Operation Of Hydropower Stations Research Articles

An integrated analysis of transcriptome and metabolome to reveal the effects of temperature stress on energy metabolism and physiological responses in Schizothorax wangchiachii muscles

The unique hydrological situation of Jinsha River and the construction and operation of large hydropower stations may cause resident Schizothorax wangchiachii to experience acute changes in water temperature. To reveal the response mechanisms of S. wangchiachii to high and low temperature stress, we conducted a stress experiment. Compared with the control group, the activity of antioxidant enzymes (SOD\\CAT) increased first and then decreased at high temperature, while MDA activity in the low temperature group continued to increase slowly. The activities of glycolytic enzymes were increased initially and then decreased including HK and PFK, but PK activity continued to increase throughout the stress period. Transcriptome sequencing showed that a large number of genes in muscle tissues were differentially expressed after high and low temperature stress, and the main enriched pathways included glycosaminoglycan biosynthesis, lysine degradation, glycerolipid metabolism, the PPAR signaling pathway, and the adipocytokine signaling pathway. Significant metabolic pathways were identified as enriched according to the metabolic differences,such as glycerophospholipid metabolism, qRT-PCR was used to verify gene expression. The results suggested that both high temperature and low temperature stress induced physiological responses in S. wangchiachii that maintained homeostasis by regulating glucolipid metabolism and amino acid degradation. This study revealed the response mechanisms of S. wangchiachii to high and low temperature stress, information that may serve as a reference for the study of responses in other fish to environmental changes in the upper reaches of the Yangtze River or where they are displaced by hydropower station construction.

How does the daily regulation hydropower station reduce the hydrological regime impact? A case study in upper Yellow River

ABSTRACT Human activities, particularly the regulation of hydropower stations, have profoundly altered river flow patterns. While studies have extensively assessed the impact of large or multi-year regulated hydropower stations on hydrological regimes using indicators of hydrological alteration (IHA) and range of variability approach (RVA), the impact of daily regulation hydropower stations has received comparatively less attention. This study aims to evaluate the influence of daily regulation hydropower stations on hydrological regime changes, focusing on the upper Yellow River region in China. Using daily runoff data from 1954 to 2020 at the Guide station, the study compares the impacts of multi-year regulated (Longyangxia) and daily regulation (Laxiwa and Nina) hydropower stations. The Mann-Kendall test showed that 27 out of 32 Indicators of Hydrological Alteration (IHAs) had significant trends under Longyangxia operation, which reduced to 18 IHAs with the inclusion of daily regulation stations. The Range of Variability Approach (RVA) revealed that only 46.87% of IHAs exhibited high alteration from the natural regime when daily regulation was considered, down from 75.00% with Longyangxia alone. This suggests that daily regulation can mitigate the negative impacts of multi-year regulation, potentially enhancing the river's eco-hydrological health.

Intelligent Low-Consumption Optimization Strategies: Economic Operation of Hydropower Stations Based on Improved LSTM and Random Forest Machine Learning Algorithm

The economic operation of hydropower stations has the potential to increase water use efficiency. However, there are some challenges, such as the fixed and unchangeable flow characteristic curve of the hydraulic turbines, and the large number of variables in optimal load distribution, which limit the progress of research. In this paper, we propose a new optimal method of the economic operation of hydropower stations based on improved Long Short-Term Memory neural network (I-LSTM) and Random Forest (RF) algorithm. Firstly, in order to accurately estimate the water consumption, the LSTM model’s hyperparameters are optimized using improved particle swarm optimization, and the I-LSTM method is proposed to fit the flow characteristic curve of the hydraulic turbines. Secondly, the Random Forest machine learning algorithm is introduced to establish a load-distribution model with its powerful feature extraction and learning ability. To improve the accuracy of the load-distribution model, we use the K-means algorithm to cluster the historical data and optimize the parameters of the Random Forest model. A Hydropower Station in China is selected for a case study. It is shown that (1) the I-LSTM method fits the operating characteristics under various working conditions and actual operating characteristics of hydraulic turbines, ensuring that they are closest to the actual operating state; (2) the I-LSTM method is compared with Support Vector Machine (SVM), Extreme Learning Machine (ELM) and Long Short-Term Memory neural network (LSTM). The prediction results of SVM have a large error, but compared with ELM and LSTM, MSE is reduced by about 46% and 38% respectively. MAE is reduced by about 25% and 21%, respectively. RMSE is reduced by about 27% and 24%, respectively; (3) the RF algorithm performs better than the traditional dynamic programming algorithm in load distribution. With the passage of time and the increase in training samples, the prediction accuracy of the Random Forest model has steadily improved, which helps to achieve optimal operation of the units, reducing their average total water consumption by 1.24%. This study provides strong support for the application of intelligent low-consumption optimization strategies in hydropower fields, which can bring higher economic benefits and resource savings to renewable energy production.

