To address the issues of a low number of levels and poor torque ripple suppression effect in existing asymmetric bridge power converters for switched reluctance motors(SRM),a direct instantaneous torque control(DITC)based on a novel multi-level power converter is proposed.Firstly,a bridge arm shared five-level power conversion topology was derived for the SRM.Control flexibility was increased by achieving multiple-level combinations with the least number of power devices by providing shared bridge arms both vertically and horizontally.Secondly,an improved DITC strategy with limited switching states is developed to eliminate the switching state disorder in the commutation overlap zone caused by shared bridge arms.On this basis,various factors such as torque error,rotor position,and capacitor voltage balance are comprehensively considered to formulate conduction rules for each phase to minimize motor torque ripple.The suggested bridge arm shared multilevel torque control not only lowers current and torque ripple but also enhances motor copper loss and operating efficiency,according to comparative simulation and experimental results with traditional asymmetrical bridge power converters.

The photovoltaic (PV) power generation process is susceptible to the interference of meteorological factors with volatility, which seriously impacts the stability of PV grid connection. To solve the above problems, this paper proposes a numerical prediction method for PV power generation with improved K-means, HPO-VMD and HPO-BiLSTM. Firstly, to reduce the influence of data diversity and randomness on the PV power prediction accuracy, the arrangement entropy is combined with K-means clustering algorithm to achieve weather typing under different meteorological factors. Then, for the existence of strong volatility and randomness of PV power data, HPO-VMD data decomposition method is proposed to achieve adaptive data decomposition and improve the smoothness of PV power values. Subsequently, the PV power numerical prediction model is constructed based on the BiLSTM method. Meanwhile, to reduce the adverse effects of improper selection of model parameters on the model prediction accuracy, the hunter–prey algorithm (HPO) is used to achieve the model parameter rectification. Finally, simulation experiments of the proposed method are conducted based on actual data from Alice Springs site, and the experimental and analytical results verify the effectiveness and generalization of the proposed method.

To address the issues of low control precision and potentially unsolvable control laws for flexible joint under uncertain disturbance and multiple constraints, a model predictive control (MPC) method based on an unknown state estimator (USE) and constraint adaptive hierarchical planning (CAHP) is proposed. The USE designed based on the low-pass filter can estimate the lumped disturbance without relying on the acceleration signal feedback and the accurate dynamic model, and is compatible with discretized predictive models. Meanwhile, a constraint adaptive hierarchical planning (CAHP) method is designed based on propositional logic. Adaptive weighting coefficients dynamically adjust the priority of constraints like obstacle avoidance and saturation. This enhances the solvability of the control problem while maximizing constraint satisfaction. Simulation results show that the proposed method enables the flexible joint system to achieve high-accuracy trajectory tracking and effective obstacle avoidance under uncertain disturbances, while satisfying all constraint conditions. Compared with the traditional fixed priority MPC method, the USE-CAHP-MPC method improves the control accuracy and robustness of the flexible joint drive system.

In order to solve the problems of interconnection and communication security of monitoring system the distributed energy resources (DER) with different ownership, the virtual power plant (VPP) can be effectively employed. This paper proposes the information model of DER monitoring terminal based on the IEC 61850-7-420, and studies the extensible message and presence protocol (XMPP) mapping to realize the real-time data communication service. The built-in security mechanisms TLS (Transport Layer Security) and SASL (simple authentication and security layer) of XMPP can ensure the security of information transmission. This paper also presents a platform to test the transmission performance of XMPP mapping, and the results show that XMPP properly meets the security communication requirements of DER monitoring system.

The mismatch between the rate of the new energy development and the system’s peak-shaving capacity has resulted in severe wind abandonment. Based on the grid connection of wind power and natural gas peak-shaving, a model of unit commitment considering wind power consumption and natural gas peak-shaving and taking into account a combination of system economics and wind power consumption capability is designed. Natural gas peak-shaving is added to improve the system’s peak-shaving capacity, and a wind abandonment penalty constraint is added to reduce the amount of wind abandoned by the system, and the model is solved by an improved genetic algorithm. Finally, to verify how wind power and natural gas peak-shaving impact unit commitment, the IEEE-30 node system is used. The results show that natural gas peak-shaving reduces system operating costs and improves the safety of the system. This model ensures the economics of system operation while positively promoting wind power consumption effectively and reasonably.

