Minimum Operating Research Articles

Design and Technoeconomic Analysis of Fischer–Tropsch Fixed‐Bed Synthesis with Cobalt‐Based Catalysts

A multitubular Fischer–Tropsch (FT) reactor with gas recycle and a cobalt‐based catalyst is simulated by a 2D fixed‐bed model that considers the complex kinetics, all relevant mass and heat transfer aspects, and also the influence of the changing molar flow rate by the FT reaction, of pressure drop, and of formation of steam, which decreases the reaction rate of FT synthesis. Optimal values of gas velocity and single‐tube diameter and length are determined by a technoeconomic analysis. The comparison of the data of the FT reactor modeled in this work with data of commercial reactors indicates that the used model reflects reality well and is reliable. A superficial gas velocity of 0.5 m s−1, a tube diameter of 3 cm, and a length in a range of 12–20 m are appropriate for a high production rate of C2+‐hydrocarbons with minimal operating costs of the FT unit, even for a large range of the electricity price from 0.06 to 0.3 € kWh−1.

Optimization of solar-air source heat pump heating system with phase change heat storage

The optimization of heating system has always been of much concern, among which the annual life cycle cost (ALCC) was widely used as an optimization method, while the non-guaranteed hours were often overlooked. This study proposed the elasticity-economy (E-E) objective function as an optimizing indicator, and demonstrated it taking a solar assisted heat pump heating system with phase change material (SC-ASHP-PCM) as an example. Firstly, the single variation impact was analyzed. After optimizing the thermal performance of sub-systems, the proportion of heat supplied by solar collector (SC) and phase change material (PCM) sub-systems increased by 5.4 % and 3.4 %, respectively. Subsequently, the Hooke-Jeeves algorithm was developed to optimize multi-factors, hence minimizing the E-E objective function. The optimal solution was achieved when the non-guaranteed rate was 5 % and the penalty factor was 150 CNY/h. Compared with the baseline situation, the system energy consumption (156.8 × 103 kW‧h) was reduced by 30 %, and the E-E objective function was reduced by 24 %. Furthermore, the minimum operating cost was 18.3 CNY/m2, saving up to 46 % compared to traditional heating systems. The method is generalized to obtain the optimal energy saving potential under different non-guaranteed hours, which provides guidance for the heating systems' design and operation.

Two-Stage Optimal Scheduling Based on the Meteorological Prediction of a Wind–Solar-Energy Storage System with Demand Response

With large-scale wind and solar power connected to the power grid, the randomness and volatility of its output have an increasingly serious adverse impact on power grid dispatching. Aiming at the system peak shaving problem caused by regional large-scale wind power photovoltaic grid connection, a new two-stage optimal scheduling model of wind solar energy storage system considering demand response is proposed. There is a need to comprehensively consider the power generation cost of various types of power sources, day-ahead load forecasting information, and other factors and plan the day-ahead output plan of the energy storage system with the minimum system operation cost as the optimization objective of day-ahead dispatching. The demand response strategy is introduced into the time-ahead optimal scheduling, and the optimization of the output value of the energy storage system in each period is studied with the goal of minimizing the system adjustment cost. The particle swarm optimization algorithm is used to solve the model, and the IEEE33 node system is used for an example simulation. The results show that using the demand response and the collaborative effect of the energy storage system can suppress the uncertainty of wind power and photovoltaic power, improve the utilization rate of the system, reduce the power generation cost of the system, and achieve significant comprehensive benefits.

Optimizing smart microgrid performance: Integrating solar generation and static VAR compensator for EV charging impact, emphasizing SCOPE index

