Journal of Hydroelectric Engineering

水力发电学报

Office Online

Included Databases

The journal is included in the following databases:
(i)Scopus,
(ii)The Chinese Science Citation Database Source Journals,
(iii)The Chinese Science Journal Abstract Database,
(iv)The Chinese Science and Technology Papers Statistics and Analysis Database,
(v)China Newspaper Subscription Guide Information Database,
(vi)Chinese Academic Journals (CD).


2023 Vol. 42, No. 10 Published: 2023-10-25

	1	Hydro-wind-solar power complementary short-term optimal scheduling considering participation of price-based demand response ^Hot!
		JIANG Guangzi, PENG Yang, JI Changming, LUO Shiqi, YU Xianliang
		DOI: 10.11660/slfdxb.20231001
		As the scale of wind and photovoltaic energy integration increases, it is more difficult to satisfy the needs of large-scale new energy integration by only using hydropower and other peak-shaving resources on the power source side. To address this issue, we develop a short-term optimization model for hydro-wind-solar power complementary scheduling considering participation of the price-based demand response (PDR), which adjusts optimally the next-day load curve using PDR on the load side. And this model is decomposed into two sub-models of single target optimization, and solved in stages to reduce solution difficulty. Finally, it is applied to the system of the Wudongde hydropower station and the wind and photovoltaic power stations in Kunming and Yuxi. The results show that PDR has an obvious peak-load shifting effect on the load curve, so it not only can improve the source-load matching, but also can enhance the accommodation capacity of wind and solar power and increase the system’s total power generation. This demonstrates the effectiveness of the model and a new idea for the large-scale accommodation of new energy in the power grid.
		2023 Vol. 42 (10): 1-12 [Abstract] ( 81 ) PDF (3495 KB) ( 326 )

	13	Technology framework and association modes of renewable energy systems. Empirical research on international patent data
		XIONG Qian, TANG Wenzhe, LI Yinsheng
		DOI: 10.11660/slfdxb.20231002
		Establishing a stable, efficient, and intelligent renewable energy system is important for promoting energy transition. Based on the patents of renewable energy systems, this study sorts out the technology framework systematically and uses social network analysis to reveal the current status and dynamic characteristics of technology associations in China and abroad. The results show an increasing trend has occurred recently in the number of patents related to renewable energy generation, energy storage, multi-energy complementation, and smart grids. Technologies for renewable energy systems can be divided into three categories－energy acquisition and application, energy conversion, and energy system construction－covering 13 technology fields. Compared with other countries, the technology network density in China continues to rise; most of its technology associations are in two modes－“energy acquisition and utilization - energy conversion” and “energy conversion - energy systems construction”. The technology network density in Japan is relatively low, and the latter mode dominates its technology associations. The United States has a high level of technology network density in recent years, and most of its technology association modes are shifting from the former to the latter. These findings not only serve as empirical references for technology innovation and integration in renewable energy development, but also provide practical implications for collaboration between energy industries.
		2023 Vol. 42 (10): 13-26 [Abstract] ( 94 ) PDF (3586 KB) ( 307 )

	27	Study on water supply risk transfer laws based on infectious disease dynamic model
		XI Jiayi, XUE Xiaojie, BAI Tao, LI Xiong, XU Dongping
		DOI: 10.11660/slfdxb.20231003
		Inter-basin water transfer projects suffer from the issues of unclear water supply risk transfer laws and unsatisfactory dynamic risk management effect. To explore the risk transfer law, this paper identifies risk factors, quantifies the risks using the expert scoring and mutation coefficient method, and develops a water supply risk transfer model based on the infectious disease dynamics. We have applied this model in a case study of the initial stage of the Hanjiang-to-Weihe River Water Diversion Project, and examined six risk schemes to reveal its risk transfer law. The results show the number of months under water supply risks is positively correlated with the number of risk sources. When the runoff forecast error risk is not considered, an earlier implementation of the optimal operation measures leads to a shorter water supply risk period and a higher recovery level; When the error risk is considered, the control effect of optimal operation measures on water supply risks is insignificant. No positive correlation is observed between the risk transfer capability and the number of risks; risk damage is positively correlated with the number of risk sources. The results are of great significance for prevention and control of water supply risks and risk reduction and control programs of a water diversion project.
		2023 Vol. 42 (10): 27-39 [Abstract] ( 64 ) PDF (1804 KB) ( 337 )

