Supply Points Research Articles

Analysis of pneumatic parameters to identify leakages and faults on the demand side of a compressed air system

Despite their significant use in industrial automation, compressed air systems have a typical efficiency of around 10–20%. Literature shows that data monitoring systems are being introduced to detect losses, however, demand side monitoring techniques make use of highly dedicated proprietary equipment which has a number of limitations. This study sought to setup an experimental methodology that identifies the effective parametric data which can be monitored on the demand side to identify inefficiencies in compressed air systems. A compressed air test bed was used to quantifiably compare and contrast leakage inefficiencies in varying system complexities and at different system pressures. The test results confirmed that benchmarking is essential when monitoring data on the demand side. Furthermore, it was also concluded that a single pressure sensor, installed at the supply point of an automation system, could be used to detect the pressure difference which is caused by a leak further downstream along the system. This research establishes that this data can be used to estimate the volume of compressed air that is wasted due to a leak. Analysis of the data collected has shown how a 1.6 mm leak results in a pressure drop of around 10%, downstream to the leak. As expected, a leakage increases the air flowrate, however it is concluded that the percentage increase is relative to the complexity and size of the pneumatic system and may not be significantly conclusive when comparing diagnostic data. It is demonstrated that the measurable effects on pressure and flow rate become less profound in more complex systems. • A pneumatic test bed was used to identify parameters which can detect inefficiencies. • As the flowrate increased by 155 L/min, the system pressure decreased by 0.1 bar. • A 1.6 mm leak results in a pressure drop of around 10%, downstream to the leak. • One pressure sensor can detect and quantify a leak in a pneumatic system. • Effects on pressure and flowrate become less quantifiable in complex systems.

Assessment of the potential emergency hazard of the gas distribution system during operation

The object of the study was the gas distribution networks of various pressure categories that supply gas to municipal and industrial consumers from gas supply points, for example, gas distribution stations (GDS), during operation process the gas networks are exposed to a large range of loads and impacts, which, in combination with a long period of operation, leads to a decrease in the level of reliability. Studies have shown that the reduction of the emergency hazard for the used pressure categories in the gas distribution network in comparison with the higher category is 1.2 – 2 times, while at the same time there is decrease in the reduced costs to 40 percent or more.

Emergency logistics scheduling with multiple supply-demand points based on grey interval

This study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points. In large-scale natural disasters, it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster sites and to determine emergency material scheduling solutions accurately. Furthermore, the quantity of emergency materials required at each disaster site is uncertain. To address this issue, in this study, we developed an emergency material scheduling model with multiple logistics supply points for multiple demand points based on the grey interval numbers. To optimize the proposed multi-supply-point and multi-demand-point emergency material scheduling mode, a multi-objective optimization algorithm based on a genetic algorithm was used. Experimental results demonstrate that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm optimization multi-objective solution algorithm. Additionally, the multi-supply point and multi-demand point emergency material dispatch model and optimization algorithm provides robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities.

Faulty Line Selection Method Based on Comprehensive Dynamic Time Warping Distance in a Flexible Grounding System

A flexible grounding system is a system in which the neutral point of the power supply is grounded via the arc suppression coil in parallel with a low-resistance resistor. When operating normally or a temporary ground fault occurs, the arc suppression coil is used for grounding, whereas the small resistance is switched on when a permanent ground fault occurs. At present, the problem of low protection sensitivity when a high-resistance ground fault occurs in a flexible grounding system has not been solved yet. According to the characteristics of low waveform similarity between the faulty line and the non-faulty line when a single-phase grounding fault occurred, a new faulty line selection method based on a combination of Dynamic Time Warping (DTW) distance and the transient projection method is proposed in this paper. Firstly, the fault transient signal is extracted by a digital filter as a basis for faulty line selection. Secondly, the transient zero-sequence current of each line is projected onto the busbar transient zero-sequence voltage, and the projected DTW distance of each line is calculated. Finally, according to the calculation formula of waveform comprehensive similarity coefficient, the Comprehensive DTW (CDTW) distance is obtained, and the top three CDTW distance values are selected to determine the faulty line. If the maximum value is greater than the sum of the other two CDTW distance values, the line corresponding to the maximum value is judged as the faulty line; otherwise, it is judged as a busbar fault. The simulation results based on MATLAB/Simulink and field data test show that the method can accurately determine the faulty line under diverse fault conditions.

