Hydro Energy Research Articles

The Role Sampling Campaign: Opportunities for Utilizing Natural Landscapes to Fulfill Microhydro-Based Renewable Energy in Remote Area

Abstract West Java, as a province with a low electrification ratio, especially in remote areas, faces significant challenges. Recent data shows that around 77,626 households (34.91%) do not yet have access to electricity. Nonetheless, the southern region of West Java has great potential thanks to its diverse natural morphology. These landscape characteristics open up opportunities to utilize renewable energy sources, such as micro-hydro potential, to meet electricity needs. The objectives of this study include (1) Priority Election Needs of Area of Interest (AOI); (2) Sampling Campaign: Micro Hydro Opportunities in AOI. The research method used was survey research with a mixed approach. Data collection techniques include field data documentation; geospatial analysis and interviews. Data analysis was descriptive statistics. The results showed that (1) Garut Regency (3.76%) is a priority location with Singajaya sub-district (14.34%) and Sukamulya village (34.32%); (2) Sukamulya Village has potential micro hydro energy opportunities at Tiis waterfall at the foot of Mount Lumbung, the results of a rough assessment of this location can provide electrical energy to surrounding family groups. The implication of this research output can be a relevant reference for the local government to be followed up in the future action plan.

A holistic analysis of environmental impacts and improvement pathways for the Brazilian electric sector based on long-term planning and life cycle assessment

Brazil presents a high share of renewable electricity generation, mainly due to its favorable hydroelectric potential. However, reports estimate that demand will grow substantially in the long term, requiring a significant diversification of the electricity mix. In this context, this paper analyzes how the environmental impacts of electricity generation tend to change over the horizon 2025–2050 in Brazil and identifies improvement opportunities accounting for environmental and economic factors. To do so, the Open Source Energy Modeling System (OSeMOSYS) is applied to estimate the composition of the electricity mix in 2050. Then, life cycle assessment (LCA) is used to evaluate the associated environmental impacts across ten categories. Lastly, hybrid weighted ɛ-constraint multi-objective optimization (MOO) is employed to evaluate which sources can be used to minimize climate change and the levelized cost of electricity while ensuring that other categories are reasonably restrained. The results indicate that the environmental performance of the Brazilian electricity matrix tends to deteriorate substantially, both when analyzing overall impacts and impacts per kWh. Moreover, the proposed MOO approach suggests that some sources, mainly hydropower, onshore wind, and centralized PV present an all-around economic/environmental performance and might be favorable for expanding the power system.

Prioritization of investment order in Brazil among renewable energy sources: an analysis using the SWARA-MOORA-3NAG method

Purpose This paper aims to comprehensively analyze renewable energy alternatives in Brazil, focusing on identifying the most suitable option for investment in the country’s sustainable development. Design/methodology/approach The study adopts the step-wise weight assessment ratio analysis-multiobjective optimization by ratio analysis −3NAG (a combination of three normalization methods) methodology, a multicriteria decision-making approach, to evaluate and rank renewable energy sources based on key criteria such as resource availability, cost-effectiveness, job creation potential and environmental impact. Findings The analysis reveals that solar energy emerges as the preferred choice for Brazil, offering significant advantages over other alternatives such as hydroelectric, wind and biomass energy. Solar energy’s distributed generation capability, cost reduction trends and positive environmental impact contribute to its favorable position in meeting Brazil’s energy needs. Research limitations/implications While the study provides valuable insights into renewable energy selection, there are limitations regarding the criteria’ scope and the exclusion of specific renewable energy options. Future research could explore sensitivity analyses and incorporate additional criteria to enhance the study’s comprehensiveness. Originality/value This research contributes to the existing literature by thoroughly analyzing renewable energy alternatives in Brazil using a robust multicriteria decision-making methodology. The study’s findings provide actionable guidance for policymakers, businesses and stakeholders seeking to promote sustainable energy development in the country.

