Multi-deployment of dispersed power sources became an important need with the rapid increase of the Distributed generation (DG) technology and smart grid applications. This paper proposes a computational tool to asses...Multi-deployment of dispersed power sources became an important need with the rapid increase of the Distributed generation (DG) technology and smart grid applications. This paper proposes a computational tool to assess the optimal DG size and deployment for more than one unit, taking the minimum losses and voltage profile as objective functions. A technique called radial basis function (RBF) neural network has been utilized for such target. The method is only depending on the training process;so it is simple in terms of algorithm and structure and it has fast computational speed and high accuracy;therefore it is flexible and reliable to be tested in different target scenarios. The proposed method is designed to find the best solution of multi- DG sizing and deployment in 33-bus IEEE distribution system and create the suitable topology of the system in the presence of DG. Some important results for DG deployment and discussion are involved to show the effectiveness of our proposed method.展开更多
With the explosive development of wireless communication and low power embedded techniques, Body Area Network (BAN) has opened up new frontiers in the race to provide real-time health monitoring. IEEE 802 has establis...With the explosive development of wireless communication and low power embedded techniques, Body Area Network (BAN) has opened up new frontiers in the race to provide real-time health monitoring. IEEE 802 has established a Task Group called IEEE 802.15.6 inNovember 2007 and aims to establish a communication standard optimized for low power, high reliability applied to medical and non-medical application for BANs. This paper overviews the path loss model and the communication scheme for implant-to-body surface channel presented by IEEE 802.15.6 standard. Comparing with the standard scheme where BCH (Bose-Chaudhuri-Hochquenghem) code is employing, we propose a new coding solution using convolutional code operating with Bit Interleaver based on the properties of implant-to-body surface channel. To analyze the performance of the two Error Correct Coding (ECC) schemes, we performed simulations in terms of Bit Error Rate (BER) and power consumption on MATLAB and FPGA platform, respectively. The simulation results proved that with appropriate constraint length, convolutional code has a better performance not only in BER, but also in minimization of resources and power consumption.展开更多
The paper dwells on the unified power quality indexes characterizing the phenomenon of voltage unbalance in three-phase systems. Voltage unbalance is one of the commonest occurrences in the town mains of 0.38 kV volta...The paper dwells on the unified power quality indexes characterizing the phenomenon of voltage unbalance in three-phase systems. Voltage unbalance is one of the commonest occurrences in the town mains of 0.38 kV voltage. The phenomenon describes as inequality of vector magnitude of phase voltage and shearing angle between them. Causes and consequences of the voltage unbalance in distribution networks have been considered. The algorithm, which allows switching one-phase load, has been developed as one of the methods of reducing the unbalance level. The algorithm is written in the function block diagram programming language. For determining the duration and magnitude of the unbalance level it is proposed to introduce the forecasting algorithm. The necessary data for forecasting are accumulated in the course of the algorithm based on the Function Block Diagram. The algorithm example is given for transforming substation of the urban electrical power supply system. The results of the economic efficiency assessment of the algorithm implementation are shown in conclusion. The use of automatic switching of the one-phase load for explored substation allows reducing energy losses (active electric energy by 7.63%;reactive energy by 8.37%). It also allows improving supply quality to a consumer. For explored substation the average zero-sequence unbalance factor has dropped from 3.59% to 2.13%, and the negative-sequence unbalance factor has dropped from 0.61% to 0.36%.展开更多
