Minimum Operating Research Articles

Resilience enhancement strategy of multi-energy coupling distribution network considering movable energy storage equipment

With the deepening of energy transformation, multi-energy coupling has become an effective method to alleviate the energy gap and improve the energy utilization rate. As a bridge connecting users and the power system, the distribution network is becoming multi-energy coupling as well. Therefore, to ensure a stable supply of power, heat, and other energy sources, it is of great significance to study the resilience improvement of multi-energy coupling distribution networks. This paper proposes a strategy for improving the resilience of multi-energy coupling distribution networks considering movable energy storage equipment (MESS) configuration. Firstly, the multi-energy coupling distribution network model is established, and the mathematical model of each piece of equipment is established considering the coupling of the power grid and heat grid. Secondly, based on the loss of load probability (LOLP), considering the importance of the load, it is expanded to the loss of important load probability as an index to evaluate the resilience of distribution networks. Thirdly, a distribution network resilience improvement model based on the configuration and operation of the MESS is established, and the optimal configuration capacity and operation strategy of the MESS is solved by taking the minimum operation cost as the objective function, i.e., the configuration cost of the MESS, the load shedding cost and the cost of wind and PV abandonment. Finally, based on the IEEE-33 node distribution network, a multi-energy coupling distribution network model is built, which verifies that the method proposed in this paper can effectively reduce the total cost and improve the resilience of the multi-energy coupling distribution network.

Understanding the Operating Speed Profile Patterns Using Unsupervised Machine Learning Approach: Short-Term Naturalistic Driving Study

Several studies have measured the minimum operating speed on horizontal curves to model the operating speed to assess the geometric design consistency. Most of these studies approximated equal lengths of deceleration and acceleration in the operating speed profiles for the curves and assumed the minimum operating speed position at the midpoint of the curve. In contrast, a few recent studies showed different percentages of deceleration lengths on the curve and measured the minimum operating speed at the deceleration end on the curve to model the operating speed. A defined pattern of the operating speed profile on the horizontal curve was not reported in the previous studies and therefore presents opportunities to determine the patterns of the operating speed profiles on curves. In this study, the operating speed profiles of different drivers for the given features of the horizontal curve were studied, and the clustering technique was used to categorize the different patterns in the operating speed profiles on horizontal curves. The optimal number of clusters was determined using four methods: silhouette, elbow, gap statistic, and NbClust function. The different patterns observed from the clustering results are as follows: (1) complete deceleration on the curve, (2) complete acceleration on the curve, (3) deceleration length slightly greater or lower than acceleration length, and (4) longer deceleration/acceleration lengths followed by shorter acceleration/deceleration lengths, respectively. The study results imply that all operating speed profiles are not symmetric around the midpoint of the curve (MC), and the group of drivers exhibited defined patterns of the operating speed profiles on the curves. This study helps in understanding the different patterns of operating speed profiles exhibited by the drivers and the measurement of the minimum operating speed at the deceleration end to model the operating speed to assess the geometric design consistency.

Design and Experiment of Discharge Control Methods for Three-Stage Coil Gun Experiments

The aim of this study was to design operation methods for three-stage coil gun experiments and to fabricate and compare prototypes of control systems using these methods. Two methods are proposed: (1) recognizing the position of a projectile using a photointerrupter and (2) operating a control circuit to supply power to a silicon-controlled rectifier when the projectile reaches an intended position by registering the delay time between coil gun operations. The distance between the projectile and the solenoid coil during a coil gun operation is a key design factor. For the multi-stage coil gun manufactured in this study, the discharge time must be determined according to the position of the projectile, which moves at high velocity. Therefore, the selected method should have minimal operation error and allow the circuit to be easily used according to the coil gun stage and configuration. This study compares the prototypes of coil gun discharge circuits that were fabricated based on the proposed methods by applying them to three-stage coil guns and measuring their velocities. The findings of this study could be used to suggest design methods for experimental models for coil guns with fewer stages according to the final velocity and coil gun stage to be manufactured.

