Hydroelectric Generation Research Articles

The political economy of the climate crisis in Southern Africa

ABSTRACT This article maps out the dynamics of the climate crisis that is unfolding globally, but whose consequences have a disproportionate impact on countries in sub-Saharan Africa and the wider global South. Although these countries have contributed insignificant amounts of greenhouse gas emissions (compared to their industrialised counterparts), their populations are the major victims of climate change, whose disastrous impacts were recently witnessed in Zimbabwe during Cyclone Idai and in South Africa during the Durban floods. In addition, Southern Africa is experiencing climate change-induced droughts, depleting water in major dams and undermining hydroelectric power generation, especially in Zambia and Zimbabwe. As a result, the region is experiencing dangerous power outages affecting agriculture and other key industries. This article adopts a novel decolonial perspective to make sense of these extreme weather events, arguing that the climate crisis is already affecting the livelihoods of many people in Southern Africa and that it is often the poor and vulnerable who suffer most from the impacts of climate change. There is thus a need for industrialised countries to contribute towards the costs of climate change mitigation since they are historically responsible for most of the carbon emissions.

Increasing ecological sustainability using the combinations of technologies to produce power

The study attempts to analyze the impact of hybrid energy systems on environmental sustainability in the context of the circular economy network. The hybrid energy sources follow the principle of circular economy, which aims to reduce raw material use and waste which is very fruitful in promoting environmental sustainability. However, the study uses quarterly data from Pakistan from 2011Q1 to 2020Q4 to accomplish the proposed study objective. The study constructs 5 hybrid systems of energy to analyze the impact and applies Auto Regressive Distributive Lag Model (ARDL) to estimate the results. It is found that electricity generation through solar photovoltaic (SPV), wind turbine (WND), hydroelectricity (HYDE) and nuclear power generation (NPG) play a positive role in increasing environment sustainability. The results explain that SPV, NPG, and HYDE contribute 2.29%, 2.04%, and 0.42% to environmental sustainability, respectively. Hybrid systems of energy (Hybrid 1,2,3,4 and 5) positively impact ecological sustainability, but the intensity of each hybrid system in sustaining the environment is different. Among five hybrid systems, the hybrid-5 (SPV-WND-HYDE-NPG) energy system is more environmentally friendly and has the highest contribution towards environmental sustainability. The study suggests incorporating hybrid energy systems provides the means of transition toward a circular economy, ultimately promoting ecological sustainability. The study proposes to the officials of the Pakistani government and policymakers to initiate effective policies to encourage hybrid energy systems because the significance of hybrid systems ensures a low carbon economy and makes a path towards sustainable economic development.

“The Last Victims of the Indian War”: Celilo Falls, the Dalles Dam, and Infrastructural Colonization

In 1957, the Dalles Dam was constructed on the Columbia River between Washington and Oregon. When the dam was completed, it inundated Celilo Falls, a Native American fishery and cultural gathering point that had been in use for at least 12,000 years. Prior to dam construction, the federal government and local agencies issued a number of reports stating the necessity of the dam for economic development through hydroelectric power generation, improved shipping navigation, flood control, and expanded irrigation capacity. These reports often sought to determine the financial payout that would be made to the groups with treaty rights to fish at their “usual and accustomed” places, such as Celilo Falls. However, the reports rarely engage with the cultural significance of Celilo Falls or the depth of opposition that people had to the dam. The research discussed here is based on archival government reports alongside the voices of affected tribal members preserved through The Confluence Project and other sources. This article develops the idea that reclamation infrastructure in the U.S. West plays a key role in colonizing efforts from federal to local scales, reflecting the aims of the settler state. Through an analysis of government documents alongside the recollections of Indigenous elders from the mid-Columbia region, this article offers insights into how reclamation infrastructure functions as an aspect of settler colonialism and relies on theorizations of this process from the people most affected by the loss of Celilo Falls.

