argue that it is feasible to provide “low-cost solutions to the grid reliability problem with 100% penetration of WWS wind, water and solar power across all energy sectors in the continental United States between 2050 and 2055”, with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.
Increasing concerns about greenhouse gas (GHG) emissions in the United States have spurred interest in alternate low carbon fuel sources, such as natural gas. Life cycle assessment (LCA) methods can ...be used to estimate potential emissions reductions through the use of such fuels. Some recent policies have used the results of LCAs to encourage the use of low carbon fuels to meet future energy demands in the U.S., without, however, acknowledging and addressing the uncertainty and variability prevalent in LCA. Natural gas is a particularly interesting fuel since it can be used to meet various energy demands, for example, as a transportation fuel or in power generation. Estimating the magnitudes and likelihoods of achieving emissions reductions from competing end-uses of natural gas using LCA offers one way to examine optimal strategies of natural gas resource allocation, given that its availability is likely to be limited in the future. In this study, the uncertainty in life cycle GHG emissions of natural gas (domestic and imported) consumed in the U.S. was estimated using probabilistic modeling methods. Monte Carlo simulations are performed to obtain sample distributions representing life cycle GHG emissions from the use of 1 MJ of domestic natural gas and imported LNG. Life cycle GHG emissions per energy unit of average natural gas consumed in the U.S were found to range between −8 and 9% of the mean value of 66 g CO2e/MJ. The probabilities of achieving emissions reductions by using natural gas for transportation and power generation, as a substitute for incumbent fuels such as gasoline, diesel, and coal were estimated. The use of natural gas for power generation instead of coal was found to have the highest and most likely emissions reductions (almost a 100% probability of achieving reductions of 60 g CO2e/MJ of natural gas used), while there is a 10–35% probability of the emissions from natural gas being higher than the incumbent if it were used as a transportation fuel. This likelihood of an increase in GHG emissions is indicative of the potential failure of a climate policy targeting reductions in GHG emissions.
•Flexible CCS increases profitability by 0–35% depending on CO2 prices.•Regenerator undersizing increases the value of flexible CCS.•Value of flexible CCS decreases with CO2 prices.•Flexible CCS is ...not desired when overall plant is profitable.•The value of perfect information does not exceed 10%.
We performed a study to determine whether flue gas bypass and solvent storage can increase the profitability of a power plant equipped with post-combustion carbon capture technology. By increasing flexibility, these technologies allow increased output when electric energy prices are high. We used the Integrated Environmental Control Model to characterize cost and operational parameters of a pulverized coal (PC) plant with both amine and ammonia carbon-capture systems, as well as a natural gas combined cycle plant with amine capture. We constructed profit-maximization operating models with both perfect and imperfect information about electric energy prices in a large electricity market in the Eastern United States. We optimized the size of the regenerator and solvent storage vessels to maximize profitability. Results indicate that the profitability benefits of flexible CCS range from 0 to 35%. Most of the potential benefit is capital savings from allowing the regenerator to be undersized. The benefits of flexible CCS were found to decline with increasing CO2 prices, with steady-state units preferable above a CO2 emissions price of $40/tonne. Flexible CCS was never optimal when the overall plant was profitable. While flexible CCS can boost profitability under policies that force plants with CCS to be built even where they are not profitable, it is less relevant under market-based policies that incentivize CCS through CO2 prices.
Hydropower may be a low-carbon option to increase power generation in developing countries, but these countries are some of the most vulnerable to climate change. Climate change can affect hydropower ...generation through changes in the timing and magnitude of precipitation, rising temperatures, and glacier mass changes. Evaluating climate impacts on hydropower generally requires detailed local input data and hydrological models, which may not be available in many developing nations. Nevertheless, the need to understand the impacts is essential for the developing world. Here we present a modeling framework that relies on remotely sensed and global gridded datasets forced by an ensemble of 21 general circulation models (GCMs) under two representative concentration pathways (RCPs) to evaluate climate-induced impacts on hydropower through the 21st century. We include 134 hydropower plants (>100 MW), representing 42% of hydropower installed capacity in South America, across five regions of Brazil, Colombia, and Peru. Our results suggest the median monthly usable capacity would increase for Colombia (+2.6% to +8.4% for RCP 4.5 and 8.5, respectively) and Peru (+6.7% to +9.3% for RCP 4.5 and 8.5, respectively) by 2100 relative to the late 20th century. For Brazil, we observe a mix of reductions and increases in usable capacity. While our results suggest potential reductions for the dry season usable capacity in the Parana, Paraguay, and Southeast Atlantic regions of Brazil, we also observe slight increases in usable capacity during the rainy months for all its regions. These results can help inform future planning decisions and potential interconnections between the three countries. Additionally, the proposed framework can contribute to an increased capability to evaluate climate-induced risks to power systems in developing countries, where data and computation resources can be limited.