To enhance the performance and robustness of predictive torque control amidst modeling errors and parameter variations in switched reluctance motor (SRM) drive systems, this paper proposes a model-free predictive torque control strategy utilizing a linear extended state observer. Initially, a novel torque error dynamic compensation method is introduced, enabling accurate mapping of phase torque to phase current. This method is characterized by its simplicity, ease of parameter setting, and its capability to bypass the complexities of solving the torque inverse model. Subsequently, an improved model-free predictive control algorithm is developed for current regulation. This algorithm substitutes the SRM’s nonlinear model with a super local model and employs a linear extended state observer to estimate internal disturbances, such as model errors and parameter variations. The primary advantage of this algorithm is its data-driven nature, eliminating the dependence on precise mathematical models of the motor drive system. Ultimately, the reference voltage, generated by combining the current and disturbance estimation values from the linear extended state observer, is modulated via PWM and conveyed to the power converter to facilitate torque smoothing control. The efficacy of the proposed control method in enhancing parameter robustness and reducing torque ripple in SRM drive systems has been corroborated through simulations and experimental studies.

Accurate phase line topology identification of LV lines facilitates the handling of line faults, which is of great significance for the safe and stable operation of distribution networks. In this paper, we model and analyze the LV lines based on graph theory, and propose a phase line relationship identification scheme based on the combination of HPLC and k-means clustering for the problem of missing or dynamically changing phase line relationships of LV lines in the station area. Aiming at the known phase-line relationship in the station area such as distribution panel, two phase-line configuration schemes, Terminal extension and new phase-line description logical node PPLD, are proposed. The area is divided by combining the configuration information of IEC 61850 SCL and the information of metering automation system. If HPLC is configured in the unknown region, HPLC is used to identify the phase line relationship. If HPLC is not configured, k-means based algorithm is used for correlation analysis between voltage measurements. Example results from a place in Shandong show that the accuracy of the method proposed in this paper is 93.96 % on average, which is higher compared to the existing methods.Significance: Accurate identification of phase-line relationships in LV lines is essential for optimising load through phase-change switches. In this study, we propose a novel phase line relationship identification scheme that combines HPLC and k-means algorithm based on the existing equipment in the station area. Leveraging the known topology within the existing equipment (LTU, switchboard, etc.) in the station area, we introduce two phase line configuration schemes, Terminal extension (extending the known phase line relationship) and the new phase line description logical node PPLD (a novel approach for configuring known phase line relationships). Additionally, we suggest a method of regional division to recognise phase line relationships in unknown regions. If HPLC is configured, it is used for phase line identification; otherwise, a k-means based algorithm analyses voltage measurements. By tailoring identification schemes to the actual characteristics of the station area, we significantly reduce the amount of data to be identified, improving accuracy and resource efficiency.

针对同步磁阻电机模型预测转矩控制转矩脉动大且受电感参数影响大的问题,提出一种改进的同步磁阻电机模型预测转矩控制方法.利用带遗忘因子的递推最小二乘法对电感参数进行辨识,将辨识得到的电感参数用于模型预测转矩控制中,可提高模型预测控制中数学模型的准确性、减少电感参数变化对模型预测转矩控制性能的影响.引入离散空间矢量调制技术,该技术通过合成大量的虚拟矢量提高系统的稳态性能,同时提出一种电压矢量选择简化方法,避免计算全部电压矢量,可减少计算量.仿真结果表明,该方法转矩与磁链脉动小,具有良好的动稳态性能.

