Hydropower Station Research Articles

Soil and Water Conservation Vegetation Restoration in Alpine Areas—Taking a Hydropower Station as an Example

Soil and Water Conservation Vegetation Restoration in Alpine Areas—Taking a Hydropower Station as an Example

Monitoring Hazards in Dam Environments Using Remote Sensing Techniques: Case of Kulekhani-I Reservoir in Nepal

Maintaining the operability of a hydroelectric power station at a scale originally designed is being compromised by continuous reservoir sedimentation. The underlying factors include a complex mix of landscape alterations owing to natural and anthropogenic activities around dam areas, such as gully erosion, landslides, floods triggered by heavy rainfall, climate change, and construction activities. The hydropower projects in the low-to-mid mountain regions of Nepal are witnessing a combination of these phenomena, affecting their optimal performance in meeting long-term sustainable power supply targets. This paper presents a combination of geo-spatial analysis and field evaluations to identify the trends from Kulekhani-I, one of the oldest storage-type hydropower projects in Nepal, using long-term time series remote sensing satellite imagery from 1988 to 2020. Our analysis shows an expansion of the surface water content area over time, attributed mainly to high sedimentation deposition owing to multiple factors. This study has identified an urgent need for addressing the following two key contributory factors through an effective control mechanism to avoid rapid sedimentation in the reservoirs: natural—landslides and floods leading to mainly silt deposition during heavy rainfalls; and anthropogenic—road construction materials dumped directly in the reservoir. Effective implementation of a remote sensing monitoring scheme can safeguard future damages to dam environments of more recently built storage-type hydropower projects.

Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection

In 2019, more than 16% of the globe’s total production of electricity was provided by hydroelectric power plants. The core of a typical hydroelectric power plant is the turbine. Turbines are subjected to high levels of pressure, vibration, high temperatures, and air gaps as water passes through them. Turbine blades weighing several tons break due to this surge, a tragic accident because of the massive damage they cause. This research aims to develop predictive models to accurately predict the status of hydroelectric power plants based on real stored data for all factors affecting the status of these plants. The importance of having a typical predictive model for the future status of these plants lies in avoiding turbine blade breakage and catastrophic accidents in power plants and the resulting damages, increasing the life of these plants, avoiding sudden shutdowns, and ensuring stability in the generation of electrical energy. In this study, artificial neural network algorithms (RNN and LSTM) are used to predict the condition of the hydropower station, identify the fault before it occurs, and avoid it. After testing, the LSTM algorithm achieved the greatest results with regard to the highest accuracy and least error. According to the findings, the LSTM model attained an accuracy of 99.55%, a mean square error (MSE) of 0.0072, and a mean absolute error (MAE) of 0.0053.

Intelligent Inversion Analysis of Surrounding Rock Parameters and Deformation Characteristics of a Water Diversion Surge Shaft

The water diversion surge shaft is vital for a hydropower station. However, the complex geological properties of the surrounding rock make it challenging to obtain its mechanical parameters. A method combining particle swarm optimization (PSO) and support vector machine (SVM) algorithms is proposed for estimating these parameters. According to the engineering geological background and support scheme, a three-dimensional model of the water diversion surge shaft is established by FLAC3D. An orthogonal test is designed to verify the accuracy of the numerical model. Then, the surrounding rock mechanical parameter database is established. The PSO-SVM intelligent inversion algorithm is used to invert the optimal values of the mechanical parameters of the surrounding rock. The support for excavating the next layer depends on the mechanical parameters of the current rock layer. An optimized design scheme is then compared and analyzed with the original support scheme by considering deformation and plastic characteristics. The research results demonstrate that the PSO-SVM intelligent inversion algorithm can effectively improve the accuracy and efficiency of the inversion of rock mechanical parameters. Under the influence of excavation, the surrounding rock in the plastic zone mainly fails in shear, with maximum deformation occurring in the middle and lower parts of the excavation area. The maximum deformation of the surrounding rock under support with long anchor cables is 0.6 cm less than that of support without long anchor cables and 4.07 cm less than that of support without an anchor. In the direction of the maximum and minimum principal stress, the maximum depth of the plastic zone under the support with long anchor cables is 1.3 m to 2.6 m less than that of the support without long anchor cables and the support without an anchor. Compared with the support without long anchor cables and support without an anchor, the support with long anchor cables can effectively control the deformation of the surrounding rock and limit the development of the plastic zone.

