Loading Problem Research Articles

Rooftop Solar PV, Coal Plant Inflexibility and the Minimum Load Problem

Australia’s National Electricity Market (NEM) has amongst the highest take-up rates of rooftop solar PV in the world. As with California, this has produced a distinctive load shape termed the “duck curve.” The Queensland version is being principally driven by non-scheduled (i.e., uncontrolled) rooftop solar PV. When combined with inflexible coal plant, it leads to a “minimum load problem.” In this article, we examine the feasibility of dispatch with ever-expanding rooftop solar PV resources in the NEM’s Queensland region and minimal demand elasticity. We find episodes of intractable dispatch throughout the year with rising intensity in the winter and spring months. Furthermore, we find no ability to “export your way out of the problem” via larger interstate interconnectors because the same problem is emerging in the adjacent region at the same time. Resolution ultimately requires inflexible coal plant exit, and entry of flexible plant. JEL Classification: D25, D80, G32, L51, Q41

Hierarchical porous MnO2/3D graphene oxide/carbon cloth used as practical mass-loading supercapacitor electrodes

Supercapacitor electrodes with high mass loading of active materials often exhibit low areal capacitances due to stacking problem of heavy loading. In this study, we present a 3D hierarchical porous graphene oxide (GO) nanosheets grown on carbon cloth (CC), termed as 3DGO/CC. With its high specific surface area, ample space to accommodate the volume expansion, and ideal ion transfer pathways, 3DGO/CC emerges as a promising candidate for high-loading active materials. Utilized as an efficient support matrix for MnO2 loading, an ultrahigh mass loading of MnO2 (17.32 mg cm−2) is deposited onto the surface of 3DGO, forming a MnO2/3DGO/CC electrode without stacking. The conductive porous 3DGO/CC composite scaffold optimizes the utilization of MnO2 active material, resulting in a high areal capacitance. An optimal electrode achieves an impressive areal capacitance of 3.18 F cm−2 at 1 mA cm−2 which was 4.1 times higher than that of the pristine MnO2/CC electrode and maintains a retention of 74.5 % at 32-fold current density. Ultimately, the assembled asymmetric supercapacitor demonstrates a superior electrochemical performance with a maximum energy density of 495.36 μWh cm−2 at the power density of 1.02 mW cm−2. This study supplies an efficient method for preparing MnO2-based electrodes with excellent areal capacitance.

Research into multi-directional high stability techniques in the same plane for satellite static testing

In order to ensure the structural strength reliability of spacecraft base plate during launch and operation, it is necessary to perform the structural strength test of load synchronous loading on the base plate in the same plane to evaluate its structural bearing capacity under certain axial and shear loads. In order to meet the test requirements and simulate the real stress condition of the base plate, a reliable implementation scheme is proposed in this paper. Multi-directional uniform loading of a satellite base plate is completed by using the same plane multi-directional high stability test technology. The mechanical test of a satellite using this technology shows that the test strain is consistent with the theoretical simulation deformation. This technology effectively solves the problem of uniform loading in the same plane of the satellite base plate in mechanical testing.

Design and Simulation Analysis of Bridge Anti-collision Structure based on Nonlinear Numerical Simulation

In order to solve the dynamic nonlinear problem of bridge loads and responses during ship collisions, a design method for bridge anti-collision structures based on nonlinear numerical simulation was proposed. The author describes in detail the entire process of collision force evolution, energy conversion, and plastic deformation of the anti-collision energy dissipator, and conducts a comprehensive simulation of it. The experimental results show that when a ship with a mass of 1000 tons collides forward at speeds of 1, 3, and 5 meters per second, the collision depth is 0.23, 1.46, and 3.95 meters, respectively, less than the maximum allowable collision depth of 4.3 meters, and the collision energy dissipator is still in the protective working state for the bridge pier. When a ship with a mass of 3000 tons collides with the collision avoidance energy dissipator at a speed of 3 or 5 meters per second, the collision depth exceeds the maximum allowable collision depth, and the collision avoidance energy dissipator fails, the ship will directly collide with the wharf. The plastic deformation of the anti-collision energy dissipator provided has important reference value for design.

