Hydroelectric Generation Research Articles

Modeling Electricity Generation and Consumption in Cameroon

Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models' results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26%, 5.26%, and 5.77% deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

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.

Assessing the influences of future water development projects in Tekeze-Atbara-Setit basin on the Nile River inflow at Aswan, Egypt

Study regionThe Tekeze-Atbara-Setit (TAS) basin as a portion of the Eastern Nile Basin (ENB) in Africa. Study focusENB consists of four sub-basins; one of them is the Tekeze-Atbara-Setit basin. TAS basin is subject to future water development projects, including irrigation projects and hydropower dams. Potential impacts of these projects need to be assessed regarding the inflow and hydroelectric generation at Egypt's High Aswan Dam (HAD). New hydrological insights for the regionTwo models are coupled offline; The Soil Water Assessment Tool (SWAT) model and HEC-Reservoir Simulation Model (HEC-ResSim). Base-case scenario is created without the expected future projects, in addition to five additional scenarios representing hydropower and irrigation projects. The maximum annual inflow at HAD declines by 1.6 km3 in the hydropower scenarios, while the produced power at HAD descends by 9.5 %. The maximum reduction in the annual inflow for hydropower and irrigation projects scenario at HAD is 4.63 km3 and 35.2 % for power reduction. Finally, the proposed future development project in TAS basin will have negative impacts on the flow, and generated hydropower at HAD in Egypt.

Green conversion of waste polyester into few-layer graphene for interfacial solar-driven evaporation and hydroelectric electricity generation

The coupling of solar-driven interfacial evaporation with hydrovoltaic technology is emerged as a hopeful approach to alleviate energy crisis and freshwater shortage. However, constructing low-cost evaporators with high-performance freshwater and electricity co-generation and unveiling the co-generation mechanism remain a grand challenge. Herein, we report the green transformation of waste poly(ε-caprolactone) into graphene through a salt-assisted carbonization strategy and build a flexible bi-functional graphene-based evaporator for freshwater and electricity co-generation. The graphene exhibits a typical wrinkled structure with curved edges and is composed of 7–8 discontinuous layers with rich oxygen-containing groups. The graphene-based evaporator exhibits excellent sunlight absorption (98%), photo-to-thermal conversion property, good water transport ability, low water evaporation enthalpy, and low thermal conductivity of 0.06 W m−1 K−1. The evaporator not only exhibits a notable water evaporation rate (2.92 kg m−2 h−1), but also achieves the maximum output voltage of 310 mV, surpassing many previously reported evaporators/generators. The result of molecular dynamics simulation proves the diffusion difference between H+ and OH− in water and graphene, which eventually leads to the voltage generation. Not only will this work help to improve the upcycling of waste plastics and achieve carbon neutrality, but it will also open an avenue for co-generation of freshwater and electricity.

Study of Unsymmetrical Magnetic Pulling Force and Magnetic Moment in 1000 MW Hydrogenerator Based on Finite Element Analysis

The large dimensions of the 1000 MW hydroelectric generator sets require high mounting accuracy. Small deviations can lead to asymmetry, which in turn triggers unbalanced magnetic pulls and moments. Therefore, symmetry is a central challenge in the installation and operation of giant hydroelectric generators. In this paper, the effects of radial eccentricity, axial offset, and rotor shaft deflection on the unbalanced magnetic pull and moment are investigated by transient finite element analysis of the asymmetric magnetic field. The results of the time-domain and frequency-domain analyses show that asymmetric operation generates unbalanced magnetic forces and moments. These forces and moments increase linearly with increasing offset or deflection rate. When the eccentricity meets the installation criteria, the unbalanced magnetic pull forces are small and within acceptable limits. This study helps to understand the relationship between asymmetry and unbalanced magnetic pulling forces in large hydroelectric generators, and provides a theoretical basis for standardizing installation deviation control.

Data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on multi-head attention mechanism

