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This study compared the effects of accentuated eccentric warm-up on power, speed, and agility in 12 male varsity soccer players who were assigned in a counterbalanced randomized order to 3 warm-up protocol sequences: 1) Accentuated Eccentric Warm-Up (ACC); 2) Modified FIFA 11+ Warm-Up (MFI); and 3) Dynamic Warm-Up (DYN). Peak Power Output (PPO), Peak Vertical Ground Reaction Force (PVGRF), Peak Velocity (PV), 10-m (10M) and 20-m Speed Test (20M), and agility (AG) were assessed immediately following each warm-up protocol. Data were analyzed by using One-Way Repeated Measures ANOVA, with Bonferroni post-hoc tests applied for pairwise comparisons. Significance level was set at a P value < 0.05. The findings indicate significant differences in PPO (P < 0.001, partial η² = 0.82), PV (P < 0.001, partial η² = 0.48), 10M (P < 0.003, partial η² = 0.42), 20M (P < 0.001, partial η² = 0.50) and AG (P < 0.001, partial η² = 0.69) were found among the 3 warm-up protocols. Post-hoc analysis revealed that the PPO, 20M, and AG of the ACC was significantly better than the MFI and DYN. Also, the PV and 10M of the ACC was significantly better than that the DYN. Additionally, the PPO and AG of MFI was significantly better than that the DYN (P < 0.05). However, there were no significant differences observed in the PVGRF among the warm-up protocols (P > 0.05). Our results indicate that the ACC is an effective method for enhancing power, speed, and agility via the use of PAP during the preload exercise. Coaches and athletes are encouraged to incorporate the ACC to enhance the power, speed, and agility of soccer players. [ABSTRACT FROM AUTHOR]

The performance benefits of using tip devices on wind turbines has been well-documented. However, previous studies show that adding blade tip devices such as winglets leads to a significant increase in blade root bending moment, potentially requiring structural reinforcement with cost and weight drawbacks. A new and unique design philosophy for retrofit blade tip devices for wind turbines is presented. By balancing generated aerodynamic and centrifugal loads, these devices offer an increase in power production without the need for structural reinforcement. Predicted performance and cost benefits of using retrofit blade tip devices on the National Renewable Energy Laboratory 5 MW reference wind turbine are shown. The addition of blade tip devices resulted in significant improvements in the coefficient of power (Cp) and annual energy production (AEP). [ABSTRACT FROM AUTHOR]

Due to rising demand and expanding economies, forecasting electricity loads is vital for electrical system management. Precise forecasts assure both economic stability and effective utilization. The basis for generating schedules and managing energy is established by prediction, which is crucial for power stations and transmitting facilities. The purpose of this research is to develop an efficient load prediction approach. Hence, this study presents a novel fine-tuned backtracking search-driven log-sigmoid recurrent network (FBS-LRN) framework for improved thermal electricity load prediction. In the proposed framework, the FBS optimization strategy is introduced for recurrent network activated dynamically in long and short term memory (LSTM) with the log-sigmoid function. In the beginning, the FBS optimization approach is employed to improve the LSTM's characteristics to tackle the issue that the LSTM's performance will be impacted by the unpredictability of its internal properties. Next, using the Python platform, the electricity load projection framework, depending on the suggested FBS-LRN will be implemented into practice and examined using several criteria. The comprehensive research reveals that the suggested approach has superior prediction accuracy and efficacy compared to the current models. Planning for power production and use in the electrical system can be aided within thermal by higher-quality load forecasts. [ABSTRACT FROM AUTHOR]

Power systems are run by combining different energy producers while the demand serves as the system's energy user and covers all of the non-flexible and flexible loads, including electric vehicles (EVs). This study investigated the trip pattern impact of EVs, utilizing the Orca Algorithm (OA), in optimizing power production, applied to the IEEE-62 bus system as a model. Considering one-way and two-way trips over several categories of typical roads, the mobility of 14,504 EVs, divided into four driving patterns (Mobility 1-4), was estimated. Approximately 2,933 EVs traveled for working/business/study purposes, 3,862 EVs traveled for service/shopping purposes, approximately 5,376 EVs traveled for leisure purposes, while 2,334 EVs traveled for other reasons. The system had a total demand of 18,234.9 MVA, including 3,352.8 MW for electric vehicles and 14,151.5 MW for non-flexible loads. The EVs traveled a total of 119,018 km in Mobility 1, 141,799 km in Mobility 2, 184,614 km in Mobility 3, and 82,637 km in Mobility 4. The power produced was also used to charge the EVs during trips. [ABSTRACT FROM AUTHOR]

This study aims to study the ability to deploy concentrated solar energy systems, specifically the solar power tower in Jordan, to promote the development of Jordan by utilizing the abundant solar radiation present in the region and taking advantage of available open spaces. This work used the SAM software to conduct a simulation for the Gemasolar power plant located in Spain, in the south of Jordan. Three different cooling systems were implemented. The application of this plant aims to utilize the benefits of energy storage through molten salt, enabling energy production in the absence of sunlight. It was also found that implementing the Gemasolar plant in the southern region of Jordan increases energy production by 8.1% compared to its implementation in Spain, highlighting the success of this system in Jordan. [ABSTRACT FROM AUTHOR]