Two-phase matheuristic for assignment and truck loading problems

We introduce a novel two-phase matheuristic for assignment and truck loading. The scope of our approach involves scenarios with an extensive amount of items requiring assignment to a heterogeneous fleet of trucks and subsequent transportation. A distinguishing feature of our matheuristic lies in the fact that the complex underlying problem is divided into subproblems which later are merged into a global solution. The proposed matheuristic tackles the assignment problem in its first phase, followed by a complex truck loading algorithm to validate the assignment solution in the second phase. This enables the identification of optimal solutions and adaptability to diverse use cases. This approach is motivated by the ROADEF/EURO challenge 2022 and is awarded with the scientific prize of the challenge. We demonstrate superior performance on selected instances, showcasing the potential for significant cost reduction in Renault’s supply chains.

Влияние глубины и интенсивности сезонных колебаний на деятельность гостиниц

Currently, hospitality enterprises are faced with the problem of loading the number of rooms. At the same time, many hotels are faced with seasonal fluctuations in the volume of sales of hotel services. This situation leads to a lack of profit in certain periods, uneven workload on the enterprise and personnel, etc. Different types of hotel enterprises are affected by seasonality to varying degrees. Seasonality is relevant for various hotels, both resort and city. At the same time, each hotel may have its own seasonality: the factors that caused seasonal fluctuations differ. In some cases, these are climatic conditions, in others, event events in the region, focus on serving a certain segment, etc. Thus, the impact of seasonality on hotel operations should not be underestimated. The main problem here lies in the need to forecast the volume of sales of services, taking into account seasonal fluctuations. When assessing the impact of seasonality on sales volumes of hotel services, it is necessary to take into account such parameters as the depth, intensity, and duration of seasonal fluctuations. The object of research in this article is the GRINN hotel complex, located in the city of Orel. The study of seasonal fluctuations for this hotel enterprise is relevant. The work uses a method for determining seasonal fluctuations, which consists in calculating seasonality indices. They were calculated as a percentage of average monthly levels for a number of years to the total average monthly volume of services sold for the entire billing period. For the calculation, reporting data provided by the GRINN Group of Companies for six years (2017-2022) were used. First of all, the attendance of the GRINN Group of Companies was analyzed, as well as load factors. The data obtained made it possible to calculate seasonality indices. On their basis, “seasonal waves” were built. At the same time, a comparison was made between the pre-pandemic period and the pandemic period. Next, we compared the load factor and turnover in the GRINN Group of Companies. During the research, the following results were obtained. The maximum attendance of the hotel complex was noted in 2022 (38,832 people), the maximum average annual occupancy rate was in 2019 (50.3%). The year 2020 was the least successful year for the company, which was due to the coronavirus pandemic. In 2021-2022, a gradual recovery of indicators begins. In general, the following conclusions were drawn. The GRINN Group of Companies is characterized by minor seasonal fluctuations. They are determined by the specifics of this hospitality enterprise. Since the company is focused on serving organized groups and business tourists, attendance is influenced by the business activity of the region, as well as event events. In addition, it was established that there is no close connection between the occupancy level of a hotel and its profitability. It was proven that fewer customers can generate more revenue and vice versa. It was determined that the GRINN Group of Companies has the necessary potential to combat seasonal fluctuations.