Nowadays the optimal allocation of distributed generation (DG) in the distribution network becomes the popular research area in restructuring of power system. The capacitor banks introduced in the distribution network...Nowadays the optimal allocation of distributed generation (DG) in the distribution network becomes the popular research area in restructuring of power system. The capacitor banks introduced in the distribution networks for reactive power compensation also have the capacity to minimize the real and reactive power losses occurred in the system. Hence, this research integrates the allocation of renewable energy DG and capacitor banks in the radial distribution network to minimize the real power loss occurred in the system. A two-stage methodology is used for simultaneous allocation of renewable DG and capacitor banks. The optimum location of renewable energy DG and capacitor banks is determined using the distributed generation sitting index (DGSI) ranking method and the optimum sizing of DG and capacitor banks is found out for simultaneous placement using weight improved particle swarm optimization algorithm (WIPSO) and self adaptive differential evolution algorithm (SADE). This two-stage methodology reduces the burden of SADE and WIPSO algorithm, by using the DGSI index in determining the optimal location. Hence the computational time gets reduced which makes them suitable for online applications. By using the above methodology, a comprehensive performance analysis is done on IEEE 33 bus and 69 bus RDNs and the results are discussed in detail.展开更多
虚拟电厂(virtual power plant,VPP)可利用异构网络实现分布式新能源聚合调度,实现综合效益提升。为了提高VPP在不同网络下的丢包与时延等非理想传输能力,提出面向异构通信网络的设备接入优化算法。首先,分析总结了VPP设备充放电容量、...虚拟电厂(virtual power plant,VPP)可利用异构网络实现分布式新能源聚合调度,实现综合效益提升。为了提高VPP在不同网络下的丢包与时延等非理想传输能力,提出面向异构通信网络的设备接入优化算法。首先,分析总结了VPP设备充放电容量、出力特性、接入网络时延、网络承载能力等约束条件,考虑异构网络下设备接入的丢包率和时延理论性能构建了以收益损失最小化为目标的优化模型。然后,利用分层求解和贪婪算法进行模型求解,获得设备的接入方式。最后,仿真验证了所提模型和算法的有效性和可靠性。结果表明,所提算法可提高网络接入容量并降低系统收益损失,实现收益最大化。展开更多
随着配电网复杂性日益增加以及对电能质量要求不断提高,谐波污染和网络损耗已成为影响新型电力系统稳定性和运行效率的关键因素。通过同步优化电容器和有源功率滤波器(active power filter,APF)的配置,实现谐波抑制与网络损耗最小化的...随着配电网复杂性日益增加以及对电能质量要求不断提高,谐波污染和网络损耗已成为影响新型电力系统稳定性和运行效率的关键因素。通过同步优化电容器和有源功率滤波器(active power filter,APF)的配置,实现谐波抑制与网络损耗最小化的双重目标。利用谐波功率流分析模型进行谐波评估,根据谐波穿透法进行频域建模。对失真配电网络中的电容器和APF的同步配置建模,利用粒子群优化(particle swarm optimization,PSO)算法解决电容器和APF同步配置的混合整数非线性规划问题。实验结果表明:适当配置电容器和APF能够显著改善网络的电压质量,所提的同步优化方法不仅在降低系统成本的同时,显著提高了新型电力系统配电网的电能质量和运行效率。展开更多
配电网线损时间序列受高比例新能源接入的影响,呈现高度的非线性和波动性,面对此种类型的数据,使得常规的预测模型难以捕捉其变化趋势,预测值往往滞后于真实值变化,而模态分解再预测的处理方法能够较好地应对此问题。因此,该文提出了一...配电网线损时间序列受高比例新能源接入的影响,呈现高度的非线性和波动性,面对此种类型的数据,使得常规的预测模型难以捕捉其变化趋势,预测值往往滞后于真实值变化,而模态分解再预测的处理方法能够较好地应对此问题。因此,该文提出了一种基于缎蓝园丁鸟(satin bower birdoptimization algorithm,SBO)算法优化的二次模态分解和卷积双向长短期记忆神经网络的线损预测框架,以合理划分线损分量,并针对各分量设计预测模型开展预测。首先采用改进完全集合经验模态分解(improved complete ensemble empirical mode decomposition with adaptive noise,ICEEMDAN)对历史线损数据进行初次分解,得到各ICIMFn分量并计算其样本熵;对样本熵最高的ICIMF1利用经SBO优化的变分模态分解(variational mode decomposition,VMD)对其进一步分解,得到各VIMFn分量。其次,考虑分解后线损各分量受天气负荷等不同因素影响,依据最大互信息系数(maximal information coefficien,MIC),提取对各线损分量产生影响的主要因素,实现特征降维。最后,结合组合模型的各自特点,建立基于卷积双向长短期记忆神经网络(convolutional neural networks-Bidirectional long short term memory,CNN-BiLSTM)的预测模型,使用CNN对分解后的各分量进行特征提取,输入到BiLSTM中,建立时间特征关系,学习历史数据间的正、反向规律,最终输出线损预测结果。与现有方法相比较,所提方法在应对滞后效应的同时,提升了预测效率及精度,为精细化线损管理提供了数据支持。展开更多
Increased grid integration of photovoltaic(PV)has aggravated the uncertainty of distribution network operations.For a distribution network with PV,the impact of the PV location on the network power losses and voltage ...Increased grid integration of photovoltaic(PV)has aggravated the uncertainty of distribution network operations.For a distribution network with PV,the impact of the PV location on the network power losses and voltage fluctuations is investigated with analytical derivations reflected by the line impedance.Optimization approaches of the PV location with consideration of two aspects,i.e.,minimum network power losses and minimum voltage fluctuations,are analyzed.A particle swarm optimization(PSO)algorithm is used to synthesize an optimal compromised solution so as to determine the PV location.A 10 kV distribution network with one PV is established on the time-domain simulation environment PSCAD/EMTDC.The simulation results justify the theoretical analysis and indicate that when the active power of the PV is more/less than twice that of the overall loads/end loads,the network power losses and node voltage fluctuations are both minimum when the PV is integrated into the head/tail end of the network.When the active power of the PV is between the above two conditions,nodes t/f can be identified for the integration of the PV between the head/end nodes of the network to achieve the minimum network power losses/voltage fluctuations,respectively.The effectiveness of the proposed optimization approach is verified and can provide a reference for selecting the PV location in the distribution network.展开更多