Ice accretion on transmission lines seriously threaten the stable operation of power grid. The current research focuses on the discharge development and flashover characteristics of ice‐covered insulator. Due to the irregular structure of the insulator, very few studies concentrate on the mechanism of ice accumulation. In the present study, the local collision coefficient was determined, and then a three‐dimensional numerical model for rime ice deposit accumulation on polymeric insulator was established based on computational fluid dynamics and verified by experiments. Results show that the local collision efficiency decreases along the rod and the edge of the shed from the front stagnation point to both sides, whose maximum values are 0.73 and 0.74 in the research scope. Rime ice amount on the insulator increases with the increment of environmental parameters including wind velocity, liquid water content, and median volume diameter of water droplet. It was proved by numerical simulation and artificial tests that the position with a high collision efficiency is heavily covered with rime ice. Through comparison and analysis, the numerical model can well simulate the process of rime ice accretion on polymeric insulator, and the relative error of ice amount between calculated by the model and that obtained by the test is less than 18.8%. The research in this paper realizes the visualization of rime ice‐coating process of polymeric insulator. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

The large-scale access of distributed power puts forward higher requirements for the monitoring of the distribution networks, and the topology identification of low-voltage power lines can effectively promote the integration of monitoring data and the distribution network information, effectively realizing the rapid identification of faults and ensuring the safety of users. In this paper, the method of graph theory was used to simplify the analysis of low-voltage lines, and the full topology identification strategy was proposed. Based on IEC 61850 SCL topology configuration information, line topology identification within the region was realized, and the correlation between regions was determined by the injection method. According to the configuration information, regional association information, and user’s collection information, the low-voltage station area line topology was divided into known regional topology and unknown regional topology. Aiming for the identification of line topology in the unknown region, according to the similarity of voltage fluctuations over short electrical distances, clustering analysis of user’s voltage data in the unknown region was carried out based on the k-means clustering algorithm. The test results showed that this scheme can realize the identification of topology in the region.

针对仿人柔性关节负载突变引起的关节振动问题,提出一种基于状态观测器的转矩补偿控制方法.通过控制电动机输出与扰动力矩等值的转矩增量,使关节力矩快速平衡变化后的负载力矩,缩短弹性元件被动适应负载变化的振荡过程.设计了估计负载扰动转矩和电动机转速的状态观测器,并利用Lyapunov函数证明其收敛性;建立基于比例积分-积分比例(PI-IP)转速调节器的驱动系统控制结构,并将观测器的输出前馈输入到转速调节器中,提高系统抗干扰能力.仿真结果表明,与比例积分微分(PID)控制和关节力反馈比例微分(PD)控制相比,所提方法能够在负载变化后的 0.6s内使电动机转速恢复稳定,并在 1 s内实现关节振动抑制,关节转速调节时间分别缩短了约 1.8s和 0.9s,有效提升系统动态调节能力.最后,通过在一体化柔性关节测试平台上的实验,验证了所提方法的有效性.

针对开关磁阻电机(SRM)常规终端滑模控制器(SMC)响应速度慢和传统滑模观测器(SMO)存在的抖振问题,提出一种基于改进终端SMC和变速趋近律SMO的SRM瞬时转矩控制(DITC)方法.设计了电机速度误差可快速收敛的改进非奇异快速终端滑模面和可自适应调整趋近律速度的变速幂次趋近律,利用等效控制法,得出了连续非奇异控制律.通过Lyapunov函数证明了该系统的稳定性和有限时间收敛性.设计了变速趋近律SMO以实现SRM无位置传感器控制.采用双曲正切函数作为切换函数,并引入快速幂次趋近律作为SMO速度观测的趋近律,克服了传统SMO固定开关增益带来的抖振和收敛速度问题.通过Lyapunov函数证明了SMO运行的稳定性.仿真和实验验证了所提方法的有效性.结果表明:与常规终端SMC相比,改进终端SMC能够在0.07 s内实现对期望转速的跟踪,调节时间减少了0.04 s,并且系统稳定时转速波动降低了0.5 r/min,具有更好的响应速度和稳定性.在负载突增时,系统转速可在0.02 s内调节至给定值,恢复时间减少了0.05 s,具有更好的调节性能.变速趋近律SMO能够在0.01 s内实现转速估计误差的收敛,且误差波动维持在2 r/min以内,可实现电机转速和转子位置的准确估计.

