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URI permanente para esta colecciónhttps://hdl.handle.net/10953/230

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Integrating organic Rankine cycles for waste heat recovery from onboard diesel generators in the maritime sector: Simulation and techno-economic assessment
(ELSEVIER, 2025-05-21) Sánchez-Lozano, Daniel; Aguado-Molina, Roque; Escámez, Antonio; Hernández-Torres, José Antonio; Pérez-Torreglosa, Juan; Vera, David
The maritime sector's dependence on fossil fuels, coupled with the rising crude oil prices, underscores the urgent need to enhance ship efficiency and advance the decarbonization of the marine sector. This paper evaluates the technical and economic feasibility of integrating organic Rankine cycle (ORC) systems in diesel-electric propulsion marine distribution vessels. A comprehensive simulation and optimization of a 1.6 MW ORC unit, using acetone as the working fluid, has been conducted. The system is designed to recover waste heat from the exhaust gases of diesel generators aboard a vessel. Under an 85% load of the diesel generators, the ORC bottoming unit demonstrates a net electrical efficiency of 8.45% with a thermodynamic cycle efficiency of 18.73%. It is estimated that this system could reduce annual carbon dioxide emissions and diesel fuel consumption by 18.5% compared to conventional systems. From a financial perspective, assuming a conservative discount rate of 8%, the ORC system demonstrates long-term viability with a cumulative profit of 44% on the initial investment, a payback period of 11.7 years, and an internal rate of return of 12.8%. Additionally, the advantages of integrating the ORC technology with direct current distribution networks are highlighted, simplifying system architecture and improving energy efficiency.
Low-cost real-time monitoring and automated control system for a bench-scale portable downdraft gasifier
(ELSEVIER, 2025-06-09) Rodríguez-Orta, Antonio; Sánchez-Raya, Manuel; Aguado-Molina, Roque; Gómez-Galán, Juan Antonio; Vera, David; López-García, Diego
This research work focuses on the development of a real-time monitoring and automated control system with remote access, as well as integrated data collection and storage, for a portable biomass gasification prototype to generate electricity from agricultural waste. The prototype consists of an air-blown downdraft fixed-bed gasifier and a producer gas conditioning unit, which operate together in a remotely controlled ensemble. The proposed system stands out for its compact size, transportability, and low-cost design, making it suitable for implementation in small agricultural facilities, especially in areas where conventional electrification is limited or non-existent. Two preliminary tests were conducted to evaluate the performance of the monitoring system. In the first test, the system achieved a target temperature of 600 °C in less than 20 minutes and maintained it within a variation range of ±25 °C. After holding this temperature for an hour, the setpoint was raised to 800 °C, with the system achieving the new target in less than 10 minutes. In the second test, a setpoint of 800 °C was reached in 16 minutes, with an additional 3 minutes required for stabilization. Both tests, lasting approximately 4 hours each, consumed a total of 13.43 kg of biomass. The results demonstrate the system's ability to reach target temperatures in less than 25 minutes while maintaining stable temperature oscillations. The system's graphical interface enables intuitive, real-time, and remote monitoring and management of temperatures in several zones along the gasifier's height. Additionally, the interface allows manual or algorithmic control of the system's actuators, with the ability to modify the control algorithms through over-the-air updates.
