Optimal Start-up Research Articles

Synergistic effects of organic matter degrading and electroactive biofilms for rapid startup of sediment microbial fuel cells: From laboratory scale to in situ application

Sediment microbial fuel cells (SMFCs) have been developed as sensors and reactors to remediate polluted environment and facilitate online monitoring. However, their industrial feasibility is hampered by long startup times. In this paper, we demonstrated that SMFCs could be rapidly initiated by employing precultured anodes. The performance of precultured anodes in reducing startup times was strongly influenced by the duration of culture time. High-throughput sequencing techniques and community level physiological profiling (CLPP) methods were utilized to study the structural and functional diversity of the bacterial communities on incubated anodes. Results revealed that the collaborative role of organic matter degrading biofilms and electroactive biofilms on the anodes in expediting startup. Network interactions analysis further showed more compact co-occurrence patterns, less topological roles of individual Operational Taxonomic Units (OTUs) and dominant modules were obtained after SMFCs setup. This was primarily due to the formation of more stable and higher microbial carbon metabolism functions anode biofilms. An optimal biomass level of 2000 μg protein cm−2 on the anode was typically achieved seven days after SMFCs initiation. Based on the results of laboratory experiments, the optimal start-up strategy was obtained, and successfully applied to the starting of in-situ on-line monitoring sensors. This study could realize the potential of SMFCs for large-scale field applications.

Enhancing distribution system stability and efficiency through multi‐power supply startup optimization for new energy integration

AbstractThis paper addresses the challenge of maximizing power capture from new energy sources, including coal, wind, solar, and hydroelectric power, which often lack sufficient inertia support. This deficiency can lead to frequency instability and cascading failures within the power system. A cooperative optimization model for the start‐up of multiple power supplies, designed to enhance the integration of new energy sources while maintaining system stability is proposed. The model incorporates primary frequency modulation and the intrinsic inertia support capabilities of self‐synchronous voltage source field stations, considering dynamic frequency constraints. Additionally, it employs new energy units with primary frequency modulation to provide inertia support during curtailment, particularly when conventional units cannot meet frequency standards due to existing constraints. Extensive simulations and comparative analyses demonstrate that the proposed model improves new energy utilization by up to 37.5% and reduces operational costs by approximately 16%, enhancing overall operational efficiency in high energy consumption scenarios.

Closed-Form Optimal Current-Limiting Curve-Based Variable Duty-Cycle Soft Start-Up Strategy for the LLC DC Transformer

Closed-Form Optimal Current-Limiting Curve-Based Variable Duty-Cycle Soft Start-Up Strategy for the <i>LLC</i> DC Transformer

Optimization of catalyst service cycle and start-up considering the reactor-distillation-HEN integration and climate

Considering the catalyst deactivation and seasonal temperature variation, a systematic method is proposed for clarifying the dynamic variation of system operating parameters and targeting the optimal catalyst regeneration cycle and start-up date. Relationships between catalyst activity, reactor inlet and outlet temperatures, reactor heat load, and running time are deduced, as well as that between column temperatures, pressures, energy demands, processing capacity, and production month. Diagrams are constructed to illustrate the parameter variations. With the energy consumption and processing capacity combined, an evaluation index is introduced for integrating the reactor-separator-heat exchanger network (HEN) and optimizing the production start-up date. The proposed method is intuitive and efficient and can be used for system design, guiding production, or fault diagnosis. A benzene alkylation process is studied; the optimal regeneration cycle of the ZSM-5 catalyst is 11 months, and the best start-up date is August, saving 2.32 × 105 kgce (kg standard coal) per production cycle.

Establishing mainstream partial nitrification in the membrane aerated biofilm reactor by limiting the oxygen concentration in the biofilm