Deriving Ritz formulation for the Static Flexural Solutions of Sinusoidal Shear Deformable Beams

This paper presents the Ritz variational method for the static bending analysis of sinusoidal shear deformable beams. The theory accounts for transverse shear deformation and satisfies transverse shear stress-free conditions at the top and bottom surfaces of the beam. The total potential energy functional for the thick beam bending problem is formulated and minimized using a Ritz procedure. The problem considered simply supported boundary conditions and two cases of loading – uniformly distributed load over the span and point load at the center. The function is a function of two unknown displacement functions constructed in terms of unknown generalized displacement parameters and shape functions that satisfy the boundary conditions. Ritz minimization of the functional is used to find the generalized displacement parameters and then the displacements w(x) and The displacements and stresses are found for the loading distributions considered. It is found that the results obtained agree remarkably well with the exact results obtained using the theory of elasticity. The differences between the present results and the exact solutions are less than 0.3% for maximum transverse displacement for both cases of loading considered. For uniform load over the beam, the result for l/t = 10 is 0.112% greater than the exact solution. For the point load at the center, the result for l/t = 10 is 4.468% greater than the exact solution. The increased difference in the point load case is due to the singular nature of the point load problem.

Optimizing smart home appliance energy monitoring using Factorial Hidden Markov Models for Internet of Behavior

The energy demand which is increasing globally strongly underlines the necessity of solutions that will improve power efficiency. This study addresses the research problem of enhancing energy management in smart homes through Non-Intrusive Load Monitoring (NILM), a method that enables consumers and companies to optimize their energy usage by disaggregating total household energy consumption into specific appliance-level data. The research focuses on the creation and establishment of an Internet of Behavior (IoB) model that encourages NILM to develop more energy-efficient and clever residential buildings as its main goal. The Factorial Hidden Markov Model (FHMM) is employed as the core methodology in this NILM process, facilitating the disaggregation of overall household energy usage into individual appliance consumption patterns. This method was used over the known Reference Energy Disaggregation Dataset (REDD) for comparing the actual energy consumption of the appliances with the projected estimates. The results are evidence that the FHMM method is an energy disaggregation technique that can provide important information about the customer usage of energy and, hence will help in the strategic shifting of high-energy appliances to non-peak hours for the user. This study's main value lies in the new application of IoB-based NILM methods to increase energy efficiency, which is the real solution for energy costs and the grid peak load problem. The results of the proposed method are compared with other methods and real data. The comparisons show the acceptable response of the proposed method when it is compared with the real data and is better than another method.

The Influence of Rural Ecological Environment Development by China's Industrialization Process

This article aims to solve the problem of heavy pollution load in rural ecological environment at present. This article elaborates on the relevant concepts and theories of rural industrialization and ecological environment protection, mainly using a combination of qualitative and quantitative methods to analyze the current situation of rural ecological environment pollution in the research area. The research results indicate that the current rural ecological environment pollution load in China is heavy and severe, especially the use of fertilizers, pesticides, agricultural plastic films, livestock and poultry breeding, rural life, and township enterprise production, which have caused varying degrees of harm to the regional rural ecological environment. Therefore, effective measures must be taken to achieve the organic combination of rural industrialization and ecological environment protection. This article provides guidance for promoting the optimization and upgrading of rural industrial structure, achieving a win-win situation of economic and ecological benefits.

Integrated packing and routing: A model and its solutions

This paper introduces the two-level vehicle routing and loading problem (2L-VRLP), an innovative model integrating the two-level bin packing and vehicle routing problems to address real-world logistics challenges that require simultaneous packing and transportation decisions. By capturing the essence of dual-level packing (boxes onto pallets, pallets onto vehicles) and optimising vehicle routing, the 2L-VRLP offers an integrated framework that outperforms traditional separated models, demonstrating superior solutions that align closely with practical logistics operations. We propose a set of heuristic algorithms tailored for the 2L-VRLP’s unique requirements and explore automated algorithm selection using an artificial neural network (ANN), marking a step towards incorporating machine learning in logistics optimisation. This work not only showcases the 2L-VRLP model’s potential to enhance logistics management but also sets the groundwork for future research and applications in this domain.

