Hydroelectric Power Research Articles

Vortex rope identification in Francis turbine based on cyclostationary extended dictionary learning

Francis turbine is one of the most commonly used hydraulic machinery for hydroelectric power generation, but its stability is frequently jeopardized by vortex rope. It is crucial to promptly and accurately detect vortex rope for the reliable operation of turbine unit. To address this challenge, the Cyclostationary Extended Dictionary Learning (CEDL) approach is proposed to identify vortex rope in Francis turbine. CEDL utilizes the Fisher discrimination criterion and low-rank constraints through the preprocessing and extending strategies to achieve accurate identification. Preprocessing specifically refers to the construction of filter for raw data based on cyclostationarity Then, the trained dictionary is used to extract features, and a linear classifier is developed based on these features. To evaluate the proposed method, vortex rope experiments are conducted in a Francis turbine under five conditions, and every condition includes four states: normal state, initial vortex rope, stable vortex rope and severe vortex rope. The results reveal three main findings. Firstly, the trained atoms in each sub-dictionary exhibit unique characteristics such as tonal frequency at 7 kHz and broadband frequency during 12–20 kHz, which are linked to the evolution stages of vortex rope. Secondly, the dictionary trained for a specific condition can achieve a classification accuracy of up to 90%, and even exceed 97% in some cases. Finally, the dictionary trained in a specific working condition can achieve relatively high classification accuracy in the scenarios of other working conditions.

Impact of Installation Deviations on the Dynamic Characteristics of the Shaft System for 1 Gigawatt Hydro-Generator Unit

The shaft system, transferring the kinetic energy of water flow into electrical energy, is the most critical component in hydropower plants. Installation deviations of the shaft system for a giant hydro-generator unit can have significant impacts on its dynamic characteristics and overall performance. In this investigation, a three-dimensional geometry of the shaft system of an operating hydro-generator unit prototype with a rated power of 1 GW is established. Then, the calculation model of the shaft system is generated accordingly with tetrahedral and hexahedral elements. By applying different boundary conditions, the finite-element method is used to analyze the influences of installation deviations, including shaft radial misalignment and angular misalignment, on the dynamic characteristics of the shaft system. The calculation results reveal that the installation deviations change the natural frequencies, critical speeds, and mode shapes of the shaft system to a certain degree. The natural frequencies of the backward precession motion with installation deviations are reduced by 23% and 38% for the rated speed and the maximum runaway speed. Furthermore, for the forward precession motion, they increased by 30% and 48%, respectively. The critical speeds for the shaft system with radial and angular deviations are 3.2% and 3% larger than the critical speed of the shaft system without any mounting deviations. The radial and angular installation deviations below the maximum permissible values will not result in the structural performance degradation of the 1 GW hydro-generator shaft system. The conclusion drawn in this research can be used as a valuable reference for installing other rotating machinery.

A Robust Approach using M-Estimation for Dynamic Panel Autoregressive Model

This paper presents a robust M-estimation approach for first-order panel autoregressive models, addressing the challenges posed by high persistence levels of the autoregressive parameter and individual heterogeneity. Generalized method of moments estimators widely used in dynamic panel models exhibit substantial finite sample biases and are sensitive to weak instruments, particularly as the autoregressive parameter gets close to unity. Our proposed weighted M-estimator, which uses a power function for the scale parameter in Huber’s loss function, offers a robust alternative. By minimizing the variance of model parameters through an optimal tuning parameter, our method enhances the efficiency and robustness of parameter estimates. We demonstrate the superiority of the proposed approach through several Monte-Carlo simulations and an application to hydro-electric power output data, providing comprehensive comparisons with existing generalized method of moments estimators.

