Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.

Low-carbon generation expansion planning considering uncertainty of renewable energy at multi-time scales

With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.

Topology Optimization for Harmonic Excitation Structures with Minimum Length Scale Control Using the Discrete Variable Method

Continuumtopology optimization considering the vibration response is of great value in the engineering structure design.The aimof this studyis toaddress the topological designoptimizationof harmonic excitationstructureswith minimumlength scale control to facilitate structuralmanufacturing.Astructural topology design based on discrete variables is proposed to avoid localized vibration modes,gray regions and fuzzy boundaries in harmonic excitation topology optimization.The topological design model and sensitivity formulation are derived.The requirement of minimum size control is transformed into a geometric constraint using the discrete variables.Consequently,thin bars,small holes,and sharp corners,which are not conducive to the manufacturing process,can be eliminated from the design results.The present optimization design can efficiently achieve a 0–1 topology configuration with a significantly improved resonance frequency in a wide range of excitation frequencies.Additionally,the optimal solution for harmonic excitation topology optimization is not necessarily symmetric when the load and support are symmetric,which is a distinct difference fromthe static optimization design.Hence,one-half of the design domain cannot be selected according to the load and support symmetry.Numerical examples are presented to demonstrate the effectiveness of the discrete variable design for excitation frequency topology optimization,and to improve the design manufacturability.

Research on the intelligent internet nursing model based on the child respiratory and asthma control test scale for asthma management of preschool children

BACKGROUND Childhood asthma is a common respiratory ailment that significantly affects preschool children.Effective asthma management in this population is particularly challenging due to limited communication skills in children and the necessity for consistent involvement of a caregiver.With the rise of digital healthcare and the need for innovative interventions,Internet-based models can potentially offer relatively more efficient and patient-tailored care,especially in children.AIM To explore the impact of an intelligent Internet care model based on the child respiratory and asthma control test(TRACK)on asthma management in preschool children.METHODS The study group comprised preschoolers,aged 5 years or younger,that visited the hospital's pediatric outpatient and emergency departments between January 2021 and January 2022.Total of 200 children were evenly and randomly divided into the observation and control groups.The control group received standard treatment in accordance with the 2016 Guidelines for Pediatric Bronchial Asthma and the Global Initiative on Asthma.In addition to above treatment,the observation group was introduced to an intelligent internet nursing model,emphasizing the TRACK scale.Key measures monitored over a six-month period included the frequency of asthma attack,emergency visits,pulmonary function parameters(FEV1,FEV1/FVC,and PEF),monthly TRACK scores,and the SF-12 quality of life assessment.Post-intervention asthma control rates were assessed at six-month follow-up.RESULTS The observation group had fewer asthma attacks and emergency room visits than the control group(P<0.05).After six months of treatment,the children in both groups had higher FEV1,FEV1/FVC,and PEF(P<0.05).Statistically significant differences were observed between the two groups(P<0.05).For six months,children in the observation group had a higher monthly TRACK score than those in the control group(P<0.05).The PCS and MCSSF-12 quality of life scores were relatively higher than those before the nursing period(P<0.05).Furthermore,the groups showed statistically significant differences(P<0.05).The asthma control rate was higher in the observation group than in the control group(P<0.05).CONCLUSION TRACK based Intelligent Internet nursing model may reduce asthma attacks and emergency visits in asthmatic children,improve lung function,quality of life,and the TRACK score and asthma control rate.The effect of nursing was significant,allowing for development of an asthma management model.

Multi-time scale analysis of precipitation variation in Guyuan, China:1957-2005

Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.