Multi-objective multi-population simplified swarm optimization for container loading optimization with practical constraints

The container loading problem (CLP) holds significant importance in logistics and supply chain management due to its direct influence on transportation costs and times, thereby impacting the competitive advantages of enterprises across industries. Although there are existing studies for CLP, there remains a gap in addressing the optimization of multiple objectives while satisfying practical constraints. Moreover, container loading methods must also meet performance requirements such as high computational speed, explainability, and implementation capability. Although meta-heuristic-based algorithms have shown effective computational capabilities and performance, such algorithms often being trapped in the local optima especially when searching in the vast solution space of the CLP, particularly as the quantity and diversity of cargo sizes and shapes increase. Motivated by realistic needs, this study aims to develop a UNISON-based framework that integrates the merging spaces algorithm, a novel simple but effective hybrid simplified swarm optimization genetic algorithm (SSO-GA), and a multi-populations co-evolution strategy to determine the loading sequence of parcels to maximize space utilization and weight balance while satisfying to practical constraints. Specifically, the merging spaces algorithm merges fragmented small spaces resulting from loaded parcels into larger spaces, thereby facilitating the accommodation of additional parcels. The hybrid SSO-GA splits encoded solutions and updates segment using novel strategies resulting in the rearrangement of a group of parcels and their corresponding layouts for better space utilization. Furthermore, the multi-populations co-evolution strategy enhances the diversity of the search space and stabilizes solution quality by simultaneously exploiting the best solutions and exploring alternative solutions during the solution update process. An empirical study was conducted by using a public benchmark dataset which demonstrated the practical effectiveness of the proposed framework by significantly improving average space utilization while ensuring center balance and satisfying practical constraints. Furthermore, this study can also serve as a digital support system capable of assisting decision-makers in optimizing container loading operations, thereby improving productivity and saving valuable time.

Distributionally robust planning for power distribution network considering multi-energy station enabled integrated demand response

—To copy with the peak valley difference and peak load problem of power distribution network (PDN), this paper proposes a distributionally robust planning model for PDN considering the flexible management via the multi-energy station (MES) based integrated demand response (IDR). The planning covers reinforcement of the existing substation and feeders as well as the investment of MES and IDR. The IDR involves the incentive interruptible load response (ILR), transferable load response (TLR) and price-based power-gas substitution (PGS) which is implemented on MES. The MES integrates multiple energy storages and energy coupling devices, which is served as a platform for PDN operator to centrally track the final demand and improve the response potential of IDR. The proposed planning method aims at minimizing the present value of PDN investment cost and operation cost during the planning period. To handle the uncertainty of PDN end-use loads, a two-stage Kullback–Leibler divergence (KLD)-based distributionally robust optimization (DRO) planning model is formulated. Finally, the columns and constraints generation algorithm is utilized to solve the KLD-DRO planning model. Case studies are carried out on a practical 152-bus urban distribution system to validate the effectiveness of the proposed methodology and quantitatively analyze the key influence factors of PDN investment.

Optimal chiller loading considering the energy loss associated with the switching of chillers based on a novel hybrid fuzzy-metaheuristic method

In existing research, the energy loss associated with the switching of chillers has not been taken into account when addressing the traditional optimal chiller loading (tra-OCL) problem. Chillers incur a certain amount of energy loss during the switching process in practical operations. Hence, it is crucial to investigate the optimal chiller loading problem considering the energy loss associated with the switching of chillers (loss-OCL). In this study, we propose a novel parameter adaptation imperialist competitive algorithm based on parallel fuzzy inference systems (PA-ICA-PF) to solve the loss-OCL problem. Three operators—velocity adaptation, velocity divergence, and mutation-crossover—are introduced to enhance assimilation, revolution, and imperialist competition stages. Two fuzzy inference systems are utilized to concurrently guide searches in the solution space, ensuring a balance between diversification and intensification. The proposed method was experimentally verified in an actual multi-chiller system. Experimental results indicate that the total energy consumption of the system, when addressing the loss-OCL, is significantly lower than the actual value but slightly higher than the tra-OCL. This suggests that the proposed method is capable of obtaining the optimal partial load ratio of chillers while accounting for energy losses. To further validate the effectiveness of the proposed algorithm, we compared it with existing algorithms. Experimental results demonstrate that the proposed PA-ICA-PF method exhibits the best performance.

