Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.     

Integrated model for renewable energy planning in Turkey

All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements.     

COMPARISON OF ALTERNATIVE ENGINEERING DESIGNS1

ABSTRACT: Procedures are presented for comparing and evaluating alternative engineering designs for a particular water resources project. By using certain aspects of fuzzy set theory, it is possible to introduce both quantitative and qualitative considerations into the decisionmaking process. In addition, the viewpoints of the various interest groups involved with the water resources development can be realistically incorporated by the evaluation techniques for the alternative designs. Methods are given for eliminating undesirable alternatives and thereby obtaining a reduced set of possible feasible solutions to the problem. Because of the flexibility of the evaluation methods, the viable alternatives should not only satisfy economical, technical. environmental and other types of constraints, but these possible solutions should be politically feasible as well. A method is formulated for checking the sensitivity of the feasible results with respect to the factors that are considered in the analysis.     

OPTIMAL WATER USE AND SALINITY CONTROL FOR ENERGY - UPPER COLORADO RIVER BASIN1

ABSTRACT: The Upper Colorado River Basin contains appreciable amounts of undeveloped fuel resources. Large quantities of oil shale, coal, and uranium have attracted recent economic and commercial interests. Development of these resources and subsequent conversion to alternative energy forms require an adequate supply of water. Water use for large scale energy development will place increasing demands on an already overstressed allocation of Colorado River water. Present water quality is at a concentration where increased salinity will result in economic detriments to holders of downstream water rights. The salt and water exchange in mining, processing, and spent fuel disposal processes has been incorporated as part of a two-level minimum cost linear programming algorithm. Mathematical simulation results provide an optimal use of Upper Colorado River water for levels of energy output such that salinity concentrations are maintained below predetermined levels.     

CAPITAL COST OF RURAL WATER DISTRIBUTION SYSTEMS1

ABSTRACT: The cost of water service to rural residents is very high compared to urban areas. This is true even after subsidization by Farmers Home Administration (FmHA) loans and grants. Capital cost data on 44 projects financed by the Ohio office of the FmHA during the period August 1968 to January 1977 are used to derive cost equations for 26 components of rural water distribution systems. These components represent 92 percent of the capital cost of the pipeline distribution systems studied. The data can be used to economically design rural water supply systems from a capital cost viewpoint. More data are needed on operation and maintenance costs as well as central and cluster well costs before totally economic system designs can be undertaken.     

ANALYZING THE IMPACT OF LAND USE ON SEWER SERVICE AREA PLANNING1

ABSTRACT: The density and distribution of land uses has important consequences for the planning of sewerage systems and for the costs of these systems. This paper examines these consequences using a simplified service area model. The model determines the area to be served by a central waste treatment plant, where alternative on-lot disposal systems are also available. The model is applied to various urban area configurations, which are summarized by their total populations and by their population density distributions. Both minimum regional cost and minimum local cost service area configurations are determined. In addition, the sensitivity of the model to the parameters of the cost and population density functions is assessed. It is found that the model is most sensitive to the parameters of the collection cost function.     

A NONLINEAR MULTILEVEL MODEL FOR REGIONAL WATER RESOURCES PLANNING1

ABSTRACT: A nonlinear multilevel transportation model is developed to study large-scale allocations in a water resources system. The model uses a modified transportation matrix formulated with nonlinear cost functions as the basic subregional model and the goal coordination method for multilevel decomposition and optimization of the overall regional system. The model is applied to projected water requirements for Salt Lake County in 1985. Sources of water supply - surface water, ground water, import water, and reuse of reclaimed wastewater on a restricted basis - are available to satisfy water requirements for municipal, industrial, and agricultural sectors in four subregions. The conjugate gradient projection method is used to optimize the first level subregional models having cost functions of the form of C = aX^b, and the second level problem is solved using the conjugate gradient method.     

REGIONAL DETECTION OF CHANGE IN WATER QUALITY VARIABLES1

ABSTRACT: The detection of change in a hydrologic varaible, particularly water quality, is a current problem. A method is presented for testing whether there has been a shift in the mean of a hydrologic variable based on the well established bivariate normal distribution theory. In this technique, the dependent, or target, and the independent, or control, variables are formed as weighted linear combinations of the mean values at a number of locations in a selected target and control area. The weighting factors are determined based on a mathematical programming technique which minimizes the conditional coefficient of variation thereby minimizing the number of observations required to detect a change of a preselected magnitude in the mean of the target area. The result is a situation where a savings in the number of observations required to detect a change is a consequence of adding more stations: the space-time tradeoff. Two applications of the technique are presented, the first using electrical conductivity (EC) data from two sets of river basins and the second using EC data from a set of basins as the target variable and annual discharge as the control. The results indicate that a significant savings in time can be achieved by using this method.     

基于灰色-马尔科夫模型的我国能源消费结构优化调整

本文以我国1997—2010年的消费结构数据为基础,运用灰色-马尔科夫链模型对数据进行了分析和预测,然后通过MATLAB预测了我国未来十年的能源消费结构,结合我国政府承诺的非化石能源目标对模型预测结果做了进一步的修正,最后根据能源发展趋势给出了能源消费结构的优化策略。     

基于模糊AHP模型的飞行评价体系

一种正确有效的飞行训练评估方法是保障飞行训练质量的必要前提和基础,而传统的评估方法多采用单一指标评价法或横向指标比较法,这种方法虽然简单易行,但没有充分考虑到评估体系自身的多样性,不能够真实反映飞行训练状态。本文提出了以模糊综合法为主体,专家评价、层次分析法相结合的综合评价方法,通过构造隶属度矩阵,建立飞行训练评估模型,克服了飞行教员评价的主观性,比较全面、客观的进行综合评估,量化计算过程,为真实、有效的飞行训练奠定基础。