Analysis of the cause of power system inertia generation and decline

Variable renewable energy sources (RES) are becoming more and more common, and traditional power generation plants are rapidly being replaced by them. As RES are used more frequently, power electronics are also utilized more frequently, both to connect RES and as drives for electric motors. As a result, the inertia level of the power system is continuously decreasing, and the frequency stability of the power system is facing severe challenges. Traditional power-generating methods such as thermal, hydroelectric, nuclear, and natural gas use generators to produce electric energy. By utilizing the rotational inertia of the steam turbine unit, the frequency fluctuation trend that occurs in the power grid can be delayed. However, photovoltaic power generation lacks rotating machinery and has no rotational inertia, whereas wind turbines operate at a modest speed and have negligible rotational inertia. The response capability is reduced significantly when the power grid's frequency changes. Any electric power system tends to rely on rotational inertia. The relevant factors impacting the inertia level of the power system are introduced based on the concept of inertia of the power system. The power system experiences inertia from the synchronous grid-connected generation side, the load side, and the grid-connected generation side of the converter. These three sources make up the majority of the inertia in the system. From the aspects of the power generating side, grid side, and load side, approaches and strategies to increase the frequency stability of power systems are introduced.

Paper-Based Hydroelectric Generators for Water Evaporation-Induced Electricity Generation.

The research presented in this paper introduces a novel environmental energy-harvesting technology that harnesses electricity from the evaporation of water using porous structural materials. Specifically, a strategy employing paper-based hydroelectric generators (p-HEGs) is proposed to capture the energy produced during water evaporation and convert it into usable electricity. The p-HEGs offer several advantages, including simplicity in fabrication, low cost, and reusability. To evaluate their effectiveness, the water evaporation-induced electrical output performance of four different p-HEGs are compared. Among the variants tested, the p-HEG combining wood pulp and polyester fiber exhibits the best output performance. At room temperature, this particular p-HEG generates a short-circuit current and open-circuit voltage of ≈0.4µA and 0.3V, respectively, thereby demonstrating excellent electrical stability. Furthermore, the electrical current and voltage generated by the p-HEG through water evaporation are able to power an LED light, both individually and in series and parallel connections. This study delves into the potential of electricity harvesting from water evaporation and establishes it as a viable method for renewable energy applications.

Spatial and Temporal Analysis of Hydrological Modelling in the Beas Basin Using SWAT+ Model

In this research, the SWAT+ model was employed to elucidate hydrological dynamics within the Beas Basin. The primary objectives encompassed the calibration of the SWAT model for accurate water balance quantification, annual simulation of salient hydrological components, and a decadal analysis of trends in fluvial discharge and sediment transport. The methodology encompasses simulating hydrological data with the SWAT+ model, followed by calibration and validation using flow data from Larji and Mahadev hydroelectric plants. The model’s efficacy in depicting streamflow and other hydrological components is corroborated by statistical measures such as the Nash–Sutcliffe efficiency and PBIAS. The water balance analysis delivers insights into the basin’s hydrological characteristics, including surface flow, water yield, and evapotranspiration. The temporal analysis exposes intricate seasonal and interannual variability in flow and sediment discharge, while spatial distribution highlights heterogeneity across the basin. These findings have practical implications for water resource management, including optimizing water allocation, hydroelectric power generation, irrigation, and environmental concerns. Limitations, such as data quality and model simplifications, are acknowledged, and future data collection and observations are recommended for improved model performance. In essence, these researches enhance understanding of the Beas Basin’s hydrology, setting a course for future investigations to integrate more data sources, refine model parameters, and consider climate and land-use changes for a richer comprehension of the basin’s hydrological dynamics.

Low-Carbon Economic Dispatch of Electricity and Cooling Energy System

In response to the issue of the hydropower consumption of run-of-river hydropower stations in Southwest China, the district cooling system can provide regulation capacity for hydropower utilization and suppress fluctuations caused by the uncertainty of hydropower. The innovative method is to utilize the thermal characteristics of pipelines and buildings, as well as the thermal comfort elasticity to shift the cooling and electricity loads, which helps to consume the surplus hydroelectric power generation. Taking the minimum total cost of coal consumption in thermal power units, hydropower abandonment penalty, and the carbon trading cost as the objective function, models were established for power supply balance constraints, heat transport constraints, and unit output constraints. The hybrid integer linear programming algorithm was used to achieve the low-carbon economic dispatch of the electric-cooling system. The calculation examples indicate that compared to the traditional real-time balance of cooling supply, the comprehensive consideration of thermal characteristics in a cooling system and flexible thermal comfort have a better operational performance. The carbon trading cost, coal consumption cost, and abandoned hydropower rate of a typical day was reduced by 4.25% (approximately CNY 7.55 × 104), 4.47% (approximately CNY 22.23 × 104), and 3.66%, respectively. Therefore, the electric-cooling dispatch model considering the thermal characteristics in cooling networks, building thermal inertia, and thermal comfort elasticity is more conducive to the hydropower utilization of run-of-river stations.