The rapid global increase in electric vehicle (EV) usage, driven by its low CO2 emissions, uncomplicated maintenance, and minimal operating costs, has prompted extensive research in the field of electric vehicle charging station (EVCS). The integration of EVCS into the current distribution grid poses challenges due to potential power losses and voltage variations beyond acceptable limits. This complexity is heightened by the growing penetration of randomly dispersed solar-based distributed generation (SDG) and battery energy storage system (BESS). To address these challenges, distribution static VAR compensator (DSVC) systems have been introduced, offering benefits such as enhanced power transfer capacity, improved voltage regulation, and increased system security without requiring extensive infrastructure upgrades. This study offers SCOPE, a novel multi-objective framework that unifies the optimization goals of minimizing real power loss, lowering bus voltage variation, maximizing system voltage stability, minimizing system operating costs, and mitigating CO2 emissions. The EVCS problem is optimized within this multi-objective framework utilizing an improved bald eagle search algorithm (IBESA). The proposed model accounts for vehicle to grid (V2G) capabilities and the actual driving patterns of users over a 24-h horizon. The formulation of a smart microgrid (SMG) structure is based on modifying the standard IEEE 33-bus test radial distribution network (RDN), comprising three interconnected SMGs serving residential, commercial, and industrial users. The optimization approach based on IBESA is utilized to optimize both the siting and capacity of EVCS as well as renewable energy sources (RESs). The findings show that SDG and DSVC are effective at lowering the SCOPE index, highlighting the advantages of the suggested approach.

Coordinated optimization of source‐grid‐load‐storage for wind power grid‐connected and mobile energy storage characteristics of electric vehicles

AbstractThe rapid growth in the number of electric vehicles (EVs), driven by the ‘double‐carbon’ target, and the impact of uncontrolled charging and discharging behaviour and discharged battery losses severely limit electric vehicles’ low carbon characteristics. Existing research on systemic low‐carbon emissions and electric vehicle charging and discharging issues is usually determined by considering only carbon trading markets or charging and discharging management on the source side. In this regard, a coordinated and optimized operation model that considers the participation of electric vehicle clusters in deep peaking and the source network load and storage adjustable resources is proposed. The upper layer establishes a real‐time price‐based demand response mechanism for the load side with the minimum net load fluctuation as the objective function; the middle layer establishes a comprehensive operation mechanism for the source and storage side that includes an orderly charging and discharging peaking compensation mechanism for electric vehicles, and a deep peaking mechanism that takes into account clean emission, and constructs an optimal operation model with the minimum comprehensive operating cost as the objective function; the lower layer establishes a distribution network loss minimization model for the network side that takes into account the orderly charging and discharging of electric vehicle as the objective function. The optimal load model with the objective function of minimizing the distribution network loss is established at the lower level. Finally, the original problem is transformed into a mixed integer linear programming problem, and the model's effectiveness is verified by setting different scenarios. The model reduces the total cost by 22.22%, improves the wind power consumption rate by 19.55%, reduces the actual carbon emission by 16.66%, and reduces the distribution network loss by 13.91% compared to the basic model.

Optimal allocation method for MIES-based shared energy storage using cooperative game theory and CSP

To further promote the efficient use of energy storage and the local consumption of renewable energy in a multi-integrated energy system (MIES), a MIES model is developed based on the operational characteristics and profitability mechanism of a shared energy storage station (SESS), considering concentrating solar power (CSP), integrated demand response, and renewable energy output uncertainty. We propose a corresponding MIES model based on co-operative game theory and the CSP and an optimal allocation method for MIES shared energy storage. The model considers the maximum operating benefit of the SESS as the upper objective function and the minimum operating cost of the MIES as the lower objective function. First, the Karush–Kuhn–Tucker conditions of the lower-layer model are transformed into constraints of the upper-layer model, and the Big-M method is used to linearize the nonlinear problem and convert the two-layer nonlinear model into a single-layer linear model. Second, based on the Nash negotiation theory, the benefits of each IES in the MIES are allocated. Finally, the fuzzy chance constraints are used to relax the power balance constraints, and the trapezoidal fuzzy numbers are transformed into a deterministic equivalence class to assess the impact of renewable energy output uncertainty on system operation. The validity and rationality of the proposed two-layer model are verified through simulation, and the results demonstrate that the proposed shared storage capacity leasing model can effectively reduce the total operation cost, increase the profitability of the shared storage operator, and increase the utilization rate of the SESS.

