Hydroelectric Research Articles

Economic Development in Tropical Queensland & Net Zero

The Paper reviews the realities of the economy of the Tropical Queensland region and the pathways to achieving further economic development. It identifies the need to continue developing industries based on the region’s mineral and biological resources and locational advantages that earn income from outside the region while pursuing opportunities to develop higher order manufacturing and services as population and the economy grows to replace goods and services currently imported into the area. Satellite mapping of carbon absorption as indicated by plant growth indicates that tropical Australia’s absorption is roughly equivalent to southern Australia. But with only 5% of Australia’s population living in the area, CO2 emissions generated in the area will be very much lower. However, the Paper provides evidence that the structure of the economy of the Tropical Queensland region results in it being very energy dependent on a per capita basis and the overwhelming majority of the energy consumed is currently from fossil fuels. On top of this, the economies of the Mackay and Central regions are heavily dependent on exports of fossil fuels overseas. Against this background, the Paper canvasses a number of major challenges net zero poses to future growth and development including the threat of higher energy costs to the competitiveness of the region’s agricultural, fishing, mining and tourism industries’ ability to compete in international markets, the threat that restrictions on tree clearing pose to the further realisation of the area’s large underdeveloped agricultural potential, and the potential demise of fossil fuel exports. However, the Paper also explores some opportunities, pointing to the region’s strong solar generation potential, the high potential role of tropical agriculture in biofuels and potential in hydro electricity generation.

Fault diagnosis in hydropower units based on chaotic Kepler optimization algorithm-enhanced BiLSTM model

Safe and stable operation of hydropower units is the cornerstone of the whole hydroelectric power generation system. This paper proposes a deep learning model based on the chaotic Kepler optimization algorithm (CKOA) for fault diagnosis of hydropower units. The Tent chaotic function is introduced to initialize the initial population of KOA, which accelerates the convergence speed of the KOA algorithm and improves the global search capability by improving the uniformity and uncertainty of the population. CKOA is used to optimize the hyperparameters of Bidirectional Long Short-term Memory (BiLSTM) to improve the robustness and generalization ability of the model, making it suitable for dealing with complex nonlinear fault signals of hydropower units. The experimental results show that the training accuracy and testing accuracy of the CKOA-BiLSTM model are 97.6% and 98.3%, respectively, which are better than those of the LSTM, BiLSTM, and KOA-BiLSTM models. Meanwhile, diagnosing faults from the acoustic point of view, the accuracy of impact faults in hydropower units is much higher than that of wear and tear faults. This study can serve as a valuable supplement to the existing hydropower units condition monitoring and fault diagnosis system.

A comprehensive review of effective parameters to improve the performance of the Savonius turbine using a computational model and comparison with practical results

Amidst growing global concerns over climate change and escalating greenhouse gas emissions from fossil fuels, the pursuit of renewable energy sources has become critical. This study focuses on harnessing hydropower using Savonius turbines, which are known for their efficiency in generating energy at lower flow rates. However, the intrinsic low efficiency of these turbines necessitates precise optimization tailored to specific river or channel conditions. In this research, we optimized the performance of Savonius turbines by analyzing key parameters such as the height-to-diameter ratio, blade twist, and the integration of multi-stage configurations with deflectors. Our findings reveal significant efficiency improvements through strategic modifications. Specifically, by reducing the height-to-diameter ratio from 1.2 to 0.8 and maintaining a Tip Speed Ratio (TSR) of 0.6, the power coefficient increased by 15%, from 0.33 to 0.38. Further optimization was achieved by adjusting the blade twist angle, with an increase in power coefficient up to an optimal angle of 45°, beyond which efficiency declined. Implementing a two-stage turbine setup with a 90-degree phase difference between stages further improved the power coefficient to 0.51 at the same TSR. Additionally, the use of deflectors, particularly at a 90° angle, significantly boosted the power coefficient, highlighting their effectiveness in optimizing water flow impact on the turbine. This comprehensive study not only advances the understanding of Savonius turbine optimization but also contributes to broader renewable energy applications. The research offers critical insights into sustainable hydroelectric power generation, providing practical solutions to enhance turbine performance for real-world applications.

Determination of effects of climate change on hydropower generation at Kamburu dam-Kenya.