Improving safety criteria for transporting hazardous goods by road through optimizing the geometric parameters of their stowage

The object of research is the process of cargo transportation by road. The problem of efficient loading and securing of hazardous goods in box containers during their transportation by road is considered. The basic principles of the voxel-based interpretation of the model of loading box containers on road transport are presented, and a general principle for calculating the fractal dimension of such three-dimensional objects has been developed. The calculation is based on the procedure of reducing the dimensionality of space by cutting the object into separate layers and determining the fractal dimensionality of two-dimensional slices. The proposed principle could be used to estimate the fractal dimension of three-dimensional objects in practical tasks in any industry. A method for simplified calculation of fractal characteristics of three-dimensional bill of lading models of cargo stowage has been devised. The method is based on the assessment of the quality of blocking of the constituent elements of the spatial system in three coordinate directions by the fractal dimension of two-dimensional images of their frames. The method provides opportunities for calculating the quantitative characteristics of the quality of cargo stowage from the standpoint of its transportation safety. A method for fractal stowing of goods in box containers on a truck platform has been proposed. This method of fractal stowage provides for the absence of slippage and displacement of boxes in the package and makes it impossible for them to overturn in extreme situations. The use of the fractal stowage method allows for an efficient and low-cost technology of securing the cargo as it involves only a circular bandage of the top layer of the loaded package of boxes and its fastening to the vehicle platform at four points

HE EFFECT OF LOADS SUPERPOSITION ON TECHNICAL STRUCTURES, ENVIRONMENT AND LIVING ORGANISMS

The current state of calculation the result of the superposition of loads, or their effects, on a material body is analyzed. The limits of the current calculation methods, based on strength theories, in the case of technical structures are shown. The results of experimental research that refer, in general, to the superposition of two loads of the same nature and without addressing problems of loads of a different nature (mechanical, chemical, electrical, magnetic, radioactive etc.), in the case of technical structures and the environment is analyzed. Starting from the principle of critical energy, which is based on the concepts of the total specific energies’ participation of the loads and of the critical participation, general relations are deduced for these concepts, in the case of the nonlinear behavior of matter, as a function of power. These results are applied to the calculation of the superposition of loads of different nature on a technical structure, the environment and living organisms, taking into account the deterioration of matter. The influence of the loading speed (static, shock ...) is taken into account based on the value of the exponent in the behavior law, which was not possible in the previous calculation methods. From the analysis of the results obtained in the paper, it is found the utility and the high degree of generality of the principle of critical energy and of the concept of the specific energy participation.

Air cargo transportation, loading, and phase-based maintenance service scheduling in demand channel routes

The article proposes an approach for modeling and solving the air cargo transportation, loading, and phase-based maintenance scheduling problems within demand channels. Demand channel transportation presents unique challenges to meeting the earliest pickup and delivery requirements during emergencies. The complexities in transportation involve issues with airport-aircraft compatibility, fleet selection, task assignments, route construction, and effective loading–unloading procedures. The challenges include coping with flight connections due to airport-aircraft compatibility, dealing with limited refueling and maintenance facilities, and swiftly adapting to unforeseen maintenance events by identifying and utilizing available fleets. In this context, the article delineates a demand channel route planning strategy that considers airport-aircraft compatibility, task integrity, priority, partial refueling strategy, and maintenance schedules spanning short to long-haul phases. Formulated as a Mixed Integer Linear Programming (MILP) problem, the solution employs a novel acyclic route construction procedure within a fuel-conscious network. We propose an insertion heuristic with multi-faceted algorithmic interconnections for producing a near-optimal solution suitable for real-world applications. Our insertion procedure has been shown to have very high computational performance, with an average 1.32 percent optimality gap. It can be scaled up to the most critical cargo mission, with up to 190 ports, 95 aircraft, and 380 tasks.