The use of nanofluids (NFs) as heat transfer fluids (HTFs) is one way of improving the thermal performance of parabolic trough solar collectors (PTSCs). This study presents a comparative analysis of the thermal performance of a PTSC using nanofluids as HTF. Two categories of nanoparticles (NPs) (green and conventional) and two base fluids (water and Syltherm 800) giving eight nanofluids are used in a one-dimensional quasi-static thermal model, simulated from a numerical code written in Matlab. After numerical validation of the proposed model, the comparative analysis in static and dynamic regimes linked to solar radiation shows that green NPs present not only differentiated positive but also negative effects on thermal performance depending on the base fluids compared to conventional NPs, and that the combination of green nanoparticles with high thermal capacity base fluids presents more positive than negative thermal effects. The impact of conventional NPs is more significant with water, at around 0.005 MWh, than with Syltherm 800, which averages around 0.002 MWh. The use of HTF configurations based on Syltherm 800 increases production by around 1 MWh more than that of water. HTF configurations based on Syltherm 800 generate around $0.004/kWh less than water on average. HTFs based on Syltherm 800 produce around 7.5 kgCO2/year more than water.

Based on the significance and role of ChatGPT in the power and knowledge production, this research aims to display how ChatGPT responds to questions that are by nature controversial and debatable, as their values depend on the agency or power that answers them. The main question of this work is whether this artificial intellegince model is influenced by any discourse(s). The approaches employed in this work are Michel Foucault's discourse analysis and Norman Fairclough's Critical Discourse Analysis. It is contended that discourses are ubiquitously everywhere in social practices. To Fairclough and Foucault, language production is strongly connected to power and knowledge production. Therefore, utilising a qualitative method in the examination, the work wishes to identify the discourse(s) that can affect ChatGPT's responses and discuss its implications for knowledge and power production. The research discovered that ChatGPT's answers unveiled a prejudice towards capitalist discourse, established knowledge, and suppressed alternative opinions. Also, the definitions of capitalism and communism by ChatGPT were insufficient because the political and ideological dimensions of capitalism were ignored, which can be considered major findings of this present work regarding the two selected systems. This indicates that ChatGPT's knowledge production, an example or model from the ongoing technological revolution, cannot be relied on for being biased in its responses. [ABSTRACT FROM AUTHOR]

The control system for a micro-hydropower plant using an Archimedes screw turbine is the focus of this work. Three control systems were implemented based on a Barreda micro-hydropower plant (Spain) currently in operation: an optimal water level control ( O W L C ) system, a maximum power point monitoring ( M P P T ) system, and a water level control ( W L C ) system. The comparison was made using several assessment indicators: electricity production, micro-hydropower plant efficiency, and gearbox fatigue. The electricity production is similar in the O W L C and M P P T systems (energy gain + 0.5 % ) and significantly lower in the W L C system (energy gain − 12 % ). The efficiency of the micro-hydro plant is similar in the O W L C and M P P T systems (average efficiency gain + 0.9 % ) and significantly lower in the W L C system (average efficiency gain − 15 % ). The mechanical stress on the gearbox is similar in the O W L C and W L C systems and significantly higher in the M P P T system. It can be concluded that the O W L C system performs better as concerns the three assessment indicators used, followed by the M P P T system. The W L C system is not recommended for use, due to its low electricity production and low efficiency of the micro-hydropower plant. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the effect of stroke rate on performance, technique and core stability during rowing ergometer. Twenty-four high-level rowers performed maximal intensity one-minute bouts at 20, 28 and 34 spm on a RowPerfect3 ergometer. Power at the handle, legs, trunk and arms levels were determined, and core kinematics and neuromuscular activations were measured. The power at the handle was enhanced with a higher stroke rate in the first half of the drive phase due to higher segment’s powers. This resulted in technical changes, as for instance greater mean to peak power ratio at each segment level. The higher trunk power preceded a delayed trunk extension but without significant increase in the erector spinae activation. This underlines the role of the core stability to transfer forces at a higher stroke rate. However, no co-activation parameters between trunk flexors and extensors helped further to understand this force transfer. Rowing at low stroke rate can be a training strategy to work on earlier trunk extension, while maintaining erectors spinae levels of activation. Training at higher stroke rate will induce a rowing technique closer to competition with greater neuromuscular activations, and maximise power production. [ABSTRACT FROM AUTHOR]

In a previous work, a solar chimney power plant integrated with a solid sorption cooling system for power and cold cogeneration was developed. This prior work showed that reusing the heat released from the adsorption bed enhances the system's utilization of solar energy and increases the turbine's output power. In the present paper, a subsequent modification to the arrangement and operation of the preceding system is introduced. The primary objective of the modification is to enhance performance and increase the plant's capacity to effectively harness the available solar radiation. The method involves placing the condenser tubes at the solar collector entrance. Therefore, the airflow captures the condenser-released heat before it enters the collector. The modified configuration and operation of the system are discussed. A dynamic mathematical model is established to simulate the hybrid system's operation and evaluate its parameters. The obtained results show that a 5.95% increase in output power can be achieved by recovering the heat of condensation. Furthermore, the modified system attains a 6% increase in solar-to-electricity conversion efficiency compared with the basic system. The findings suggest that the modified system, which recycles condenser heat, provides noticeable enhanced performance compared with the basic system. [ABSTRACT FROM AUTHOR]

