The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction

ABSTRACT

In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective.     

Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.     

Optimization of contactless transformer coupling transmission system by Taguchi method

A contactless transformer coupling (CTC) transmission system transmits electric energy via an alternating magnetic field through an air-gap. The transmitted power can be enhanced by the application of resonant effects. Transmitting and receiving coils are usually single layer solenoids with series capacitors, which, in combination, allow the receiving element to be tuned to the required transmitter frequency. An input DC source is used to obtain high-frequency AC signal through the standardized half-bridge DC/AC switching circuit. Further, the high-frequency signal passes through matching transformer and contactless coupling induction coil, which can be considered as an isolated input and output stage. Coupling must be tight to achieve high efficiency. This paper then applies the methods of Taguchi parameter design forthe contactless transformer coupling transmission system, which enhances the output voltage, loss factor, and output efficiency of the transmission system. The results of measurement verify the feasibility of this structure in the experiment.     

Limited occurrence of denitrification in four shallow aquifers in agricultural areas of the United States

The ability of natural attenuation to mitigate agricultural nitrate contamination in recharging aquifers was investigated in four important agricultural settings in the United States. The study used laboratory analyses, field measurements, and flow and transport modeling for monitoring well transects (0.5 to 2.5 km in length) in the San Joaquin watershed, California, the Elkhorn watershed, Nebraska, the Yakima watershed, Washington, and the Chester watershed, Maryland. Ground water analyses included major ion chemistry, dissolved gases, nitrogen and oxygen stable isotopes, and estimates of recharge date. Sediment analyses included potential electron donors and stable nitrogen and carbon isotopes. Within each site and among aquifer-based medians, dissolved oxygen decreases with ground water age, and excess N(2) from denitrification increases with age. Stable isotopes and excess N(2) imply minimal denitrifying activity at the Maryland and Washington sites, partial denitrification at the California site, and total denitrification across portions of the Nebraska site. At all sites, recharging electron donor concentrations are not sufficient to account for the losses of dissolved oxygen and nitrate, implying that relict, solid phase electron donors drive redox reactions. Zero-order rates of denitrification range from 0 to 0.14 micromol N L(-1)d(-1), comparable to observations of other studies using the same methods. Many values reported in the literature are, however, orders of magnitude higher, which is attributed to a combination of method limitations and bias for selection of sites with rapid denitrification. In the shallow aquifers below these agricultural fields, denitrification is limited in extent and will require residence times of decades or longer to mitigate modern nitrate contamination.     

A SEDIMENT RESUSPENSION AND WATER QUALITY MODEL OF LAKE OKEECHOBEE1

ABSTRACT: The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeechobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspend. ed solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is light-limited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sediment-water interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.     

DISSOLVED GAS ANALYSIS FOR ASSESSING THE FATE OF NITRATE IN WETLANDS1

ABSTRACT: Dissolved gas analysis permits direct detection of ground water denitrification, a technique we used in this study to assess the fate of nitrate in a riparian wetland. Dissolved argon (Ar) and dinitrogen (N₂) were measured in transects of nested piezometers installed at different depths within upwelling regions of a riparian wetland. The method uses the Ar content in the water as a natural inert tracer for assessing background content of N₂ from the previous air/water equilibrium. Within the wetland under study, anoxic to suboxic ground water became more oxic in piezometers close to the aquifer layer, indicating upwelling of oxic ground water. Assessment of loss of nitrate and Ar in ground water within an upwelling zone indicated that shallow piezometers had significant N₂ loss through degassing. Most of the measured nitrate‐nitrogen (NO₃^?‐N) loss of 205 μM in a piezometer nest could be accounted for by total N₂‐N produced (169 μM N), calculated from changes in dissolved N₂ and estimated N₂ degassed. Degassing due to methane (CH₄) production was also detected in some shallow piezometers within nests. This technique for analysis of dissolved gases in ground water can be applied to detect small changes in N gas concentration and aids in assessing the fate of nitrate along a ground water flow path.     

高频变压器饱和电流测试装置的设计

本文设计一种高频变压器饱和电流测试装置,解决开关电源设计过程中变压器饱和电流测试困难的问题,在开关电源设计的过程中方便工程师对高频变压器的评估,准确地设计出合理的高频变压器参数,缩短开发周期、提高所开发产品的可靠性。     

黄曲霉侵染对不同品种花生生理特性的影响

以高抗黄曲霉花生品种J11、中抗品种HY22和敏感性品种JH1012为材料进行黄曲霉侵染,在不同时间段取样测定各品种花生种皮和籽仁的毒素含量,并同时测定籽仁中脂肪酸和亚油酸、油酸含量。结果表明,各花生品种的种皮内毒素含量随侵染时间增加而升高,到最大值后保持稳定;而籽仁中的毒素含量较低,不同品种花生受侵染后毒素含量大小表现为高抗品种〈普通品种〈高感品种。亚油酸和脂肪含量与黄曲霉毒素含量呈显著正相关,而油酸呈显著负相关,说明高油酸含量和低脂肪、亚油酸含量的花生品种对黄曲霉毒素的侵染有一定抵抗作用。     