Long-term variability of ice regime characteristics in river mouth areas of the western coast of the White Sea on the background of climatic changes

The paper presents results of the comprehensive study of the long-term variability of the main elements of the ice regime for the period 1955–2020 in mouth areas of the rivers Gridina, Kuzema, Pongoma, Kem, Shuya, Nizhny Vyg, Suma, Nyukhcha and Maloshuika flowing into the White Sea on its western coast (Republic of Karelia, Arkhangelsk region). The average daily air temperatureы in sites of the State observation network of Roshydromet – marine hydrometeorological coastal stations Gridino, Kem and Onega - were used as initial information for this work. Information about the main characteristics of the ice regime (times of coming of characteristic dates of ice phenomena) of the rivers was presented by data from nine hydrological posts. The mean values of characteristics of the ice regime (average statistical dates and durations of the ice regime phases) of the rivers under consideration (except those regulated by the cascade of hydroelectric power stations). were calculated. Statistical analysis of time series of the mean air temperatures obtained for the cold season on the western coast of the White Sea and the duration of periods with ice phenomena on the above rivers made possible to reveal two quasi-homogeneous periods with a turning point in 1990. This analysis shows that the temperature background in years 1991–2020 is significantly higher (by 1.4 °C) than the similar one in 1956–1990, and at the same time the average duration of ice phenomena decreased to almost two weeks (shorter by 11 days). The regression analysis allowed finding the presence of a statistically significant negative trend in the duration of ice phenomena for the whole period (1956–2020), which is −3.3 days/10 years. At the same time, the shortening of the duration of the periods with ice phenomena is due equally to both a shift in the time of the beginning of the stable ice formations towards later dates (1.6 days/10 years), and the earlier dates of the ice phenomena end (−1.7 days/10 years).

The Baihetan Hydropower Station Project in Jinsha River

The Baihetan Hydropower Station Project in Jinsha River

Effects of cascade hydropower stations on hydrologic cycle in Xiying river basin, a runoff in Qilian mountain

Effects of cascade hydropower stations on hydrologic cycle in Xiying river basin, a runoff in Qilian mountain

Long-Term Optimal Scheduling of Hydro-Photovoltaic Hybrid Systems Considering Short-Term Operation Performance

Integrating photovoltaic power stations into large-capacity hydropower stations is an efficient and promising method for regulating large-scale photovoltaic power generation. However, constrained by the time step length, traditional long-term scheduling of hydro-PV hybrid systems does not adequately consider short-term operational performance indicators, resulting in sub-optimal scheduling plans that fail to coordinate the consumption of photovoltaic power and the utilization of water resources in the basin. To address this, this study established a long-term optimal scheduling model for hydro-PV hybrid systems. This model overcomes the limitation of the time step length in long-term scheduling by incorporating long-term power generation goals and short-term operation performance targets into the long-term optimal scheduling process based on scheduling auxiliary functions. In case studies, the optimised model balanced the long-term power-generation goals and short-term operational performance targets by redistributing energy across different periods. Compared to optimization models that did not consider short-term operation performance, in a typical normal year, the model effectively reduced the electricity curtailment volume (28.54%) and power shortage volume (10.91%) of the hybrid system while increasing on-grid electricity (0.03%). Similar improvements were observed in wet and dry years. These findings provide decision support for hydropower scheduling in the context of large-scale photovoltaic power integration.

