Detection of energy theft and defective smart meters in smart grids using linear regression

The utility providers are estimated to lose billions of dollars annually due to energy theft. Although the implementation of smart grids offers technical and social advantages, the smart meters deployed in smart grids are susceptible to more attacks and network intrusions by energy thieves as compared to conventional mechanical meters. To mitigate non-technical losses due to electricity thefts and inaccurate smart meters readings, utility providers are leveraging on the energy consumption data collected from the advanced metering infrastructure implemented in smart grids to identify possible defective smart meters and abnormal consumers’ consumption patterns. In this paper, we design two linear regression-based algorithms to study consumers’ energy utilization behavior and evaluate their anomaly coefficients so as to combat energy theft caused by meter tampering and detect defective smart meters. Categorical variables and detection coefficients are also introduced in the model to identify the periods and locations of energy frauds as well as faulty smart meters. Simulations are conducted and the results show that the proposed algorithms can successfully detect all the fraudulent consumers and discover faulty smart meters in a neighborhood area network.     

Grid synchronization and control of distributed generation unit with flexible load compensation capabilities using multi-output LMS-filter

This paper deals with grid synchronization and control of single-phase voltage source inverter in distributed generation (DG) systems using a multi-output adaptive filter. Besides the active power injection, the proposed control enables the inverter to compensate load harmonic and reactive currents based on the capacity of inverter. The currents to be compensated are obtained using a multi-output adaptive filter structure that operates on the principle of variable step size (VSS) least mean squares (LMS) algorithm. The main objective of VSS-LMS filter is to decompose the load current into harmonic and reactive current components and compute their RMS values. The currents extracted by the VSS-LMS filter are used in developing a flexible compensation based on load compensation factors. The load compensation factors are calculated based on the remaining capacity of the inverter and priority. Harmonic currents compensation is given first priority over the reactive currents. In addition to harmonic currents detection, the same VSS-LMS filter is used in developing a phase locked loop unit for synchronizing the inverter with fundamental point of common coupling (PCC) voltage. Synchronizing the DG inverter with fundamental PCC voltage would make the proposed control algorithm insensitive to grid voltage harmonics and frequency fluctuations. The feasibility and the efficacy of the proposed control algorithm are demonstrated using hardware-in-the-loop (HIL) based experiments.     

互联电网恢复控制的自适应优化

建立统一考虑负荷恢复的收益、控制代价及恢复过程中系统风险的恢复控制优化模型.提出2层优化框架,按"分区独立优化、协调动态分区"方式自适应优化,克服离线预案依据的场景及措施优先顺序不变的缺点.同时将研究从自下而上(bottom-up)策略拓展到自上而下(top-down)策略和混合策略,包括各类策略内部的优化和不同策略之间的协调.基于自适应优化和风险决策的观点,设计模块算法.按大停电防御体系的信息、分析、控制3个要素,设计在线决策支持系统的框架模型,阐明各功能模块间的逻辑关系,并用仿真验证了其有效性和自适应性.     

基于数据仓库的网架恢复群体智能决策支持系统

电力系统网架恢复问题具有多目标、多约束、连续和整型变量混杂以及不确定性等特点,难以建立精确的数学模型进行求解。综合考虑暂态过电压、工频过电压、自励磁、负荷恢复引起的频率波动、机组/负荷特性及其重要程度、恢复时间、线路可用传输容量、设备故障概率等约束条件和影响因素,建立了基于数据仓库的输电网架恢复群体智能决策支持系统模型,提出三段式的输电网架恢复策略,利用多属性效用理论综合考虑各属性评价值并做出最终恢复决策。该系统既可为案例推理生成可行的案例库,又可在实际恢复过程中为决策者提供在线支持。     

A Method of Determining Target Configurations for Power System Restoration Using a Mixed Integer Programming Approach

When electricity supply is interrupted due to a fault, it is essential that the power system be restored promptly according to an adequately planned restoration procedure. A problem of obtaining an appropriate target system for restoration is referred to as a power system restoration problem. The authors have already proposed a very efficient method based on the network simplex method which is in the category of mathematical programming approaches. Although the method is effective for most system conditions, it is likely to give an undesirable result in the case of abnormal network conditions. This paper proposes an effective and computationally fast solution algorithm based on the mixed integer programming approach, which can resolve the shortcoming of the former method The solution speed is improved greatly by incorporating the, restoration strategies of system operators. The following assumptions are postulated in this approach: (1)0–1 variables are allocated to branches and loads to present their status; (2) continuous variables are taken to represent branch flows: and (3) costs are assigned to branches to represent their priorities during restorative operations and power flow limits. The proposed approach can be used to complement the former approach. The new approach has been applied to restoration problems of practical size, and simulation results demonstrate its advantage over the former method for intricate operating conditions.     

