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．     

HYDRO-POWER SYSTEM SIMULATION TECHNIQUE1

ABSTRACT. The non-power requirements of a large hydro-power system of multiple-purpose projects often conflict with the best power peaking operation. In order to schedule an optimum multiple-purpose operation, advanced procedures that necessitate the use of computers are required. Special techniques are used in a computer program developed in the Reservoir Control Center, North Pacific Division of the Corps of Engineers that provide the ability to define operating constraints in order of priority. These techniques are easily adapted to practical reservoir regulation problems so that the program is useful in daily reservoir regulation scheduling.     

The Volta Lake and Declining Rainfall and Streamflows in the Volta River Basin

This paper looks at the rainfall and streamflow patterns over two distinct time periods, i.e., 1950–1970 and 1971–1991 within the two most prominent catchments in the Volta river system – White Volta and the Oti basins. The first period (1950–1970) represents relatively vegetated catchments and low population whilst the latter (1971–1990) represents intense land use practices resulting from increased population that have severely degraded the environment. These two catchments are among the most significant contributors to the Volta lake. The Volta lake, which was formed between 1962 and 1966 in Ghana and created primarily for hydroelectric power generation, will probably be one of the greatest man-made lakes for a long time. It produces 912MW of electricity at its maximum operating capacity. Recently, there have been declines in the lake levels resulting most probably from inadequate rainfall and/or runoff from the river catchments that feed the lake. Comparisons of runoffs for the two time periods show reductions in mean streamflows of 32.5% at Saboba on the Oti and 23.1% at Nawuni on the White Volta.     

Water Use by Thermoelectric Power Plants in the United States1

Abstract: Thermoelectric power generation is responsible for the largest annual volume of water withdrawals in the United States although it is only a distant third after irrigation and industrial sectors in consumptive use. The substantial water withdrawals by thermoelectric power plants can have significant impacts on local surface and ground water sources, especially in arid regions. However, there are few studies of the determinants of water use in thermoelectric generation. Analysis of thermoelectric water use data in existing steam thermoelectric power plants shows that there is wide variability in unitary thermoelectric water use (in cubic decimeters per 1 kWh) within and among different types of cooling systems. Multiple‐regression models of unit thermoelectric water use were developed to identify significant determinants of unit thermoelectric water use. The high variability of unit usage rates indicates that there is a significant potential for water conservation in existing thermoelectric power plants.     

A Spatial equilibrium perspective for planning the production of electrical energy

A spatial and temporal equilibrium model of production, consumption, prices, and transmission is constructed to determine the efficient pricing and allocation of electrical energy in the United States. Regional coordination is technically feasible and economically attractive. It also maximizes environmental efficiencies. The duplication of electrical generation and transmission facilities yields a misallocation of resources.The utilities put forth specific arguments against coordinated operations. Yet in a fully integrated power system, each region would be expected to maximize the benefits of time diversity by purchasing from outside the region in lieu of the expansion of regional capacity. The Federal Energy Regulatory Commission has not yet made a serious move to encourage regional coordination and planning, but the Commission has the authority to promote such operations if it chooses to do so.The author is an economist with the Department of Energy. The views expressed are those of the author and do not necessarily represent the policies of the Department of Energy or the views of other staff members.     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

铬渣中铬的浸出行为

采用BCR法连续浸提研究铬渣中铬的存在形态,结果表明:铬渣中总铬和六价铬主要以残渣态和可氧化态形式存在;通过铬渣动态连续浸提实验与静态浸提实验研究了浸提剂和活性炭对铬渣中铬浸出行为的影响,研究发现p H值为3.1的醋酸浸提剂浸出液中铬浓度最低,且添加活性炭后的静态浸出液中铬的浓度有不同程度降低。     

我国生物质气化发电行业综合风险评价

针对我国生物质气化发电行业的现状,总结诸多风险的影响因素,建立了我国生物质气化发电行业综合风险评价体系。该评价体系主要包括5个一级风险影响因素:市场风险、技术风险、安全风险、管理风险、环境风险,每个一级影响因素包括4个二级风险影响因素。由层次分析法获得各个一级影响因素和二级影响因素的权重值,根据所构建的评价集和评分标准,结合模糊综合评价法对我国生物质气化发电行业现状的综合风险等级做定量定性分析。综合风险评价研究结果表明,生物质气化发电行业处于"较高"的风险等级,与实际情况相符。综合风险评价体系的构建合理,所建立的评价方法以及相应对策分析可为决策者提供参考依据。     

SMART-SREC: A stochastic model of the New Jersey solar renewable energy certificate market

Markets for solar renewable energy certificates (SRECs) are gaining in prominence in many states, stimulating growth of the US solar industry. However, SREC market prices have been extremely volatile, causing high risk to participants and potentially less investment in solar power generation. Such concerns necessitate the development of realistic, flexible and tractable models of SREC prices that capture the behavior of participants given the rules that govern the market. We propose an original stochastic model called SMART-SREC to fill this role, building on established ideas from the carbon pricing literature, and including a feedback mechanism for generation response to prices. We calibrate the model to the New Jersey market and backtest it, analyzing parameter sensitivity and demonstrating its ability to reproduce historical dynamics. Finally, we run simulations to investigate the role and impact of regulatory parameters, thus providing insight into the crucial role played by market design.