Small-scale fire tests in the underwater tunnel section model with new sidewall smoke extraction

The Shenzhen–Zhongshan Bridge is a 24‐km‐long bridge and tunnel system,including a 6.8-km-long super cross section subsea tunnel.To solve the smoke exhaust problem of a super large cross-section subsea tunnel,the tunnel has a new smoke exhaust system that combines a horizontal smoke exhaust cross section at the top and sidewall smoke exhaust holes.In order to evaluate the potential fire hazards of this type of tunnel,a 1:30 tunnel model was established and 140 smallscale experiments on underwater tunnel fires were conducted.By changing the fire power,fire location,and fan operation mode,different scenarios of submarine immersed tunnel fire were simulated and the related key parameters such as fire smoke diffusion behavior and smoke temperature distribution were studied.On this basis,the optimal smoke control strategy was proposed for different fire scenarios.The research results indicate that the new smoke exhaust system can fully utilize the smoke flow characteristics,significantly improve smoke exhaust efficiency,and increase available evacuation time,thus further enhancing the fire safety of super large cross-section subsea tunnels.

Market-based control strategy for long-span structures considering the multi-time delay issue

To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.

Research on multi-time scale doubly-fed wind turbine test system based on FPGA+CPU heterogeneous calculation

As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.

Optimal Tracking Controller Design for a Small Scale Helicopter

A model helicopter is more difficult to control than its full scale counterpart. This is due to its greater sensitivity to control inputs and disturbances as well as higher bandwidth of dynamics. This work is focused on designing practical tracking controller for a small scale helicopter following predefined trajectories. A tracking controller based on optimal control theory is synthesized as a part of the development of an autonomous helicopter. Some issues with regards to control constraints are addressed. The weighting between state tracking performance and control power expenditure is analyzed. Overall performance of the control design is evaluated based on its time domain histories of trajectories as well as control inputs.

Application of Time Scale to Parameters Tuning of Active Disturbance Rejection Controller for Induction Motor

Active disturbance rejection controller (ADRC) has good performance in induction motor (IM) control system, but controller parameter is difficult to tune. A method of tuning ADRC parameter by time scale is analyzed. The IM time scale is obtained by theoretical analysis. Combining the relations between scale time and ADRC parameters, ADRC parameter tuning in IM vector control based stator flux oriented is obtained. This parameter tuning method is validated by simulations and it provides a new technique for tuning of ADRC parameters of IM.

Remote Control and Telemetry System for Large-scale Model Test at Sea

Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary to have a stable experimental system for the test.Since the experimental area is large, a remote control system and a telemetry system are essential, and were designed by the authors.An experiment was conducted on the Songhuajiang River to test the systems.The relationship between the model's speed and its electromotor's revolutions was also measured during the model test.The results showed that the two systems make it possible to carry out large-scale model tests at sea.

Assessment of Stress Cognitive Control and Executive Function with Stress Control Rating Scale (ECOSTRESS) and Low Resolution Brain Electromagnetic Tomography (LORETA) (In Portuguese People in Situations of Unemployment and Economic Insufficiency)

This article reviews the constructs of stress, appraisal, coping, according to a transactional perspective, and executive function, and presents a stress control rating scale (ECOSTRESS), which design is founded in these constructs. This psychometric tool is useful in the assessment of cognitive control of stress, correlated with the function of dorsolateral prefrontal cortex. It has been validated for its use in the assessment of Portuguese people in situations of stress related to unemployment and economic insufficiency. Also, within the context of the cognitive control of stress, it is highlighted the usefulness of low resolution brain electromagnetic tomography (LORETA).

Decentralized robust guaranteed cost control for a class of interconnected singular large-scale systems with time-delay and parameter uncertainty

The decentralized robust guaranteed cost control problem is studied for a class of interconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality （LMI） via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.

Filter-based iterative learning control for linear large-scale industrial processes

In the procedure of the steady-state hierarchical optimization with feedback for large-scale industrial processes, a sequence of set-point changes with different magnitudes is carried out on the optimization layer. To improve the dynamic performance of transient response driven by the set-point changes, a filter-based iterative learning control strategy is proposed. In the proposed updating law, a local-symmetric-integral operator is adopted for eliminating the measurement noise of output information,a set of desired trajectories are specified according to the set-point changes sequence, the current control input is iteratively achieved by utilizing smoothed output error to modify its control input at previous iteration, to which the amplified coefficients related to the different magnitudes of set-point changes are introduced. The convergence of the algorithm is conducted by incorporating frequency-domain technique into time-domain analysis. Numerical simulation demonstrates the effectiveness of the proposed strategy,