Physics-based modeling of debris flows and assessing the performance of effective mitigation measures

BackgroundClimate change-induced geohazards are increasingly posing a critical threat to the sustained functionality and resilience of constructed infrastructures. Among these hazards, debris flows represent significant natural disasters, particularly in mountainous terrains, causing widespread property damage and loss of life globally. These phenomena involve complex interactions between solid and fluid forces, resulting in long run-out distances and high-speed flows. Predicting and monitoring debris flows is challenging due to the intricate interplay of these forces.ObjectiveThe objective of this study is to evaluate the structural damage caused by debris flows and assess the efficacy of rigid barrier structures with passages/apertures.MethodEmploying Smoothed Particle Hydrodynamics, a Lagrange-based mesh-free computational technique, the researchers simulated the impact of debris on a stiff structure. The focus was on the Rishiganga river valley in the Indian state of Uttarakhand, a region recently devastated by a debris flow that severely compromised essential infrastructure, including a hydroelectric power station. The research entailed modeling the debris flow in this specific locale and analyzing its effects on an assumed downstream rigid structure. Additionally, the study explored the outcomes of introducing a rigid barrier upstream.Results and ConclusionResults indicated a substantial reduction in the impact on the downstream structure with the presence of an upstream rigid structure. Moreover, as the number of apertures in the upstream barrier was increased, the impact of flow on the downstream structure further diminished, because of a more streamlined flow pattern.

Unveiling the prediction model and mechanism of the collapse of bank slope in the lancangjiang area

This study takes the bank collapse at the left bank of Badi Township of the Lidi Hydropower Station in the Lancang Area as an example. To address the lack of in-depth research on the prediction model and mechanisms of bank collapse, this study conducts field drilling surveys, investigates influencing factors, analyzes causal mechanisms, and proposes prediction methods based on the geological survey data of bank collapse in the reservoir area. The study explores the stratigraphic lithology, determines the key parameters for bank collapse prediction, and studies the failure modes and bank collapse mechanisms. It also proposes the finite element method of bank collapse to predict the width and elevation of bank collapse and provides the influence on the surrounding environment. The results show that the collapsed bank on the left bank of Badi Township is a high and steep soil-like slope, and forms the collapse and retreat type of failure mode after impoundment. The Kachukin method, the bank slope structure method, and the proposed finite element method are used to predict the width and elevation of the collapsed bank. The results indicate that the Kachujin method predicts a larger range of bank collapses and is biased towards safety. In contrast, the prediction ranges of the bank slope structure method and the finite element method are close. The bank collapse position is located in the middle and rear of the residential houses in Badi Township, which is consistent with the on-site investigation and has strong reliability. The predicted width of the bank collapse is about 34 m and the elevation is about 1,845 m. The research results can be directly applied to preventing and controlling bank collapse and have powerful practical application value.

Impact of excavation footage on vertical shaft lining deformation and surrounding rock stress in Xiyu conglomerate

The Xiyu conglomerate, which is extensively distributed in Xinjiang, China, presents challenges for vertical shaft construction owing to its poor cementation and low strength. The selection of an appropriate footage length is paramount for ensuring safe construction. Based on the shaft pipeline construction project of the Xinlongkou Hydropower Station on the Kuitun River, this study investigated the impact of footage length on the stability of vertical shafts within the Xiyu conglomerate strata using finite element simulation and measurement data to analyze the lining displacement and change in stress in the surrounding rock. The results show that the excavation footage has little effect on the lining’s horizontal displacement during vertical shaft excavation. A mathematical model was developed to describe how the vertical displacement of the lining varies with the excavation footage and vertical shaft depth. Below a critical threshold, the stress in the surrounding rock cannot be effectively alleviated, leading to a concentration of stress; above that critical threshold, an excessively large excavation increases the load on the surrounding rock. Based on the simulation results and factors such as economic benefits, construction speed, and safety, an excavation footage of 4 m is judged to be appropriate.

The ecological operation of ChiTan hydropower station based on hydrological alteration using the PCA method

ABSTRACT Water infrastructure affects the quantity, quality, and environment of water. During reservoir construction, only the social-economic benefits were considered and the health of the downstream river was neglected. Due to the severe downstream river system, the operators and managers faced the challenge of the downstream ecosystem. Many scholars are concerned with the reservoir's optimum functioning, which considers social and economic advantages. Numerous significant opinions and research findings are being presented on ecological scheduling at the moment, both in China and overseas, which surely deepen the connotations of ecological scheduling and serve as the research basis and critical reference of this work. The influence of hydropower development on hydrological conditions, the categorization and calculation of environmental runoff, and the building and solution of ecological scheduling models are all discussed and researched in this work. The study examined how the ChiTan hydropower project influenced the Jinxi River's flow. The total hydrologic alteration calculated using RVA is 50.53%. The component analysis is also utilized to eliminate the statistical redundancy in the hydrologic indicators. The indicators’ monthly flow for July and August's mean minimum flow for 7 days are relevant indicators for the Jinxi River basin's hydrologic modification regime.

