Energy Output Research Articles

Incidence Angle Effect: Validation of New Measurement Methods for IEC 61853‐2

ABSTRACTThe incidence angle effect causes a decrease in the photogenerated current of PV modules when they are subject to incident irradiance at wide angles: Its relevance should be quantified for accurate energy yield purposes and has recently gained significance due to the rising interest in novel integrated PV applications, where vertical or nonoptimal tilt are favored (e.g., in urban structures, in agrivoltaics, and vehicles). The international standard IEC 61853‐2 presents both outdoor and indoor measurement methods: However, the indoor measurement method for commercial‐size modules is often impractical due to irradiance uniformity limitations on the volume spanned by the tested module upon rotation in most of the solar simulators available on the market. In recent years, new solutions have been proposed to overcome these limitations and allow wider adoption of this standard: However, method validations and interlaboratory comparisons have been conducted so far only on small‐area samples, and a real validation on commercial‐size modules is still missing. In this work, we aim at filling this gap, reporting the results of an interlaboratory comparison conducted within the international project team that is currently working at the new edition of IEC 61853‐2. The results show a remarkable agreement between different measurement methods, thus validating more options for the evaluation of this important effect.

On-Grid Hybrid PV/WT Renewable Energy System for Green Hydrogen Production

The term "Power-to-X" (PtX) refers to a set of techniques for converting electrical energy into another form of energy, primarily focusing on hydrogen production. Produced hydrogen can be stored, distributed, and then used directly (to regenerate electricity, generate heat, or in transportation, steel, and chemical industries) or indirectly to produce ammonia, fertilizers, methane, methanol, e-fuels, and more. Thus, PtX is a mean of storing intermittent energy and a key contributor to the energy transition and decarbonization. In this article, we examine a grid-connected green hydrogen production system. This 1 MW renewable capacity system consists of a 300 kW wind turbine, a 700 kW photovoltaic field, and a 209 kW electrolyzer. In this system, any excess energy is integrated into the grid, enhancing overall energy sustainability. Conversely, when energy output is insufficient for the electrolyzer, the deficit is sourced from the grid, ensuring continuous and reliable operation. This dynamic interaction with the grid optimizes energy usage and reinforces the stability of the system. The results show an annual hydrogen production of about 16 tons, renewable energy production of approximately 1.9 GWh/year, a 20.85% capacity factor, a shortage of about 144.5 MWh, and an energy excess of about 824 MWh.

A genetic algorithm approach for flexible power point tracking in partial shading conditions

A novel Flexible Power Point Tracking (FPPT) algorithm based on Genetic Algorithms (GAs) is presented in this study. The algorithm is designed to effectively handle fluctuating solar irradiation levels and partial shading scenarios. The main objective is to enhance power output and tracking accuracy under dynamic environmental conditions, based on extensive simulations. The results showed superior performance for power output, tracking accuracy, and convergence speed than traditional techniques. Its adaptability to changing environmental conditions renders it suitable for real-time implementation, thereby contributing to efficient power generation in PV systems. Simulations demonstrate the efficacy of the algorithm in maximizing power extraction and meeting grid-code requirements under dynamic conditions. The comparative analyses underscore the superiority of the GA-based FPPT algorithm, highlighting its potential to significantly improve power point tracking in photovoltaic systems. This shows significance of adaptive algorithms in modern PV systems, particularly for reducing the effects of partial shading on energy yield. More research is required on the refinement of the algorithm's performance for long-term reliability and scalability in larger PV installations fostering advancements in photovoltaic power point tracking toward sustainable energy systems.

Dynamic Pricing and Energy Management of Virtual Power Plant Based on Source-Charge Uncertainty

With the intermittent, random and volatile distributed renewable energy mass influx into the grid and power market, the power system will face greater challenges. As a small energy autonomous system that integrates distributed generation, energy storage and load, virtual power plant connects the power market and end users, and it is also an important subject of power market reform. Its operating efficiency directly determines the effectiveness of market reform. However, virtual power plant faces the market risk of double uncertainty of internal renewable energy output and load demand during operation, so it needs to optimize the market behavior to protect its own interests. Therefore, the paper takes virtual power plant as the research object, and discusses the dynamic pricing strategy of virtual power plant considering the double uncertainty of source and charge and real-time market linkage from the aspects of theoretical analysis, modeling construction and simulation analysis, to provide reference for decision pricing of virtual power plant and formulation of electricity market reform policy.