	40	Multi-time scale complementarity analysis of hydropower, wind power and photoelectric resources in lower reaches of Jinsha River
		TIAN Lu, MING Bo, ZHANG Wei, HUANG Kangdi
		DOI: 10.11660/slfdxb.20231004
		Complementarity analysis of various energy sources is a basis for scientific planning of large wind power and photovoltaic bases. In this paper, a complementary evaluation index system based on a volatility description is formulated, and a multi-time scale analysis of the complementarity of hydropower, wind power and photoelectric is made for the study area: a hydropower, wind power and photoelectric-integrated clean energy base in the lower reaches of the Jinsha River. The results show that the power distribution trends of wind power and photovoltaic power－obtained from Greenwich and PhotoVoltaic Geographic Information System (PVGIS)－agree with the measured sequence, which have high reliability. The complementarity of wind power and photovoltaic is weak, and its probabilities are only 25.5%, 0.0% and 37.2% in intra-day, intra-year and inter-year scales, respectively. Runoff, wind power and photovoltaic are highly complementary, and the probabilities raise to 46.5%, 100.0% and 53.5% in the three scales, respectively.
		2023 Vol. 42 (10): 40-49 [Abstract] ( 111 ) PDF (2967 KB) ( 319 )

	50	Extracting optimal operation rules for Yalong River cascade reservoirs
		ZHONG Sirui, HE Yanfeng, GUO Shenglian, XIE Yuzuo, YU Chuntao, MA Shungang, ZENG Qiang
		DOI: 10.11660/slfdxb.20231005
		A deterministic model of reservoir optimal operation is usually difficult to be directly applied to practical operation. To improve applicability, we develop a new joint optimal operation model for the Yalong River cascade reservoirs and use the Gaussian radial basis function (RBF) to extract operation rules, and then calibrate the rule and verify its fitting errors. The results show the annual power generation of the cascade is increased by 98.32 billion kW?h or an increase of 8.73% compared with its design value. The new operation processes optimized by the model for the Lianghekou, Jinping I and Ertan reservoirs follow certain common patterns. The determination coefficient of Gaussian RBFs is larger than 90%, and it can fit the operation rules effectively. This achieves a simulated power generation greater than the design value by 51.27 billion kW?h (+5.67%).
		2023 Vol. 42 (10): 50-59 [Abstract] ( 93 ) PDF (1113 KB) ( 331 )

	60	Analysis of attribution of hydrological drought in Nenjiang River basin and its future evolution trends
		MEN Baohui, PANG Jinfeng, ZHANG Teng, JIANG Meitong
		DOI: 10.11660/slfdxb.20231006
		Under the influences of climate change and human activities, the Nenjiang River basin has suffered floods and droughts frequently. This study constructs a distributed hydrological model for this basin and a set of standard runoff drought indexes (SRIs) over various time scales, using its 1980-2013 runoff data measured at the hydrological stations of Shihuiyao, Tongmeng, Jiangqiao, and Dalai. Coupling the Budyko theory and the hydrological simulation method, we conduct an attribution analysis on the changes in its runoff and hydrological drought characteristics caused by the construction and operation of the Nirki reservoir. And how the hydrological drought will evolve in the future is explored using the Coupled Model Intercomparison Project in the sixth phase (CMIP6). Our findings reveal that on an annual scale, human activities are the dominant factor contributing as much as 80% to runoff evolution. The hydrological drought characteristics in the basin manifest a general trend of intensification from its upstream to downstream, with its upstream region primarily influenced by climate change and downstream region by human activities. Under future climate scenarios, its SRI sequence demonstrates an intensified volatility with an alternating dry and wet pattern; its drought duration will be increasing, indicating an elevated risk of future drought in the whole basin.
		2023 Vol. 42 (10): 60-74 [Abstract] ( 82 ) PDF (5986 KB) ( 173 )

	75	Joint information entropy mathematical model for droplet formation in flood discharge atomization
		PENG Yanxiang, ZHANG Hua, HE Guicheng
		DOI: 10.11660/slfdxb.20231007
		When a high-speed water jet impacts the surface of downstream water, a large number of moving water droplets are generated in the downstream space. How to determine the size distribution of these water droplets has become an important scientific issue. In meteorology, various types of rainfall droplet spectra are often fitted using the Gamma distribution. Such a distribution is also frequently adopted in the modeling of droplet sizes in flood discharge atomization. However, this method lacks physical significance and its computational accuracy is limited. To overcome the shortcomings, this paper develops a joint information entropy distribution model of water droplets in a non-equilibrium open system based on the maximum entropy increase method, and formulates an error function method to solve the model parameters. The results show that in calculation of the droplet size probability density in jet flow discharge, this model has the best agreement with experimental data, compared with the Gamma distribution method or the traditional maximum entropy distributions. Under different operating conditions, the determination coefficient of its calculations is 3.5% and 25.3% higher than the other two methods respectively, and the root mean square error is 72.4% and 79.0% lower respectively; Under different operating conditions, there exists an equal proportional relationship between the average droplet diameters. This shows our new method would lay a theoretical basis for predicting the particle size distribution of flood discharge atomization.
		2023 Vol. 42 (10): 75-85 [Abstract] ( 50 ) PDF (633 KB) ( 182 )