A new multi-generation plant incorporated with the ammonia synthesis reactor, a Cu-Cl cycle, and a S-Graz cycle plus a gas turbine cycle for electricity, hydrogen as well as ammonia production recommended and dissected from exergy, energy, exergoeconomic, exego-environmental, and environmental (5E) aspects, in this research. Furthermore, to investigate the effect of input variables on the plant function criteria, exhaustive sensitivity evaluations were carried out and disputed in detail. The exergy and energy yields, the products 'sum unit cost, the cost rate of environmental penalty as well as the emission rate of the offered poly-generation plant have been 41.16%, 45.57%, 369.6 $/GJ, and 0.0001319, respectively. Besides, the plant provided the net power output, hydrogen, and, ammonia of 151488 kW, 0.2199 kg/s, and 1.884 kg/s, sequentially. Also, the whole exergy destruction rate of the plant was computed at about 128.289 MW. Finally, the sensitivity investigations resulted that increasing the hydrogen molar flow rate and high-temperature turbine (HTT) inlet temperature had a positive effect on the techno-eco-environmental performances of the system. [Display omitted] • Introduction a new poly-generation system for power, ammonia, and hydrogen generation. • The aimed plant provides 0.2199 kg/s, 1.884 kg/s, and 151488 kW of hydrogen, ammonia, and power respectively. • The energy and exergy efficiencies and SUCP are about41.16%, 45.57%, and 369.6 $/GJ. [ABSTRACT FROM AUTHOR]

It is challenging for the European power system to exactly predict RES output and match energy production with demand due to changes in wind and sun intensity and the unavoidable disruptions caused by severe weather conditions. Therefore, in order to address the so-called "flexibility challenge" and implement the variable RES production, the European Union needs flexible solutions. In order to accommodate quicker reactions, compared to those performed today, and the adaptive exploitation of flexibility, grid operators must adjust their operational business model, as the electrical grid transitions from a fully centralized to a largely decentralized system. OneNet aspires to complete this crucial step by setting up a new generation of grid services that can fully utilize distributed generation, storage, and demand responses while also guaranteeing fair, open, and transparent conditions for the consumer. Using AI methods and a cloud-computing approach, the current work anticipates that active management of the power system for TSO–DSO coordination will be improved by the web-based client-server application F-channel. In the current work, a user's experience with the platform for a Business Use Case (BUC) under the scenario of severe weather conditions is presented. The current work aims to increase the reliability of outage and maintenance plans for the system operators (SOs) by granting them a more accurate insight into the conditions under which the system may be forced to operate in the upcoming period and the challenges that it might face based on those conditions. In this way, the methodology applied in this case could, via AI-driven data exchange and analyses, help SOs change the maintenance and outage plans so the potential grave consequences for the system can be avoided. The SOs will have accurate forecasts of the relevant weather parameters at their disposal that will be used in order to achieve the set targets. The main results of the presented work are that it has a major contribution to the optimal allocation of the available resources, ensures the voltage and frequency stability of the system, and provides an early warning for hazardous power system regimes. [ABSTRACT FROM AUTHOR]

Reverse electrodialysis (RED), an emerging membrane-based technology, harnesses salinity gradient energy for sustainable power generation. Accurate characterization of electrical parameters in RED stacks is crucial to monitoring its performance and exploring possible applications. In this study, a DC electronic load module (DCELM) is implemented in a constant current condition (CC mode) for characterization of lab scale RED process, using a RED prototype in-house designed and manufactured (RU1), at different data capture setups (DCS), on which the total number of steps for data capture (NS) and the number of measurements per step (ρ) are the parameters that were modified to study their effect on obtained electrical parameters in RED. NS of 10, 50, and 100 and ρ of 10 and 20 were used with this purpose. The accuracy of resulting current and voltage steps can be enhanced by increasing NS and ρ values, and according to obtained results, the higher accuracy of resulting output current and voltage steps, with low uncertainty of the average output steps (AOS) inside the operational region of power curve, was obtained using a DCS of NS = 100 and ρ = 20. The developed DCELM is a low-cost alternative to commercial electronic load devices, and the proposed methodology in this study represents an adaptative and optimizable CC mode characterization of RED process. The results obtained in this study suggest that data capture conditions have a direct influence of RED performance, and the accuracy of electrical parameters can be improved by optimizing the DCS parameters, according to the required specifications and the scale of RED prototypes. [ABSTRACT FROM AUTHOR]