Pembangkit Listrik Tenaga Air Pikohidro untuk Kebutuhan Pengembangan Lokasi Wisata Bendungan Desa Menaming Rokan Hulu Riau

The Menaming Dam is located in Menaming Village, about 3 km away from residential areas, so it is far from the reach of electricity service providers. From the dam, the water is distributed through irrigation canals to the rice fields and fishery and contains hydraulic power, then could be utilized for electricity generation. The location of the dam has attractive views so that it becomes tourism, but there is no electricity available, causing its development to be hindered. Utilization of water resources in irrigation can be done by developing a waterwheel as driving for electricity generators. The power plant with an undershot waterwheel is very suitable to be developed because it is easy to manufacture and maintain. Besides that, the structure and shape can add to the beauty and attractiveness of visitors to tourist sites. Now a hydroelectric power plant has been installed with a total power of about 70 W. Electricity is transmitted using cables through the power poles and an LED light is installed on each of them. Furthermore, in one of the stalls in the tourist location, the installation of lights and sockets for charging mobile phones was made. Lights were also installed in an adjacent house.

The effect of lubrication on the tribological properties of polymer composites for high contact pressure hydropower bearings

Premature failure of polymeric self-lubricating bearings is a limiting factor in the sustainable and continued operation of hydropower plants. In this work, the tribological performance of two novel polymer composites was studied with respect to commercially available materials. The materials were evaluated under dry and lubricated conditions, using water and an environmentally adaptive lubricant (EAL). The two tested commercial materials yielded a low dry sliding friction and wear. Under water lubricated conditions, the in-house developed polyphenylene sulphide (PPS) based composite provided an exceptionally low friction and a wear rate of a factor of 3 lower than the best performing commercial material. Using the EAL wear was reduced for most materials by up to 85%.

Biodiversity impacts of Norway's renewable electricity grid

Norway aims to transform into a low-emission nation by 2050. However, the energy transition comes with challenges, as expanding renewable energy infrastructure requires significant land areas, which raises concerns about associated environmental impacts, particularly on species richness. The first system-wide life cycle assessment (LCA) approach that integrates multiple biodiversity models is presented, evaluating the current effects of renewable energy production and transmission in Norway. The impacts of Norwegian hydropower and onshore wind power plants are quantified, which contribute 98% of Norway's electricity generation. Additionally, the effects of power lines are included to assess the spatial origins of the biodiversity impacts derived from both energy production and transmission relative to where electricity was transmitted to and consumed in Norway. The analyses show that hydropower exerts the most substantial impact on species richness and that the electric grid affects mostly mammal richness due to habitat conversion and fragmentation. As energy production primarily originates in western-central and northern Norway, regions with low electricity generation, such as south-east Norway, import a substantial share of the biodiversity impacts for their energy consumption. However, integrating an international dimension is crucial, as multiple European countries exchange energy with Norway, and thus also contribute to the pressure on local species richness. The results present the current operational impacts on biodiversity caused by Norway's electricity system. Since Norway intends to increase its renewable energy production capacity in the coming decades, this approach can serve as an instrument for developing scenarios to assess the future construction of hydropower, onshore wind power, and power lines. It can help shape Norway's energy future, ensuring a holistic approach that integrates impacts on species diversity and promotes an environmentally friendly energy transition. While focused on Norway, the methodology is adaptable to other regions if the required data is available.

Machine learning-based uncertainty analysis in power system planning: Insights and pathways for decarbonization

This study performs an extensive uncertainty analysis of decarbonization pathways for the Canadian power system. By leveraging machine learning (ML) techniques, we represent complexities and nonlinear behaviors of the power system, which are challenging to observe using traditional modeling methods due to computational limitations. We further utilize K-means clustering and statistical methods to identify correlations, investigate the effects of uncertainty in key parameters (capital costs, demand, and carbon tax), and identify opportunities for diversification of the power generation mix. Key findings include the increased flexibility of gas combined cycle (generation mean 4.8 TWh, installed capacity mean 4.8 GW) over gas simple cycle (generation mean 22.3 GWh, 0 installed capacity) in response to carbon tax, highlighting its role in a low-carbon future. Variations in solar and wind deployment rates, influenced by capacity factors and location-specific costs, underscore the necessity of a flexible grid system. This analysis reveals important correlations between renewable deployment, and transmission expansion and gas combined cycle reliance. The results also highlight minimal sensitivity of hydroelectric power generation (∼ 43 % of scenarios) to changes in input parameters. The novelty of our work lies in proposing a comprehensive approach which uses ML techniques to go beyond the capabilities of existing models, specifically by performing extensive uncertainty analysis and provides key insights into system behavior, causative factors, and an expanded breadth of potential pathways. Taken together, this proposed approach lays a foundation for strategic planning and policy formulation.