Japanese Version of the Parent Health Locus of Control Scales: Validity and Reliability

The Parent Health Locus of Control (PHLOC) Scales measure parents’ beliefs about the factors that affect their children’s health. The aim of our study was to develop a Japanese version of the Parent Health Locus of Control (JPHLOC) Scales and to verify its validity and reliability. The JPHLOC scales consist of six scales: Professional Influence, Parental Influence, Child Influence, Media Influence, Fate Influence, and God, Buddha, and the Spirits Influence. Our questionnaire was administered to 231 principal caregivers from Japan whose children were under 6 years of age. The items, related to the “God, Buddha, and the Spirits Influence” scale, showed a floor effect. The exploratory factor analysis indicated that JPHLOC’ six factors functioned similarly to the PHLOC’ factors. The Fate Influence and Child Influence factor structures in JPHLOC scales were different from the corresponding factor structures in the original PHLOC scales in the functioning of only one item. There were statistically significant correlations between JPHLOC scales and Japanese version of the Parenting Stress Index-Short Form (PSI-SF), which add evidence to the criterion-related validity of JPHLOC scales. Furthermore, applying the known-groups method, our study showed that there was a significant difference across the JPHLOC scale scores, owning to differences in the children’s and caregivers’ demographics, which provides an evidence for construct validity. The Cronbach’s alpha coefficients for the six scales were estimated between 0.73 and 0.93. In a test-retest study, the interclass correlation coefficients for the six scales were ranged between 0.80 and 0.90. The results suggested that the JPHLOC scales have sufficient reliability and validity. The JPHLOC scales are applicable to the caregivers of healthy children. We confirm that the PHLOC scales are also applicable to Japanese caregivers.

Sample-data Decentralized Reliable H∞ Hyperbolic Control for Uncertain Fuzzy Large-scale Systems with Time-varying Delay

这份报纸学习样品数据的问题为有变化时间的延期的不明确的连续时间的模糊大规模系统的可靠 H 夸张控制。第一，模糊夸张模型( FHM )被用来为某些复杂大规模系统建立模型，然后根据 Lyapunov 指导方法和大规模系统的分散的控制理论，线性 matrixine 质量( LMI )基于条件 arederived toguarantee H 性能不仅当所有控制部件正在操作很好时，而且面对一些可能的致动器失败。而且，致动器的精确失败参数没被要求，并且要求仅仅是失败参数的更低、上面的界限。条件依赖于时间延期的上面的界限，并且不依赖于变化时间的延期的衍生物。因此，获得的结果是不太保守的。最后，二个例子被提供说明设计过程和它的有效性。

Decentralized Iterative Learning Controllers for Nonlinear Large-scale Systems to Track Trajectories with Different Magnitudes

在为大规模工业进程的层次不变的优化编程，一种可行技术是使用真实系统的信息以便修改基于模型的最佳。在这种情形，有不同大小的步功能类型控制决定的一个序列被计算，由哪个真实系统连续地被刺激。在这份报纸，一套反复的学习控制器为大规模非线性的工业过程的一个班在分散的模式被嵌进层次不变的优化的过程。为每个分系统的控制器被用来产生升级的控制信号的一个序列以便与不同规模承担顺序的步骤控制决定的责任。学习控制设计的目的是连续地精制系统的短暂性能。借助于卷绕旋转积分的 Hausdorff 年轻的不平等，更新的规则的集中在 Lebesgue-p 标准的意义被分析。集中上的非线性和相互作用的发明被讨论。建议控制计划的有效性和有效性被一些模拟表明。

On the decomposition problem of neutral type linear large scale control system in the theory of stabilization(1)

In this paper we choose the symmetric positive definite solutionof Riccati matrix algebraic equation and,construct a positive defini-tequadratic form V-function and,use Lyapunov deco mpositionequivalence method founded by Liu Yong-qing to obtain the condi-tions of the asymptotic stability of the solution of neutral typelinear large scale control system,the estimate formula of thedecom posing coefficients and time delay are also given.