A comprehensive literature review on spare parts logistics management in the maritime industry

Supply chain and logistics management for spare parts is of key importance in the maritime industry, in order to ensure high availability and reliability of assets, while keeping operating costs in acceptable levels. Supply chain and logistics operations for spare parts incorporate high complexity, uncertainty and costs, due to special characteristics of the maritime sector, as for instance moving assets, globally scattered points of supply and demand, strict time windows and multi-actor setting. Typically, the asset owner purchases spare parts for their vessel from a foreign supplier, and consolidates them in a regional warehouse. Subsequently, these spare parts are shipped to a port using various means of transport such as air freight, sea freight or road freight. Finally, once the vessel calls at subject port, the spare parts are delivered and used on board for maintenance activities. For repairable items, the reverse logistics process also does exist; a spare part is offloaded from a vessel, repaired and then re-delivered on board. Efficiently handling such a logistics network constitutes a great challenge, nevertheless, this topic has received little attention in the literature and a systematic review is currently missing. In this paper, the authors attempt to address this research gap by performing a systematic literature review on spare parts supply chain and logistics management in the maritime sector. To achieve this objective, after applying the defined inclusion and exclusion criteria on the initial search results, a set of (30) eligible papers, participating in the review, has been identified. These selected papers are illustrated and discussed in detail, with the purpose of addressing the research questions initially set by the authors. Fundamentally, this study aims to describe the current state of the art in the subject area, identify existing challenges and trends, and finally provide suggestions on future research. We aspire that the results of this review can be used as the foundation for future research on spare parts supply chain management in the maritime sector.

Interleaved Boost Integrated Flyback Converter for Power Factor Correction in Brushless DC Motor Drive

The scope of this research is to manage the speed of Permanent Magnet Brushless DC Motor Drive (PMBLDCMD) for various less capacity applications. In the circuit, a 1ϕ AC power is given to Diode Rectifier and the converted DC supply is given to condenser, which leads to abnormal pulsating current. Because of this pulsating current, the power quality disturbances arise at the supply point. Hence, the PMBLDCMD requires Power Factor Correction (PFC) converter for many household and profitable applications. The rotors of PMBLDCMD are driven by 3ϕ voltage source inverter (VSI), which performs electronic commutation. The range of PFC converter for feeding PMBLDCMD has high emphasis on the power quality (PQ) norms, cost and performance of controllers. The proposed converter requires very less components, which imposes less stress, low ripple and less power loss with positive voltage polarity. The chopper is used to correct the power factor. Various chopper layouts like buck boost Converters and boost converters with single switch are used. The mostly used regulated structures for PFC converters govern the current with continuous conduction technique and to govern the potential differential tracker using discontinuous conduction method (DCM). The processes like examining, modelling and governing of PFC converters are applied for upgrading the quality of power in AC supply.

Analysis of Mode of Access to Quality Public Water Supply in Jalingo Metropolis, Taraba State

This study analyse the mode of access to safe public water supply in Jalingo Metropolis. The study applied both survey and experimental research designs. The survey design involves sampling consumers' modes of accessing the public water supply, whereas the experimental approach involved laboratory investigation of water quality. A cross-sectional study carried out among 348 consumers who had access to public water supply and seven supply points each served by the three (3) production units of the Taraba State Water and Sewerage Corporation (TAWASCO) in Jalingo metropolis were selected. The standard procedures for water sample collection was done, which were analysed using the Wagtech Water Quality analysis machine in the World Health Organization Modern Laboratory located within Rural Water Supply and Sanitation Agency (RUWASA) office in Jalingo. Whereas, the questionnairs elicited information on the mode of access to water by the residents. The questionnaire data were analysed using frequency count and simple percentage. The result revealed that both the physical and chemical characteristics of public water supply in Jalingo metropolis are within the permissible limits of WHO and NSDWQ. The coliform count for the water samples were in trace amount and within the standard limits of WHO/NSDWQ. On the mode of access to safe water supply, the result revealed that majority of the respondents (80%) in Magami and ATC production channels do not have direct connection to the main water supply from RUWASA but gain access through indirect connection from neighboring houses/compounds. It was only from the Mile Six production channel that majority of the respondents (70%) reported that they access water from taps located within the house. This implies that most of the residents in the study area do not have connection to the main supply, which delivers water directly to their homes. The study therefore recommended that the government should ensure equitable distribution of portable water to the generality of the public.

