COMPARISON OF RESERVOIR LINEAR OPERATION RULES USING LINEAR AND DYNAMIC PROGRAMMING1

ABSTRACT: Mathematical optimization techniques are used to study the operation and design of a single, multi-purpose reservoir system. Optimal monthly release policies are derived for Hoover Reservoir, located in Central Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Important characteristics of the former approach are derived, discussed, and graphically illustrated using Hoover Reservoir as a case example. Simulation procedures are used to examine and compare the overall performance of the optimal monthly reservoir release policies derived under the two approaches. Results indicate that, for the mean detention time and the corresponding safe yield target water supply release under existing design of Hoover Reservoir, the dynamic programming policies produce lower average annual losses (as defined by a two-sided quadratic loss function) while achieving at least as high reliability levels when compared to policies derived under the chance-constrained linear programming method. In making this comparison, the reservoir release policies, although not identical, are assumed to be linear. This restricted form of the release policy is necessary to make the chance-constrained programming method mathematically tractable.     

Considerations for preserve design based on the distribution of rare plants in Great Smoky Mountains National Park,USA

Park design principles are proposed on the basis of consideration and analysis of rare plant species in Great Smoky Mountains National Park, USA. Rare species richness can be used as a simple measure of preservation success. A semilogartihmic species-area model for the Smokies was used in this analysis. Species richness would increase logarathmically with expansion of the national park area. An analysis of the relationship between species richness and the distribution of geologic and topographic features in the national park was also reported. An asymptotic relation was documented for the accumulation of newly recorded rare and endangered vascular plant species in the Smokies region up to 1978. Several multiple regression linear models predicted rare vascular plant species richness in Great Smoky Mountains National Park from area and topographic variates.Preserve design criteria can be based upon species-area, environmental gradient, and natural features distribution patterns for the specific taxa and biogeographic region under consideration. In addition, natural history characteristics for particular vulnerable species must be assessed. Rather than concentrating on the preservation of undocumented immigration and extinction processes, preserve design should be directed towards protecting geographic components and gradient patterns characteristic of a region.     

DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.     

系统结构特征在事故致因中的应用研究

从二维空间的角度出发，提出了系统的结构特征；联系紧密和联系松散；复杂式相互作用和直线式相互作用的概念及其特点，并探讨了系统结构特征在系统事故致因中的应用分析。     

IMPROVED RIVER BASIN UTILIZATION THROUGH SYSTEMS ANALYSIS1

ABSTRACT. Theoretical and practical results are summarized for a study to determine optimal water resource allocation in a proposed water conservancy district. The area of this district, which covers several river basins, contains a large number of existing and proposed facilities such as reservoirs and diversions. The operation of all of these facilities was to be determined along with the sizing of the proposed facilities in order to optimize given objective functions. Related efforts in optimal river basin utilization were surveyed, and linear programming was selected as an expedient optimization technique. The problem is formulated by identifying time stages which together constitute a repetitive cycle such as a year. With these stages, it is possible to associate operational and capacity variables with network components, which are branches and nodes. Objective functions are assembled for the component variables. Constraint equations are written in terms of the variables to reflect network nodal continuity, capacity restrictions, and adjudications such as water rights. A numerical example is considered in which the existing and proposed facilities are aggregated to produce a small, tractable number of facilities. This paper examines the example results and suggests future improvements for models of this type.     

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.     

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.     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.     

MANY RESOURCES,MANY USES: A SYSTEM ANALYSIS APPROACH TO RENEWABLE RESOURCE DEVELOPMENT1

ABSTRACT: Decisionmaking associated with the Nation's 1.7 billion acres of forest and range land has become increasingly complicated because of the rise in competition for resource use and in the awareness of environmental and social effects. This system analysis approach uses four models to synthesize pertinent masses of information into measures of economic, environmental, and social impacts. The system results can be used to help evaluate alternative national programs. The models are:

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UNIT HYDROGRAPHS – A COMPARATIVE STUDY1

ABSTRACT. Unit hydrographs derived by using two methods, linear programming and least squares, are compared. Test data comprise rainfall and runoff information from four storms over the North Branch Potomac River near Cumberland, Maryland. The mathematical bases of these methods for unit-hydrograph derivation are explained. The linear programming method minimizes the sum of absolute deviations, and the least squares method minimizes the sum of the squares of deviations. Computer subroutines are readily available for application of these methods. The unit hydrographs derived with the two methods are practically the same for storms 2 and 3, but differ somewhat for storms 1 and 4. However, the reconstituted direct surface runoff hydrographs are similar to those observed with the exception of the hydrograph for storm 4 which had a relatively more non-uniform rainfall excess of a considerably larger duration.