Accurate and reliable daily reservoir inflow forecast plays an essential role in several applications involving the management and planning of water resources, such as hydroelectric generation, flood control, water supply, and basin ecological dispatching. Runoff usually exhibits strong non-linearity, high uncertainty, and spatial and temporal variability. Existing techniques fail to capture complete dynamics change processes effectively. A data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on a multi-head attention mechanism was developed, referred to as the GWOCS-VMD-CNN-Transformer (GCVCT). First, the model utilize Grey Wolf Optimizer coupled with Cuckoo Search (GWO-CS) algorithms to optimize parameters in variational mode decomposition model (VMD). This approach helps obtain highly correlated intrinsic mode function (IMF) components, enhancing the frequency resolution of the input dataset. The proposed method overcomes the bottleneck of other available methods by decomposing the time series to capture the main long-term and short-term properties of hydrological processes. Second, the convolution neural network and Transformer (CNN-Transformer) are based on a multi-head attention mechanism as the objective predictive method. Finally, six evaluation indicators verify the performance of the proposed approach. The approach’s reliability was evaluated using the historical daily reservoir inflow data from the Xiluodu (XLD) and Wudongde (WDD) reservoirs in the Jinsha River Basin, China. Several single and hybrid models were developed for comparative analysis. The results indicate that the proposed ensemble approach fits better than other developed model methods. The GCVCT model showed excellent performance in forecasting the inflows of XLD and WDD reservoirs, with NSE values of 0.985 and 0.984, respectively. Furthermore, the GCVCT framework forecast capacity for peak inflow was further verified through discussion and analysis of the 48 peak flows during the validation period, consistently outperforming other models in predicting peak flow for both study reservoirs. This framework provides an effective method for the scientific optimal scheduling of hydropower reservoirs, enabling more sustainable and efficient management practices. It also demonstrates the potential of powerful deep-learning models in intelligent hydrological forecasting.

Analyzing sedimentation patterns in the Naumure Multipurpose Project (NMP) reservoir using 1D HEC-RAS modeling

Naumure Multipurpose Project (NMP) featuring a 169 m high Concrete Face Rock Filled Dam (CFRD) is the proposed reservoir project in the West Rapti River with an installed capacity of 218.34 MW. Most of the rivers in Nepal carry significant sediment loads that will consequently catalyze reservoir sedimentation. This phenomenon prevails as the primary factor in reducing reservoirs useful life, making ineffective for both flood control and hydroelectricity generation. Ultimately, such process of sedimentation has adverse impacts on projects economic feasibility and long-term sustainability. Therefore, the objective of this research was to examine the expected sediment deposition pattern in the NMP reservoir throughout its operational period by employing 1D HEC-RAS model to simulate the sedimentation process. The model was simulated for 10, 20, 30, 40 and 50 years. Yang’s equation as a sediment transport function, Active layer as a bed sorting method and Toffaleti as a fall velocity method were best suited for the river reach. The delta deposition was formed between 11 km and 22 km upstream of the dam region in the Jhimruk river, with the sediment deposition depth reaching peaks of about 23 m, 38 m, 39 m, 41 m and 49 m in 10, 20, 30, 40 and 50 years, respectively. Similarly, the delta deposition was formed between 13 km and 33 km upstream of dam region in the Madi river, with the sediment deposition depth reaching peaks of about 47 m, 62 m, 60 m, 68 m and 75 m in 10, 20, 30, 40 and 50 years respectively. Headcutting of delta deposition occurred between 20 and 30 year due to high flood during low stage of reservoir. Furthermore, the study revealed that about 6.22%, 11.61%, 15.94%, 22.96% and 25.65% of the storage capacity of NMP reservoir will be depleted in 10, 20, 30, 40 and 50 years respectively.

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.

Scenarios for wind capacity deployment in Colombia by 2050: A perspective from system dynamics modeling

Over the past few decades, there has been significant development in actions aimed at global energy transition, with the goal of reducing greenhouse gas emissions. The energy sector plays a significant role in this endeavor, contributing 76% of the world's total emissions. Considering electrification as an alternative promotes the deployment of technologies that use renewable sources, such as wind energy in coastal and offshore areas. In Colombia, wind energy alone has an accumulated technical potential of approximately 82 GW, mainly concentrated along the northeastern coast. Exploiting this technology enables the development of the national electrical system, reducing dependence on hydroelectric generation, strengthening the system against climate seasonality by ensuring supply security, environmental sustainability, and equitable energy access. Supported by system dynamics modeling, this paper presents four scenarios that explore possible futures for wind capacity deployment in Colombia between 2020 and 2050. It considers uncertainties in political and economic domains, as well as crucial national factors such as social acceptance, supply chain development, and transmission infrastructure. Favorable alignment of these factors towards wind diffusion could lead to nearly 29 GW of installed capacity by 2050, representing 40% of the projected total capacity of the electricity sector.

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.

