Boron and strontium isotopic characterization of coal combustion residuals: validation of new environmental tracers.

In the U.S., coal fired power plants produce over 136 million tons of coal combustion residuals (CCRs) annually. CCRs are enriched in toxic elements, and their leachates can have significant impacts on water quality. Here we report the boron and strontium isotopic ratios of leaching experiments on CCRs from a variety of coal sources (Appalachian, Illinois, and Powder River Basins). CCR leachates had a mostly negative δ(11)B, ranging from -17.6 to +6.3‰, and (87)Sr/(86)Sr ranging from 0.70975 to 0.71251. Additionally, we utilized these isotopic ratios for tracing CCR contaminants in different environments: (1) the 2008 Tennessee Valley Authority (TVA) coal ash spill affected waters; (2) CCR effluents from power plants in Tennessee and North Carolina; (3) lakes and rivers affected by CCR effluents in North Carolina; and (4) porewater extracted from sediments in lakes affected by CCRs. The boron isotopes measured in these environments had a distinctive negative δ(11)B signature relative to background waters. In contrast (87)Sr/(86)Sr ratios in CCRs were not always exclusively different from background, limiting their use as a CCR tracer. This investigation demonstrates the validity of the combined geochemical and isotopic approach as a unique and practical identification method for delineating and evaluating the environmental impact of CCRs.

A COMPARISON OF MARKET CLEARING TOOLS IN ELECTRICITY SYSTEMS

To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.

Refueling in nuclear engineering: the FUELCON project

Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.

Prospect for EPM application to environmental technology

EPM seems to have good prospects for the future not only in the materials processing but also in environmental technologies by the help of superior features like contactless processing, clean heating and melting, and good controllability. In the present paper, the authors commentate on the possibility of EPM to avoid environmental issues of energy, resources and hazardous wastes by the use of the functions of Lorentz force and Joule heating. Firstly, the present situation and future trend of electric power generation is outlined, and then some examples of the application of EPM to environmental technologies are introduced, which have been performed by the author’s group. Examples are as follows: production of spherical solar cell from a liquid jet by using intermittent electromagnetic force; fabrication of semi-solid Al-Si slurry for die-casting of vehicle-parts to reduce the weight of vehicle; electromagnetic separation of nonmetallic inclusions from liquid Al scrap and its application to the fabrication of partially particle-reinforced aluminum alloy; electromagnetic melting of hazardous wastes from power plants to stabilize wastes in glass state.

ENEL: business prospects and risks in nuclear energy

This report examines the level of debt of ENEL and how that will be impacted by its plans for new nuclear power plants.

2009 world nuclear industry status report

Although some countries plan to build new nuclear power plants in the near future, in aggregate the data indicates that nuclear power's influence will continue to dwindle across the globe in coming decades.

HTS Machines as Enabling Technology for All-Electric Airborne Vehicles

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development.

The technical merits of turbogenerating shown through the design, validation and implementation of a 1 dimensional engine model

Turbocompounding is the process of recovering a proportion of an engine’s fuel energy that would otherwise be lost in the exhaust process and adding it to the output power. This was first seen in the 1930s and is carried out by coupling an exhaust gas turbine to the crankshaft of a reciprocating engine. It has since been recognised that coupling the power turbine to an electrical generator instead of the crankshaft has the potential to reduce the fuel consumption further with the added flexibility of being able to decide how this recovered energy is used. The electricity generated can be used in automotive applications to assist the crankshaft using a flywheel motor generator or to power ancillaries that would otherwise have run off the crankshaft. In the case of stationary power plants, it can assist the electrical power output. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimise the specific fuel consumption for different engine operating conditions. This method of energy recapture is termed ‘turbogenerating’.

This paper gives a brief history of turbocompounding and its thermodynamic merits. It then moves on to give an account of the validation of a turbogenerated engine model. The model is then used to investigate what needs to be done to an engine when a turbogenerator is installed. The engine being modelled is used for stationary power generation and is fuelled by an induced biogas with a small portion of palm oil being injected into the cylinder to initiate combustion by compression ignition. From these investigations, optimum settings were found that result in a 10.90% improvement in overall efficiency. These savings relate to the same engine without a turbogenerator installed operating with fixed fuelling.