A comparative sustainability assessment of several grid energy storage technologies
(ELSEVIER, 2025-06-13) Aguado-Molina, Roque; Cartelle-Barros, Juan José; de-la-Cruz-López, María Pilar; Lara-Coira, Manuel; del-Caño-Gochi, Alfredo
The global energy transition toward a low-carbon economy is driving increasing penetration of variable energy sources into electricity markets. This unprecedented deployment of intermittent renewables confronts decision-makers in the electricity sector with the challenge of selecting among different energy storage technologies, a choice that must be made on the basis of sustainability criteria. Existing studies present shortcomings, including the absence of the social dimension, the use of weights against sustainable development, or the application of methodologies affected by the rank reversal issue, among others. To address gaps in current knowledge, this study presents a novel probabilistic model for assessing the global sustainability of grid energy storage technologies. The model is based on the MIVES (Modelo Integrado de Valor para una Evaluación Sostenible)–Monte Carlo method, which combines requirement trees, value functions, the analytic hierarchy process, and probabilistic simulations. It consists of 19 indicators and makes it possible to obtain a sustainability index (SI), as well as partial economic, social, environmental, and technical indices for each technology. Data from an extensive literature review were integrated with expert input and estimations based on linear correlations to address challenges in assessing social and environmental indicators. The model was applied to six technologies: pumped hydroelectric energy storage (PHES), compressed air energy storage (CAES), liquid air energy storage (LAES), vanadium redox flow batteries (VRFB), sodium-sulfur batteries (NaSB), and hydrogen energy storage (HES). A comprehensive sensitivity analysis is also included. To the best of the authors’ knowledge, no existing study has utilized the innovative methodology presented in this paper, nor has any related research achieved the scope and depth proposed here. The top-performing technologies identified for the economic, social, environmental, and technical dimensions of sustainability are CAES, VRFB, LAES, and PHES, respectively. In terms of global sustainability, VRFB, LAES and PHES are the best options, while HES consistently ranks last. NaSB and CAES occupy intermediate positions.
An ensemble multi-ANN approach for virtual oxygen sensing and air leakage prediction in biomass gasification plants
(ELSEVIER, 2025-01-16) Escámez, Antonio; Aguado-Molina, Roque; Sánchez-Lozano, Daniel; Jurado-Melguizo, Francisco; Vera, David
A recurring challenge in the operation of biomass gasification plants is the occurrence of air leaks, which prevent the resulting lean producer gas from meeting the required standards for power generation. In order to address this issue, an ensemble model composed of multiple artificial neural networks (ANNs) was developed to predict the oxygen concentration in the gas mixture and detect anomalous operating conditions (air leakage). Throughout an extensive experimental campaign, the volumetric composition of the gas mixture from a semi-industrial scale downdraft gasifier fueled with biomass pellets was systematically measured and recorded at a constant time step of 10 s using an inline portable syngas analyzer equipped with NDIR, TCD and ECD sensors. The ensemble multi-ANN model was trained with a total of 24 representative datasets, including instances of both normal and anomalous operating conditions, using k-fold cross validation with 10 submodels. The results revealed an R² of 0.99 and an RMSE below 0.3, indicating that the model’s error margin is lower than that of the ECD sensor. The developed model can serve as a supervisor for the ECD sensor by performing a double verification or even potentially replacing the ECD sensor, with the model assuming the task of predicting the oxygen concentration using the data recorded by the NDIR sensor.
Sustainability of gasification-based cogeneration with agri-food residues and heat recovery technologies: Techno-economic and life cycle analyses
(ELSEVIER, 2025-04-11) Anvari, Simin; Aguado-Molina, Roque; Vera, David; Jurado-Melguizo, Francisco; Rosen, Marc A.
The valorization of agri-food waste through biomass gasification integrated with heat recovery technologies is a promising option for sustainable renewable energy. Comprehensive evaluation of such energy systems requires both life cycle assessments (LCAs) and techno-economic analyses (TEAs). This study investigates the potential of three agri-food residues—almond hulls, exhausted olive pomace (EOP), and date palm fronds (DP)—as biomass fuels for gasification from a sustainability standpoint. Two configurations for combined production of electricity and heat in the form of hot water are evaluated: one using a cleaning and cooling unit coupled to an internal combustion engine (ICE), and another using an externally fired gas turbine combined with an organic Rankine cycle bottoming unit (EFGT_ORC). Results reveal that the EFGT_ORC cogeneration system consistently requires lower biomass input than the ICE cogeneration unit, with DP fronds demanding the highest biomass input in the ICE configuration at 36 g/s, followed by almond hulls at 32 g/s, and EOP at 28 g/s. ICE cogeneration contributes to higher climate change environmental impact, with emissions around 2.95 × 10−2 kg CO2 eq. for all fuels. In terms of human health, DP fronds have a greater impact in EFGT_ORC cogeneration than in ICE. Almond hulls exhibit slightly better economic performance compared to EOP and DP fronds. However, regardless of the biomass fuel, biomass and electricity price variations significantly affect system sustainability. The ICE system offers faster returns on investment, but is more vulnerable to increasing biomass prices, whereas the EFGT-ORC system demonstrates more resilience to biomass price fluctuations.
