Unit Load Research Articles

Exploring service quality of inland container depot-empirical evidence from the Red River Delta, Vietnam

Inland Container Depots (ICDs) are inland multi-modal terminals where goods in intermodal loading units can be transferred directly to seaports. The contribution of ICDs to regions’ economic and social growth is undeniable. To achieve the sustainable development of ICDs, evaluating and improving their service quality is critical. This study aims to investigate the factors contributing to the service quality of ICD in a developing country. The data utilized covers some ICDs in the Red River Delta, Vietnam. Regarding analytic methods, descriptive statistics first were run to show the level of aspects of service quality of ICDs. Subsequently, attitudinal statements were analyzed using exploratory factor analysis before linear regression was applied to recognize the factors influencing the service quality of ICDs. Generally, the service quality of ICDs was evaluated at an acceptable level but far from the high one. The results suggested that the four influential service quality factors included location and accessibility, facilities, process and management, and labor. Based on the findings of contributing factors, managerial implications were proposed.

Recovering Low-Grade Heat from Flue Gas in a Coal-Fired Thermal Power Unit

To achieve the goals of carbon peaking and carbon neutrality, the retrofitting of existing coal-fired power plants is crucial to achieving energy-saving and emission reduction goals. A conventional recovery system of waste heat typically occurs downstream of the air preheater, where the energy quality in flue gas is low, resulting in limited coal-saving benefits. This study proposes a scheme involving a flue gas exchanger bypassing the air preheater and low-temperature economizers, which is used to transfer the waste heat from flue gas to primary and secondary air (System I). Additionally, a heat pump can be introduced to provide supplementary energy for primary and secondary air, as well as the condensate from the steam turbine (System II). The coal consumption rate and exergy efficiency are used to evaluate the two schemes. The results show that both waste heat recovery systems can increase the power output of the coal-fired unit by recovering waste heat. System II can boost power output by approximately 13.98 MW. The power increase in both waste heat recovery systems show a declining trend as the unit load decreases. This increased power is primarily attributed to the medium- and low-pressure cylinders, while the contributions from ultra-high-pressure and high-pressure cylinders are negligible. The increased power output for the medium-pressure cylinder ranges from approximately 3.49 to 3.58 MW, while the low-pressure cylinder has an increased power output of around 10.10 to 10.19 MW. The coal consumption rate is decreased from 250.3 g/(kW·h) to 247.5 g/(kW·h) under a full load condition for both systems, which can be augmented at lower load conditions. System II outperforms System I at 30% load condition, achieving a reduced coal consumption rate of 3.36 g/(kW·h). System I has an exergy efficiency of 40%, while System II shows a higher efficiency of 44%.

Applications and analyses of ammonia slip control based on precise ammonia injection technologies guided by big data

Abstract After the implementation of ultra-low emission policies, the pollutant emissions from the coal-fired power generation systems in China have been further reduced, which creates more critical requirements for the control accuracies of denitrification systems using selective catalytic reduction technology and controls of ammonia slip. This article presents big data-based technologies for controlling ammonia slip, through precise ammonia injections, which were applied and demonstrated for a flue gas denitrification system of a Chinese coal-fired power plant. Through examinations and analyses of the basic operating conditions of the unit and parameters, such as NOx emission control efficiency, ammonia injection amount of the denitrification system, and non-uniformity of NOx concentrations in the denitrification zone were compared before and after the implementation of these technologies, the outcome proves that this artificial intelligence algorithm based on big data can effectively solve the automatic control problem of denitrification system under complex working conditions such as varied unit loads, day and night operation changed coal source. In addition to the effective controls of the ammonia slip of the system, the controls of NOx emission of the system become more stabilized, creating a successful example for wider applications of these precise ammonia injection control technologies in the future. Analyses show that NOx non-uniformities can be reduced by more than 50% under both stable and variable load conditions. NOx fluctuations at the unit outlet are tightly controlled within ±10 mg/Nm3 under variable load conditions and within ±5 mg/Nm3 under stable conditions. The average ammonia injection amounts under various load conditions have decreased by 15.7%.

Opportunistic maintenance for a novel load-sharing system with dependent degradation rate and volatility

For traditional degrading load-sharing systems, a typical assumption lies in the only effect of unit load on its degradation rate. However, motivated by a laser system example with positive correlation between degradation rate and volatility, we present a novel load-sharing system with general degradation rate-volatility-load correlation. Furthermore, to take account for unit economic dependence caused by sharable maintenance set-up cost, and the window period generated by the maintenance on some unit, opportunistic maintenance (OM) strategy is introduced to offer the opportunity of simultaneously maintaining another working unit under control-limit criteria. Based on the semi-regenerative process, the long-run average cost rate is minimized to obtain the optimal inspection interval, preventive maintenance and OM thresholds. Compared to the traditional condition-based maintenance strategy separately for each unit, the effectiveness of OM strategy is validated through numerical examples and case studies, offering broad managerial insights for engineers to reduce maintenance expenses.

