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.     

快速评定砂浆配方对钢筋腐蚀的影响

用电化学方法测定砂浆试件中钢筋的极化电阻，并测定了砂浆的孔隙率，结果发现:砂浆的孔隙率、孔径分布与钢筋极化电阻大小有良好的对应关系。电化学方法能可靠、快速测定砂浆配合比、添加剂对钢筋腐蚀速度的影响。     

测定地下水流向的多计数管探头的研制

多计数管流向探头;;单孔;;总流向;;局部流向;;滤水管 掌握地下水的流动方向,有助于研究地下水的运动规律。利用放射性单孔法可以测定地下水流某一点流动方向。 应用放射性指示剂在单孔中测定地下水流向的方法由奥地利的梅尔霍费于1963年首先提出,1964年波兰的鲍劳斯齐克等把这种方法用于现场测量。放射性单孔流向测量方法有若干种,其原理基本相同,仅测量装置结构有区别,早期有单管旋转式探头。我们从1983年7月     

冲击回波法检测隧洞混凝土衬砌厚度

冲击回波法是通过接收、分析在混凝土中传播的回波信号，判断结构混凝土厚度和内部质量的新型无损检测技术。室内试验和工程应用研究表明，该方法为隧洞混凝土衬砌厚度检测提供了一个有效的测试手段。     

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.     

Comparison of Representative Heuristic Algorithms for Multi-Objective Reservoir Optimal Operation

Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.

     

基于LMDI和STIRPAT模型的区域用水影响因素定量分析研究

区域用水影响因素分析对落实最严格水资源管理制度、实现节水型社会建设具有重要意义。为定量表征区域用水变化和影响因素之间的关系,通过LMDI因素分解识别人口规模、经济发展水平、节水技术水平对用水变化的影响程度,采用STIRPAT模型解析用水总量对人口规模、经济发展水平、节水技术水平变化的变动响应关系,以榆林市2000—2017年用水及影响因素变化为例开展了实证研究。结果显示:人口规模和经济发展水平对用水增长起到正向促进作用,节水技术水平起到负向抑制作用。人口规模、经济发展水平、节水技术水平效应依次为8 163.124万m~3、144 238.924万m~3、-126 161.049万m~3;人口规模、经济发展水平、节水技术水平每变化1%,用水将分别变化1.208%、0.061%和0.037%;经济发展水平和节水技术水平是用水变化的主要影响因素,但用水对人口规模变化敏感程度最高。最后,结合榆林市水资源特点提出针对性措施和建议,以期为榆林市水资源规划与管理提供参考。     

高坝泄洪诱发场地振动响应分析及传播规律

为研究高坝泄洪诱发场地振动的问题,提出一种基于黏弹性人工边界的有限元数值模拟和水力学模型试验相结合的方法计算场地振动响应。以国内某工程为例,计算不同工况下场地振动响应,分析泄洪量和泄洪调度方式对场地振动的影响,揭示不同岩体条件下振动波的传播规律。结果表明:该工程各种泄洪方式都不会对周边居民的生活造成影响;泄洪量越大,下游场地振动响应越大,当3个溢洪洞泄洪条件一致时,采用2号洞泄洪最不利;同等泄洪条件下,采用4洞均分泄洪的振动响应小于按设计开度泄洪的振动响应;模型范围内放大振动波的主因是断层左右岩体性质的差异,断层的存在进一步加大了放大效应。     

变化环境下考虑物理机制的SD需水预测研究

随着气候变化与人类活动作用的加剧,流域水资源受变化环境的影响愈加显著。研究变化环境下的流域水资源系统变化特征及需水预测对支撑流域水资源管理与合理配置具有重要的指导意义。基于系统动力学原理,耦合了考虑物理机制的需水预测方法,建立水资源系统模型,以黄河流域为例,分析了多因子驱动及多要素胁迫作用下黄河流域水资源系统变化特征,采用MPI气候模式预估的未来气温、降水结果及未来流域5种不同的经济社会发展情形,预测了黄河流域2017—2030年的水资源供需演变趋势。结果表明:①黄河流域的生活需水量随着流域人口及人均用水需求的增加不断增长。随着产业结构调整,工业需水量呈现缓慢减少态势,生态及三产需水量逐年增加,农业灌溉需水量呈下降趋势;②在加强流域水资源管理力度、增加节水技术投资的前提下,保障流域经济、社会协调发展,注重发展经济的同时兼顾流域生态环境保护,满足黄河流域下一阶段的经济社会可持续发展的要求;③为保障黄河流域水资源可持续发展,实现黄河流域生态保护和高质量发展,需要调整流域水资源管理策略,提高节水程度,促进流域产业结构优化。     

窝崩抢护治理中树头石阻水效果试验研究

河堤窝崩发生后,首先需要确定的是抢护治理方案,减缓窝塘流速,遏制窝塘进一步发展。在诸多抢护治理方案中,树头石方案具有较好的减速促淤效果,但树头高度和抛投间距在以往的设计中都是依经验确定,缺乏理论基础和试验依据。通过制作长江扬中河段指南村窝崩模型,在窝崩口门附近流速模拟相似的基础上,对窝塘内同一高度3种间距的树头石排列型式和同一间距3种高度的树头石进行了试验,用三点法测量了窝塘内12个点的流速、流向。试验结果表明:窝塘内表层流速受惯性影响较大,底层流速受地形影响较大;窝塘内布置不同高度和不同间距的树头石时,平均流速随树头石高度的增加而减小,随树头石间距的减小而减小,窝内流速的减小,意味着泥沙淤积强度的增大;另一方面,树头石高度的增大和间距的减小,都会增加工程的投资成本,研究认为在相对树高为0.15、间距为6 m×6 m时综合效果较佳。