Analysis of Surrounding Rock Stability and Supporting Structure Effect Based on a Hydropower Station Underground Cavern

The surrounding rock stability is a main difficult problem in the hydropower station construction and operation. Taking one hydropower station as object, FLAC 3D numerical simulation software was used to calculate the changes in surrounding rock failure zone distribution, surrounding rock strain, and block safety factor before and after supporting. The stability of the surrounding rock after excavation was analyzed and effect of the supporting structure was also evaluated. Finding that: the supporting structure can effectively improve the stability of surrounding rock. After supporting, the failure zone range, the deformation of surrounding rock, and the internal force of the supporting structure all reduced, while the safety factor of the block improved. Due to the effect of bolt, the deformation of the surrounding rock transformed from plastic to elastic, and the rebound zone of the surrounding rock increased, while the plastic and failure zone reduced. The depth of the failure zone on the downstream side is greater than that on the upstream side, and a large number of cracking zones are distributed on the downstream side. At the same time, due to the influence of cracks and geological fracture, the failure of surrounding rock around the main powerhouse is higher than that around the tailgate chamber higher than that in the main transformer chamber. The safety factor of the key blocks distributed around the main transformer chamber and the main power house improved, the sliding form of some blocks transformed from collapse to single-surface sliding.

Deformation Characteristics and Stability Prediction of Mala Landslide at Miaowei Hydropower Station under Hydrodynamic Action

In recent years, with the completion of the construction of large-scale hydropower projects in China, a series of engineering geological problems that occurred during the operation of the hydropower station have become an important issue affecting the normal operation of hydropower stations. Landslides on reservoir slopes triggered especially by water storage and other factors related to the construction of hydropower stations seriously affect the normal operation of the hydropower station and lead to other geological disasters. Research indicates that many reservoir-area landslides are triggered by hydrodynamic forces resulting from water level fluctuations in hydroelectric power stations. The Mala landslide of Miaowei Hydropower Station in the Lancang River Basin of China is taken as the engineering example to study the influence of hydrodynamic forces on the deformation characteristics and stability trends of the landslide. This paper explores the formation mechanism and influencing factors of the Mala landslide by conducting a field investigation of the Mala landslide and analyzing the monitoring data. Additionally, this paper also discusses the impacts of water storage, rainfall, and engineering construction on landslide induction. It is considered that the evolution of the Mala landslide from the initial stage of water storage to the current state mainly includes four stages: small-scale bank collapse stage, creep deformation stage, accelerated sliding stage, and uniform sliding stage. Moreover, the changes in the trend of landslide stability are analyzed using the two-dimensional finite element method. The research results provide a valuable reference for understanding the formation mechanism and predicting the deformation of reservoir landslides, which has considerable engineering practical significance.

Prediction of Tail Water Level under the Influence of Backwater Effect Based on Deep Learning Models: A Case Study in the Xiangjiaba Hydropower Station