The economics of global green ammonia trade – “Shipping Australian wind and sunshine to Germany”

This paper contributes to understanding the transformation of global energy trade to green energy carriers, focusing on green ammonia as the foreseeable first green hydrogen carrier. We provide a comprehensive overview of today's ammonia trade and assess scaling options for the trade of green ammonia. To that aim, we develop an optimization model for the integrated assessment of the green ammonia value chain that covers all steps from green ammonia production in an exporting country, up to delivery to a harbor in an importing country. The model endogenously chooses among different technology options and determines cost minimal operation. In a case study, we apply the model to the large-scale import of ammonia from Australia to Germany in a scenario for 2030. The results show that green ammonia can reach cost parity with gray ammonia even for moderate gas prices (but not necessarily with blue ammonia) if CO2 prices are high enough. We also provide a sensitivity analysis with respect to the interest rate and other key technical and economic parameters and show that cracking ammonia to provide pure hydrogen comes at a 45% cost markup per MWh at the destination.

Exergoeconomics evaluation on optimal operation conditions in crude oil gathering and transportation system

ABSTRACT At present, most of the energy analysis of the engineering system is only from the energy point of view. In this paper, the theory of exergoeconomics is combined with the operation optimization of the gathering and transportation system. In terms of exergy flow distribution and the construction of each equipment, the exergy value of total 17 exergy flows and the non-energy cost of 6 main equipment in the process are calculated. An exergoeconomic model in technological process of gathering and transportation system is established. Combined with the exergoeconomic cost valuation strategy, 11 auxiliary equations are used to get the economic cost of each flow unit in the process. Taking the minimum operation exergy cost as the objective function, a mathematical model of operation optimization in exergoeconomics is established, and each decision variable is constrained on the basis of the actual site conditions. The objective function within the range of process requirements is solved by iterative method. The optimal water mixing temperature is 47.1°C, and the optimal water mixing volume is 840.7 m3/d under the actual working condition of the site in light of the calculation results.

Multi-energy optimization under the water-energy-carbon nexus in a typical iron and steel plant

The multi-energy system in iron and steel plants has strong coupling characteristic, which makes the energy distribution complex and difficult in energy management. Additionally, the steel works is a manufacture process with high-carbon emissions, and it is vital to assess the environmental stress from the sights of nexus between energy, water and carbon emission. In this study, a multi-energy and multi-objective mixed integer non-linear programming (MINLP) model is established to optimize the energy system under the water-energy-carbon nexus in iron and steel plant. And the multi-energy is considered the couple of gas-steam-electricity. The multi-objective functions include the economic performance, the CO2 emissions, the water generation, and the global energy efficiency. Due to the contradictory of the objective functions, the utopia tracking approach is used to normalize and assess the functions. To fit the actual situation of the equipment, this paper made a fitting curve for the energy efficiency of the equipment. The minimum economic operation cost results show that the studied iron and steel plant has great potential in reducing economic cost (7.6 %), emission mitigation (4.7 %), system water production improvement (807 t) and global energy efficiency (54.48 %). Besides, the research will help the iron and steel plant to reach the carbon peak and carbon neutrality target.

Risk Factors of Perioperative Brain Injury in Children Under Two Years Undergoing Coarctation Repair