Contrast training (CT) is a unique exercise approach that leverages post-activation potentiation (PAP) by integrating heavy and light loads while maintaining identical movement patterns within a single strength training. Objective: This study aimed to explore and compare the effects of post-activation performance enhancement (PAPE) using different contrast training protocols on vertical jumping performance. Methodology: Thirteen male varsity basketball players participating in this study were assigned in a counterbalanced randomized order to three contrast exercise sequences. Each protocol involved three distinct exercises: barbell back squat (BS) at 80% of 1-repetition maximum (1RM), weighted jump squat (WJ) at 20% 1RM, and bandassisted jump squat (BA) at 20 ± 5% of body-weight reduction (BWR). The contrast training 1 (CT1) involved 6 repetitions (reps) of BS followed by 12 reps of WJ. Contrast training 2 (CT2) consisted of 6 reps of BS followed by 12 reps of BA. Contrast training 3 (CT3) comprised three exercises: 6 reps of BS followed by 6 reps of WJ and 6 reps of BA. Peak power output (PPO), peak vertical ground reaction force (PVGRF), and peak barbell velocity (PBV) were assessed immediately following each CT program. Results: PBV and PVGRF significantly increased after CT1, CT2, and CT3 (p < 0.05). However, no significant differences were observed among the various contrast exercise conditions (p> 0.05). There were no significant differences in PPO immediately after the CT trial across the three conditions and between pre-post assessments (p > 0.05). Notably, significant differences in PBV were found among the three conditions (p < 0.02, partial η² = 0.63). Post-hoc analysis revealed that the PBV of CT2 was significantly better than that of CT1 and CT3. Conclusion: Our results indicate that CT is an effective method for enhancing jumping performance through the use of PAP during the preload exercise. The most significant improvement in jumping performance was observed with the combination of high-load resistance training followed by band-assisted jump squats. Therefore, coaches and athletes are encouraged to incorporate the CT method to enhance the jumping performance of basketball players. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) is an adaptive system that has the ability to predict the relationship between the input and output parameters without defining the physical and operation conditions. In this study, some queries about using ANN methodology are simply clarified especially about the neurons number and their relationship with input and output parameters. In addition, two ANN models are developed using MATLAB code to predict the power production of a polycrystalline PV module in the real weather conditions of Iraq. The ANN models are then used to optimize the neurons number in the hidden layers. The capability of ANN models has been tested under the impact of several weather and operational parameters. In this regard, six variables are used as input parameters including ambient temperature, solar irradiance and wind speed (the weather conditions), and module temperature, short circuit current and open circuit voltage (the characteristics of PV module). According to the performance analysis of ANN models, the optimal neurons number is 15 neurons in single hidden layer with minimum Root Mean Squared Error (RMSE) of 2.76% and 10 neurons in double hidden layers with RMSE of 1.97%. Accordingly, it can be concluded that the double hidden layers introduce a higher accuracy than the single hidden layer. Moreover, the ANN model has proven its accuracy in predicting the current and voltage of PV module.

This paper presents a MATLAB/Simulink model to design and assess Solar Chimney Power Plants (SCPPs) in any location worldwide, offering a simple and efficient approach that saves time and costs, while maintaining the flexibility of the design process. The model evaluates the physical and engineering specifications, pressure loss, power production, and characteristics of SCPPs. The model is applied to evaluate an SCPP in Kufa, Iraq, where no previous study has been conducted to evaluate such renewable energy sources. The proposed model's reliability is demonstrated by comparing the results to those from previous literature. The study concludes that the SCPP's power production built with a glazed roof radius of 50 m, a chimney radius of 5 m, a roof height of 2 m, and the chimney height of 50 m was highest during the summer months due to high solar radiation and temperatures, with the highest average production occurring in July at 537.87 kW, 12% greater than the least productive month of January. The SCPP's annual average power production is 6,122.3 kW, indicating high efficiency for renewable energy in these regions. The study also found that ambient temperature has a greater impact on energy production than solar radiation within a certain range. Otherwise, solar radiation has the greatest impact. The paper highlights the significance of temperature in regions such as Kufa, where the temperature can reach as high as 42.3 °C, and the impact of temperature and radiation on power production. This study provides a reliable model that can aid in designing and evaluating SCPPs in various locations.

This work focused on prescribing, designing, implementing, and evaluating a pilot project conducted in the Greek power system that addressed balancing and congestion management issues that system operators (SOs) face within the clean energy era. The considered pilot project fully focused on the development of the F-channel platform, including the idea behind this application, the steps that were taken in the process, and the outcomes of the performed activities fitting into the overall picture of the OneNet project. The specified F-channel platform is a web-based, client-server application that uses artificial intelligence (AI) techniques and cloud computation engines to improve the management of the active power for the TSO-DSO coordination. The flexibility of the grid's resources was identified, and an integrated monitoring system based on the precise forecasting of variable generation and demand was implemented. The focus areas were congestion management, frequency control, and voltage control services, for which corresponding network models were created in close cooperation with system operators. The obtained results are essential for the remaining demonstration results because they offer an incredibly accurate basis for further research into their use in congestion management and other weather-related enhanced transmission and distribution system planning and operation practices. [ABSTRACT FROM AUTHOR]

Modern information and communication technologies are being incorporated into traditional power grid systems to create the smart grid of the real world. The newly provided information flow and intrinsic creation, transport, storage, and the use of electricity are all facilitated by the energy transfer, especially as the complete deployment of the Internet of Things in the power grid, also known as the power Internet of Things (PIoT). These new 5G technologies and the value generated by novel services and market processes can all be used to maximize the value of scarce resources like energy. This paper develops a framework for a cyber-physical power system based on IoT (CPPS-IoT). Automobiles, aircraft, defense, factory equipment, wellness equipment, industrial control, connected cars, and other sectors and industries are all benefiting from the fast growth of CPS technology. A smart electric grid is created when dispersed sources of energy and electrical infrastructure are linked together to provide global exchange of information, sensible decision, including true flexible control using the CPPS. Cyber-physical systems have great benefits because they combine IoT with physical processes and mediate how humans interact with the natural environment. Cyber-physical systems use sensor networks and embedded computers to keep tabs on and manipulate the physical world around them. They include built-in feedback loops that enable the environment to trigger their communication, control, or processing. The proposed method makes systems safer and more efficient, decreasing the cost of developing and running these systems. The accuracy is 89%, and the proposed method's error rate is 48%. [ABSTRACT FROM AUTHOR]

