Performance Analysis Methodology Research Articles

Steady-state analysis of a hybrid power supply system using an induction generator with a shunt AC/DC converter

Hybrid power supply systems (HPSSs) are considered as a good option for electric power supply of remotely located from the grid consumers due to significant fuel savings compared to diesel sets. Quick development and improvement of HPSSs may be achieved using specialized methodologies and programs. In the paper a schematic diagram is proposed and operation principles of a 400 V / 50 Hz HPSS were developed. The system’s main component is the master generating unit of the hydropower plant using a 250 kW induction generator (IG). The voltage of the system is controlled by the controller of the AC/DC power converter. The electrical frequency of the system is controlled by the speed controller of the hydropower turbine. A wind turbine, an energy storage system and a regulated dump load are connected to the IG through the AC/DC converter. Goal. The paper aims to develop a methodology for steady state performance analysis of the hydraulic turbine driven isolated IG operating in parallel through an AC/DC power converter with additional sources and consumers of active power. Methodology. The methodology for evaluation of performance characteristics of the IG operating in the proposed system has been developed. The methodology is based on the equivalent circuit of the system, equations of active and reactive power balance in the system and the superposition method. Results. The equations of frequency, voltage and power regulators of the system are given. The performance characteristics of the IG operating in the system supplying resistive and RL load in «constant voltage – constant frequency» mode are obtained. Novelty. The developed methodology is innovative in taking into account the control algorithms of the system. The comparative analysis of the IG’s performance operating in the stand-alone generating unit and in the generating unit connected to the proposed system is performed. Practical value. The developed methodology can be used for development and performance improvement of hybrid AC power systems.

A robust methodology for PEC performance analysis of photoanodes using machine learning and analytical data.

Machine learning (ML) is increasingly applied across various fields, including chemistry, for molecular design and optimizing reaction parameters. Yet, applying ML to experimental data is challenging due to the limited number of synthesized samples, which restricts its broader application in device development. In energy harvesting, photoanodes are crucial for solar-driven water splitting, generating hydrogen and oxygen. We explored electrodes like hematite and bismuth vanadate for photocatalytic uses, noting varied photoelectrochemical performances despite similar preparations. To understand this variability, we applied a data-driven ML approach, predicting photocurrent values and identifying key performance influencers even with limited experimental data in the research development of inorganic devices. We have utilized multiple machine learning algorithms to predict the target value in the calculation process, where the contributions of the dominant descriptors were unknown. We introduced a novel methodology, incorporating clustering to manage multicollinearity from correlated analytical data and Shapley analysis for clear interpretation of contributions to performance prediction. This method was validated on hematite and bismuth vanadate, showing superior predictability and factor identification, and then extended to tungsten oxide and bismuth vanadate heterojunction photoanodes. Despite their complexity, our approach achieved determination coefficients (R2) with a prediction accuracy over 0.85, successfully pinpointing performance-determining factors, demonstrating the robustness of the new scheme in advancing photodevice research.

КОМБІНОВАНЕ РЕГУЛЮВАННЯ КОМУТОВАНИМИ КОНДЕНСАТОРАМИ Й ВЕНТИЛЬНИМ ПЕРЕТВОРЮВАЧЕМ НАПРУГИ АСИНХРОННОГО ГЕНЕРАТОРА АВТОНОМНО ПРАЦЮЮЧОЇ МІНІ-ГЕС

The principles of operation and a static simulation model of the power-generating equipment of the autonomous power supply source based on a hydroelectric unit with a 275 kVA induction generator and a combined capacitor-inverter excitation system supplying a symmetrical passive load have been developed. The initial excitation of the generator is carried out by a bank of capacitors of the initial excitation. During low power demand the generator voltage is kept constant by adjusting the reactive power of the semiconductor converter, and at high loads, the voltage is adjusted as a result of the switching of additional capacitor banks. The developed methodology for performance analysis the pro-posed power supply source is based on the IG equivalent circuit. Computations of the static characteristics of the gen-erator operating with a constant rotor speed were carried out and the obtained static characteristics were analyzed for two set values of the load power factor. Ref. 5, fig. 4, table.

