Individual Power Plants Research Articles

Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions.

Expanded use of reduced complexity approaches in epidemiology and environmental justice investigations motivates detailed evaluation of these modeling approaches. Chemical transport models (CTMs) remain the most complete representation of atmospheric processes but remain limited in applications that require large numbers of runs, such as those that evaluate individual impacts from large numbers of sources. This limitation motivates comparisons between modern CTM-derived techniques and intentionally simpler alternatives. We model population weighted PM2.5 source impacts from each of greater than 1,100 coal power plants operating in the United States in 2006 and 2011 using three approaches: 1) adjoint PM2.5 sensitivities calculated by the GEOS-Chem CTM; 2) a wind field-based Lagrangian model called HyADS; and 3) a simple calculation based on emissions and inverse source-receptor distance. Annual individual power plants’ nationwide population weighted PM2.5 source impacts calculated by HyADS and the inverse distance approach have normalized mean errors between 20% and 28% and root mean square error ranges between 0.0003 and 0.0005 μg m−3 compared to adjoint sensitivities. Reduced complexity approaches are most similar to the GEOS-Chem adjoint sensitivities nearby and downwind of sources, with degrading performance farther from and upwind of sources particularly when wind fields are not accounted for.

Design of Standalone Solar Power Plantusing System Advisor Model in Indian Context

The design parameters of standalone solar power plant should be analysed for feasible power generation and utilization at any site under consideration. Solar-powered photovoltaic system provides anunpolluted energy solution to current global warming. The solar input parameters and weather data are important to configure the desired power output. A simulation is necessary for the system which provides information on input data, loss under consideration, system efficiencies and gross energy yield. Standalone system is suited for small power generation setup which is not connected to grid. India being a tropical country with major sunny days throughout the year individual power plant setup helps consumers to depend less on government supplied power. Installation at site, system degradation and life time reliability analysis is crucial for long term power optimization.Virtual simulations have been carried out on PV systems for Bangalore station using system advisor model. This paper considers various design parameters to be considered before setting up a standalone system.

Fine-Scale Analysis of the Energy-Land-Water Nexus: Nitrate Leaching Implications of Biomass Cofiring in the Midwestern United States.

As scientists seek to better understand the linkages between energy, water, and land systems, they confront a critical question of scale for their analysis. Many studies exploring this nexus restrict themselves to a small area in order to capture fine-scale processes, whereas other studies focus on interactions between energy, water, and land over broader domains but apply coarse resolution methods. Detailed studies of a narrow domain can be misleading if the policy intervention considered is broad-based and has impacts on energy, land, and agricultural markets. Regional studies with aggregate low-resolution representations may miss critical feedbacks driven by the dynamic interactions between subsystems. This study applies a novel, gridded energy-land-water modeling system to analyze the local environmental impacts of biomass cofiring of coal power plants across the upper MISO region. We use this framework to examine the impacts of a hypothetical biomass cofiring technology mandate of coal-fired power plants using corn residues. We find that this scenario has a significant impact on land allocation, fertilizer applications, and nitrogen leaching. The effects also impact regions not involved in cofiring through agricultural markets. Further, some MISO coal-fired plants would cease generation because the competition for biomass increases the cost of this feedstock and because the higher operating costs of cofiring renders them uncompetitive with other generation sources. These factors are not captured by analyses undertaken at the level of an individual power plant. We also show that a region-wide analysis of this cofiring mandate would have registered only a modest increase in nitrate leaching (just +5% across the upper MISO region). Such aggregate analyses would have obscured the extremely large increases in leaching at particular locations, as much as +60%. Many of these locations are already pollution hotspots. Fine-scale analysis, nested within a broader framework, is necessary to capture these critical environmental interactions within the energy, land, and water nexus.