The proliferation of nitrite oxidizing bacteria (NOB) still remains as a major challenge for nitrogen removal in mainstream wastewater treatment process based on partial nitrification (PN). This study investigated different operational conditions to establish mainstream PN for the fast start-up of membrane aerated biofilm reactor (MABR) systems. Different oxygen controlling strategies were adopted by employing different influent NH4+-N loads and oxygen supply strategies to inhibit NOB. We indicated the essential for NOB suppression was to reduce the oxygen concentration of the inner biofilm and the thickness of aerobic biofilm. A higher NH4+-N load (7.4 g-N/(m2·d)) induced higher oxygen utilization rate (14.4 g-O2/(m2·d)) and steeper gradient of oxygen concentration, which reduced the thickness of aerobic biofilm. Employing closed-end oxygen supply mode exhibited the minimum concentration of oxygen to realize PN, which was over 46% reduction of the normal open-end oxygen mode. Under the conditions of high NH4+-N load and closed-end oxygen supply mode, the microbial community exhibited a comparative advantage of ammonium oxidizing bacteria over NOB in the aerobic biofilm, with a relative abundance of Nitrosomonas of 30–40% and no detection of Nitrospira. The optimal fast start-up strategy was proposed with open-end aeration mode in the first 10 days and closed-end mode subsequently under high NH4+-N load. The results revealed the mechanism of NOB inhibition on the biofilm and provided strategies for a quick start-up and stable mainstream PN simultaneously, which poses great significance for the future application of MABR.

Startup characteristics of the large length–diameter ratio high-temperature heat pipe

Large length–diameter ratio high-temperature sodium heat pipes (HTSHPs) are uniquely structured heat-transfer devices with significant application potential in high-temperature solar thermal power and small-scale nuclear systems. This study tested HTSHPs' startup characteristics examining various parameters. Results indicate that the transition temperature for flow transition is 564 K, and the continuous flow transition temperature is 722 K. Heat pipes at 15 % fill ratio are adaptable across various inclination angles, whereas those at 25 % and 35 % fill ratios show optimal startup at smaller angles (15°, 30°), with decreasing startup time as angle increases, notably significant at 45°.The start-up time refers to the duration from the initiation of heating to the point when all the normal operational temperature points of the HTSHP reach the continuous flow transition temperature during the condensation section. During the experiments, heat pipes with a large length–diameter ratio exhibit heat transfer instability, temperature oscillation and local overheating. Reducing the fill ratio and inclination angle effectively reduces the probability of temperature oscillation and local overheating. This study proposes a novel method for optimizing temperature oscillations in heat pipe design, offering pioneering insights and experimental data crucial for specialized high-temperature heat pipe research.

Internal Flow Characteristics of Centrifugal Pumps under Different Startup Combination Schemes

Pump station engineering is a water conservancy project used for long-distance water transfer, irrigation and drainage, and urban living and industrial water supply. Centrifugal pumps are one of the main pump types commonly used in pumping stations, and their operation is of considerable importance for the safety, stability, and efficient operation of pumping stations. This paper takes a large pumping station with seven centrifugal pump units as the research object and combines experimental research and numerical simulation. The axial flow velocity uniformity, average cross-sectional deviation angle, and hydraulic loss of the pump inlet section are evaluated, and the internal flow characteristics of the pump under different startup combination conditions are analyzed based on entropy generation and vorticity. This study also explores the operational performance of the pump station under different startup combination conditions, revealing the mutual influence mechanism between different startup combinations of pump stations and the internal and external characteristics of centrifugal pumps and introducing the optimal startup combination scheme for the pump station system. Research results indicate that the difference in energy loss of centrifugal pumps under different startup combinations is mainly manifested in the impeller and guide vane flow channels. For the two existing inlet flow channel structures in the pump station, the unit effectively operates when the inlet flow channel is tilted to the left. The optimal startup combination method of the pump station under different startup combinations is determined.

КЛАССИФИКАЦИЯ И ПОДхОДы К СОЗДАНИЮ СТАРТАП-СТУДИЙ В УНИВЕРСИТЕТАх

The article is devoted to issues related to the development of project activities in educational institutions. In modern conditions, the activities of educational institutions are increasingly connected with entrepreneurship and business communities. Issues regarding the creation and development of Start-up studios in educational institutions are becoming especially relevant. When creating startup studios, it is important to understand the specifics of different types of startup studios and the parameters of their activities in order to correlate them with the goals of the educational institution and the project being implemented. An educational institution can choose for itself the most optimal Startup Studio model, taking into account the size of the educational institution, its territorial location, its financial and personnel capabilities. This article presents the results of a study on the classification of Startup Studios and concludes that for educational institutions the most optimal are University Startup Studios, which in recent years have been quite actively created, operating and bringing real innovative projects to educational institutions.