Migratory lifestyle carries no added overall energy cost in a partial migratory songbird.

Seasonal bird migration may provide energy benefits associated with moving to areas with less physiologically challenging climates or increased food availability, but migratory movements themselves may carry high costs. However, time-dynamic energy profiles of free-living migrants-especially small-bodied songbirds-are challenging to measure. Here we quantify energy output and thermoregulatory costs in partially migratory common blackbirds using implanted heart rate and temperature loggers paired with automated radio telemetry and energetic modelling. Our results show that blackbirds save considerable energy in preparation for migration by decreasing heart rate and body temperature 28 days before departure, potentially dwarfing the energy costs of migratory flights. Yet, in warmer wintering areas, migrants do not appear to decrease total daily energy expenditure despite a substantially reduced cost of thermoregulation. These findings indicate differential metabolic programmes across different wintering strategies despite equivalent overall energy expenditure, suggesting that the maintenance of migration is associated with differences in energy allocation rather than with total energy expenditure.

Enhanced MPPT approach for grid-integrated solar PV system: Simulation and experimental study

The global solar energy utilization has significantly risen, mostly due to the technological, economic, and environmental advantages it offers, particularly through the implementation of photovoltaic (PV) systems. The energy output of PV systems is contingent upon climate conditions. A new hybrid two-stage maximum power point tracking (MPPT) system developed to optimize power extraction and increase efficiency in PV systems. The system consists of two stages: a perturb and observe (P&O) MPPT for regulating the reference voltage in the first stage, and an enhanced model reference adaptive controller (EMRAC) for adjusting the DC-DC converter duty cycle in second stage. This system is designed primarily for 100.7 kW three-phase grid-integrated PV systems operating in environments with rapidly changing solar irradiation and temperature levels. In order to demonstrate efficacy of the suggested approach, a probabilistic evaluation is conducted across three levels of uncertain scenarios, namely ropp, step irradiance profile, and rapid changing irradiation and temperature profile. The proposed approach attained maximum power point (MPP) in 0.11 s and had an average tracking efficiency of 98.28 %. Quantitative, statistical, comparative and experimental analyses utilizing the dSPACE 1202 reveal the effectiveness of the proposed control strategy and demonstrate the superior performance over P&O, INC and ANN based on the power output, response time, power loss, efficiency, and error rates.

Enhancement of the energy and exergy analysis capabilities of the yoghurt process: a case study of the dairy industry

This study provides a comprehensive analysis of the thermal and exergy characteristics of a dairy plant that produces yoghurt. This study aims to perform a comprehensive analysis of the thermal and exergy aspects of a dairy facility that produces yoghurt. This study also seeks to improve the accuracy of the results by evaluating the reliability of the energy and production data. A comprehensive analysis of energy and exergy is utilized to enhance the yoghurt production process. Moreover, the Grassmann-Sankey diagram is employed to produce a map of energy density. The process’s energy and exergy efficiencies were assessed by taking into account the enhancements and alterations made in addition to the existing implementations. Analysis of the yoghurt production process revealed that the total energy input was 113.9 [kW], the total energy output was 72.05 kW as well and the energy efficiency was 63.3%. The exergy input and output for the yoghurt production process were calculated to be 48.95 [kW] and 29.77 [kW], and the exergy efficiency was determined to be 60.8%. This study is expected to promote the growth of livestock and agriculture in the energy sector, and is forecasted to act as a catalyst for future research. This study, which is the first of its kind in the region and is expected to stimulate further research, reveals that improving energy efficiency and conservation in the production of yoghurt products enhances the factory’s overall energy efficiency.

Outdoor Performance Analysis of Semitransparent Photovoltaic Windows with Bifacial Cells and Integrated Blinds

The stricter requirements for the energy performance of buildings are creating a market for several building‐integrated photovoltaic (BIPV) technologies, including photovoltaic (PV) windows. Herein, an innovative multifunctional PV window concept designed to enhance energy generation while providing overheating protection for better indoor thermal and visual comfort is presented. This concept utilizes bifacial c‐Si solar cell strips combined with venetian blinds, all embedded in a unique insulating glazing unit. The bifacial technology increases the energy yield by using the blinds as reflectors, directing more irradiance to the cells’ rear side. The goal of this study is to analyze the outdoor performance of this concept under real operating conditions. Twelve demonstrators are installed and monitored. Various measurement campaigns are conducted, examining the impact of different blind types, tilt angles, sun positions and sky conditions. The highest energy boosts occur when the blinds are fully closed at a 75° angle with their convex side facing outward. Blinds with the highest specular reflectance achieve a maximum performance increase of 25% on sunny days and a daily average increase of 12% compared to the case of no blinds.

