Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville–Thermalito Complex (OTC) – a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation–storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California.     

Flexural behaviour of RC slabs strengthened with prestressed CFRP strips using different anchorage systems

The Externally Bonded Reinforcement (EBR) technique using Carbon Fiber-Reinforced Polymers (CFRP) has been commonly used to strengthen concrete structures in flexure. The use of prestressed CFRP material offers several advantages well-reported in the literature. Regardless of such as benefits, several studies on different topics are missing. The present work intends to contribute to the knowledge of two commercially available systems that differ on the type of anchorage: (i) the Mechanical Anchorage (MA), and (ii) the Gradient Anchorage (GA). For that purpose, an experimental program was carried out with twelve slabs monotonically tested under displacement control up to failure by using a four-point bending test configuration. The effect of type of anchorage system (MA and GA), prestrain level (0 and 0.4%), width (50 mm and 80 mm) and thickness (1.2 mm and 1.4 mm) of the CFRP laminate, and the surface preparation (grinded and sandblasted) on the flexural response were the main studied parameters. Better performance was observed for the slabs: (i) with prestressed laminates, (ii) for the MA system, and (iii) with sandblasted surface preparation.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

IRS-P6 LISS-3和Landsat-5 TM两种多光谱传感器影像数据的对比分析

随着载有各种新型传感器的卫星相继发射升空,不同传感器之间的相互比较成了一个研究热点。首先从传感器的轨道特征、光谱范围等方面对IRS-P6 LISS-3和Landsat-5 TM进行了机理方面的对比分析,选取3对同日过空的遥感影像,研究了IRS-P6 LISS-3和Landsat-5 TM遥感数据在可见光-近红外、短红外各对应光谱波段之间的关系,建立TM和LISS-3各波段之间的相互转换公式,与Chander等提出的转换公式进行对比分析。结果表明:实际TM和模拟TM多光谱数据之间具有较强的相关关系,决定系数R²均大于0.97;模拟TM与实际TM的水体指数(MNDWI)和归一化植被指数(NDVI)空间散点分布和实际LISS-3与实际TM的空间散点分布相比,具有更强的相关关系,其决定系数R²有一定提高,散点分布趋于对称。因此,所求的关系转换方程具有较高的精度和有效性,效果优于Chander等提出的转换公式。     

组合隔板式鱼道水力特性数值模拟研究

鱼道是为鱼类提供洄游通道的一种重要的工程措施。基于Flow-3D采用标准RNG k-ε紊流模型和Tru-VOF追踪自由液面方法,对鱼道池室内流场进行三维紊流数值模拟,研究池室内水流流速、流态空间分布,分析鱼道的水力特性对目标鱼类洄游上溯的影响。结果表明:溢流堰与竖缝组合隔板式鱼道在设计流速v=0.75 m/s条件下,竖缝处平均流速为0.83 m/s,竖缝处流速分布范围为0.76~0.89 m/s;堰上流速为0.90~1.12 m/s,回流区流速分布范围为0.09~0.25 m/s,流速大小在鱼类的克流能力范围之内,但靠竖缝隔板处存在明显的主流贴壁现象。为此开展了池室优化方案设计,使鱼道池室流态满足鱼类上溯要求。     

面向金泽水库取水安全的太浦河多目标联合调度研究

为强化上海市黄浦江供水系统的重要组成部分金泽水源地取水安全,又兼顾太湖流域及太浦河沿线区域防洪、供水需求,开展了太浦河太浦闸与沿线88个闸控口门的多目标联合调度研究。在分析太浦闸及两岸河道现有调度方式的基础上,拟定了两类共10个联合调度方案。采用细化后的太湖流域水量水质模型,对各调度方案进行了模拟。然后,构建了反映防洪、供水、水环境需求的多目标函数,采用蚁群优选算法对所有调度方案进行了优选。结果表明:与现状调度方案相比,太浦闸同时根据太湖水位和金泽断面水质情况加大下泄流量,同时太浦河沿线河道闸门有序控制,可显著提高金泽水源地关键水质指标达标率、抬升金泽水源地最低水位,又基本不影响流域及区域其他调度需求。     

Study on early warning index of spatial deformation for high concrete dam

Owing to the deficiency in early warning for high concrete dam,a formula was established to characterize the deformation behavior of high concrete dam as a whole.The early warning index of spatial deformation was calculated by low probability principle on the basis of the deformation entropy formula proposed.The steps were as follows.Firstly,the probability method was utilized to define the degree of order and degree of chaos for each survey point.Secondly,the weight distribution among the survey points was...