System Performance Research Articles

Realizing rapid cooling and latent heat recovery in the thermoelectric-based battery thermal management system at high temperatures

To realize rapid cooling of the battery at high temperatures and effective latent heat recovery from phase change materials (PCMs), a thermoelectric-based battery thermal management system (BTMS) is proposed. Additionally, a transient multiphysics numerical model is developed to predict the system's thermal performance, and the concept of the latent heat recovery rate of PCMs is introduced. Results show that the introduction of thermoelectric coolers (TECs) significantly enhances the system's efficiency in cooling the battery at high temperatures (Stage 1) and recovering PCM latent heat (Stage 2). The overall thermal performance can be further improved by utilizing PCMs with a higher mass fraction of expanded graphite (EG) or increasing the TEC input current. Moreover, after the end of Stage 2, the power supply for TECs is interrupted, and the system enters Stage 3, which only relies on PCMs to control the battery temperature. The duration of Stage 3 increases with the EG mass fraction, achieving a peak of 3830 s at an EG mass fraction of 12%. Considering the thermal performance and power consumption of the system, the optimal solution is determined as an EG mass fraction of 12% and a TEC input current of 4 A. In this situation, the required time for Stage 1 and Stage 2 is 170 s and 620 s, with the latent heat recovery rate of PCMs up to 361.94 J/kg/s. The findings will provide new insights for the development of the thermoelectric-based BTMS.

Real-time diagnosis and monitoring of biofilm and corrosion layer formation on different water pipe materials using non-invasive imaging methods

Water distribution networks play a crucial role in ensuring a reliable water supply, yet they encounter challenges such as corrosion, scale formation, and biofilm growth due to interactions with environmental elements. Biofilms and corrosion layers are significant contaminants in water pipes, formed by complex interactions with pipe materials. As the structure of these contamination layers varies depending on the pipe material, it is essential to investigate the contamination layer for each material individually. Specifically, biofilm growth is typically investigated concerning organic sources, while the growth of humus layers is examined in relation to inorganic elements such as manganese (Mn), iron (Fe), and aluminum (Al), which are major elements and organic substances found in water pipes. Real-time imaging of recently contaminated layers can provide important insights to improve system performance by optimizing operations and cleaning processes. In this study, cast iron (7.10 ± 0.78 nm) exhibits greater surface roughness compared to PVC (5.60 ± 0.14 nm) and provides favorable conditions for biofilm formation due to its positive charge. Over a period of 425 h, the fouling layer on cast iron and PVC surfaces gradually increased in fouling thickness, porosity, roughness, and density, reaching maximum value of 29.72 ± 3.6 μm, 11.44 ± 1.1%, 41673 ± 1025.6 pixels, and 0.80 ± 0.3 fouling layer pixel/layer pixel for cast iron, and 8.15 ± 0.4 μm, 20.64 ± 0.9%, 35916.6 ± 755.7 pixels, and 0.58 ± 0.1 fouling layer pixel/layer pixel, respectively. Within the scope of the current research, CNN model demonstrates high correlation coefficients (0.98 and 0.91) in predicting biofilm thickness for cast iron and PVC. The model also presented high accuracy in predicting porosity for both materials (over 0.91 for cast iron and 0.96 for PVC). While the model accurately predicted biofilm roughness and density for cast iron (correlation coefficients 0.98 and 0.94, respectively), it had lower accuracy for PVC (correlation coefficients 0.92 for both parameters).

Experimental and simulation study on the performance of a solar assisted multi-source heat pump drying system in Zhengzhou area

Zhengzhou of Henan province is an important agricultural production base. To improve the performance of the combined drying system and promote the development of agricultural products in Zhengzhou area, a solar assisted multi-source heat pump (SMSHP) drying system was proposed based on a traditional solar assisted air source heat pump (SASHP) drying system. The simulation models were developed for the air source heat pump (ASHP), SASHP, and SMSHP drying system respectively. The coefficient of performance, energy consumption and specific moisture extraction rate of the drying systems under different seasons were analyzed. Moreover, to validate the simulation models, an experimental platform of the combined drying system was designed and set up, and the experimental tests were carried out on the ASHP, SASHP, and SMSHP drying system. The simulation results revealed that the SMSHP drying system had lower energy consumption, higher coefficient of performance and specific moisture extraction rate than that of the SASHP drying system. The most significant performance enhancement was observed in spring, where the SMSHP system demonstrated a 22.69 % increase in coefficient of performance, a 19.2 % increase in specific moisture extraction rate, and a 16.11 % decrease in energy consumption compared to the SASHP drying system. Comparing with the experimental data, the simulation model errors of the energy consumption, coefficient of performance, and specific moisture extraction rate of the SMSHP drying system were 3.19 %, 0.28 %, and 2.27 %, respectively. Therefore, the accuracy of the simulation results was confirmed. To better calculate the heat provided by the solar collection system, the concept of the tank heating guarantee rate was first introduced, and it was found to be more scientific than the solar energy guarantee rate. At last, The economic and environmental benefit of the drying systems were analyzed during the life cycle, and the SMSHP drying system exhibited better comprehensive performance than the SASHP drying system. This paper provides valuable insights into the comprehensive utilization of solar energy and the control logic of solar assisted air source heat pump combined drying system under different seasons.