Accurate forecasting of the tail water level (TWL) is of great importance for the safe and economic operation of hydropower stations. The prediction accuracy is significantly influenced by the backwater effect of downstream tributaries and the operation of adjacent hydropower stations, but the explicit quantification method of the backwater effect is lacking. In this study, a deep-learning-model-based forecasting method for TWL predictions under the backwater effect is developed and applied in the Xiangjiaba (XJB) hydropower station, which is influenced by the backwater effect of downstream tributaries, including the Hengjiang River (HJR) and the Minjiang River (MJR). Firstly, the random forest algorithm was used to analyze the influence of HJR and MJR flows with different lag times on the TWL prediction error of the XJB hydropower station. The results show that the time lags of the backwater effect of HJR and MJR run offs on the TWL of the XJB are 5~7 h and 1~2 h, respectively. Then, the run off thresholds of the HJR and MJR for impacting the TWL of the XJB station are obtained through scenario comparison, and the results show that the run off thresholds of the HJR and the MJR are 700 m3/s and 7000 m3/s, respectively. Finally, based on the analysis of the time lag and the threshold of the backwater effect, a deep learning model (LSTM)-based TWL forecasting method is established and applied to predict the TWL of the XJB station. The results show that the forecasting model has a good predictive performance, with 98.22% of absolute errors less than 20 cm. The mean absolute error over the validation dataset is 5.27 cm, and the maximum absolute error is 63.35 cm. Compared with the LSTM-based prediction model without considering the backwater effect, the mean absolute error decreased by 31%, and the maximum absolute error decreased by 71%.

A two-dimensional model for jet splashing rainfall intensity distribution in dam discharge based on laboratory experiments

Flood discharge atomization is a phenomenon of water droplets and mist diffusion caused by dam discharge, which brings heavy rainfall around the dam. The unnatural rainfall is harmful to the safe operation of hydropower stations and the stability of slopes. Jet splashing is the most important factor in the formation of flood discharge atomization. The splashing rainfall intensity and diffusion region are highly dependent on the jet impingement conditions. In this study, a two-dimensional splashing model is derived that describes the splashing rainfall distribution when a jet impinges on a plunge pool surface in terms of the jet impingement conditions. Given the close relationship between the splashing rainfall intensity distribution and the motion trajectories of droplets, it is hypothesized that certain droplet trajectories can accurately represent the distribution of rainfall intensity. The characteristic ejection angle of splashing droplets and the splashing diffusion coefficient are introduced to estimate the characteristic trajectories of droplets. Experimental data from laboratory tests are used to estimate the parameters of the splashing model. The current predictions are compared with the data from laboratory tests and prototype observations. The results suggest that the model accurately predicts the relative rainfall intensity at the upper region of the predicted curves, which corresponds to approximately 1/10 of the total height of the ideal parabola.

Analysis of the suitable ecological flow of benthic animals in the lower reaches of Xiangjiaba Reservoir in the upper reaches of the Yangtze River based on the physical habitat model

Abundant water resources have facilitated the completion and operation of numerous large-scale water conservation projects. However, the operation of cascade hydropower stations has changed the natural hydrological regime of rivers, thereby affecting the integrity and stability of downstream benthic animal habitats. To quantitatively evaluate the impact of infrastructure development, we proposed a coupling of hydrodynamic and habitat models, with benthic animals as indicator species (because they are highly sensitive to hydrological changes). This study established a physical habitat model of benthic animals in the upper reaches of the Yangtze River, from the Xiangjiaba to Zhutuo sections by coupling the MIKE21 hydrodynamic model with a habitat model. This model coupled the changes in hydrological conditions and ecological processes to quantitatively reflect the effects of flow changes on river habitat quality, which can be used to predict the effects of hydrological changes on water ecosystems and provide fundamental information for ecological flow and scheduling decisions. Our results showed that by jointly regulating the suitable outflow of the Xiangjiaba Reservoir and the inflow of the Tuojiang, Minjiang, and Hengjiang rivers (three tributaries with water conservancy projects), the minimum flow in the non-flood season and the maximum flow in the flood season could be controlled more precisely. This increases the suitable habitat area for benthic animals as well as improves the stability of their habitat. This study fills the gap in the physical habitat model of benthic animals in the upper reaches of the Yangtze River as well as enriches the research ideas of ecological flow regulation. Moreover, this indicates the first application of the physical habitat model to the joint ecological flow regulation of the main tributaries, thus opening new directions for the application of the physical habitat model.

