Technical Performance Index Research Articles

A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System

Logistics is significantly impacted by quality/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.

Evaluating vessel technical performance index using physics-based and data-driven approach

Ship's performance and its emissions are affected by several factors like operational state, weather, and maintenance condition. Rating ships with performance indices, such as AER, is not really helpful as these factors are affected by the ship's technical and operational condition, obscuring the benefits of energy-saving technologies and improved maintenance condition. To promote energy-efficient ships and reduce emissions, DNV proposed a simple and intuitive Vessel Technical Index (VTI) which is expected to represent the change in technical performance of ships over time. This paper presents two different schemes to estimate VTI, namely, physics-based and data-driven approaches, to validate their applicability as well as compare their performance. The results are based on the measured in-service data from a bulk carrier, equipped with advanced sensors for speed and wave measurements. Although the VTI values from the data-driven approach are slightly overestimated, the mean trend of VTI over time, representing the change in performance of the ship, is quite comparable. The uncertainty in the results is reduced almost by half using the measured wave spectrum for physics-based VTI, whereas the data-driven approach creates an opportunity for ship performance monitoring without the need for speed-through-water measurements, which are considered unreliable for most ships.

Hydraulic modeling and prediction of performance for a drinking water supply system towards the achievement of sustainable development goals (SDGs): A system case study from Uganda

The world is currently confronted with water scarcity which is associated with deteriorating public sanitation and health, pollution, and ecosystem damage. Maintaining the performance of water supply schemes during a long-term demographic transition would achieve sustainability. This study employs a hydraulic modeling tool to predict the future performance of a water supply system, Najjembe Town water supply scheme, Uganda. Results showed that the flow velocity in the network ranges from 0.01 to 2.36 m/s. The pipeline velocities in the network are generally low under the predicated scenario, and pipes never run full. Flow velocities in some areas are below the recommended minimum velocity (0.6 m/s). The negative pressures were observed in some areas of the network due to high nodal water demand. The proposed hydraulic infrastructural changes improved the global technical performance indexes for pressure (TPIP) and velocity (TPIV) to 89.9–99.3% and 80.9–99.5%, respectively. The implementation of the water supply management plan complied with several sustainable development goals (SDGs) interlinked to targets regarding the provision of clean water and sanitation (SDG 6), supporting agricultural practices to achieve zero hunger (SDG 2), promoting good human health and well-being (SDG 3), promoting gender equality (SDG 5), and economic growth (SDG 8). Defining the linkage between water supply management planning and SDGs would assist in the long-term planning of water infrastructural needs in a sustainable and cost-efficient manner, addressing anomalies in coverage and assisting water supply managers and policy-makers in the sector in making well-informed decisions.

Simulation and prediction of residential grid-connected photovoltaic system performance

This paper presents the analysis of the actual, predicted, and simulated technical performance of a residential 2.835 kW<sub>p</sub> retrofitted grid-connected photovoltaic (GCPV) system under the feed-in-tariff (FiT) scheme in Klang, Malaysia located in the equatorial region. The technical performance indices of the GCPV system were assessed based on the three-year energy production in 2018, 2019 and 2020. The actual and predicted technical performance were calculated using SEDA mathematical model, which the solar irradiation data was acquired from PVsyst software. Meanwhile, the simulated technical performance was obtained using PVsyst software. The results showed that the prediction using mathematical model has higher percentage difference within the range of 12.54-13.29%, compared to PVsyst simulation that was within 7.93-11.93%. This study has highlighted the factors that contributed to the technical performance underprediction of both mathematical model and PVsyst simulation, which are the estimation of losses and annual irradiation data accuracy. Lastly, the FiT gross income calculated for the three consecutive years were within the range of 3310.80 MYR and 3357.30 MYR. This FiT gross income result conveys an example of Malaysian case study, to enlighten the public, on the economic aspect of installing GCPV system under FiT scheme.

