SOME CONJUNCTIVE DESALTING STUDIES EN THE UNITED KINGDOM1

ABSTRACT .Operating rule procedures are developed for the optimal use of desalination in conjunction with surface water impoundments. Results obtained from the use of hill-climbing and dynamic programming methods are compared. Benefits to be obtained from the integrated use of desalination are demonstrated through a case study for the Barcelona area of Spain.     

ECOLOGICAL MODELS AND ENVIRONMENTAL STUDIES1

The recent world-wide trend towards centralization of all environmental management functions into one regulatory agency has illustrated the necessity for resources management agencies to adopt a total systems viewpoint. Environmental systems are typically complex and multi-dimensional in nature. Mathematical models for the management of air, water and land resources have found wide acceptance among planners and decision-makers. Ecological models of life processes have not reached the same state of development or acceptance. A general review of ecological systems theory and examples of the types of ecological models that have been developed to date arc presented in this paper. With this material as a background and given the vast literature on engineering and economic models, a conceptual framework for an approach to environmental studies and the analysis of polluted environmental systems is presented.     

LINEAR PROGRAMMING APPLICATIONS IN WATER RESOURCES1

Applications of linear programming to water quality and water quantity problems are discussed, and a fairly comprehensive sample of recent literature in these areas is reviewed. Basic elements of linear programming are also discussed. Emphasis is placed on the elements of linear programming that make it a useful tool for analyzing water resource problems and the basic features of various water resource problems that render them amenable to meaningful analysis by linear programming.     

THE DEVELOPMENT OF A MODEL TO EVALUATE HYDROLOGIC RISK IN WATER RESOURCE SYSTEM DESIGN1

In this paper, a procedure for analyzing a water resource system with special emphasis on evaluation of acceptable economic risk due to occasional failures to deliver water is proposed. The basic methodology includes the development of a simple mathematical model which describes the physical hydrologic and economic characteristics of a single reservoir irrigation and city water supply system and an evaluation of economic benefits of the system with full and partial deliveries of water. The system is simulated for various combinations of decision variables (system magnitudes) and an optimum design is obtained by response surface technology. Emphasis is placed on the basic model and methodology although, in order to introduce some realism, the procedure is applied to data based on the existing reservoir system on the South Concho River in West Central Texas.     

SIMULATION/OPTIMIZATION TECHNIQUES FOR MULTI-BASIN WATER RESOURCE PLANNING1

A set of simulation and optimization tools capable of analyzing the development and operation of a complex, multi-basin, interconnected water resource are explained. These models provide valuable information regarding the important questions: (1) “When should new projects be build?” (2) “How big should they be?” and (3) “How should the system be operated?” Since these tools were developed by and for practicing engineers, their applicability to real-world problems is mandatory. To assure this, testing was done on an actual proposed project, the Texas Water System.     

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.     

废水生化处理出水吸收SO2过程相平衡关系的确定

应用相平衡理论对吸收液－ＳＯ２体系的相平衡关系进行了系统研究,确定了吸收相平衡的数学模型,并通过试验对数学模型进行了验证,结果表明,数学模型计算值与试验实测值基本吻合。     

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.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

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.