Optimization of Cascade Small Hydropower Station Operation in the Jianhe River Basin Using a One-Dimensional Hydrodynamic Model

Hydropower development brings benefits in terms of power generation and flood control, but it also has inevitable ecological impacts. These impacts must be considered and addressed in order to ensure sustainable development and minimize harm to the environment. This study utilized the MIKE 11 HD modeling system to construct a hydrological and hydrodynamic model of the Jianhe River basin. The model incorporates the flow demand of ecologically sensitive targets for scheduling purposes and was calibrated and validated using hydrological data from 2014 to 2022. The hydrodynamic model was then applied to analyze the evolution characteristics of the water level in the main stream of the Jianhe River, identify key areas and periods for hydropower station operation, and calculate the minimum ecological water requirement using verification and estimation methods. Based on these findings, an ecological dispatching scheme for the cascade hydropower stations in the Jianhe River basin was developed. The results demonstrate satisfactory performance of the constructed NAM model for rainfall runoff and the 1D hydrodynamic MIKE 11 HD model for the Jianhe River basin. The deterministic coefficients exceed 0.8, and the relative errors in the total water volume are below 5.5%. The critical time and space interval for hydropower station operation in the main stream of the Jianhe River is identified as December to February of the following year, with the highest risk of flow interruption occurring in January, primarily concentrated between the Duoluo II and Huahai hydropower stations. If the appropriate dispatching scheme is not implemented in the areas prone to flow interruption during critical periods, it will have a negative impact on the ecological environment. These findings provide a scientific basis and decision support for developing multi-objective ecological flow guarantee schemes for rivers.

A Parameter Sensitivity Analysis of Hydropower Units under Full Operating Conditions Considering Turbine Nonlinearity

A parameter sensitivity analysis is an important part of the stability study of hydro turbine regulation systems, which helps operators to deepen their understanding of the characteristics and connections among the various parts of these systems. Considering that large hydropower stations undertake an essential regulation task in the power grid, the safety and stability of their operation cannot be ignored. To this end, taking a unit in a giant hydropower station in China as an example, a hydraulic–mechanical–electrical coupling model of the hydraulic turbine regulation system is established. A comprehensive parameter sensitivity indicator and parameter sensitivity analysis framework are proposed. On this basis, the sensitivity of the main system variables to parameter changes under full operating conditions is investigated by considering two different control modes of the unit (i.e., corresponding to different grid types). The results show that the sensitivity of the system state to the mechanical parameters of the generator is the highest in the power control mode, while the sensitivity to the electrical parameters of the generator and excitation system is higher in the frequency control mode. The sensitivity of the system with these key parameters also shows different patterns of change with a change in the unit operating conditions. The relevant findings can provide some theoretical guidance for the operation of hydropower stations and help to reduce the risk of system instability.

Discussion on the monotonicity principle of the two-stage problem in joint optimal operation of cascade hydropower stations

The joint optimal dispatching of cascade hydropower stations aims to maximize economic benefits while satisfying various constraints. However, numerous studies have failed to acknowledge the significance of the intrinsic optimization principle and lack discussion on this issue. This study started with a mathematical principle analysis of the optimization problem and studied the optimality principle puzzle of the joint optimal dispatching of cascade hydropower stations. First, a two-stage optimization problem was constructed to describe the relationship between the variation in discharge and the incremental function of the total energy generation of the reservoir. Subsequently, the first and second derivatives of the cascade total generating capacity increment to cascade reservoir discharge variation were derived, and the existence condition of monotonically decreasing the first derivative was proposed. Moreover, the monotonicity principle was proven through numerical simulations by comparing the optimization results of POA and the monotonicity principle coupled IPOA in the cascade hydropower stations operation of the Jinsha River, it was found that in terms of power generation and computational efficiency, IPOA is superior to POA. Finally, using this optimization principle, the optimal operation mode of the two typical cascade reservoirs was analyzed in the case studies. The example results show that the proposed optimal principle can theoretically analyze and clarify the optimal operation mode of cascade reservoirs, and the operation modes of the two typical cascade reservoirs can provide guidance and reference for the operation modes of cascade reservoirs in real life.

Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models

Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models

Reconstruction of integrated hydraulic turbine characteristics curve based on classification weight neural network

To address the shortcomings in the drawing and processing of comprehensive characteristic curves of hydraulic turbines and the problems in the operation and management of small hydropower stations, this paper proposes a method for reconstructing the comprehensive characteristic curves based on classification weight neural network. Firstly, this study discretizes the comprehensive characteristic curve of the target turbine factory package to obtain multiple sets of discrete data points, and compares them with the actual operating data of small hydropower plants, and then pre-processes the operating data by the type and operating characteristics of the unit. Next, this paper uses XGBoost to classify the two types of data to obtain the leaf node optimal scores and uses the scores as the prediction weights of the deep neural network to grid the discrete points of the hydraulic turbine for prediction, and finally obtains the specific integrated characteristic graph of the unit. The method based on classification weight neural network can substantially improve the accuracy and reliability of composite characteristic curves while avoiding multivariate nonlinear mathematical problems, which provides a new method and idea for the reconstruction and expansion of the hydraulic turbine characteristic curve, and also provides a theoretical basis for the safe and economic operation of hydropower units.

Existence of hidden attractors in nonlinear hydro-turbine governing systems and its stability analysis

This work studies the stability and hidden dynamics of the nonlinear hydro-turbine governing system with an output limiting link, and propose a new six-dimensional system, which exhibits some hidden attractors. The parameter switching algorithm is used to numerically study the dynamic behaviors of the system. Moreover, it is investigated that for some parameters the system with a stable equilibrium point can generate strange hidden attractors. A self-excited attractor with the change of its parameters is also recognized. In addition, numerical simulations are carried out to analyze the dynamic behaviors of the proposed system by using the Lyapunov exponent spectra, Lyapunov dimensions, bifurcation diagrams, phase space orbits, and basins of attraction. Consequently, the findings in this work show that the basins of hidden attractors are tiny for which the standard computational procedure for localization is unavailable. These simulation results are conducive to better understanding of hidden chaotic attractors in higher-dimensional dynamical systems, and are also of great significance in revealing chaotic oscillations such as uncontrolled speed adjustment in the operation of hydropower station due to small changes of initial values.

An integrated method to identify and evaluate the impact of hydropower development on terrestrial ecosystem

Hydropower development has an important impact on the growth of vegetation in the basin, identifying and assessing the impact of engineering factors on vegetation dynamics is essential for sustainable watershed ecosystem management. In the paper, a integrated method coupling with Bfast, Theil-Sen Median and Mann-Kendall methods based on remote sensing was developed to identify the time and magnitude of abrupt changes for NDVI, judge the NDVI change trend and detect their potential drivers. Results showed that times of major abrupt changes of NDVI for areas around Wudongde, Baihetan, Xiluodu and Xiangjiaba hydropower stations were consistent with the construction and operation time of hydropower stations and the abrupt climate change time in the statistical yearbook. The proportion of areas with positive abrupt changes of NDVI around two early operational hydropower stations with 42.9 and 26.1% were higher than those around two newly operational hydropower stations with 12.9 and 25.8%. Results obtained from Theil-Sen Median and Mann-Kendall methods showed that areas with improved vegetation coverage for two early operational hydropower stations accounted for 83.99 and 80.21%. And those areas were mainly distributed along river direction (both sides of Jinsha river). Only 9.66 and 11.43% of areas had degraded vegetation, which indicated that the operation of hydropower stations can contribute to the recovery of regional NDVI. Results also indicated that the climate change may be a potential factor to promote regional vegetation growth. But, the growth rate of vegetation reached 0.000018 and 0.000024 caused by hydropower station operation was far higher than that between 0.000008 and 0.000010 caused by climate change. This work provides an important theoretical and technical support for ecological impact assessment of climate change and engineering construction.