It has been demonstrated that energy systems driven by conventional energy sources like fossil fuels are one of the main causes of climate change. Organic Rankine cycles can help to reduce that impact, as they can be operated by using the industrial waste heat of renewable energies. The present study presents a comprehensive bibliographic review of organic Rankine cycles. The study not only actualizes previous reviews that mainly focused on basic cycles operating on subcritical or supercritical conditions, but also includes the analysis of novel cycles such as two-stage and hybrid cycles and the used fluids. Recuperative and regenerative cycles are more efficient than reheated and basic single-stage cycles. The use of two-stage cycles makes it possible to achieve higher thermal efficiencies and net power outputs of up to 20% and 44%, respectively, compared with those obtained with single-stage cycles. Theoretical studies show that hybrid systems, including Brayton and organic Rankine cycles, are the most efficient; however, they require very high temperatures to operate. Most organic Rankine cycle plants produce net power outputs from 1 kW up to several tens of kW, mainly using microturbines and plate heat exchangers. [ABSTRACT FROM AUTHOR]

The power conversion of salinity gradient energy (SGE) between concentrated brine from seawater desalination and seawater by reverse electrodialysis (RED) benefits energy conservation and also dilutes the discharge concentration to relieve the damage to coastal ecosystems. However, two key performance indexes of the maximum net power density and energy conversion efficiency for a RED stack harvesting the energy usually cannot reach the optimal simultaneously. Here, an optimization study on the two indexes was implemented to improve the performance of RED in harvesting the energy. A RED model for capturing the SGE between concentrated brine and seawater was constructed, and the correlation coefficients in the model were experimentally determined. Based on the model, the effects of a single variable (concentration, flow rate, temperature, thickness of the compartment, length of the electrode) on the performance of a RED stack are analyzed. The multi-objective optimization method based on the genetic algorithm was further introduced to obtain the optimal solution set, which could achieve the larger net power density and energy conversion efficiency with coordination. The ranges of optimal feed parameters and stack size were also obtained. The optimal flow velocity of the dilute solution and the concentration of the dilute solution are approximately 7.3 mm/s and 0.4 mol/kg, respectively. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) is an adaptive system that has the ability to predict the relationship between the input and output parameters without defining the physical and operation conditions. In this study, some queries about using ANN methodology are simply clarified especially about the neurons number and their relationship with input and output parameters. In addition, two ANN models are developed using MATLAB code to predict the power production of a polycrystalline PV module in the real weather conditions of Iraq. The ANN models are then used to optimize the neurons number in the hidden layers. The capability of ANN models has been tested under the impact of several weather and operational parameters. In this regard, six variables are used as input parameters including ambient temperature, solar irradiance and wind speed (the weather conditions), and module temperature, short circuit current and open circuit voltage (the characteristics of PV module). According to the performance analysis of ANN models, the optimal neurons number is 15 neurons in single hidden layer with minimum Root Mean Squared Error (RMSE) of 2.76% and 10 neurons in double hidden layers with RMSE of 1.97%. Accordingly, it can be concluded that the double hidden layers introduce a higher accuracy than the single hidden layer. Moreover, the ANN model has proven its accuracy in predicting the current and voltage of PV module. [ABSTRACT FROM AUTHOR]

The partial evaporation organic Rankine cycle (PE-ORC) is an emerging technology for the efficient exploitation of low-temperature heat sources. The purpose of the present study is the energy and thermodynamic analysis of a solar-fed PE-ORC with a solar field of evacuated flat plate collectors coupled to a sensible storage tank. The studied PE-ORC operates with the environmentally friendly working fluid R1233zd(E) with variable evaporation percentage in the expander inlet. The thermodynamic investigation is done with a validated model in Engineering Equation Solver, and the transient analysis is performed with the TRNSYS tool by coupling it with the thermodynamic model. According to the dynamic analysis, the annual electrical yield is found at 6243 kWh, while the maximum obtained value is found at 3.81 kW. Moreover, the annual mean solar field efficiency was calculated at 45.0%, the annual mean thermodynamic cycle efficiency at 8.71% and the annual mean system efficiency at 3.68%.

This paper presents a study of the impact of icing on the performance of a pitch-regulated large wind turbine. Numerical simulations of six blade sections of the NREL 5 MW wind turbine at various free stream velocities are performed. Blade Element Momentum (BEM) method along Computational Fluid Dynamics (CFD) bases multiphase numerical simulations are used for this study. Analysis shows that the simulated parameters are in good agreement with the real conditions for each blade element during operation, except for the three-dimensional effects. The analysis of accreted ice shapes and air/droplet flow fields around the blade profile sections was carried out, and the calculation of aerodynamic performance, and energy production degradation was also performed. The tip of the blade is most affected by icing, it is characterized by the greatest changes in the aerodynamic performance. Maximum reduction in the wind turbine performance is estimated to be around 24%. [ABSTRACT FROM AUTHOR]

