Gasification technology assessment of sterile coal to clean electrical power generation.

Sterile coal is a low-value residue associated to the coal extraction and mining activity. According to the type and origin of the coal bed configuration, sterile coal production can mainly vary on quantity, calorific value and presence of sulphur compounds. In addition, the potential availability of sterile coal within Spain is apparently high and its contribution to the local power generation would be of interest playing a significant role. The proposed study evaluates the availability and deployment of gasification technologies to drive clean electricity generation from waste coal and sterile rock coal, incorporating greenhouse gas emission mitigation systems, like CO2, H2S and NOx removal systems. It establishes the target facility and its conceptual basic design proposal. The syngas obtained after the gasification of sterile coal is processed through specific conditioning units before entering into the combustion chamber of a gas turbine. Flue gas leaving the gas turbine is ducted to a heat recovery steam generation boiler; the steam produced within the boilerdrives a steam turbine. The target facility resembles a singular Integrated Gasification in Combined Cycle (IGCC) power station. The evaluation of the conceptual basic design according to the power output set for a maximum sterile contribution, established that rates over 95% H2S and 90% CO2 removal can be achieved. Noticeable decrease of NOx compounds can be also achieved by the use of commercial technology. A techno-economic approach of the conceptual basic design is made evaluating the integration of potential unitsand their implementation within the target facility aiming toachieve clean power generation. The criterion to be compliant with the most restrictive regulation regarding environmental emissions is setting to carry out this analysis.

A bankable method for the field testingor a CPV plant

The bankability of CPV projects is an important issue to pave the way toward a swift and sustained growth in this technology. The bankability of a PV plant is generally addressed through the modeling of its energy yield under a b aseline loss scenario, followed by an on-site measurement campaign aimed at verifying its energetic behavior. The main difference between PV and CPV resides in the proper CPV modules, in particular in the inclusion of optical lements and III-V multijunction cells that are much more sensitive to spectral variations than xSi cells, while the rest of the system behaves in a way that possesses many common points with xSi technology. The modeling of the DC power output of a CPV system thus requires several impo rtant second order parameters to be considered, mainly related to optics, spectral direct solar radiation, wind speed, tracker accuracy and heat dissipation of cells.

Detecting and characterising ramp events in wind power time series

In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain

Illinois solar weather program /

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Accuracy of SRM and power tap power monitoring systems for bicycling

Purpose: Although manufacturers of bicycle power monitoring devices SRM and Power Tap (PT) claim accuracy to within 2.5%, there are limited scientific data available in support. The purpose of this investigation was to assess the accuracy of SRM and PT under different conditions. Methods: First, 19 SRM were calibrated, raced for 11 months, and retested using a dynamic CALRIG (50-1000 W at 100 rpm). Second, using the same procedure, five PT were repeat tested on alternate days. Third, the most accurate SRM and PT were tested for the influence of cadence (60, 80, 100, 120 rpm), temperature (8 and 21degreesC) and time (1 h at similar to300 W) on accuracy. Finally, the same SRM and PT were downloaded and compared after random cadence and gear surges using the CALRIG and on a training ride. Results: The mean error scores for SRM and PT factory calibration over a range of 50-1000 W were 2.3 +/- 4.9% and -2.5 +/- 0.5%, respectively. A second set of trials provided stable results for 15 calibrated SRM after 11 months (-0.8 +/- 1.7%), and follow-up testing of all PT units confirmed these findings (-2.7 +/- 0.1%). Accuracy for SRM and PT was not largely influenced by time and cadence; however. power output readings were noticeably influenced by temperature (5.2% for SRM and 8.4% for PT). During field trials, SRM average and max power were 4.8% and 7.3% lower, respectively, compared with PT. Conclusions: When operated according to manufacturers instructions, both SRM and PT offer the coach, athlete, and sport scientist the ability to accurately monitor power output in the lab and the field. Calibration procedures matching performance tests (duration, power, cadence, and temperature) are, however, advised as the error associated with each unit may vary.

Muscle metabolism during constant- and alternating-intensity exercise around critical power

Few studies have focused on the metabolic responses to alternating high- and low-intensity exercise and, specifically, compared these responses to those seen during constant-load exercise performed at the same average power output. This study compared muscle metabolic responses between two patterns of exercise during which the intensity was either constant and just below critical power (CP) or that oscillated above and below CP. Six trained males (mean +/- SD age 23.6 +/- 2.6 y) completed two 30-minute bouts of cycling (alternating and constant) at an average intensity equal to 90% of CR The intensity during alternating exercise varied between 158% CP and 73% CP. Biopsy samples from the vastus lateralis muscle were taken before (PRE), at the midpoint and end (POST) of exercise and analysed for glycogen, lactate, PCr and pH. Although these metabolic variables in muscle changed significantly during both patterns of exercise, there were no significant differences (p > 0.05) between constant and alternating exercise for glycogen (PRE: 418.8 +/- 85 vs. 444.3 +/- 70; POST: 220.5 +/- 59 vs. 259.5 +/- 126mmol.kg(-1) dw), lactate (PRE: 8.5 +/- 7.7 vs. 8.5 +/- 8.3; POST: 49.9 +/- 19.0 vs. 42.6 +/- 26.6 mmol.kg(-1)dw), phosphocreatine (PRE: 77.9 +/- 11.6 vs. 75.7 +/- 16.9; POST: 65.8 +/- 12.1 vs. 61.2 +/- 12.7mmol.kg(-1)dw) or pH (PRE: 6.99 +/- 0.12 vs. 6.99 +/- 0.08; POST: 6.86 +/- 0.13 vs. 6.85 +/- 0.06), respectively. There were also no significant differences in blood lactate responses to the two patterns of exercise. These data suggest that, when the average power output is similar, large variations in exercise intensity exert no significant effect on muscle metabolism.