Land Use and Land Cover Change Detection Using the Random Forest Approach: The Case of The Upper Blue Nile River Basin, Ethiopia.

Monitoring land use change dynamics is critical for tackling food security, climate change, and biodiversity loss on a global scale. This study is designed to classify land use and land cover in the upper Blue Nile River Basin (BNRB) using a random forest (RF) algorithm. The Landsat images for Landsat 45, Landsat 7, and Landsat 8 are used for classification purposes. The study area is classified into seven land use/land cover classes: cultivated lands, bare lands, built-ups, forests, grazing lands, shrublands, and waterbodies. The accuracy of classified images is 83%, 85%, and 91% using the Kappa index of agreements. From 1983 to 2022 periods, cultivated lands and built-up areas increased by 47541 and 1777 km2, respectively, at the expense of grazing lands, shrublands, and forests. Furthermore, the area of water bodies has increased by 662 km2 due to the construction of small and large-scale irrigation and hydroelectric power generation dams. The main factors that determine agricultural land expansion are related to population growth. Therefore, land use and land cover change detection using a random forest is an important technique for multispectral satellite data classification to understand the optimal use of natural resources, conservation practices, and decision-making for sustainable development.

SWAT model-based quantification of the impact of land use land cover change on sediment yield in the Fincha watershed, Ethiopia

In recent years, Ethiopia is facing problems due to soil erosion, mainly because of the conversion of natural vegetation into cultivated land to answer to increasing human pressure. Such changes in coverage are fostering soil erosion, which is also affecting dam reservoirs, because of the increasing sediment yield entering the lake. The present study focuses on the Ethiopian Fincha watershed and takes advantage of the potentiality of the Soil and Water Assessment Tool (SWAT) model, to investigate how land use land cover changes impact soil erosion and the consequent sediment yield entering the Fincha Dam. The SWAT model was calibrated and validated using time series data of stream flow and sediment covering the period 1986-2008, and its performance was evaluated by looking at the coefficient of determination, Nash-Sutcliffe simulation efficiency, and per cent bias. Once validated, the SWAT model was applied to derive sediment yield for the future 30 years, based on forecasted land use land cover conditions. The results show that the mean annual soil loss rate increased from 32.51 t ha−1 in 1989 to 34.05 t ha−1 in 2004, reaching 41.20 t ha−1 in 2019. For the future, a higher erosion risk should be expected, with the annual soil loss rate forecasted to be 46.20 t ha−1 in 2030, 51.19 t ha−1 in 2040, and 53.98 t ha−1 in 2050. This soil erosion means that sediments transported to the Fincha Dam, located at the watershed outlet, increased significantly in the last 30 years (from 1.44 in 1989 to 2.75 mil t in 2019) and will have the same trend in the future (3.08–4.42 mil t in 2020 and 2050, respectively), therefore highly affecting the Fincha reservoir services in terms of reduction of water volume for irrigation and hydroelectric power generation. By providing possible medium/long-term scenarios, the present work can help land planners and decision-makers in developing future land management strategies based on actual projections, eventually aiming to reduce soil erosion at the watershed scale and guarantee the sustainable development of the Fincha region and its key hydraulic infrastructures.