Forecasting Electricity Demand of Municipalities Through Artificial Neural Networks and Metered Supply Point Classification

Forecasting Electricity Demand of Municipalities Through Artificial Neural Networks and Metered Supply Point Classification

Predviđanje brzine vetra zasnovano na dugotrajnoj memoriji primenom nelinearne autoregresivne neuronske mreže

Globally, wind power is a technologically matured and commercially accepted technology. However, intermittent and fluctuating wind speed makes it difficult to connect it directly to the grid. It becomes less attractive from the quality and continuous power supply point of view. Nevertheless, the wind speed is affected by meteorological parameters like temperature, pressure, and relative humidity and may be predicted better using all of these parameters or some of the theses as inputs. Since the weather conditions of a particular month repeat approximately after ten years and sometimes even year to year depending on geographical location. This study investigates the errors associated with predicting the wind speed of a particular calendar month using the historical data of the same calendar month in the previous years. Authors propose a strategy for long-term prediction of wind speed based on two nonlinear autoregressive neural network models, (i) nonlinear autoregressive neural network and (ii) nonlinear autoregressive neural networks with exogenous inputs. The models are developed by training the networks with hourly mean wind speed values for seven years, from 2011 to 2017, for three sites in the Eastern Province of Saudi Arabia. These models are used to predict the wind speed for 2018, and the results are compared with the measured data. Both models' effectiveness is evaluated by considering the impact of the exogenous parameters (temperature and atmospheric pressure). The study found that the prediction accuracy of wind speed in long-term forecasting depends not only on the location but also on the repeatability of training samples across the years.

DG Locational Incremental Contribution to Grid Supply Level

Due to decarbonisation and decentralisation of energy sectors, the rise of distributed generation (DG) will modify generation and demand patterns at grid supply points (GSPs), where the interface between distribution and transmission systems takes place. With the increasing penetration of such devices, methodologies able to evaluate its contribution to both local distribution network and transmission system become crucial. This paper proposes an analytical method to evaluate the DG locational incremental contribution (LIC) to the interface with the transmission grid. Accordingly, the original model of the UK engineering recommendation P2 is enhanced by studying the impacts from high-voltage distribution networks (i.e. ≤ 132 kV) under normal and contingent conditions. This approach enables a more accurate network security assessment, especially when considering contingencies such as distribution system faults. To illustrate the proposed method, the original P2 model is compared against different enhanced approaches on three basic distribution networks, followed by a case study and a sensitivity analysis on a revised IEEE 14-bus GSP system. The proposed LIC method produces results that assess a wider range of conditions including DG penetration, concentration, and system reliability. Furthermore, it provides an increased DG visibility for transmission planning and operation.

Simultaneous Estimation of Behind-the-Meter Solar and Wind Power at the Bulk Supply Point

The presence of distributed energy resources in private premises has observed a large deployment worldwide driven by favorable governmental policies and technology development. In Northern Ireland, the small-scale generation capacity including solar and wind power has fast-grown accounting for over 17% of peak load in 2021, which makes net demands more volatile and diminishes the accuracy of electric demand forecasting activities. Different from traditional load forecasting methods based on the relationship between heterogeneous variables and net demand fluctuation, a novel approach is proposed to separately forecast the invisible components (e.g. wind & solar power) within the net demand. The critical challenge in the separate forecasting is how to extract behind-the-meter components from the measured net demand data, namely net demand disaggregation, for which continuous wavelet transform is applied to bring out the detailed fluctuation of net demand and an iterative search algorithm is proposed to separate the components in the net demand. The results reported show that the proposed demand disaggregation method contributes to reduce the forecasting error by more than 14%. Methods like the proposed net demand disaggregation can benefit utilities and system operators in performing their daily activities regarding load forecasting in serving areas and power systems they operate.

The main characteristics of the insurance market for longevity risk: a literature review

Longevity risk is the probability of surviving more than own financial resources. This paper aims to define the characteristics of the insurance market for longevity risk. First, it identifies the aging of the population between the OECD countries and the need for long-term care services (i.e., their quality of life). Second, it tries to summarize the main characteristics of the insurance market for longevity risk from the literature point of view. According to the financial literature, the market to ensure the aging population's long-term needs can be considered a puzzle as there are some constraints from the two sides of the market. From the demand point of view, two issues limit the request for insurance products: the role of the State and misunderstanding about the exposure at risk by the population. At the same time, there are other constraints from the supply point of view: the adverse selection and moral hazard issues that impact the pricing of longevity risk. All these constraints limit the growth of this market. Third, it identifies some suggestions for further investigation in the growing field of financial literature. This paper contributes to the existing literature by identifying the constraints that avoid the insurance market's growth for longevity risk and by remembering some solutions to reassess the role of the welfare state.