Study on the application and performance of liquid crystal emulsion system in sunscreen products

ABSTRACT Liquid crystal (LC) emulsion is a new emulsion system which has excellent application potential in the field of cosmetics. In this study, the LC emulsifier and traditional emulsifier were used to prepare the emulsions containing different types of sunscreen agents, respectively. The microstructure, sunscreen performance and rheological properties of the emulsions were studied systematically. The results showed that the formation of LC structure was not affected by sunscreen agents. LC structure can also enhance the sunscreen property of the emulsion as well as improve the sensory property. Further, we combined different sunscreen agents to prepare LC sunscreen emulsion. The sunscreen performance and repair effectiveness of emulsion were evaluated by human test. The results showed that LC sunscreen emulsion has an increased SPF value from 56 to 70 compared to non-LC sunscreen emulsion. Meanwhile, the LC structure also enhanced the moisturising properties of the emulsion, and the TEWL value of LC emulsion and non-LC emulsion was 67.4% and 96.5%, respectively. In addition, LC sunscreen emulsion has higher safety and better storage stability. In conclusion, this study provided the practical application of LC emulsion systems as well as the important guidance for developing excellent sunscreen emulsions.

Competency Standardization for Indonesian Tourism Human Resources: Implementation in Education, Training and Competency Certification

The increasing trend of Indonesia's tourism competitiveness has placed it as one of the priority industrial sectors in Indonesia. However, this achievement is not in line with increasing the competitiveness of human resources (HR). The national work competency standardization system (SKKN), which the Indonesian Government has implemented since 2012, has not been effective, and human resources' competitiveness has even shown a negative trend. It is feared that this situation will hamper the growth rate of Indonesia's tourism competitiveness in the future. The purpose of this study is to critically analyze the application of the SKKNI system, which is focused on education, training, and competency certification of Indonesian tourism human resources, to uncover the inhibiting factors for its implementation. This education, training, and competency certification are the main components in the performance of the SKKNI system in Indonesia. The research was carried out by reviewing the relevant literature, analyzing the processes and elements in applying the SKKNI system. Research data is secondary data collected from data sources of Government and non-government institutions and scientific and non-scientific literature available on official government websites and the internet. The research results are then triangulated to get a comprehensive picture and understanding of the application of the SKKNI system. The results showed that the implementation of the SKKN system was effective in increasing the capacity of Indonesian tourism human resources but has a tiny growth Quantitatively. The main obstacle is limited trainer, assessor, facilities, and educational, training, and certification institutions to produce trained and certified human resources of tourism.

Membrane hybrid system assembled with MXene@h-BN for efficient typical pharmaceuticals removal and self-cleaning: Synergetic effect on adsorption-photocatalytic process

Membrane filtration is regarded as one of the promising technologies for water treatment. However, insufficient micropollutants removal and membrane fouling still limited the further application. Herein, this study engineered a novel membrane hybrid system integrating typical pharmaceuticals removal and membrane self-cleaning by assembled layered MXene and hexagonal boron nitride (h-BN). By doping a small amount of MXene into h-BN (mass ratio of 1 to 10), the synergetic process of adsorption and photocatalytic degradation were achieved. Based on experimental and density functional theory (DFT) calculation results, the chemisorption-photodegradation performance of the membrane hybrid system assembled with 1/10 MXene@h-BN was significantly enhanced due to the termination group and conductive property of MXene. In addition, trimethoprim (TMP) degradation by the above membrane followed the Langmuir–Hinshelwood model, indicating pollutants removal initiated not only on the membrane surface but also in the bulk solution under simulated solar irradiation. This phenomenon was attributed to the generation of •OH and 1O2 by forming Ohmic contact with altered internal band structure. The durability and practical experiments with secondary effluent from local wastewater treatment were also tested. The exceptional self-cleaning performance of the membrane hybrid system assembled with 1/10 MXene@h-BN was demonstrated by lower membrane fouling and maintaining durability even after five cycles. Furthermore, the performance (both pollutants removal and flux) of the modified membrane for secondary effluent treatment was also considerable, validating its potential for practical application. Owing to the excellent features, the membrane assembled with MXene@h-BN is anticipated to be an ideal candidate for advanced wastewater treatment.