Excavation deformation characteristics of underground caverns across fault fracture zone: a case study at Baihetan hydropower station

Excavation deformation characteristics of underground caverns across fault fracture zone: a case study at Baihetan hydropower station

ეროვნული საკანონმდებლო რეგულაციების მიმოხილვა და ანალიზი შრომის სამართლის და შრომის უსაფრთხოების მიმართულებით

National legislative acts - Georgian Laws, Georgian Government resolutions, as well as Orders of Ministry of Internally displaced persons from occupied territories, Labour, Health and Social Affairs of Georgia concerning labour law and labour safety are considered. On the basis of survey and analysis of these legislative acts the authors of this article express their view, namely, it/s necessary: enlarge sphere of supervision over the objects with heightened technical danger; for every danger object elaborate standard in Georgian; on the basis of accumulated experience revise the periodicity of inspection of some objects; for some important enterprises of Georgia (mines, caves, metro, hydroelectric power stations) create mine – rescue service within the limits of state institution. Owing to these measures the level of technical safety will increase and the number of accidents will decrease.

Impacts of Large Hydropower Projects on the Ecological Environment of Watersheds: A Case Study of Ertan Reservoir Area

Ertan Hydroelectric Power Station was the first large-scale water conservancy facility in western China, and with its completion, the ecological pattern of the reservoir area has changed dramatically; however, the changes in habitat quality before and after the completion of the reservoir have not yet been systematically monitored and evaluated. In this study, we analyzed the spatial and temporal characteristics of the remote sensing ecological index (RSEI), used CA-Markov model and GeoDetector, evaluated the ecological environment of the Ertan Reservoir area in each five-year period from 1995 to 2020, simulated the ecological quality of the Ertan Reservoir area in 2025, and revealed the nine drivers and their interactions affecting ecological quality of the watershed from a geologic point of view, and finally put forward reasonable planning and targeted protection suggestions. Finally, rational planning and targeted protection recommendations were proposed. The main results were as follows: (1) After the completion of the Ertan Hydropower Station, the spatial distribution of the RSEI in the reservoir area varied significantly, with a trend of “rising-declining-rising” in time, and the area share of “good” area increased the most, by 19.83%. (2) The degree of grading of each driving factor had different degrees of influence on the size of the RSEI value, and its interaction enhanced the spatial differentiation of the RSEI. (3) The average value of the RSEI is 0.66 in 2025, and the ecological environment quality will show a steady improvement in five years. The results of the study can provide a reference for constructing RSEI indicators for large hydropower facilities.

A comprehensive framework for evaluating and predicting investment risks in renewable energy projects: a case study of Maynak hydropower station

ABSTRACT This study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. This framework aims to reduce the uncertainties inherent in renewable energy projects. To achieve this, we utilize the variable weight matter-element extension model to establish the project’s fundamental reliability function. We then refine this model by incorporating evidence theory to assess the project’s risk level and derive precise risk index measurements. We utilize the GM model to forecast potential future risks associated with the project. In addition, a case study is presented on the risk assessment and prediction for the Maynak Hydropower Station. Our findings reveals that the project encountered significant investment risks in 2008, 2014, 2020, and 2022. Key risk indicators include political turmoil，policy change，imperfect legislation，cultural risk，exchange rate changes，technical risks and management risks. Furthermore, the investment risk level declined from 2023 to 2027, with our risk measurement outcomes closely aligning with actual conditions, thereby validating the effectiveness and applicability of our model.