The main characteristics of the insurance market for longevity risk: a literature review

Longevity risk is the probability of surviving more than own financial resources. This paper aims to define the characteristics of the insurance market for longevity risk. First, it identifies the aging of the population between the OECD countries and the need for long- term care services (i.e., their quality of life). Second, it tries to summarize the main characteristics of the insurance market for longevity risk from the literature point of view. According to the financial literature, the market to ensure the aging population’s long- term needs can be considered a puzzle as there are some constraints from the two sides of the market. From the demand point of view, two issues limit the request for insurance products: the role of the State and misunderstanding about the exposure at risk by the population. At the same time, there are other constraints from the supply point of view: the adverse selection and moral hazard issues that impact the pricing of longevity risk. All these constraints limit the growth of this market. Third, it identifies some suggestions for further investigation in the growing field of financial literature. This paper contributes to the existing literature by identifying the constraints that avoid the insurance market’s growth for longevity risk and by remembering some solutions to reassess the role of the welfare state.

Development of a heuristic to solve the general transportation problem

The transportation problem is well known and has very important applications. For this well-researched model, there are very efficient approaches for solving it that are available. These approaches include formulating the transportation problem as a linear program and then using the efficient methods such as the simplex method or interior point algorithms. The Hungarian method is another efficient method for solving both the assignment model and the general transportation model. An assignment problem is a special case of the transportation model in which all supply and demand points are 1. Every transportation problem can be converted into an assignment problem since rows and columns can be split so that each supply and each demand point is 1. The transportation simplex method is another method that is also used to solve the general transportation problem. This method is also called the modified distribution method (MODI). To use this approach, a starting solution is required and the closer the starting solution to the optimal solution, the fewer the iterations that are required to reach optimality. The fourth method for transportation models is the network simplex method, which is the fastest so far. Unfortunately, all these approaches for transportation models are serial in nature and are very difficult to parallelize, which makes it difficult to efficiently use the available massively parallel technology. There is a need for an efficient approach for the transportation problem, which is easily parallelizable. This paper presents a See-Saw approach for solving the general transportation problem. This is an extension of the See-Saw approach for solving the assignment problem. The See-Saw moves can be done independently, which makes the approach proposed in this paper more promising than the available methods for transportation models

Coordinated, sensitivity-based DSM for enhanced cross-border power transfers

This paper discusses the use of coordinated wide area demand side management (DSM) for facilitating cross-border power transfers between the interconnected transmission networks. It proposes a methodology for ranking transmission network loads eligible for DSM programs based on the network topology and the size of DSM assets. The influence of network topology is accounted for by considering distribution factors (DFs), and the size of DSM assets by considering the available demand flexibility (upward or downward variation) of load buses. The industrial end-users connected directly to transmission network and the bulk supply points of distribution networks are considered the two main types of DSM providers at the transmission level. The proposed approach facilitates analytical evaluation of the effects of DSM on power transfers and such makes a valuable decision-support tool for any transmission system operator, whether it is used for network operation or planning. The methodology is illustrated on a simplified model of four interconnected European transmission networks and thus provides a realistic assessment of the extent to which cross-border DSM can be used to regulate power transfers between countries.

EMC Testing of Electricity Meters Using Real-World and Artificial Current Waveforms

In 2015, the energy measurement of some static electricity meters was found to be sensitive to specific conducted electromagnetic disturbances with very fast current changes caused by highly nonlinear loads, leading to meter errors up to several hundred percent. This article describes new results on the electromagnetic compatibility (EMC) of 16 different meters from all over Europe when exposed to real-world disturbance signals. Those test signals were obtained from household appliances and onsite measurements at metered supply points all over Europe. The results show that also the interference signals recorded onsite can cause measurement errors as large as several hundred percent, even for meters that pass the present EMC standards. This unambiguously demonstrates that the present immunity testing standards do not cover the most disturbing conducted interference occurring in present daily-life situations due to the increased use of nonlinear electronics. Furthermore, to enable the adoption of potential new test waveforms in future standards for electricity meter testing, artificial test waveforms were constructed based on real-world waveforms using a piece-wise linear model. These artificial test waveforms were demonstrated to cause meter errors similar to those caused by the original real-life waveforms they are representing, showing that they are suitable candidates for use in improved standardization of electricity meter testing.

