Search Results (31)

This work focuses on optimizing energy dispatch in a hydroelectric power plant (HPP) with a large number of generating units (GUs) and uncertainties caused by sediment accumulation in the water intakes. The study was realized at Jirau HPP, and integrates Markov Decision Processes (MDPs) and Particle Swarm Optimization (PSO) to minimize losses and enhance the performance of the plant’s GUs. Given the complexity of managing the huge number of units (50) and mitigating load losses from sediment accumulation, this approach enables real-time decision-making and optimizes energy dispatch. The methodology involves modeling the operational characteristics of the GUs, developing an objective function to minimize water consumption and maximize energy efficiency, and utilizing MDPs and PSO to find globally optimal solutions. Our results show that this methodology improves efficiency, reducing the turbinated flow by $0.9\%$ while increasing energy generation by $0.34\%$ and overall yield by $0.33\%$ compared to the HPP traditional method of dispatch over the analyzed period. This strategy could be adapted to varying operational conditions, and could provide a reliable framework for hydropower dispatch optimization. Full article

Micro-hydroelectric power plants play a fundamental role in microgrid systems and rural electrification projects based on non-conventional renewable energies, where the stability of the electricity supply and load variability are critical factors for efficient operation. This work focuses on analyzing the impact of electrical load variation on the performance of a 10 kW micro hydroelectric power plant equipped with a Pelton turbine coupled to an electric generator. The main objective is to characterize the behavior of the turbine–generator system under different operating conditions, evaluating the hydraulic performance of the turbine, the electrical performance of the generator, and the overall performance of the micro power plant. Key variables such as flow rate, pressure, shaft speed, mechanical torque, current, and electrical voltage are monitored, considering the effect of electrical consumption on each of them. The experimental methodology includes tests at different electrical loads connected to the generator, using the spear system, which allows the flow rate in the injector to be modulated. The results indicate that reducing the flow rate using the spear increases the torque on the shaft, as well as the electrical current and voltage, for the same energy demand. Likewise, it is observed that the electrical efficiency of the generator remains stable for shaft speeds above 400 rpm, while the overall efficiency of the turbine–generator improves by up to 25% at this same speed. However, a voltage drop of more than 8% is recorded when the electrical power consumption increases from 3 kW to 9 kW, which demonstrates the sensitivity of the system to load variations. This work provides a comprehensive view of the dynamic behavior of micro-hydraulic power plants under realistic operating conditions, proposing an experimental methodology that can be applied to the design, optimization, and control of small-scale hydroelectric systems. These results provide novel experimental evidence on how electrical load variations affect the global performance of P -based micro hydropower systems. Full article

This review explores the pressing need for decarbonization strategies in the off-grid Indigenous communities of Northern Quebec, particularly focusing on Nunavik, where reliance on diesel and fossil fuels for heating and electricity has led to disproportionately excessive greenhouse gas emissions. These emissions underscore the urgent need for sustainable energy alternatives. This study investigates the potential for improving building energy efficiency through advanced thermal insulation, airtight construction, and the elimination of thermal bridges. These measures have been tested in practice; for instance, a prototype house in Quaqtaq achieved over a 54% reduction in energy consumption compared to the standard model. Beyond efficiency improvements, this review assesses the feasibility of renewable energy sources such as wood pellets, solar photovoltaics, wind power, geothermal energy, and run-of-river hydropower in reducing fossil fuel dependence in these communities. For instance, the Innavik hydroelectric project in Inukjuak reduced diesel use by 80% and is expected to cut 700,000 t of CO₂ over 40 years. Solar energy, despite seasonal limitations, can complement other systems, particularly during sunnier months, while wind energy projects such as the Raglan Mine turbines save 4.4 million liters of diesel annually and prevent nearly 12,000 t of CO₂ emissions. Geothermal and run-of-river hydropower systems are identified as long-term and effective solutions. This review emphasizes the role of Indigenous knowledge in guiding the energy transition and ensuring that solutions are culturally appropriate for community needs. By identifying both technological and socio-economic barriers, this review offers a foundation for future research and policy development aimed at enabling a sustainable and equitable energy transition in off-grid Northern Quebec communities. Full article

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of water use, such as hydroelectric power generation and agriculture. Reduced flows in river basins, coupled with increased water consumption, can significantly affect energy generation and food production. Within this context, this paper presents an analysis of climate change impacts in a large basin of Brazil between the Amazon and Cerrado biomes, considering the effects of water demands. Inflow projections were generated for seven power plant reservoirs in the Tocantins–Araguaia river basin, using projections from five climate models. The results indicate significant reductions in flows, with decreases of more than 50% in the average flow. For minimum flows, there are indications of reductions of close to 85%. The demand for water, although growing, represents a smaller part of the effects, but should not be disregarded, since it impacts the dry periods of the rivers and can generate conflicts with energy production. Full article