Real-time, high-resolution quantitative measurement of multiple soil gas emissions: selected ion flow tube mass spectrometry

A new technique is presented for the rapid, high-resolution identification and quantification of multiple trace gases above soils, at concentrations down to 0.01 microL L(-1) (10 ppb). The technique, selected ion flow tube mass spectrometry (SIFT-MS), utilizes chemical ionization reagent ions that react with trace gases but not with the major air components (N2, O2, Ar, CO2). This allows the real-time measurement of multiple trace gases without the need for preconcentration, trapping, or chromatographic separation. The technique is demonstrated by monitoring the emission of ammonia and nitric oxide, and the search for volatile organics, above containerized soil samples treated with synthetic cattle urine. In this model system, NH3 emissions peaked after 24 h at 2000 nmol m(-2) s(-1) and integrated to approximately 7% of the urea N applied, while NO emissions peaked about 25 d after urine addition at approximately 140 nmol m(-2) s(-1) and integrated to approximately 10% of the applied urea N. The monitoring of organics along with NH3 and NO was demonstrated in soils treated with synthetic urine, pyridine, and dimethylamine. No emission of volatile nitrogen organics from the urine treatments was observed at levels >0.01% of the applied nitrogen. The SIFT method allows the simultaneous in situ measurement of multiple gas components with a high spatial resolution of < 10 cm and time resolution <20 s. These capabilities allow, for example, identification of emission hotspots, and measurement of localized and rapid variations above agricultural and contaminated soils, as well as integrated emissions over longer periods.     

A two-stage support-vector-regression optimization model for municipal solid waste management - a case study of Beijing, China

In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through coupling the support-vector-regression (SVR) model with an interval-parameter mixed integer linear programming (IMILP). The developed TSOM can not only predict the city's future waste generation amount, but also reflect dynamic, interactive, and uncertain characteristics of the MSW management system. Four kernel functions such as linear kernel, polynomial kernel, radial basis function, and multi-layer perception kernel are chosen based on three quantitative simulation performance criteria [i.e. prediction accuracy (PA), fitting accuracy (FA) and over all accuracy (OA)]. The SVR with polynomial kernel has accurate prediction performance for MSW generation rate, with all of the three quantitative simulation performance criteria being over 96%. Two cases are considered based on different waste management policies. The results are valuable for supporting the adjustment of the existing waste-allocation patterns to raise the city's waste diversion rate, as well as the capacity planning of waste management system to satisfy the city's increasing waste treatment/disposal demands.     

隔吸声屏障在变压器噪声控制中的应用

针对城市电厂变压器的噪声污染,以北京太阳宫燃气热电冷联供工程中应用的变压器噪声控制为例,通过分析研究变压器声源不同的频谱特性,并根据厂界噪声控制目标计算声源的超标贡献量和设计降噪量,开发设计了变压器降噪隔吸声屏障,针对变压器的低频噪声,设计特殊的隔吸声结构,并成功应用于工程实践,取得了理想效果。     

Modeling the Impacts of Two Bark Beetle Species Under a Warming Climate in the Southwestern USA: Ecological and Economic Consequences

Predicted climate warming is expected to have profound effects on bark beetle population dynamics in the southwestern United States. Temperature-mediated effects may include increases in developmental rates, generations per year, and changes in habitat suitability. As a result, the impacts of Dendroctonus frontalis and Dendroctonus mexicanus on forest resources are likely subject to amplification. To assess the implications of such change, we evaluated the generations per year of these species under three climate scenarios using a degree-day development model. We also assessed economic impacts of increased beetle outbreaks in terms of the costs of application of preventative silvicultural treatments and potential economic revenues forgone. Across the southwestern USA, the potential number of beetle generations per year ranged from 1–3+ under historical climate, an increase of 2–4+ under the minimal warming scenario and 3–5+ under the greatest warming scenario. Economic benefits of applying basal area reduction treatments to reduce forest susceptibility to beetle outbreaks ranged from 7.75/ha (NM) to7.75/ha (NM) to 95.69/ha (AZ) under historical conditions, and 47.96/ha (NM) to47.96/ha (NM) to 174.58/ha (AZ) under simulated severe drought conditions. Basal area reduction treatments that reduce forest susceptibility to beetle outbreak result in higher net present values than no action scenarios. Coupled with other deleterious consequences associated with beetle outbreaks, such as increased wildfires, the results suggest that forest thinning treatments play a useful role in a period of climate warming.     