A comprehensive methodology for analysis of coagulation performance: Dosing approach, isotherm modelling, FTIR spectroscopy and floc characterization

Isolated studies for the evaluation of coagulation considering either microscopic or macroscopic dimensions have largely been discussed. However, comprehensive analysis of coagulation including various dimensions is imperative to design an optimal coagulation system. In this work, a comprehensive methodology has been described which includes dosing approach, mathematical modelling, chemical analysis by FTIR (Fourier Transform Infrared) spectroscopy, image analysis for floc properties and various analytical procedures. Jar tests were performed on simulated waters containing humic acid and kaolin using high basicity PACl (Poly Aluminium Chloride). A PODR (point of diminishing return) approach is used for the determination of coagulant dose corresponding to TOC (Total Organic Carbon), DOC (Dissolved Organic Carbon) and UV254 (Ultraviolet Absorbance at 254 nm). On average, PODR for UV254 was slightly greater than that of TOC followed by that of DOC. The correlation between the input TOC and PODR values was in the order: TOC (R2 = 0.84) > UV254 (R2 = 0.83) > DOC (R2 = 0.65). The isotherms are analyzed by non-linear error functions: RMSE (Root mean square error), HYBRID (Hybrid fractional error function), ARE (Average relative error), MPSD (Marquardt's percent standard deviation) and Chi-Square. It was observed that error functions RMSE, HYBRID and Chi-Square can be successfully used for non-linear analysis. However, ARE and MPSD cannot be used at low concentrations as they showed high residual values. Further, image processing is used to analyze floc size and fractal dimension. The interactions of species and the physical structure of flocs derived based on adsorption isotherms are corroborated by using the FTIR data.

Flamenco Negro: uma análise do espetáculo da Companhia De Arte La Negra Ana Medeiros

ABSTRACT This paper proposes an analysis of the spectacle Flamenco Negro, based on the theoretical framework of the sociology of art and the sociology of ethnic-racial relations, combining the analysis of the social context of production of the work with the methodology of performance analysis. The study found that the process of creating such a work of art was part of a social network articulating a community of meaning that helped to form the dancers’ own racial consciousness, enabling them to reaffirm their position and their way of dancing within the art scene and resize the black diaspora as a collective experience by highlighting the hybridity between Afro-diasporic dances and musicalities in Flamenco.

Stochastic, individual animal systems simulation model of beef cow-calf production: development and validation.

A stochastic, individual animal systems simulation model describing U.S. beef cow-calf production was developed and parameterized to match typical U.S. Angus genetics under cow-calf production conditions in the Kansas Flint Hills. Model simulation results were compared to available actual, multivariate U.S. cow-calf production data reported according to beef cow-calf standardized performance analysis (SPA) methodology through North Dakota State University's CHAPS program to assess model validity. Individual animal nutrition, reproduction, growth, and health characteristics, as well as production state are determined on a daily time step. Any number of days can be simulated. These capabilities allow for decision analysis and assessment of long-run outcomes of various genetic, management, and economic scenarios regarding multiple metrics simultaneously. Parameterizing the model to match Kansas Flint Hills production conditions for the years 1995 through 2018, 32 different genetic combinations for mature cow weight and peak lactation potential were simulated with 100 iterations each. Sire mature cow weight genetics ranged from 454 to 771 kg in 45 to 46 kg increments. Sire peak lactation genetics were considered at 6.8, 9, 11.3, and 13.6 kg/d for all eight mature cow weights. Utilizing model results for the years 2000 to 2018, raw model results were assessed against actual historical cow-calf production data. Exploratory factor analysis was applied to interpret the underlying factor scores of model output relative to actual cow-calf production data. Comparing modeled herd output with CHAPS herd data, median average calf weaning age, average cow age, percent pregnant per cow exposed, and percent calf mortality per calf born of model output was 3.4 d greater, 0.2 yr greater, 1 percentage point less, and 1.7 percentage points greater, respectively. Subtracting the median CHAPS pre-weaning average daily gain from the median modeled pre-weaning average daily gain for each of the eight respective mature cow weight genetics categories, and then calculating the median of the eight values, the median difference was -0.21 kg/d. Performing the same calculation for birth weight and adjusted 205 d weaning weight, the modeled data was 4.9 and 48.6 kg lighter than the CHAPS data, respectively. Management and genetic details underlying the CHAPS data were unknown.