Climate change is one of the main problems that humanity is currently facing due to carbon dioxide emissions caused by fossil fuel consumption. Organic Rankine cycles may play an important role in reducing these emissions since they can use industrial waste heat or renewable energies. This study presents the proposal and modeling of an organic Rankine cycle integrated into a double-effect absorption cooling system for the simultaneous production of power and cooling. The working fluids utilized were the ammonia–lithium nitrate mixture for the absorption system and benzene, cyclohexane, methanol, and toluene for the organic Rankine cycle. The influence of the primary operating parameters on the system performance was analyzed and discussed in terms of cooling load, turbine power, energy utilization factor, and exergy efficiency for a wide range of operating conditions. It was found that, for all cases, the cooling load was dominant over the turbine power since the minimum cooling load obtained was above 50 kW, while the maximum turbine power was under 12.8 kW. For all the operative conditions analyzed, the highest performance parameters were obtained for benzene, achieving an energy utilization factor of 0.854 and an exergy efficiency as high as 0.3982. [ABSTRACT FROM AUTHOR]

Urban wind Energy is one of the new renewable ways of producing electricity, which researchers have not studied very much. From earlier studies, it is impossible to state if it is or is not recommended to install wind turbines in Urban Areas. Further inverstigation are required to have a more accurate answer, including wind potential, suitability and possibility of installation. On the rooftop of the Technical Faculties Laboratory of the University of Prishtina “HASAN PRISHTINA", a Horizontal Axis Wind Turbine and a Vertical Axis Wind Turbine have been installed. Both turbines are with the same capacity of 300 watts. A small meteorological station is installed among wind turbines to provide meteorological data. Results from installing these devices are presented in this research, where the turbines' power production potential is presented. The energy situation in Kosovo is presented, well as the pollution caused from the old fashion power plants. Research also includes the comparision between theoretical and real power production from each turbine separately. The wind data and power production results for both turbines are presented for two years, 2019 and 2020. The more suitable turbine is chosen by comparing the results, after which its main characteristics are shown at the end of the study.

This study explores an innovative integration of solar energy with thermal energy storage for power production and cooling system support, utilizing phase change materials (PCMs) to enhance solar system performance, particularly for the cooling demands of an office building. The cooling load of a target office building in Ardabil City, Iran, is calculated for a typical day. Optimization is conducted using Multi-Objective Particle Swarm Optimization (MOPSO) to select the optimal zeotropic mixture as the working fluid, aimed at maximizing efficiency and minimizing heat source requirements. The system is designed to meet the needs of a two-story office building. Analysis of photovoltaic modules integrated with PCM under various parameters led to the selection of 25 PVT-PCM units in a series. The total setup includes 730 modules covering 365 m2, achieving a mass flow rate of 2.92 kg/s and supporting a 40 kW cooling load in the Ejector Refrigeration Cycle (ERC). The development of this solar-powered cooling system presents a sustainable, economically viable solution for building cooling. It demonstrates significant advancements in thermal efficiency through the strategic use of PCMs and optimized zeotropic mixtures in ejector refrigeration cycles. The system's scalable design offers a model for adapting to diverse climatic conditions, marking a notable contribution to sustainable building technologies. • A novel integration of an ejector refrigeration system with a PVT-PCM system is introduced. • The best zeotropic mixture as the working fluid of the ERC system to optimize its performance, is selected. • The building hourly cooling load is calculated utilizing CLTD/CLF methods, expanded in the ASHRAE. • The proposed system supports over 70% of cooling energy needs, even in periods of low sunlight. • In a series of 25 solar systems with a mass flow rate of 0.1 kg/s, the optimum thermal energy can be achieved. [ABSTRACT FROM AUTHOR]

The paper details the development, manufacturing, and evaluation of a compact Organic Rankine Cycle (ORC) system fueled by Concentrated Solar Power (CSP). The initial selection of the starting point of the cycle is described, considering the operational conditions of the ORC (such as the properties of the ambient temperature and solar field) and operational limitations. The study outlines the construction of a radial turbine generating 3 kW of power and conducts numerical simulations of fluid flow within the turbine components such as the nozzle and wheel. The course includes system engineering, focusing on the computation and selection of critical components including pumps, exchangers, and sensors. The findings of the laboratory tests are presented in the second part. The experiment utilized a thermal oil boiler for heating. The results show an isentropic efficiency of around 42% and a cycle efficiency of 6% under the initial test conditions, indicating promising performance over a wide range of pressure drops.

The control system for a micro-hydropower plant using an Archimedes screw turbine is the focus of this work. Three control systems were implemented based on a Barreda micro-hydropower plant (Spain) currently in operation: an optimal water level control (OWLC) system, a maximum power point monitoring (MPPT) system, and a water level control (WLC) system. The comparison was made using several assessment indicators: electricity production, micro-hydropower plant efficiency, and gearbox fatigue. The electricity production is similar in the OWLC and MPPT systems (energy gain +0.5%) and significantly lower in the WLC system (energy gain −12%). The efficiency of the micro-hydro plant is similar in the OWLC and MPPT systems (average efficiency gain +0.9%) and significantly lower in the WLC system (average efficiency gain −15%). The mechanical stress on the gearbox is similar in the OWLC and WLC systems and significantly higher in the MPPT system. It can be concluded that the OWLC system performs better as concerns the three assessment indicators used, followed by the MPPT system. The WLC system is not recommended for use, due to its low electricity production and low efficiency of the micro-hydropower plant.