Development and comprehensive thermo-economic analysis of a novel compressed CO2 energy storage system integrated with high-temperature thermal energy storage

This study introduces an innovative compressed CO2 energy storage (CCES) system poised to significantly enhance the management of fluctuating renewable energy sources. Unlike traditional system layouts, a high-temperature thermal energy storage (HTES), an ejector cycle and a flash process are adopted in the system and innovatively integrated into its charging and discharging process. These above methods aim to reduce geographic limitations and improve round-trip efficiency. Thermodynamic and economic models are established to conduct a comprehensive evaluation, engaging in detailed parameter analysis followed by multi-objective optimization. The analysis indicates that increasing turbine inlet pressure and temperature significantly improves system performance. While increasing flash pressure and the temperature of low-pressure storage benefit round-trip efficiency (RTE) and levelized cost of electricity (LCOE), it negatively impacts the energy storage density (ESD). Additionally, setting the ejector back pressure at approximately 7.5 MPa optimizes performance. Multi-objective analysis indicates that the optimal low-pressure storage temperature is approximately 295.07 K, with the associated flash pressure and ejector back pressure set at 3.94 MPa and 7.48 MPa, respectively. Under these conditions, the proposed system achieves the optimal RTE, ESD and LCOE of 50.43 %, 16.60 kWh/m³, and 0.0992 $/kWh, respectively. Compared to other similar systems, the proposed system exhibits preferable balance performance.

The Role of Risk Factors in System Performance: A Comprehensive Study with Adaptive Progressive Type-II Censoring

The quality performance of many vital systems depends on how long the units are performing; hence, research works started focusing on increasing the reliability of systems while taking into consideration that many factors may cause the failures of operating systems. In this study, the combination of a parametric generalized linear failure rate distribution model and an adaptive progressive Type-II censoring scheme for practical purposes is explored. A comprehensive investigation is performed on the risk factors that cause failure and determines which of the factors has a more harmful effect on the units. A lifetime experiment is performed under the condition of an adaptive progressive Type-II censoring scheme to obtain observations as a result of the competing factors of failures. The obtained observations are assumed to follow a three-parameter generalized linear failure rate distribution and are assumed to be competing to cause failure. Two statistical inference methods are employed for estimating this model’s parameters: the frequentist maximum likelihood method and the Bayesian approach. Our model’s validity is demonstrated through extensive simulations and real data applications in the medical and electrical engineering fields.

Chip-Level Defect Analysis with Virtual Bad Wafers Based on Huge Big Data Handling for Semiconductor Production

Semiconductors continue to shrink in die size because of benefits like cost savings, lower power consumption, and improved performance. However, this reduction leads to more defects due to increased inter-cell interference. Among the various defect types, customer-found defects are the most costly. Thus, finding the root cause of customer-found defects has become crucial to the quality of semiconductors. Traditional methods involve analyzing the pathways of many low-yield wafers. Yet, because of the extremely limited number of customer-found defects, obtaining significant results is difficult. After the products are provided to customers, they undergo rigorous testing and selection, leading to a very low defect rate. However, since the timing of defect occurrence varies depending on the environment in which the product is used, the quantity of defective samples is often quite small. Unfortunately, with such a low number of samples, typically 10 or fewer, it becomes impossible to investigate the root cause of wafer-level defects using conventional methods. This paper introduces a novel approach to finding the root cause of these rare defective chips for the first time in the semiconductor industry. Defective wafers are identified using rare customer-found chips and chip-level EDS (Electrical Die Sorting) data, and these newly identified defective wafers are termed vBADs (virtual bad wafers). The performance of root cause analysis is dramatically improved with vBADs. However, the chip-level analysis presented here demands substantial computing power. Therefore, MPP (Massive Parallel Processing) architecture is implemented and optimized to handle large volumes of chip-level data within a large architecture infrastructure that can manage big data. This allows for a chip-level defect analysis system that can recommend the relevant EDS test and identify the root cause in real time even with a single defective chip. The experimental results demonstrate that the proposed root cause search can reveal the hidden cause of a single defective chip by amplifying it with 90 vBADs, and system performance improves by a factor of 61.