IM-TD3: A Reinforcement Learning Approach for Liquid Rocket Engine Start-Up Optimization

IM-TD3: A Reinforcement Learning Approach for Liquid Rocket Engine Start-Up Optimization

Startup optimization of gas foil bearings-rotor system in proton exchange membrane fuel cells

The startup performance is crucial to the high-efficient operation of the sustainable power generation system. Current literature usually focuses on catalysts and startup strategy to improve startup performance of the proton exchange membrane fuel cell, which ignores the gas foil bearings-rotor system that directly affects startup response. Therefore, in this paper, the effects of bump foil structure, coating, and nominal clearance on the startup response of the bearings-rotor system are first investigated experimentally. Multi-objectives optimization mathematical model considering simultaneously lower power consumption, takeoff speed, and vibration is presented based on grey relational analysis. The optimal bearings-rotor system with radial trisection bump foil, coating MoS2, and nominal clearance of 50 μm is identified. Compared to average values, the power consumption of the optimal system is diminished by 27.2% while the takeoff speed and nonlinear vibration are reduced by 16.2% and 47.3%, respectively. These findings can be used to improve energy efficiency and startup performance for fuel cells. The systematic methodology proposed in this study can be extended to other investigations about the startup.

CO2 Emission-Constrained Short-Term Unit Commitment Problem Using Shuffled Frog Leaping Algorithm

The increasing concerns about greenhouse gas emissions have made it necessary to incorporate environmental constraints in the operation of power systems. The CO2 emission-constrained short-term unit commitment problem (CSCUCP) is a multiobjective optimization problem that involves minimizing both the cost of operation and the CO2 emissions. This paper proposes an integer-coded shuffled frog-leaping algorithm (SFLA) to minimize both total CO2 emissions and operating costs for the unit commitment problem (UCP) over a one-day scheduling period. The SFLA is inspired by the natural food-searching behavior of frogs. The proposed method aims to determine the optimal start-up and shut-down times for generating units to meet fluctuating loads while minimizing operating costs and CO2 emissions. The method takes into account fuel costs, start-up and shut-down costs, and maintenance costs while satisfying various constraints. The study uses the IEEE 39 bus with a 10-unit test system, and the results are related to conventional methods. The proposed method consistently produces lower CO2 emissions and total operating costs compared to the existing methods.

Experimental study on electrochemical, starting-up, and energy-saving properties of a hybrid supercapacitor as automotive starter power under low-temperature conditions

Hybrid supercapacitors (HSCs) are considered a potential energy storage device due to their unique advantages. In this study, the electrochemical-heat generation behaviors of HSCs were analyzed through experimental tests. Then, the electrochemical characteristics, start-up performance, and fuel consumption of 12 V/70 Ah HSCs, a lead-acid battery, and an LiFePO4 battery were compared to further evaluate the law and mechanism of the low-temperature condition, leading to the aforementioned performance attenuation. After 100 continuous charge/discharge cycles, the capacity retention rate of the HSCs was 2.53 % higher than that of the lithium cell, and the Coulombic efficiency of the lithium cell was 0.56 % higher than that of the HSCs. Additionally, when the temperature dropped from 0 °C to −20 °C, the overall fuel consumption of the HSC energy storage power increased by 0.11 mL. When the temperature decreased from −15 °C to −20 °C, the discharging capacity of the HSC energy storage power decreased slightly by 2.5 Ah and the charging time increased by 0.36 h. Overall, the HSC energy storage power exhibited optimal low-temperature start-up performance, fuel-saving effect, and lower capacity attenuation. Relevant research is expected to provide experimental data and theoretical support for the industrialization of HSCs.

Start-Up Strategy-Based Resilience Optimization of Onsite Monitoring Systems Containing Multifunctional Sensors

In nonrepairable multifunctional systems, the lost function of a component can be restored by the same function from another component; therefore, the activation mechanism of redundant functions illustrates that multifunctional systems have resilience features. This study evaluates the resilience of multifunctional systems and analyzes the properties of system resilience first. To determine the optimal start-up strategy, a resilience-oriented start-up strategy optimization model for onsite monitoring systems (OMSs) is established to maximize system resilience under a limited budget. In this study, real-time reliability is regarded as the system performance to evaluate the system resilience, and a two-stage local search based genetic algorithm (TLSGA) is proposed to solve the resilience optimization problem. The results of our numerical experiments show that the TLSGA can more effectively solve the problems for OMSs, with high function failure rates and low component failure rates compared with classical genetic algorithms under 48 systems. Moreover, the optimal combinations of unmanned aerial vehicles (UAVs) for an OMS under a limited budget shows that UAVs with a higher carrying capacity should be given priority for selection. Therefore, this study provides an effective solution for determining the optimal start-up strategy to maximize the resilience of OMSs, which is beneficial for OMS configuration.