Application of discrete random forest algorithm in multi-person asynchronous parallel disassembly sequence planning for hydropower station equipment maintenance

Application of discrete random forest algorithm in multi-person asynchronous parallel disassembly sequence planning for hydropower station equipment maintenance

Numerical simulation of multiphase flow and prediction of sediment wear in a large Pelton turbine

AbstractThe problem of sediment wear presents a significant challenge for hydraulic turbines operating in sediment‐rich rivers, particularly for high‐head Pelton turbines. In this study, the VOF model, SST k–ω model, and DPM model were employed to simulate the gas–liquid–solid three‐phase flow within a large Pelton turbine, which operates under a rated water head of 671 m and has a single capacity of 500 MW, at a hydropower station situated on a sediment‐laden river. The sediment wear prediction model, derived from the sediment wear test of the model turbine, was utilized to forecast the sediment wear on the flow components of the Pelton turbine at the hydropower station. The results show that there are obvious pressure and velocity gradients near the nozzle outlet of the Pelton turbine in the power station, and the wear of the nozzle surface is gradually increasing, and the wear in the downstream area of the nozzle is more serious. The wear rate at the needle tip surface reached 1.372 μm/h, while the socket ring surface exhibited a wear rate of 3.175 μm/h. he highest wear rate recorded for the water bucket is 0.940 μm/h. After a year of continuous operation, the maximum erosion observed was 5.62 mm on the runner bucket made of stainless steel and wear‐resistant metal, 8.23 mm on the spray needle, and 19.05 mm on the nozzle mouth ring, highlighting the severity of sediment wear on the Pelton turbine. It is recommended that surface treatment technology be applied to the flow‐through components of the Pelton turbine at this hydropower station to enhance the wear resistance of the turbine and extend the operational life of the unit.

RUSSIAN-MONGOLIAN COOPERATION IN THE ELECTRIC POWER INDUSTRY: PROBLEMS AND PROSPECTS

This article is devoted to the study of existing problems and prospects for the development of cooperation between the Russian Federation and Mongolia in the field of electric power. The author briefly describes the history of the development of Russian-Mongolian relations in this area and current legal framework, another point of interest is the study of existing energy problems in Mongolia. Particular attention is paid to the advantages that the Russian side has in its energy cooperation with Mongolia. The author then analyzes the areas of cooperation between Russia and Mongolia in the field of electric power, specifically: thermal energy (the most important traditional area), development of electrical grid infrastructure, hydropower, nuclear energy and, finally, alternative energy. For each area, the author provides information about the degree of its development in Mongolia and the opportunities available to the Russian side while interacting with Mongolian partners. The article provides a list of the most significant, including those already implemented, those under development, or those with a promising future. In addition, the author studies the existing problems that hinder the deepening of Russian-Mongolian cooperation in the electric power industry, such as opposition from other states (primarily the so-called «third neighbor» countries) and unresolved contradictions regarding Mongolian hydroelectric power station projects in the Selenga River basin. The author concludes that if the Russian side properly realizes the available advantages, there are good chances to resolve the controversial issues and achieve success in the development of Russian-Mongolian cooperation in the electric power industry, thereby contributing to economic growth and strengthening energy security of both countries.

Co-optimization for day-ahead scheduling and flexibility response mode of a hydro–wind–solar hybrid system considering forecast uncertainty of variable renewable energy

Hydropower, characterized by its quick ramping speed and energy buffering capacity, has the ability to respond to the flexibility demand caused by the forecast uncertainty of variable renewable energy (VRE). However, how to determine the flexibility supply of each hydropower station to ensure the reliable execution of the day-ahead scheduling in the intraday operation is a challenging issue for a hydro–wind–solar hybrid system (HWSHS). Due to complex characteristics of cascade hydropower stations, there is a mutual influence between the day-ahead scheduling and its execution. Therefore, flexibility response mode (FRM) is proposed to determine the flexibility supply of each hydropower station according to the flexibility demand of VRE, and a co-optimization model is constructed to optimize the day-ahead scheduling and the parameters of FRM considering the forecast uncertainty of VRE. A HWSHS in Guizhou province, China, is employed as a case study. The results suggest that the FRM can ensure the reliable execution of the day-ahead scheduling in the intraday operation. Compared to a contrast model without FRM, the execution deviation and its duration are decreased by more than 22% and 37%, respectively, in both long-run and out-of-sample analyses.