Temperature regimes of evaporator pipes at partial loading of power units

Temperature regimes of evaporator pipes at partial loading of power units

A novel algorithm for optimizing genset operations to minimize fuel consumption in remote diesel-RES microgrids

This paper addresses the challenge of reducing fuel consumption in Diesel-RES (Renewable Energy Sources) isolated microgrids, particularly focusing on Diesel Genset’s (DG) operation. The study introduces a basic rule based energy management system that serves as a platform to test out various DG operational strategies with a novel approach. Two optimization strategies—load dispatch optimization and unit commitment optimization—are explored to unequally distribute loads among different grid-connected DGs and sequence their start/stop based on predictive demand profiles respectively. Additionally, the integration of a spinning reserve-providing battery is investigated to alleviate DGs from their spinning reserve constraint, resulting in higher operational loads and consequently higher efficiency. The proposed model is applied on a case study of the Tahitian power system, demonstrating reductions in fuel consumption. The combined application of the proposed DG load dispatch and unit commitment optimizations, along with the integration a spinning-reserve-providing battery, yielded a 2.6 % reduction in fuel consumption and 6kt decrease in CO2 emissions over a year compared to a basic DG operation without a battery.

Behind-the-Meter Load and PV Disaggregation via Deep Spatiotemporal Graph Generative Sparse Coding With Capsule Network.

Nowadays, rooftop photovoltaic (PV) panels are getting enormous attention as clean and sustainable sources of energy due to the increasing energy demand, depreciating physical assets, and global environmental challenges. In residential areas, the large-scale integration of these generation resources influences the customer load profile and introduces uncertainty to the distribution system's net load. Since such resources are typically located behind the meter (BtM), an accurate estimation of BtM load and PV power will be crucial for distribution network operation. This article proposes the spatiotemporal graph sparse coding (SC) capsule network that incorporates SC into deep generative graph modeling and capsule networks for accurate BtM load and PV generation estimation. A set of neighboring residential units are modeled as a dynamic graph in which the edges represent the correlation among their net demands. A generative encoder-decoder model, i.e., spectral graph convolution (SGC) attention peephole long short-term memory (PLSTM), is devised to extract the highly nonlinear spatiotemporal patterns from the formed dynamic graph. Later, to enrich the latent space sparsity, a dictionary is learned in the hidden layer of the proposed encoder-decoder, and the corresponding sparse codes are procured. Such sparse representation is used by a capsule network to estimate the BtM PV generation and the load of the entire residential units. Experimental results on two real-world energy disaggregation (ED) datasets, Pecan Street and Ausgrid, demonstrate more than 9.8% and 6.3% root mean square error (RMSE) improvements in BtM PV and load estimation over the state-of-the-art, respectively.

DETERMINING THE OPTIMAL NUMBER OF STRETCH FILM LAYERS FOR ENSURING PALLETIZED CARGO STABILITY: A SIMULATION STUDY

Numerical simulation tests were carried out to determine the influence of the characteristic features of a load unit (such as: weight, height, number of load layers, coefficient of friction between the layers) per number of wraps with stretch film necessary to ensure unit stability. Manufacturers of stretch film sometimes provide guidelines on how many layers of film should be used depending on the weight and height of the load. But they do not explain on the basis of which studies these values were determined. Performing simulations similar to those made in this work in laboratory conditions would be very expensive. The work attempts to determine such relationships by simulation methods. A developed by the author in his earlier works dynamic model of a layered cargo unit wrapped with stretch film was used. The study plan was to check 108 cases. On the basis of the collected data, an attempt was made to develop a mathematical formula that would allow to estimate the optimal number of foil wraps when certain parameters of the load unit are known. In the author's opinion such an estimate could reduce film consumption, which would have a positive impact on the environment.

