基于人工智能技术的配网用户侧负荷态势感知方法

为解决现有配网用户侧负荷态势感知方法感知误差大的问题,提出了基于人工智能技术的配网用户侧负荷态势感知方法。分析了配网用户侧负荷异常情况,筛选出零电量用户,构建人工智能技术负荷态势感知模型,对负荷群态势进行量化分析。使用机器学习方法划分负荷空域集合,计算每一个集合的异常得分,使用雷达图法评估零电量电力用户异常程度。以态势负荷时间序列能量值为基准进行归一化处理,结合Fisher判别法对待感知态势进行动态预测,获取态势感知类别。实验结果表明,该方法与实际最高感知负荷相差0.05 MW,最高感知误差为0.20,说明使用该技术能够得到精准的感知结果。

基于随机森林的配网用户侧负荷态势智能感知

配网用户侧负荷态势感知时受不可信数据的影响,造成能量失衡,影响负荷感知结果精度。为了保证配网用户安全用电,结合随机森林方法进行配网用户侧负荷态势智能感知。采用随机节点构造多个决策树,通过简单随机抽样法从基于随机森林的负荷态势智能感知模型中获取多个决策结果。构建负荷态势划分依据函数,划分负荷态势类别。量化处理异构负荷态势,保持能量守恒,避免影响感知结果。利用迭代搜索方法分解负荷时间序列,结合随机森林感知方法对用户侧负荷态势进行智能感知。由实验结果可知,该方法与负荷统计结果只存在最大为2 kW·h的误差,具有精准的感知效果。

小水电对配网用户的影响分析及预防措施

随着水力发电技术的迅速发展,水利资源丰富的地区有大量分布式小水电接入当地配电网。并网小水电在向电网输送功率的同时,由于缺乏规范化管理等原因,含有小水电的配网线路会出现电压过高等现象。含小水电的配网线路由于主供线路故障跳闸后,会形成孤网运行,线路将出现高频、高压的工况,严重时引起用户电器设备损坏,同时也影响线路的检无压重合闸。该文从小水电运行机理出发,对小水电影响配网用户的原因进行了分析,并提出了具体的预防措施,为减少小水电对配网用户的影响提供了具体的改进思路。

配网用户受令资格远程培训考试系统的设计与实现

配网用户受令资格远程培训考试系统的设计与开发,能够建立配网用户受令资格培训库,以保证培训质量,实现运维人员的自主培训。系统采用计算机智能组卷技术,实现受令资格题库在线考试,系统节约了调度人员的工作时间,提高了培训效率,同时提高了配网用户的服务体验,更好地服务于客户。

基于配网末端用户供电可靠性提升的微电网技术探析

末端电网巩固提升对进一步提升供电能力、供电质量和服务水平,支持国家双碳目标加快落地具有重要积极意义。本文从微电网技术入手,深入分析提升配网末端用户供电可靠性的技术手段,以此在推动末端电网发展的基础上让微电网技术得到落实,促进我国农村区域新能源发展,提升电网可靠供电水平。

User Association and Wireless Backhaul Bandwidth Allocation for 5G Heterogeneous Networks in the Millimeter-Wave Band

The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up with a macro base station （MBS） and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capa- bility and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Mul- tiple Output （MIMO） downlink employing Zero-Force Beamforming （ZFBF）, is chosen as the network utility for the objective func- tion. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,z and the wireless backhaul band- width factor α. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the con- ventional SINR-based user association strate- gies.

Joint subcarrier and power allocation with threshold in cooperative multiuser networks

In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combinable allocation shows high computational complexity, so we allocate subcarriers and power separately. At firstly, we distribute subcarriers to relays and users under the assumption of equal power distribution. Here, we propose an equal capacity increment （ECI） allocation strategy to achieve tradeoff between total throughput and fairness. To further improve the system performance, we introduce threshold into ECI strategy, named ECI strategy with threshold （ECI-T）, where subcarriers with bad performance are prevented from transmitting. Subsequently, a water-filling method is adopted to distribute the power to cooperative links in order to fully utilize the limited power. Simulation results show that system performance of the proposed schemes is significantly enhanced compared with an existing resource allocation scheme. Besides, the resource allocation schemes with the water- filling method notably outperform schemes with equal power allocation.

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.

Context-Oriented Multi-RAT User Association and Resource Allocation with Triple Decision in 5G Heterogeneous Networks

In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.

UTILITY OPTIMIZATION SCHEDULING FOR MULTI-POINT VIDEO SURVEILLANCE IN UBIQUITOUS NETWORK

Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.