文摘Multi-deployment of dispersed power sources became an important need with the rapid increase of the Distributed generation (DG) technology and smart grid applications. This paper proposes a computational tool to assess the optimal DG size and deployment for more than one unit, taking the minimum losses and voltage profile as objective functions. A technique called radial basis function (RBF) neural network has been utilized for such target. The method is only depending on the training process;so it is simple in terms of algorithm and structure and it has fast computational speed and high accuracy;therefore it is flexible and reliable to be tested in different target scenarios. The proposed method is designed to find the best solution of multi- DG sizing and deployment in 33-bus IEEE distribution system and create the suitable topology of the system in the presence of DG. Some important results for DG deployment and discussion are involved to show the effectiveness of our proposed method.
文摘With the explosive development of wireless communication and low power embedded techniques, Body Area Network (BAN) has opened up new frontiers in the race to provide real-time health monitoring. IEEE 802 has established a Task Group called IEEE 802.15.6 inNovember 2007 and aims to establish a communication standard optimized for low power, high reliability applied to medical and non-medical application for BANs. This paper overviews the path loss model and the communication scheme for implant-to-body surface channel presented by IEEE 802.15.6 standard. Comparing with the standard scheme where BCH (Bose-Chaudhuri-Hochquenghem) code is employing, we propose a new coding solution using convolutional code operating with Bit Interleaver based on the properties of implant-to-body surface channel. To analyze the performance of the two Error Correct Coding (ECC) schemes, we performed simulations in terms of Bit Error Rate (BER) and power consumption on MATLAB and FPGA platform, respectively. The simulation results proved that with appropriate constraint length, convolutional code has a better performance not only in BER, but also in minimization of resources and power consumption.
文摘The paper dwells on the unified power quality indexes characterizing the phenomenon of voltage unbalance in three-phase systems. Voltage unbalance is one of the commonest occurrences in the town mains of 0.38 kV voltage. The phenomenon describes as inequality of vector magnitude of phase voltage and shearing angle between them. Causes and consequences of the voltage unbalance in distribution networks have been considered. The algorithm, which allows switching one-phase load, has been developed as one of the methods of reducing the unbalance level. The algorithm is written in the function block diagram programming language. For determining the duration and magnitude of the unbalance level it is proposed to introduce the forecasting algorithm. The necessary data for forecasting are accumulated in the course of the algorithm based on the Function Block Diagram. The algorithm example is given for transforming substation of the urban electrical power supply system. The results of the economic efficiency assessment of the algorithm implementation are shown in conclusion. The use of automatic switching of the one-phase load for explored substation allows reducing energy losses (active electric energy by 7.63%;reactive energy by 8.37%). It also allows improving supply quality to a consumer. For explored substation the average zero-sequence unbalance factor has dropped from 3.59% to 2.13%, and the negative-sequence unbalance factor has dropped from 0.61% to 0.36%.
文摘Nowadays the optimal allocation of distributed generation (DG) in the distribution network becomes the popular research area in restructuring of power system. The capacitor banks introduced in the distribution networks for reactive power compensation also have the capacity to minimize the real and reactive power losses occurred in the system. Hence, this research integrates the allocation of renewable energy DG and capacitor banks in the radial distribution network to minimize the real power loss occurred in the system. A two-stage methodology is used for simultaneous allocation of renewable DG and capacitor banks. The optimum location of renewable energy DG and capacitor banks is determined using the distributed generation sitting index (DGSI) ranking method and the optimum sizing of DG and capacitor banks is found out for simultaneous placement using weight improved particle swarm optimization algorithm (WIPSO) and self adaptive differential evolution algorithm (SADE). This two-stage methodology reduces the burden of SADE and WIPSO algorithm, by using the DGSI index in determining the optimal location. Hence the computational time gets reduced which makes them suitable for online applications. By using the above methodology, a comprehensive performance analysis is done on IEEE 33 bus and 69 bus RDNs and the results are discussed in detail.