矿用三角形连接异步电动机利用真空断路器投入电网时,会引起电网电压下降,产生过大的瞬态电流,破坏电机的绝缘强度.为解决这一问题,文章提出一种采用永磁真空断路器分相将三角形连接异步电动机投入电网的控制策略.在转速为0的条件下,建立投入电网过程中异步电动机两相非对称与三相对称的数学模型,确定定子电流与合闸相位的时域表达式,分析不同合闸相位对定子电流的影响,结合电机参数推导出电机各相投入电网的最佳相位.仿真结果表明,在最佳的合闸相位,电机B、C两相同时投入电网,随后A相投入电网,电机启动电流相较于三相同时投入减小38.65％,考虑实际合闸固有时间误差最大波动情况下,启动电流减小30.65％,说明电机利用永磁真空断路器分相投入电网方法可以很好地抑制电机启动时产生的瞬态冲击电流.

针对传统阿胶制粒机多电机速度同步控制精度低和控制系统响应速度慢的问题,提出了一种无速度传感器的多电机均值耦合非奇异全局快速Terminal滑模速度同步控制方法.首先,设计转速自适应磁链观测器,避免了加热筒体温度较高导致电机速度传感器检测精度不足的问题;然后,利用均值耦合策略对多电机转速进行耦合控制,实现系统误差全局补偿,保证多电机速度误差同步收敛;其次,通过设计具有非线性函数的非奇异全局快速Terminal滑模面,实现电机速度误差在有限时间内全局快速收敛,并消除了Terminal滑模的奇异问题,提高了单电机速度跟踪精度,降低了多电机间速度同步误差;最后,利用Lyapunov函数证明了观测器和控制器的稳定性及收敛性.仿真与实验结果表明:速度观测器能够在0.4 s内实现速度跟踪,当系统存在负载扰动时,调节时间小于0.05 s,具有良好的跟踪性能和稳态精度;与均值耦合滑模多电机速度同步控制相比,本文控制方法能够在0.15 s内实现对期望转速的跟踪,各电机同步误差调节时间减少了1.2 s,响应速度快,能够有效抑制负载扰动,具有更好的动态调节能力、稳态精度和鲁棒性,可满足阿胶制粒工艺的要求.

输电线路覆冰积雪严重影响电网的安全稳定运行.目前的研究重点关注绝缘子覆雪放电发展过程及闪络特性.由于绝缘子结构复杂,对覆雪的增长过程缺乏系统的分析.本文基于计算流体力学原理,在不同的环境参数条件下,对XP-70绝缘子表面不同位置的雪晶颗粒碰撞特性进行了理论分析和仿真计算,在此基础上建立了绝缘子三维覆雪数值计算模型.研究表明,在气流绕流绝缘子过程中,存在降压增速和增压减速两个相反的过程;绝缘子迎风侧局部碰撞系数从前驻点处沿钢帽或伞裙向两侧逐渐减小,迎风侧伞裙边缘和钢帽处的局部碰撞系数远远大于其他位置,最大可达0.74.绝缘子表面的覆雪量随风速(v)、液态水含量(LWC)以及颗粒直径(MVD)等环境参数的增大而增大,覆雪量最大可达2.19 kg.经仿真和试验验证,局部碰撞系数最大的位置,覆雪最严重,而且试验和模型仿真结果的误差小于17％.

This paper presents a novel indirect predictive control method to reduce the torque ripple of switched reluctance motor drive in electric vehicle (EV) application. The proposed indirect predictive torque control algorithm includes two parts: torque inverse model and robust predictive current controller. The torque inverse model adopts the form of adding torque error compensator to the simple linear model to realize the accurate mapping from torque to current, which avoids the complex calculation of the traditional torque inverse model. Then the predictive current controller is designed to traverse all candidate switching states and use the switching state of minimizing the cost function as the optimal output. Further, the modeling error, parameter variations and sampling error are equivalent to a total disturbance, which are compensated by the developed disturbance observer to improve the robustness of the predictive control. The proposed predictive control scheme indirectly realizes the instantaneous torque control through the accurate tracking of current, which is easy to implement, and is suitable for driving electric vehicles. Simulation experiments are performed to verify the effectiveness of the proposed predictive control algorithm.