This study aimed to determine the effects of climate change on hydropower generation at Kamburu Dam, Kenya. Kamburu power plant has been experiencing low volumes of water with the shortage of rainfall from its catchment area. This study primarily utilised rainfall and temperature data, as well as field survey data collected through questionnaires. Primary data was collected using questionnaires, photography, checklists, and observation guides. Secondary data sources included Kengen and the meteorological department's annual reports. The study used simple stratified sampling. The four villages of the Kivaa sub-location were sampled into 20 households, making a total of 80 households; Kengen and meteorological stations sampled every 10 respondents to make a total of 100 respondents. Collected data from the questionnaires were coded and analysed using SPSS 29. The results of this research showed that the area experiences increasing temperatures of 0.044? every year and decreasing rainfall of 0.5897mm every year. The research forecasted a decadal increase in temperature of 0.44? and a decadal decrease in rainfall of 5.897mm. The research also showed a decrease in hydropower of 18,790MWH every year, translating to a decadal decrease of 187,790MWH. The research concluded that climate change has greatly affected hydropower production at the Kamburu Dam power plant. The research recommends afforestation and re-afforestation activities, putting rules and regulations of watershed management, upgrading the Kamburu dam infrastructure to fit climate-resilient, expanding the capacity of the dam, and energy storage, among others.

Ecological and socio‐political conflicts in the Turga Hydroelectric Project: An examination through the lens of political ecology

AbstractThe present paper critically examines water‐assisted developmental projects and their associated conflicts through the lens of political ecology, with a particular focus on hydroelectric power generation in the Global South. These projects often catalyze localized socio‐cultural, political, and ecological tensions, especially in indigenous territories where human–nature relationships have evolved through colonial and postcolonial ecological transformations. Our approach conceptualizes political ecology to explore the multidimensional conflicts tied to such projects, using the Turga Pumped Storage Hydroelectric Project in the Purulia district of West Bengal, India, as a case study. This region exemplifies the socio‐ecological conflicts between state‐led hydroelectric initiatives and the local indigenous communities, providing critical insights into the broader dynamics of water‐based development in the Global South. The five primary areas of inquiry in this paper include (1) the environmental ramifications of the Turga Pumped Storage Hydroelectric Project on Purulia's landscapes, wildlife, and ecosystems; (2) the social consequences that have emerged, including displacement, resource access disparities, and challenges to local livelihoods; (3) the power dynamics that shape the decision‐making processes surrounding the project, shedding light on the role of government policies and corporate interests; (4) comparative analyses with similar hydroelectric projects globally, providing valuable insights into the uniqueness of the Purulia case; and (5) the policy implications and recommendations to ameliorate the conflicts and foster a more sustainable and equitable approach to hydroelectric development. This study highlights the critical role of political ecology in understanding human–nature conflicts and resource management. It emphasizes the need for an integrative approach that considers both technological and socio‐political aspects. The Turga Pumped Storage Project in Purulia offers broader insights into the global challenges of sustainable energy and climate change, underscoring the importance of inclusive and environmentally responsible energy production and resource management.

Promoting environmental sustainability: A policy perspective on hydroelectric power generation, foreign direct investments, and financial development

In today's rapidly evolving world, characterized by the menace of global warming and the ever-pressing call for sustainable energy solutions, the trilogy of hydroelectric power generation, foreign direct investment, and environmental quality is a compelling and indispensable dimension; all of which necessitate simultaneous consideration. In this quest, this research article aims to explore the nexus between hydroelectric power generation, foreign direct investment, and sustainability—within the framework of financial development. To this end, we have utilized annual data of the world's ten largest hydroelectric power-generating countries in the year 2021 for the period 1992–2019, and utilize the Westerlund-Edgerton LM Bootstrap, Augmented Mean Group, and Dumitrescu-Hurlin panel bootstrap causality methods as our main econometrics' batteries. Based on the empirical outcomes that study entails that financial development, foreign direct investments, and increasing economic growth reduce the environmental quality. We observed that hydroelectric power generation is an important driving force on environmental quality. The empirical outcomes further infer that as the financial development levels of countries increase, the positive impact of hydroelectric power generation on environmental quality becomes more significant. The study findings will help policymakers to organize environmental quality strategies that are more realistic and accurate.