Addressing the limitation of Operational Flexibility in Power Generation with Pumped Hydro Energy Storage System – Indian Perspective

The global climate change scenario has impacted and taken corrective measures in shifting the sourcing of primary energy and efficient end-use pattern with more focus to utilise renewable energy resources to replace the depleting fossil fuels. Electric power generation capacity in the Indian subcontinent has gradually been improved to substantially contribute to intermittent and variable renewable power generation mix up to 40% of grid demand. However, the injection of grid-integrated renewable power as per the availability of generation potential will necessitate limiting the power generation from generating plants running on fossil fuel. But the operational flexibility of fossil fuel power plants is mostly designed to run efficiently with a 55% minimum technical load on the machines. In the above situation, stable grid availability and operation with a desirable spinning reserve may be taken care of suitably with an on-grid energy storage system, and in the Indian context, a pumped hydro energy storage system may play a critical role to take care of grid operational variability with adequate measures on frequency and voltage correction through periodic power generation and power draw. In this paper, the feasibility of a pumped hydro storage system from an Indian power sector perspective has been reviewed about the present national power scenario.

Study on the Evolutionary Process and Balancing Mechanism of Net Load in Renewable Energy Power Systems

With the rapid development of renewable energy sources such as wind and solar, the net load characteristics of power systems have undergone fundamental changes. This paper defines quantitative analysis indicators for net load characteristics and examines how these characteristics evolve as the proportion of wind and solar energy increases. By identifying inflection points in the system’s adjustment capabilities, we categorize power systems into low, medium, and high renewable energy penetration. We then establish adjustment models that incorporate traditional coal power, hydropower, natural gas generation, adjustable loads, system interconnections, pumped-storage hydroelectricity, and new energy storage technologies. A genetic algorithm is employed to optimize and balance the net load curves under varying renewable energy proportions, analyzing the mechanism behind net load balance. A case study, based on real operational data from 2023 for a provincial power grid in western China, which is rich in renewable resources, conducts a quantitative analysis of the system’s adjustment capability inflection point and net load balancing strategies. The results demonstrate that the proposed method effectively captures the evolution of the system’s net load and reveals the mechanisms of net load balancing under different renewable energy penetration levels.

Exploring the future hydropower production of a run-of-river type plant in the source region of the Tigris Basin (Türkiye) under CMIP6 scenarios

This assessment presents a framework for exploring the changing climate impacts on the energy production capacity of a run-of-river type plant, using the Basoren Weir and Hydropower Plant (HPP) as a case study. The Basoren Project is planned considering historical streamflow records in the source region of the Euphrates-Tigris River Basin (ETRB), which is a prominent hotspot warming at nearly double the global average rate. The quantification is built on precipitation and maximum/minimum temperature datasets from 24 Global Climate Models (GCMs) belonging to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under the moderate- and high-end Shared Socioeconomic Pathway (SSP) scenarios of SSP2-4.5 and SSP5-8.5, as well as the CMIP6 historical experiment (HEXP) scenario. The distribution mapping method is employed to adjust the raw GCM datasets for systematic biases. The Soil and Water Assessment Tool (SWAT) is preferred in producing daily runoff time series for the bias-adjusted simulations of each GCM over the historical (1988-2009) and three future (2025-2049, 2050-2074, and 2075-2099) periods. The ramifications of the changing climate on the Basoren HPP's energy production capacity are assessed based on the medians of the operational results reached for each GCM under the future societal development scenarios of SSP2-4.5 and SSP5-8.5, considering the medians achieved under the HEXP scenario as the reference case. The results indicate potential reductions in the mean yearly energy production of the Basoren HPP by 7.9%, 5.5%, and 5.3% under the SSP2-4.5 scenario, and by 5.8%, 8.0%, and 17.3% under the SSP5-8.5 scenario for the periods 2025-2049, 2050-2074, and 2075-2099, respectively. While declining spillway releases are expected to partly offset the impact of decreasing streamflow rates on energy production, the shift from a snow-dominated to a rain-dominated hydrologic regime necessitates re-optimizing the power capacities of the ETRB plants to maintain effective use of hydropower potential.