Rooftop PV Potential Determined by Backward Ray Tracing: A Case Study for the German Regions of Berlin, Cologne, and Hanover

ABSTRACTPhotovoltaics (PV) on building rooftops is a major contributor to the decarbonization of energy systems. We simulate the PV energy yield potential for 2.5 million individual roofs in three German regions. We cumulate the results for each single roof to calculate the cost‐potential curves for the three cities Berlin, Cologne, and Hanover. These curves give the amount of electricity that can be generated at less than a given cost per kWh. We find that these curves have the shape of a hockey stick. Neglecting the dependence of PV investment on building size and thus on the system sizes causes largely different cost‐potential curves that differ by 11%–18% for flat roofs due to their heterogeneous building size distribution. The cost‐potential curves of the three cities are very similar when appropriately normalized, for example, by the local solar irradiation and the settlement area of the city, despite substantial variations in population density. This allows for an extrapolation of our results. For Germany, we reveal an upper limit for the total electricity generation from rooftop PV of 762 TWh/a with cost as low as 6.9 ct/kWh without accounting for area losses due to chimneys, air conditioning systems, and so forth. We estimate the actual potential to be at least half of that figure.

Optimizing biomass energy production in the southern region of Iran: A deterministic MCDM and machine learning approach in GIS

This study employs a deterministic approach, distinguishing itself from other renewable energy evaluations, to assess the potential of electrical energy derived from biomass sources in the southern region of Iran. The primary objectives include pinpointing optimal locations for maximal biomass production and subsequent energy generation within distinct climates and topographies, using fuzzy- Analytic Hierarchy Process (AHP). Additionally, Principal Component Analysis (PCA) identify key factors influencing biomass and energy production. The study quantifies electrical and thermal energy derived from biomass sources across various climates. The findings indicate that regions with lower altitudes and humid climates (1530 km2) demonstrate superior biomass performance, leading to increased electrical and thermal energy production. The feature selection process highlights the significant impact of climate and soil characteristics on biomass production and energy output. Analysis of biomass energy production reveals maximum electrical energy production ranging from 674.88 kWh/ha to 711.36 kWh/ha. The results of the Long Short-Term Memory (LSTM) method confirm its high accuracy in estimating electrical energy, with a significant correlation coefficient of 0.98. We conclude that by identifying locations with the best biomass sources based on climate, it is possible to increase the derived electrical energy. These insights are critical for informing energy policies aimed at optimizing biomass energy production and its integration into sustainable power grids.

Feasibility study of floating solar photovoltaic systems using techno-economic assessment and multi-criteria decision-making method: A case study of Bangladesh

Many developing countries with abundant solar resources and rich history of agriculture, face overpopulation and land shortage issues. Floating solar photovoltaics (FSPVs) do not compete with agriculture for land and offer higher energy potential than land-based photovoltaics (LBPVs). For feasibility and site suitability evaluation of FSPVs, this study proposes an integrated approach of techno-economic assessment (TEA) and multi-criteria decision making (MCDM), based on a case study of Bangladesh. The system advisor model (SAM) was used to conduct TEA, evaluating the potential of nine FSPV sites on a regional scale using ten criteria. Combined compromise solution (CoCoSo) was implemented to determine the optimum site. Bergobindopur lake was ranked top, with the highest energy yield and lowest cost of energy of 1564 kWh/kW and $0.055/kWh respectively. Case study of Bergobindopur revealed buy-all-sell-all electricity tariff was more profitable than net billing and net metering. Energy generation was found to be influenced by tilt angle and soiling. Sensitivity analyses demonstrated the superiority of FSPVs over LBPVs for varying electricity prices, degradation and discount rates, project durations, and investor's equities. Longer project durations and lower equities resulted in higher profits for investors. The proposed approach contributes to the expansion of FSPV in land-constrained areas.