BackgroundTo investigate clinical manifestations and factors of perioperative brain injury (PBI) after surgical repair of coarctation of the aorta (CoA) combined with other heart malformations under cardiopulmonary bypass (CPB) in children under two years. MethodsThe clinical data of 100 children undergoing CoA repair were retrospectively reviewed between January 2010 and September 2021. Univariate and multivariate analyses were performed to identify factors of PBI development. Hierarchical and K-means cluster analyses were conducted to evaluate the association between hemodynamic instability and PBI. ResultsEight children developed postoperative complications, and all of them had a favorable neurological outcome one year after surgery. Univariate analysis revealed eight risk factors associated with PBI. Multivariate analysis indicated operation duration (P = 0.04, odds ratio [OR], 2.93; 95% confidence interval [CI], 1.04 to 8.28) and pulse pressure (PP) minimum (P = 0.01; OR, 0.22; 95% CI, 0.06 to 0.76) were independently associated with PBI. The following three parameters emerged for cluster analysis: PP minimum, mean arterial pressure (MAP) dispersion, and systemic vascular resistance (SVR) average. Using cluster analysis, PBI mainly occurred in subgroups 1 (12%, three of 26) and 2 (10%, five of 48). The mean value of PP and MAP in subgroup 1 was significantly higher than in subgroup 2. The mean SVR in subgroup 1 was the highest. The lowest PP minimum, MAP, and SVR were observed in subgroup 2. ConclusionLower PP minimum and longer operation duration were independent risk factors for developing PBI in children under two years during CoA repair. Unstable hemodynamics should be avoided during CPB.

D-overlap functions: Construction, characterization and ordinal sum representation

In this paper, we focus on the so-called D-overlap functions defined over grid of unit square, which are a class of discrete aggregation operators. The core contents are: (i) it proposes the notion of D-overlap functions and shows three construction methods for D-overlap functions in virtue of n-dimensional semi-quasi-overlap functions, convex combination and I-matrixes; (ii) it gives equivalent characterization of D-overlap functions using I-matrixes and, by upper triangular matrix, a representation of the minimum operator min is got; (iii) it provides ordinal sum representation of 1-Lipschitz D-overlap functions. These theoretical results can facilitate the applications of overlap functions related theory in real problems involving qualitative information fusion, especially in expert systems, pattern recognition and statistical data processing.

A Multi-Period Model for Optimal Changi Airport Check-In Counter Operations

Growth in air passenger flow has caused severe congestion at the airport check-in counter, posing a significant problem for airport management. Particularly during the check-in process, the necessary authorities must coordinate sufficient facilities with adequate staffing levels. The airport check-in counter problem (ACCAP) is a field concerned with establishing the optimal number of check-in counters to balance operating expenses and passenger wait times in order to reduce airport congestion. Expanding the number of counters and staff to a minimum operating cost is able to prevent the congestion problem from escalating without incurring further operating expenses. This paper focused on proposing optimal scheduling of airport check-in counters operations, including staffing. A dynamic model with multi-period principles is adapted to address the aforementioned problem by balancing the trade-off between service performance and operational cost. As a case study, data from Singapore Changi International Airport was utilized. The findings are also discussed in terms of the flow of passengers throughout the airport check-in procedure and operations. As a result, the number of activated counters is minimized throughout all shifts by applying the dynamic model at the average service time. At the same time, there are fewer passengers in the queue.

A 79 pW, 106 ppm/°C NMOS-only current reference with leakage current isolation based on body bias technique

A pico-watt, NMOS-only current reference has been proposed and simulated using 0.18-μm deep N-well CMOS process in this paper. To significantly reduce the power consumption to 79 pW and minimal operating voltage to 0.8 V, body bias technique is introduced. A level shift is proposed and used for isolating the N-channel/P-sub diode leakage current, which decrease the temperature coefficient to 106 ppm/°C when temperature changes from 0 to 125 °C. Besides, the line sensitivity and line regulation are obtained as 1.39%/V and 0.31%/V, respectively.

Ensuring the Reliability of Gas Supply Systems by Optimizing the Overhaul Planning