Assessing the potential for gas supersaturation downstream of hydropower plants in Norway, Austria and Germany

Hydroelectric power facilities can generate episodic total dissolved gas supersaturation (TDGS), which is harmful to aquatic life. We developed a decision tree-based risk assessment to identify the potential for TDGS at hydropower plants and conducted validation measurements at selected facilities. Applying the risk model to Norway's hydropower plants (n = 1696) identified 473 (28 %) high-risk plants characterized by secondary intakes and Francis or Kaplan turbines, which are prone to generating TDGS when air is entrained. More than half of them discharge directly to rivers (283, 17 % of total). Measurements at 11 high-risk plants showed that 8 of them exhibited biologically relevant TDGS (120 % to 229 %). In Austria and Germany, the analysis of hydropower plants was limited due to significant data constraints. Out of 153 hydropower plants in Austria, 80 % were categorized at moderate risk for TDGS. Two Austrian plants were monitored, revealing instances of TDGS in both (up to 125 %). In Germany, out of 403 hydropower plants, 265 (66 %) fell into the moderate risk, with none in the high-risk category. At a dam in the Rhine River, TDGS up to 118 % were observed. Given the uncertainty due to limited data access and the prevalence of run-of-river plants in Austria and Germany, there remains an unclarified risk of TDGS generation in these countries, especially at spillways of dams and below aerated turbines.The results indicate a previously overlooked potential for the generation of biologically harmful TDGS at hydropower installations. It is recommended to systematically screen for TDGS at hydropower installations through risk assessment, monitoring, and, where needed, the implementation of mitigation measures. This is increasingly critical considering the expanding global initiatives in hydropower and efforts to maintain the ecological status of freshwater ecosystems.

Hydropower Enhancing the Future of Variable Renewable Energy Integration: A Regional Analysis of Capacity Availability in Brazil

As the share of variable renewables in the power system generation mix increases, meeting capacity requirements becomes challenging. In this context, hydropower reservoirs can play a vital role in integrating renewable energy due to their storage potential, contributing to meeting power supply criteria. However, given that reservoirs serve multiple purposes, various constraints can limit their capacity potential. This article introduces an analytical methodology that is designed to evaluate the maximum available power of hydro plants in critical scenarios. By applying concepts related to hydropower production calculations for the peak power demand and metrics evaluating the compliance with supply criteria, this study distinguishes itself from region-specific investigations. It conducts a generalized analysis of power availability across all regions of Brazil, with a focus on identifying the reasons for the most significant power losses and their specific locations. The results of this analysis demonstrate the feasibility of enhancing the available power of reservoirs, effectively addressing demand fluctuations, and sustainably improving energy security. This is particularly crucial in countries that are heavily reliant on renewables, including hydropower, for a huge portion of their electricity. The findings underscore the feasibility of increasing the penetration of variable renewable generation by optimizing the operation of existing hydropower plants. This optimization not only enhances energy security but also contributes to a more resilient and sustainable future, benefiting policy makers, energy planners, and stakeholders in the field of hydropower with reservoirs.