Selection of antioxidants for capacitor grade polypropylene film: Insights into electrical performance of the oil-film system.

High voltage power capacitors employ the oil-impregnated polypropylene film as the insulation. The swelling phenomenon might drive the antioxidants and small molecules within the film to migrate into the oil. It is necessary to comprehensively investigate the physical migration mechanism of antioxidants and their impact on the electrical performance of the oil-film combination insulation system and, consequently, formulate the proper selective prescription of antioxidants. Theoretical elucidation of the competitive interaction mechanism between the film and the oil in attracting antioxidant molecules was achieved through the calculation of inter-molecular binding energy, and the migration coefficient ηm was introduced to quantify the migration characteristics of antioxidants. Experimentally, the effects of antioxidants on the space charge distribution of the film, the dielectric properties of the oil, and the breakdown characteristics of both the film and oil were investigated. The experimental conclusions are consistent with theoretical analysis. The lamellar structure antioxidant molecules with ηm > 1 tend to migrate from the film to the oil, which results in increased dielectric loss and decreased breakdown strength of the insulating oil. In addition, the presence of phosphorus atoms in phosphite antioxidants contributes to a reduction in the breakdown strength of the film. For capacitor grade polypropylene film, in addition to the synergistic effect between different types of antioxidants on the thermo-oxidative stability, the structure of the antioxidant molecules and its influence on the electrical performance of the oil-film systems should also be taken into account.

Machine Learning-Based Social Media Review Analysis for Recommending Tourist Spots

In recent years, the tourism industry has witnessed significant growth, resulting in an increased demand for effective and personalized tourist place recommendation systems. In this study, a tourist spot recommendation system is proposed which is built by developing a machine learning model based on a Support Vector Machine (SVM), Decision Tree (DT), and k-Nearest Neighbors(k-NN). Public experiences and opinions regarding the various spots available in popular social media sites such as TripAdvisor, Google, Instagram, and TikTok are utilized to train the model. The system matches the probability of the user query with the predicted probability of reviews for a particular spot. The SVM algorithm, known for its robustness in handling high-dimensional data, is adapted to model the complex relationships between users' reviews, spots, and their attributes. Real-world data is used to evaluate the system's performance, demonstrating its ability to significantly improve the user experience and contribute to the sustainable growth of the tourism sector. The system's capability was demonstrated as it achieved a notable F1-Score of 0.78 when SVM was implemented. Additionally, a promising accuracy rate of 93.023% was observed when random queries were used for tourism spot prediction, emphasizing that SVM outperformed DT and k-NN.

High-Capacity Coherent WDM Networks Empowered by Probabilistic Shaping and End-to-End Deep Learning

To optimize the functionality of coherent optical fiber communication (OFC) systems and enhance their capacity related to long-haul transmissions, wavelength-division multiplexing (WDM) and probabilistic constellation shaping (PCS) techniques have been used. This paper develops an end-to-end (E2E) deep learning (DL)-based PCS algorithm, i.e., autoencoder (AE) for a high-order modulation format WDM system that minimizes nonlinear effects while ensuring high capacity and considers system parameters, in particular those related to the OFC channel. Only the AE of the central channel is trained to meet the specified performance objective, as the system design employs identical AEs in each WDM channel. The simulation results show that the architecture should consist of two hidden layers, with thirty two nodes per hidden layer and a ”32×modulation order” batch size to obtain optimal system performance, when designing AE using a dense layer neural network. The behavior of the AE is examined to determine the optimum launch-power ranges that enhance the system's performance. The developed AE-based PCS-WDM provides a 0.4 shaping gain and outperforms conventional solutions.

Error performance and capacity of subcarrier BPSK modulated THz wireless systems with pointing errors

Terahertz (THz) technology is poised to play a pivotal role in the future sixth-generation (6 G) wireless systems, offering substantial benefits with its extremely high bandwidth and rapid transmission speeds. This paper explores subcarrier-modulated THz wireless systems, analyzing their performance under the log-normal and gamma-gamma models. It provides a detailed examination of how composite turbulence and pointing errors impact the system performance. Closed-form solutions for the bit error rate and outage probability are derived for various conditions of turbulence and pointing errors. Furthermore, the paper delves into the asymptotic error performance, presenting numerical results that confirm the accuracy of the derived solutions across different propagation distances, turbulence strengths, and pointing error scenarios. The study offers critical insights into how different conditions affect the system performance, which is essential for characterizing subcarrier THz links in forthcoming 6 G deployments.