	86	Vibration fault diagnosis of hydropower units based on IMF energy moment and BiLSTMNN
		DENG Xiaoqin, QU Weihua, CHEN Jinbao, WANG Yunhe, ZOU Yidong, HU Wenqing, XIAO Zhihuai
		DOI: 10.11660/slfdxb.20231008
		Aimed at the nonstationary and nonlinear vibration signals of hydropower units, a fault identification method is constructed combining the IMF energy moment and the bi-direction long short-term memory neural network (BiLSTMNN). First, we use the complementary ensemble empirical mode decomposition (CEEMD) method to process the normal and fault vibration signals from a hydropower unit, and obtain the intrinsic mode functions (IMF) and the residual components with different frequencies. Then, the IMF energy moment is calculated and used as the fault feature. And we use the fault features as inputs and the fault categories as outputs, and train BiLSTMNN to obtain a fault identifier for the unit. The operation state of the unit can be identified as a normal or specific fault type by combining this identifier with the IMF energy moment characteristics of the real-time signals. Finally, two sets of comparative experiments are designed based on the sample data collected on a rotor test stand and from the on-site observation of a hydropower unit. The results show our new method is effective in mining signal features and can achieve a high accuracy of fault diagnosis.
		2023 Vol. 42 (10): 86-95 [Abstract] ( 74 ) PDF (3722 KB) ( 243 )

	96	Analysis of vibration transmission path of pipeline embankment structure based on transfer entropy
		ZHANG Jianwei, XING Shuai, JIANG Qi, YE Hexin
		DOI: 10.11660/slfdxb.20231009
		Pipeline embankment is a complex engineering structure; its coupled vibration of the "water flow-pipeline-embankment" trinity during operation－usually coupled with noise interference caused by multi-source excitation－makes it more difficult to identify its vibration transmission path. This paper presents a vibration path analysis for pipeline embankment structures based on the combination of the transfer entropy theory and VMD-SVD noise reduction method, with application to an embankment crossing pipeline project in Guangdong. First, a vibration source analysis is conducted, and the effectiveness of the transfer entropy method is verified through the simulated signals. Then, the VMD-SVD combined filtering method is used to determine adaptively the order of each IMF separated from the vibration test signal and to filter out vibration noise. Finally, based on the theory of transfer entropy, the vibration transmission path of the pipeline embankment structure is identified, and its correctness and efficacy are verified quantitatively with the help of information transmission rate. The results show that irregular vibration starts from the pumping station unit and gradually propagates outward along the pipeline axis. For the pipeline section passing over the embankment, 42.4% of its vibration energy is transmitted to the upper covering soil layer, and only 37.6% continues to propagate downward along the pipeline axis. This study helps identify the key nodes of vibration transmission in pipeline embankments, and is useful for the operation and management of pipeline embankments.
		2023 Vol. 42 (10): 96-104 [Abstract] ( 44 ) PDF (819 KB) ( 242 )

	105	Buckling characteristics of penstocks with composite lining under complex constraints
		WANG Hanhui, SU Kai, ZHANG Cunhui, WANG Boshi
		DOI: 10.11660/slfdxb.20231010
		The critical elastic solution of stiffened penstocks under external pressure is calculated based on the Mises theory to study the buckling characteristics of a penstock with composite lining and partial drainage board laying. Then, we consider variations in constraint strength, material nonlinearity, and the non-uniformity of the surrounding medium, and develop a three-dimensional numerical model of composite lining based on ABAQUS. This model is applied to a comprehensive study on the critical instability characteristics of the penstock under the local constraints of the surrounding medium, and comparison is made with the tunnel exposed penstock scheme and the underground penstock scheme. The results show that the constraint effect of self-compacting concrete improves the penstock’s external pressure resistance, while the existence of drainage board reduces its resistance. The Mises solution adopted in the standard is suitable for the stability design of penstocks under external pressure with full-circle external constraints. After the local drainage board is laid, the penstock's critical buckling pressure is close to that of the tunnel exposed penstock scheme, both showing multi-wave instability. Thus, for the penstock with composite lining, we recommend the constraint effect is not necessary to be considered in its buckling stability design.
		2023 Vol. 42 (10): 105-115 [Abstract] ( 45 ) PDF (4193 KB) ( 155 )