An MILP model based on a processing strategy of complex multisource constraints for the short-term peak shaving operation of large-scale cascaded hydropower plants

Hydropower with flexible regulation plays an important role in short-term peak shaving operations. However, short-term peak shaving operation is a challenging problem due to the large scale, the nonconvex and nonlinear characteristics, and the complex multisource tasks. This study proposes a mixed integer linear programming (MILP) model, termed MILPoPSC, based on a processing strategy for complex multisource constraints, tailored for short-term peak shaving in large-scale cascaded hydropower plants. The MILP model, designed to incorporate multisource tasks by abstracting them into constraints, ensures that task requirements are met. A novel multisource constraint transformation method is introduced to derive constraint expressions related to power flow, facilitating the unification of constrained variables. Additionally, a classification and integration method based on restriction mode and set theory is proposed to improve solving efficiency by integrating constrains of the same type. The proposed method was applied to 7 hydropower cascade plants in the Wujiang River. The results showed that the linearization method and the processing strategy of complex multisource constraints can successfully reduce the complexity of the MILP model without affecting the solution quality. This indicates that MILPoPSC has good practical value for the short-term peak shaving operation of large-scale cascaded hydropower plants in China.

Optimization and reconstruction of pelton buckets based on statistical techniques, artificial neural networks and CFD modelling

During operation Pelton turbines suffer from erosion and cavitation wear, which decreases the hydraulic efficiency. Welding repair is a cost-effective method for recovering the original bucket geometry but requires templates to ensure proper results. However, those templates may be unavailable for Pelton units with decades of operation. This is the case of one of the 2.8 MW Pelton units at Nima II, a small hydropower plant in Colombia that began operation in 1942. This paper presents the redesign and optimization of the bucket. First, the bucket is rebuilt following both, technical recommendations, and Design of Experiments (DOE) to verify the effects of the basic dimensions on the hydraulic efficiency. Experimental measurements on the eroded turbine validate the two-phase computational fluid dynamics (CFD) modelling to be applied in the optimization process. Second, the best inner surface is found by using a multi-objective optimization based on Artificial Neural Networks trained by the previous DOE and a genetic algorithm. At the end, the CFD results suggest a total hydraulic efficiency recovery of 8 %. Further experimental tests on the optimized runner showed a difference of 0.7 % from the predicted value.

Biodiversity and Ichthyofaunal Richness of Fish Population in River Subansiri in the Downstream of the Lower Subansiri Hydro-electric Power Project Dam, Assam, India

Biodiversity and Ichthyofaunal Richness of Fish Population in River Subansiri in the Downstream of the Lower Subansiri Hydro-electric Power Project Dam, Assam, India

Optimizing ecological benefits in weekly-regulated hydropower plants: A framework integrating power market information

The production of hydropower has profound impacts on the sustainability of downstream river ecosystems. However, current studies often overlook the crucial role of power market information in this process. This study aims to investigate the ecological impact of power market information on the downstream river of weekly-regulated hydropower plants. Additionally, it explores strategies to enhance ecological benefits while minimizing the adverse effects on power generation. To achieve these, this study proposes an ecological management framework for the downstream river of hydropower plants. This framework effectively models the scheduling of hydropower plants in the context of the power market and tracks changes in ecological indicators to assess the ecological consequences of power market information. Through a case study conducted in the Wujiang River Basin, we analyze the impact of electricity price characteristics on release flow and downstream ecological benefits. We also provide recommendations for optimizing generation strategies to enhance ecological benefits while minimizing revenue losses. The findings of this study can serve as a reference for the ecological management of hydropower plants, ensuring the sustainability of power generation.

