Hydropower Development in China: A Leapfrog Development Secured by Technological Progress of Dam Construction

It has been over 110 years since China’s first hydropower station, Shilongba Hydropower Station, was built in 1910. With the support of advanced dam construction technology, the Chinese installed capacity keeps rising rapid growth, hitting around 356 GW nationwide by the end of 2019, and the annual electricity production exceeds 10,000 TWh. At present, China contributes to 25% of global installed hydropower capacity, ranking first in the world for 20 consecutive years since 2001 and surpassing the combined of the 4 countries ranking second to fifth. This paper reviews China’s progress in the context of global hydropower development and examines the role of technological advance in supporting China’s hydropower projects, especially dam construction technology. China is currently actively promoting the “integration of wind, solar, hydro, and coal power generation and energy storage” and building a smart grid of multi-energy complementary power generation. New technologies and new concepts are expected to continue to lead the world’s hydropower development trends

A Predictive Analysis Method of Shafting Vibration for the Hydraulic-Turbine Generator Unit

The shafting vibration for the Hydraulic-Turbine Generator Unit (HGU) inevitably affects the safe and stable operation of the Units. Excessive shafting vibration could cause fatigue damage of materials, which eventually leads to malfunction of HGU and even results in damage accidents in serious cases. Generally speaking, the vibration is mainly generated from the high-speed rotation of the shafting, and mechanical, hydraulic, and electrical factors as the vibration exciting sources may be coupled all to cause a vibration of the HGU, so it is necessary to take the whole shafting as a specific object of study. In recent years, many scholars have conducted much research on them and their results are focused more on how to control the influence of external excitation sources of vibration, but still lack consideration of the shafting’s internal mechanism of vibration. In this paper, a predictive analysis method is proposed to reveal the internal mechanism of vibration. Starting from the analysis of natural vibration characteristics of the shafting, this study establishes the finite element calculation model of the shafting of the HGU based on the finite element analysis method. By selecting appropriate research methods and calculation procedures, the modal analysis of the dynamic characteristics of the shafting structure is carried out. Finally, the first ten-order natural vibration characteristics and critical rotational speed of the shafting structure are successfully calculated, and the results conform to the basic laws of shafting vibration. In addition, by comparing the relationship between rotational frequency such as the rated speed, runaway speed, and critical speed of the shafting, the possibility of resonance of the HGU is analyzed and predicted, and then some suggestions for optimization design such as increasing the shafting’s stiffness and balancing its mass distribution are proposed. Therefore, this study provides a basis for guiding the structural design and optimization of the shaft system in engineering, and avoids the resonance caused by the excitation source such as rotational frequency, thereby ensuring the safe and stable operation of the HGU

A Predictive Analysis Method of Shafting Vibration for the Hydraulic-Turbine Generator Unit

The shafting vibration for the Hydraulic-Turbine Generator Unit (HGU) inevitably affects the safe and stable operation of the Units. Excessive shafting vibration could cause fatigue damage of materials, which eventually leads to malfunction of HGU and even results in damage accidents in serious cases. Generally speaking, the vibration is mainly generated from the high-speed rotation of the shafting, and mechanical, hydraulic, and electrical factors as the vibration exciting sources may be coupled all to cause a vibration of the HGU, so it is necessary to take the whole shafting as a specific object of study. In recent years, many scholars have conducted much research on them and their results are focused more on how to control the influence of external excitation sources of vibration, but still lack consideration of the shafting’s internal mechanism of vibration. In this paper, a predictive analysis method is proposed to reveal the internal mechanism of vibration. Starting from the analysis of natural vibration characteristics of the shafting, this study establishes the finite element calculation model of the shafting of the HGU based on the finite element analysis method. By selecting appropriate research methods and calculation procedures, the modal analysis of the dynamic characteristics of the shafting structure is carried out. Finally, the first ten-order natural vibration characteristics and critical rotational speed of the shafting structure are successfully calculated, and the results conform to the basic laws of shafting vibration. In addition, by comparing the relationship between rotational frequency such as the rated speed, runaway speed, and critical speed of the shafting, the possibility of resonance of the HGU is analyzed and predicted, and then some suggestions for optimization design such as increasing the shafting’s stiffness and balancing its mass distribution are proposed. Therefore, this study provides a basis for guiding the structural design and optimization of the shaft system in engineering, and avoids the resonance caused by the excitation source such as rotational frequency, thereby ensuring the safe and stable operation of the HGU