CRITIC-TOPSIS Method

The increasing demand for electricity has driven the development of hybrid renewable energy systems (HRES) in developing countries and remote areas. HRES combines various renewable energy sources to overcome the limitations of each source by utilizing their respective strengths. Although HRES has advantages such as flexibility and low pollution, the development of renewable energy needs to consider environmental impacts and principles of sustainable development. This study aims to find the optimal configuration of a hybrid renewable energy system in the new capital region of Indonesia, namely IKN Nusantara in East Kalimantan province. We conducted a geospatial approach and literature review to gather relevant information, such as solar radiation data, hydropower potential, and biomass potential. We utilized the hybrid optimization model for electric renewables (HOMER) software to design the HRES, and we optimized the results using the multi-criteria decision-making (MCDM) method. The experimental results show that the combination of PV and hydro is the optimal configuration in terms of energy and environmental aspects, with a relative closeness value of 0.675 compared to the ideal solution. Therefore, the implementation of MCDM to evaluate and determine the best configuration of HRES in the IKN Nusantara region is worth considering for further research and development.

Analysis of renewable energy resources based on frank power aggregation operators and EDAS method for circular bipolar complex fuzzy uncertainty

The model of circular bipolar complex fuzzy (Cir-BCF) sets computed based on the membership function, non-membership function, and radius among both functions for each value of the universal set. The technique of the Cir-BCF set is the modified or extended form of fuzzy sets, complex fuzzy sets, bipolar fuzzy sets, bipolar complex fuzzy sets, and simple circular bipolar fuzzy sets to cope with uncertain and vague information. In this manuscript, we describe the novel technique of frank operational laws based on Cir-BCF values for frank t-norm and frank t-conorm. Further, we simplify the model of Cir-BCF frank power averaging (Cir-BCFFPA), Cir-BCF frank power weighted averaging (Cir-BCFFPWA), Cir-BCF frank power geometric (Cir-BCFFPG), Cir-BCF frank power weighted geometric (Cir-BCFFPWG) operators, and highlighted their valuable properties, called idempotency, monotonicity, and boundedness. Moreover, analysis of renewable energy resources is very awkward and complicated, but it is natural sources of energy that are refilled constantly or relativeness quickly on a human timescale. Further, solar energy, hydroelectric energy, geothermal energy, biomass energy, and wind energy are five major sources of energy, but it is complex to find which one is the best and which one is worst. For evaluating the above problems, we construct the technique of evaluation based on the distance from the average solution (EDAS) method under the presence of the Cir-BCF numbers (Cir-BCFNs). At the end, we arrange the comparison between proposed and existing techniques based on some numerical examples to describe the validity and proficiency of the initiated information.

Mediating role of energy uncertainty for environmental management in electricity generation: The evidence from Pakistan

This groundbreaking study examines the relationship between CO2 intensity, aggregated and disaggregated fossil fuels, clean and nuclear energy, and, as a mediating variable, energy uncertainty for Pakistan during 2019M01 and 2022M10 with monthly data. To this end, the ARDL Bound Testing method is used to identify the long-run relationship of the studied factors. The empirical results suggest that under the mediating effect of energy uncertainty, renewables and nuclear energy in electricity generation have a negative association with CO2 intensity. In contrast, fossil fuels in generating electricity influence positively CO2 intensity in the aggregated analysis. Moreover, the disaggregated results under the mediating role of energy uncertainty reveal that only hydro energy reduces CO2 intensity as renewables, bioenergy, wind, and solar energy do not impact CO2 intensity. Both coal and gas energies cause a rise in CO2 intensity. Regarding nuclear energy, it also has a negative relation with CO2 intensity. The increase in energy uncertainty leads to a fall in CO2 intensity in aggregated and disaggregated analyses as well. Wavelet coherence analysis shows that CO2 intensity and energy uncertainty depend on each other dynamically for almost the whole employed period.