Sizing of Degradation Based Battery Storage Systems for Operating Cost Minimization in Microgrids

Abstract: A microgrid is a low voltage distribution network designed to provide power for small scale and isolated communities consisting of distributed generation and Energy Storage Systems .One of the major issues in the isolated microgrids with intermittent nature of distributed generation is the balance of energy demand. This can be achieved by appending renewable energy sources with suitable Battery Energy Storage Systems, to provide the reserve support in meeting the load demand. Battery degradation effect plays a major role in analysing the performance of BESS Life Time. This depends on average kWh and average MWh throughput discharge from BESS. Therefore, microgrid system with BESS considering degradation effect should be optimized in such a way as to obtain minimum operating cost while ensuring minimum electricity cost to customers. This paper presents an optimization algorithm for microgrid operating cost and customer electricity cost minimization for 24hrs time horizon while considering BESS degradation effect by determining kWh and MWh throughput. Particle Swarm Optimization (PSO), Accelerated particle swarm optimization (APSO), Jaya optimization (JAYA) technique and Linear programming interior point algorithm (LP-IP) have been applied to determine the optimal operating cost and electricity cost by simulating BESS degradation parameters

An improved gain and directivity design of an antipodal Vivaldi antenna for ultra‐wideband detection

AbstractA novel antipodal Vivaldi antenna (AVA) is proposed to achieve improved gain and directivity. To enhance the bandwidth of the antenna, a series of equal‐sized slots are etched onto the patch surface. Additionally, a dielectric lens with a fan‐shaped structure is integrated along the patch openings to boost gain. The length of the lens which will affect the radiation characteristics of the antenna in the end‐fire direction will be discussed. Furthermore, three arrays of directors are added to enhance the directivity. The fabricated antenna is then measured using a vector network analyzer in a microwave chamber to assess its performance. The results indicate that the antenna's minimum operating frequency is reduced by 0.5 GHz after etching the slots. Besides, the average gain is improved by 1 dBi after installing the fan‐shaped expansion structure. By introducing the directors, the sidelobe levels decrease and the 3 dB Half‐Power Beamwidth becomes sharper. Finally, an ultra‐wideband (UWB) detection experiment is designed to analyze the detection capability of the fabricated antennas. The results demonstrate that the antenna is well‐suited for UWB applications.

Shortcuts to Adiabaticity in Krylov Space

Shortcuts to adiabaticity provide fast protocols for quantum state preparation in which the use of auxiliary counterdiabatic controls circumvents the requirement of slow driving in adiabatic strategies. While their development is well established in simple systems, their engineering and implementation are challenging in many-body quantum systems with many degrees of freedom. We show that the equation for the counterdiabatic term—equivalently, the adiabatic gauge potential—is solved by introducing a Krylov basis. The Krylov basis spans the minimal operator subspace in which the dynamics unfolds and provides an efficient way to construct the counterdiabatic term. We apply our strategy to paradigmatic single- and many-particle models. The properties of the counterdiabatic term are reflected in the Lanczos coefficients obtained in the course of the construction of the Krylov basis by an algorithmic method. We examine how the expansion in the Krylov basis incorporates many-body interactions in the counterdiabatic term. Published by the American Physical Society 2024

Quantification of stimulus-evoked tactile allodynia in free moving mice by the chainmail sensitivity test.

Chronic pain occurs at epidemic levels throughout the population. Hypersensitivity to touch, is a cardinal symptom of chronic pain. Despite dedicated research for over a century, quantifying this hypersensitivity has remained impossible at scale. To address these issues, we developed the Chainmail Sensitivity Test (CST). Our results show that control mice spend significantly more time on the chainmail portion of the device than mice subject to neuropathy. Treatment with gabapentin abolishes this difference. CST-derived data correlate well with von Frey measurements and quantify hypersensitivity due to inflammation. Our study demonstrates the potential of the CST as a standardized tool for assessing mechanical hypersensitivity in mice with minimal operator input.