The physical and numerical modeling to design the breast wall spillway – AS case study

ABSTRACT The river systems in the Himalayan region exhibit year-round flow due to precipitation during the rainy season and snow/glacier melt in summer. These rivers carry massive sediment loads, especially during monsoons. Hydraulic engineers face the challenge of designing infrastructure capable of managing this sediment. Breast wall spillways are recommended for their ability to handle floodwaters and sediment disposal. The hydraulics of breast wall/orifice spillways changes with the varying reservoir level. The flow is free flow for reservoir water levels below the top of the sluice, whereas for higher water levels the flow is orifice flow. Orifice spillways are designed to pass water through openings or gates, where the flow is primarily governed by the hydraulic head and the orifice size. The flatter bottom profile helps in smoothly directing the flow through the opening without causing significant turbulence or separation, especially when the gate is partially open. Hence, the crest profile is flatter as compared to the overflow crest profile to avoid flow separation and negative pressures on the crest for small gate openings. Kwar Hydro Electric Project is one such Himalayan region project planned across the Chenab River in which a breast wall spillway has been provided to serve the dual-purpose of flood and sediment disposal. The present paper describes the physical and numerical hydraulic model studies conducted for Kwar H .E. Project, Jammu and Kashmir, to evolve a breast wall spillway profile, ski jump type energy dissipator at the toe of the spillway.

The Environmental Impact of Hydroelectric Power Generation

Hydroelectricity is daily elements that appears everywhere in human societies. It is a clean and renewable resources that is produced by fast speed of water. The effective way of generating energy feasibly prompted to different countries that have rivers. The construction of dams boosted tourists, fishing industries, timbering, and hunting. Expanded more leisure activities for people. The increases of dams also impacted on local economies such as jobs and selling electricity. However, this paper also highlights that these dams also damaged local ecosystem, deforestation, and pollution. They generate electricity by spinning the blades. As a consequence, fishes can smash and crewed into those machines and killed, including some endanger animals. Dams destroyed their biomes. Some weak dams still depend on burning coals and fuels. Waste gases get absorbed by water and algae, and finally pollute water. The polluted water can kill plantations and crops, hence causing economic losses and damaging the ecosystem. Deforestation is also caused by those waste chemicals and gases. The waste absorbed by soils caused acidic soil, and waste gases will cause climate change, which is the main reason of biome shift or deforestation. Poor soil availability conducted by acidic soil step forward decreasing of plants. Generally, dams directed and undirected caused environmental damage, that humans can never affords.

Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire

The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.

Optimizing dynamic voltage restorers with Bee Optimization Algorithm for enhanced power quality in modern hydro turbine grids

ABSTRACT This study explores the optimization of dynamic voltage restorers (DVRs) within hydro turbine systems using the Bee Optimization Algorithm (BOA), focusing on enhancing power system stability and quality through advanced control strategies. Emphasizing total harmonic distortion (THD) minimization, the research addresses power quality challenges prevalent in hydroelectric power generation. Detailed simulations demonstrate how BOA effectively reduces THD, optimizing DVR performance in response to grid disturbances typical in renewable energy integrations. Findings validate the BOA's efficacy in improving voltage stability and underscore the potential of bio-inspired algorithms for smart grid applications in hydro settings. This approach not only supports the reliability of hydroelectric power systems but also opens new avenues for employing multi-objective optimization techniques to advance DVR functionality, contributing to the sustainable management of energy infrastructures.

Dam(n) Displacement: Compensation, Resettlement, and Indigeneity

Hydroelectric dams produce electricity, provide flood control, and improve agricultural irrigation. But the building and operation of these dams frequently involve forced displacement of local communities. Displacement often has an outsized impact on indigenous persons, who are disproportionately poor, repressed, and politically marginalized. One can limit these adverse effects in various ways: (1) taking seriously the ethics of dam-induced development, (2) rooting out corruption, (3) paying compensation at or near the beginning of dam projects, (4) using land-for-land exchanges, (5) disbursing resettlement funds as needed until displaced persons are firmly established in their new locations, and (6) having entities that loan money to foreign governments for power dams insist that a percentage of the loan be sequestered to cover compensation and resettlement costs. This sextet of sensible measures must, however, be applied to highly different countries and indigenous persons. This application will be unsuccessful unless these measures fit the local situations on the ground. This Article shows how one can succeed in two quite different countries–China and Guatemala–in which past efforts have proved inadequate. Maya Achi displaced by the Chixoy Dam in Guatemala are an “indigenous people” under any traditional definition. Ethnic minorities displaced by dams in China are not traditional indigenous peoples because historical narratives of outsider conquest and colonization do not apply to them. They are, however, indigenous ethnic minorities. The Han Chinese supermajority dominates, represses, and discriminates against them. China ought to treat them in basically the same way that other countries ought to treat their indigenous peoples.