The aim of the article is the development of methods for optimal overhaul planning of compressor station equipment. Nowadays, due to uncertainties in the forecast of gas supply flow rates, increasing the reliability and energy efficiency of main gas pipelines is an urgent problem. The dependence of operating costs for major repairs on the maintenance periodicity is extreme. Reducing equipment’s maintenance period leads to an increase in repair costs. It also increases the reliability of equipment operation. Overall, all these facts reduce the probability of emergency failures and related expenses for emergency recovery, gas losses, and undersupply to consumers. Therefore, an optimal maintenance frequency exists, at which the total operating costs will be minimal. A procedure for optimizing the periodicity of repairs and equipment replacement is proposed. It was realized by constructing an objective function as a dependence of exploitation costs on the inter-repair period of major repairs. A probabilistic approach was applied to assess the aging process. The characteristics of the equipment’s state are described by distribution densities (i.e., pre-repair, inter-repair, and full-service life), which vary depending on product initialization time. The main characteristics of major repairs are their duration and intensity, which are evaluated by the quality factor related to repair costs. The extremum of the objective function is sought by the method of competing options. It was determined that the optimal management of the frequency of equipment replacement can be realized by choosing the optimal values of the average service life, average operation time of units until the first planned and preventive repair, and quality factor. As a result, the required technical condition for the technological equipment is ensured under minimum operating costs without reducing the system’s reliability.

Mobile technology as a dependable alternative to language labs and to improve listening skills

There is an incessant gap between language acquisition and adoption of modern technologies, especially in semi-urban parts of economically growing countries in Asia. There is a need to establish infrastructure for Computer Assisted Language Learning (CALL), Information Communication Technology (ICT), Virtual Reality (VR), and Augmented Reality (AR) to enrich English Language Teaching. Though these types of establishments instil confidence and fluency among English learners, investment in procurement, running costs towards maintenance and service cost deter institutions from establishing Language Labs and Language studios. The objective of this study was to establish Mobile-Assisted Language Learning (MALL) in higher education institutions and enhance English fluency and accuracy with minimal operation and low maintenance cost. The study also methodologically shortlisted open-source mobile applications based on users' feedback on their user-friendliness, skill-levels, content, and options that promote Learners' Autonomy. A quantitative true-experimental study was conducted at the Vellore Institute of Technology, Vellore, India, to develop the listening skills of (n=121) students of first-year Bachelor of Technology in a varied branch. The pre-test and post-test results revealed improvements in the experimental group. The findings would immensely help the underprivileged to serve ESL learners from any part of the globe who intend to enhance their proficiency in English.

Optimal Operation of Integrated Energy Systems Based on Multi-Energy Coupling With Power-to-Gas Technology

Abstract Natural gas and renewable energy sources make up an increasingly large proportion of power generation due to their being environmentally friendly. Because of the intermittent and fluctuating output of renewable energy sources, the emerging technology of power-to-gas (P2G) units is of great significance to alleviate. This paper focuses on the coordinated optimization of the combined gas and electricity network (CGEN) system with bidirectional energy conversion. Gas-fired power generation (GPG) plants and P2G are considered as linkages between the two networks. A unified CGEN mathematical model is established with the minimum operation cost as the objective function. The injection and production process of underground natural gas storage (UNGS) is also taken into consideration that is not available in other literature. Variables such as the output of P2G and gas-fired power generation plants, the supply of UNGS, and the wind curtailment are optimized correspondingly. The improved 24-node power grid (PG) and Belgium 20-node natural gas pipeline network (NGPN) are adopted to test the validity and capability of the proposed model, and then we compare the results CGEN model with the single Belgium NGPN to analyze the impact on the NGPN. Moreover, we adopt a coupled operation system of a 6-node power system and a 7-node NGPN to further analyze the influence of P2G on the CGEN. The results show that compared with the system without P2G, the total operating cost of the system is reduced by 9.39%, the natural gas load shedding is reduced by 26.1%, and the wind curtailment is reduced from 326 MWh to zero.