Probabilistic analysis of water-sealed performance in underground oil storage considering spatial variability of hydraulic conductivity

For underground water-sealed oil storage, the spatial variability of the surrounding rock has a significant impact on the water-sealed effect of a water curtain system. This study presents a methodology for the probabilistic analysis of water curtain performance in underground oil storage, considering the spatial variability of hydraulic conductivity of the surrounding rock based on field data. Anisotropic random fields representing the spatial variability of hydraulic conductivity were established through spatial statistical analysis of field data and introduced into the finite element model of underground oil storage for water-sealed reliability analysis. The water-sealed performance of different water curtain system schemes was studied using Monte Carlo simulation (MCS). The results showed that the difference between the horizontal spatial correlation and the vertical spatial correlation of the surrounding rock has a significant impact on the water-sealed effect of the water curtain system. An excessively large pressure of water curtain boreholes provided a small contribution to improving water curtain performance. The distance between the water curtain holes and the caverns had the less significant affecting the water-sealed reliability of the storage cavern. Finally, the optimal design of the water curtain system is discussed. This study provides valuable insights and a theoretical basis for the optimisation of water curtain system design parameters for underground water-sealed oil storage.

Towards an Accurate Aerodynamic Performance Analysis Methodology of Cross-Flow Fans

Cross-flow fans (CFFs) have become increasingly popular in recent years. This is due to their use in several domains such as air conditioning and aircraft propulsion. They also show their utility in the ventilation system of hybrid electric cars. Their high efficiency and performance significantly rely on the design parameters. Up to now, there is no general approach that predicts the CFFs’ performance. This work describes a new methodology that helps deduce the performance of CFFs in turbomachinery, using both analytical modeling and experimental data. Two different loss models are detailed and compared to determine the performance–pressure curves of this type of fan. The efficiency evaluation is achieved by realizing a multidisciplinary study, computational fluid dynamics (CFD) simulations, and an optimization algorithm combined to explore the internal flow field and obtain additional information about the eccentric vortex, to finally obtain the ultimate formulation of the Eck/Laing CFF efficiency, which is validated by the experimental results with good agreement. This approach can be an efficient tool to speed up the cross-flow fans’ design cycle and to predict their global performance.

A 5S Lean Strategy for a Sustainable Welding Process

The correct performance of the welding processes used to join metal parts or structural elements is considered to be of vital importance to guarantee the reliability of these products during their useful lives. Adequate workstation design ensures a safe environment in which an operator can perform these processes correctly. In order to guarantee the quality of welding seams, which are used to join metal parts and structural elements, a series of standards have been developed; these standards establish requirements to guarantee the correct performance of welding processes, and the inspection of the metal welds obtained. The 5S methodology has proven to be a valid tool for improving workplaces in industrial and service activities; it is a capstone methodology when companies implement lean production approaches. This work presents a framework for applying the 5S methodology in metal welding workplaces. It defines an index to evaluate the degree of implementation of the 5S methodology, and the application of the important performance analysis methodology (IPA). Fuzzy logic is used to treat the uncertainty in evaluating the different evaluation indicators proposed. This framework is applied to a real practical case, to provide an example of its use in establishing good manufacturing practices that guarantee compliance with the requirements of welding standards, and guaranteeing the correct handling and storage of the materials and tools used in welding processes for the manufacture of welded parts and structural elements.

Slovenian health care system performance in the light of Euro Health Consumer Index 2012

Health care systems are complex entities with several stakeholders that include patients, health care providers, payers, regulators and government. For lay and professional public, the methodology of health care system performance analysis, result interpretation and translation to policy making is not well understood. Slovenian health care system performance results from a Swedish health care analyst (Euro Health Consumer Index 2012) and opportunities for improvement are discussed. We specifically addressed methodological challenges of international health care system performance comparisons.