Techno-economic assessment of an off-grid biomass gasification CHP plant for an olive oil mill in the region of Marrakech-Safi, Morocco
(MDPI, 2023-05-12) Sánchez-Lozano, Daniel; Escámez, Antonio; Aguado-Molina, Roque; Oulbi, Sara; Hadria, Rachid; Vera, David
A substantial number of off-grid olive oil mills in Morocco are powered by diesel-fired generators, which hugely contribute to air pollution and greenhouse gas emissions. In this research work, a biomass gasification combined heat and power (CHP) plant fueled with local by-products was explored as a renewable alternative to electrify off-grid olive oil mills in this country. The case study considered a gasification CHP plant with a rated power of 80 kWe, in order to enable adaptation of the producer gas flow rate to abrupt changes in the power generation unit under dynamic operation. A downdraft gasifier and a producer gas conditioning unit were modeled under steady state operation using Cycle-Tempo, while the power generation unit was modeled in the Thermoflex simulation environment under partial and full load operation. Olive cake pellets and olive pruning chips were evaluated as biomass feedstock, with moisture contents ranging from 5% to 20% (wet basis). The results from the simulation of the gasification CHP plant showed net electrical efficiencies and CHP efficiencies around 18% and 35%, respectively. Finally, a profitability assessment of the gasification CHP plant was developed for 2 months of continuous operation, together with a sensitivity analysis. The results for the baseline scenario reveal a payback period of 7–8 years and a 68.5% accumulated profit based on the capital investment, which suggest that biomass gasification CHP plants can represent an economically feasible and sustainable solution for the electrification of off-grid areas in Morocco.
Power Gain and Daily Improvement Factor in Stand-Alone Photovoltaic Systems With Maximum Power Point Tracking Charge Regulators. Case of Study: South of Spain
(American Society of Mechanical Engineers, 2013-11) Muñoz-Rodríguez, Francisco José; Jiménez-Castillo, Gabino; Fuentes-Conde, Manuel; Aguilar-Peña, Juan Domingo
The performance reliability of a stand-alone photovoltaic system (SAPV) depends on the long-term performance of the batteries. In this way, a charge controller becomes an essential device which not only prevents the batteries from suffering deep discharges and overvoltages but also monitors the battery state of charge (SOC) in order to maximize charging efficiency and energy availability. At present, pulse width modulated (PWM) charge regulators dominate the market for this type of component in SAPV systems. However, in recent years, to improve energy management, more manufacturers have developed controllers with strategies for maximum power point tracking (MPPT). PWM charge controllers do not always make optimum use of the available power given by the maximum power point and this gives a loss of power. These power losses depend on battery voltage, irradiance and temperature. However, they can be avoided by using a MPPT charge controller which operates the array at its maximum power point under a range of operating conditions, as well as regulating battery charging. The advantage, in terms of energy gain, provided by this type of charge regulator depends on weather conditions. This paper will study the power gain provided by this type of charge controller, depending on the module temperature and the battery voltage. The paper will, additionally, provide a study of the gain in energy yield, also shown as improvement factor, F, for SAPV systems installed in Jaén (South of Spain). This study may illustrate the behavior of these two types of charge controllers in warm weathers, like Mediterranean climates. Furthermore, it will analyze the suitability of MPPT charge controllers and their benefits in this type of climate. It will be shown that MPPT charge regulator global efficiency constitutes a key issue in making a choice between MPPT and PWM charge regulators. The results given here may be not only of interest for SAPV systems with no access to the electricity grid but also for battery back-up PV grid-connected PV (GCPV) systems.