Experiences as heuristics for geothermal public perception: Testing the correlation between thermal waters recreation and geothermal energy perception

This research focuses on the question of how geothermal energy public perception is formed within a national context where news media do not pay attention to geothermal energy, and there is no active opposition to geothermal energy. The research builds on theoretical underpinnings of heuristics in energy perceptions and highlights the importance of physical experiences and associations as sources of experiential learning. Through a survey conducted among members of the general public in Slovenia, the role of thermal water recreation in shaping public perception of geothermal energy is empirically tested. The results show that, in this context, geothermal energy is highly positively assessed compared to hydro energy and nuclear energy, and that there is a correlation between frequency of thermal recreation and certain aspects of public perception of geothermal energy. The policy implications go beyond the simple recommendation of including tourism in public awareness campaigns but point to the specific vulnerability of energy acceptance in this context, where perceptions are formed based on “thinking fast”, and where the media and the public discourse on geothermal energy have not (yet) considered the potential risks and opposition to geothermal projects.

An assessment of run of river hydropower potential in Great Britain

In the UK, hydropower produces 1.65 GW of energy, only 2% of the national capacity. With most large-scale storage-based hydropower potential sites already utilised in the UK, further development is minimal due to financial, environmental and construction time concerns. However, run of river (RoR) is a type of hydropower that has the potential for further development. While there are studies that estimate different ranges of RoR hydropower potential, the last UK-wide study was undertaken in 1989, meaning it is outdated. In this study, a methodological framework was created to assess the potential of RoR hydropower in Great Britain (GB) (Northern Ireland was omitted from this study due to a lack of river flow data). The hydrological, technical, financial and realisable potentials for pico, micro, mini and small RoR hydropower were determined. The results show that the total hydrological potential is 20 GW, the technical potential is 11 GW, the financially viable potential is 320–420 MW and the realisable potential is 290–320 MW. Most realisable schemes are either mini or small, situated in the west and north-west parts of GB. This study adds to the understanding of the RoR potential in GB and offers a reliable estimate of RoR hydropower that can be produced alongside suitable RoR scheme locations.

Estimating the Wind Power by Using K-Nearest Neighbors (KNN) and Python

In recent years the production and distribution of renewable energy has become a popular trend in power generation, and renewable energy sources such as hydro, solar, and wind energy are examples of natural and clean energy sources. Among the renewable energy sources, wind energy source is one of the trending and crucial energy sources that has outstanding electricity power generation. This research investigates an estimation model of wind power to address the real-life issues in renewable energy power generation by estimating an accurate amount of wind power production by applying the machine learning (ML) K-Nearest Neighbors (KNN) technique integrated with Python programming. To achieve the expected outcome for this research, it is expected to collect data from wind energy, wind speed forecasts, and all the relevant information that supports the research in analyzing the technique. There are various meteorological methods to evaluate the performance of wind power generation, but in this research, the methodology is to employ machine learning techniques such as KNN integrated with Python coding to achieve estimated wind energy output. Python is a software program and is diversely used for coding various algorithmic formulas to obtain results. In this research, Python is best suited for investigating the performance of the KNN technique for estimating the most accurate result for wind power generation. Here, the report presents the methods of applying the KNN technique and displaying the outcome on screen by a graph representation. The outcome of the research showed that the KNN is a more reliable technique to make an accurate prediction on wind power generation. A similar approach can be implemented in various renewable energy data to estimate an accurate energy output.

Impacts of Renewable Energy Transitions on the Economic Growth in Malaysia: A Dynamic ARDL Simulations

This study explores the dynamic relationships between renewable energy transitions and economic growth in Malaysia, with a specific focus on hydroelectric power, using the Dynamic Autoregressive Distributed Lag (D-ARDL) simulations. The research leverages extensive time-series data from 1988 to 2022 to analyze the impacts of hydroelectric and non-renewable energy consumption on the nation's economic trajectory. Our findings indicate a positive long-term relationship between hydroelectric power usage and GDP growth, highlighting renewable energy's pivotal role in sustainable economic development. Additionally, the study examines the short-term adjustments and the effectiveness of hydroelectric power in reducing dependence on non-renewable energy sources, which are crucial for achieving Malaysia's Nationally Determined Contributions (NDC) for 2030. The dynamic ARDL simulations provide nuanced insights into the potential future impacts of increased hydroelectric power usage, underscoring its dual benefits for economic growth and environmental sustainability. This research contributes to the understanding of energy transitions within the context of Malaysia's unique economic and environmental landscape, offering implications for policy and investment in renewable energy infrastructure.