Вдосконалення способів виконання захистів ліній зв’язку з підстанціями розосереджених джерел генерації

The article deals with the problems of using relay protection of power lines. Attention is paid to the peculiarities of the operation of protection under different modes of operation of these lines, namely: normal, post-accident and scheduled repair. The protection of two-sided power lines that connect individual local power plants to powerful electrical systems, including dispersed generation sources, local systems, and dispersed generation sources, must meet the general requirements of providing the required sensitivity, selectivity for various types of damage. Difficulties in providing the required sensitivity when using maximum current protections on such lines are associated with low levels of short-circuit currents from dispersed generation sources and local electrical systems. The features of the relay protection performance in redundant power supply of consumers using dispersed generation sources are given. The maximum operating current of the line consumed from the electrical system is 2 - 3 times the rated current, which is determined by the power of the generators of the dispersed sources of generation. In this case, the short-circuit currents from the low-power generators of the dispersed sources of generation are proportional to the maximum operating currents of the line. On double-sided power lines that connect local systems and dispersed power sources to a high-power electrical system, maximum current directional protection provides selectivity and are the main types of protection for such lines. Key words: power supply, relay protection, reclosers, sectionalizers, distributed sources of generation, short circuit, sectioning, selectivity

Impacts of transboundary coal air pollution from Balkan region to European public health

Abstract Background Western Balkan region holds coal power plants that are old, inefficient and substandard. In 2016, the region’s 16 plants emitted more SO2 than the entire 250 European coal power plants. In this study we modelled the transboundary nature of air pollution affecting this region and EU. Methods We calculated health impacts and costs from Western Balkan coal plants by the following steps: (1) Identify coal power plants in the Western Balkans in 2016; (2) Source 2016 coal power plant emissions data; (3) Model the pollutant exposure resulting from the emissions from Western Balkan coal power plants; (4) Calculate health impacts associated with modelled pollutant exposures; (5) Attribute the health impacts to individual coal power plants; (6) Calculate the cost of the health impacts. Results The modeling shows that every year Western Balkans’ plants cause 3,000 premature deaths, 8,000 cases of bronchitis in children, and other chronic illnesses costing both health systems and economies a total of € 6.1-11.5 billion. The EU bears the majority of health cost, more than half of these health costs relate to the EU (€ 3.1 to 5.8 billion), a third (32%) to Western Balkan countries (€ 1.9 to 3.6 billion) and around 17% in other countries. Moreover, Bulgaria and Croatia’s health budgets are the most heavily impacted. Costs needed to cover the health impacts of Western Balkan coal pollution amount to € 0.3-0.7 billion. For Bulgaria this is the same as 10%-18% of the country’s total health expenditure in 2016. For Croatia (costs of € 0.2-0.4 billion), it amounts to 8%-14% of total health expenditure in 2016. Discussion These results imply an coal phase out to protect public health. Strong enforcement of the existing pollution control measures are needed. Political processes such as EU accession of Balkan countries may be a door to prioritise pollution control and air quality, in particular by excluding companies planning new coal power capacity from EU financing.

Quantifying the System-Level Resilience of Thermal Power Generation to Extreme Temperatures and Water Scarcity

Severe weather events, such as extreme temperatures and water scarcity, can have significant impacts on the operation of critical electrical power infrastructure and, consequently, pose major threats to its resilience. Differently from existing studies that focus on the impact of extreme weather on individual power plants, this article quantifies the resilience of thermal power generation to extreme temperatures and the different levels of water availability from a system-level perspective. This article starts by introducing the fundamental engineering models of thermal power plants’ cooling systems. A system-level quantification methodology is then proposed, which also introduces a multicoordinate resilience-oriented metric that assesses system vulnerability through the concepts of conditional value-at-risk and its rate of change in response to changes in the considered weather conditions. The numerical results obtained using a simplified version of the British transmission system not only demonstrate that the proposed framework is well suited to quantify the system-level resilience of the test system to extreme temperatures and different levels of water availability and scarcity but also highlight the benefits of using the newly defined resilience metric in such studies.