Characterization of Climatic Parameters and River Flow Capacity on Electricity Generation in Jebba Dam, Nigeria

This study examined the characterization of climatic parameters and river flow capacity on electricity generation in Jebba Dam, Nigeria. It is a known fact that climatic parameters of rainfall, temperature and evaporation have the capacity to influence reservoir inflow and outflow as well as hydropower generation. The study collected secondary data of climatic parameters, reservoir inflow and outflow as well as hydropower generation from Mainstream Energy Solution Limited in 2018. The data were analyzed using averages and represented in graphs and charts. The results showed that there was rise in power generation from July to December with November having the highest power generation of 432.5MWH. Reservoir inflow and outflow rose from July to December with September having the highest discharge of 4860m3 /sec inflow and 4858 m3 /sec outflow. There was noticeable rise in rainfall pattern from May to November with September having the highest rainfall regime of 330.4mm in the Jebba river basin. However, February and November had the highest temperature regime of 360C each in the Jebba river basin. The highest evaporation rate was recorded in March having 25m3 /sec during the period. Finally, the study has revealed the effects of these climatic parameters on the reservoir flow and hydropower generation in the Jebba dam. Therefore, the government should strictly consider the phenomenon of climate change as it affects hydroelectric power generation in Nigeria without further delay.

Issues of Crack Formation in Supporting Structures of a Hydroelectric Generator and Their Remedies

Issues of Crack Formation in Supporting Structures of a Hydroelectric Generator and Their Remedies

Identifying the influence of blade number and angle of attack on a breastshot type waterwheel micro hydroelectric power generator using ANOVA

This study focuses on optimizing the performance of micro-hydro power generation, specifically the breastshot type waterwheel. The limited availability of non-renewable energy sources and the high cost of developing renewable energy sources in the energy sector pose challenges, making it essential to find new energy sources and improve energy efficiency. The 2004–2022 national electricity plan aims to increase electricity access in rural areas, including remote regions like Bogor Regency, where access to electricity is limited. Many residents have constructed their own micro hydroelectric power generators, but their vulnerability to natural disasters is a concern. The study investigates the potential of breastshot waterwheel technology for micro hydroelectric power generation. The study involved testing a micro hydro power plant with 6, 8, and 10 blades and blade angles of 0°, 30°, and 45°. The current research focuses on performance optimization, including the use of ANOVA analysis to know the significant impact of blade number and angle on the waterwheel’s rotation. The maximum rotational speed was achieved with 10 blades and an angle of attack of 0°, 30°, and 45°, with respective speeds of 153.59 RPM, 155.84 RPM, and 164.95 RPM. The study indicates that the higher the number and angle of attack of blades, the greater the rotation of the breastshot type waterwheel. ANOVA tests showed that the number of blades had a significant impact on the waterwheel’s rotation, with an F-test value of 6.32 and a p-value of 0.012. On the other hand, the angle of attack of the blade had no significant impact, with an F-test value of 3.20 and a p-value of 0.067

Simulation of shell and tube type heat exchanger for square geometry using computational fluid dynamics method

Heat exchangers have various types of design models, one example is the shell and tube type heat exchanger. This tool is useful for raising or lowering the temperature. One of its uses is in the hydroelectric power generation industry, namely as an oil cooler bearing. This study aims to design and simulate a shell and tube type heat exchanger with tube inner diameters of 20 mm and 25 mm and also tube arrangement square and rotated square. From the design results obtained a total length of 1318.59 mm, 300 mm outer diameter of the shell and 320 mm inner diameter of the shell. The simulation results show that variations in tube diameter and tube arrangement greatly affect the performance of the heat exchanger, the highest value for the overall heat transfer coefficient is found in the tube square arrangement variation with the number of tubes 61 of 112.15 W/m2.K and the lowest value in the tube arrangement variation square with the number of tubes 55 is 106.48 W/m2.K, the highest value of pressure drop on the shell side is found in the variation of the tube square arrangement with the number of tubes 55.

Impact of climatic factors on the prediction of hydroelectric power generation: a deep CNN-SVR approach

This study, which aims to make predictions using a previously unused deep hybrid Convolutional Neural Network-Support Vector Regression approach for hydropower generation, was carried out using a unique meteorological data set as input data. The unique dataset was collected from Kaman Meteorology Directorate and Hirfanlı HEPP in Turkey, from 2007 to 2021, to estimate the HEPP's Net Head and Hydroelectric Power Generation on a daily basis. The performances of the prediction models were benchmarked in addition to the used CNN-SVR model with Machine Learning (ML) models (Boosting Random Forest Regression (BRFR) and Weighted K-Nearest Neighbor Regression (WKNNR)) and Deep Learning (DL) models (Long-Short Term Memory (LSTM) and Deep Belief Network (DBN)). The comparison results of the used CNN-SVR model with other alternative models showed that CNN-SVR performed effectively with the highest correlation coefficient of 0.971 for NH and 0.968 for PP.