Numerical Study on the Lateral Load Response of Offshore Monopile Foundations in Clay: Effect of Slenderness Ratio

To meet growing energy demands, offshore wind turbines (OWTs) with higher energy outputs are being developed, presenting increased challenges for their foundation design. Over the past decade, extensive research on the design optimization of OWT support structures has significantly reduced the anticipated costs of offshore wind farm development. Various design methods have been developed and applied in practice, each with its own advantages and limitations. In this study, 3D finite element (FE) modeling, validated against the measured response of a large-scale test monopile, is used to investigate the lateral load response of monopiles with different geometries and slenderness ratios in smaall and large displacements. The results are compared to the standard p–y method, and specific behavioral and design aspects of large-diameter monopiles, such as the moment contribution ratio from different resisting components and the minimum embedment length criteria, are evaluated and discussed. The results showed that the maximum and minimum differences between the 3D FE modeling and one-dimensional (1D) DNV p–y method are 41% and 11% for large displacements, and 32.5% and 13.3% for small displacements, respectively. As the slenderness ratio increases, the discrepancy between the finite element (FE) modeling results and the 1D DNV p–y method decreases, with an average difference of about 13% across all monopile diameters at an L/D ratio of 10, in both small and large displacements, indicating the reasonable accuracy of the 1D method for slenderness ratios of 10 and above. Among the three minimum embedment length criteria examined, the DNV recommended and vertical-tangent criteria offered shorter embedment lengths. The primary resisting moment across all slenderness ratios comes from the distributed lateral load along the monopile shaft (MCRp−y), which increases as the L/D ratio increases.

Pitching Stabilization Control for Super Large Ships Based on Double Nonlinear Positive Feedback under Rough Sea Conditions

Due to the rapid development of a global navigation satellite system and the rapid growth of ships, the traditional control algorithms are not suitable; hence, the longitudinal rocking phenomenon generated by external disturbances is more serious when a ship is sailing. This paper takes a mathematical model of the super large oil tanker “KVLCC2”’s longitudinal motion as the controlled plant, establishing a multi-input multi-output instability control system, using the root trajectory shaping method and a weighting matrix to ensure the stability of its transfer function’s mathematical model. An improved closed-loop gain-shaping algorithm is utilized to design a simple robust controller. And a dual nonlinear positive feedback control algorithm is added to the control system to further improve the controller’s pitching stabilization performance and reduce the controller’s output energy. In order to verify that the controller has a consistently strong robustness, simulation experiments are carried out by adding a level 6, 7 and 8 wind wave model and a perturbation link to the control system, respectively. The results show that when the value of the hysteresis constant is taken as 0.25, the output values of the heave displacement and the pitch angle are greatly reduced, and the longitudinal rocking phenomenon is significantly improved. The dual nonlinear positive feedback control algorithm enhances the ship’s pitching stabilization control capability and further reduces the controller’s output energy, which provides technical support for the smooth and efficient sailing of super large ships under changing sea conditions. Combined with a global navigation satellite system, this algorithm provides a new method for pitching stabilization control of super large ships.

Research on Optimal Scheduling Strategy of Differentiated Resource Microgrid with Carbon Trading Mechanism Considering Uncertainty of Wind Power and Photovoltaic

Accelerating the green transformation of the power system is the inevitable path of the energy revolution; the increasing installed capacity of new energy and the penetration rate of electricity, uncertainty regarding new energy output, and the rising proportion of distributed power supply access have led to the threat against the safe and stable operation of the current power system. With the increasing uncertainty on both sides of power supply and demand, the microgrid (MG) is needed to effectually aggregate, coordinate, and optimize resources, such as adjustable resources, distributed power supply, and distributed energy storage in a certain area on the demand side. Therefore, in this paper, the uncertainty of wind power and PV is first dealt with by Latin hypercube sampling (LHS). Secondly, differentiated resources in the MG region can be divided into adjustable resources, distributed power supply, and energy storage. Adjustable resources are classified according to demand response characteristics. At the same time, the MG operating cost and carbon trading mechanism (CTM) are comprehensively considered. Finally, a low-carbon economy optimal scheduling strategy with the lowest total cost as the optimization goal is formed. Then, in order to verify the effectiveness of the proposed algorithm, three different scenarios are established for comparison. The total operating cost of the proposed algorithm is reduced by about 30%, and the total amount of carbon trading in 24 h can reach nearly 600 kg, bringing economic and social benefits to the MG.