QoE-Oriented Resource Allocation for Multiuser-Multiservice Femtocell Networks

The pursuit of high data rate and assurance of quality of experience(QoE) for end users represent the main goals of future wireless communication systems.By introducing MOS(Mean Opinion Score) based assessment models for different types of applications,this paper proposed novel QoE-oriented radio resource allocation(RRA) algorithms for multiuser-multiservice femtocell networks.An optimal QoE-oriented RRA strategy is first analyzed using time-sharing method which is applicable to best effort applications.RRA algorithms based on the cross-layer architecture are then proposed for all types of applications by considering parameters extracted from different layers of networking protocols.In the proposed algorithms,a priority mechanism is employed to ensure fairness.Simulation results show that the proposed algorithms can significantly improve the overall perceived quality from the users' perspective in comparison with traditional Quality of Service(QoS)oriented algorithms.

Uplink user allocation scheme in cognitive coexistent cellular network

In order to address spectrum resource scarcity in traditional cellular networks,television(TV)white space is considered as a potential solution to offload a portion of network traffic and enlarge network capacity.This paper describes a cognitive cellular network which allocates low geometry users to the TV white space based on a proportional fair criterion.An uplink user allocation scheme is proposed and the validity of the proposed scheme is established by simulation of the cellular network usage in conjunction with the TV white space.The simulation results show clear improvements in both the user and the system performance with the cognitive coexistent cellular network compared with the traditional cellular network,and that the performance of the proposed user allocation scheme is superior to other user allocation schemes.

Optimal joint relay selection and resource allocation with QoS constraints in multiuser OFDM-based cellular networks

This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.

A trust domain-based multi-agent model for network resource selection

Because of the anonymity and openness of E-commerce, the on-line transaction and the selection of network resources meet new challenges. For this reason, a trust domain-based multi-agent model for network resource selection is presented. The model divides the network into numbers of trust domains and prevents the inconsistency of information maintained by different agents through the periodical communication among the agents. The model enables consumers to receive the response from the agents much quicker because the trust values of participators are evalUated and updated dynamically and timely after the completion of each transaction. In order to make users choose the best matching services and give users with trusted services, the model takes into account the similarity between services and the service providers＇ recognition to the services. Finally, the model illustrates the effectiveness and feasibility according to the experiment.

User-Oriented Graph Based Frequency Allocation Algorithm for Densely Deployed Femtocell Network

Femtocell is a promising technology for improving indoor coverage and offloading the macrocell.Femtocells tend to be densely deployed in populated areas such as the dormitories.However,the inter-tier interference seriously exists in the co-channel Densely Deployed Femtocell Network(DDFN).Since the Femtocell Access Points(FAPs) are randomly deployed by their customers,the interference cannot be predicted in advance.Meanwhile,new characteristics such as the short radius of femtocell and the small number of users lead to the inefficiency of the traditional frequency reuse algorithms such as Fractional Frequency Reuse(FFR).Aiming for the downlink interference coordination in the DDFN,in this paper,we propose a User-oriented Graph based Frequency Allocation(UGFA)algorithm.Firstly,we construct the interference graph for users in the network.Secondly,we study the conventional graph based resources allocation algorithm.Then an improved two steps graph based frequency allocation mechanism is proposed.Simulation results show that UGFA has a high frequency reuse ratio mean while guarantees a better throughput.

Development and Implementation of GSM-Based Distribution Automation System with Graphic User Interface in Nigeria Electric Power Distribution Network

Lack of up-to-date information on efficient operation and maintenance of EPDS （electric power distribution systems）, Nigeria is addressed by designing and implementing an indigenous real-time monitoring and diagnosis system. The system encompasses the development of software driven hardware positioned at the remotely located sub-stations at the low voltage level to keep track of the network in real-time. The detection of faults exploits threshold passing algorithm through continuous monitoring of the network power quality. Communication between the RTU （remote terminal unit） and the DCC （distribution control center） which is based on GSM is initiated by disturbance. The DCC performs fault evaluation processing using the received data and predetermined faults signatures to determine the nature of disturbance and presents the result in graphic user interface environment. A fault reporting time of 2 s was achieved. The developed system exhibits a high degree of accuracy and manifests no spurious reports during testing. The resultant system limits the effects of interruption and increases power availability by reducing the down time. The system strengthens engineering and management capabilities required to enhance reliability by providing information about the network health status.

A calculation method for a power user's CIC under specific conditions in smart distribution grid

This paper presents a practical method for calculating a power user’s customer interruption costs(CIC)under specific conditions.This novel method has been developed,based on the CIC results predicted by Lawrence Berkeley National Laboratory(LBNL),so that the key factors,such as customer type,customer size,interruption occurrence time and interruption duration can be considered.As compared to the LBNL method,the method proposed here is easy to understand and easy to execute with an acceptable error.It lays a solid foundation for further investigation of distributed generators and demand response in assessing reliability value of smart distribution grid(SDG).The effectiveness of the proposed method is confirmed through the assessment of RBTS-Bus2.