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Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide.

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This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

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The study presents a complete one-dimensional model to evaluate the parameters that describe the operation of a Proton Exchange Membrane (PEM) electrolyzer and PEM fuel cell. The mathematical modeling is implemented in Matlab/Simulink® software to evaluate the influence of parameters such as temperature, pressure, and overpotentials on the overall performance. The models are further merged into an integrated electrolyzer-fuel cell system for electrical power generation. The operational description of the integrated system focuses on estimating the overall efficiency as a novel indicator. Additionally, the study presents an economic assessment to evaluate the cost-effectiveness based on different economic metrics such as capital cost, electricity cost, and payback period. The parametric analysis showed that as the temperature rises from 30 to 70 °C in both devices, the efficiency is improved between 5-20%. In contrast, pressure differences feature less relevance on the overall performance. Ohmic and activation overpotentials are highlighted for the highest impact on the generated and required voltage. Overall, the current density exhibited an inverse relation with the efficiency of both devices. The economic evaluation revealed that the integrated system can operate at variable load conditions while maintaining an electricity cost between 0.3-0.45 $/kWh. Also, the capital cost can be reduced up to 25% while operating at a low current density and maximum temperature. The payback period varies between 6-10 years for an operational temperature of 70 °C, which reinforces the viability of the system. Overall, hydrogen-powered systems stand as a promising technology to overcome energy transition as they provide robust operation from both energetic and economic viewpoints.

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Abstract The growth in the use of solar energy has encouraged the development of techniques for short-term prediction of solar photovoltaic energy generation (PSPEG). Machine learning with Artificial Neural Networks (ANNs) is the most widely used technique to solve this problem. However, comparative studies of these networks with distinct structural configurations, input parameters and prediction horizon, have not been observed in the literature. In this context, the aim of this study is to evaluate the prediction accuracy of the Global Horizontal Irradiance (GHI), which is often used in the PSPEG, generated by ANN models with different construction structures, sets of input meteorological variables and in three short-term prediction horizons, considering a unique database. The analyses were performed with controlled environment and experimental configuration. The results suggest that ANNs using the input GHI variable provide better accuracy (approximately 10%), and their absence increases error variability. No significant difference (p>0.05) was identified in the prediction error models trained with distinct meteorological input data sets. The prediction errors were similar for the same ANN model in the different prediction horizons, and ANNs with 30 and 60 neurons with one hidden layer demonstrated similar or higher accuracy than those with two hidden layers.

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Solid-state nanochannels have attracted substantial attention of the scientific community due to their remarkable control of ionic transport and the feasibility to regulate the iontronic output by different stimuli. Most of the developed nanodevices are subjected to complex modification methods or show functional responsiveness only in moderate-ionic-strength solutions. Within this project, we present a nanofluidic device with enhanced ionic current rectification properties attained by a simple one-step functionalization of single bullet-shaped polyethylene terephthalate (PET) nanochannels with polyaniline (PANI) that can work in high-ionic-strength solutions. The integration of PANI also introduces a broad pH sensitivity, which makes it possible to modulate the ionic transport behavior between anion-selective and cation-selective regimes depending on the pH range. Since PANI is an electrochemically active polymer, ionic transport also becomes dependent on the presence of redox stimuli in solution. We demonstrate that PANI-functionalized single-nanochannel membranes function as an efficient salinity gradient-based energy conversion device even in acidic concentrated salt solutions, opening the door to applications under a variety of novel operating conditions.

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This paper presents a fuzzy-multiple objective optimization methodology to plan stand-alone electricity generation systems. The optimization process considers three main objectives, namely technology cost, environmental and societal impacts. For each feasible solution of the Pareto set, a system reliability index is evaluated along the lifetime of the project. As a key contribution, the decision making process is carried out by applying a fuzzy satisfaction method (FSM). The FSM accounts simultaneously four key performance indexes (KPI): technical, economic, environmental and social. The novelty of the proposal lies on the inclusion of societal impact (local wealth creation) in the FSM used here to select the more appropriate solution. Previous contributions on FSM only accounts two of four indexes considered in this paper. The methodology was applied in a Colombian case study. The results show the importance of the simultaneous consideration of technical, economic, environmental and social objectives in the evaluation of off-grid energization solutions.