In a previous work, a solar chimney power plant integrated with a solid sorption cooling system for power and cold cogeneration was developed. This prior work showed that reusing the heat released from the adsorption bed enhances the system’s utilization of solar energy and increases the turbine’s output power. In the present paper, a subsequent modification to the arrangement and operation of the preceding system is introduced. The primary objective of the modification is to enhance performance and increase the plant’s capacity to effectively harness the available solar radiation. The method involves placing the condenser tubes at the solar collector entrance. Therefore, the airflow captures the condenser-released heat before it enters the collector. The modified configuration and operation of the system are discussed. A dynamic mathematical model is established to simulate the hybrid system’s operation and evaluate its parameters. The obtained results show that a 5.95% increase in output power can be achieved by recovering the heat of condensation. Furthermore, the modified system attains a 6% increase in solar-to-electricity conversion efficiency compared with the basic system. The findings suggest that the modified system, which recycles condenser heat, provides noticeable enhanced performance compared with the basic system.

Summary The progression of wind turbine technology has led to wind turbines being incredibly optimized machines often approaching their theoretical maximum production capabilities. When placed together in arrays to make wind farms, however, they are subject to wake interference that greatly reduces downstream turbines' power production, increases structural loading and maintenance, reduces their lifetimes, and ultimately increases the levelized cost of energy. Development of techniques to manage wakes and operate larger and larger arrays of turbines more efficiently is now a crucial field of research. Herein, four wake management techniques in various states of development are reviewed. These include axial induction control, wake steering, the latter two combined, and active wake control. Each of these is reviewed in terms of its control strategies and use for power maximization, load reduction, and ancillary services. By evaluating existing research, several directions for future research are suggested.

Aiming to reduce the use of conventional energy sources, alternative methods should be applied in order to cover society’s needs. In this context, in the present study, the operation of a transcritical CO2 commercial refrigeration unit is investigated, coupled with two power production cycles. The first cycle is a supercritical CO2 Brayton system that is supplied with heat by a solar field including parabolic trough collectors, while the second one is an organic Rankine cycle, utilizing as a heat source the low enthalpy CO2 exiting the first cycle. The novelty of this system is attributed to the combination an advanced transcritical CO2 refrigeration system with power production cycles that operate under the optimal conditions, as well as to the reason that the operation of the refrigeration unit is independent from the solar energy, since it can provide refrigeration output regardless of the solar heat input. The results prove that the increased number of solar collectors leads to more advantageous power production results, although with higher capital costs. Furthermore, greater energy production is noted when the ambient temperature is lower and abundant solar power is available. For the case of installing five solar collectors and an organic Rankine cycle, it is found that the annual energy production of the total system is 173.72 MWh, while the annual energy consumption of the refrigeration unit is 466.66 MWh, meaning that 37.23 % of energy savings are achieved annually. For the same configuration, according to the life cycle cost analysis, the capital cost is found equal to 243.72 k€, leading to a payback period of 7.6 years. By the end of the project’s lifetime, the operation of the installed system returns 298.42 k€ to the investor.

This paper uses networks of action situations (NAS) together with actor network theory (ANT) to identify the decisions that were made in Saskatchewan regarding power production and explore what future choices are available in the context of climate change. A theoretical and methodological contribution to NAS literature is made with focus on interconnected human and non-human objects (carbon, hydro, and uranium) or 'actants' and the development of discourses supporting or opposing their development. Actants provide the nodes of focus, while discourses explain the development of actants and their links. Identification and explanation of the emergence and recession of actants on the Saskatchewan landscape are analyzed with diagnostics of telecoupled systems, polycentric governance, and flows of faction situations. Focus group and survey data are used to identify future pathways and imaginaries of power production and the actants of carbon, hydro and uranium. Actants of carbon (coal) and hydro are possibly kept alive with carbon capture and storage and import of hydro-electricity from the distant action situation in a neighboring province (if the necessary infrastructure is built). While actants of renewables are strongly emerging, uranium currently mined on the Saskatchewan landscape is receiving strong support by government due to the possibility of small modular reactors (SMRs). This expanded theoretical conception of NAS illustrates distant action situations impact on local narratives and decision-making and dynamics of polycentric governance that are neither top down nor collaborative. [ABSTRACT FROM AUTHOR]

Hydrogen has the potential to decarbonize a variety of energy-intensive sectors, including steel production. Using the life cycle assessment (LCA) methodology, the state of the art is given for current hydrogen production with a focus on the hydrogen carbon footprint. Beside the state of the art, the outlook on different European scenarios up to the year 2040 is presented. A case study of the transformation of steel production from coal-based towards hydrogen- and electricity-based metallurgy is presented. Direct reduction plants with integrated electric arc furnaces enable steel production, which is almost exclusively based on hydrogen and electricity or rather on electricity alone, if hydrogen stems from electrolysis. Thus, an integrated steel site has a demand of 4.9 kWh of electric energy per kilogram of steel. The carbon footprint of steel considering a European sustainable development scenario concerning the electricity mix is 0.75 kg CO2eq/kg steel in 2040. From a novel perspective, a break-even analysis is given comparing the use of natural gas and hydrogen using different electricity mixes. The results concerning hydrogen production presented in this paper can also be transferred to application fields other than steel. [ABSTRACT FROM AUTHOR]