Excessive Use of the Preferred Foot in on-The-Ball Skills Execution Compromises Performance and Tactical Behaviour of Football Players

This study aimed to compare tactical behaviour and performance of football players with different on-the-ball skills execution functional technical asymmetry levels and to verify whether functional technical and tactical performance indexes of football players are associated. The sample included 59 football players (14.2 ± 1.5 years of age). FUT-SAT and SAFALL-FOOT were used as instruments for performance analysis. Participants were divided in two groups: higher and lower functional technical asymmetry. Student’s t-test was used to compare the behaviour and tactical performance of the groups, and the Pearson test was used to verify associations between functional technical asymmetry and tactical performance indexes. A significance level of 5% was adopted. The higher functional technical asymmetry group showed less tactical efficiency (t57 = 1.9; p = .05; d = .17) and low performance results in the execution of defensive actions (t57 = 2.1; p = .04; d = .55; t57 = 2.1; p = .04; d = .61) compared to the lower functional technical asymmetry group. No association was found between the functional technical asymmetry and tactical performance indexes (r = -.06; p = .66). It is concluded that the levels of functional technical asymmetry affected the behaviour and tactical performance of players although functional technical asymmetry and tactical performance indexes values are not associated. Future investigations may verify how football players with high and low levels of functional technical asymmetry change their behaviour and tactical performance from different kinds of training.

The influence analysis of antenna radiation pattern aberration of airborne radar on clutter feature

In order to quantitatively evaluate the influence of the aberration of the antenna radiation pattern of airborne radar on clutter feature, the range-azimuth two dimensional (2D) model of the airborne radar clutter is established. Then the theoretic modelling and simulation analysis are proposed in three aspects, including the Doppler, power spectrum and space-time 2D characteristics of the clutter. Finally, the processing of moving target indication, pulse Doppler and space-time adaptive processing are used to suppress the clutter of the echo signals before and after the aberration. The results of the simulations indicate the aberration would elevate the sidelobe level, extend the power spectrum and bend the space-time trajectory of the clutter Doppler spectra. And the residual clutter would be elevated nearly 5 dB after STAP processing. Then the pattern preserving and fast time cancel combined space-time adaptive processing method is proposed, which can obtain narrow clutter notch and large improvement factor, and effectively suppress clutter. The modelling and quantitative analysis study have important theoretical and engineering significance for the detection capability of the airborne radar installed on the fuselage of the aircraft platform, the tactical and technical performance index, and improving the signal processing ability of airborne radar.

Enhancing static voltage stability of a power system in the presence of large-scale PV plants using a battery energy storage control scheme by the probabilistic technique

This paper aims to investigate the impact of large-scale photovoltaic plant (LS-PVP) controllers on the voltage stability (VS) of a power system. Besides, a new control strategy is proposed for the large-scale battery energy storage system (LS-BESS) to enhance a power system integrated with LS-PVPs, especially VS. To this end, a probabilistic technique, based on the stochastic nature of LS-PVPs and loads, is employed to accurately evaluate the impact of LS-PVPs on the system. Next, a new coupling between the optimization algorithm and the probabilistic technique is proposed to determine the optimal number, location, and capacity of the LS-BESSs by the probabilistic particle swarm optimization (PPSO) algorithm. The objective function is then used to simultaneously maximize the total VS and minimize the total power losses, line loading, as well as investment costs of LS-BESSs. Furthermore, technical performance indices (TPIs) are used for a more comprehensive investigation to compare the proposed solution to the synchronous generators. Finally, several disturbances occurring in the Nordic system are used to validate the effectiveness of the proposed approach, using the Monte Carlo simulation (MCS) method. According to the results, when a fault occurs, a system integrated with LS-PVPs in the stressed area does not operate better than synchronous generators. Therefore, an advanced control method is required to reduce undesirable effects of LS-PVPs. Using the proposed solution, voltage instability was prevented, LS-BESS investment costs were minimized, and negative effects of LS-PVPs on the system were reduced. Besides, costs required for expanding the transmission network as well as communication between controllers and reactive power compensation devices were reduced.