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The data included in this study was calculated based on data provided by the national project registry provided by the Colombian government. The data forecasts the evolution of the power generation capacity registered in non-conventional renewable energy source projects in three scenarios of implementation of the power generation capacity registered in the projects. Results can be used to benchmark non-conventional renewable energy sources in Colombia, interpret the effectiveness of renewable policies, and monitor the evolution of non-conventional renewable-based power generation. The data presented in the article relates to the research study: A look to the electricity generation from non-conventional renewable energy sources in Colombia [1].

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This paper presents the application of a systematic methodology to obtain a semi-physical model of phenomenological base for a 2 MW internal combustion engine to generate electric power operating with natural gas, as a function of the average thermodynamic value normally measured in industrial applications. Specifically, the application of the methodology is focused on the cylinders, exhaust manifold, and turbocharger turbine sections. The proposed model was validated with actual operating data, obtaining an error rate not exceeding 5%, which allow a thermal characterization of the Jenbacher JMS 612 GS-N based on the model. A parametric analysis is conducted; considering the volumetric efficiency, the output electric power, the effective efficiency, the exhaust gas temperature, the turbine mass flow, the specific fuel consumption under the nominal operation conditions, which is 1.16 bar in the gas pressure, 65 °C in the cooling water temperature, 35 °C in the average ambient temperature, and 1500 rpm. The results of this model can be used to evaluate the thermodynamic performance parameters of waste heat recovery systems. On the other hand, new control strategies and the implementation of state observers for the detection and diagnosis of failures can be developed based on the proposed model.

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This study aimed to produce bioethanol using Spirulina platensis biomass and the use of saccharification and fermentation wastes of bioethanol production to produce biomethane. The potential for energy generation in each technological route was quantified. Both, the enzymatic hydrolysis of the microalgae polysaccharides and the fermentation process, presented efficiencies above 80%. The fermentation of the hydrolyzate into ethanol was possible without the addition of synthetic nutrients to the must. The direct conversion of Spirulina biomass to biomethane had an energy potential of 16,770 kJ.kg-1, while bioethanol production from the hydrolysed biomass presented 4,664 kJ.kg-1. However, the sum of the energy potential obtained by producing bioethanol followed by the production of biomethane with the saccharification and fermentation residues was 13,945 kJ.kg-1. Despite this, the same raw material was able to produce both biofuels, demonstrating that Spirulina microalgae is a promising alternative to contribute in the field of renewable energies.

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Microbial life is predominantly observed as biofilms, which are a sessile aggregation of microbial cells formed in response to stress conditions. The microtiter dish biofilm formation assay is one of the most important methods of studying biofilm formation. In this study, the assay has been improvised to allow easy detection of biofilm formation on different substrata. The method has then been used to study growth conditions that affect biofilm formation, viz., the effect of pH, temperature, shaking conditions, and the carbon source provided. Glass, cellulose acetate, and carbon cloth materials were used as substrata to study biofilm development under the above conditions. The method was then extended to determine biofilm formation on the anodes of a microbial fuel cell in order to study the effect of biofilm formation on power production. A high correlation was observed between biofilm formation and power density (r = 0.951). When the electrode containing a biofilm was replaced with another electrode without biofilm, the average power density dropped from 59.55 to 5.76 mW/m2. This method offers an easy way to study the suitability of different materials to support biofilm formation. Growth conditions determining biofilm formation can be studied using this method. This method also offers a non-invasive way to determine biofilm formation on anodes of microbial fuel cells and preserves the anode for further studies.

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The objective of this study is to evaluate the potential for electricity generation in the State of São Paulo (SP) from the sewage treatment. A sewage treatment plant (STP) with domain in the production of biogas from wastewater treatment plant (WWTP) is the basis for this case study. The basic premise is that the very generation of electricity in STPs is advantageous for companies in the sanitation sector in Brazil, resulting in cost reductions of the treatment process. Gains at the end of the process are found in two levels, namely: (i) economic, by generating 165% of electricity from biogas burning in relation to the expend; (ii) energy, by adding a new sustainable and storable energy source equivalent to 4% of natural gas offered in the State of SP and 0,5% of electricity produced from biogas burning in relation to electricity consumption. In conclusion, the potential of electricity production linked to the biogas at STPs is capable of supply its domestic demand and export the surplus to other segments of the state and national economy.