Assessing the Sustainability of Small Hydropower Potential in the Threats of Natural Disasters: an Analytic Hierarchy Process-Based Approach

Assessing the Sustainability of Small Hydropower Potential in the Threats of Natural Disasters: an Analytic Hierarchy Process-Based Approach

Seismic Vulnerability Assessment of Non-Overflow Concrete Gravity Dam Section

Abstract As the economy advances, there is a growing need for energy. Harnessing hydroelectric energy has emerged as a crucial strategy for addressing the energy crisis. To promote hydropower development, numerous tall concrete dams are either under construction or in the planning stages. These dams are frequently situated in areas with elevated water levels and face the challenge of being located in regions with high seismic intensity. An accident resulting from the failure of concrete dams can pose significant threats to both economic development and public safety. Therefore, it is of crucial importance to investigate the stability of such dams, particularly under conditions of high water levels and seismic activity. The finite element program Geostudio is being undertaken to evaluate a complete numerical analysis of the dam. In this paper, Longtan Dam has been selected as the case study for the research. This study is applied in two cases: seismic and static conditions. A two-dimensional seismic numerical analysis was carried out using the Koyna earthquake acceleration time records in 1976. The results of the FEM model concluded that the dam is unsafe under sesmic conditions. The concrete-rock interface, particularly susceptible to sliding, was identified as the most critical part of the dam, presenting the most likely failure mode. The study highlights the significance of its methodology in investigating earthquake effects on dams, prioritizing it over the achieved results. The aim is for the conclusions and recommendations to provide valuable guidance for future studies and initiatives focused on enhancing safety at hydropower dams.

Hydro-Political Dynamics Between China–India–Pakistan: Dams and Transboundary River Governance Amidst Geopolitical Contestations

Transboundary rivers raise critical concerns for state security amidst contemporary ecological strain and regional geopolitics in South Asia. The challenge of ‘water security’ is underscored by the substantial reliance on transboundary rivers, compounded by the multifaceted impacts of climate change and the simmering geopolitical tensions among riparian nations, especially in the complex dynamics between India–China and India–Pakistan. This study endeavours to illuminate distinctive characteristics of the South Asian transboundary governance framework, wherein rivers are subjected to intensive damming aimed at (a) harnessing hydroelectric potential and (b) leveraging water resources as geopolitical bargaining chips, thereby exerting pressure; however, order is not specified, particularly. In this intricate milieu, international conventions often fail to reconcile internal contradictions inherent within the transboundary governance paradigm. Consequently, transboundary water resources have metamorphosed into an extension of geopolitical realities, embodying intricate interplay between hydrology, geopolitics and state security within the region, especially between China, India and Pakistan.

Assessing the impact of water scarcity on thermoelectric and hydroelectric potential and electricity price under climate change: Implications for future energy management

This study investigates the impact of water resource restrictions on thermoelectric and hydroelectric stations, analyzing its influence on demand and electricity prices. It uses General Circulation Models (GCMs) and Soil and Water Assessment Tools (SWAT) to forecast future temperature trends and estimate river flow patterns. The research provides insights into climate change's potential effects on water resources and electricity potential. The study shows a significant decrease in river flow, indicating potential issues with hydroelectric and thermoelectric systems. The study also uses an optimized Echo State Network (ESN) for accurate electricity demand, using the Modified Snow Leopard Optimization (MSLO) algorithm as a new metaheuristic model. The simulation results show a consistent increase in electricity demand scenarios, which is expected to lead to higher supply prices due to decreased production capacity. This could have significant economic effects. The investigation provides a comprehensive understanding of water resource management challenges in power production, aiding in informed decisions in the future energy industry.