A Simple and Fast Start-Up Strategy for Dual-Active-Bridge Converters With DC Bias Suppression

High power dual active bridge (DAB) converters are widely adopted in DC and hybrid AC/DC micro-grids, for which <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fast start-up dynamics</i> of DAB converters is a key requirement. Conventional start-up methods usually require complex operation stages, and a time-consuming parameter-tuning process, resulting in slow dynamics. In this work, we propose a new simple and optimal start-up method for DAB converters. Major contributions lie in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">three-folds</i> . (i) We theoretically analyze the transmission power and the peak inductor current of extended phase-shift modulation. (ii) A new Lagrange Multiplier method is proposed to solve the optimal phase-shift ratios of the underlying control problem, resulting in very fast control dynamics at maximum power transmission, fully respecting the system permissible current limit. (iii) An effective and simple strategy by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">solely</i> manipulating the gate signals in the first switching period is newly proposed to eliminate the magnetic bias. The proposed method avoids complex parameter-tuning procedures. Experimental results demonstrate the effectiveness of the proposed method. Results confirm that with the proposed solution a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">much faster</i> start-up process with a controllable inductor current <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">without</i> DC bias is achieved, in comparison with the recently reported start-up methods.

Dynamic Model Selection and Optimal Batch Design for Polyhydroxyalkanoate (PHA) Production by Cupriavidus necator.

Mathematical modelling of microbial polyhydroxyalkanoates (PHAs) production is essential to develop optimal bioprocess design. Though the use of mathematical models in PHA production has increased over the years, the selection of kinetics and model identification strategies from experimental data remains largely heuristic. In this study, PHA production from Cupriavidus necator utilizing sucrose and urea was modelled using a parametric discretization approach. Product formation kinetics and relevant parameters were established from urea-free experimental sets, followed by the selection of growth models from a batch containing both sucrose and urea. Logistic growth and Luedeking-Piret model for PHA production was selected based on regression coefficient (R2: 0.941), adjusted R2 (0.930) and AICc values (-42.764). Model fitness was further assessed through cross-validation, confidence interval and sensitivity analysis of the parameters. Model-based optimal batch startup policy, incorporating multi-objective desirability, suggests an accumulation of 2.030g l-1 of PHA at the end of 120h. The modelling framework applied in this study can be used not only to avoid over-parameterization and identifiability issues but can also be adopted to design optimal batch startup policies.

Determining optimal generator start-up sequence in bulk power system restoration considering uncertainties: A confidence gap decision theory based robust optimization approach

A reasonable start-up sequence of generators considering renewable energy generation integration can effectively improve the restoration efficiency of the power system concerned. The restoration strategy of generators is time-sensitive, however, the computation procedure of existing methods is not fast enough to meet the requirements of practical applications. In this paper, the generator start-up sequence optimization (GSSO) problem is addressed with the integration of wind-solar hybrid systems (WSSs) considered in bulk power systems. Specifically, a deterministic model for GSSO is formulated to maximize the total generation capability during the restoration procedure, in which fewer auxiliary variables are required to promote the computational efficiency. On this basis, in order to deal with the inherent and significant uncertainties of WSSs, a confidence gap decision theory (CGDT) based approach is proposed combining the advantages of stochastic optimization and the information gap decision theory based method while considering the worst-case realization of unknown probability distributions, so that a chance-constrained robust generator start-up solution is thereby attained. Moreover, the formulated CGDT based model is transformed into a mixed integer linear programming problem. Finally, the IEEE 39-bus power system and a modified version of an actual power system in China are employed to demonstrate the feasibility and efficiency of the proposed method.