All‐in‐One Hybrid Solar‐Driven Interfacial Evaporators for Cogeneration of Clean Water and Electricity

AbstractSolar‐driven interfacial evaporators (SDIEs) have recently attracted considerable interest due to their ability to harvest abundant solar energy and treat seawater/wastewater for both freshwater production and electricity generation. However, during photothermal conversion in SDIEs, a portion of the incident sunlight is inevitably wasted, which presents an opportunity for potential alternative applications. There are also other types of harvestable energy like interactions between absorber materials’ surfaces and water/ions—called hydroelectricity (HE), as a form of renewable energy. This review paper provides an overview of studies focusing on utilizing SDIEs with a single structure capable of simultaneously producing freshwater and electricity, referred to as all‐in‐one hybrid SDIEs, with a particular emphasis on the HE power generation mechanism, which is the most commonly applied. An introduction to the photothermal conversion of sunlight into heat and fundamental aspects of the HE effect in hybrid SDIEs are discussed accordingly. The key results from studies on photothermal materials employed in all‐in‐one hybrid SDIEs are then explained and compared. This review will be concluded by spotlighting recent advancements, existing challenges, and promising opportunities that lie ahead for the materials used in these systems.

Assessing the sustainability of small hydropower sites in the Citarum Watershed, Indonesia employing CA-Markov and SWAT models

ABSTRACT This study investigates the sustainability of potential small hydropower sites within the Citarum Watershed in West Java, Indonesia. The Citarum River, with a catchment area of 6,090 km2, plays a crucial role in regional water supply and hydroelectric power generation. However, environmental challenges such as deforestation, land use changes, and sedimentation pose significant risks. We employed the CA-Markov model integrated with IDRISI TerrSet software and the Soil and Water Assessment Tool to predict future land use changes and assess water supply, soil erosion, and sedimentation impacts for 2030 and 2040. The analysis revealed diverse trends in water yield across different catchment areas, with some regions showing increased water availability and others facing declines. High erosion and sedimentation rates were identified as critical issues affecting hydropower efficiency. The study highlights the need for comprehensive watershed management strategies, including reforestation, sustainable land management practices, and sediment management, to enhance the sustainability of small hydropower projects. Our findings underscore the importance of integrating environmental considerations into hydropower development to ensure the ecological integrity of the Citarum Watershed.

Potential Utilization of Tamblang Dam for Micro Hydro Power Plant to Increase Renewable Energy Mix for Indonesia

Abstract Bali, a prominent tourist destination in Indonesia, faces an increasing demand for electricity, primarily supplied by non-renewable sources. With a target to increase renewable energy mix, Bali focuses on leveraging its water resources, notably Tamblang Dam, for hydroelectric power generation. This research aims to determine the potential utilization of Tamblang Dam as a micro hydro power plant, highlighting its capacity to significantly contribute to renewable energy mix in Indonesia generally and Bali particularly. Analysis reveals a potential electricity generation of 0.52 MW, with an annual hydro power production estimate of 4.57 GWh. Considering discharge availability, height of falling water and efficiency of hydro power system. The research also underscores the project’s economic viability and profitability, emphasizing its role in fostering sustainable energy practices in the region.

Optimizing Project Management System in Construction Development: A Case Study of the Upper Cisokan Hydro Electric Power Plant

This study explores project management challenges in the Upper Cisokan Hydro Electric Power Plant (UCPS HEPP) project, focusing on delays and inefficiencies in stakeholder engagement and execution processes. Key issues identified include delays in completing the Contractor's Environmental and Social Management Plan (C-ESMP), late preparation of detailed programs, the inability to provide timely financial statements, contractor's performance, including inadequate skills and systems. The study employs both qualitative methods, including observations and semi-structured interviews with key stakeholders to identify root causes and recommend solutions. Utilizing the PMBOKGuide's principles and AHP model, the study suggests that enhancing contractor skills, improving systems, and ensuring compliance with international standards are critical for project success. The findings provide practical insights for improving project management practices in similar large-scale infrastructure projects, particularly in emerging markets.