A health condition assessment and prediction method of Francis turbine units using heterogeneous signal fusion and graph-driven health benchmark model

To ensure the safety and efficiency of hydroelectric power generation, the health condition assessment and prediction (HCAP) of Francis turbine units (FTUs) have been widely concerned. To this end, some data-driven methods based on health benchmark model (HBM) and performance deterioration index (PDI) have been proposed, but there are still some shortcomings: 1) Only one type of signal is used for FTU health monitoring and assessment, which cannot fully represent the deterioration of the system. 2) The establishment of HBM only focuses on the time sequence dependences of signals, while ignoring the inter-correlations between signals. 3) PDI based on linear difference measurement cannot integrate heterogeneous signal representations to fully assess FTU status. In this paper, a HCAP method of FTUs using heterogeneous signal fusion and graph-driven HBM is proposed. First, the multivariate data of health status are transformed into spatial-temporal graphs by establishing connections between similar signals. Furthermore, a hybrid neural network-based HBM is designed to excavate the spatial-temporal dependence relationships existing in these graphs, and learn the mapping relationship between working condition parameters and monitoring signals. Finally, Mahalanobis distance between the heterogeneous signals predicted by HBM and the measured signals in the degraded status is calculated, and the comprehensive PDI for HCAP tasks is obtained by the designed heterogeneous signal fusion function. Verification experiments show that the proposed HCAP method effectively assesses FTU deterioration degree earlier with a higher sensitivity.

Research Progress on the Application of Triboelectric Nanogenerators for Wind Energy Collection.

The escalating global energy demand necessitates the exploration of renewable energy sources, with wind energy emerging as a crucial and widely available resource. With wind energy exhibiting a vast potential of approximately 1010 kw/a per year, about ten times that of global hydroelectric power generation, its efficient conversion and utilization hold the promise of mitigating the pressing energy crisis and replacing the dominant reliance on fossil fuels. In recent years, Triboelectric Nanogenerators (TENGs) have emerged as novel and efficient means of capturing wind energy. This paper provides a comprehensive summary of the fundamental principles governing four basic working modes of TENGs, elucidating the structures and operational mechanisms of various models employed in wind energy harvesting. Furthermore, it highlights the significance of two major TENG configurations, namely, the vertical touch-separation pattern structure and the independent layer pattern for wind energy collection, emphasizing their respective advantages. Furthermore, the study briefly discusses the current strengths of nano-friction power generation in wind energy harvesting while acknowledging the existing challenges pertaining to device design, durability, operation, and maintenance. The review concludes by presenting potential research directions and prospects for triboelectric nanogenerators generation in the realm of wind energy, offering valuable insights for researchers and scholars in the field.

Finite element analysis of the localized post-weld heat treatment of a Pelton runner

Pelton and Francis runners are critical components of the turbines of hydroelectric power generation plants. When damaged in service, they must be welded to restore their shape and performance. The most common material for these components is DIN G-5CrNi13–4 or ASTM A743 grade CA6NM stainless steel, which can experience issues during welding such as high hardness in the heat-affected zone (HAZ) due to the formation of fresh martensite, hydrogen-induced cracking and high residual stresses at and around welds. Post-weld heat treatments (PWHT) are used to temper the martensite in the weld metal and the HAZ and reduce the level of residual stresses. When the regions to be treated represent a small fraction of the total volume of the runner, it is not economical to heat treat the entire part in a large furnace. Therefore, localized heat treatments constitute a cost-effective solution. In this work, a numerical model has been developed to predict the performance of an in situ PWHT device under different operating conditions. The model takes into account the calculation of the power supply requirements for the heat treatment of a Pelton runner, the effect of changing the dimensions of the heating elements, and the relevance of the environmental conditions of the repair site. Taken together, these results are important in anticipating possible adjustments required to follow the expected heat treatment curve. The potential of this model is also demonstrated by using the estimated transient power supply to determine the performance of the control system of the PWHT device and reduce the number of runs required for its tuning. This methodology can be extended to the PWHT of other geometries and materials.

Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021

Precipitation is the major input of the hydrological cycle in tropical regions. Changes in the spatial and temporal patterns of precipitation should be investigated in order to provide in-time information for both water and land use planning. Climate and land use changes have been influencing modification in the water cycle, demanding adaptations and increasing the vulnerability of water-dependent systems. This study investigated spatial and temporal changes in precipitation patterns in the Paranapanema River Basin (PPRB), Brazil. The PPRB region is an important agricultural and hydroelectric power generation hub and has been suffering from water crises in recent years, and more intensely in the last 5–10 years. The analysis used remote sensing precipitations data from September 2000 to August 2021 (summing up twenty-one hydrological years) at 0.1° resolution. Exploratory Spatial and Temporal Data Analysis (ESTDA) were applied to verify spatial local autocorrelation and hot/cold spots clusters, and temporal trends, homogeneity, and change points in the time series at Hydrological Planning Unit (HPU) scale level. The significant results were discussed based on statistical tests and land use cover change data. There is a strong presence of precipitation spatial patterns in the PPRB. Also, the PPRB presented modifications in the precipitation regime over the analyzed period, with significant change points around 2015—2017. Further monitoring is recommended in order to confirm these results in the long term, however, the provided information can already be used as an award to local and regional water bodies installed in the river basin, supporting informative water management.

What are the drivers of sustainable energy transition? Insights from an empirical analysis of household preferences for electric induction cooking in Nepal

Electricity as a clean cooking fuel is economically and environmentally efficient compared to other cooking fuels, and induction stoves are among the most efficient that could contribute to the sustainable energy transition. Nepal is rich in water resources, having resources four times higher than the global average. With increasing hydroelectricity generation, promoting induction stoves for cooking is a viable way to reduce the use of traditional fuels and Liquified Petroleum Gas imported from other countries. This study aims to identify the underlying product-specific factors influencing households’ preference for electric cooking using induction stoves and assess the impact of awareness about the benefits of induction stoves on choice probability. We used a randomized conjoint experiment along with a randomized controlled trial collecting primary data of 9500 choice responses from 950 households in the Nuwakot district of central Nepal to achieve the objective. Among the six product-specific factors considered in the conjoint analysis, monthly expenses and supply of electricity were found to be significant determinants for choosing electric induction cooking, while cooking time, sickness rate, and environmental conditions also had a certain degree of influence, whereas the effect of installation cost was found to be statistically insignificant. The lower bound of households' willingness to pay for electric induction cooking was found to be as high as 4% of their monthly income. The information treatment increases the uptake rate of the induction package by 5% and willingness to pay by 9.58%. This indicates the role of awareness and behavior change in driving a sustainable energy transition, highlighting the need for policymakers to promote cleaner cooking technologies through the effective dissemination of information The results of this study will enable policymakers to make informed decisions to promote the use of induction stoves as the primary cooking fuel, thereby contributing to efforts toward climate change mitigation.

A novel denoising method of the hydro-turbine runner for fault signal based on WT-EEMD

Sediment wear is a significant cause of hydro-turbine failure. The wavelet threshold and ensemble empirical mode decomposition (WT-EEMD) method is proposed to denoising the acoustic vibration signals of hydro-turbine runners under normal and sand-laden water flow conditions. Ensemble empirical mode decomposition (EEMD) is performed on the acquired signals, and the decomposed high-frequency intrinsic mode function (IMF) is denoised using wavelet threshold. A nonlinear threshold function is constructed instead of the traditional threshold function in the wavelet threshold algorithm. The experimental results show that the WT-EEMD method is superior to the EMD, EEMD, and wavelet threshold. Moreover, it was found that when the sand-laden water flows through the hydro-turbine, it causes a change in the frequency spectrum. This study can provide a reference for the study of sand avoidance operation of hydro-turbines and provide a valuable supplement to the existing condition monitoring and fault diagnosis system of hydroelectric generators.