Multi-AGV-Driven Pallet-Picking Scheduling Optimization (MADPSO): A Method for Flexible Multi-Level Picking Systems

In the context of increasingly competitive shipbuilding, the flexible multi-level picking system, composed of high-rise shelves, Automated Guided Vehicles (AGVs), and picking stations, has been of gradual interest because of its advantages in operation efficiency, system flexibility, and system robustness. Compared with other simple-level systems, the flexible multi-level picking system has a more complex coupling temporal relationship, which makes the scheduling optimization of shipbuilding automated collaborative order picking (SACOP) extremely difficult. In order to avoid the dilemma of finding a feasible and optimal collaborative scheduling scheme under the constraints of a complex temporal relationship, this paper proposed a multi-AGV-driven pallet-picking scheduling optimization (MADPSO) method, which takes the AGV scheduling scheme as the direct solution and modifies it to a feasible solution under the reasonably designed interaction strategy of stacker, AGV, and the interaction strategy of picking station, AGV. Furthermore, taking the minimum energy consumption and operation time as the optimization objectives, a multi-objective optimization mathematical model was established to describe MADPSO, and an improved NSGA-III algorithm was designed to solve the problem. Finally, several experiments were conducted in various scenarios and verified that using MADPSO can achieve a comprehensive optimization index improvement of 52.02–75.66% compared with traditional picking methods, which has a certain reference significance for shipyards.

The Impacts of Climate Change on Renewable Energy Sector: A Review

‌The energy sector is a complex institutional framework that includes many ministries, government agencies, aid agencies, and international organizations. Electricity levels have increased fivefold between then and now. Thousands of renewable projects have been implemented in rural areas. Many large energy projects have been built, renovated, the institutional, policy and regulatory landscape has improved to some extent, and transmission lines and distribution networks have been expanded. Despite the lack of reliable data, Afghanistan has significant reserves of fossil fuels and a promising future for renewable energy. For the next several decades, the country's wind power capacity alone will probably exceed the projected demand for electricity. Serious problems including the need for energy, the depletion of fossil fuels and their impact on the environment have drawn attention to renewable energy sources in the last ten years. Because of this, there is a growing consensus to prioritize sustainable energy systems based on energy, especially renewable energy sources that produce no pollution or emissions. The research study concludes with the involvement of renewable energy technologies with minimum operating and external cost as the best option in the future. From a policy point of view, steps must be taken in the field of renewable energy and technological innovation that require biomass resources that are associated with unsustainable long-term investments.

The research of touch screen usability in civil aircraft cockpit.

With the advancement of touch screen technology, the application of touch screens in civil aircraft cockpits has become increasingly popular. However, further analysis and research are required to fully promote its applications. The paper researched the usability of touch screens in aircraft cockpit considering the operation performance and subjective NASA-TLX workload evaluation, conducted experimental research on three touch gestures: click, drag, and zoom. Additionally, a comparative analysis was conducted on the touch performance under different layouts, positions, touch sizes, dragging direction angles, and zoom multiples. The touch performance indicators include operation time, error rate, operation speed, and workload. The experimental results show that the 21 mm size has the minimum operation time and workload, and 18 mm size has the lowest error rate in the clicking tasks. Additionally, the performance and workload of the captain's layout are better than those of the co-pilot's layout, and the performance of the center console position is best. The operation speed of the dragging tasks is faster when performed at position R3 compared to other positions. The dragging moving angles with better operation speed are 80°-190° and 250°-290°. The operation performance and workload of the zooming tasks vary depending on the zoom multiples. As the multiple increases, the operation time and workload also increase. There is no difference in operation performance or workload between zooming in and zooming out. The paper provides experimental support and suggestions based on human operation and subjective NASA-TLX workload evaluation for the application of touch screens in civil aircraft cockpits.

Construction and validation of a RARRES3-based prognostic signature related to the specific immune microenvironment of pancreatic cancer.

