Two-Stage Optimal Scheduling of Community Integrated Energy System

From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.

Two-stage treatment process of pickling wastewater in the cold-rolling production of stainless steel

Based on the characteristics of pickling wastewater in the cold-rolling production of stainless steel, a new processing route, featuring source sludge reduction, wastewater two-stage treatment, heavy metal-contained sludge and calcium salt sludge separating recovery, was proposed. As shown by the research results, after the two-stage process treatment, the effluent water can steadily reach the emission standards, the sludge yield can be decreased by more than 8% ; within the heavy metal-contained sludge, the recovery rates of Fc,Cr and Ni can either reach or surpass 95% ,and the total content ofF and S can drop to around 3%. Therefore,the sludge in the front part can be used as ferric dust. In the calcium salt sludge ,the recovery rate of F can either reach or surpass 85% ,and the total contents of Fe,Cr and Ni can fall below 0.5%. So the sludge in the rear part can be used as fluorgypsum or fluorite. Meanwhile,the results of the analysis on heavy metals leaching toxicity and morphologic distribution indicate that the two kinds of sectionalized sludge are not classified as hazardous wastes, which have a stable behavior and better utilization values compared with the former mixed- sludge.

Influence of two-stage harvesting on the properties of cold-pressed rapeseed(Brassica napus L.)oils

Rapeseed(Brassica napus L.)harvesting method is critical since it significantly determines the seed yield,oil quality,and industrial efficiency.This study investigated the influences of harvesting methods on the quality of cold-pressed rapeseed oil of two varieties.Oil color,peroxide value(POV),tocopherol content,fatty acid composition,and polarity of total polyphenols(PTP)contents of two rapeseed varieties in Huanggang and Xiangyang were compared through artificially simulated combined harvesting and two-stage harvesting.Results showed significant differences in the quality of rapeseed oil between the two harvesting methods.The red value(R-value),POV,total tocopherol contents,linoleic and linolenic acid content,and PTP content of the pressed rapeseed oil prepared by the combined harvesting method were about 27.6,5.7,15.8,2.0,0.5,and 28.6%lower than those of the oil produced from the two-stage harvesting method,respectively.Xiangyang and Huayouza62 performed better in the two regions and two varieties,respectively.To sum up,the rapeseed oil obtained 41–44 days after final flowering of combined harvesting,35 days after final flowering,and six days of post-ripening of the two-stage harvesting had the best quality.

Tourism Route Recommendation Based on A Multi-Objective Evolutionary Algorithm Using Two-Stage Decomposition and Pareto Layering

Tourism route planning is widely applied in the smart tourism field.The Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions problems,which leads to uneven distribution and weak diversity of optimization solutions of tourism routes.Inspired by these limitations,we propose a multi-objective evolutionary algorithm for tourism route recommendation(MOTRR)with two-stage and Pareto layering based on decomposition.The method decomposes the multiobjective problem into several subproblems,and improves the distribution of solutions through a two-stage method.The crowding degree mechanism between extreme and intermediate populations is used in the two-stage method.The neighborhood is determined according to the weight of the subproblem for crossover mutation.Finally,Pareto layering is used to improve the updating efficiency and population diversity of the solution.The two-stage method is combined with the Pareto layering structure,which not only maintains the distribution and diversity of the algorithm,but also avoids the same solutions.Compared with several classical benchmark algorithms,the experimental results demonstrate competitive advantages on five test functions,hypervolume(HV)and inverted generational distance(IGD)metrics.Using the experimental results of real scenic spot datasets from two famous tourism social networking sites with vast amounts of users and large-scale online comments in Beijing,our proposed algorithm shows better distribution.It proves that the tourism routes recommended by our proposed algorithm have better distribution and diversity,so that the recommended routes can better meet the personalized needs of tourists.

Use of two-stage dough mixing process in improving water distribution of dough and qualities of bread made from wheat–potato flour

The two-stage dough mixing process was innovated to improve the qualities of bread made from potato flour(PF) and wheat flour at a ratio of 1:1(w/w). The final dough was first prepared from wheat flour before being added with PF. The effects of the method on enhancing the dough qualities were verified, and the distribution of water in gluten-gelatinized starch matrix of the doughs was investigated. We observed that the bread qualities were improved, as reflected by the increase of specific volume from 2.26 to 2.96 m L g^–1 and the decrease of crumb hardness from 417.93 to 255.57 g. The results from rheofermentometric measurements showed that the dough mixed using the developed mixing method had higher maximum dough height value, time of dough porosity appearance, and gas retention coefficient, as well as enhanced gluten matrix formation compared to that mixed by the traditional mixing method. The results from low-field nuclear magnetic resonance confirmed that the competitive water absorption between gluten and gelatinized starch could restrict the formation of gluten network in the dough mixed using the traditional mixing process. Using the novel mixing method, gluten could be sufficiently hydrated in stage 1, which could then weaken the competitive water absorption caused by gelatinized starch in stage 2;this could also be indicated by the greater mobility of proton in PF and better development of gluten network during mixing.

Multi-objective optimization for leaching process using improved two-stage guide PSO algorithm

A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.

Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

A two-stage process with temperature-shift for enhanced anthocyanin production in strawberry cell suspension cultures

A two-stage process with temperature-shift has been developed to enhance the anthocyanin yield in suspension cultures of strawberry cells. The effect of the temperature-shift interval and the shift-time point was investigated for the optimization of this strategy. In this process, strawberry cells were grown at 30℃ （the optimum temperature for cell growth） for a certain period as the first stage, with the temperature shifted to a lower temperature for the second stage. In response to the temperature shift-down, anthoeyanin synthesis was stimulated and a higher content could be achieved than that at both boundary temperatures but cell growth was suppressed. When the lower boundary temperature was deereased, cell growth was lowered and a delayed, sustained maximum anthocyanin content was achieved. Anthocyanin synthesis was strongly influeneed by the shift-time point but cell growth was not. Consequently, the maximum anthocyanin content of 2.7 mg（?）g-fresh cell-1 was obtained on day 9 by a temperature-

A two-stage but time-saving reconstructive scheme to treat severe lower limb length discrepancy:Two case reports

Limb length discrepancy(LLD)is a common orthopedic condition that can result in significant functional impairment,pain,and cosmetic deformities.Current reconstructive techniques for severe LLD are primarily based on callus distraction,which is a time-consuming process that can lead to complications,such as significant infection,joint stiffness,and stress fractures.To reduce the therapeutic time and minimize the risk of complications,we investigated the use of vascularized bone flaps as a technical supplement to callus distraction in the reconstruction of short limbs.We present two cases of severe LLD in the upper and lower legs,in which a twostage reconstruction approach was used.In the first stage,external fixation was applied to the affected limb to correct the soft tissue length and convert the short deformity into a bone defect.In the second stage,the bone defect was reconstructed using bilateral(patient A)or unilateral(patient B)free vascularized fibula bone grafts.Both patients had complete survival of the fibular grafts without stress fractures,and bone consolidation took 8 months(patient A)and 4 months(patient B).Compared to the traditional callus distraction,the two-stage approach was found to be more time-saving and reliable.The entire reconstructive scheme required 18 and 4 months for patients A and B,respectively,whereas the traditional callus distraction required 41 and 17 months,respectively.These findings suggest that the use of vascularized bone flaps as a technical supplement for callus distraction may provide an effective and efficient alternative for the treatment of severe LLD.Further studies are needed to validate these results and assess the long-term outcomes of this approach.

A New Two-Stage Tunable Space-Time Adaptive Detector

In order to improve the rejection capability of mismatched interferer signals,a new two-stage detector is proposed under homogeneous scenarios with unknown covariance matrix,which is obtained by cascading the adaptive matched filter(AMF)detector and the enhanced RAO(EnRAO)detector.The new detector has constant false alarm performance,and the closed-form expression of probability of false alarm and probability of detection is derived.The performance of the new detector is assessed,and analyzed in comparison with other detectors.The results show that,the proposed detector can provide enhanced rejection capability in the case of mismatch,but the performance of the detector is slightly lost under the condition of matching.

Design and experiment of high-productivity two-stage vacuum pressure swing adsorption process for carbon capturing from dry flue gas

A two-stage vacuum pressure swing adsorption(VPSA)process that coupled kinetically controlled and equilibrium controlled separation process with reflux has been investigated for capturing carbon dioxide from dry flue gas(85%N_(2)/15%CO_(2)).In the first enriching stage,carbon molecular sieve(CMS),which shows kinetic selectivity for CO_(2)/N_(2),is adopted as the adsorbent to remove most N_(2)in feed gas,thereby upgrading CO_(2)and significantly reducing the amount for further refinement.The second stage loads zeolite 13X as adsorbent to purify the CO_(2)-rich flow from the first stage for meeting the requirements of National Energy Technology Laboratory.Series of experiments have been conducted for adsorption isotherms measuring and lab-scale experimental validation as well as analysis.The effect of feed composition on the separation performance of the PSA system was studied experimentally and theoretically here.The optimal results achieved 95.1%purity and 92.9%recovery with a high CO_(2)productivity(1.89 mol CO_(2)·h^(-1)·kg^(-1))and an appropriate energy consumption of 1.07 MJ·(kg CO_(2))^(-1).Further analysis has been carried out by simulation for explicating the temperature,pressure,and concentration distribution at cyclic steady state.

Nonlinear Modeling for a Two-Stage Degradation System Based on Nonhomogeneous Poisson Process

The degradation process modeling is one of research hotspots of prognostic and health management(PHM),which can be used to estimate system reliability and remaining useful life(RUL).In order to study system degradation process,cumulative damage model is used for degradation modeling.Assuming that damage increment is Gamma distribution,shock counting subjects to a homogeneous Poisson process(HPP)when degradation process is linear,and shock counting is a non-homogeneous Poisson process(NHPP)when degradation process is nonlinear.A two-stage degradation system is considered in this paper,for which the degradation process is linear in the first stage and the degradation process is nonlinear in the second stage.A nonlinear modeling method for considered system is put forward,and reliability model and remaining useful life model are established.A case study is given to validate the veracities of established models.