Performance assessment of a multi-level shuttle system: an optimisation-embedded simulation study on time and energy consumption

ABSTRACT In response to the dynamic demands of modern e-commerce and supply chains, this paper addresses the critical need for adaptability and efficiency through the implementation of automated storage and retrieval systems. By using an optimisation-embedded simulation methodology, the proposed study focuses on a multi-level shuttle system designed to overcome the inherent limitations of traditional storage systems. A comprehensive discrete event simulation model is developed to evaluate the performance of the multi-level shuttle system. This model includes calculations of travel time and energy consumption, taking also into account stochastic handling times associated with repetitive tasks. In addition, a dynamic programming algorithm is integrated in the simulation model to optimise the sequencing of storage and retrieval missions performed by the handling machine. The study systematically investigates various design and operational parameters, including warehouse configurations and capacity, simultaneous handling of multiple unit loads, and the dimensions of the optimisation sessions. For all configurations tested, the research demonstrates operational advantages in the simultaneous handling of two unit loads. Theoretical contributions extend the current state of simulation models for automated warehousing systems. For practitioners, the study provides empirical insights to support decision making in the configuration of automated warehouses.

On the use of vibrations and temperatures for the monitoring of plastic chain conveyor systems

In industrial automation, the transportation of unit loads plays a crucial role. This paper addresses the under-explored area of plastic chain conveyors, a versatile and efficient means of transport within production processes. Despite their widespread use, these conveyors suffer from wear and tear due to continuous contact between the chain and guide rails, often leading to unscheduled shutdowns and increased costs. The literature on monitoring solutions for such systems is sparse, particularly for plastic chains. This paper aims to bridge this gap by surveying the most common wear mechanisms for these systems and presenting a physical model that describes the interaction between the chain links and guide rails, based on chain of masses, springs and dampers and the Archard wear model. This model allows to relate the variations due to wear with other physical quantities, such as passage frequencies of the links and heat generated due to friction. The comprehensive model provides analytical formulas to understand the vibrations induced by the chain on the platform and the guide-rail temperatures. To validate the model and evaluate how the measurements are affected by the degradation of the system, an extensive experimental campaign was conducted on a conveyor test rig, acquiring vibration and temperature data. The end goal is to identify and discuss methodologies suitable for estimating the wear mechanisms of conveyor systems, with a focus on the constraints of industrial environments. Hence, this study aims to lay the groundwork for defining monitoring solutions that enhance the maintenance efficiency of plastic chain conveyor systems. The results suggest that the power Spectral Densities (PSD) of the platform’s accelerations are sufficient to estimate the average links pitch, which in turn could be used to assess the chain elongation. Besides, the local temperatures confirmed the model observations, making them suitable for estimating the slide-rail thinning.

Monitoring of thick-walled pressure elements to determine transient temperature and stress distributions using the measured fluid's pressure and wall's temperature

The paper presents a new stress monitoring method for cylindrical pressure elements of the power unit. It can be used to monitor a power unit's start-up, shutdown, and load change to reduce the unit's connection time to the power grid. The outer surface of the component is thermally insulated. Circumferential thermal stress at the point of its concentration at the hole edge is determined based on the stress determined at a greater distance from the hole. The circumferential thermal and pressure stresses at the hole edge are calculated by multiplying the stress values determined for the non-weakened wall by the respective concentration factors. In addition, the heat transfer coefficient (HTC) at the inner surface of the pressure element is necessary to determine the thermal stress concentration factor. Heat transfer correlations available in the literature are used to calculate HTC. The transient element wall temperature is measured five to 12 mm from the inner surface of the cylindrical component. An analysis of the measurement point locations on the accuracy of temperature and stress determining at the inner component surface was investigated. A practical application of the proposed method using real measurement data is presented.

Modelling and optimization of ATM cash-loading under stochastic demand

A set of ATMs in commercial areas were considered for business transactions. Customer demand for money requires prompt cash supply; to harmonize optimality options for ATM cash loading to sustain customers. We formulated this tis decision as a multi-stage stochastic process with Markovian demand of ATM cash among customers. The loading and operations of the ATMs were governed by cash demand and supply; with unit (loading, operational, and shortage) costs. The study considered the ATM cash demand of ten ATMs in regions within commercial centres of Kampala city. The relevant data was collected every hour throughout four months. The task focused on optimizing cash-loading decisions that minimize the operational costs of managing ATMs. The optimality of cash loading decisions were determined using the Markov decision processes. The tested model revealed optimal state-dependent options and operational costs of managing ATMs cost-effectively. As a cost optimization strategy for managers in the banking industry, the productivity of ATMs towards improved efficiency and utilization of resources for cash provision to customers emerged; supporting a larger customer base for business transactions.

