On power series statistical convergence and new uniform integrability of double sequences

In the present paper,we mostly focus on P_(p)^(2)-statistical convergence.We will look into the uniform integrability via the power series method and its characterizations for double sequences.Also,the notions of P_(p)^(2)-statistically Cauchy sequence,P_(p)^(2)-statistical boundedness and core for double sequences will be described in addition to these findings.

A Hybrid Integrated and Low-Cost Multi-Chip Broadband Doherty Power Amplifier Module for 5G Massive MIMO Application

In this paper,a hybrid integrated broadband Doherty power amplifier(DPA)based on a multi-chip module(MCM),whose active devices are fabricated using the gallium nitride(GaN)process and whose passive circuits are fabricated using the gallium arsenide(GaAs)integrated passive device(IPD)process,is proposed for 5G massive multiple-input multiple-output(MIMO)application.An inverted DPA structure with a low-Q output network is proposed to achieve better bandwidth performance,and a single-driver architecture is adopted for a chip with high gain and small area.The proposed DPA has a bandwidth of 4.4-5.0 GHz that can achieve a saturation of more than 45.0 dBm.The gain compression from 37 dBm to saturation power is less than 4 dB,and the average power-added efficiency(PAE)is 36.3%with an 8.5 dB peak-to-average power ratio(PAPR)in 4.5-5.0 GHz.The measured adjacent channel power ratio(ACPR)is better than50 dBc after digital predistortion(DPD),exhibiting satisfactory linearity.

Channel estimation in integrated radar and communication systems with power amplifier distortion

To reduce the negative impact of the power amplifier(PA)nonlinear distortion caused by the orthogonal frequency division multiplexing(OFDM)waveform with high peak-to-average power ratio(PAPR)in integrated radar and communication(RadCom)systems is studied,the channel estimation in passive sensing scenarios.Adaptive channel estimation methods are proposed based on different pilot patterns,considering nonlinear distortion and channel sparsity.The proposed methods achieve sparse channel results by manipulating the least squares(LS)frequency-domain channel estimation results to preserve the most significant taps.The decision-aided method is used to optimize the sparse channel results to reduce the effect of nonlinear distortion.Numerical results show that the channel estimation performance of the proposed methods is better than that of the conventional methods under different pilot patterns.In addition,the bit error rate performance in communication and passive radar detection performance show that the proposed methods have good comprehensive performance.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.

有源电力滤波器补偿的PI解耦控制技术研究

电网中电压和电流波形的失真会产生谐波,导致电网功率因数降低,并影响电力系统的稳定性和可靠性。为了确保电力系统的正常工作,研究了基于有源电力滤波器补偿的比例积分(PI)解耦控制技术。设计了基于二极管钳位式的有源电力滤波器模型。结合基尔霍博电压法,降低控制谐波和解除部分变量耦合。针对设备非线性产生的谐波,分析有源电力滤波器的可逆性,获得输入雅可比矩阵,以实现滤波器旋转坐标的线性化。利用变换矩阵转换转动角速向量,输入谐波的幅度,输出电流取样延迟,完成无差PI解耦控制。试验结果表明,所提技术能够有效解耦滤波器的谐波电流成分,从而补偿电网中的失真电流。该技术可以减少谐波对电力系统的整体影响,保证设备的正常运行。

基于改进灰色预测单神经元PI的全超导托卡马克核聚变发电装置快控电源电流控制

全超导托卡马克核聚变发电装置(EAST)快控电源负载电感的电流受多种不确定环境因素的影响而难以预测,灰色预测无需精确对象模型,只需少量已知信息即可实现输出电流短期预测,已在EAST快控电源中有了一定研究应用。为解决灰色预测在EAST快控电源中对突变信号边沿预测精度低和预测延时时间长的问题,提出一种改进灰色预测算法实现输出电流预测。在一个开关周期内对输出电流进行等时长间隔采样4次作为原始序列,将滚动式采样预测改为逐周期采样预测,在实现灰色预测的过程中不必依赖过去几个周期的历史采样信息,只需本周期的4个原始采样值即可实现输出电流的预测。根据预测电流与参考电流误差自适应调整单神经元比例-积分(PI)控制的输出增益,实现输出电流的快速准确控制。仿真和实验结果表明,在EAST快控电源电流预测过程中所提出的改进灰色预测,对比传统灰色预测具有更高的预测精度和更小的预测延时,改进灰色预测变增益单神经元PI控制能够在减小电流超调的同时加快输出电流响应速度。

Multi-Sinusoidal Waveform Shaping for Integrated Data and Energy Transfer in Aging Channels

Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.

Traction power systems for electrified railways:evolution,state of the art,and future trends

Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.

Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.

An overview of the policies and models of integrated development for solar and wind power generation in China

Under the goal of “Carbon Emission Peak and Carbon Neutralization”, the integrated development between various industries and renewable energy(photovoltaic, wind power) is of great significance in China. This paper summarizes the relevant policies, integration schemes and typical cases of the integrated development between renewable energy and other industries. First, the development status of wind and solar generation in China is introduced. Second, we summarize the relevant policies issued by the National Development and Reform Commission, National Energy Administration and other departments to promote the integrated development in photovoltaic and wind power generation in China. Third, eight kinds of photovoltaic three-dimensional development models are described, including “photovoltaic + agriculture, industry, environmental protection, transportation, architecture, communication, hydrogen and ecology”. Fourth, eight kinds of wind power threedimensional development models are summarized, including “Offshore wind power + marine ranch, marine energy, marine tourism, marine oil and gas, hydrogen, communication, Energy Island” and “Onshore wind power+ courtyard”. In the future, the promotion and application of the above integrated development projects will be accelerated. This overview aims to provide reference for the design in photovoltaic and wind energy systems and help potential investors to make decisions.