An Integrated Process of a Two-Stage Fixed Bed Syngas Production and F-T Synthesis for GTL in Remote Gas Field

A novel process for catalytic oxidation of methane to synthesis gas (syngas),which consists of two consecutive fixed-bed reactors with air introduced into the reactors,integrated Fischer-Tropsch synthesis,was investigated.At the Same time,a catalytic combustion technology has been investigated for utilizing the F-T offgas to generate heat or powr energy.The results show that the two-stage fixed reactor process keep away from explosion of CH4/O2.The integrated process is fitted to produce diesel oil and lubricating oil in remote gas field.

Empirical Study of Classification Process for Two-stage Turbo Air Classifier in Series

The suitable process parameters for a two-stage turbo air classifier are important for obtaining the ultrafine powder that has a narrow particle-size distribution, however little has been published internationally on the classification process for the two-stage turbo air classifier in series. The influence of the process parameters of a two-stage turbo air classifier in series on classification performance is empirically studied by using aluminum oxide powders as the experimental material. The experimental results show the following: 1) When the rotor cage rotary speed of the first-stage classifier is increased from 2 300 r/min to 2 500 r/min with a constant rotor cage rotary speed of the second-stage classifier, classification precision is increased from 0.64 to 0.67. However, in this case, the final ultrafine powder yield is decreased from 79% to 74%, which means the classification precision and the final ultrafine powder yield can be regulated through adjusting the rotor cage rotary speed of the first-stage classifier. 2) When the rotor cage rotary speed of the second-stage classifier is increased from 2 500 r/min to 3 100 r/min with a constant rotor cage rotary speed of the first-stage classifier, the cut size is decreased from 13.16 μm to 8.76 μm, which means the cut size of the ultrafine powder can be regulated through adjusting the rotor cage rotary speed of the second-stage classifier. 3) When the feeding speed is increased from 35 kg/h to 50 kg/h, the 'fish-hook' effect is strengthened, which makes the ultrafine powder yield decrease. 4) To weaken the 'fish-hook' effect, the equalization of the two-stage wind speeds or the combination of a high first-stage wind speed with a low second-stage wind speed should be selected. This empirical study provides a criterion of process parameter configurations for a two-stage or multi-stage classifier in series, which offers a theoretical basis for practical production.

Two-Stage Inspection Model Based on a Three-Stage Failure Process

As the non-periodic inspections are common in practice,a two-stage inspection model based on a three-stage failure process is proposed. The two-stage inspection means that the system is inspected with the first inspection interval T_1 and the second inspection interval T_2. Because of the three color schemes commonly used in industry,three stages are divided by the system lifetime:normal, minor defective and severe defective stages. Upon the failure of the system,replacement is carried out. Maintenance is done once identifying the severe defective stage. However,when the minor defective stage is identified by the second inspection interval T_2,action of halving the subsequent inspection interval is adopted.Otherwise,no action is required. Our objective function is to optimize the inspection intervals so as to minimize the expected cost per unit time. Finally,a numerical example is presented to illustrate the effectiveness of the proposed model.

Two-stage revision in periprosthetic knee joint infections

Periprosthetic joint infection(PJI)following total knee arthroplasty is one of the most catastrophic and costly complications that carries significant patient wellness as well as economic burdens.The road to efficiently diagnosing and treating PJI is challenging,as there is still no gold standard method to reach the diagnosis as early as desired.There are also international controversies with respect to the best approach to manage PJI cases.In this review,we highlight recent advances in managing PJI following knee arthroplasty surgery and discuss in depth the two-stage revision method.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Two-stage reproduction derived from cells of thallus could directly contribute to seeds for green tidal algal Enteromorpha(Ulva) prolifera/clathrata bloom,with disclosure of their ephemeral trait

Green tidal algal Enteromorpha species complete their life cycles by the isomorphic alternation of generations.The provenance of green tide caused by them in the western Yellow Sea has been disputed. The cell reproduction derived from adult thallus was observed on E. clathrata collected from Shantou City, Guangdong Province in this study. Subsequently, it further found that E. proliferia collected from Qingdao City, Shandong Province and Qinhuangdao City, Hebei Province, produced reproductive cells by somatic cells of its early infantile thallus or branch. The latter is functionally similar to that the seedlings of red alga Porphyra yezoensis produce the monospores, and could exquisitely explain the ephemeral or opportunistic trait and environmental adaptation ability of Enteromorpha species. Changes in growth conditions may induce the two types of cell reproduction.They contribute to the bloom, and can effectively reveal the seasonally occurring large-scale and on-year and offyear phenomenon. The latter may have played a decisive role in its formation. This paper analyses the legal status of the species name, the type of generation during bloom, ephemeral traits, the role of microscopic propagule, the area of origin, on-year and off-year phenomenon, early warning and prevention and control of the species, and so on. On this basis, further study on the influence of environmental factors on cell reproduction of early infantile thalli or branches will achieve a positive effect for early warning and prevention and control of the green tidal algal bloom.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.