An Experimental Method for Evaluating Ammonia Emission Rates of Bio-Curtain

Bio-curtain (i.e., curtain) is a permeable cover equipped with a spraying system for ammonia (NH3) control in a swine facility. Previous studies investigated the NH3 reduction effects primarily based on concentration units. It is challenging to determine the actual efficiency because of the large amount of air discharged through the large surface of the curtain, and external wind rapidly dilutes and disperses the exhausted air. Therefore, this study investigates a technique to evaluate the NH3 reduction effect of the curtain in terms of emission rate. We constructed a metallic cover with a single hole around the curtain to gather the air discharged through it. The NH3 reduction effect was calculated by comparing the NH3 emission rate that was monitored in the barn exhaust fan and at the single hole of metallic cover during the non-spray and spray treatments inside the curtain at the maximum and minimum operating rate of the barn’s exhaust fan. NH3 emission rates declined both non-spray and spray at the minimum operation rate of the barn exhaust fan, but the reduction effect was higher in spray conditions than non-spray. Accumulating NH3-absorbed water inside the curtain under the low ventilation of the exhaust fan caused these circumstances.

A reduced order model for triethylene glycol natural gas dehydration system

In natural gas processing plants, glycol dehydration is commonly used to remove water from the gas streams, to avoid pipeline blockage and equipment breakdown due to hydrates formation. This paper proposed a reduced order model developed based on integrated simulation-optimization approach for the glycol dehydration system, with the aim to minimize its operating cost while satisfying pipeline quality specifications. Steady-state process simulation software was used to identify important operating parameters for the glycol dehydration process; these include reboiler temperature and flow ratio of the regeneration column, and solvent flowrate. The identified parameters are built into a non-linear programming model, which was developed as a reduced order model for ease of implementation in the plant. The studied parameters are reboiler duties, hot oil, condenser, and pump, as well as TEG make-up flow rate and CO2 equivalent (CO2-eq) emissions. The Pareto Front is developed to identify the minimum operating cost at different levels of water dew point specification. The work has resulted in the annual savings of more than 34.6%.

Decentralized Energy Management System in Microgrid Considering Uncertainty and Demand Response

Smart energy management and control systems can improve the efficient use of electricity and maintain the balance between supply and demand. This paper proposes the modeling of a decentralized energy management system (EMS) to reduce system operation costs under renewable generation and load uncertainties. There are three stages of the proposed strategy. First, this paper applies an autoregressive moving average (ARMA) model for forecasting PV and wind generations as well as power demand. Second, an optimal generation scheduling process is designed to minimize system operating costs. The well-known algorithm of particle swarm optimization (PSO) is applied to provide optimal generation scheduling among PV and WT generation systems, fuel-based generation units, and the required power from the main grid. Third, a demand response (DR) program is introduced to shift flexible load in the microgrid system to achieve an active management system. Simulation results demonstrate the performance of the proposed method using forecast data for hourly PV and WT generations and a load profile. The simulation results show that the optimal generation scheduling can minimize the operating cost under the worst-case uncertainty. The load-shifting demand response reduced peak load by 4.3% and filled the valley load by 5% in the microgrid system. The proposed optimal scheduling system provides the minimum total operation cost with a load-shifting demand response framework.

Thermal efficiency appraisal of hybrid nanocomposite flow over an inclined rotating disk exposed to solar radiation with Arrhenius activation energy

The energy crisis forced the world to look for alternate energy solutions. Amongst these, solar energy is the first choice of scientists that convert solar radiation into heat or electricity to meet the energy deficit. Despite its marginally high installation cost, this renewable energy solution is long-lasting with minimum operating cost. Heading in the same direction, the attributes of the solar radiation towards the heat transfer rate of hybrid nanocomposite comprising paraffin wax amalgamated with copper-oxide, and cobalt-oxide (CuO-Co3O4) nanocomposites and thin-film spraying over an inclined rotating disk are discussed. The nanocomposites are considered in varied shapes. The model is supported by the Arrhenius activation energy in the concentration equation and the convective boundary condition at the surface. The model assumptions are translated into the system of partial differential equations which are then converted into differential equations with apposite similarity transformations. The numerical solution of the transformed system is obtained by the Keller box method. The obtained results are analyzed graphically. The maximum heat transfer rate is witnessed in the case of spherical-shaped particles. Furthermore, the hybrid nanocomposite fluid velocity is augmented when the width of the film is improved.