The assembly error of flexible joints and the change in joint stiffness during movement make the actual value of joint parameters inconsistent with the given value, which affects the joint control accuracy. In order to suppress the influence of parameters error, a parameters identification method for flexible joint combined offline identification and online compensation is proposed. First, the offline identification model of inertia, mass, and damping and the online identification model of joint stiffness are established, respectively. Then, a hybrid tracking differentiator based on an improved Sigmoid function is designed to track the differential signals of joint motion parameters, and the Lyapunov function is designed to prove its convergence. The adaptive differential evolution is used as the identification algorithm, and the improved adaptive crossover, mutation factor, and Metropolis acceptance criterion are designed to improve the convergence speed. Finally, a feedforward control structure based on identification is designed to compensate for the model deviation. Simulation and experimental results show that the improved differentiator can effectively improve the tracking speed and derivation accuracy of the signals. Compared with other algorithms, the proposed identification method has a faster convergence speed and higher identification accuracy, and feedforward compensation control can effectively correct model parameters and improve control accuracy.

Aimed at the problem of large torque ripple and low efficiency caused by the poor current tracking effect of switched reluctance motor (SRM), a torque ripple reduction method of switched reluctance motor based on a five-level converter is proposed. A novel five-level converter with A and C phases or B and D phases sharing the same bridge arm is designed. Compared with the traditional converter, the control is more flexible and the cost is lower. According to the nonlinear model of SRM, the conduction region is reclassified, and the phase output torque with a large inductance change rate is preferred to avoid excessive peak current at the beginning of commutation. Aimed at the problem of poor winding current tracking ability when the speed and load conditions change greatly, the direct instantaneous torque control (DITC) method based on the five-level converter is proposed, and the DITC conduction rules at low and high speeds are designed. According to the current speed, the torque error, and the rotor position, the appropriate conduction mode is selected to make sure that the motor can run stably at a low speed and the current can track the required value in time at a high speed, so as to realize the reduction of torque ripple. The simulation and experimental results show that compared with the traditional DITC, the control strategy can reduce the torque and current ripple in a wide speed range and improve the dynamic characteristic of the torque.

为提高炒药机温度控制系统控制精度和响应速度,提出了一种改进的模糊滑模控制方法.改进内容包括滑模面和趋近律的设计.设计了一种带有指数函数的滑模面,当误差较大时,控制加热系统保持最大功率输出,缩短了系统调节时间;为抑制固定切换增益引起的抖振现象,设计了带有幂-指函数切换增益的指数趋近律,利用模糊控制器调节幂-指函数的权重,当系统误差较小时,利用幂函数快速衰减的优点,有效抑制了抖振.MATLAB仿真结果表明:与传统模糊滑模控制相比,本文控制方法的调节时间缩短54.94％;对抖振现象具有明显的抑制作用.工程应用效果表明:采用本控制方法的炒药机在稳定工作时,温度波动范围为士 2.12℃,符合中药炒制工艺要求.

针对阿胶珠炮制对电磁炒药机温度控制精度和响应速度的要求,提出了一种基于干扰观测器的改进粒子群优化(PSO)径向基函数神经网络(RBFNN)PID的控制方法.根据阿胶珠电磁炒药机结构,建立阿胶珠电磁炒药机温度控制系统数学模型,通过对控制系统结构分析,构建RB F神经网络结构.利用RB F神经网络的自学习能力,采用梯度下降法对自身参数进行适当调整,实现PID参数动态调整,使系统惯性和时滞性有效抑制.为降低外部干扰影响,分析并构建干扰观测器模型,使干扰量得到实时观测和有效补偿.为弥补RB F神经网络模型参数精度不足,以系统误差瞬时值为适应度函数,利用改进PSO算法对RBF神经网络模型参数寻优,获取最佳控制性能.仿真结果表明:与传统PID控制方法和RBFNN-PID控制方法相比,所提控制方法使调节时间分别减少35 s和19 s,超调量分别降低19.2％ 和13.1％;与无干扰观测器相比,所提控制方法对外部干扰抑制能力平均提高50％;所提控制方法满足阿胶珠炮制工艺的要求.