Strategic implementation of variable-thickness insulation layers for stratospheric airships

Excessive heat transfer from photovoltaic systems to airship hulls poses a threat to flight safety. To address this issue, a theoretical model was developed that combines thermal, heat transfer, and optimization models for airships with variable-thickness insulation layers. The study investigates the daily thermal behavior of stratospheric airships, focusing on the effects of thermal conductivity and insulation thickness. To balance weight reduction with insulation effectiveness, temperature constraints were used, and insulation thickness was optimized across different sections of the airship using a simulated annealing algorithm (SAA). Results indicate that adjusting thermal conductivity and insulation thickness can mitigate overheating and overpressure, albeit with a reduced solar energy output. Notably, variable-thickness insulation achieved a 9.7 % weight reduction at 40°N latitude, enhancing both photovoltaic system design and insulation material selection for stratospheric airships.

Evaluating solar ramp rate correlations by simple radiation and wind measurements

The stability of photovoltaic (PV) energy output is critical to power supply and is a crucial factor for the reliability of power supply systems but is significantly influenced by the unpredictable shading caused by clouds. Assessing the variability of solar radiation across a spatially dispersed PV fleet can be challenging, as it is usually lower than that taken by routine measurements at a singular, localized point. This study refines the previously developed spatial radiation variability model by depicting the attenuation mode of solar irradiance correlation across spatial distances and considering the differences in the along-wind and cross-wind directions under various weather and solar radiation conditions. These modes are further connected to the variables that properly depict the weather conditions and are straightforward to measure. The data being adopted in developing and validating the model are collected from 17 pyranometers over a 0.56 km2 area for about half a year with a 1-s resolution. The model's performance, with a percentage root-mean-square error that surpasses isotropic models by 2.42 %–10.6 % for solar ramp intervals ranging from 5 to 240 s, underscores its accuracy and potential for optimizing the integration of PV fleets into power grids.

A novel solar-driven thermogalvanic cell with integrated heat storage capabilities

Low-grade heat sources like solar thermal radiation offer a vast energy resource. However, their low utilization rate limits energy recovery and conversion efficiency. Solar thermogalvanic cells, utilizing solar thermal radiation as a heat source, are considered an effective way to harness solar energy. However, their widespread application is hindered by performance instability due to periodic solar radiation fluctuations. This study developed composite electrodes with high conductivity, excellent photothermal properties, and heat storage capabilities, and applied them in thermogalvanic cells. Compared to traditional thermal chemical cells, the new heat storage electrode materials significantly enhance the stability and energy output efficiency. The results show that under temperature fluctuations, the new thermal chemical cells (EG/SA/LA-TGCs) significantly improve power output stability. The temperature difference increased from 6 °C to 17 °C, with the open-circuit voltage rising to 32 mV. Thanks to the electrodes’ heat storage and release capability, the heat released by the electrodes sustains the cell’s power generation. The discharge duration per unit volume of the electrode reached 12.74 min/cm3, 15 times longer than traditional thermal chemical cells.

Deep learning analysis of green ammonia synthesis: Evaluating techno-economic feasibility for sustainable production

This research presents a comprehensive optimization of green ammonia synthesis in Morocco by leveraging advanced deep learning techniques to maximize the utilization of the country's abundant renewable energy resources. By employing deep learning models such as LSTM and LSTM_adv, we forecast ammonia production over the next decade, improving strategies for production and energy storage. Our findings confirmed the viability of sustainable ammonia production in Dakhla and highlighted its transformative potential for global sustainability goals. Under the optimal scenario of 20 % photovoltaic and 80 % wind energy, the production cost was US$575 per tNH3, delivering an energy output of 8916.64 GWh and a daily ammonia production of 2503.36 tNH3. Shifting to 100 % wind energy further enhances the potential, increasing daily ammonia production to a maximum of 3090 tNH3 while reducing the production cost to US$376 per tNH3. These results demonstrate the significant economic and environmental benefits of using renewable energy sources for ammonia production in Morocco. By leveraging a country's abundant wind and solar resources, we can contribute to a sustainable and energy-independent future.