A new tool to analysing photovoltaic self-consumption systems with batteries
(Elsevier, 2021-05) Muñoz-Rodríguez, Francisco José; Jiménez-Castillo, Gabino; de-la-Casa Hernández, Jesús; Aguilar-Peña, Juan Domingo
Most of the studies that can be found in the literature for analysing self-consumption systems with storage focus on global self-consumption and self-sufficiency indices and it may be very difficult to define the role of the array power and battery. In this sense, a new approach to analysing this type of systems is provided where direct and battery self-sufficiency and self-consumption indices are defined. The latter represent the direct photovoltaic self-consumed energy and the one provided by the battery. New direct and battery ZEB points are also presented. Furthermore, this type of system is generally analysed using complex 3D plots. Therefore, a new and intuitive 2D contour tool is provided: the iso selfconsumption curves. The new approach has been applied to three households located in Spain. Results show that it may be reached a global self-sufficiency of 50% considering array powers and rated capacities below 3.5 kWp and 1 kWh, respectively, where direct and battery self-sufficiency indices may reach 40% and 10%, respectively. This new method together with the graphical tool may help not only to analyse this type of system but to properly size the array power and the rated capacity from either an energetic or profitability approach.
Distributed generation and photovoltaic selfconsumption. Energy potential for the olive mill industries in Spain
(Publicaciones DYNA SL, 2020-09) Martínez-Calahorro, Antonio Javier; Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Muñoz-Rodríguez, Francisco José
The industrial sector faces a new paradigm of energy offshoring, where distributed generation can play a leading role in reducing energy costs in industries, as well as in its C02 emissions. This work shows the potential that photovoltaic self-consumption systems can present to face part of the consumption in the industries of the agri-food sector, specifically the oil mills. The electrical consumption of this type of industry for an oil mill is analyzed, as well as the level of coupling between the actual consumption profiles and the estimated photovoltaic generation profiles for a given range of powers of the photovoltaic generator. The analysis method is easily extrapolated to any mill located in Spain. Likewise, and given that this type of industry has a very characteristic consumption profile, the results obtained are easily transferable to other oil mills. For the mill analyzed, and from an annual perspective, a level of use of the generated photovoltaic energy of 75% with a self-sufficiency index of 20% has been estimated, highlighting the great potential of this technology, as an energy option in this type of industry, as well as in any other that presents a consumption with little variability.
Effects of smart meter time resolution when analyzing photovoltaic self-consumption system on a daily and annual basis
(Elsevier, 2021-02) Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Tina, Giuseppe Marco; Muñoz-Rodríguez, Francisco José
The management of photovoltaic self-consumption systems is based mainly on updating energetic parameters such as generation and household power consumption connected via smart devices. The expected rapid increasing volume of data collected with different time resolutions is surely a topic that deserves great attention. The choice of a proper recording interval should balance the amount of monitored data and a proper energy analysis in order not only to take effective and timely decisions but also to help this technology to be more efficient. In the literature, only specific nominal array powers for annual reporting period or an array power range for daily reporting period have been considered. In this context, the error, when matching photovoltaic generation and household power consumption profiles considering different recording intervals (1, 10, 15, 30 and 60 min) and different reporting periods (daily and annual), will be estimated as a function of the array power (up to 10 kWp) for five households and a resident’s association. Results depend on the reporting periods and it may be advisable to use 1 min and 10 min of recording intervals in order to estimate performance metrics in this type of system for a daily and annual basis, respectively.