Creating sustainable capacity for river science in the Congo basin through the CRuHM project.

In this article, we examine the scientific and sustainable research capacity outcomes of the 'Congo River: user Hydraulics and Morphology' or CRuHM project, a six-year effort supported by the Royal Society's Africa Capacity Building Initiative. This project brought together a consortium of African and UK universities to undertake the first large-scale scientific expeditions to the Congo basin of the modern era in order to better understand the hydraulics and geomorphology of this understudied but globally important river. The river is essential for navigation, irrigation, drinking water and hydroelectric power generation for the 10 basin countries and is critically important for biodiversity and global nutrient, carbon and climatological cycles. This article summarizes the new scientific understanding contributed by the project and the steps taken to ensure a meaningful legacy that would continue long beyond the finite lifetime of available funding. Actions taken to achieve this include establishing a new hydrology research centre at the University of Kinshasa as well as steps to build a wider international community of Congo basin researchers. In this way, we hope to build momentum for future funding initiatives and collaboration.

How does geopolitical risk affect clean energy generation? Daily evidence from five highly Russia-reliant European countries

Europe has recently experienced an energy crisis that began with the war between Russia and Ukraine and continued with reciprocal sanctions and power cuts, increasing geopolitical tensions and risks. In such an environment, European countries must decide how to replace energy imports from Russia. As the best option may be to rely on clean energy, this study explores how geopolitical risk (GPR) affects clean electricity generation (i.e., hydro, solar, wind, & nuclear) in five European countries (i.e., Bulgaria, Czechia, Germany, Romania, and Switzerland), which have a high dependency on Russia. The study therefore uses daily data between January 2, 2019 and January 29, 2024 and applies a set of nonlinear methods (i.e., wavelet coherence, quantile-on-quantile regression, Granger causality in quantiles, and quantile regression). The results show that (i) there is a strong dependence of GPR on renewable and nuclear electricity generation over different times, frequencies, and countries; (ii) GPR stimulates hydro electricity generation at higher quantiles across countries except the Czechia; (iii) GPR increases solar electricity generation at higher quantiles in all countries except the Czechia and Switzerland; (iv) GPR mainly stimulates wind electricity generation at higher quantiles, except for Bulgaria and Switzerland; (v) GPR is almost inefficient in nuclear electricity generation. Overall, the study clearly shows the supportive effect of the GPR in promoting renewables, while this is not the case for nuclear energy. Therefore, European countries can rely on renewables as the best alternative against energy blackouts in the short term, considering the varying effect based on time, frequency, quantile, country, and clean energy sources.

A Review of the Impact of Impounded Rivers in KSA and as an Assessment of their Potential for Hydroelectric Power Generation

A Review of the Impact of Impounded Rivers in KSA and as an Assessment of their Potential for Hydroelectric Power Generation

Scalable and Interpretable Forecasting of Hydrological Time Series Based on Variational Gaussian Processes

Accurate streamflow forecasting is crucial for effectively managing water resources, particularly in countries like Colombia, where hydroelectric power generation significantly contributes to the national energy grid. Although highly interpretable, traditional deterministic, physically-driven models often suffer from complexity and require extensive parameterization. Data-driven models like Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) networks offer simplicity and performance but cannot quantify uncertainty. This work introduces Sparse Variational Gaussian Processes (SVGPs) for forecasting streamflow contributions. The proposed SVGP model reduces computational complexity compared to traditional Gaussian Processes, making it highly scalable for large datasets. The methodology employs optimal hyperparameters and shared inducing points to capture short-term and long-term relationships among reservoirs. Training, validation, and analysis of the proposed approach consider the streamflow dataset from 23 geographically dispersed reservoirs recorded during twelve years in Colombia. Performance assessment reveals that the proposal outperforms baseline Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) models in three key aspects: adaptability to changing dynamics, provision of informative confidence intervals through Bayesian inference, and enhanced forecasting accuracy. Therefore, the SVGP-based forecasting methodology offers a scalable and interpretable solution for multi-output streamflow forecasting, thereby contributing to more effective water resource management and hydroelectric planning.

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.