Theoretical modeling and investigation of the influence of deaerator on the transient process in power plants

Deaerator is one of the most important equipment for steady state and dynamic operation of power plants. The deaerator energy storage utilization process is one of the most essential ways to enhance the variable load rate of power plants. The purpose of this study is to improve the dynamic simulation performance of the deaerator during unit load changes by constructing a more reasonable deaerator model, aiming to provide guidance for practical operations. In this paper, a thermal mass microelement algorithm is proposed for the heat transfer between droplets and steam in the deaerator, followed by segmental modeling of the deaerator. By comparing with the operation data of a power plant, the steady state operation error of the deaerator model is within 0.6 %. Subsequently, the unit load variation process is simulated and the dynamic variation accuracy of the model proposed in this paper is enhanced by 1–2 % compared to the lumped parameter model. The dynamic characteristics of the deaerator are obtained by simulating the step and ramp changes of the deaerator boundary conditions and the deaerator start-up process. In addition, during the simulation of condensate throttling, the maximum power of the unit using the deaerator model in this paper is 0.2–1.5 MW larger than that of the lumped parameter model.

State of-The-Art Multi-Input DC-DC Converter Topologies and their Control Techniques: A Review

Environmental awareness and technological advancement have made renewable energy sources such as fuel cell,solar photovoltaic (PV), wind energy an emerging research area. Power electronics converters are used as interface betweenthe renewable energy sources and the load unit, aimed at matching these sources with the load demand and improving thesteady-state and dynamic characteristics. Traditional method of using multiple single-input single-output dc-dc converter tointegrate several renewable energy sources, comes with challenges in controller design, poor efficiency, low power densityand increase in cost. To address these limitations, the use of an integrated multi-port converter is a preferable solution.Recently, several multi-port dc-dc converter topologies have been reported each having its peculiarity in terms of number ofcomponent count, relationships between input and output, voltage conversion ratio, control algorithm and efficiency. Thisarticle reviewed multi-port dc-dc converters presented by different research groups from the point of view of topology, inputand output relation and structure. Furthermore, control algorithms proposed to solve various control problems are alsoreviewed.

Flexible resource allocation optimization model considering global K-means load clustering and renewable-energy consumption

Abstract Vigorously developing flexible resources in power systems will be the key to building a new power system and realizing energy transformation. The investment construction cost and operation cost of various flexible resources are different, and the adjustment ability is different in different timescales. Therefore, the optimization of complementary allocation of various resources needs to take into account the economy and adjustment ability of different resources. In this paper, the global K-means load clustering model is proposed and the 365-day net load is reduced to eight typical daily net loads by clustering. Secondly, a two-level optimization model of flexible resource complementary allocation considering wind power and photovoltaic consumption is constructed. The flexible resources involved include the flexible transformation of thermal power, hydropower, pumped storage, energy storage, and demand response. The upper-layer model optimizes the capacity allocation of various flexible resources with the minimum investment and construction cost as the goal and the lower layer optimizes the operating output of various units with the minimum operating cost as the goal. The results of the example analysis show that the flexible capacity of thermal power units has nothing to do with the abandonment rate of renewable energy. As the abandonment rate of renewable energy decreases, the optimal capacity of pumped storage, electrochemical energy storage, and hydropower units increases. When the power-abandonment rate of renewable energy is 5%, the optimal allocation capacity of thermal power flexibility transformation, pumped storage, electrochemical energy storage, hydropower unit, and adjustable load in Province A is 5313, 17 090, 5830, 72 113, and 4250 MW, respectively. Under the condition that the renewable-energy abandonment rate is 0, 5%, and 10% respectively, the configured capacity of pumped storage is 20 000, 17 090, and 14 847 MW, respectively.

Coordinating regulation reliability and quality of pumped storage units for renewables by a novel scheduling-control synergic model

As the largest electricity storage facility, pumped storage is crucial for power systems but faces significant trade-offs between regulation quality for variable renewable energy (VRE) and the reliability of pumped storage units (PSUs). The flexible regulation requirement necessitates frequent startup-shutdown cycling, part-load operations, and accelerated wear of PSUs, thereby jeopardizing their reliability. Limited research on refined PSU-level scheduling strategies compromises the reliability of PSUs and the operation of VRE systems, especially given the diverse unit characteristics within a plant. This work innovatively couples the hydraulic characteristics of PSUs with reliability-based scheduling order, proposing a refined dual-layer scheduling strategy composed of unit commitment and load dispatch within a Wind-Solar-Pumped Storage Hybrid System (WSPSHS). Meanwhile, this work breaks from the traditional independent research paradigm between scheduling and control, establishing a refined synergic approach that integrates 15-min-level scheduling with second-level power control. Furthermore, this approach supports the development of a reliability assessment model that includes metrics on effectiveness and regulation losses of PSUs. In a North China case study, four cases with different combinations of hydraulic characteristics and reliability-based scheduling orders are comparatively evaluated. The results demonstrate that: (1) the refined strategy considering hydraulic characteristics and reliability significantly improves the reliability of PSUs by 9.91%. (2) the approach can effectively regulate PSUs and manage the WSPSHS, maintaining the operating efficiency of PSUs above 90% and achieving a VRE consumption rate of 95.47%. (3) The techno-economic performance of plants can be significantly improved, reducing operational intensity and risks, particularly for low-reliability PSUs, without negatively impacting the regulation quality of the hybrid system. This work can be extended to other energy systems with PSUs for effectively balancing VRE regulation demands with PSU reliability, and offering insights for reliable and efficient operation of power stations and grids.