Load Frequency Optimal Active Disturbance Rejection Control of Hybrid Power System

The widespread adoption of the power grid has led to increased attention to load frequency control (LFC) in power systems. The LFC strategy of multi-source hybrid power systems, including hydroelectric generators, Wind Turbine Generators (WTGs), and Photovoltaic Generators (PVGs), with thermal generators is more challenging. Existing methods for LFC tasks pose challenges in achieving satisfactory outcomes in hybrid power systems. In this paper, a novel method for the multi-source hybrid power system LFC task by using an optimal active disturbance rejection control (ADRC) strategy is proposed, which is based on the combination of the improved linear quadratic regulator (LQR) and the ADRC controller. Firstly, an established model of a hybrid power system is presented, which incorporates multiple regions and multiple sources. Secondly, utilizing the state space representation, a novel control strategy is developed by integrating improved LQR and ARDC. Finally, a series of comparative simulation experiments has been conducted using the Simulink model. Compared with the LQR with ESO, the maximum relative error of the maximum peaks of frequency deviation and tie-line exchanged power of the hybrid power system is reduced by 96% and 83%, respectively, by using the proposed strategy. The experimental results demonstrate that the strategy proposed in this paper exhibits a substantial enhancement in control performance.

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.

Transition towards net zero emissions: Integration of a PV/T system with a hydroelectric generator and the impact of demand-side management

With the aim of diversifying different energy sources and achieving net zero emissions, hybrid renewable energy sources (HRES) represent the future of the world. However, several HRES simulation software do not integrate the Photovoltaic/thermal (PV/T) system. This article designs an optimal design model for a tri-hybrid Photovoltaic/thermal/hydroelectric (PV/T/H) system for a rural locality in the North Cameroon region. The two Demand Side Management (DSM) strategies used reveal that the DSM strategy significantly reduced the energy cost by 59 % and the emission by CO2 22 % compared to the No-DSM mode. Although the use of battery storage (BSS) is used in both cases, the optimal solutions obtained thanks to the multi-objective optimization method implemented on Matlab led to 418 PV/T panels, 2 MH generators, 2 diesel generators (DG) and 217 PV/T panels and 1 DG for DSM and No-DSM mode respectively. This study is a demonstration of the effect of dynamic tariffs and active demand management technologies on PV/T/H modeling and optimization. It also reveals the need to hybridize PV/T with other energy systems to increase performance and achieve net zero emissions.

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.

Numerical Investigation of Effects of Ripple Type Needle Erosion on Pressure Inside a Pelton Nozzle

Abstract Pelton turbines, a commonly used impulse turbine for hydroelectric generation which converts the potential energy of the water into kinetic energy through a needle structure within the nozzle system. However, the exposure of the Pelton turbine components such as needle, seat ring, buckets to the sediment laden water can erode these components. The erosion on the needle can also lead to the efficiency degradation. This study aims to investigate the effect of needle erosion on the pressure dynamics within the Pelton nozzle system. For the study purpose, the nozzle system from Pelton rig at the Waterpower Laboratory, NTNU is used and a general erosion pattern is developed through literature and field information. The research focuses on analysing the difference in pressure distribution between the normal and eroded needles under different opening conditions, with the objective of understanding how erosion affects the nozzle performance. Single-phase 3-D simulations are performed with an unstructured ANSYS mesh and the CFX solver. This study examines the static pressure at the inner surface of the nozzle casing wall. The results show that for a constant head at the inlet boundary condition, the static pressure with eroded needles was significantly lower than that with normal needles. The pressure difference was around 1.88 kPa for a 60% nozzle opening and around 3.57 kPa for a 40% nozzle opening. The reduction in pressure is due to the increased area in the needle orifice and nozzle outlet caused by erosion, which is more pronounced at lower openings. The findings reveal a direct correlation between needle erosion and alterations in pressure distribution, highlighting the necessity for vigilant monitoring and timely maintenance. The study provides valuable insights into optimizing turbine performance in sediment-laden water conditions and underscores the importance of addressing needle erosion to maintain efficiency.

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

Unraveling the hydropower vulnerability to drought in the United States

Abstract Drought, a potent natural climatic phenomenon, significantly challenges hydropower systems, bearing adverse consequences for economies, societies, and the environment. This study delves into the profound impact of drought on hydropower generation (HG) in the United States, revealing a robust correlation between hydrologic drought and hydroelectricity generation. Our analysis of the period from 2003 to 2020 for the Contiguous United States (CONUS) indicates that drought events led to a considerable decline in hydroelectricity generation, amounting to approximately 300 million MWh, and resulting in an estimated loss of $28 billion to the sector. Moreover, our findings highlight the adverse environmental effect of drought-induced HG reductions, which are often compensated by increased reliance on natural gas usage, which led to substantial emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxide (NO X ), totaling 161 700 kilotons, 1199 tons, and 181 977 tons, respectively. In addition to these findings, we assess the state-level vulnerability of hydropower to drought, identifying Washington and California as the most vulnerable states, while Nevada exhibits the least vulnerability. Overall, this study enhances understanding of the multifaceted effects of drought on hydropower, which can assist in informing policies and practices related to drought management and energy production.