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191.
Stephen C. Newbold 《Journal of the American Water Resources Association》2002,38(2):341-353
ABSTRACT: This paper presents an optimization framework for prioritizing sites for wetlands restoration on a watershed or landscape scale. The framework is designed for analyzing the potential environmental impacts of alternative management strategies while accounting for economic constraints, thereby aiding decision makers in explicitly considering multiple management objectives. The modeling strategy consists of two phases. First, relationships between the configuration of land use types in a watershed and valued ecosystem services are specified mathematically. Second, those functions are incorporated into a spatial optimization model that allows comparisons of the expected environmental impacts and economic costs of management strategies that change the configuration of land use in the watershed. By way of a stylized example, this paper develops the general structure of the framework, presents simulation results based on two production functions for ecosystem services, and discusses the potential utility of the methodology for watershed management. 相似文献
192.
Seok-Ku Ko Darrell G. Fontane John W. Labadie 《Journal of the American Water Resources Association》1992,28(1):111-127
ABSTRACT: Development of optimal operational policies for large-scale reservoir systems is often complicated by a multiplicity of conflicting project uses and purposes. A wide range of multiobjective optimization methods are available for appraising tradeoffs between conificting objectives. The purpose of this study is to provide guidance as to those methods which are best suited to dealing with the challenging large-scale, nonlinear, dynamic, and stochastic characteristics of multireservoir system operations. As a case study, the selected methodologies are applied to the Han River Reservoir System in Korea for four principal project objectives: water supply and low flow augmentation; annual hydropower production, reliable energy generation, and minimization of risk of violating firm water supply requirements. Additional objectives such as flood control are also considered, but are imposed as fixed constraints. 相似文献
193.
根据毕节地区16个主要造林树种的生态生物学特性,结合本区气候和土壤生态条件,运用 Fuzzy 二级评价模型,对各土类水土保持树种的适宜程度进行了综合评价。 相似文献
194.
Patrick A. Mower J. Philip J. O'Kane Jerry D.F. Sherrif Tim Wyatt J. David Barrett 《Journal of the American Water Resources Association》1971,7(4):831-843
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. 相似文献
195.
Donald E. Evenson Joe C. Moseley 《Journal of the American Water Resources Association》1970,6(5):725-736
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. 相似文献
196.
邓民宪 《防灾减灾工程学报》1999,(2)
根据震害调查分析和试验研究结果,建立了由环境因素和管道结构参数组成的,对架空管道震害预测进行二级多因素模糊综合评判的方法。文中给出了计算、评价构成二级评判因素地震烈度、场地类型、工作状态和结构种类各档次正态模糊数范数ak的参数和对实际情况如何确定的方法。本文为面广量大的已建架空管道的震害预测工作提供了一套科学性强,方便实用的计算方法。 相似文献
197.
Mingxing Yu 《International Journal of Green Energy》2020,17(5):332-348
ABSTRACTWind 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. 相似文献
198.
Surender Reddy Salkuti 《International Journal of Green Energy》2020,17(8):457-466
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. 相似文献
199.
Xinyou Lin Guangji Zhang Shenshen Wei Yanli Yin 《International Journal of Green Energy》2020,17(8):488-500
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. 相似文献
200.
Surender Reddy Salkuti 《International Journal of Green Energy》2020,17(13):853-863
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. 相似文献