Short-term load distribution model for giant cascade serial diversion-type hydropower stations

With the development of complex cascade serial diversion-type hydropower plants (CSDHP) in Southwest China, it has become imperative to study short-term scheduling challenges that are distinctive to this type of hydropower facility. Unlike conventional cascade hydropower stations, which have large reservoirs to regulate the outflow between stations, the CSDHP system consists of several diversion-type hydropower plants connected in series, requiring strict matching of turbine discharge between upstream and downstream facilities. In addition, these plants impose complex operation constraints, such as multiple units sharing one tunnel, which greatly increases the difficulty of short-term scheduling. This paper proposes a short-term optimal scheduling model for CSDHP systems aimed at achieving efficient load distribution among units while minimizing water consumption. The model takes into account the strict matching of turbine discharge and the complex constraints of multiple units sharing one tunnel. Subsequently, the model is transformed into a mixed integer linear programming problem using specified linearization techniques, with complexity further addressed via an iterative resolution method. A case study of a cascade illustrates the model’s efficacy in facilitating effective unit load distribution under complex hydraulic and electrical constraints, which substantially reduces the system’s water consumption by up to 6.1% during the dry season and 1.8% during the flood season, and reducing the number of crossing forbidden zones by 50.0% and 52.0%, respectively. The result shows the models’ potential to enhance day-ahead scheduling for the CSDHP system.

Stress Wave Propagation and Decay Based on Micro-Scale Modelling in the Topology of Polymer Composite with Circular Particles.

This article deals with stress wave decay performance, analysing the stress wave propagation generated by an impulsive unit load in a 2D representative unit cell (RUC) of a polymer composite with circular particles representing spherical particles, elliptical particles, and short fibres. The micro-scale numerical simulation uses explicit finite element analysis (FEA). The micro-response to an impulsive unit load creates a stress wave amplitude interacting with the material structure and tends to weaken and absorb energy. The stress wave damping is determined by the decaying amplitudes of Mises stress at the front of the stress wave. The stress wave damping is evaluated for different ratios of tensile modules and material densities of matrix and reinforcing material and other factors, such as percentage and particle size, applied to nine topologies of RUCs, and even the presence of an interfacial region is analysed. Moreover, the article visualises the phases of stress wave decay in various particle distributions, i.e., various topologies. Analysing the different topologies of the same particle volume (area) percentage, the study proved that the composite topology and resulting wave-particle and wave-wave interactions are other sources of material damping. The presence of even a small percentage, 3.5 area%, of reinforcing circular particles in the matrix brings a significant increase in stress wave damping up to about 40-43% (depending on the topology) compared to a homogeneous matrix with stress wave damping of 12.5% under the same conditions. Moreover, the topology with the same volume (area) percentage can increase particle stress wave damping by 15.3%.

Dynamic Equivalents of Active Distribution Networks Based on Active Synthesis Load Units

Dynamic Equivalents of Active Distribution Networks Based on Active Synthesis Load Units

Experience sharing on abnormal handling during operation of 350MW DC boiler after major overhaul

Recently, during the commissioning period of a 350MW DC boiler in a certain power plant, multiple abnormal situations occurred, which are relatively rare. For example, in normal operation, when the oil pressure of the supply fan suddenly rises to 10MPa full range, the moving blades of the supply fan cannot be adjusted, resulting in an automatic decrease in fan output, negative pressure fluctuations, and a decrease in unit load; Oil leakage in the control oil pipe of the air supply fan, causing a decrease in system oil pressure; A large amount of steam leakage occurs in the water valve of the warm valve; Leakage and other issues with the cooling water control valve of the superheater. Serious impact on the safe operation of the unit. Through summary and analysis, the root cause problem was ultimately discovered and thoroughly solved. This article mainly summarizes the analysis of abnormal causes and the sharing of experience in the handling process.