Minimizing Buoyancy Factor of Metallic Pressure-Hull Subjected to Hydrostatic Pressure

To increase the payload, reduce energy consumption, improve work efficiency and therefore must accordingly reduce the total hull weight of the submersible. This paper introduces a design optimization process for the pressure-hull of submarines under uniform external hydrostatic pressure using both finite element analysis (FEA) and optimization tools. A comprehensive study about the optimum design of the pressure hull, to minimize the weight and increase the volume, to reach minimum buoyancy factor and maximum operating depth minimizing the buoyancy factor (B.F) is taken as an objective function with constraints of plate and frame yielding, general instability and deflection. The optimization process contains many design variables such as pressure-hull plate thickness, unsupported spacing, dimensions of long and ring beams and finally the elliptical submersible pressure-hull diameters. The optimization process was conducted using ANSYS parametric design language (APDL) and ISIGHT. The Multi-Island Genetic Algorithm (G.A) is considered to conduct the optimization process. Additionally, parametric analysis is done on the pressure hull to examine the effect of different design variables on the pressure-hull design. As a result, the B.F of the proposed optimal model is reduced by an average of 31.78% compared with Reference Model (RM). Maximum von Mises stress is reduced by 27% as well. These results can be helpful for submarine pressure-hull designers.

Multi-objective optimal allocation of distributed generation considering the spatiotemporal correlation of wind-photovoltaic-load

• A multi-objective DG planning model is developed from the perspective of multi-dimensional data mining. • The model is used to solve the correlation analysis for wind speed, light intensity, and load demand of adjacent regions. • The spatiotemporal correlation, economic and system safety and environmental benefits are considered. • The effects of the seasonal difference on the favorable level of the DG's grid connection have been investigated. Aiming at the problem of the distributed generation (DG) planning caused by the strong spatiotemporal coupling between DG output and load demand in adjacent areas, a multi-objective planning model is proposed to describe the spatiotemporal correlation of sources. By combining the most weight supported tree (MWST) and depth first search (DFS), the method achieves the a priori requirement for constructing bayesian network (BN) structure using the K2 algorithm. Then, the MDK2-BN model is established through the measured data, which can describe the correlation between multi-dimensional wind-photovoltaic-load. A DG multi-objective programming model with maximum annual profit rate and minimum comprehensive operation risk is constructed. The results has three main advantages: (1) the MDK2-BN structure can achieve satisfactory results when dealing with small networks. (2) the MDK2-BN model conforms to the spatiotemporal correlation of the DG output, and the proposed configuration can improve the access capacity of DG. (3) the favorable level of the DG's grid connection can be effectively improved by considering the seasonal difference in performance and providing the planners with the decision-making references that balance the economic benefits, system operational safety, and environmental benefits.

Software package for analysis and design of overhead power transmission line structures

The article describes an algorithm for calculating wires and cables implemented by determining the loads on the supports, taking into account the compatibility of deformations of structural elements of an overhead power line (overhead line), atmospheric conditions and the profile of the route for all possible modes of operation of overhead lines. Wires and cables are exposed to the load from their own weight, as well as additional impacts in the form of horizontal wind load and the weight of icy deposits. Using the reduced equation of state of the wire (lightning-proof cable), the amount of tension in the operational state is determined if the voltages in the initial state and the values of loads and temperatures are known. It is revealed that for small spans, the voltage value is greatly influenced by temperature, and for large spans by load, which means there must be such a boundary (critical) span value at which the influence of temperature and load on the voltage value will be the same. As a result, software has been developed to solve the problem of determining the stress-strain state of wires and cables and collecting loads on overhead line supports. The developed calculation subsystems can function independently or be included in the software package as components written in the algorithmic language FORTRAN. In contrast to the traditional calculation, emergency loads for anchor-corner supports are determined not only in the ice regime, but also at minimum and average operating temperatures. The calculation in the software package allows us to consider the alternate breakage of all phases of wires and cables in both the left and right spans.