Assessment of Urban Water Supply System Based on Query Optimization Strategy

As a complicated water treatment system project, an urban water supply plays a significant role in enhancing ecological civilization construction, promoting social-economic sustainable development, and improving the living environment of humans. This paper has the goal of improving water treatment efficiency and reducing water treatment cost based on comparative studies by applying two types of distributed database query optimization methods, including the system for a distributed database (SDD-1) and all reduction algorithms. The approach involves the components of partial relations and deletes the database components that are unrelated to a query, using only attributes related to a query. Thereby, the realization process becomes simple, with a small amount of transmitted data. The results show that the validity and convenience of all reduction algorithms involve the whole query process. An algorithm is independent of the chart of static characteristics and can realize all reduction states without depending on analyzing the benefits from intermediate semijoin results, which will ultimately contribute to reductions in the transmission of useless data in the network and communication costs. Implementation of the query optimization strategy can improve water treatment efficiency, reduce water treatment cost, lower water treatment expense, and implement effective communication

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications

Long-, Medium-, and Short-Term Nested Optimized-Scheduling Model for Cascade Hydropower Plants: Development and Practical Application

This paper presents a nested approach for generating long-term, medium-term, and short-term reservoir scheduling models, which is based on the actual needs of the scheduling operation of the Three Gorges–Gezhouba (TG-GZB) cascade reservoirs. The approach has established a five-tier optimal scheduling model in which the time interval of the scheduling plan prepared by the model can be as short as 15 min, meeting the real-time scheduling requirements of the cascade hydropower station system. This study also presents a comparatively comprehensive introduction to all solving algorithms that have ever been adopted in the multi-time scale coordinated and optimized scheduling model. Based on that, some practical and efficient solving algorithms are developed for the characteristics of the scheduling model, including the coupled iterative method of alternating reservoirs (CIMAR)—the improved dynamic programming (IDP) algorithm and the improved genetic algorithm (IGA). In addition, optimized-scheduling solutions were generated by each of the three algorithms and were compared in terms of their convergence rate, calculation time, electric energy generated, and standard deviation of the algorithm. The results based on the Cascade Scheduling and Communication System (CSCS) of Three Gorges–Gezhouba, China, which includes two interlinked mega-scale reservoir projects, show that scheduling models have better efficiency and good convergence, and more importantly, the maximization of the power generation benefits of the hydropower plants has been achieved without violating any of the reservoir scheduling regulations

Hierarchical prediction of industrial water demand based on refined Laspeyres decomposition analysis

A recent study decomposed the changes in industrial water use into three hierarchies (output, technology, and structure) using a refined Laspeyres decomposition model, and found monotonous and exclusive trends in the output and technology hierarchies. Based on that research, this study proposes a hierarchical prediction approach to forecast future industrial water demand. Three water demand scenarios (high, medium, and low) were then established based on potential future industrial structural adjustments, and used to predict water demand for the structural hierarchy. The predictive results of this approach were compared with results from a grey prediction model (GPM (1, 1)). The comparison shows that the results of the two approaches were basically identical, differing by less than 10%. Taking Tianjin, China, as a case, and using data from 2003-2012, this study predicts that industrial water demand will continuously increase, reaching 580 million m(3), 776.4 million m(3), and approximately 1.09 billion m(3) by the years 2015, 2020 and 2025 respectively. It is concluded that Tianjin will soon face another water crisis if no immediate measures are taken. This study recommends that Tianjin adjust its industrial structure with water savings as the main objective, and actively seek new sources of water to increase its supply