Estimating power plant CO2 emission using OCO-2 XCO2 and high resolution WRF-Chem simulations

Anthropogenic CO2 emission from fossil fuel combustion has major impacts on the global climate. The Orbiting Carbon Observatory 2 (OCO-2) observations have previously been used to estimate individual power plant emissions with a Gaussian plume model assuming constant wind fields. The present work assesses the feasibility of estimating power plant CO2 emission using high resolution chemistry transport model simulations with OCO-2 observation data. In the new framework, 1.33 km Weather Research and Forecasting-Chem (WRF)-Chem simulation results are used to calculate the Jacobian matrix, which is then used with the OCO-2 XCO2 data to obtain power plant daily mean emission rates, through a maximum likelihood estimation. We applied the framework to the seven OCO-2 observations of near mid-to-large coal burning power plants identified in Nassar et al (2017 Geophys. Res. Lett. 44, 10045–53). Our estimation results closely match the reported emission rates at the Westar power plant (Kansas, USA), with a reported value of 26.67 ktCO2/day, and our estimated value at 25.82–26.47 ktCO2/day using OCO-2 v8 data, and 22.09–22.80 ktCO2/day using v9 data. At Ghent, KY, USA, our estimations using three versions (v7, v8, and v9) range from 9.84–20.40 ktCO2/day, which are substantially lower than the reported value (29.17 ktCO2/day). We attribute this difference to diminished WRF-Chem wind field simulation accuracy. The results from the seven cases indicate that accurate estimation requires accurate meteorological simulations and high quality XCO2 data. In addition, the strength and orientation (relative to the OCO-2 ground track) of the XCO2 enhancement are important for accurate and reliable estimation. Compared with the Gaussian plume model based approach, the high resolution WRF-Chem simulation based approach provides a framework for addressing varying wind fields, and possible expansion to city level emission estimation.

Modeling Emissions and Ozone Air Quality Impacts of Future Scenarios for Energy and Power Production in the Rocky Mountain States.

This study examines air quality impacts of scenarios for energy production and use in 2030 across Colorado, northern New Mexico, Utah, and Wyoming. Scenarios feature contrasting levels of oil and gas production and shares of electricity from coal, natural gas, and renewables. Hourly emissions are resolved for individual power plants; oil and gas emissions are basin-specific. Ozone decreased from 2011 to the 2030 baseline, with median and 90th percentile reductions in maximum daily 8 h average (MDA8) ozone across the four-state domain of 3.5 and 7.1 ppb, respectively, resulting in 200 fewer premature deaths annually. Relative to the 2030 baseline, MDA8 ozone increased in the "cheap gas" scenario, with median and 90th percentile increases of 0.1 and 1.0 ppb, and declined in a scenario with greenhouse gas (GHG) emissions fees, with median and 90th percentile reductions of 0.2 and 1.5 ppb. Reduced coal generation lowered SO2 emissions in all future scenarios compared to 2011. GHG emissions from electricity and oil and gas production declined by 4% (CO2-equivalent) from 2011 to the 2030 baseline, increased by 10% from the 2030 baseline to the cheap gas scenario, and declined by 28% from the 2030 baseline to the GHG fees scenario.

Systematic error and uncertain carbon dioxide emissions from U.S. power plants

ABSTRACTCarbon dioxide (CO2) emissions from U.S. power plants are independently reported by the U.S. Energy Information Administration (EIA) and the Clean Air Markets Division (CAMD) within the U.S. Environmental Protection Agency (EPA). Differences between the CAMD and EIA emission tallies show that the amount of CO2 produced by an individual power plant is less certain than might be imagined or desired. These differences are attributed to systematic error and random measurement error. Random error cannot be retroactively corrected, whereas systematic error can be corrected where relevant data are available. Accordingly, this study identified and, where possible, corrected systematic error affecting the CAMD and EIA CO2 emission tallies for 1065 power plants that emitted more than 25,000 tons of CO2 during 2013. The EIA tallies were corrected by accounting for emission factor error, acid-gas sorbent consumption, and combustion of biogenic fuel. The CAMD tallies were likewise corrected by accounting for unreported unit emissions. It was not possible to objectively correct systematic error affecting about 11% of the power plants, and subjective corrections were not attempted. At these plants, the CAMD and EIA emission tallies sometimes differed by more than 20% due to missing unit error, plant identification error, temporal measurement error, or inferred reporting error. Comparisons of the CAMD and EIA emission tallies before and after correction for systematic error show the effectiveness of these corrections. The comparisons also show the persistence of random measurement error.Implications: Understanding the uncertainty of CO2 emission tallies for USA power plants might inform emission inventories, atmospheric flow models or inversions, and emission reduction policies. Knowing the cause and size of measurement errors that contribute to this uncertainty might also help to identify ways to improve the measurement methods and reporting protocols that these CO2 emission tallies are based on.