Performance analysis indices for Rooftop Solar Photovoltaic system
(IEEE, 2023-07-09) Jiménez-Castillo, Gabino; Martínez-Calahorro, Antonio Javier; Rus-Casas, Catalina; Snytko, Anastasiia; Muñoz-Rodríguez, Francisco José
The integration of rooftop solar photovoltaic systems into the electricity grid may be crucial in the current energy scenario. At present, this type of electricity generation is cost-competitive in many countries due to its modularity, the availability of the solar resource and the cost of the components, without the need for subsidies. Rooftop Solar Photovoltaic systems have the potential to cover 20-30% of electricity demand in Spain. In order to assess the potential of this technology and to facilitate the deployment of this type of systems, it is very important to provide a proper performance analysis of PV Rooftops systems from monitored data. In this way, self-consumption and self-sufficiency indices are commonly used, however they may not provide a complete assessment. Hence, indices such as the self-sufficiency index for sunshine hours, self-production index and grid-liability rate are also analyzed. These indices estimate the performance of rooftop solar PV systems and provide maximum and minimum values when estimated as a function of array peak power. Moreover, new indices such as the self-production index and the grid-liability rate for sunshine duration have been developed to estimate the system's performance during sunshine hours. These indices can complement the commonly used metrics and improve the performance analysis from monitored data. Moreover, they may also help determine the proper size of the array power of these systems in the industrial sector. The metrics are evaluated using data from four canning industries equipped with rooftop solar photovoltaic systems that have been monitored for a year.
A new approach based on economic profitability to sizing the photovoltaic generator in self-consumption systems without storage
(Elsevier, 2020-04) Jiménez-Castillo, Gabino; Muñoz-Rodriguez, Francisco José; Rus-Casas, Catalina; López-Talavera, Diego
A proper assessment of the cost-competitiveness and profitability of self-consumption systems is crucial to promoting the transition from grid-dependent to energy self-sufficient buildings. Most of the approaches found in the literature may not take into account economic parameters such as taxes, depreciation and the cost of financing, which have a significant effect on the economic profitability of an investment. Moreover, they only focus on discrete array powers and relatively high recording intervals when estimating the self-consumed energy. In order to manage the aforementioned challenges, a new method will be developed to size the PV generator in a PV self-consumption system which provides the NPV curve together with the self-consumption and self-sufficiency indices for a wide range of array powers which suits residential self-consumption systems. Two scenarios will be considered depending on whether the generated surplus electricity is wasted or it is remunerated from the grid operator. Results show that not only the chosen scenario but the electricity tariff may be key parameters when optimizing NPV. Furthermore, the impact of the recording interval may be significant when estimating NPV. Percentage errors of 11.4% and 33.6% may be reached when considering a recording interval of 15 and 60 min, respectively.
Monitoring PWM signals in stand-alone photovoltaic systems
(Elsevier, 2019-02) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Rus-Casas , Catalina; Casa-Hernández, Jesús; Tina, Giuseppe Marco
The performance of stand-alone photovoltaic (SAPV) systems can be evaluated by monitoring them in the field using data acquisition systems (DASs). Most SAPV systems use battery charge controllers with pulse width modulation (PWM) to regulate the current into the battery. The PWM signals generated by battery charge controllers imply monitoring challenges due to the complexity of this type of signal. In this sense, the aim of this paper is to develop a new and simple monitoring technique for SAPV systems which can estimate the signals provided by a PWM battery charge controller, thus avoiding expensive DASs, simultaneous sampling and the huge amount of collected data. The estimation of PWM signal parameters, such as the duty factor (df) or high and low states, shows high accuracy, with the mean absolute percentage error lower than 1.4%, a mean relative error within 1.4%, and the coefficient of determination higher than 0.9. Furthermore, the proposed technique may easily be used for other electrical devices where PWM is employed.
A new approach to sizing the photovoltaic generator in self-consumption systems based on cost–competitiveness, maximizing direct self-consumption
(Elsevier, 2019-01) López-Talavera , Diego; Muñoz-Rodríguez , Francisco José; Jiménez-Castillo, Gabino; Rus-Casas, Catalina
Applications for sizing Photovoltaic (PV) self-consumption systems have been studied over recent years in order to achieve either an optimization of the cost of energy, the investment cost or any economic profitability criteria. However, PV self-consumption systems at the residential or small business level can be designed with the aims of reducing the electricity consumption from the conventional local grid and achieving competitiveness with grid electricity prices. These criteria will provide not only greater environmental benefits, security and independence of the grid but it will make the cost of PV self-consumption electricity competitive with electricity prices from the power grid. In this sense, this paper proposes a method to size the generator for a PV self-consumption system based on cost-competitiveness, maximizing direct self-consumption. The method will be applied for three different households located in the south of Spain using the household daily consumption and generation profiles for a single year. However, the method here illustrated can be applied to other countries. The results obtained suggest that residential direct PV self-consumption systems with an annual global irradiation at the optimal tilt angle higher than 1000 kWh/(m2·year) may be a feasible investment to future owners of these systems.
