Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.

Discussion on the Soil and Water Conservation Model in Mountain Photovoltaic Power Generation Project

In the context of rising global energy demand and increasing awareness of environmental protection,photovoltaic power generation,as a clean and renewable form of energy,has become increasingly important and has received widespread attention and application worldwide.However,during the construction and operation of mountain photovoltaic power generation projects,water and soil erosion has become a major challenge,which not only restricts the sustainable development process of the project,but also has a significant negative impact on the local ecological environment.This article deeply analyzes the multiple causes,extensive impacts and effective prevention and control strategies of water and soil erosion in mountain photovoltaic power generation projects.The results show that rainfall intensity,terrain slope,soil type and vegetation coverage are the four key factors leading to soil erosion.Soil erosion not only causes a sharp decline in soil fertility,but also aggravates the problem of sediment deposition in rivers and reservoirs,and poses a direct threat to the stability and operating efficiency of photovoltaic equipment.In order to deal with the above problems,this paper innovatively puts forward a series of soil and water conservation technologies,covering multiple dimensions such as engineering measures,plant measures,farming measures and temporary measures,and deeply discusses the application models and management strategies of these measures in key stages such as planning and design,construction,operation and maintenance.Through specific case analysis,the successful practical experience of soil and water conservation is refined and summarized,and the key role of community cooperation,technical support and modern monitoring technology in preventing and controlling soil and water erosion is further emphasized.This article aims to achieve a win-win situation of ecological environment protection and energy development and utilization through scientific planning and effective governance,and contribute to the construction of a green,low-carbon,and sustainable energy system.

Topic Controlled Steganography via Graph-to-Text Generation

Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.

Feasibility Assessment of Fast Numerical Simulations for Real-Time Monitoring and Control of PEM Fuel Cells

Computational models that ensure accurate and fast responses to the variations in operating conditions,such as the cell tem-perature and relative humidity(RH),are essential monitoring tools for the real-time control of proton exchange membrane(PEM)fuel cells.To this end,fast cell-area-averaged numerical simulations are developed and verifi ed against the present experiments under various RH levels.The present simulations and measurements are found to agree well based on the cell voltage(polarization curve)and power density under variable RH conditions(RH=40%,RH=70%,and RH=100%),which verifi es the model accuracy in predicting PEM fuel cell performance.In addition,computationally feasible reduced-order models are found to deliver a fast output dataset to evaluate the charge/heat/mass transfer phenomena as well as water production and two-phase fl ow transport.Such fast and accurate evaluations of the overall fuel cell operation can be used to inform the real-time control systems that allow for the improved optimization of PEM fuel cell performance.

Next Generation Transcriptome Sequencing and Quantitative Real-Time PCR Technologies for Characterisation of the Bemisia tabaci Asia 1 mtCOI Phylogenetic Clade

A programme of functional genomics research is underway at the University of Greenwich,UK,to develop and apply genomics technologies to characterise an economically-important but under-researched Bemisia tabaci（Hemiptera：Aleyrodidae）,the Asia 1 mtCOI phylogenetic group.A comparison of this putative species from India with other important B.tabaci populations and insect species may provide targets for the development of more effective whitefly control strategies.As a first step,next-generation sequencing（NGS）has been used to survey the transcriptome of adult female whitefly,with high quality RNA preparations being used to generate cDNA libraries for NGS using the Roche 454 Titanium DNA sequencing platform.Contig assemblies constructed from the resultant sequences（301 094 reads）using the software program CLC Genomics Workbench generated 3 821 core contigs.Comparison of a selection of these contigs with related sequences from other B.tabaci genetic groups has revealed good alignment for some genes（e.g.,HSP90）but misassemblies in other datasets（e.g.,the vitellogenin gene family）,highlighting the need for manual curation as well as collaborative international efforts to obtain accurate assemblies from the existing next generation sequence datasets.Nevertheless,data emerging from the NGS has facilitated the development of accurate and reliable methods for analysing gene expression based on quantitative real-time RT-PCR,illustrating the power of this approach to enable rapid expression analyses in an organism for which a complete genome sequence is currently lacking.

Control Effects of Several Technical Measures on Overwintering Generation of Oriental Fruit Moth in Peach Orchard

Peeling trunk,binding insect-attracting belt,cleaning orchard and soil-covering under the crown were the control methods on overwintering generation of oriental fruit moth.However,they had not been applied widely on the production because of the lack of systematic quantitative evaluation.Aiming at this fact,the control effects of these technical measures were studied in peach with different ripening period.The results showed that peeling trunk was the best with the control effect of88.64%.The control effect of binding insect-attracting belt of grass bundle was74.13%,which was the most economical and efficient.Covering with soil layer of 3cm under the crown during the middle ten days of March could holdback the adult getting out from soil.Cleaning deadwood could clean out the overwintering larvae on the ground.

Quality control of marine big data——a case study of real-time observation station data in Qingdao

Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.

Applying real-time control to enhance the performance of nitrogen removal in CAST system

A bench-scale reactor（72 L） red with domestic sewage, was operated more than 3 months with three operation modes： traditional mode, modified mode and real-time control mode, so as to evaluate effects of the operation mode on the system performance and to develop a feasible control strategy. Results obtained from fixed-time control study indicate that the variations of the pH and oxidation-reduction potential（ORP） profiles can represent dynamic characteristics of system and the cycle sequences can be controlled and optimized by the control points on the pH and ORP profiles. A control strategy was, therefore, developed and applied to real-time control mode. Compared with traditional mode, the total nitrogen（TN） removal can be increased by approximately 16% in modified mode and a mean TN removal of 92% was achieved in real-time control mode. Moreover, approximately 12.5% aeration energy was saved in real- time control mode. The result of this study shows that the performance of nitrogen removal was enhanced in modified operation mode. Moreover, the real-time control made it possible to optimize process operation and save aeration energy.

Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems:An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.

Control performance comparison between tuned liquid damper and tuned liquid column damper using real-time hybrid simulation

Tuned liquid damper (TLD) and tuned liquid column damper (TLCD) are two types of passive control devices that are widely used in structural control. In this study, a real-time hybrid simulation (RTHS) technique is employed to investigate the diff erence in control performance between TLD and TLCD. A series of RTHSs is presented with the premise of the same liquid length, mass ratio, and structural parameters. Herein, TLD and TLCD are physically experimented, and controlled structures are numerically simulated. Then, parametric studies are performed to further evaluate the diff erent performance between TLD and TLCD. Experimental results demonstrate that TLD is more eff ective than TLCD under diff erent amplitude excitations.

Intercross real-time control strategy in alternating activated sludge process for short-cut biological nitrogen removal treating domestic wastewater

To develop technically feasible and economically favorable dynamic process control(DPC)strategies for an alternating activated sludge(AAS)system,a bench-scale continuous-flow alternating aerobic and anoxic reactor,performing short-cut nitrogen removal from real domestic wastewater was operated under different control strategies for more than five months.A fixed-time control(FTC) study showed that bending-points on pH and oxidation-reduction potential(ORP)profiles accurately coincided with the major biologic...

Validation of housekeeping genes as internal controls for studying the gene expression in Pyropia haitanensis(Bangiales, Rhodophyta) by quantitative real-time PCR

Pyropia haitanensis is an economically important mariculture crop in China and has a high research value for several life phenomena, for example environmental tolerance. To explore the mechanisms underlying these characteristics, gene expression has been investigated at the whole transcriptome level. Gene expression studies using quantitative real-time PCR should start by selecting an appropriate internal control gene; therefore, the absolute expression abundance of six housekeeping genes （18S rRNA （18S）, ubiquitin-conju-ating enzyme （UBC）, actin （ACT）, β-tubulin （TUB）, elongation factors 2 （EF2）, and glyceraldehyde-3-phos- phate dehydrogenase （GAPDH） examined by the quantitative real-time PCR in samples corresponding to different strains, life-cycle stages and abiotic stress treatments. Their expression stabilities were assessed by the comparative cycle threshold （Ct） method and by two different software packages： geNorm and NormFinder. The most stable housekeeping gene is UBC and the least stable housekeeping is GADPH. Thus, it is proposed that the most appropriate internal control gene for expression analyses in P. haitanensis is UBC. The results pave the way for further gene expression analyses of different aspects of P. haitanensis biology including different strains, life-history stages and abiotic stress responses.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Construction Simulation and Real-Time Control for High Arch Dam

A method of combining dynamic simulation with real-time control was proposed to fit the randomness and uncertainty in the high arch dam construction process. The mathematical logic model of high arch dam construction process was established. By combining dynamic construction simulation with schedule analysis, the process of construction schedule forecasting and analysis based on dynamic simulation was studied. The process of real-time schedule control was constructed and some measures for dynamic adjustment and control of construction schedule were provided. A system developed with the method is utilized in a being constructed hydroelectric project located at the Yellow River in northwest China, which can make the pouring plan of the dam in the next stage (a month, quarter or year) to guide the practical construction. The application result shows that the system provides an effective technical support for the construction and management of the dam.

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Following Control for a UUV using Temporary Path Generation Guidance

A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.

Real-time hybrid simulation for structural control performance assessment

Real-time hybrid simulation is an attractive method to evaluate the response of structures under earthquake loads. The method is a variation of the pseudodynamic testing technique in which the experiment is executed in real time, thus allowing investigation of structural systems with rate-dependent components. Real-time hybrid simulation is challenging because it requires performance of all calculations, application of displacements, and acquisition of measured forces, within a very small increment of time. Furthermore, unless appropriate compensation for actuator dynamics is implemented, stability problems are likely to occur during the experiment. This paper presents an approach for real-time hybrid simulation in which compensation for actuator dynamics is implemented using a model-based feedforward compensator. The method is used to evaluate the response of a semi-active control of a structure employing an MR damper. Experimental results show good agreement with the predicted responses, demonstrating the effectiveness of the method for structural control performance assessment.

Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems

With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

Multi-channel 28-GHz millimeter-wave signal generation on a silicon photonic chip with automated polarization control

We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave(MMW) signals for 5 G multi-user applications. The fabricated silicon photonic chip has a footprint of 1.1 × 2.1 mm^2 and integrates 7 independent channels each having on-chip polarization control and heterodyne mixing functions. 7 channels of4-Gb/s QPSK baseband signals are delivered via a 2-km multi-core fiber(MCF) and coupled into the chip with a local oscillator(LO) light. The polarization state of each signal light is automatically adjusted and aligned with that of the LO light, and then 7 channels of 28-GHz MMW carrying 4-Gb/s QPSK signals are generated by optical heterodyne beating. Automated polarizationcontrol function of each channel is also demonstrated with ～7-ms tuning time and ～27-dB extinction ratio.