Study on recovery and utilization of cold energy for insulation design of liquid hydrogen tanks

Insulation design is one of the key technologies for Liquid Hydrogen (LH2) tanks. To enhance the insulation efficiency and energy utilization of the LH2, this study proposes a novel approach to enhance the insulation performance of LH2 tank and cold energy cascade utilization of LH2. Three Cryo-cooling Insulation Systems (CIS) with various insulation schemes are designed, analyzed and compared from the perspectives of insulation performance, consumption and energy utilization efficiency. An optimal insulation scheme among three CISs is identified and evaluated. Additionally, a dimensionless number (Ψ) is proposed to assess the insulation advantages of the CISs. And the insulation performance and economic feasibility of the system be effectively balanced. The findings reveal that the insulation performance of the proposed CIS outperforms previous insulation methods by a factor of 239.13. Among the schemes in three CISs, Schemes 2 (Position of CSs at 6th, 25th and 35th layers), Schemes 3 (Position of CSs at 10th, 40th and 45th layers), and Schemes 3 (Position of CSs at 3rd, 40th and 45th layers) exhibit superior insulation performance in Cases #1 (CIS of LN2-LAr), Cases #2 (CIS of R14-R170), and Cases #3 (CIS of R1150-R23). Notably, Case #1 achieves the highest insulation performance, showing improvements of 2.58 and 1.63 times over Case #2 and Case #3, respectively. However, the energy output in Case #1 is approximately 248.12 W, constituting 83.10 % and 71.60 % of Case #2 and Case #3, respectively. Case #1 demonstrates the highest specific energy output, with improvements of 30.12 % and 81.05 % compared to Case #2 and Case #3, respectively. In terms of the exergy utilization rate of each equipment, the exergy utilization rate of equipment in Case #1 is the highest among the three cases. The study underscore the feasibility of cold energy utilization for insulation, providing solutions for energy conversion and thermal management of LH2 tanks through cryo-cooling cascade utilization.

Dose rate dependent genotoxic and metabolic effects predict onset of impaired development and mortality in Atlantic salmon (S. salar) embryos exposed to chronic gamma radiation

Release of radionuclides to the environment from either nuclear weapon and fuel cycles or from naturally occurring radionuclides (NORM) may cause long term contamination of aquatic ecosystems and chronic exposure of living organisms to ionizing radiation, which in turn could lead to adverse effects compromising the sustainability of populations. To address the effects of chronic ionizing radiation on the development of fish, Atlantic salmon embryos were exposed from fertilization until hatching (88 days, 550 day-degree) to dose rates from 1 to 30 mGy·h−1 gamma radiation (60Co). The lowest adopted dose rate was similar to the highest doses measured in some water bodies right after the Chernobyl accident (1 mGy·h−1), however, well above current environmentally realistic scenarios (20 μGy·h−1), or the threshold assumed for significant effects on fish population (40 μGy·h−1). Dose dependent effects were observed on survival, hatching, morbidity, DNA damage, antioxidant defenses, and metabolic status. Histopathological analysis showed dose rate dependent impairment of eye and brain tissues development and establishment of epidermal mucus cell layers accompanied by increased DNA damage at doses ≥1.3 Gy (dose rates ≥1 mGy·h−1).At ≥32.8 Gy (dose rates ≥20 mGy·h−1) deformities and developmental growth defects resulted in respective 46 and 95 % pre-hatch mortality. The 10 mGy·h−1 exposure (≥ 12 Gy total dose) caused significantly increased DNA damage, impaired eye development, and both premature and delayed hatching, while no deformities or effect on survival were observed. We observed a dose rate dependent reduction from dose rate ≥ 20 mGy·h−1 (≥ 27 Gy total dose) on antioxidant SOD, catalase and glutathione reductase enzyme activities. The reduction of antioxidant enzyme activities was in line with observed developmental delay and disturbance to time of hatching. Metabolomic profiles showed a clear shift at dose rates ≥10 mGy·h−1 (≥ 12 Gy total dose) in pathways related to oxidative stress, detoxification, DNA damage and repair. Due to gamma radiation exposure, a switch of central metabolism from glycolysis, citric acid cycle and lactate production towards pentose phosphate pathway indicated a rewiring mechanism for increased production of reductive equivalents to maintain redox homeostasis at the expense of energy output and thus embryonic development.