计及特级负荷恢复的网架重构分时段全局优化方法

制定科学合理的网架重构恢复方案对加快系统恢复进程、减小停电损失具有重要作用。针对当前分时段恢复方案优化策略无法实现时段间协调优化的不足,提出一种网架重构分时段恢复方案全局优化方法。首先,鉴于特级负荷对维持社会稳定和恢复过程的重要性,将其纳入网架重构过程的恢复目标;之后,综合考虑多种约束,建立了协调机组、特级负荷和网架结构三方面恢复效果的网架重构分时段全局优化模型。该模型是一个含整数决策变量的复杂的多目标优化决策模型。通过分析总结已有恢复操作序列优化制定方法的内在逻辑,提出了一种分时段全局优化两步求解策略,即首先优化求解时段数参考值,再进行恢复方案全局优化。结合非支配近邻免疫算法和变异系数法对建立的模型进行求解。新英格兰10机39节点系统算例和我国西南某地区实际电网算例验证了本文所提模型和算法的有效性。     

A multiagent approach to distribution system restoration

This paper proposes a multiagent approach to decentralized power system restoration for a distribution system network. The proposed method consists of several feeder agents (FAGs) and load agents (LAGs). LAG corresponds to the customer load, while a FAG is developed to act as a manager for the decision process. From the simulation results, the proposed multiagent system was able to reach the right solution by making use of only local information. This means that the proposed multiagent restoration system is a promising approach to more large‐scale distribution networks. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(3): 21–28, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20065     

黑启动及其决策支持系统

由于黑启动过程的复杂性 ,在制定黑启动方案时 ,不仅需要采用数值仿真程序来检验方案的可行性 ,也需要采用专家系统来优化方案。文中提出的决策支持系统采用专家系统处理知识性的规则预选出数个较优的启动方案 ,并通过数值仿真来检验方案的可行性 ,最后用风险决策中的期望值法则算出各方案的期望发电量 ,为调度人员提供了一个科学、直观的决策依据     

基于多agent的电力系统主从递阶恢复决策

将多agent技术的分布式信息处理和主从递阶决策方法有机结合,提出一种分布式电力系统恢复的主从递阶决策模型.采用面向agent技术设计了主从递阶恢复决策系统的体系结构、各级调度agent的内部功能结构以及基于承诺和约定的交互协作机制.各级调度层的承诺为其恢复行为提供了一定程度的可预见性,约定作为变化的恢复过程中监控子调度层承诺进展的手段,为动态环境中的主从决策层的协作提供了灵活性.仿真结果显示,该模型不仅能够处理分布式群体决策中的多决策主体之间的配合问题,而且能灵活处理恢复过程中所出现的问题.     

配电网多时段在线恢复决策问题的两阶段求解算法

大停电事故后,在配电网失去上级电网支撑的情况下,可协同多种本地电源恢复网内重要负荷供电,减小损失,提升韧性。为了实现有限发电资源的优化配置,此场景下的恢复问题通常可以建模为多时段恢复问题。然而由于恢复问题中的整数变量和非凸潮流约束,目前尚无方法能够对其有效求解,无法满足在线决策要求。文中提出多时段在线恢复决策问题的两阶段高效求解算法:第1阶段为基于最大生成树算法的辐射状拓扑确定算法,第2阶段为确定负荷状态的整数变量松弛迭代算法。最后,在改进的62节点配电网算例进行测试,验证了两阶段求解算法的可行性和优势,表明所提算法能够实现在线应用,辅助运行人员进行恢复决策。     

电力系统恢复的主从递阶决策模型及其优化算法

引入主从递阶决策概念，建立了一种适合于大面积停电后分布式恢复的主从递阶决策模型。该模型包括主从递阶恢复决策结构和基于承诺与约定的主从递阶决策模型。通过自下而上的可行性检验与自上而下的目标优化，限制问题的求解规模，避免了对大规模系统直接求解的困难。针对主从递阶决策问题的优化求解，提出基于回溯算法的优化方法。山东电网的仿真结果表明，该方法充分考虑了电力系统分层递阶调度的特点，能满足大规模电力系统大面积停电后分层分区恢复协调调度决策的要求。     