Shared energy storage system for prosumers in a community: Investment decision, economic operation, and benefits allocation under a cost-effective way

With the rapid development of distributed renewable energy, energy storage system plays an increasingly prominent role in ensuring efficient operation of power system in local communities. However, high investment cost and long payback period make it impossible for prosumers to own the storage system. In this context, considering the complementarity of power generation and consumption behavior among different prosumers, this paper proposes an energy storage sharing framework towards a community, to analyze the investment behavior for shared storage system at the design phase and energy interaction among participants at the operation phase. Therefore, under the sharing mode that the operator invests and virtualizes physical storage system to provide virtual storage services for prosumers, this paper first establishes a two-stage optimization model. Based on a new storage sharing contribution rate index and asymmetric Nash bargaining model, a profit-allocation mechanism is designed. Then, combined with alternating direction method of multipliers, to achieve a mutual benefit and win-win situation. Finally, the above model is simulated by three buildings' realistic data, and the effectiveness of shared energy storage system is analyzed by using different technical and economic performance indexes. Additionally, the influence of battery cost, carbon tax, electricity price, and the uncertainties of renewable energy output power and load on shared storage system planning are also discussed. Numerical results show that, compared with personal energy storage scenario, the proposed storage sharing mechanism can achieve 6.09% cost savings, the self-consumption rate and self-sufficiency rate of renewable energy respectively increase by 5.01% and 5.21%, and all financial evaluation indexes have improved. In short, this paper can give practical guidelines for investors and prosumers to reasonably plan and share energy storage system, and provide realistic references for the government to effectively implement the shared energy storage.

Designing of an anti-rutting and High Ductility Asphalt Mixture based on mortar performance

The anti-rutting and anti-cracking performance of asphalt mixtures are a pair of contradictions that are difficult to coordinate. In order to ensure the rutting resistance of asphalt mixture to meet the requirements of the specification, while improving its deformation capacity and crack resistance. Based on the mortar performance, the Anti-rutting and High Ductility Asphalt Mixture with excellent anti-rutting performance and deformation performance was designed in this paper. With the filler-asphalt ratio as the control index, SBS modified asphalt and SHV modified asphalt was selected to design five asphalt mortars with different filler-asphalt ratios of 0, 0.5, 1.0, 1.5, 2.0. Variation laws of mortar technical indicators were investigated by rotational viscosity test, cone penetration test, and BBR test. Asphalt mixtures were prepared and a rutting test and small beam bending test were carried out to ensure the consistency of the mixture skeleton state by grouting molding. The influence of the mortar performance index on the road performance of the mixture was evaluated by conducting correlation analysis, and then an anti-rutting and high-ductility asphalt mixture was proposed based on mortar performance. The obtained results showed that the technical indicators of asphalt mortar had a good correlation with the filler-asphalt ratio, and the developed regression model could be used to determine the correlation and design of the mortars. The technical performance index of mortar was found to be directly correlated with the road performance index of the mixture. The developed anti-rutting and high-ductility asphalt mixture not only had good anti-rutting performance but also had good deformation capacity and cracking resistance. Its anti-rutting performance could meet the specification requirements, and the maximum flexural strain could reach 7161 με. The performance of asphalt mortar determines the road performance of the mixture. The rutting resistance and cracking resistance of the mixture could be coordinated by designing asphalt mortar to improve its comprehensive road performance. To guarantee that the dynamic stability of the mixture met the required specifications and the deformation ability was good, the critical value of each technical index of asphalt mortar was recommended.