Steady-state performance and dynamic performance of heterogeneous platoons under a connected environment

Under the vehicle-to-vehicle (V2V) environment, the steady-state performance and the dynamic performance are both crucial for the traffic system. This paper proposes an in-depth methodology to provide some insights into the comprehensive changes of steady-state performance and dynamic performance of a heterogeneous platoon, which contains human-driven vehicles (HDVs) and connected and automated vehicles (CAVs). To further understand the impacts of various feedback information, an improved full velocity difference model that incorporates multiple feedback communicating information is developed. Based on the transfer function, the stability and steady-state error are proposed to characterize the steady-state performance, while the degree of fluctuation and duration of fluctuation are used to measure the dynamic performance. On the one hand, a key finding is that there are inconsistencies in steady-state and dynamic performance under particular feedback information. The acceleration or spacing feedback information can enhance the steady-state performance while degrading the dynamic performance. The speed difference feedback information yields the opposite result. On the other hand, it is discovered that compared to several types of feedback information, combining just one type of information is enough to boost the platoon performance. When the number of CAVs is considerable, combining two types of information will considerably increase the duration time. Therefore it is important to find the key feedback information for the platoon performance. The main purpose of this paper is to present a methodology of platoon performance analysis instead of discussing the various traffic scenarios. As a result, while certain results may alter in some specific scenarios, the proposed methodology and core contribution remain applicable to various traffic scenarios.

Long term cooling safe shutdown performance analysis for SMART with passive safety system using MARS-KS

Passive safety systems have been adopted in reactor design to enhance safety especially in SMRs after the TMI-2 accident in 1979. The passive system has high operational reliability with natural driving forces such as gravity, natural circulation and stored energy. In recent years, development of innovative SMRs has emerged as a global R&D initiative for sustainable energy to challenge the carbon neutrality of climate change. The passive safety system makes reactor design simple and thus enhances the reliability of the reactor. As advanced reactors adopt passive safety systems, regulatory requirements and guides are required. Thus, development of regulatory guide and detailed regulatory review methodology for the passive safety systems is needed. In this paper, long term cooling safe shutdown acceptance criteria and performance analysis methodology are proposed for the regulatory standard design approval for the SMART100 integral reactor with fully passive system which has been jointly developed by KAERI in Korea and K.A.CARE in Saudi Arabia. The long term cooling safe shutdown performance analyses are performed until 72 hours to evaluate the methodology, and sensitivity analyses are also performed to provide a technical basis for the regulatory independent review for the long term cooling performance of the SMART100 passive safety systems.

Performance Evaluation of Parallel Data-Intensive Simulations Based on Graph Partitioning Approach

Scientific simulations require both increasing computing and storage power, parallel and distributed computing are strongly recommended to deal with them. Despite the power of the parallel approach to solving complex simulations, it is more difficult and error-prone, therefore, several factors create significant programming challenges and have the effect of reducing performance, which must be carefully managed to achieve high parallelism. This paper aims, on the one hand, to evaluate the performance of parallelism based on the graph partitioning approach, and on the other hand, to propose a performance analysis methodology that aims to help scientists to investigate the impact of inter-processor communication on the performance of an application First, a multilevel k way algorithms are used to compute a distribution of the calculations and associated data of simulation. Second, a performance evaluation strategy is used to investigate the efficiency of parallelism. Finally, we examine the results of the experiment and explain the perspective of this study.

Technical Indicators for the Comparison of Power Network Development in Scenario Evaluations

The problem of electric network expansion has different implications concerning the definition of criteria for the comparison of different candidate projects. Transmission expansion planning usually involves a set of economic and technical influences on market framework and on network operation over defined scenario evolutions, or even combining generation and transmission planning, although the application to real-sized networks usually implies cost-benefit analysis. In this paper, a methodology for performance analysis of a set of network development projects is proposed, including zonal market framework and load flow analysis, in order to individuate possible candidate projects and their influence on active power losses, admissible load increase and admissible renewable generation increase. Those merit indicators are compared among candidate projects by means of Analytic Hierarchy Process (AHP) method, aiming at determining the most promising solution under different weights of criteria. Moreover, the influence of network development investment cost on project selection is assessed by means of an extension of AHP. The procedure is applied to yearly operation of NREL-118 test system.

Towards Improving Technical Performance of a 747 MW Thermal Power Plant

In this paper, performance evaluation and technical audit of a 747 MW thermal power plant consisting of three generating units is conducted. The factors influencing the performance of the plant have been identified and improvements in processes and mechanical, electrical, instrumentation, and safety engineering are suggested. These improvements would result in better profitability, productivity, and performance. The paper further discusses technical issues and challenges and identifies key areas where improvements are possible. Future recommendation for the operation of the plant that would result in better throughput are also presented. The methodology of performance analysis presented in the paper will help improving operational efficiency of thermal power plants in developing countries.