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Abstract: Humanity is increasingly dependent on energy, which demand grows every year. Renewable energy sources are consolidated alternatives in the market, previously installed on a small scale but now thought as large plants. The correct operation, taking full advantage of the generation potential, depends on studies of the place of implantation, such as radiation levels, temperature, latitude, etc. Two photovoltaic systems installed in the city of Curitiba were studied in order to monitor their respective performances through figures of merit.

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The use of nonrenewable energy sources to provide the worldwide energy needs has caused different problems such as global warming, water pollution, and smog production. In this sense, lignocellulosic biomass has been postulated as a renewable energy source able to produce energy carriers that can cover this energy demand. Biogas and syngas are two energy vectors that have been suggested to generate heat and power through their use in cogeneration systems. Therefore, the aim of this review is to develop a comparison between these energy vectors considering their main features based on literature reports. In addition, a techno-economic and energy assessment of the heat and power generation using these vectors as energy sources is performed. If lignocellulosic biomass is used as raw material, biogas is more commonly used for cogeneration purposes than syngas. However, syngas from biomass gasification has a great potential to be employed as a chemical platform in the production of value-added products. Moreover, the investment costs to generate heat and power from lignocellulosic materials using the anaerobic digestion technology are higher than those using the gasification technology. As a conclusion, it was evidenced that upgraded biogas has a higher potential to produce heat and power than syngas. Nevertheless, the implementation of both energy vectors into the energy market is important to cover the increasing worldwide energy demand.

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ABSTRACT Photovoltaic solar energy is increasingly present in the urban environment through the distributed generation. This kind of generation is characterized by the installation along the distribution network feeders, in low or medium voltage, and contribute to provide energy near the point of consumption. In this sense, this study aims to analyze the demand and consumption curves of the buildings of the Federal University of Technology - Paraná (UTFPR) in the Neoville's headquarters. The methodology consists in the application of COPEL's CAS Hemera platform, in order to determine the potential for the implementation of the Grid-Connected Photovoltaic Systems in this place, because they allow the reduction of costs with electric energy from the application of distributed generation. In February 2016, a grid-connected photovoltaic system was installed in one of the university's blocks, which generated approximately 11 MWh of electric energy this year. This work proposes a scenario for the expansion of this photovotaic system and presents the contribution of photovoltaic generation, using the available coverage showing the shifting or reduction of energy demand peaks and the energy contribution to UTFPR's Neoville headquarters. The results of this study show that the proposed scenario will effectively change the profile of the university demand curve.

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ABSTRACT This study presents a system of conversion of mechanical energy produced by physical activity into electric energy obtained by a CC generator coupled to the pedal of an ergometric bicycle. It presents the converter that will be used to adjust the voltage and power coming from the system, as well as the details of the converter design, the simulation and the primary experimental results of the structure. The methodological procedures related to the development of the converter and data acquisition through simulation were carried out based on the bibliographic research. The study is documentary as equipment manuals were used.

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ABSTRACT The present study evaluates the economic viability of the application of solar energy for electric power generation via the use of photovoltaic systems in a residential consumption unit in the city of Curitiba. Since the energy from the sun is abundant, clean, renewable and has the potential to compete in productivity and profitability, the evaluation of the applicability of these systems in homes, not only in industrial parks, is of great interest. A household with the determined consumption profile was chosen for this case study through simulations with the HomerPro software. After analyzing the data, the photovoltaic potential of the State of Paraná was estimated to investigate the possibility of photovoltaic generation growth in the state energy matrix and its consequences.

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ABSTRACT Photovoltaic systems have been consolidated in the global energy scenario as an option of low environmental impact energy generation, high reliability and great applicability in urban centers, acting like energy generators near the point of consumption. The Federal University of Technology of Paraná (UTFPR), with the proposal of testing the performance of grid-connected photovoltaic systems (On Grid PV Systems) and help its entry into the Brazilian energy matrix, implemented this technology in two of its buildings: Green Office (GO) And Neoville. This paper analyzed the effects of dust on the Photovoltaic Systems performance based on daily energy. The analysis was carried out from the solar irradiance data from the places where the panels are installed and the electrical power data collected at the mass memory of the inverter of the two systems, in order to be analyzed and compared before and after the cleaning of the photovoltaic modules. The results at the end of the study indicate that dust directly impacts in the performance of the PV system.

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