: There has been an ever-increasing demand for energy from the past decades. Renewable energy technologies play a major role in satisfying the energy demand as well as in a decreased CO2 emissions. Solar and Wind energies are the major upcoming technologies in renewable energies. Decentralized power production is a system where the energy production and consumption are very close to each other. Microgrids can be decentralized or grid connected and they, with renewable energy sources, encounter a problem of storage as the power production from solar and wind is intermittent. This paper discusses the comparison between using batteries and pumped storage hydropower (PSH) as an energy storage system and the integration of wind and solar PV energy sources. HOMER software simulations are used to obtain optimized renewable energy integration in microgrid and to understand its economic analysis. Two scenarios are run with the model where one considers battery and the other considers PSH to obtain the economic and technical best results of these microgrids. The economic analysis showed a lower net present cost (NPC) and levelized cost of energy (LCOE) for the microgrid with PSH. The results show that microgrid with storage of PSH is economical with an NPC of 45.8 M€ and an LCOE of 0.379 €/kWh in comparison with batteries solution which has an NPC of 95.2M€ and an LCOE of 0.786 €/kWh. The role of storage is understood by differentiating the data into different seasons using Python for data analysis. Furthermore, sensitivity analysis is made by varying the capital cost multiplier of Solar PV and Wind Turbine to obtain optimal solutions.
Analysis of extreme events of annual flow peaks are used for sizing hydraulic structures for specified return period. Cumulative distribution functions are applied to annual flow peak records in order to obtain extreme values with different return periods. In Colombia, when performing a frequency analysis, hydrological planners often do not know a priori the best cumulative distribution function for making analysis. In the present research, annual flow peak records from 49 hydrometric stations located in important rivers were collected, with the objective of determining the most representative cumulative distribution function. The best results were achieved using the generalized extreme value (GEV) cumulative distribution function with the maximum likelihood method.
Emptying processes are typical maneuvers that should be performed by water distribution companies for operation purposes. These processes involve a complex numerical analysis, since a set of algebraic and ordinary differential equations needs to be solved for the intricacy of hydraulic and thermodynamic formulations for two analyzed phases (liquid and gas). This research provides an implicit equation to compute exactly the final conditions in water emptying operations in single pipelines without an air valve (or admitted air). The implicit expression was developed by considering that for all final conditions, the water velocity is null, and thus, the water column length and air pocket pressure can be computed. The friction factor, internal pipe diameter, and opening maneuvers of drain valves do not disturb the final conditions in draining processes. The developed implicit formulation was validated using experimental measurements in a pipeline with a total length of 4.36 m. The equation is of utmost importance, since it can be utilized for engineers to easily plan for future conditions in water distribution networks.
Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations.
Water utilities frequently perform pipeline-emptying operations for maintenance, repair, and operational management. This process involves transient flow conditions with entrapped air. It must be carefully controlled, as the expansion of air pockets can generate sub-atmospheric pressures that may lead to pipeline collapse. The mathematical modelling of emptying processes with air valves has been extensively studied in recent years; however, such approaches typically rely on complex algebraic–differential equation systems. This study advances understanding of this phenomenon by proposing a novel procedure that uses a machine learning model to approximate system behaviour while avoiding fully coupled hydraulic formulations. An experimental facility consisting of a pipeline with an internal diameter of 0.042 m and a total length of 4.6 m was used, in conjunction with a complete regulation valve manoeuvre. The system was first calibrated using experimental data and subsequently employed in Monte Carlo simulations to generate a dataset for training the machine learning model. The results demonstrate that a Rational Quadratic Gaussian Process Regression model can accurately predict the minimum sub-atmospheric pressure, achieving a coefficient of determination greater than 0.999 during validation and testing. The proposed framework is presented as a proof-of-concept and has been validated only for the specific case study analysed. While the results highlight its potential to support planning for emptying operations under varying air-admission conditions and air-pocket sizes, further validation is required before generalising to real-world water distribution systems. For practical implementation, the model must be appropriately trained for each specific installation.
In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values.
Emptying pipelines can be critical in many water distribution networks because subatmospheric pressure troughs could cause considerable damage to the system due to the expansion of entrapped air. Researchers have given relatively little attention to emptying processes compared to filling processes. The intricacy of computations of this phenomenon makes it difficult to predict the behaviour during emptying, and there are only a few reliable models in the literature. In this work, a computational model for simulating the transient phenomena in single pipes is proposed, and was validated using experimental results. The proposed model is based on a rigid column to analyse water movement, the air–water interface, and air pocket equations. Two practical cases were used to validate the model: (1) a single pipe with the upstream end closed, and (2) a single pipe with an air valve installed on the upstream end. The results show how the model accurately predicts the experimental data, including the pressure oscillation patterns and subatmospheric pressure troughs.