Designing and Solving Location-Routing-Allocation Problems in a Sustainable Blood Supply Chain Network of Blood Transport in Uncertainty Conditions

Purpose: In this paper, a location-routing-allocation problem in a multi-objective blood supply chain network was designed to reduce the total cost of the supply chain network, the maximum unmet demand from distribution of goods, and decline greenhouse gas emissions due to the transport of goods among different levels of the network. The network levels considered for modeling include blood donation clusters, permanent and temporary blood transfusion centers, major laboratory centers and blood supply points. Other objectives included determining the optimal number and location of potential facilities, optimal allocation of the flow of goods between the selected facilities and determining the most suitable transport route to distribute the goods to customer areas in uncertainty conditions. Methodology: Given that the model was NP-hard, the NSGA II and MOPSO algorithms were used to solve the model with a priority-based solution. Findings: The results of the design of the experiments showed the high efficiency of the NSGA II algorithm in comparison with the MOPSO algorithm in finding efficient solutions. Originality/Value: This study addresses the issue of blood perishability from blood sampling to distribution to customer demand areas.

Suministro y calidad del agua de escurrimientos en la selva mediana subcaducifolia de la Costa de Oaxaca, México

Introduction: Land use change and waste discharge from coffee processing may be affecting quantity and quality of water supplying urban areas in the coastal region of Oaxaca.Objective: To determine the level of contamination of aquifers and estimate surface water runoff in micro-watersheds of Pluma Hidalgo and Santa María Huatulco in Oaxaca, Mexico.Materials and methods: Seven water supply points were analyzed during the rainy season of 2019. The following physicochemical parameters were determined: pH, total dissolved solids, electrical conductivity, hardness, total solids, chlorides, and chemical oxygen demand (COD). Surface runoff was estimated using the Raws and Prevert methods.Results and discussion. Water bodies are within the permissible limits for human use. The Chacalapilla spring was classified as moderately hard (85 mg CaCO3∙L-1), while the seven water bodies exceeded the permissible limit for COD (40 to 200 mg∙L-1); therefore, water is in a contaminated classification range and is not suitable for human consumption. Surface runoff values suggest a medium conservation condition of vegetation cover; areas with higher cover recorded lower runoff coefficients.Conclusions. The physicochemical parameters indicated that water from Pluma Hidalgo and Santa María Huatulco is suitable for human use, but not for drinking

Design of Power Supply Modification of Variable Traffic Signs

This paper describes the design of mobile power sets for variable traffic signs for the use of energy storage in lead-acid battery. The supply point is intended primarily for use in powering traffic lights and mobile variable traffic signs for line traffic control. A test sample of the system was assembled, on which a series of measurements were performed to verify its functionality.

Analisis Supply Chain Risk Management Industri Budidaya Lobster Air Tawar Dengan Pendekatan FMEA

The growing interest of the Indonesian people in the cultivation of LAT (Freshwater Lobster) is one of the effects of government regulation no. 56/ Permen-KP/2016. Since the occurrence of the Covid-19 pandemic with regional restrictions, one of the LAT cultivation industries of the Red Claw (Cherax Quadricarinatus) type in the Sidoarjo area, East Java, has experienced problems in supplying lobster to consumers in various regions outside cities in Indonesia. The delay in the supply of lobster results in delays in the supply of raw materials for consumers, the majority of whom are restaurant or restaurant activists. The success of supply chain management is determined by the number of costs that can be minimized, short time, and quality that is maintained, as well as the level of risk minimization (supply chain risk). Based on the problems that occur, risk identification will be carried out in each process to see its effect on cost, time, and quality. Then proceed with determining the weight based on the level of resistance (severity), possible resistance (occurrence), and the cause of the detected obstacle (detection). The last step is to calculate the RPN (Risk Priority Number) value obtained from the severity results. From the results of the analysis of risk identification and calculation of RPN with the FMEA approach, the highest risk weight with an RPN value of 105 was obtained due to the risk factor for the increase in distribution costs of cultivation products due to the impact of the Covid-19 Pandemic. Thus, the company should consider reorganizing its business strategy to focus on areas that are close to the point of supply of freshwater crayfish.