Integrating diffusion dialysis for sustainable acid recovery from ion exchange regeneration stages: Characterization of metal and non-metal ions migration

Seawater mining presents a potential option for recovering the European Union’s Critical Raw Materials (CRMs), but direct extraction from seawater is challenging due to their low concentrations, as most of them are Trace Elements (TEs) (at levels of mg/L or µg/L). Saltworks bitterns (ultraconcentrated brines resulting from the sea salt production process) offer an alternative solution, naturally concentrated up to 40 times more than seawater. These bitterns can be further processed with chelating Ion Exchange (IX) sorbents to selectively extract TEs. However, this process requires an acidic elution stage with strong acids, followed by neutralization, to recover TEs through precipitation, demanding extensive chemicals consumption. Diffusion Dialysis (DD) could be used to recover the excess acid without external reagents, using an acid-resistant Anion Exchange Membrane (AEM). This study evaluates DD through batch and once-through tests for acid recovery from simulated IX eluate generated in the elution stage of TEs (B, Ga, Ge, Co, Sr) recovery from saltworks bitterns.Batch tests achieved high recoveries for HCl (45–50 %) and H2SO4 (30–37 %), being the theoretical maximum attainable recovery equal to 50 %. B and Ge only partially permeated through the membrane (82 % rejection) by a diffusion mechanism in their neutral form (H3BO3(aq), H4GeO4(aq)). Ga, Co and Sr, in cationic form, were highly rejected (>96 %). Permeability followed the order Ga < Sr < Co ≪ Ge < B, due to the relevant charge and size. HCl permeability correlated linearly with concentration, while H2SO4 was inversely proportional. Once-through tests showed higher acid (74 % HCl, 62 % H2SO4) and oxoacid (66 % H3BO3(aq), 52 % H4GeO4(aq)) recovery at a low specific flow rate, or apparent flux, (0.38 L/(m2membrane·h)) due to increased residence time. Water to acid flow rate ratios did not affect species transport when an excess of water was guaranteed. Conversely, an influence was observed when the ratio was below 1, with a minimum at 0.18, where a very low passage of species was observed due to the reduced dilution volume of the dialysate solution (water). A 1D transport model, incorporating the solutes permeabilities determined experimentally, effectively described the system performance, especially for HCl and B, albeit slightly overestimating the other TEs’ transport.

X-ray fluorescence detection system for trace elements in oil based on graphite curved crystal technology

Curved crystal technology is a key technology in the field of X-ray fluorescence trace detection. To detect trace sulfur, chlorine, and silicon in oil, the key parameters of Johann-type graphite curved crystal design were calculated based on geometrical optics theory and mathematical modeling, and a curved crystal optical system was designed. Subsequently, the hardware, firmware, software, and mechanical structure were designed according to specific requirements. Following the development of the relevant equipment, laboratory tests were performed on standard petroleum samples. Experimental results show that technology based on bent crystals can significantly reduce the detection limit of the instrument, and the detection limit of sulfur, chlorine, and silicon can reach below 1 ppm. In accordance with the experimental results, possible interference factors were analyzed, and suitable solutions were proposed. The performance of the proposed system was thus directly verified, showcasing its applicability in detecting trace elements.

Non-Dispersive Extraction of Chromium(VI) by Cyphos IL102/Solvesso 100 Using the Pseudo-Emulsion-Based Strip Dispersion Membrane Operation.

The removal of chromium(VI) from an acidic (HCl) medium through non-dispersive extraction with strip dispersion (NDXSD) was investigated using a microporous PVDF membrane support in a permeation cell. The ionic liquid Cyphos IL102 (phosphonium salt) in Solvesso 100 was used as an organic phase. In NDXSD, the stripping phase (NaOH) is dispersed in the organic phase on the cell side with an impeller stirrer adequate to form a strip dispersion. This pseudo-emulsion phase (organic + strip solutions) provides a constant supply of the Cyphos IL102/Solvesso 100 to the membrane phase. Various hydrodynamic and chemical parameters, such as variation in the feed and pseudo-emulsion stirring speeds, HCl and Cr(VI) concentrations in the feed phase, and carrier concentration, were investigated. Results indicated that the best chromium(VI) transport was obtained under the following conditions: feed and pseudo-emulsion stirring speeds of 1000 min-1 and 600 min-1, respectively; an HCl concentration in the feed phase of 0.1 M; a chromium concentration of 0.01 g/L in the same phase; and carrier concentration in the organic phase in the 2-5-10% v/v range. From the experimental data, several mass transfer coefficients were estimated: a bulk diffusion coefficient of 3.1·10-7 cm2/s and a diffusion coefficient of 6.1·10-8 cm2/s in the membrane phase and mass transfer coefficients in the feed (5.7·10-3 cm/s) and membrane phases (2.9·10-6 cm/s). The performance of the present system against other ionic liquids and the presence of base metals in the feed phase were investigated.