Demand response of grid-connected microgrid based on metaheuristic optimization algorithm

ABSTRACT Demand Response Programs (DRPs) have gained the microgrid (MG) operators phenomenal attention for mobilizing the end-users in alleviating the uncertainties associated with renewable energy sources. In this research work, the effective MG energy management system (EMS) in conjunction with price-driven DRPs is proposed to achieve synergistic coordination between the energy providers and consumers and reduce operational costs. The flexible price elasticity model is implemented instead of using the price elasticity models with a preordained constant value like most existing literature. This results in a more realistic characterization of customer responsiveness to energy price changes and promotes the DRPs under a grid-connected MG environment. With this regard, a stochastic day-ahead energy management strategy is proposed to incorporate four distinct DRPs and schedule the MG distributed energy resources. The proposed strategy is verified on a practical 3-feeder MG test system with a majority of 50% industrial load considered. The short-term scheduling period of 15 min ahead solar and wind power forecast is considered to optimize the microgrid dispatch costs accurately. The intermittent nature of renewable energy sources is addressed by employing a stochastic-based scenario generation and reduction approach. A novel and nature-inspired Black Widow Optimization (BWO) is applied to determine the optimal scheduling configuration. The effectiveness of the BWO is validated in terms of rate of convergence, computational time, and solution efficacy. Finally, the best DRP has been chosen based on its technical and economic performance indices by employing a multi-criteria decision-making approach.

Optimal day ahead energy consumption management in grid‐connected microgrids

The day-ahead scheduling of microgrids in the presence of nondispatchable distributed generators (DGs) is a challenging task for microgrid operators. The valve point loading problem of distributed generators and its effect on input-output characteristics is not extensively covered in the published scientific literature on microgrids. In this research work, the day-ahead scheduling problem of microgrids is formulated in the presence of DGs with a nonconvex cost function. First, the flexible load-shaping based demand-side management strategy is adopted to reduce the peak loads and enhance the DG's unit operational costs. The impact of demand-side management and price-driven demand response programs on convex and nonconvex energy management system (EMS) problems is investigated. Furthermore, the short-term scheduling horizon of 15-minutes resolution time is considered for both solar and wind power to maintain forecast accuracy. The state-of-art optimization algorithm of quantum particle swarm optimization is devised to solve the proposed problem in the presence of the nonconvex cost function of DGs. The technical performance indices for each demand response program is evaluated, and the best alternative demand response program is chosen by implementing analytical hierarchy process. The proposed algorithm efficiently solves the nonconvex EMS problem, and the simulation results yield a 12.11% reduction in operating cost without compromising customer satisfaction. Computational time, convergence characteristics, and solution effectiveness in contrast to recently reported metaheuristic algorithms are examined for the effectiveness of the suggested algorithm.

Research on the Statistical Model System of Each Balanced Game Based on Big Data

The article uses the holistic, comprehensive and dynamic diversified and complex thinking mode of big data system theory. The article creates a generalized linear model for the value of each technical and tactical performance index and the game result in each score-balanced game. To define the linear relationship between the technical and tactical performance indicators of the game and the probability of winning the game; finally, adopt the data series inference method to define the significance of the linear relationship between each technical and tactical performance indicator and the probability of winning the game. The research found that the information provided by the model created in the paper can be used in football practice such as game performance evaluation, opponent information detection, selection and modification of training preparation plans.

Optimal Power Allocation for Cooperative Pattern Division Multiple Access Systems

This study focuses on the power allocation (PA) problem in code division multiple access (PDMA) networks with amplify-and-forward (AF) relays. We provide two wireless communication technical performance indexes, which are system throughput and outage probability. A multiobjective version of particle swarm optimization is proposed to solve Pareto-optimal solutions for optimal PA problems. A novel programming model is built based on improvement of constraint functions, and the accuracy and efficiency of solution can be improved via compact constraints. The technique for order preference by similarity to an ideal solution is proposed to balance the performance indicators, which include outage probability and system throughput. It has been calculated that the proposed approach for optimal PA is verified and performs better than a genetic algorithm approach.