<p class="Resumen">El proceso de vaciado en conducciones de agua genera depresiones por la expansión del aire en el interior de las tuberías y esto podría causar el colapso del sistema dependiendo de las condiciones de instalación y de la rigidez de la conducción. En este artículo se presenta el análisis de sensibilidad del modelo matemático desarrollado por los autores, analizando los principales parámetros hidráulicos y termodinámicos que intervienen en este proceso tales como: diámetro interior de la tubería, factor de fricción, pendiente longitudinal de la tubería, coeficiente politrópico, diámetro de la ventosa, tamaño de la bolsa de aire y tiempo de apertura. Este análisis se realizó para dos casos posibles: Caso No. 1, tubería con el extremo aguas arriba cerrado; y Caso No. 2, tubería con una ventosa instalada en el extremo aguas arriba. Los resultados muestran que para el Caso No. 1 los parámetros que más inciden en las depresiones son la pendiente longitudinal de la tubería, el coeficiente politrópico y el tamaño de la bolsa de aire; mientras que para el Caso No. 2, la mayoría de los parámetros influyen significativamente durante el proceso de vaciado.</p>
Public drinking water service providers must comprehensively understand and effectively characterise user demands, especially during peak hours, which not only impact the maximum demand within the distribution network but also determine the dimensions of interior networks within buildings. Residential consumers show different consumption patterns based on socioeconomic factors, spatial location, climatic conditions and the consistency and quality of service delivered by public service providers. This study focused on assessing 1,317,584 users distributed across four distinct service areas in Bogotá, Colombia. To achieve this, a stratified random sampling of 1233 residential subscribers was conducted and 320 reference digital Y290 Aquabus micro-meters were installed to characterise the four service areas. The installations were grouped into sets of 320 users until the entire sample of 1233 subscribers was encompassed. The results demonstrated that the rational method provided the most accurate fit for estimating the probable maximum flow rates compared to the values measured and, consequently, is the most suitable method for application within the region of interest. However, whereas the Hunter Unal method displayed a reasonable fit, it tended to underestimate the size of internal networks within buildings. The remaining methods, such as the British, square root, simultaneity, Hunter, NTC 1500 Hunter and Chilean methods, did not yield significant adjustments and tended to overestimate the probable maximum flow rates as well as the internal networks within buildings. The results indicate that, depending on the method used to calculate the probable maximum flow or design flow of the internal network, there can be a deviation factor when compared to the actual peak flow measured (real maximum flow). This deviation factor ranges from 0.79 (calculated less than measured) to 3.77 (calculated greater than measured). Additionally, a sizing case study was conducted, which involved applying all methods to a scenario involving a residential user. This study aimed to determine the variation expected in the estimation of the diameter of the supply pipe to the internal network when using the flow results from different methods. This analysis serves to conclude the research.
A key element for water supply systems is the design of the water intake components. Mobile floating platforms (barges) are helpful when the hydraulic system displays substantial variations in water levels. This study presents the hydrological considerations that should be considered for the design of the barge's pipeline runway. The analysis takes into consideration the maximum and minimum water levels measured at the location. The study was carried out at the Magdalena River -Plato (Colombia) station, finding variations in water levels of between 12.3 m and 16.1 m for return periods of 25 and 100 years, respectively. This information is helpful for designers and consultants in order to design an appropriate barge pipeline runway.
An entrapped air pocket can induce pressure surges in sewer systems. Previous studies on entrapped air in these systems have focused on analysing its effects under conditions where air is expelled. This research introduces a mathematical model to calculate pressure surges caused by air pocket compression in a sealed manhole (without an orifice size) that may occur at the output of a pumping station. The model is based on the rigid water column theory, the polytropic law, and the continuity equation. The proposed model is validated using a 7.3 m long experimental facility equipped with a sealed chamber simulating a sealed manhole cover. It is demonstrated to accurately predict the peak pressure head of 18.9 metres and the associated pressure oscillations. A sensitivity analysis is also performed to assess variations in model behaviour. Furthermore, the model effectively captures the system’s final conditions. Lastly, a case study illustrates the model’s applicability to a water installation with a length of 250 m.
