71 resultados para variable power, cycle-run, stochastic cycling


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Arsenic (As) is ubiquitous in the environment in the carcinogenic inorganic forms, posing risks to human health in many parts of the world. Many microorganisms have evolved a series of mechanisms to cope with inorganic arsenic in their growth media such as transforming As compounds into volatile derivatives. Bio-volatilization of As has been suggested to play an important role in global As biogeochemical cycling, and can also be explored as a potential method for arsenic bioremediation. This review aims to provide an overview of the quality and quantity of As volatilization by fungi, bacteria, microalga and protozoans. Arsenic bio-volatilization is influenced by both biotic and abiotic factors that can be manipulated/elucidated for the purpose of As bioremediation. Since As bio-volatilization is a resurgent topic for both biogeochemistry and environmental health, our review serves as a concept paper for future research directions.

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This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

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Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

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Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

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Gas fired generation currently plays an integral support role ensuring security of supply in power systems with high wind power penetrations due to its technical and economic attributes. However, the increase in variable wind power has affected the gas generation output profile and is pushing the boundaries of the design and operating envelope of gas infrastructure. This paper investigates the mutual dependence and interaction between electricity generation and gas systems through the first comprehensive joined-up, multi-vector energy system analysis for Ireland. Key findings reveal the high vulnerability of the Irish power system to outages on the Irish gas system. It has been shown that the economic operation of the power system can be severely impacted by gas infrastructure outages, resulting in an average system marginal price of up to €167/MWh from €67/MWh in the base case. It has also been shown that gas infrastructure outages pose problems for the location of power system reserve provision, with a 150% increase in provision across a power system transmission bottleneck. Wind forecast error was shown to be a significant cause for concern, resulting in large swings in gas demand requiring key gas infrastructure to operate at close to 100% capacity. These findings are thought to increase in prominence as the installation of wind capacity increases towards 2020, placing further stress on both power and gas systems to maintain security of supply.

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Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

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Currently wind power is dominated by onshore wind farms in the British Isles, but both the United Kingdom and the Republic of Ireland have high renewable energy targets, expected to come mostly from wind power. However, as the demand for wind power grows to ensure security of energy supply, as a potentially cheaper alternative to fossil fuels and to meet greenhouse gas emissions reduction targets offshore wind power will grow rapidly as the availability of suitable onshore sites decrease. However, wind is variable and stochastic by nature and thus difficult to schedule. In order to plan for these uncertainties market operators use wind forecasting tools, reserve plant and ancillary service agreements. Onshore wind power forecasting techniques have improved dramatically and continue to advance, but offshore wind power forecasting is more difficult due to limited datasets and knowledge. So as the amount of offshore wind power increases in the British Isles robust forecasting and planning techniques are even more critical. This paper presents a methodology to investigate the impacts of better offshore wind forecasting on the operation and management of the single wholesale electricity market in the Republic of Ireland and Northern Ireland using PLEXOS for Power Systems. © 2013 IEEE.

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The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

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Globally the amount of installed terrestrial wind power both onshore and offshore has grown rapidly over the last twenty years. Most large onshore and offshore wind turbines are designed to harvest winds within the atmospheric boundary layer, which can be vary variable due to terrain and weather effects. The height of the neutral atmospheric boundary layer is estimated at above 1300m. A relatively new concept is to harvest more consistent wind conditions above the atmospheric boundary layer using high altitude wind harvesting devices such as tethered kites, air foils and dirigible rotors. This paper presents a techno-economic feasibility study of high altitude wind power in Northern Ireland. First this research involved a state of the art review of the resource and the technologies proposed for high altitude wind power. Next the techno-economic analysis involving four steps is presented. In step one, the potential of high altitude wind power in Northern Ireland using online datasets (e.g. Earth System Research Laboratory) is estimated. In step two a map for easier visualisation of geographical limitations (e.g. airports, areas of scenic beauty, flight paths, military training areas, settlements etc.) that could impact on high altitude wind power is developed. In step three the actual feasible resource available is recalculated using the visualisation map to determine the ‘optimal’ high altitude wind power locations in Northern Ireland. In the last step four the list of equipment, resources and budget needed to build a demonstrator is provided in the form of a concise techno-economic appraisal using the findings of the previous three steps.

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The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

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Organic Rankine Cycle (ORC) is the most commonly used method for recovering energy from small sources of heat. The investigation of the ORC in supercritical condition is a new research area as it has a potential to generate high power and thermal efficiency in a waste heat recovery system. This paper presents a steady state ORC model in supercritical condition and its simulations with a real engine’s exhaust data. The key component of ORC, evaporator, is modelled using finite volume method, modelling of all other components of the waste heat recovery system such as pump, expander and condenser are also presented. The aim of this paper is to investigate the effects of mass flow rate and evaporator outlet temperature on the efficiency of the waste heat recovery process. Additionally, the necessity of maintaining an optimum evaporator outlet temperature is also investigated. Simulation results show that modification of mass flow rate is the key to changing the operating temperature at the evaporator outlet.

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We describe a simple strategy, which is based on the idea of space confinement, for the synthesis of carbon coating on LiFePO4 nanoparticles/graphene nanosheets composites in a water-in-oil emulsion system. The prepared composite displayed high performance as a cathode material for lithium-ion battery, such as high reversible lithium storage capacity (158 mA h g-1 after 100 cycles), high coulombic efficiency (over 97%), excellent cycling stability and high rate capability (as high as 83 mA h g -1 at 60 C). Very significantly, the preparation method employed can be easily adapted and be extended as a general approach to sophisticated compositions and structures for the preparation of highly dispersed nanosized structure on graphene. 

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Conventionally, radial turbines have almost exclusively used radially fibred blades. While issues of mechanical integrity are paramount, there may be opportunities for improving turbine efficiency through a 3D blade design without exceeding mechanical limits. Off-design performance and understanding of the secondary flow structures now plays a vital role in the design decisions made for automotive turbocharger turbines. Of particular interest is extracting more energy at high pressure ratios and lower rotational speeds. Operating in this region means the rotor will experience high values of positive incidence at the inlet. A CFD analysis has been carried out on a scaled automotive turbine utilizing a swing vane stator system. To date no open literature exists on the flow structures present in a standard VGT system. Investigations were carried out on a 90 mm diameter rotor with the stator vane at the maximum, minimum and 25% mass flow rate positions. In addition stator vane endwall clearance existed at the hub side. From investigation of the internal flow fields of the baseline rotor, a number of areas that could be optimized in the future with three dimensional blading were identified. The blade loading and tip leakage flow near inlet play a significant role in the flow development further downstream at all stator vane positions. It was found that tip leakage flow and flow separation at off-design conditions could be reduced by employing back swept blading and redistributing the blade loading. This could potentially reduce the extent of the secondary flow structures found in the present study.

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The development of 5G enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable. Hence, it is first necessary to fully understand how and how much the performance of multiple-input multiple-output (MIMO) systems deteriorates with PA nonlinearities. In this paper, we first reduce the ergodic achievable rate (EAR) optimization from a power allocation to a power control problem with only one optimization variable, i.e. total input power. Then, we develop a closed-form expression for the EAR, where this variable is fixed. Since this expression is intractable for further analysis, two simple lower bounds and one upper bound are proposed. These bounds enable us to find the best input power and approach the channel capacity. Finally, our simulation results evaluate the EAR of MIMO channels in the presence of nonlinearities. An important observation is that the MIMO performance can be significantly degraded if we utilize the whole power budget.