	116	Study on instability simulation of soil-rock slope and anti-sliding effect of array baffles
		MA Chunhui, CHEN Lei, YANG Jie, LI Nian, XU Xiaoyan
		DOI: 10.11660/slfdxb.20231011
		During the construction of pumped storage power stations, numerous large soil and rock slopes have been formed, and their stability seriously affect the reliable operation of the projects. We use a three-dimensional discrete element simulation method to study the instability process and impact range of the slopes, reflecting more accurately the characteristics of soil and stone materials and the large deformation characteristics of slope instability and the anti-sliding effect of baffles. Based on the accumulation forms and velocity variation patterns of sliding bodies, the instability of soil and rock slopes is divided into four stages: rapid sliding, secondary sliding, stable sliding, and creep sliding. By monitoring the velocity and energy evolution of particles at different positions, the impact of slope instability without protective measures on the downstream rivers and buildings is analyzed. By developing discrete element simulation schemes for rectangular, circular, and triangular cross-sections of the array baffles, an evaluation system for their anti-sliding effect is constructed, including multiple evaluation indicators such as impact force, stacking velocity, stacking displacement, and their interception capacity. After comprehensive analysis, we recommend that triangular cross-section array baffles be adopted for the soil and rock slope engineering of the Zhen'an pumped storage power station. This study is thought to be useful for instability simulation and protection design of similar slope engineering.
		2023 Vol. 42 (10): 116-127 [Abstract] ( 63 ) PDF (3735 KB) ( 229 )

	128	Improved DSAE model for anomaly detection of dam seepage safety monitoring data
		YU Hongling, WANG Xiaoling, CHENG Zhengfei, YU Jialin, WU Guohua, ZHENG Mingwei
		DOI: 10.11660/slfdxb.20231012
		Dam seepage safety monitoring suffers a drawback of low detection efficiency and low accuracy by previous abnormal detection methods, and a problem that most of them fail to consider comprehensively the randomness and fuzziness of monitoring data in formulating the abnormal threshold values. This paper presents an improved deep sparse autoencoder (DSAE) method for the anomaly detection of dam seepage safety monitoring data. This method optimizes the hyperparameters of DSAE by using the improved Aquila optimization (IAO) algorithm based on chaotic initialization and nonlinear flight rate, and extracting residual component of monitoring data by the singular spectrum analysis method. The new IAO-DSAE method so obtained can realize a high-precision reconstruction of the residual components of monitoring data. To improve the reliability of anomaly detection, we modify the process of anomaly threshold formulation by adopting the expectation and entropy of the reverse cloud algorithm in replacement of the mean and standard deviation used in the traditional 3σ method, so as to achieve a comprehensive consideration of the influence of randomness and fuzziness of monitoring data on the formulation. An engineering case study shows that compared with the anomaly detection methods based on statistical model method and 3σ method, the prediction based on the seepage safety monitoring data that are processed by our new method can raise the accuracy by 5.56% and 6.99%, respectively, verifying the applicability and effectiveness of the new method.
		2023 Vol. 42 (10): 128-138 [Abstract] ( 83 ) PDF (5243 KB) ( 192 )

	139	Deformation prediction model of concrete faced rockfill dams based on factor fusion
		LIN Chuan, GUI Xingyu, ZHU Lüyun, SU Yan, LIN Mengjing, TANG Yanfang, CHEN Wei
		DOI: 10.11660/slfdxb.20231013
		The measured deformation of a concrete faced rockfill dam is highly nonlinear and complicated, owing to a variety of influential factors and the collinearity among them. To improve the deformation prediction in dam analysis, this paper develops a deformation prediction model of concrete faced rockfill dams based on the factor fusion. First, we use the variational mode decomposition to decompose a deformation time series so as to effectively reduce its complexity and enhances feature extraction. Next, we employ the partial least square regression to reduce and fuse the influential factors of deformation, reducing the impact of multicollinearity between independent variables on model construction and enhancing model interpretability. Finally, we reconstruct and predict the subsequences using a one-dimensional convolutional network fused with a gated recurrent unit neural network. Analyses of certain real projects show our model greatly improves the efficiency and accuracy of deformation prediction for concrete faced rockfill dams, and is also useful for deformation monitoring and analysis of similar dams.
		2023 Vol. 42 (10): 139-152 [Abstract] ( 67 ) PDF (4265 KB) ( 274 )