In this study, a novel marine diesel engine waste heat recovery layout is designed and thermodynamically analyzed for hydrogen production, electricity generation, water desalination, space heating, and cooling purposes. The integrated system proposed in this study utilizes waste heat from a marine diesel engine to charge an organic Rankine and an absorption refrigeration cycle. The condenser of the Organic Rankine Cycle (ORC) provides the heat for the single stage flash distillation unit (FDU) process, which uses seawater as the feedwater. A portion of the produced freshwater is used to supply the Polymer Electrolyte Membrane (PEM) electrolyzer array. This study aims to store the excess desalinated water in ballast tanks after an Ultraviolet (UV) treatment. Therefore it is expected to preclude the damage of ballast water discharge on marine fauna. The integrated system's thermodynamic analysis is performed using the Engineering Equation Solver software package. All system components are subjected to performance assessments based on their energy and exergy efficiencies. Additionally, the capacities for power generation, freshwater production, hydrogen production, and cooling are determined. A parametric study is conducted to evaluate the impacts of operating conditions on the overall system. The system's overall energy and exergy efficiencies are calculated as 25% and 13%, respectively, where the hydrogen production, power generation, and freshwater production capacities are 306.8 kg/day, 659 kW, and 0.536 kg/s, respectively. Coefficient of Performance (COP) of the absorption refrigeration cycle is calculated as 0.41. • A novel onboard multigeneration WHR system for ships is proposed. • The freshwater is stored in ballast tanks after thermal treatment to preserve marine fauna. • The effects of different parameters on the system outputs are investigated. • Over 300 kgH 2 /day production capacity is achieved for H 2 added fuel use. [ABSTRACT FROM AUTHOR]

In the present research, an integrated solar-geothermal energy system is proposed. This energy system consists of a single flash geothermal cycle, single effect absorption refrigeration cycle, heat pump cycle for drying process, solar energy saving comportment, two steam turbines for power production, cooling system for domestic usage and heating for industrial application. The aim of this system is providing cooling and heating for domestic and industrial appliances and drying food products. The energy and exergy efficiency of the system were 92% and 57%, respectively. The effect of parameters such as surrounding temperature, the temperature and the mass flow rate of geothermal tank, and the outlet water temperature of the generator of absorbtion cooling system on energy and exergy efficiency of the system were investigated. The overall energy efficiency does not change by increasing surrounding temperature from 270 K to 320 K, but overall exergy efficiency, turbine 1, and turbine 2 decrease almost 7%, 3% and 4%, respectively. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study on the power extraction of the hydrofoil by performance of the coupled oscillating heave and pitch motions. The numerical analysis is conducted by using the Reynolds Average Navier-Stokes (RANS) equations and the realizable k- ɛ turbulent model of the Star-CCM+ software. A 3D oscillating hydrofoil of NACA0015 section with aspect ratio of 7 is selected for the present analysis at two inflow velocities and three frequencies. The numerical results of lift and drag coefficients, horizontal and vertical forces coefficients, power efficiency in time domain and average value of those parameters are presented and discussed. According to the numerical results, the high efficiency of hydrofoil is found at the reduced frequency of 0.18 and the flow velocity of 1 m/s and the low efficiency is obtained at the reduction frequency of 0.06 and the flow velocity of 2 m/s. Moreover, the contour results of vorticity, streamline and pressure distribution are also presented and discussed. The computational model depicts clear vortex patterns surrounding the hydrofoil, which has a major impact on the power performance of oscillating hydrofoil.

Reverse electrodialysis (RED), an emerging membrane-based technology, harnesses salinity gradient energy for sustainable power generation. Accurate characterization of electrical parameters in RED stacks is crucial to monitoring its performance and exploring possible applications. In this study, a DC electronic load module (DCELM) is implemented in a constant current condition (CC mode) for characterization of lab scale RED process, using a RED prototype in-house designed and manufactured (RU1), at different data capture setups (DCS), on which the total number of steps for data capture (NS) and the number of measurements per step (ρ) are the parameters that were modified to study their effect on obtained electrical parameters in RED. NS of 10, 50, and 100 and ρ of 10 and 20 were used with this purpose. The accuracy of resulting current and voltage steps can be enhanced by increasing NS and ρ values, and according to obtained results, the higher accuracy of resulting output current and voltage steps, with low uncertainty of the average output steps (AOS) inside the operational region of power curve, was obtained using a DCS of NS = 100 and ρ = 20. The developed DCELM is a low-cost alternative to commercial electronic load devices, and the proposed methodology in this study represents an adaptative and optimizable CC mode characterization of RED process. The results obtained in this study suggest that data capture conditions have a direct influence of RED performance, and the accuracy of electrical parameters can be improved by optimizing the DCS parameters, according to the required specifications and the scale of RED prototypes.

This work focused on prescribing, designing, implementing, and evaluating a pilot project conducted in the Greek power system that addressed balancing and congestion management issues that system operators (SOs) face within the clean energy era. The considered pilot project fully focused on the development of the F-channel platform, including the idea behind this application, the steps that were taken in the process, and the outcomes of the performed activities fitting into the overall picture of the OneNet project. The specified F-channel platform is a web-based, client-server application that uses artificial intelligence (AI) techniques and cloud computation engines to improve the management of the active power for the TSO-DSO coordination. The flexibility of the grid’s resources was identified, and an integrated monitoring system based on the precise forecasting of variable generation and demand was implemented. The focus areas were congestion management, frequency control, and voltage control services, for which corresponding network models were created in close cooperation with system operators. The obtained results are essential for the remaining demonstration results because they offer an incredibly accurate basis for further research into their use in congestion management and other weather-related enhanced transmission and distribution system planning and operation practices.