ANALYSIS OF THE POTENTIAL DEVELOPMENT OF MICRO HYDRO POWER PLANT (PLTMH) IN ABENAHO DISTRICT, YALIMO REGENCY

This study examines the feasibility of the location for the construction of a micro hydro power plant (PLTMH) in Landikma Village, Abenaho District, in relation to the district government's plans. The specific objectives of this study are to determine the potential location of a PLTMH based on the applicable technical principles, as well as to compile a feasibility study for the construction of a PLTMH to support lighting/electricity services. The survey method was applied to identify the description of the existing conditions, with reference to the criteria for PLTMH development. Data analysis was carried out using quantitative and qualitative methods. Based on the research results, the PLTMH construction site in Landikma Village, Abenaho District, Yalimo Regency meets the eligibility to build a 177kW micro-hydro power plant. The river discharge at the location of the development plan is 0.950 m3/s, so the result of calculating the potential electric power generated by the PLTMH is 326.2 kW. This electrical energy is capable of meeting the lighting needs of 521 houses, assuming that each house gets 450 watts of electric power. Strategic environmental studies need to be carried out to ensure that this development does not have the potential to cause negative impacts on the environment. The PLTMH development process must also be accompanied by a comprehensive Detail Engineering Design (DED). In addition, local communities must also be involved in the process of reviewing the development, evaluation and supervision to ensure the sustainability of development and the sustainability of natural resources around the PLTMH construction site. Keywords: Potential Study, power plant, micro hydro, turbine, river.

Assessing the social life cycle impacts of the Spanish electricity mix: A decadal analysis

Power generation systems are crucial to national energy transitions, such as Spain's, which stands as a notable example. However, this profound transformation could have multifaceted implications, leading to unintended consequences on society. The present work is the first to understand the social impacts of the Spanish power sector and their technology supply chains using the social life cycle sssessment methodology. The functional unit is 1 kWh of electricity produced by the technologies in the Spanish electricity mix. A cradle-to-gate approach is taken using a supply chain protocol to complete the system boundaries. The social life cycle inventory, comprising data on national suppliers, working hours and social flows, was integrated into the PSILCA database to derive the social profile of each power technology and, consequently, to obtain a comprehensive view of the Spanish power sector. The results reveal that social impact associated with the Spanish electricity mix has increased or remained stable from 2010 to 2022. Analysis of four indicators (child labour, contribution of the sector to the economic development, frequency of forced labour and women in the sectoral labour force) reveals significant differences, highlighting three main social hotspots: i) solar PV panel production in East and Southeast Asia, particularly China, ii) natural gas extraction and refining in North Africa, concentrated in Algeria, for natural gas combined cycle and cogeneration plants, and iii) construction and operation of hydropower and nuclear plants in Spain. This study demonstrates that current strategies for Spain's power sector transition may not guarantee a favourable social performance, emphasizing the need for balanced environmental and social considerations in energy policy making, aligned with the Sustainable Development Goals.

Fault diagnosis method for hydropower unit via the incorporation of chaotic quadratic interpolation optimized deep learning model

Hydro-turbine fault diagnosis is crucial for hydropower plants’ safe and stable operation. This paper proposes a deep learning model for hydro-turbine fault diagnosis based on chaotic quadratic interpolation optimization (CQIO). Chaotic mapping optimizes the initial population of the QIO algorithm by introducing randomness and diversity, improving the algorithm’s performance and stability. The CQIO is used to calculate the optimal hyperparameter combinations for CNN-LSTM models. It can improve the model’s stability and reduce computational resource consumption. The results show that the fault accuracy of the proposed method reaches 96.7% and 93.6%, respectively, which is higher than the CNN, LSTM, CNN-LSTM, and QIO-CNN-LSTM models. Notably, the diagnostic accuracy about impact faults exceeds that of wear faults, with the latter exhibiting an augmented diagnostic accuracy as sediment increases.