Tumor immune microenvironment (TiME) is prognostically instructive in Pancreatic adenocarcinoma (PAAD). However, the potential value of TiME-related genes in the individualized immunotherapy of PAAD has not been clarified. Correlation between Immune-Related Genes (IRGs) and immune-related transcription factors (TFs) was performed to prove the immune correlation of selected genes. Immune-related molecular subtypes were identified by consensus clustering. The TiME-score, an immune microenvironment-related prognostic signature for PAAD, was constructed using minimum absolute contraction and selection operator regression (Lasso-Cox). The International Cancer Genome Consortium (ICGC) dataset validated the reliability of TiME-score as external validation. Single-cell samples from GSE197177 confirmed microenvironment differences of TiME-score hub genes between tumor and its paracancer tissues. Then, RARRES3, a hub gene in TiME-score, was further analyzed about its upstream TP53 mutation and the specific immune landscape of itself in transcriptome and Single-cell level. Eventually, TiME-score were validated in different therapeutic cohorts of PAAD mice models. A 14-genes PAAD immune-related risk signature, TiME-score, was constructed based on IRGs. The differences of TiME-score hub genes in single-cell samples of PAAD cancer tissues and adjacent tissues were consistent with the transcriptome. Single-cell samples of cancer tissues showed more pronounced immune cell infiltration. The upstream mutation factor TP53 of RARRES3 was significantly enriched in immune-related biological processes. High RARRES3 expression was correlated with a worse prognosis and high macrophages M1 infiltration. Additionally, the immunohistochemistry of hub genes AGT, DEFB1, GH1, IL20RB, and TRAF3 in different treatment cohorts of mice PAAD models were consistent with the predicted results. The combination of immunotherapy, chemotherapy and targeted therapy has shown significantly better therapeutic effects than single drug therapy in PAAD. TiME-score, as a prognostic signature related to PAAD-specific immune microenvironment constructed based on RARRES3, has predictive value for prognosis and the potential to guide individualized immunotherapy for PAAD patients.

Fixed and mobile energy storage coordination optimization method for enhancing photovoltaic integration capacity considering voltage offset

Mobile energy storage has the characteristics of strong flexibility, wide application, etc., with fixed energy storage can effectively deal with the future large-scale photovoltaic as well as electric vehicles and other fluctuating load access to the grid resulting in the imbalance of supply and demand. To this end, this paper proposes a coordinated two-layer optimization strategy for fixed and mobile energy storage that takes into account voltage offsets, in the context of improving the demand for local PV consumption. Among them, the upper layer optimization model takes into account the minimum operating cost of fixed and mobile energy storage, and the lower layer optimization model minimizes the voltage offset through the 24-h optimal scheduling of fixed and mobile energy storage in order to improve the in-situ PV consumption capacity. In addition, considering the multidimensional nonlinear characteristics of the model, the interaction force of particles in the Universe is introduced, and the hybrid particle swarm-gravitational search algorithm (PSO-GSA) is proposed to solve the model, which is a combination of the individual optimization of the particle swarm algorithm and the local search capability of the gravitational search algorithm, which improves the algorithm’s optimization accuracy. Finally, the feasibility and effectiveness of the proposed model and method are verified by simulation analysis with IEEE 33 nodes.

Measurement of phase modulation time dynamics of liquid crystal spatial light modulator

Liquid crystal spatial light modulators for precise dynamic manipulation of coherent light fields, used in diffractive optoelectronic optical data processing systems, are considered. This paper presents the results of a study of the temporal dynamics of the HoloEye PLUTO-2 VIS-016 liquid crystal spatial light modulator for analysis of light fields rate modulation. Experiments using binary phase computer generated holograms and binary focusing phase diffractive optical elements were conducted. Based on experimental data, the time characteristics of the modulator response were determined. It was found that when the rise time of the diffraction efficiency was 146 ms after the hologram displaying onto the SLM, and when switching to a new hologram, the decay time was 97 ms. These results allowed the dynamic generation of an alternating holograms at a refresh rate of 2 Hz with an interference level of –16 dB. Increasing the frequency of fringe pattern updates increases the level of interframe noise in the generated holograms, and when updated at the specification frequency, the generated distributions cannot be separated. Determining the actual frame rate based on the rise and decay times of the diffraction efficiency makes it possible to correctly calculate the minimum operating time of an information optical system containing a liquid crystal spatial light modulator.