Energy management system for surveillance and performance analysis of a micro-grid based on discrete event systems

ABSTRACT This paper proposes an energy management system for an effective operation of micro-grids. In recent years, the penetration of the distributed energy resources such as photovoltaic and wind turbine generators into the electrical networks has been increasing. These resources generate perturbations and instability in the electrical grid. Battery energy storage system is the most used recently on micro-grids in order to manage the integration of intermittent of energy resources and help the control system to reduce the undesirable effects like power fluctuations because of perturbations (fault, short-circuit,…etc). However, for control and management purposes, a power distribution network can be modeled as a discrete or hybrid (discrete events and continuous variables) event system. This distributed topology will enhance the resilience of the power grid, facilitate the integration of distributed energy resources, especially renewable sources, accommodate energy storage units, and enhance the quality of delivered power. The main objective of this paper is to highlight a methodology for surveillance and performance analysis of a micro-grid during a perturbation based on discrete event systems. This systematic control method is effective in managing many operations in smart grids. As result, the formulation of power network control problems in discrete event system is useful for energy management, control, modeling, and monitoring with diagnosis applications.

Importance Performance Analysis of Service quality for Locals and Expats in Indian Restaurants in Taiwan: Case Study

In the recent era, service quality has played a key role in each organization. This study aims to evaluate the service quality performance of ChilliesineIndian restaurants located in Taichung city of Taiwan. In this context, we have adopted the DINERSERV questionnaire after reviewing various literature. Importance performance analysis methodology has been used to understand the service performance of each service item. The study will evaluate and analyze the service quality desired as per the customer in Taichung city under the context of the service quality. IPA being a marketing tool to give a vivid picture for managers to make decision and understand their competitive advantage and improve on the rest.

Performance Analysis of Internet of Things Interactions via Simulation-Based Queueing Models

Numerous middleware application programming interfaces (APIs) and protocols were introduced in the literature in order to facilitate the application development of the Internet of Things (IoT). Such applications are built on reliable or even unreliable protocols that may implement different quality-of-service (QoS) delivery modes. The exploitation of these protocols, APIs and QoS modes, can satisfy QoS requirements in critical IoT applications (e.g., emergency response operations). To study QoS in IoT applications, it is essential to leverage a performance analysis methodology. Queueing-network models offer a modeling and analysis framework that can be adopted for the IoT interactions of QoS representation through either analytical or simulation models. In this paper, various types of queueing models are presented that can be used for the representation of various QoS settings of IoT interactions. In particular, we propose queueing models to represent message-drop probabilities, intermittent mobile connectivity, message availability or validity, the prioritization of important information, and the processing or transmission of messages. Our simulation models demonstrate the significant effect on delivery success rates and response times when QoS settings are varied.

A Novel Data Management Methodology and Case Study for Monitoring and Performance Analysis of Large-Scale Ground Source Heat Pump (GSHP) and Borehole Thermal Energy Storage (BTES) System

Aalto New Campus Complex (ANCC) is a recently inaugurated educational facility at Aalto University, located in Otaniemi (Espoo), Finland. Within over 40,000 m2, it comprises two faculties, a shopping center, recreational areas, and a metro station. ANCC is also a large-scale application of Ground Source Heat Pump (GSHP)–Borehole Thermal Energy Storage (BTES) in Finland, comprising an irregular BTES field of 74 boreholes with an overall length of roughly 23 km and 4 million m3 of energy storage. Therefore, accurate monitoring of the GSHP–BTES energy system is crucial for sustainable and efficient long-term operation. Due to the fundamental issues affecting the accuracy of all thermal energy meters, a novel methodology adjusting for consistency of the measured data (in order to accomplish daily energy balance on both sides of the GSHP) is developed. The proposed methodology is used also in conjunction with reconstruction of missing relevant data before April/May 2020 by applying linear regression techniques. The developed data management is considered essential due to its capability to handle measured data with high uncertainty (thermal meters) by using highly accurate data regarding the GSHP power demand. Additionally, operational data and relevant GSHP performance indicators for the 18-month period starting from July 2019 is presented and analyzed.

Methodology for Performance Analysis of Distributed Knowledge-Based Systems

Methodology for Performance Analysis of Distributed Knowledge-Based Systems