Fuel-melting aggregate “MAGMA-1” for processing wastes of electric steelmaking

Toughening of ecological requirements to metallurgical production and economic factors, stipulated by competitiveness at the metal products market, increased actuality of utilization of slags, sludges and dust, obtained in steelmaking. It was shown, that from the economic point of view, processing of slags obtained at operation of modern ultra-powerful electric arc furnaces (EAF), is the item of highest interest. At present, their processing is restricted often by maximum possible recovery of metallic inclusions. At that the problem of utilization slag remains, dust and sludges remains unsolved. A pyrometallurgical method of electric steelmaking slags processing in EAF was considered. The process involves application of liquid phase reducing of metal oxides and correction of slag composition aimed at obtaining cast slag marketable products and clinker for cement industry. Data of test heats for slags utilization at the 5-ton EAF presented. The proposed technology enables to make industrial scale processing of slags with obtaining cast iron and melted clinker. Taking into consideration that EAF coefficient of efficiency, accounting fuel consumption for electrical energy obtaining is not high and is 23–24%, it was proposed to do slags processing in fuel-melting aggregates, in which the efficiency of primary energy utilization is higher (efficiency coefficient is 25–40%). The firm OJSC NTP “Akont” developed a technical project of a fuel-melting aggregate “MAGMA-1” for processing electric steelmaking slags. Its basic technical data and performance indices presented. It was shown that additional decrease of fuel consumption can be provided at utilization of liquid slag tapped out of EAF in a course of a heat, as well as at charge heating in a tubular rotating heater by waste gases.

Analysis of Photovoltaic & Battery Energy Storage System Impacts on Electric Distribution System Efficacy

Uncertain nature of renewable energy sources like solar irradiation poses a serious concern of loss of power supply reliability. Battery energy storage (BES) system helps in improving system reliability by storing surplus energy generated and supplying the load in case of energy deficit. Thus BES allows improvement of microgrid performance and reduces operational cost by increasing the utilization of renewable energy sources. This paper presents an energy management strategy (EMS) to dictate the power flow among photovoltaic (PV) panels, BES and the load considering a proposed time-of-use (TOU) pricing as the control factor. Its efficacy in improving power supply reliability as well as power quality issues of a 69-bus radial distribution system (RDS) is evaluated from technical performance indices like power loss, voltage deviation index and security margin and economic performance considering costs of power import from the grid and active power loss and financial benefit from battery discharge. Grasshopper Optimization Algorithm (GOA), is used to optimize the sizes and placements of three PV-BES units to minimize an objective function aptly formulated combining the technical performance indices using weighted sum method. The results are contrasted against another two cases of with only PV and without PV and BES integration. Finally, the proposed system is analysed from economic perspective and the benefits obtained are compared. The results are evident of both technical and economic advantages of integrating both PV and BES units at optimal locations (load bus). The optimization results obtained from GOA have been compared with that from Genetic Algorithm (GA). GOA proves to be fast, effective and reliable in resolving power flow optimization problem.

Association between technical and economic performance indexes and dairy farm profitability

ABSTRACT This study aimed to evaluate the determinant profitability indexes of typical dairy farms located in Brazil. The empirical sample included detailed technical and financial information of 61 Brazilian dairy farms across a longitudinal data set (10 years). Numerous technical and economic indexes were estimated, and Pearson’s correlation coefficients were calculated to determine the relationship between each index and profitability. After selecting the significant indexes, regression equations were generated to determine the relationship between each index and profitability. The results [...]

Customer and Model Based Performance Evaluation of Water Distribution Systems: The case of Adama Town, Ethiopia

The aim of this study was to evaluate the performance of the existing water supply system of Adama Town by considering direct and indirect performance measurements. The paper also investigates the application of technical performance index to evaluate the operational performance of the water distribution system and to easily identify the critical areas in the network. The evaluation carried out based on WaterNetGen tools an extension of EPANET to attain direct performance measurement and Minitab16 software to analyze primary data to achieved indirect performance measurement. Based on water tap flows result, most of the residences got water at night time and were not satisfied with the town water supply services. The greatest minimum slack pressure and velocity occurred in a small area of the network, and the global technical performance index of pressure and velocity were 35.75% and 46.19%, respectively.