NOMA Empowered Energy Efficient Data Collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.

Electricity-Carbon Interactive Optimal Dispatch of Multi-Virtual Power Plant Considering Integrated Demand Response

As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.

A Special Issue:“Key Technologies of Virtual Power Plant and Distributed Energy Resources”for Global Energy Interconnection

The increasing penetration of renewable and distributed energy resources(DERs)is transforming the power grid into a new type of clean and low-carbon power system.However,the uncertainty and volatility of DERs have also brought severe challenges to the secure and reliable operation of the power systems.In order to successfully integrate renewable DERs,virtual power plant(VPP)has emerged as a new technique for coordinating demand-side DERs,which has drawn significant attention from industry and academia.

Robust optimal dispatch strategy of integrated energy system considering CHP-P2G-CCS

Integrated energy systems(IESs)can improve energy efficiency and reduce carbon emissions,essential for achieving peak carbon emissions and carbon neutrality.This study investigated the characteristics of the CHP model considering P2G and carbon capture systems,and a two-stage robust optimization model of the electricity-heat-gascold integrated energy system was developed.First,a CHP model considering the P2G and carbon capture system was established,and the electric-thermal coupling characteristics and P2G capacity constraints of the model were derived,which proved that the model could weaken the electric-thermal coupling characteristics,increase the electric power regulation range,and reduce carbon emissions.Subsequently,a two-stage robust optimal scheduling model of an IES was constructed,in which the objective function in the day-ahead scheduling stage was to minimize the start-up and shutdown costs.The objective function in the real-time scheduling stage was to minimize the equipment operating costs,carbon emission costs,wind curtailment,and solar curtailment costs,considering multiple uncertainties.Finally,after the objective function is linearized with a ψ-piecewise method,the model is solved based on the C&CG algorithm.Simulation results show that the proposed model can effectively absorb renewable energy and reduce the total cost of the system.

全桥LLC谐振变换器的积分滑模-PI混合控制

全桥LLC谐振变换器的PI控制存在响应慢和鲁棒性差的问题,滑模控制存在高频抖振问题。针对这些问题,提出了基于模糊规则切换的积分滑模-PI混合控制方法。首先,通过扩展函数描述法建立全桥LLC谐振变换器的大信号模型,利用输入输出反馈线性化设计滑模面;然后,利用扫频法验证PI控制设计的合理性;最后,经多次实验,确定模糊控制的最佳输入和输出隶属度函数,实现在瞬态时由滑模控制起主导作用,在稳态时仅使用PI控制的混合控制方法。在MATLAB/Simulink中进行仿真分析,仿真结果表明,所提控制方法不仅具有滑模控制的瞬态响应快、鲁棒性强的优点,还消除了高频抖振,具有良好的控制效果。

Dispatch of a Coal Mine-Integrated Energy System:Optimization Model with Interval Variables and Lower Carbon Emission

In the coal mining process,a large amount of Coal Mine-Associated energy(CMAE),such as coal mine methane and underground wastewater,is produced.Research on the modeling and optimization dispatching of a Coal Mine-Integrated Energy System(CMIES)with CMAE effectively saves energy and reduces carbon pollution.CMAE has great uncertainties owing to the affections of the hydrogeology conditions and mining schedules.In addition,thermal loads have high comfort requirements in mines,which brings great challenges to the optimization dispatching of CMIESs.Therefore,this paper studies the architecture and solution of CMIESs with a flexible thermal load and source-load uncertainty.First,to effectively improve the electric and thermal conversion efficiency,the architecture of CMIES,including a concentrating solar power station,is built.Second,for the scheduling model with bilateral uncertainty,the interval representation method with interval variables is proposed,and a multi-objective scheduling model based on the interval variables and flexible thermal load is constructed.Finally,we propose a solution method for the model with interval variables.A case study is conducted to demonstrate the performance of our model and method for lowering carbon emissions and cost.

Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.

APF直流侧电压自适应PI控制

三相三线制有源滤波器(APF)大多采用传统的PI控制策略来控制直流侧的电容电压。为了提高有源滤波器的性能指标,在传统的PI控制基础上,结合最小隶属度模糊控制理论,提出模糊PI的直流侧电压自适应控制。模糊PI控制可以根据实时情况改变比例和积分参数,解决了传统PI控制器在非线性系统中的缺点。MATLAB仿真表明,模糊PI自适应控制与传统PI控制相比,跟踪性能更强,直流侧电压超调量更低,动态性能更好,并且有效地降低了电网谐波的畸变量。

永磁同步电机抗积分饱和PI控制研究

永磁同步电机矢量控制中传统PI控制器在给定输入发生较大幅度变化造成积分项逐渐累加,引起积分饱和,从而使转速及转矩超调,系统调节变缓,控制系统控制性能降低。针对这一问题,在传统PI控制基础上提出了一种抗积分饱和PI控制控制策略,将该控制策略分别应用到永磁同步电机速度环和电流环PI控制中。为验证该控制策略的有效性,基于MATLAB/Simulink仿真平台构建了永磁同步电机抗积分饱和PI控制系统仿真模型。仿真实验结果表明,与传统的PI控制算法相比较,所构建抗积分PI控制模型系统超调量明显降低,能够快速到达稳态,具有较好的动态性能和抗干扰能力。