Wind integration studies are an important tool for understanding the effects of increasing wind power deployment on grid reliability and system costs. This paper provides a detailed review of the ...statistical methods and results from 12 large-scale regional wind integration studies. In particular, we focus our review on the modeling methods and conclusions associated with estimating short-term balancing reserves (regulation and load-following). Several important observations proceed from this review. First, we found that many of the studies either explicitly or implicitly assume that wind power step-change data follow exponential probability distributions, such as the Gaussian distribution. To understand the importance of this issue we compared empirical wind power data to Gaussian data. The results illustrate that the Gaussian assumption significantly underestimates the frequency of very large changes in wind power, and thus may lead to an underestimation of undesirable reliability effects and of operating costs. Secondly, most of these studies make extensive use of wind speed data generated from mesoscale numerical weather prediction (NWP) models. We compared the wind speed data from NWP models with empirical data and found that the NWP data have substantially less power spectral energy, a measure of variability, at higher frequencies relative to the empirical wind data. To the extent that this difference results in reduced high-frequency variability in the simulated wind power plants, studies using this approach could underestimate the need for fast ramping balancing resources. On the other hand, the magnitude of this potential underestimation is uncertain, largely because the methods used for estimating balancing reserve requirements depend on a number of heuristics, several of which are discussed in this review. Finally, we compared the power systems modeling methods used in the studies and suggest potential areas where research and development can reduce uncertainty in future wind integration studies.
Summary
In the ongoing debate about the climate benefits of fuel switching from coal to natural gas for power generation, the metrics used to model climate impacts may be important. In this article, ...we evaluate the life cycle greenhouse gas emissions of coal and natural gas used in new, advanced power plants using a broad set of available climate metrics in order to test for the robustness of results. Climate metrics included in the article are global warming potential, global temperature change potential, technology warming potential, and cumulative radiative forcing. We also used the Model for the Assessment of Greenhouse‐gas Induced Climate Change (MAGICC) climate‐change model to validate the results. We find that all climate metrics suggest a natural gas combined cycle plant offers life cycle climate benefits over 100 years compared to a pulverized coal plant, even if the life cycle methane leakage rate for natural gas reaches 5%. Over shorter time frames (i.e., 20 years), plants using natural gas with a 4% leakage rate have similar climate impacts as those using coal, but are no worse than coal. If carbon capture and sequestration becomes available for both types of power plants, natural gas still offers climate benefits over coal as long as the life cycle methane leakage rate remains below 2%. These results are consistent across climate metrics and the MAGICC model over a 100‐year time frame. Although it is not clear whether any of these metrics are better than the others, the choice of metric can inform decisions based on different societal values. For example, whereas annual temperature change reported may be a more relevant metric to evaluate the human health effects of increased heat, the cumulative temperature change may be more relevant to evaluate climate impacts, such as sea‐level rise, that will result from the cumulative warming.
This study estimates the life cycle greenhouse gas (GHG) emissions from the production of Marcellus shale natural gas and compares its emissions with national average US natural gas emissions ...produced in the year 2008, prior to any significant Marcellus shale development. We estimate that the development and completion of a typical Marcellus shale well results in roughly 5500 t of carbon dioxide equivalent emissions or about 1.8 g CO sub(2)e/MJ of gas produced, assuming conservative estimates of the production lifetime of a typical well. This represents an 11% increase in GHG emissions relative to average domestic gas (excluding combustion) and a 3% increase relative to the life cycle emissions when combustion is included. The life cycle GHG emissions of Marcellus shale natural gas are estimated to be 63-75 g CO sub(2)e/MJ of gas produced with an average of 68 g CO sub(2)e/MJ of gas produced. Marcellus shale natural gas GHG emissions are comparable to those of imported liquefied natural gas. Natural gas from the Marcellus shale has generally lower life cycle GHG emissions than coal for production of electricity in the absence of any effective carbon capture and storage processes, by 20-50% depending upon plant efficiencies and natural gas emissions variability. There is significant uncertainty in our Marcellus shale GHG emission estimates due to eventual production volumes and variability in flaring, construction and transportation.
The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On ...the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.
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