CLIMATE FACTOR FOR SMALL-BASIN FLOOD FREQUENCY1

ABSTRACT: A climate factor, C_T, (T = 2–, 25-, and 100-year recurrence intervals) that delineates regional trends in small-basin flood frequency was derived using data from 71 long-term rainfall record sites. Values of C_T at these sites were developed by a regression analysis that related rainfall-runoff model estimates of T-year floods to a sample set of 50 model calibrations. C_T was regionalized via kriging to develop maps depicting its geographic variation for a large part of the United States east of the 105th meridian. Kriged estimates of C_T and basin-runoff characteristics were used to compute regionalized T-year floods for 200 small drainage basins. Observed T-year flood estimates also were developed for these sites. Regionalized floods are shown to account for a large percentage of the variability in observed flood estimates with coefficients of determination ranging from 0.89 for 2-year floods to 0.82 for 100-year floods. The relative importance of the factors comprising regionalized flood estimates is evaluated in terms of scale (size of drainage area), basin-runoff characteristics (rainfall. runoff model parameters), and climate (C_T).     

干旱对电力生产的影响

本文以１９９４年～１９９５年干旱对陕西省电力生产的影响为例，论述了干旱对电力生产的影响，在此基础上提出了相应的减灾对策．     

我国“四荒”资源的成因及其开发潜力

“四荒”是指可资农业利用而目前尚未开发的土地和水面，包括荒山、荒地、荒滩和荒水。人为开发利用不当是我国“四荒”资源的主要成因。“四荒”资源按其适宜性可分为宜农、宜园、宜林、宜牧、宜水产养殖５种类型，都有一定规模的开发潜力。     

四川省科技人力资源潜力与结构变化

通过对四川省科技人力资源的潜力、结构变化的分析,提出建立统一规范的科技人才培养经费投入政策,加强科技人才资源的再开发,不拘一格引进科技人才,建立四川省科技人力资源监测系统等对策。     

低压直流电托车的改造

分析了AC380伏电托车触电原因，介绍了低压直流电托车改造方案及运行效果。     

炼铁厂2#电除尘的设计与应用

新疆八一钢铁有限责任公司炼铁厂上料系统1^#转运站，1^#a转运站，2^#转运站及1^#、2^#高炉高道料仓在上料时，粉尘污染较为严重，为解决粉尘污染问题，1999年炼铁厂组织设计与施工了40m^2单室卧式3电场除尘器，工程投运后，收尘效果良好，岗位粉尘浓度与外排浓度均低于国家标准。     

Correlation of indoor radon concentration to commonly available geologic data

Over the last several years, the inhalation of decay products coming from radon-222 has become a national health concern. It is estimated that somewhere between 16,000 and 20,000 people die annually in the United States from lung cancer due to exposure to these decay products. Nationwide, 95% of all homes have not been tested for radon, and so it would seem that any methodology that could give a general idea of indoor radon concentrations (without actually testing the house itself) might be useful. While not intended to replace a radon test, which is both simple and inexpensive, our project attempts to predict indoor radon concentrations based on easily obtainable information from Soil Conservation Service county soil surveys and US Geological Survey surficial geology maps. We have chosen four parameters: soil permeability, surficial geology, soil shrink-swell potential, and distance to the nearest geologic fault. Of these four variables, surficial geology and distance to fault correlated well to winter indoor radon concentrations as measured by short-term (48-h) tests. While it is understood that there are limits to this methodology, primarily because of map scale problems, the correlations mentioned above were very strong and suggest further study would be useful.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.