A review of biomass co-firing in North America

Biomass fuels have long been accepted as useful renewable energy sources, especially in mitigating greenhouse gases (GHG), nitrogen oxides, and sulfur oxide emissions. Biomass fuel is carbon neutral and is usually low in both nitrogen and sulfur. For the past decade, various forms of biomass fuels have been co-combusted in existing coal-fired boilers and gas-fired power plants. Biomass is used as a supplemental fuel to substitute for up to 10% of the base fuel in most full commercial operations. There are several successful co-firing projects in many parts of the world, particularly in Europe and North America. However, despite remarkable commercial success in Europe, most of the biomass co-firing in North America is limited to demonstration levels. This review takes a detailed look at several aspects of biomass co-firing with a direct focus on North America. It also explores the benefits, such as the reduction of GHG emissions and its implications. This paper shows the results of our studies of the biomass resources available in North America that can be used in coal-fired boilers, their availability and transportation to the power plant, available co-firing levels and technologies, and various technological and environmental issues associated with biomass co-firing. Finally, the paper proffers solutions to help utility companies explore biomass co-firing as a transitional option towards a completely carbon-free power sector in North America.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

Adaptive backstepping droop controller design for multi-terminal high-voltage direct current systems

Wind power is one of the most developed renewable energy resources worldwide. To integrate offshore wind farms to onshore grids, the high-voltage direct current (HVDC) transmission cables interfaced with voltage source converters (VSCs) are considered to be a better solution than conventional approaches. Proper DC voltage indicates successive power transfer. To connect more than one onshore grid, the DC voltage droop control is one of the most popular methods to share the control burden between different terminals. However, the challenges are that small droop gains will cause voltage deviations, while higher droop gain settings will cause large oscillations. This study aims to enhance the performance of the traditional droop controller by considering the DC cable dynamics. Based on the backstepping control concept, DC cables are modelled with a series of capacitors and inductors. The final droop control law is deduced step-by-step from the original remote side. At each step the control error from the previous step is considered. Simulation results show that both the voltage deviations and oscillations can be effectively reduced using the proposed method. Further, power sharing between different terminals can be effectively simplified such that it correlates linearly with the droop gains, thus enabling simple yet accurate system operation and control.

A Reliability Assessment Approach for the Urban Energy System and Its Application in Energy Hub Planning

With the increasing utilization of combined heat and power plants (CHP), electrical, gas, and thermal systems are becoming tightly integrated in the urban energy system (UES). However, the three systems are usually planned and operated separately, ignoring their interactions and coordination. To address this issue, the coupling point of different systems in the UES is described by the energy hub model. With this model, an integrated load curtailment method is proposed for the UES. Then a Monte Carlo simulation based approach is developed to assess the reliability of coordinated energy supply systems. Based on this approach, a reliability-optimal energy hub planning method is proposed to accommodate higher renewable energy penetration. Numerical studies indicate that the proposed approach is able to quantify the UES reliability with different structures. Also, optimal energy hub planning scheme can be determined to ensure the reliability of the UES with high renewable penetration.

Nuclear disasters and health: lessons learned, challenges, and proposals

Past nuclear disasters, such as the atomic bombings in 1945 and major accidents at nuclear power plants, have highlighted similarities in potential public health effects of radiation in both circumstances, including health issues unrelated to radiation exposure. Although the rarity of nuclear disasters limits opportunities to undertake rigorous research of evidence-based interventions and strategies, identification of lessons learned and development of an effective plan to protect the public, minimise negative effects, and protect emergency workers from exposure to high-dose radiation is important. Additionally, research is needed to help decision makers to avoid premature deaths among patients already in hospitals and other vulnerable groups during evacuation. Since nuclear disasters can affect hundreds of thousands of people, a substantial number of people are at risk of physical and mental harm in each disaster. During the recovery period after a nuclear disaster, physicians might need to screen for psychological burdens and provide general physical and mental health care for many affected residents who might experience long-term displacement. Reliable communication of personalised risks has emerged as a challenge for health-care professionals beyond the need to explain radiation protection. To overcome difficulties of risk communication and provide decision aids to protect workers, vulnerable people, and residents after a nuclear disaster, physicians should receive training in nuclear disaster response. This training should include evidence-based interventions, support decisions to balance potential harms and benefits, and take account of scientific uncertainty in provision of community health care. An open and joint learning process is essential to prepare for, and minimise the effects of, future nuclear disasters.

Emotional response to images of wind turbines: A psychophysiological study of their visual impact on the landscape

Social acceptance for wind turbines is variable, providing a challenge to the implementation of this energy source. Psychological research could contribute to the science of climate change. Here we focus on the emotional responses to the visual impact of wind turbines on the landscape, a factor which dominates attitudes towards this technology. Participants in the laboratory viewed images of turbines and other constructions (churches, pylons and power-plants) against rural scenes, and provided psychophysiological and self-report measures of their emotional reactions. We hypothesised that the emotional response to wind turbines would be more negative and intense than to control objects, and that this difference would be accentuated for turbine opponents. As predicted, the psychophysiological response to turbines was stronger than the response to churches, but did not differ from that of other industrial constructions. In contrast with predictions, turbines were rated as less aversive and more calming compared with other industrial constructions, and equivalent to churches. Supporters and non-supporters did not differ significantly from each other. We discuss how a methodology using photo manipulations and emotional self-assessments can help estimate the emotional reaction to the visual impact on the landscape at the planning stage for new wind turbine applications.