MODELING THE HYDROCHEMISTRY OF THE CANNONSVILLE WATERSHED WITH GENERALIZED WATERSHED LOADING FUNCTIONS (GWLF)1

ABSTRACT: A previous modeling study used the Generalized Watershed Loading Functions (GWLF) model to simulate stream‐flow, and nutrient and sediment loads to Cannonsville Reservoir from the West Branch Delaware River (WBDR). We made several model revisions, calibrated key parameters, and tested the original GWLF model and a revised GWLF model using more recent data. Model revisions included: addition of unsaturated leakage between unsaturated and saturated subsurface reservoirs; revised timing of sediment export; inclusion of urban sediments and dissolved nutrients; tracking of particulate nutrients from point sources; and revised timing of septic system loads. The revision of sediment yield timing resulted in significant improvements in monthly sediment and particulate phosphorus predictions as compared to the original model. Addition of unsaturated leakage improved hydrologic predictions during low flow months. The other model changes improve realism without adding significant model complexity or data requirements. Goodness of fit of revised model predictions versus stream measurements, as measured by the Nash‐Sutcliff coefficient of model efficiency, exceeded 0.8 for streamflow‐0.7 for sediment yield and dissolved nitrogen (N) and 0.6 for particulate and dissolved phosphorus (P). The revised GWLF model, with limited calibration, provides reasonable estimates of monthly streamflow, and nutrient and sediment loads in the Cannonsville watershed.     

An environment-friendly engine selection methodology for aerial vehicles

Emitted exhaust gases from aircraft are an issue of concern from an environmental perspective. Many research studies have been conducted aiming to reduce aircraft emissions in the hope of preventing any further increase in climate change and global warming. Within this scope, the present study intends to present a methodology for an optimum gas turbine engine selection with regard to emitted exhaust gases. The methodology focuses on five different turbofan engines which constitute the power unit of a commonly used passenger aircraft. At the end of the study, it is considered to be impossible to achieve a minimum exhaust emission for each gas. For this reason, it is considered to be better to optimize the engine with the aim of reducing nitrogen oxide emissions or other exhaust emissions.     

CO2 mineral sequestration in oil-shale wastes from Estonian power production

In the Republic of Estonia, local low-grade carbonaceous fossil fuel--Estonian oil-shale--is used as a primary energy source. Combustion of oil-shale is characterized by a high specific carbon emission factor (CEF). In Estonia, the power sector is the largest CO(2) emitter and is also a source of huge amounts of waste ash. Oil-shale has been burned by pulverized firing (PF) since 1959 and in circulating fluidized-bed combustors (CFBCs) since 2004-2005. Depending on the combustion technology, the ash contains a total of up to 30% free Ca-Mg oxides. In consequence, some amount of emitted CO(2) is bound by alkaline transportation water and by the ash during hydraulic transportation and open-air deposition. The goal of this study was to investigate the possibility of improving the extent of CO(2) capture using additional chemical and technological means, in particular the treatment of aqueous ash suspensions with model flue gases containing 10-15% CO(2). The results indicated that both types of ash (PF and CFBC) could be used as sorbents for CO(2) mineral sequestration. The amount of CO(2) captured averaged 60-65% of the carbonaceous CO(2) and 10-11% of the total CO(2) emissions.     

A NONLINEAR MODEL OF A WATER RESERVOIR SYSTEM WITH MULTIPLE USES AND ITS OPTIMIZATION BY COMBINED USE OF DYNAMIC PROGRAMMING AND PATTERN SEARCH TECHNIQUES

A fairly realistic nonlinear model of a water reservoir system with multiple uses has been developed based on available data, and the optimum of the system based on the developed model has been determined by the combined use of dynamic programming and the pattern search techniques. Both the simplex search and the Hooke and Jeeves pattern search have been used. The approach in modeling and optimization can treat complex inequality constraints. The benefits or losses resulting from four purposes or uses of water, namely, urban water supply, hydroelectric power generation, irrigation, and recreation, are taken into account in the profit function. Other uses such as flood control, navigation, and fish and wildlife enhancement are considered indirectly by the use of inequality constraints. It appears that the approach developed in this work can treat a water resource allocation problem involving complex inequality constraints.     

Cumulative impact of marinas on estuarine water quality

The purpose of this work is to present a modeling approach for assessing and managing the cumulative impact of marinas on estuarine systems. In doing so, both a water-quality model and a planning and management model are developed. The water-quality model predicts biochemical oxygen demand (BOD) and fecal coliform (FC) loadings from marina sources in a hypothetical North Carolina estuary. By running the water-quality model repeatedly with varied loading input, impact coefficients are determined. These impact coefficients are used in the planning and management model, the output of which gives the sizes and locations of marinas in the estuarine system such that dissolved oxygen (DO) and FC water-quality standards are maintained.Five different estuarine development scenarios are considered. Each scenario is evaluated with respect to both maximum and uniform land development constraints. In addition, two alternative fecal coliform standards are used with each of the development options.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.