Innovative Energy Sustainable Solutions for Urban Infrastructure: Implementing Micro-Pumped Hydro Storage in Singapore’s Multi-Level Carparks

As part of the initiative to achieve Singapore’s Green Plan 2030, we propose to investigate the potential of utilizing micro-pumped hydroelectric energy storage (PHES) systems in multi-level carparks (MLCP: a stacked car park that has multiple levels, may be enclosed, and can be an independent building) as a more environmentally friendly alternative to traditional battery storage for a surplus of solar energy. This study focuses on an MLCP with a surface area of 3311 m2 and a height of 12 m, considering design constraints such as a floor load capacity of 5 kN/m2 and the requirement for a consistent energy discharge over a 12 h period. The research identifies a Turgo turbine as the optimal choice, providing a power output of 2.9 kW at a flow rate of 0.03 m3/s with an efficiency of 85%. This system, capable of storing 1655.5 m3 of water, can supply power to 289 light bulbs (each consuming 10 W) for 15.3 h, thus having the capacity to support up to three MLCPs. These results underscore the environmental advantages of PHES over conventional batteries, highlighting its potential for integration with solar panels to decrease carbon emissions. This approach not only aligns with Singapore’s green initiatives but also promotes the development of a more sustainable energy infrastructure.

The Advancement of Artificial Intelligence's Application in Hybrid Solar and Wind Power Plant Optimization: A Study of the Literature

The harnessing of solar, wind, and hydroelectric energy sources has rendered them easily accessible renewable resources, owing to their abundant availability. There is a growing body of research evincing interest in the deployment of hybrid renewable energy systems. Over recent decades, adopting hybrid technologies has engendered a positive trend, marked by broader considerations of configurations and applications within these systems. This study analytically examines the potential of hybrid solar and wind energy harvesting devices. As such, the project aims to extensively evaluate relevant literature and statistical analysis of data extracted from journal papers published between 2004 and 2023. A specific objective is to develop a complete database matrix surrounding multiple categories, including component configurations, methodological approaches, and supporting software infrastructures. Moreover, an assessment of the socio-economic, environmental, and ecological impacts of these systems is undertaken to ascertain their salience. Furthermore, this inquiry delves into the optimization strategies of these systems leveraging artificial intelligence methodologies. Critical lacunae identified during this review pertain to more emphasis on optimization metrics for PV-wind hybrid energy systems, impeding a holistic understanding of their implications on energy, economics, environment, and society. Our findings underscore prevalent methodologies such as computational modelling utilizing software suites like MATLAB/Simulink, HOMER, and others to derive empirical data. Additionally, parametric analyses emerge as the predominant approach, characterized by the application of algorithms such as Particle Swarm Optimization (PSO), Fuzzy Logic Control (FLC), and Genetic Algorithms (GA), among others. PV-wind hybrid energy systems are classified into autonomous and grid-interconnected configurations, with primary components comprising PV-wind generators. The anticipated trajectory suggests a burgeoning development of these hybrid energy harvesting systems, underpinned by their potential as clean, sustainable, and eco-friendly energy sources.

Exploring climate-change impacts on streamflow and hydropower potential: insights from CMIP6 multi-GCM analysis

ABSTRACT The generation of hydropower is profoundly influenced by shifts in streamflow patterns induced by climate change. This research examines changes in streamflow and the potential surge in hydropower generation over a span of 35 years (2015–2050) at the Bhakra Dam site within the Upper Sutlej River basin. Employing a deep learning methodology, particularly the long short-term memory (LSTM) model, in conjunction with Coupled Model Intercomparison Project (CMIP) 6 multi-global climate model (GCM), facilitates a thorough analysis of these dynamics. Six out of 14 bias-corrected statistically downscaled datasets (0.25° × 0.25° grid resolution) from CMIP6 multi-GCM were selected based on entropy and combined compromise solution techniques. This innovative approach is utilized to assess streamflows and project potential increases in hydropower at the Bhakra Dam site under shared socioeconomic pathways (SSP) scenarios, specifically SSP245 and SSP585. The results indicate a maximum increase of approximately 15% and 17% in mean monthly streamflow under SSP245 and SSP585, respectively. Moreover, dependability flows calculated at Q50, Q75, and Q90 show respective rises of 13%, 16%, and 17% under SSP245 and 21%, 17%, and 18% under SSP585. The projected hydropower potential exhibits an increase of up to 15.9% and 17.3% under SSP245 and SSP585, respectively.