Dynamic response strength of integrated foundation for multiple wind turbines

The focus of this paper is on the conceptual design of offshore multi wind turbine integrated floating foundation (MWF) and the strength analysis method of floating structures considering motion response. Firstly, the maximum environmental load and ultimate motion attitude of MWF were used as boundary conditions to solve the problem of imprecise constraint loads in traditional analysis methods. Then, a stress solving equation based on motion state and inertia release was established to solve the equivalent accuracy problem of floating body motion state. Finally, through theoretical analysis, numerical simulation, and experimental testing, it was found that the stress solution method considered the motion state of the floating body in this paper to be more accurate and reliable, with an error of less than 10% compared to the stress results of experimental testing. Improved calculation accuracy by 30%. These studies provide more accurate analytical methods and theoretical references for predicting the strength of floating structures in actual oceans.

The parallel stack loading problem of minimizing the exact number of relocations

This study addresses the parallel stack loading problem, a general optimization problem arising in storage facilities such as container yards, slab yards, and warehouses. In this problem, we load incoming items into parallel stacks in the loading phase to minimize the number of relocations in the subsequent retrieval phase. Because of difficulties in treating the nested problem structure originating from the mutual dependence of the two phases, the existing studies approximately minimized the number of relocations using surrogate objective functions. In contrast, this study considers the parallel stack loading problem aiming to minimize the exact number of relocations. We first provide an integer programming formulation and next develop a nested branch-and-bound algorithm. In a computational study, we verify the effectiveness of the proposed branch-and-bound algorithm and evaluate the known surrogate objective functions based on the exact minimization.

Physics-informed machine learning for moving load problems

Abstract This paper presents a new approach to simulate forward and inverse problems of moving loads using physics-informed machine learning (PIML). Physics-informed neural networks (PINNs) utilize the underlying physics of moving load problems and aim to predict the deflection of beams and the magnitude of the loads. The mathematical representation of the moving load considered involves a Dirac delta function, to capture the effect of the load moving across the structure. Approximating the Dirac delta function with PINNs is challenging because of its instantaneous change of output at a single point, causing difficulty in the convergence of the loss function. We propose to approximate the Dirac delta function with a Gaussian function. The incorporated Gaussian function physical equations are used in the physics-informed neural architecture to simulate beam deflections and to predict the magnitude of the load. Numerical results show that PIML is an effective method for simulating the forward and inverse problems for the considered model of a moving load.

Performance Comparison of Zevenet Multi Service Load Balancing with Least Connection and Round Robin Algorithm

Amikom Purwokerto University concentrates on Technology and Digital Business. This requires technology to be utilized optimally. The use of technology, especially internships, will make various jobs easier. KRS online is taking lecture schedules online via the AMIKOM Purwokerto Student website. There are several problems with the web server that arise due to the increasing need for information access, which causes the data traffic load to increase. Increased data traffic causes workload overload, resulting in server downtime. Experimental methods were used in this research to look for the causes of the web server's downtime. Then, implement the technology. The purpose is to evaluate the Zevenet load balancer performances by comparing the round-robin and least-connection algorithms. The decision is which algorithm will be used best to implement the Zevenet Load balancer to achieve a more efficient backend server traffic cluster distribution. The TIPHON standard Quality of Service parameters used in Zevenet Load Balancer performance testing are throughput, delay, jitter, packet loss, and CPU usage. The quality-of-service parameter test results show that the Zevenet Load Balancer with the round-robin algorithm has superior performance and shows less CPU usage. It is concluded that using the round-robin algorithm in implementing the Zevenet load balancer to overcome the problem of data traffic load sharing and minimize server downtime on the Student Amikom Purwokerto web server is more appropriate and more effective.