An innovative approach for cluster head selection and Energy Optimization in wireless sensor networks using Zebra Fish and Sea Horse Optimization techniques

In recent times, Wireless Sensor Networks (WSNs) have become an indispensable technology across various industries, offering diverse applications and services. Among the crucial performance metrics for WSNs, optimal cluster head (CH) selection and energy efficiency are paramount for cost-effective network operations. This paper proposes a novel approach for WSNs that tackles both challenges using Zebra Fish Optimization (ZFO) and Sea Horse Optimization (SHO) algorithms. The proposed approach focuses on dynamic cluster formation and CH selection. The ZFO algorithm, enhanced with a new multi-level threading technique, dynamically selects the most suitable CH based on a fitness function. Subsequently, the SHO algorithm, equipped with an innovative adaptive parameter tuning mechanism, optimizes energy consumption within the network. This two-phased approach ensures balanced performance. Performance evaluation is validated using key metrics like packet delivery ratio (PDR), throughput, network lifetime, and residual energy. Experimental results and statistical analysis demonstrate that the proposed hybrid scheme outperforms existing popular algorithms in all these metrics. The improvements range from 1.8 % to 6.9 % for PDR, 6.7 % to 24 % for throughput, 1.86 % to 7.40 % for network lifetime, and 9.65 % to 37.95 % for residual energy. These advancements are attributed to the innovative modifications introduced in both ZFO and SHO algorithms, ultimately contributing to the enhanced performance of the entire system.

Optimal Scheduling of a Cascade Hydropower Energy Storage System for Solar and Wind Energy Accommodation

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system.

Performance Measurement System Design as Link Between Strategy Formulation and Performance Information Use in Public Sector Organizations

There has long been calls for improving the link between strategic planning and performance management. Despite such calls, there are few empirical studies of how performance management system design is related to performance information use in public sector organizations, which can be important for implementing and evaluating strategies to improve public sectors organizations’ performance. Utilizing data from 135 public sector organizations consisting of municipalities, counties, central government owned higher education institutions, and agencies in Norway, this paper analyzes how strategy formulation and performance measurement system design relate to purposeful performance information use. Multivariate analysis with partial least squares path modeling (PLS-PM) found a positive relationship between formal strategic planning and logical incrementalism with performance measurement system design as well as a positive relationship between performance measurement system design and performance information use. There were no significant direct relationships between formal strategic planning or logical incrementalism and performance information use, or between organizational size or government sector and performance information use. Therefore, performance measurement system design seems to be an important link between strategy formulation and performance information use.

Maximizing solar energy generation: guidelines for optimizing photovoltaic panel placement on building facades

PurposeThis purpose of this paper is to address the research problem of optimizing photovoltaic (PV) panel placement on building facades to maximize solar energy generation.Design/methodology/approachThe study examines the significance of various design configurations and their implications for PV system performance. The research involves analysis of relevant literature and energy simulations. An exemplary case study is conducted in a hot climate zone to quantify the impacts of PV panel placement on energy generation. Various application scenarios are developed, resulting in 28 scenarios for PV on building facades. Energy simulations using Grasshopper Rhino software and Ladybug plugin components are performed.FindingsThe paper identifies key factors influencing PV panel placement and energy generation through qualitative analysis. It introduces an appropriateness matrix as a decision-making framework to evaluate placement options. The study identifies design configurations and external features impacting PV location selection and performs a qualitative classification to determine their impact on energy generation.Practical implicationsThe results and decision-making framework enable informed choices based on solar radiation levels, shading conditions, and building requirements. Optimizing PV panel placement enhances solar energy harvesting in buildings, benefiting architects and engineers.Originality/valueThe novel contributions of this paper include practical insights and guidance for strategically placing PV panels on building facades.