The rising demand for both water and energy has intensified the urgency of addressing the water–energy nexus. Energy is required for water treatment and distribution, and energy production processes require water. The increasing demand for energy requires substantial amounts of water, primarily for cooling. The emergence of new persistent contaminants has necessitated the use of advanced, energy-intensive water treatment methods. Coupled with the energy demands of water distribution, this has significantly strained the already limited energy resources. Regrettably, no straightforward, universal model exists for estimating water usage and energy consumption in power and water treatment plants, respectively. Current approaches rely on data from direct surveys of plant operators, which are often unreliable and incomplete. This has significantly undermined the efficiency of the plants as these surveys often miss out on complex interactions, lack robust predictive power and fail to account for dynamic temporal changes. The study thus aims to evaluate the potential of mathematical modeling and simulation in the water–energy nexus. It formulates a mathematical framework and subsequent simulation in Java programming to estimate the water use in hydroelectric power and geothermal energy, the energy consumption of the advanced water treatment processes focusing on advanced oxidation processes and membrane separation processes and energy demands of water distribution. The importance of mathematical modeling and simulation in the water–energy nexus has been extensively discussed. The paper then addresses the challenges and prospects and provides a way forward. The findings of this study strongly demonstrate the effectiveness of mathematical modeling and simulation in navigating the complexities of the water–energy nexus. Full article

The optimal performance of a hydroelectric power plant depends on accurate monitoring and well-functioning sensors for data acquisition. This study proposes the use of artificial neural networks (ANNs) to estimate the Pelton turbine shaft power of a 10 kW micro-hydropower plant. In the event of a failure of the sensor measuring the torque and/or rotational speed of the Pelton turbine shaft, the synthetic turbine shaft power data generated by the ANN will allow the turbine output power to be determined. The experimental data were obtained by varying the operating conditions of the micro-hydropower plant, including the variation of the input power to the electric generator and the variation of the injector opening. These changes consequently affected the flow rate and the pressure head at the turbine inlet. The use of artificial neural networks (ANNs) was deemed appropriate due to their ability to model complex relationships between input and output variables. The ANN structure comprised five input variables, fifteen neurons in a hidden layer and an output variable estimating the Pelton turbine power. During the training phase, algorithms such as Levenberg–Marquardt (L–M), Scaled Conjugate Gradient (SCG) and Bayesian were employed. The results indicated an error of 0.39% with L–M and 7% with SCG, with the latter under high-flow and -energy consumption conditions. This study demonstrates the effectiveness of artificial neural networks (ANNs) trained with the Levenberg–Marquardt (L–M) algorithm in estimating turbine shaft power. This contributes to improved performance and decision making in the event of a torque sensor failure. Full article

Modern electrical power systems integrate renewable generation, with solar generation being one of the pioneers worldwide. In Latin America, the greatest potential and development of solar generation is found in Chile through the National Electric System. However, its energy matrix faces a crisis of drought and reduction of emissions that limits hydroelectric generation and involves the definitive withdrawal of coal generation. The dispatch of these plants is carried out by the system operator, who uses a simplified mechanism, called “economic merit list” and which does not reflect the real costs of the plants to the damage of the operating and marginal cost of the system. This inefficient dispatch scheme fails to optimize the availability of stored gas and its use over time. Therefore, a real-time redispatch model is proposed that minimizes the operation cost function of the power plants, integrating the variable generation cost as a polynomial function of the net specific fuel consumption, adding gas volume stock restrictions and water reservoirs. In addition, the redispatch model uses an innovative “maximum dispatch power” restriction, which depends on the demand associated with the automatic load disconnection scheme due to low frequency. Finally, by testing real simulation cases, the redispatch model manages to optimize the operation and dispatch costs of power plants, allowing the technical barriers of the market to be broken down with the aim of integrating ancillary services in the short term, using the power reserves in primary (PFC), secondary (SCF), and tertiary (TCF) frequency control. Full article

Climate change is expected to significantly affect countries in Southern Europe and the Mediterranean Basin, causing higher-than-average temperature increases, considerable reductions in rainfall and water runoff, and extreme events such as heatwaves. These pose severe threats to local energy systems, requiring a reliable and quantitative risk analysis. A methodological approach is thus proposed which covers both energy supply and demand, utilizing the latest climate projections under different greenhouse gas emissions scenarios and an appropriate scale for each energy form. For energy supply technologies, risks are assessed through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. To analyze climate risks for energy demand, bottom–up models were developed, integrating both behavioral and policy aspects which are often considered in a very limited way. The results show that climate change will mainly affect electricity generation from hydroelectric and thermal power plants, with variations depending on the plants’ locations and uncertainties associated with precipitation and runoff changes. The climate risks for solar and wind energy were found to be low. Energy consumption will also be affected, but the range of risks depends on the ambition and the effectiveness of measures for upgrading the thermal performance of buildings and the intensity of climate change. Full article