Cost-exergy optimisation of linear Fresnel reflectors

This paper presents a new method for the optimisation of the mirror element spacing arrangement and operating temperature of linear Fresnel reflectors (LFR). The specific objective is to maximise available power output (i.e. exergy) and operational hours whilst minimising cost. The method is described in detail and compared to an existing design method prominent in the literature. Results are given in terms of the exergy per total mirror area (W/m2) and cost per exergy (US $/W). The new method is applied principally to the optimisation of an LFR in Gujarat, India, for which cost data have been gathered. It is recommended to use a spacing arrangement such that the onset of shadowing among mirror elements occurs at a transversal angle of 45°. This results in a cost per exergy of 2.3 $/W. Compared to the existing design approach, the exergy averaged over the year is increased by 9% to 50 W/m2 and an additional 122 h of operation per year are predicted. The ideal operating temperature at the surface of the absorber tubes is found to be 300 °C. It is concluded that the new method is an improvement over existing techniques and a significant tool for any future design work on LFR systems

The steady state performance of converter type reactive power compensators

As a source or sink of reactive power, compensators can be made from a voltage sourced inverter circuit with the a.c. terminals of the inverter connected to the system through an inductive link and with a capacitor connected across the d.c. terminals. Theoretical calculations on linearised models of the compensators have shown that the parameters characterising the performance are the reduced firing angle and the resonance ratio. The resonance ratio is the ratio of the natural frequency of oscillation of the energy storage components in the circuit to the system frequency. The reduced firing angle of the inverter divided by the damping coefficient, β, where β is half the R to X ratio of the link between the inverter and the system. The theoretical results have been verified by computer simulation and experiment. There is a narrow range of values for the resonance ratio below which there is no appreciable improvement in performance, despite an increase in the cost of the energy storage components, and above which the performance of the equipment is poor with the current being dominated by harmonics. The harmonic performance of the equipment is improved by using multiple inverters and phase shifting transformers to increase the pulse number. The optimum value of the resonance ratio increases pulse number, indicating a reduction in the energy storage components needed at high pulse numbers. The reactive power output from the compensator varies linearly with the reduced firing angle while the losses vary as the square of it.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to compare performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implication for generation policy in Korea as outlined in this study.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

Short-term wind power forecasting using Gaussian processes

Since wind has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safety and economics of wind energy utilization. In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. Firstly the wind speed data from NWP was corrected by a GP. Then, as there is always a defined limit on power generated in a wind turbine due the turbine controlling strategy, a Censored GP was used to model the relationship between the corrected wind speed and power output. To validate the proposed approach, two real world datasets were used for model construction and testing. The simulation results were compared with the persistence method and Artificial Neural Networks (ANNs); the proposed model achieves about 11% improvement in forecasting accuracy (Mean Absolute Error) compared to the ANN model on one dataset, and nearly 5% improvement on another.

Power optimization of random distributed feedback fiber lasers

We present a comprehensive study of power output characteristics of random distributed feedback Raman fiber lasers. The calculated optimal slope efficiency of the backward wave generation in the one-arm configuration is shown to be as high as ∼90% for 1 W threshold. Nevertheless, in real applications a presence of a small reflection at fiber ends can appreciably deteriorate the power performance. The developed numerical model well describes the experimental data. © 2012 Optical Society of America.

Identifying PV module mismatch faults by a thermography-based temperature distribution analysis

Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.

Coal-fired Power Plants with Flexible Amine-based CCS and Co-located Wind Power: Environmental, Economic and Reliability Outcomes

Carbon Capture and Storage (CCS) technologies provide a means to significantly reduce carbon emissions from the existing fleet of fossil-fired plants, and hence can facilitate a gradual transition from conventional to more sustainable sources of electric power. This is especially relevant for coal plants that have a CO2 emission rate that is roughly two times higher than that of natural gas plants. Of the different kinds of CCS technology available, post-combustion amine based CCS is the best developed and hence more suitable for retrofitting an existing coal plant. The high costs from operating CCS could be reduced by enabling flexible operation through amine storage or allowing partial capture of CO2 during high electricity prices. This flexibility is also found to improve the power plant’s ramp capability, enabling it to offset the intermittency of renewable power sources. This thesis proposes a solution to problems associated with two promising technologies for decarbonizing the electric power system: the high costs of the energy penalty of CCS, and the intermittency and non-dispatchability of wind power. It explores the economic and technical feasibility of a hybrid system consisting of a coal plant retrofitted with a post-combustion-amine based CCS system equipped with the option to perform partial capture or amine storage, and a co-located wind farm. A techno-economic assessment of the performance of the hybrid system is carried out both from the perspective of the stakeholders (utility owners, investors, etc.) as well as that of the power system operator.

In order to perform the assessment from the perspective of the facility owners (e.g., electric power utilities, independent power producers), an optimal design and operating strategy of the hybrid system is determined for both the amine storage and partial capture configurations. A linear optimization model is developed to determine the optimal component sizes for the hybrid system and capture rates while meeting constraints on annual average emission targets of CO2, and variability of the combined power output. Results indicate that there are economic benefits of flexible operation relative to conventional CCS, and demonstrate that the hybrid system could operate as an energy storage system: providing an effective pathway for wind power integration as well as a mechanism to mute the variability of intermittent wind power.

In order to assess the performance of the hybrid system from the perspective of the system operator, a modified Unit Commitment/ Economic Dispatch model is built to consider and represent the techno-economic aspects of operation of the hybrid system within a power grid. The hybrid system is found to be effective in helping the power system meet an average CO2 emissions limit equivalent to the CO2 emission rate of a state-of-the-art natural gas plant, and to reduce power system operation costs and number of instances and magnitude of energy and reserve scarcity.