Thermodynamic and economic analyses of a hybrid waste-driven CHP–ORC plant with exhaust heat recovery

A smart hybrid power plant comprising a waste-fired CHP (combined heat and power) plant accompanied by a small-scale organic Rankine cycle was recently designed and analyzed thermodynamically. The objective of this hybridization is to maximize the share of electricity production of waste-CHP plants rather than a higher heat production rate in a cost-effective manner. In this work, utilization of the exergy of the hot flue gas of the waste-fired CHP unit in order to increase the potential of the organic Rankine cycle for maximizing the net power output of the hybrid cycle is proposed and techno-economically analyzed. In addition, the effect of using alternative environmentally-friendly organic working fluids on the performance of the system was investigated. The results of the study show that by the flue gas potential utilization of the same CHP unit, the size of the organic Rankine cycle may increase significantly, leading to a larger power output of the plant. As such, the net exergy and energy efficiency values of the combined plant in various operational conditions are improved compared to its primary configuration by, respectively, about 10% and 20%, when both of the main CHP cycle and the organic Rankine cycle are working at nominal load. In addition, this exergy utilization is beneficial economically as well, decreasing the payback period of the parallelization project by about 10% (from 7.4 years to 6.7 years). The alternative organic working fluid does not make a significant change in the technical and economic performance indices of the system.

Comprehensive performance evaluation of various solar PV system configurations

This study presents a year-long comprehensive performance analysis of four distinct solar photovoltaic (SPV) system configurations with central inverter, micro inverter, fixed axis structure and dual axis sun tracker (DAST) structure installed at the Indian Institute of Technology Kharagpur, West Bengal, India. Technical and economic performance indices are used to analyse the impact of inverter technology and DAST structure using field data of one year. Specifically, technical parameters specified by IEC 61724 are used to compare simulated results with field data from June 2017 to May 2018. The difference between the simulated and measured values of all the configurations is mostly attributed to the variation in solar irradiance and module temperature data. For simulation study, daily and monthly average values are considered while daily instantaneous data are used for measured values. Comparison of measured values through energy yield, capacity factor and performance ratio (PR) indices has confirmed the superiority of dual axis micro inverter system configuration. Additionally, the impact of seasonal variation on PR values for all four system configurations is also analysed. Economic performance for 25 years of project life using payback period, net present value and levelised cost of energy indices concludes dual axis central inverter system configuration as the most economical.

Investment analysis of gas-turbine combined heat and power systems for commercial buildings under different climatic and market scenarios

The aim of the proposed work is to investigate the technical and economic suitability of a gas turbine combined heat and power system in commercial buildings. These systems are widely recognised as a promising technology to provide significant fuel savings and carbon emissions reduction where they have been widely used in industrial settings due to the relatively constant electrical and thermal loads required for industrial processes. However, their deployment has been relatively stagnant over the last few decades due to challenges such as poor planning and policy measures, energy market changes and regulatory barriers. In this context, a preliminary system design and optimisation procedure has been developed based on a sensitivity analysis of different scenarios of building loads, market and weather conditions. The optimisation is performed considering several technical and environmental parameters (e.g., energy and exergy efficiencies and primary energy saving), as well as economic indexes (e.g., net present value, pay-back period, profitability, etc.). This allows the suitability assessment of the investment for different market price scenarios under different heating degree days demand scenarios. The analysis is carried out using an Italian case study as it exhibits a wide range of heating degree days variability, while subject to a single pricing market. Results show that strong correlations occur between the technical and economic performance indices and the weather conditions for all considered configurations. The methodology and conclusions, if coupled with the possibility of applying clustering techniques to determine common patterns of energy consumptions in building blocks, represent a powerful toolset to carry out preliminary techno-economic assessment of a combined heat and power system.