Research of Dynamic Characteristics of Bearing Reducers of the TwinSpin Class in the Start-Up Phase and in the Initial Operating Hours

This paper describes the results of research in the field of monitoring dynamic characteristics of the TwinSpin cycloid bearing reducer made by SPINEA. The research in this area resulted from the requirement to monitor the condition of high-precision bearing reducers and to assess the non-linear behavior of the kinematic structures of the monitored bearing reducers, specifically to determine the optimal start-up time of a particular bearing reducer class and to plan its maintenance. The condition of contact surfaces in the operational process was identified, and the lubricant applied to the monitored class of reducers was assessed. Analyses of the applied lubricant were carried out in order to identify and monitor changes in the technical condition of the bearing reducer. The aim of the measurements was to verify the start-up time of the bearing reducer, to assess the correlation between the total content of iron particles in the lubricant and an increase in kinematic backlash in the engagement of cycloidal wheels and reducer bearings after start-up and after about 1000 h of operation, and to propose recommendations to the operator for the implementation of short-term dynamic vibration, noise, and temperature tests before the reducer itself is put into operation.

Evaluation of composting parameters, technologies and maturity indexes for aerobic manure composting: A meta-analysis

Aerobic composting is an efficient method to recover nutrients from animal manure. However, there is considerable variability in the management and maturity criteria used across studies, and a systematic meta-analysis focused on compost maturity is currently lacking. This study investigated the optimal range of startup parameters and practical criteria for manure composting maturity, as well as the effectiveness of in situ technologies in enhancing composting maturity.Most maturity indexes were associated with composting GI, making it an ideal tool for evaluating the maturity of manure composts. GI increased with declined final C/N and (Final C/N)/(Initial C/N) (P < 0.01), and therefore a maturity assessment standard for animal manure composting was proposed: a mature compost has a C/N ratio ≤23 and a GI ≥70, while a highly mature compost has a GI ≥90 and preferably (Final C/N)/(Initial C/N) ≤0.8. Meta-analysis demonstrated that C/N ratio regulation, microbial inoculation and adding biochar and magnesium-phosphate salts are effective strategies for improving compost maturity. Specifically, a greater reduction in the C/N ratio during the composting process is beneficial for improving the maturity of compost product. The optimal startup parameters for composting have been determined, recommending an initial C/N ratio of 20–30 and an initial pH of 6.5–8.5. An initial C/N ratio of 26 was identified as the most suitable for promoting compost degradation and microorganism activity. The present results promoted a composting strategy for producing high-quality compost.

ON THE ISSUE OF DETERMINING THE CONDITIONS FOR OPTIMAL START-UP OF THE MACHINE UNIT

The article presents the conclusion of analytical dependences characterising the conditions of optimal energy loss in an asynchronous electric motor for starting a machine unit equipped with an adjustable sliding link. It is shown that in the case of using adjustable sliding links in the kinematic drive chain and with significant inertia of the driven links, it is advisable to withstand the conditions of optimal start-up of the machine unit in terms of energy losses in the electric motor. To fulfill these conditions, it is necessary to maintain the high-speed mode of the asynchronous electric motor at the second stage of starting the machine unit, in which the energy losses in the asynchronous motor, on which its heating depends, will be minimal. Taking into account all factors affecting the movement of the adjustable sliding links will reduce the intensity of the machine unit start-up process.

Operation Optimization of Circulating Cooling Water System Based on Adaptive Differential Evolution Algorithm

The circulating cooling water system (CCWS) is a commonly used auxiliary system in industrial production, and it is also one of the main energy-consuming systems. The operating conditions of the system vary with the temperature changes caused by seasons, day and night, causing different energy consumption. If the system still maintains conditions when the actual conditions change, energy would be wasted. Operation optimization for the system can improve the operation effect of the system, reduce energy consumption, and increase operating efficiency. Therefore, through operation mechanism analysis for the main energy-consuming components of the CCWS that has been put into use, an operation optimization model is established integrating the domain knowledge. After that, an adaptive differential evolution (ADE) algorithm is proposed by introducing the adaptive mutation and crossover operator to solve the model. According to the minimum circulating water volume and air volume required by the system under different working conditions, the optimal start-up combination mode and operating frequency of the water pumps and fans are determined. And then, the optimal opening values of the regulating valves and baffles in the system are determined, thereby saving the energy of the system. Considering system operation knowledge, the synchronous optimization of the operation mode and operation status of the components in the system is realized. Finally, the effectiveness of the optimization method is verified through a case study.