Implications of Power Plant Idling and Cycling on Water Use Intensity.

Survey data from the Energy Information Administration (EIA) was combined with data from the Environmental Protection Agency (EPA) to explore ways in which operations might impact water use intensity (both withdrawals and consumption) at thermoelectric power plants. Two disparities in cooling and power systems operations were identified that could impact water use intensity: (1) Idling Gap-where cooling systems continue to operate when their boilers and generators are completely idled; and (2) Cycling Gap-where cooling systems operate at full capacity, while their associated boiler and generator systems cycle over a range of loads. Analysis of the EIA and EPA data indicated that cooling systems operated on average 13% more than their corresponding power system (Idling Gap), while power systems operated on average 30% below full load when the boiler was reported as operating (Cycling Gap). Regression analysis was then performed to explore whether the degree of power plant idling/cycling could be related to the physical characteristics of the plant, its environment or time of year. While results suggested that individual power plants' operations were unique, weak trends consistently pointed to a plant's place on the dispatch curve as influencing patterns of cooling system, boiler, and generator operation. This insight better positions us to interpret reported power plant water use data as well as improve future water use projections.

Wind power plant level testing of inertial response with optimised recovery behaviour

This study presents and assesses the outcomes of inertial response tests performed on a transmission system-connected wind power plant in the Canadian province of Quebec. Frequency signals representing a response to a typical loss of generation event were injected into the wind turbines’ control systems to artificially trigger an active power increase. The measurement campaign aimed to fulfil two main objectives. First, to validate the performance of a wind turbine control algorithm designed to optimise the active power behaviour after inertial response activation. Second, to study the correlation between individual wind turbine and wind power plant behaviours during, and immediately after, an inertial response event. This publication offers an update on the capabilities and limitations of type 4 wind turbines for providing inertial response functionalities. Furthermore, it underlines the importance of understanding the various parameters that have an impact on the aggregate inertial response of a wind power plant in reality as well as in dynamic simulations. This publication also addresses how simulations can be used to predict the behaviour of inertial response from wind power plants. Final results suggest that current approaches for integrating and evaluating inertial response from wind power plants in system planning studies should be revisited.

Air quality and health benefits from potential coal power plant closures in Texas

ABSTRACTAs power production from renewable energy and natural gas grows, closures of some coal-fired power plants in Texas become increasingly likely. In this study, the potential effects of such closures on air quality and human health were analyzed by linking a regional photochemical model with a health impacts assessment tool. The impacts varied significantly across 13 of the state’s largest coal-fired power plants, sometimes by more than an order of magnitude, even after normalizing by generation. While some power plants had negligible impacts on concentrations at important monitors, average impacts up to 0.5 parts per billion (ppb) and 0.2 µg/m3 and maximum impacts up to 3.3 ppb and 0.9 µg/m3 were seen for ozone and fine particulate matter (PM2.5), respectively. Individual power plants impacted average visibility by up to 0.25 deciviews in Class I Areas. Health impacts arose mostly from PM2.5 and were an order of magnitude higher for plants that lack scrubbers for SO2. Rankings of health impacts were largely consistent across the base model results and two reduced form models. Carbon dioxide emissions were relatively uniform, ranging from 1.00 to 1.26 short tons/MWh, and can be monetized based on a social cost of carbon. Despite all of these unpaid externalities, estimated direct costs of each power plant exceeded wholesale power prices in 2016.Implications: While their CO2 emission rates are fairly similar, sharply different NOx and SO2 emission rates and spatial factors cause coal-fired power plants to vary by an order of magnitude in their impacts on ozone, particulate matter, and associated health and visibility outcomes. On a monetized basis, the air pollution health impacts often exceed the value of the electricity generated and are of similar magnitude to climate impacts. This suggests that both air pollution and climate should be considered if externalities are used to inform decision making about power-plant dispatch and retirement.