Simulation of Integration of Distributed Generation into Power System Control

The paper deals with modeling of theintegration of distributed generation into the central dispatching system with regard to the electricity market environment. Due to the large number of the relative small unit power of distributed generation the resulting reserve power can achieve a remarkable quantity. However the utilization of these reserves is not obvious because of several technical issues like the cogeneration of heat power, lack of proper informatics, bounds of law about electric energy (LEE) in Hungary etc. An agent based simulation model was developed to discuss the problem. The model consists of the distributed generation units (DG-s) and the DG-concentrator (DGC) which is an interface between DG-s and the independent transmission system operator (TSO). All of them are simulated as autonomous software units suitable for decision making, learning and multi-direction communication. This is a multi-agent system, where the service, control and simulation of stochastic demand variation are easy to study. Several scenarios were discussed regarding the contracts between DG-s and TSO. The financial paragraph of the contract should ensure the willingness of private owned DG-s to provide their reserves for the central control. The results of the simulation help to find the minimum loss operation of the system.

Production of Biodiesel from WVO Using Small Scale Continuous Ultrasonic Processor

There is a need in the USA to decrease dependency on fossil fuels. One alternative fuel that has gained much popularity in the past few years is biodiesel. Biodiesel can be produced using vegetable oil, waste vegetable oil (WVO), animal fat and yellow grease as raw materials. However, the process of converting a batch of WVO into usable biodiesel is time consuming, requires a human operator to run the system, and necessitates the performance of a chemical titration for each batch of biodiesel produced. In the first phase of this project, the processor was designed and built by the senior design students utilizing a programmable logic controller (PLC) in conjunction with pumps, valves, temperature sensors, etc. to completely handle the production of biodiesel with minimum operator interaction. This was the first step toward continuous flow processor and the elimination of the titration process. In the second phase of this project, the students integrated a small Hielscher Ultrasound continuous processing unit to the automated system. This paper presents the newly developed system and demonstrates the design aspects of the automated biodiesel production processor using a PLC and ultrasonication (continuous processing) as well as how the chemical titration procedure for each batch is eliminated.

Fuel consumption optimization of a multimachines microgrid by secant method combined with IPPD table

The objective consists in optimizing the fuel consumption of a power station of small cogeneration multi machines while minimizing generated pollution. At first, a study carried out on the strategies of Economic Dispatch , was used to us to solve the unit commitment problem, whose main aim is to determine the optimal schedule of online generating units so as to meet the power demand at minimum operating cost under various system and operating constraints. This work was carried out by Secant method combined with Improved Pre-prepared Power Demand (IPPD) table which obtains the unit status information and then the optimal solution is achieved by Secant method at each power demand for 24 hours. The comparison of results of the proposed method with the results of classical method, by Matlab/Simulink, shows that the proposed approach provides qualitative solution.

Determining the Inverse of a Matrix over Min-Plus Algebra

Linear algebra over the semiring R_ε with ⊗ (plus) and ⨁ (maximum) operations which is known as max-plus algebra. One of the isomorphic with this algebra is a min-plus algebra. Min-plus algebra that is the set R_(ε^' )=R∪{ε'}, with ⊗^' (plus) and ⨁' (minimum) operations. Given a matrix whose components are elements of R_(ε^' ) is called min-plus algebra matrices. Any matrix can be connected by an inverse. In conventional algebra, a square matrix is said an invertible matrix if the det⁡〖(A)〗≠0. In contrast to max-plus algebra, a matrix is said to have inverse condition if it meets certain conditions. Some concepts from the max-plus algebra can be transformed to the min-plus, because of their structural similarity. This means that the inverse matrix concept in max-plus can be constructed into a min-plus version. Thus, this study will explain the inverse of a matrix over the min-plus algebra, property of multiplying two invertible matrices, and connection between invertible matrix and linear mapping used the literature study method, with literature sources such as books, journals, articles, and theses. The data analysis technique used in this research is qualitative data analysis technique. Then, this article has a principal result that is matrix A∈R_(ε^')^(n×n) has a right inverse if and only if there are permutations of σ and the value of λ_i<ε', i∈{1,2,3,…,n} such that A=P_σ ⊗^' D(λ_i ) which is the inverse of matrices. Furthermore, if B is the correct inverse that satisfies A⊗^' B=E then B⊗^' A=E and B is uniquely determined by A.