Forecasting and analysis of the reliability of a hydroelectric power plant in Colombia through the application of a time-varying failure rate

La generación energética en Colombia está fuertemente ligada a las centrales hidroeléctricas, lo que hace crucial la optimización de tareas de mantenimiento para garantizar su máxima disponibilidad. Por tal motivo, el presente trabajo se centra en analizar la confiabilidad de una central hidroeléctrica con el fin de respaldar la toma de decisiones en la planeación del mantenimiento. La investigación se basa en el histórico de datos de la planta, en el que se registran los reportes que causan su indisponibilidad. A partir de esta información, se determinó el MTBF (tiempo medio entres fallas) de los equipos y su confiabilidad, así como la de las dos unidades generadoras que componen la central. Finalmente, se implementó un método basado en el indicador técnico EMA (media móvil exponencial) que permitió pronosticar la tendencia de la confiabilidad en el tiempo. Los resultados obtenidos brindaron una evaluación del estado actual de la central hidroeléctrica y permitieron identificar los equipos críticos en términos de fallas, en los que se deben orientar recursos para fortalecer la disponibilidad de la planta.

Collaborative renewable development in Chile: a new path forward for the Mapuche

For years, the conflict between the Mapuche people and energy developers has persisted in Chile’s southern Biobío Region. Chile’s future as a leader in renewable development hangs on the drafting of a new law, and workable solutions are needed now more than ever. The voters decisively rejected Chile’s latest constitutional draft, which afforded Indigenous people in Chile unprecedented recognition at the price of a new governmental structure. In the midst of these political developments, Chile is shifting to develop more renewable energy. This shift will require the use of Mapuche ancestral lands and waterways, likely causing increased tensions between the Chilean government, renewable energy developers, and the Mapuche. This paper assesses the just transition approach in Chile alongside the drafting of a new constitution for the country, with particular consideration for restorative and recognition justice. We provide a comprehensive summary of Mapuche’s historic and current claims to the ancestral lands in Chile and their resistance to hydroelectric power development projects along the Biobío River. Then, we review Chilean laws and court cases dealing with hydroelectric power development projects to pinpoint energy injustice. Finally, we use the energy justice framework to propose new energy laws for Chile that will encourage needed collaboration between the Chilean government, renewable energy developers, and the Mapuche.

Assessing small hydropower viability in water-scarce regions: environmental flow and climate change impacts using a SWAT+ based tool

Water-scarce regions, like the Mediterranean, face worsening conditions due to climate change, intensifying pressure on key economic sectors such as hydropower. Additionally, environmental conservation policies, particularly the implementation of environmental flows, present challenges for hydropower systems. Certainty regarding the impact of these factors on future hydropower production is crucial for informed decision-making in the transition to sustainable energy. This study introduces S + HydPower, a tool coupled with SWAT+ to assess climate change and watershed management effects on small hydropower plant (SHP) systems. In this study, we used this tool to investigate the consequences of implementing environmental flows and climate change on run-of-river SHPs in the Catalan River Basin District (CRBD), in Catalonia. The results show that applying environmental flows would lead to a significant 27% reduction in SHP production. However, this reduction would represent only 0.25% of the region’s current energy demand. Furthermore, the study reveals a potential 38% to 73% reduction in SHP production by the end of the twenty-first century due to the combined effects of environmental flows and climate change. This suggests a substantial decline in run-of-river SHP’s contribution to the CRBD’s electricity supply. These findings emphasize the need to explore alternative and sustainable energy sources to ensure the long-term reliability and resilience of the region’s energy supply.

Projects of transition

This paper develops an analysis of the politics and temporality of infrastructure through a focus on the idea of a project. A project (noun) is an assemblage of expertise, labour, materials and resources. The development of a project to build a port, pipeline, a mine, or a hydropower plant entails the mobilization of ideas, finance, political support and the law, the containment of material forces, as well as the organization of expertise, resources and labour. To project is also a verb; to throw forwards or to imagine, visualize or speculate on a possible future, which may or may not be actualized in practice. Moreover, individual infrastructural projects are often built on the legacy of earlier projects and conceived as contributions to ambitious projections of the future – including modernization, socialism, development and state building. Our analysis of the politics and temporality of projects is both developed and illustrated through an account of infrastructural projects in the Republic of Georgia which are also understood as contributions to a larger project of transition.