Comparison of small area estimation methods applied to biopower feedstock supply in the Northern U.S. region

Increasing interest in utilization of forest biomass for bioenergy has prompted extensive contemporary research regarding costs, supply and technology for efficiently producing electricity and other forms of renewable energy. One challenge facing both researchers and users is obtaining precise estimates of available forest biomass within plausible supply areas for individual power plants. Due to the wide distribution of power plants poised to co-fire with forest biomass, assessing its availability requires methods that can yield precise and low-bias estimates of aboveground forest biomass and other key attributes at varying spatial scales. Small area estimation (SAE) methods have high potential to accomplish this due to the availability of national forest inventory data, combined with satellite imagery and other forms of remotely-sensed auxiliary information. The study assessed several indirect, direct and composite estimators of four forest attributes: aboveground tree biomass, biomass of small-diameter trees, biomass of tops and limbs, and volume at the county-level and within the estimated supply areas around power plants across 20 states in the contiguous Northern U.S. Composite estimators using both k-nearest neighbors imputation and multiple linear regression provided superior estimates of indicators of forest biomass availability based on both precision and bias at the county-level at sampling intensities as low as 10–20%, compared to the other SAE methods examined. The composite estimator using k-nearest neighbors imputation was subsequently shown to produce precise estimates of forest biomass availability for selected power plant supply areas.

Uncertainty Analysis for the CH4 Emission Factor of Thermal Power Plant by Monte Carlo Simulation

Thermal power plants are a large source of greenhouse gas emissions among energy industry facilities. Emission factors for methane and nitrous oxide depend on combustion technologies and operating conditions and vary significantly with individual thermal power plants. Due to this variability, use of average emission factors for these gases will introduce relatively large uncertainties. This study determined the CH4 emission factors of thermal power plants currently in operation in Korea by conducting field investigations according to fuel type and type of combustion technique. Through use of the Monte Carlo simulation, the uncertainty range for the CH4 emission factor was determined. The estimation showed, at the 95% confidence level, that the uncertainty range for CH4 emission factor from a tangential firing boiler using bituminous coal was −46.6% to +145.2%. The range for the opposed wall-firing boiler was −25.3% to +70.9%. The range for the tangential firing boiler using fuel oil was −39.0% to 93.5%, that from the opposed wall-firing boiler was −47.7% to +201.1%, and that from the internal combustion engine boiler was −38.7% to +106.1%. Finally, the uncertainty range for the CH4 emission factor from the combined cycle boiler using LNG was −90% to +326%.

Finding a criterion for the pressure loss of energy recovery exchangers in HVAC systems from thermodynamic and economic points of view

Heat recovery devices can help ventilation systems conserve energy; However, they cause a pressure drop in the system, and hence the system incurs an electricity consumption. In the present paper, the maximum allowable pressure drop of the recovery units is achieved from thermodynamic and economic points of view. The novelty of the research is that, unlike the existing criterion which does not differ for different cities, the introduced criteria can be calculated for each city with individual weather, economic, power plants, and energy conditions. Although the methods presented to calculate the criteria consider a broad range of effective parameters, there is no need to use complex energy simulation methods. Moreover, for each city, four types of criteria are introduced, which allows the city authorities to choose the best ones according to their city conditions, and then calculate the chosen criteria by the data of the city. In order to gain the criteria, modified enthalpy-hours and bin method variables are introduced to calculate sensible and latent energy consumption due to ventilation. The criteria are numerically calculated for Kerman city in Iran, and the results show that the recovery type and the chosen viewpoint has a considerable effect on the allowable pressure drop. The sensitivity of the results to different variables is analyzed in the end.

Airborne remote sensing and in situ measurements of atmospheric CO<sub>2</sub> to quantify point source emissions

Abstract. Reliable techniques to infer greenhouse gas emission rates from localised sources require accurate measurement and inversion approaches. In this study airborne remote sensing observations of CO2 by the MAMAP instrument and airborne in situ measurements are used to infer emission estimates of carbon dioxide released from a cluster of coal-fired power plants. The study area is complex due to sources being located in close proximity and overlapping associated carbon dioxide plumes. For the analysis of in situ data, a mass balance approach is described and applied, whereas for the remote sensing observations an inverse Gaussian plume model is used in addition to a mass balance technique. A comparison between methods shows that results for all methods agree within 10 % or better with uncertainties of 10 to 30 % for cases in which in situ measurements were made for the complete vertical plume extent. The computed emissions for individual power plants are in agreement with results derived from emission factors and energy production data for the time of the overflight.