The increasing decentralization of energy systems calls for robust frameworks to evaluate the technical and economic feasibility of hybrid renewable configurations at the community scale. This study presents an integrated methodology that combines Key Performance Indicators (KPIs), sensitivity analysis, and Multi-Criteria Decision-Making to assess hybrid systems in Castanheira de Pera, a small community in central Portugal. Fourteen configurations (C1–C14) integrating hydropower, solar PV, wind, and battery storage were simulated using HOMER Pro 3.16.2, PVsyst 8.0.16, Python 3.14.0, and Excel under both wet and dry hydrological conditions. A gate-controlled hydro-buffering model was applied to optimize short-term storage operation, increasing summer energy generation by 52–88% without additional infrastructure. Among all configurations, C8 achieved the highest Net Present Value (≈EUR 153,700) and a strong Internal Rate of Return (IRR), while maintaining a stable Levelized Cost of Electricity (LCOE) of around 0.042 EUR/kWh. Comparative decision scenarios highlight distinct stakeholder priorities: storage-intensive systems (C14, C11) maximize energy security, whereas medium-scale hybrids (C8, C7) offer superior economic performance. Overall, the results confirm that hybridization significantly improves community energy autonomy and resilience. Future work should extend this framework to include environmental and social indicators, enabling a more comprehensive techno-socio-economic assessment of hybrid renewable systems.
The prediction of the pressure inside the air pocket in water pipelines has been the topic for a lot of research works. Several aspects in this field have been discussed, such as the filling and the emptying procedures. The emptying process can affect the safety and the efficiency of water systems. Current research presents an analysis of the emptying process using experimental and computational results. The phenomenon is simulated using the two-dimensional computational fluid dynamics (2D CFD) and the one-dimensional mathematical (1D) models. A backflow air analysis is also provided based on CFD simulations. The developed models show good ability in the prediction of the sub-atmospheric pressure and the flow velocity in the system. In most of the cases, the 1D and 2D CFD models show similar performance in the prediction of the pressure and the velocity results. The backflow air development can be accurately explained using the CFD model.
This research aims to evaluate and put into practise the design of a small hydropower plant on a stream at São Vicente, in Madeira Island, supported by internet of things (IoT). The photogrammetry technique is also used with a comprehensive digital transformation, in which new concepts, methods and models, such as machine learning (ML), and big data analytics play an important role due to the huge availability time series that have to be exploited in hydropower design studies. Nowadays, digitalization and massive data availability are imposing new ways to address many of the current challenges associated with the energy and digital transition. This research is based on a simple small hydropower design, to present an integrated methodology using new methods assigned by an internet protocol system, which includes the development of different steps and components supported by GIS, photogrammetry and the use of advanced tools, with the support of a drone survey with internet communication (IoT) that allow the generation of experimentally-based estimates in situ characterization, the volumetric flow, the hydrological data treatment, the hydraulic calculations and economic estimations for a real hydro project. Therefore, hydrological variables, hydraulic analysis and topographical survey are carried out in the IoT application platform supported by new tools and methods to optimise the size of hydraulic structures, estimate the performance and potential of the hydropower plant towards the best solution for energy and digital transition. Firstly, the data-base for the all study and posterior sizing of the case study of hydropower plant are defined and then the corresponding analyses and results are presented. Then, the cost estimation for the construction, maintenance and operation of the selected elements that compose the hydropower topology are determined, as well as the respective economic balance, considering the annual energy production. In addition, both economic and environmental return on investment is discussed. Finally, an analysis to equate the cost estimates and the respective benefits of hydropower generation using this new approach applicability is stablished, taking into account some economic indicators to determine the profitability of the project.
No abstract is provided for this article.
The calculation of peak discharge in non-instrumented basins requires including morphometric parameters, which in turn depend on the map type used. This study analyses the impact of and variation in peak discharges of the Caño Ricaurte basin, Colombia, based on three types of maps at different resolution scales. The reference map used was the map made for the detailed designs of the channel analysed, which was extracted from the Master Plan of the City. Additionally, maps from a 90 × 90 m digital elevation model and contour lines extracted from Google Earth were used. The time of concentration was determined by different equations (Kirpich, Témez, Bureau, and TR-55) using the mapping methods described above, and the peak discharge was determined using rainfall-runoff models.