The penetration of renewable energies in island electricity systems (IESs) poses a series of challenges, which include, among others, grid stability, the response to demand, and the security of the supply. Based on the current characteristics of electricity demand on the islands of the Canary Archipelago (Spain) and their electricity production systems, this study presents a series of alternative scenarios to reduce greenhouse gas (GHG) emissions and increase the penetration of renewable energies. The goal is to optimize combustion-based (nonrenewable) energy production and combine it with renewable-based production that meets the requirements of dynamic response, safety, scaling, and integration with nonrenewable systems in terms of efficiency and power. As verified in the research background, the combination of power producing equipment that is generally employed on the islands is not the best combination to reduce pollution. The aim of this work is to find other possible combinations with better results. A methodology is developed and followed to obtain the lowest GHG production and to determine the measures to be applied based on: (a) changing the fuel type by switching to natural gas in the equipment that allows it; (b) using optimal combinations of the least polluting energy production equipment; (c) integrating, to the extent that it is possible, the Chira-Soria pumped hydroelectric energy storage plant into the Gran Canaria electricity system. A series of alternative scenarios are generated with different operating conditions which show the possibility of increasing the renewable installed capacity in the Canary Islands by up to 36.78% (70% in Gran Canaria), with a 65.13% reduction in GHG emissions and a 71.45% reduction in fuel consumption. The results of this study contribute, through the different measures determined through our research, to the mitigation of GHG emissions. Full article

Taiwan’s power system operates as an isolated grid, preventing the export of surplus energy. Excess electricity is either stored or discarded (curtailed). This study aims to estimate the energy storage requirement for the day with the most extreme electricity consumption behavior in a year without energy curtailment. Based on the installed capacity and actual power generation of renewable energy sources in 2022, this research estimates the power generation per GW of the installed capacity at full load. Integrating the government’s annual installation capacity plans, this study forecasts the annual power generation of renewable sources. Using the electrical load during the 2023 Spring Festival as a baseline and assuming an annual electricity consumption growth rate of 2%, combined with a minimum gas power output of approximately 6 GW, this study calculates the unused power generation, which represents the pumped-storage hydroelectricity and battery energy storage systems requirements for that day under a no-curtailment scenario. Considering the semi-annual adjustments in installation planning, this study’s code is open-sourced and designed to provide updated results with new planning data input, facilitating ongoing adjustments. Full article

Electric vehicles (EVs) offer a viable technological solution for mitigating greenhouse gas emissions in the transportation industry, addressing pressing societal concerns regarding climate change, air pollution, and sustainable energy consumption. To effectively promote widespread adoption of EVs, it is crucial to understand consumer preferences and evaluate market dynamics. In Nepal, where proven fossil fuel reserves are absent, the government is actively working towards accelerating EV adoption, leveraging the nation’s significant hydroelectric power generation potential to fulfill EVs’ charging demands. To gain insight into consumer preferences and evaluate market dynamics regarding EVs in Nepal, this study employs a comprehensive approach. Stated preference data are collected through a meticulously designed survey, and sophisticated analytical techniques, namely, the mixed logit model and latent class model, are applied for estimation purposes. The results of this study show that potential EV consumers with small family sizes, lower monthly travel distances, heightened environmental awareness, and substantial knowledge about electric vehicles are more inclined to embrace EV technology. Notably, the study highlights that a reduction in the purchase price exerts the most significant influence on increasing consumers’ likelihood of adopting battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Market simulation results suggest that a policy mix scenario, encompassing a combination of supportive measures, proves more effective in promoting EV adoption compared to relying on single policy initiatives. Furthermore, through latent class estimation, the study identifies three distinct classes of consumers within Nepal, each exhibiting significant variations in preferences. Recognizing and addressing these variations within policy frameworks is crucial for the successful promotion and widespread acceptance of EVs in Nepal. Full article

This paper focuses on designing and assessing Pumped Hydroelectric Energy Storage Systems (PHESs) connected to the grid and a PV system for self-consumption constructed at Mutah University in an area of high solar potential. By focusing on the PHES and PV literature, data in the field were acquired based on the grid code needed in Jordan. Next, a search to find a suitable location for installation was conducted. Afterwards, a load profile was added to calculate the energy demand of the university. Then the productivity of the solar power plant of Mutah University was included. Finally, MATLAB software was used to realize the amount of energy to be stored; these data were used to implement the system that was chosen and dimensioned. A PHES layout was created to find the most accurate values for parameters to optimize system performance and to investigate loss analysis. The main finding is that the system attains 9230.89 MWh/year. An annual load yields 4430 MWh/year, which covers the Mutah University demand with an estimated saving of USD 287,607,993. Full article