A Highly Resolved Mercury Emission Inventory of Chinese Coal-Fired Power Plants.

As the largest coal consumer in China, the coal-fired power plants have come under increasing public concern in regard to atmospheric mercury pollution. This study developed an up-to-date and high-resolution mercury emission inventory of Chinese coal-fired power plants using a unit-based method that combined data from individual power plants, provincial coal characteristics, and industry removal efficiencies. National mercury emissions in 2015 were estimated at 73 tons, including 54 tons of elemental mercury, 18 tons of gaseous oxidized mercury and 1 ton of particle-bound mercury. Pulverized coal boilers emitted 65 tons, mainly in the coastal provinces and coal-electricity bases. Circulating fluidized bed boilers emitted 8 tons, mainly in Inner Mongolia and Shanxi Province. The average mercury emission intensity over the Chinese mainland was 18.3 g/GWh, which was similar to the limit for low-rank coal-fired units in the United States. The overall uncertainty of national mercury emission was estimated to be -19% to 20%, with the mercury content in coal being the major contributor. In most provinces, monthly mercury emissions generally peaked in December and August. However, monthly partition coefficients of southwest China were obviously lower than other regions from June to October due to the high proportion of hydropower generation.

Comparative water scarcity footprint study of two nuclear power plants

This study compares the Life Cycle Assessment based Water Scarcity Footprint of produced energy unit in two nuclear power plants in the Czech Republic between 2005 and 2015. Primary data has been used to allocate impacts to the core processing stage. Although the real total amount of water consumption in both power plants is similar, the water scarcity footprint in Temelín nuclear power plant is of approximately 8.9 m3 H2Oeq per MWh lower than in Dukovany power plant. The cooling water has the most significant contribution to the freshwater availability impact category. Evaporation from reservoirs which are a part of water management of the individual power plants has lower, but not inconsiderable, contribution to the water consumption. In the case of Temelín nuclear power plant, the loss caused by evaporation from Hněvkovice reservoir is of approximately 6.5% of the difference between withdrawal and discharge of the power plant. In the case of Dukovany nuclear power plant, evaporation from Dalešice - Mohelno reservoir is of even around 11%.

Estimating Human Health Impacts and Costs Due to Iranian Fossil Fuel Power Plant Emissions through the Impact Pathway Approach

Air pollutants from fossil fuel fired power plants harm the environment and human health. More than 91% of Iran’s electricity production is from thermal power plants that use natural gas, diesel, and fuel oil. We apply the impact pathway approach to estimate the health impacts arising from Iranian fossil-based electricity generation emission, and in a next step, we calculate monetary costs of the estimated damages, for a one-year period starting from 20 March 2016 through 2017. We use the new version of SIMPACTS (International Atomic Energy Agency, Vienna, Austria) to investigate the health effects from 61 major Iran fossil-based power plants separately. The selected plants represent 95.6% of total Iran fossil-based power generation. Using the individual and different power plant estimates, we avoid extrapolation and our results can be considered more reliable, taking into account spatial differences. The total damage cost is 723.42 million USD (2000). The damage cost per generated electricity varies from 0.06 to 22.41 USD/MWh and average plant damage cost is 2.85 USD/MWh. Accounting for these external costs indicates the actual costs of fossil energy. The results are useful for policy makers to compare the health costs from these plants and to decide on cleaner energy sources and to take measures to increase benefits for society.

Quantifying CO2 Emissions From Individual Power Plants From Space

AbstractIn order to better manage anthropogenic CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales from the national level down to the facility level. Although the Orbiting Carbon Observatory 2 (OCO‐2) satellite was not designed for monitoring power plant emissions, we show that in some cases, CO2 observations from OCO‐2 can be used to quantify daily CO2 emissions from individual middle‐ to large‐sized coal power plants by fitting the data to plume model simulations. Emission estimates for U.S. power plants are within 1–17% of reported daily emission values, enabling application of the approach to international sites that lack detailed emission information. This affirms that a constellation of future CO2 imaging satellites, optimized for point sources, could monitor emissions from individual power plants to support the implementation of climate policies.