文摘虚拟电厂(virtual power plant,VPP)可利用异构网络实现分布式新能源聚合调度,实现综合效益提升。为了提高VPP在不同网络下的丢包与时延等非理想传输能力,提出面向异构通信网络的设备接入优化算法。首先,分析总结了VPP设备充放电容量、出力特性、接入网络时延、网络承载能力等约束条件,考虑异构网络下设备接入的丢包率和时延理论性能构建了以收益损失最小化为目标的优化模型。然后,利用分层求解和贪婪算法进行模型求解,获得设备的接入方式。最后,仿真验证了所提模型和算法的有效性和可靠性。结果表明,所提算法可提高网络接入容量并降低系统收益损失,实现收益最大化。
文摘随着配电网复杂性日益增加以及对电能质量要求不断提高,谐波污染和网络损耗已成为影响新型电力系统稳定性和运行效率的关键因素。通过同步优化电容器和有源功率滤波器(active power filter,APF)的配置,实现谐波抑制与网络损耗最小化的双重目标。利用谐波功率流分析模型进行谐波评估,根据谐波穿透法进行频域建模。对失真配电网络中的电容器和APF的同步配置建模,利用粒子群优化(particle swarm optimization,PSO)算法解决电容器和APF同步配置的混合整数非线性规划问题。实验结果表明:适当配置电容器和APF能够显著改善网络的电压质量,所提的同步优化方法不仅在降低系统成本的同时,显著提高了新型电力系统配电网的电能质量和运行效率。
文摘配电网线损时间序列受高比例新能源接入的影响,呈现高度的非线性和波动性,面对此种类型的数据,使得常规的预测模型难以捕捉其变化趋势,预测值往往滞后于真实值变化,而模态分解再预测的处理方法能够较好地应对此问题。因此,该文提出了一种基于缎蓝园丁鸟(satin bower birdoptimization algorithm,SBO)算法优化的二次模态分解和卷积双向长短期记忆神经网络的线损预测框架,以合理划分线损分量,并针对各分量设计预测模型开展预测。首先采用改进完全集合经验模态分解(improved complete ensemble empirical mode decomposition with adaptive noise,ICEEMDAN)对历史线损数据进行初次分解,得到各ICIMFn分量并计算其样本熵;对样本熵最高的ICIMF1利用经SBO优化的变分模态分解(variational mode decomposition,VMD)对其进一步分解,得到各VIMFn分量。其次,考虑分解后线损各分量受天气负荷等不同因素影响,依据最大互信息系数(maximal information coefficien,MIC),提取对各线损分量产生影响的主要因素,实现特征降维。最后,结合组合模型的各自特点,建立基于卷积双向长短期记忆神经网络(convolutional neural networks-Bidirectional long short term memory,CNN-BiLSTM)的预测模型,使用CNN对分解后的各分量进行特征提取,输入到BiLSTM中,建立时间特征关系,学习历史数据间的正、反向规律,最终输出线损预测结果。与现有方法相比较,所提方法在应对滞后效应的同时,提升了预测效率及精度,为精细化线损管理提供了数据支持。
基金This work was supported by National Natural Science Foundation of China under Grant 51807091Natural Science Foundation of Jiangsu Province BK20180478+1 种基金the China Postdoctoral Science Foundation under Grant 2019M661846,EPSRC under Grant EP/N032888/1the International Science and Technology Collaborative Project of Policy Guidance Plan of Jiangsu Province under Grant BZ2018026。
文摘Increased grid integration of photovoltaic(PV)has aggravated the uncertainty of distribution network operations.For a distribution network with PV,the impact of the PV location on the network power losses and voltage fluctuations is investigated with analytical derivations reflected by the line impedance.Optimization approaches of the PV location with consideration of two aspects,i.e.,minimum network power losses and minimum voltage fluctuations,are analyzed.A particle swarm optimization(PSO)algorithm is used to synthesize an optimal compromised solution so as to determine the PV location.A 10 kV distribution network with one PV is established on the time-domain simulation environment PSCAD/EMTDC.The simulation results justify the theoretical analysis and indicate that when the active power of the PV is more/less than twice that of the overall loads/end loads,the network power losses and node voltage fluctuations are both minimum when the PV is integrated into the head/tail end of the network.When the active power of the PV is between the above two conditions,nodes t/f can be identified for the integration of the PV between the head/end nodes of the network to achieve the minimum network power losses/voltage fluctuations,respectively.The effectiveness of the proposed optimization approach is verified and can provide a reference for selecting the PV location in the distribution network.