Photovoltaic Self-Consumption in Industrial Cooling and Refrigeration
(MDPI, 2020-12-21) Martínez-Calahorro, Antonio Javier; Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Gómez-Vidal, Pedro; Muñoz-Rodríguez, Francisco José
The industrial sector has a great opportunity to reduce its energy costs through distributed generation. In this sense, the potential of photovoltaic self-consumption systems in the industrial cooling and refrigeration sector is shown. Two industries with photovoltaic self-consumption installations are shown and the electricity consumption profile of this type of industry which has a remarkable basal electricity consumption during daytime is analyzed. The matching between consumption and photovoltaic generation profiles is provided through the self-consumption and self-sufficiency curves considering different reporting periods (monthly and annual). Moreover, a new index is presented: self-sufficiency index for sunshine hours, φSS,SH. This index evaluates the performance of the photovoltaic self-consumption system when facing the consumption only during sunshine hours. This index may complement the self-sufficiency index and may improve the analysis of this type of systems in the industrial sector. Self-consumption indices of 90% may be provided. Moreover, self-sufficiency indices for total (24 h) and for sunshine hours of 25% and 50%, respectively, for industry A, and 26% and 45% for industry B have been obtained. During daytime, half the load consumption in this type of industry may be covered by photovoltaics while achieving high levels of use of the photovoltaic energy generated.
Impacts of Array Orientation and Tilt Angles for Photovoltaic Self-Sufficiency and Self-Consumption Indices in Olive Mills in Spain
(MDPI, 2020-02-18) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Martinez-Calahorro, Antonio Javier; Tina, Giuseppe Marco; Rus-Casas, Catalina
Olive mills are extensive in the Mediterranean Basin, and Spain constitutes approximately 45% of global production. The industrial sector faces a new energetic paradigm where distributed generation provided by small renewable energy sources may reduce the dependence from fossil energy sources as well as avoid energy distribution losses. Photovoltaic self-consumption systems can play an important role in confronting this challenge due to their modularity and their decreasing cost. Most of self-sufficiency energy studies are focused on building sector and discussions about the idiosyncrasy of industrial load profiles, and their matching capability with photovoltaic generation profiles can be scarcely found. This work analyzes the potential of photovoltaic self-consumption systems as a function of the array power, array tilt, and orientation angles to face the electric consumption in olive mills. Different recording intervals and reporting periods are considered. Results show that a self-sufficiency index of 40% may be achieved on olive harvest basis. Moreover, due to the load profile particularities, percentage error lower than 1.6% has been found when considering a recording interval of 60 min when matching the olive load consumption and photovoltaic generation profiles. Chosen array tilt and orientation angles may be key parameters to maximize the self-sufficiency index.
Development of a Prototype for Monitoring Photovoltaic Self-Consumption Systems
(MDPI, 2020-01-01) Rus-Casas, Catalina; Jiménez-Castillo, Gabino; Aguilar-Peña, Juan Domingo; Fernández-Carrasco, Juan Ignacio; Muñoz-Rodríguez, Francisco José
Currently, the increasing energy consumption around the world and the environmental impact resulting from the use of fossil fuel-based energy have promoted the use of renewable energy sources such as photovoltaic solar energy. The main characteristic of this type of energy is its unpredictability, as it depends on meteorological conditions. In this sense, monitoring the power generation of photovoltaic systems (PVS) in order to analyze their performance is becoming crucial. The purpose of this paper is to design a monitoring system for a residential photovoltaic self-consumption system which employs an Internet of Things (IoT) platform to estimate the photovoltaic power generation according to solar radiation and temperature. The architecture of the developed prototype will be described and the benefits of providing the use of IoT for monitoring will be highlighted, since all data collected by the data acquisition system (DAS) may be stored in the Cloud. The comparison of the results with those of other monitoring systems was very positive, with an uncertainty that complies with the IEC61724 standard.