A mixed-integer linear programming model for hydro unit commitment considering operation constraint priorities

Optimizing hydro unit commitment (HUC) has the potential to improve water use efficiency, but should consider complex constraints from power grid, hydropower station and unit operation. When confronted with extreme operating conditions, conflicting constraints cannot be satisfied simultaneously, resulting in no feasible solution. To overcome this drawback, the constraint grading principle is proposed to illustrate how to convert hard constraints into soft constraints and rank them in priority levels. Soft constraints are destroyed according to priority levels from low to high to obtain a feasible solution, simultaneously minimizing the damage degree of soft constraints. Based on the principle, the HUC model considering operation constraint priorities is proposed. When the initial model fails to obtain a feasible solution, low-priority soft constraints are destroyed automatically. Finally, the proposed model is linearized to a mixed-integer linear programming (MILP) model. The commercial solver Lingo is adopted to obtain a feasible solution. The modeling results of Guangzhao hydropower station reveal that: The proposed method can effectively solve the problem of no feasible solution due to conflicting constraints in HUC. Comparing to the penalty function method, the proposed method has better convergence, and strictly reflects the priority of soft constraints.

Design and Application of Integrated Dispatching Communication Network for Intelligent Hydropower Stations

5G has changed the society. Its rich vertical industry applications have changed the traditional operation and maintenance mode of hydropower stations, created a customized "industry private network" for hydropower stations, met the needs of power station intelligence, further improved the hydropower station's ability to independently control its own business and operating efficiency, and created a new intelligent, safe and efficient power station.

Status of Research on Water Hammer Effect in Long Distance Pressure Pipelines

In the long distance pressure pipeline, the sudden change of instantaneous pressure caused by the rapid change of liquid velocity is called water hammer, which seriously threatens the safe operation of hydropower station. In this paper, the development and calculation methods of transient flow percussion theory are introduced, and different models and numerical methods are analyzed and compared. Finally, the problems in transient flow research and water hammer prevention measures are summarized, which is helpful to reduce the occurrence of water hammer accidents and guarantee the normal and stable operation of water supply pipeline system. This conclusion can provide reference for water hammer protection of long distance water supply system.

Transient analysis of a hydropower plant with a super-long headrace tunnel during load acceptance: Instability mechanism and measurement verification

The current development trend of China's hydropower is moving toward ultra-high heads, complex geological scenarios, ultra-large capacities, and the Tibetan region. The construction of hydropower stations with super-long headrace tunnels is conducive to overcoming the constraints of complex geological conditions and making full use of hydropower resources. However, these stations have unique technical problems that limit their commercial development, including pressure fluctuations during load rejection and the operational stability of the power-frequency regulation. In this study, a potential problem in hydropower stations with super-long headrace tunnels, the instability during load acceptance, is studied by combining prototype experiments with 1D transient numerical simulations. First, according to a test case using a prototype hydropower station, the instability phenomenon occurring during a simultaneous load acceptance of two Francis turbines in a hydropower station with a 20-km headrace tunnel is described. Next, using 1D steady-state and transient simulations, the factors leading to the instability are analyzed in detail. Finally, countermeasures for the safe operation of hydropower stations are proposed based on numerical simulations and supplementary prototype experiments. Hydropower stations with super-long headrace tunnels exhibit a characteristic where the net head decreases sharply with an increase in the flow rate. Therefore, prior to load acceptance, the maximum output achievable by the multiple units under the operating net head has to be carefully determined to avoid over-adjustment of the guide vane opening and detrimental phenomena such as operational instability and extremely low pressure in the draft tube.

Cascade hydropower stations short-term operation for load distribution considering water level synchronous variation

The load distribution of cascade hydropower stations is associated with the safe operation of the hydropower stations and power grids. The conventional load distribution of cascade hydropower stations does not consider the synchronous operation of the water level. The inconsistent water level variation process of cascade hydropower stations is not conducive to the safe operation of hydropower stations and power grids. Therefore, the main purpose of this paper is to introduce the concept of equal reservoir full storage rate (ERFSR) to guide the load distribution of cascade hydropower stations. In addition, hydropower is used for new energy consumption considering the advantages of the rapid start-stop in hydropower units. The load distribution model of cascade hydropower stations is established, and three cases are set to verify the universality of the proposed model in the upper reaches of the Yellow River. The results show that (1) The concept of ERFSR can effectively guide load distribution and realize water level synchronization of cascade hydropower stations. (2) The output process of each hydropower station can be basically consistent with the load process to achieve synchronous peak shaving. (3) New energy consumption has little effect on the daily water consumption of downstream cascade hydropower stations.