This scientific paper discusses the importance of reducing greenhouse gas emissions to mitigate the effects of climate change. The proposed strategy is to reach net-zero emissions by transitioning to electric systems powered by low-carbon sources such as wind, solar, hydroelectric power, and nuclear energy. However, the paper also highlights the challenges of this transition, including high costs and lack of infrastructure. The paper emphasizes the need for continued research and investment in renewable energy technology and infrastructure to overcome these challenges and achieve a sustainable energy system. Additionally, the use of nuclear energy raises concerns, such as nuclear waste and proliferation, and should be considered with its benefits and drawbacks. The study assesses the feasibility of nuclear energy development in Latvia, a country in Northern Europe, and finds that Latvia is a suitable location for nuclear power facilities due to potential energy independence, low-carbon energy production, reliability, and economic benefits. The study also discusses methods of calculating electricity generation and consumption, such as measuring MWh produced by power plants, and balancing supply and demand within the country. Furthermore, the study assesses the safety of nuclear reactors, generated waste, and options for nuclear waste recycling. The transition to a carbon-free energy system is ongoing and complex, requiring multiple strategies to accelerate the transition. While the paper proposes that nuclear energy could be a practical means of supporting and backing up electricity generated by renewables, it should be noted that there are still challenges to be addressed. Some of the results presented in the paper are still based on studies, and the post-treatment of waste needs to be further clarified. Full article

Pumping systems, especially those used in the water supply sector and in industrial and hydroelectric facilities, are commonly infested by the golden mussel. This causes an increase in maintenance operations (e.g., system shutdowns for cleaning) that can generate an increased energy cost. The geographical expansion of the golden mussel in Latin America presents an economic risk, not only to the ecosystem in general, but also to the energy sector. The imminence of its spread in the Amazon region, one of the main river basins in South America, is cause for concern with regard to the problems that bioinvasion of this species can cause. Given the absence of studies on the loss of energy efficiency in pumping systems impacted by the golden mussel, this study proposes a methodology to estimate the increase in energy consumption and costs of pumping under such bioinfestation. For the standardization of the methodology and development of mathematical calculations (both novel and improved equations), data from the literature (the growth of the golden mussel as a function of infestation time) and an analysis of the dimensions (length and height) of a sample of mussels available in the laboratory were considered. These data were used to calculate the roughness generated by the mussel infestation in the pumping suction and discharger pipe, which was necessary to determine the loss of energy efficiency (load loss, power consumption, and cost of pumping) resulting from the increase in energy consumption for pumping. This methodology was applied to a pumping station representative of the Brazilian Amazon as a case study. The results show an average increase in economic indicators (consumption and cost of pumping) after the system undergoes bioinfestation. This total increase corresponded to 19% and 44% in the first and second years, respectively, achieving a stabilization of the increase in the cost of pumping at 46%, in the 30 months of operation. Our results demonstrate the pioneering nature of the proposal, since these are the first quantitative data on the energy efficiency of pumping systems associated with bioinfestation by the golden mussel. These results can also be used to estimate the increase in costs caused by golden mussel bioinfestation in the raw water pumping systems of other facilities. Full article

As a major province for hydroelectric power in China, Sichuan Province has witnessed a great amount of seasonal characteristics in its hydroelectric power, endowing the clean energy industry in Sichuan with the characteristics of unstable supply in different seasons, strong power transmission capacity, and low production capacity of other non-fossil energy sources (except hydroelectric power). In this study, the mathematical model method was used to construct a structural optimization model of the clean energy industry in Sichuan Province, and to enable a quantitative analysis of the rationalization of the clean energy industrial structure in Sichuan Province. The results are proved from the cost-effectiveness of low carbon emission that hydroelectric power > wind power > photovoltaic power > natural gas > coal > oil. This study shall find the theoretical structure of the clean energy industry in Sichuan Province in 2030 with a prediction of Sichuan Province’s total future energy output and a constraint of its industrial structure model of clean energy. This paper suggests that Sichuan Province should give priority to the development of non-fossil energy sources, increase the development and utilization of power transmission channels in wet seasons, and develop clean energy and high energy consumption industries and the construction of pumped storage power stations, so as to reduce and avoid the waste of energy resources. It is also suggested that Sichuan Province should focus on developing clean energy with the capability of peak shaving, such as hydrogen energy and natural gas, while developing smart grid and long-distance transmission technology to strengthen energy conservation and emissions-reduced power generation. On this basis, Sichuan will focus on the development and utilization of natural gas as an alternative to high-carbon energy, with a view to optimizing its industrial structure of clean energy and helping China achieve the dual-carbon goals. Full article