Improvements in Performance Analysis of Photovoltaic Systems: Array Power Monitoring in Pulse Width Modulation Charge Controllers
(MDPI, 2019-05-09) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Rus-Casas, Catalina; Gómez-Vidal, Pedro
Various challenges should be considered when measuring photovoltaic array power and energy in pulse width modulation (PWM) charge controllers. These controllers are frequently used not only in stand-alone photovoltaic (SAPV) systems, but may also be found in photovoltaic (PV) self-consumption systems with battery storage connected to the electricity grid. An acceptable solution may be reached using expensive data acquisition systems (DASs), although this could be generally disproportionate to the relatively low cost of SAPV systems. Therefore, the aim of this paper is to develop new and e ective monitoring techniques which will provide the PV array direct current (DC), output power (PA,dc), and PV array DC output energy (EA), thus avoiding the use of sophisticated DASs and providing high accuracy for the calculated parameters. Only transducers and electronic circuits that provide the average and true rms values of the PWM signals are needed. The estimation of these parameters through the aforementioned techniques showed high accuracy for both series and shunt PWM battery charge controllers. Normalized root mean square error (NRMSE) was lower than 2.4%, normalized mean bias error (NMBE) was between 􀀀1.5% and 1.1%, and mean absolute percentage error (MAPE) was within 1.6%.
Development of a Utility Model for the Measurement of Global Radiation in Photovoltaic Applications in the Internet of Things (IoT)
(MDPI, 2019-03-08) Rus-Casas, Catalina; Hontoria, Leocadio; Fernández-Carrasco, Juan Ignacio; Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José
In order to develop future projects in the field of photovoltaic solar energy, it is essential to accurately know the potential solar resources. There are many methods to estimate the incident solar radiation in a certain place. However, most of them are very expensive or do not have the ideal characteristics for good monitoring of a particular photovoltaic installation. For these reasons, an electronic device connected to the internet of things (IoT) is presented in this paper which manages to measure global radiation in photovoltaic applications. The device developed has been patented in the Spanish Patent and Trademark Office. It presents some features that make it very suitable to measure photovoltaic installations with the advantage of being a low cost and very reliable device. The device has been tested to determine global horizontal irradiance obtaining a correlation coefficient R2 = 0.994.
Robust dynamic charging price in PV-assisted charging stations
(Elsevier, 2025-10-01) Tostado-Véliz, Marcos; Hasanien, Hany M.; Arévalo, Paul; Jurado-Melguizo, Francisco
With the increasing number of electric vehicles on road, the deployment of sufficient public charging infrastructures has become critical. To encourage the installation of new public charging points, such infrastructures need to be economically viable and profitable. In this regard, exploring economic activities within charging infrastructures has become a key topic to ensure the long-term financial sustainability of charging installations. In line with this objective, this paper develops a new robust methodology to setting dynamic charging prices in charging stations. Unlike to conventional charging prices based on flat tariffs, dynamic pricing strategies can follow wholesale electricity prices, potentially setting low prices and therefore displacing the fleet from domestic to public charging. The new proposal renders as a game-theoretical max-min bi-level optimization problem. To address the initial complexity of the formulation, a tailored solution algorithm is developed, which allows accessing to robust solutions efficiently. An adaptive robust modelling of uncertainties is proposed, based on intervals, which allows representing uncertainties as box-constrained variables. Moreover, this paper contributes with a new data-driven approach to determine limits on uncertainties based on bootstrapping. The new solution strategy is validated on a benchmark large-scale charging station installing a photovoltaic facility. Additionally, the effect of the risk level and photovoltaic size on final results is evaluated. In addition, the effectiveness of the charging pricing strategy is assessed, along with the influence of uncertainties on the final results.

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