一种机组恢复决策的多时段协调优化方法

为加快大停电后电网的恢复速度,在制定机组恢复方案时,应合理安排机组的启动顺序使尽可能多的火电机组实现热态启动。通过分析恢复过程中机组的串并行恢复机制,并考虑机组热启动时限对恢复顺序的影响,提出一种机组恢复决策的多时段协调优化方法。该方法采用分时段建模、多时段协调优化的全局优化策略,以热启动机组的总容量和恢复过程中机组的总发电量分别作为上、下层目标函数,建立了分时段的双层优化模型;采用基于状态优选的多种群遗传算法进行求解,实现了机组恢复决策的全局优化。通过合理控制各时段保留的方案数,既可保证方案的多样性,有效防止求解陷入局部最优,又可确保各时段的状态数有可控的上限,使计算量控制在可接受的范围内。新英格兰10机39节点系统和河北南网实际系统的算例结果验证了所提多时段协调优化方法的有效性。     

Group decision support system for backbone-network reconfiguration

Modern power system is unprecedentedly vulnerable and the society is exposed to higher blackout risks. Therefore restoration is a key issue to power systems. Reasonable backbone-network reconfiguration is necessary for re-establishing the network and restoring loads quickly. In order to speed up network reconfiguration under security constraints, a group decision support system (GDSS) is developed. A unified data platform based on data warehouse is constructed to resolve inconsistencies of data, information and models. A three-stage restoration strategy and a two-layer restoration path searching method are proposed to establish restoration schemes. Multiple attribute decision-making is implemented to evaluate alternatives and consider various attributes about restoration speed and system security comprehensively. Group decision-making provides an aggregated cardinal ranking of candidate restoration schemes. The GDSS uses expert rules for qualitative analysis and numerical computation programs for quantitative analysis, and it can resolve the semi-structured decision problem of network reconfiguration efficiently. Restoration plan of Shandong power grid is developed with the proposed method and it has been adopted by State Grid Shandong Electric Power Company. Performance results of Shandong power grid of China demonstrate the feasibility and flexibility of the method.     

基于分层案例推理的黑启动决策支持系统

分析了电力系统恢复的层次特征和基于案例推理法的黑启动任务决策系统中存在的问题,提出将分层案例推理的思想应用于黑启动调度任务决策支持。文中给出了分层案例库的框架结构及分层黑启动案例的推理算法,并结合山东电网实际,设计并实现了黑启动决策支持系统,通过问题分解、分层案例推理和子案例复用提高了系统的应变能力,其分层式图形交互案例平台清晰地表达了多层次的黑启动决策过程,能够起到调度员培训和在线决策支持的作用。     

基于D5000调度平台的在线智能恢复决策系统

电力系统恢复是十分复杂的决策问题。采用解耦思想,研制了一套在线电力系统恢复智能决策系统。该系统能够实时获取国家电网D5000调度平台数据,根据电网实际停电状态,在线辅助调度人员制定恢复供电的详细决策。该系统已经在重庆市电力公司开展了试运行,结果显示该软件能够帮助调度人员有效地制定恢复策略。该系统的应用能够提升调度人员恢复系统的能力,减少停电时间,提高供电可靠性。     

省级电网静态安全在线辅助决策优化建模

基于智能电网调度控制系统平台提出省级电网静态安全在线辅助决策优化模型。针对当前在线安全稳定分析系统辅助决策应用存在的不足,分析其中的问题,结合省级电网特点提出新的建模原则与框架,建立了基于多种控制措施和约束条件的静态安全辅助决策模型,并讨论了模型参数优化方法。该模型丰富了优化目标、控制手段,细化了控制约束条件,仿真算例表明基于该模型的辅助决策可行性更强、优化性更好。     

基于有序二元决策图的黑启动分区搜索策略

合理的黑启动分区可以实现多区域分区并举的启动,加快系统恢复进度。该文对黑启动分区进行了研究,建立了黑启动合理分区的定义和数学模型,并将该模型转化为布尔函数。设计和开发了一种基于两阶段的黑启动分区搜索算法。在第1阶段,采用有序二元决策图(ordered binary decision diagram, OBDD)表示法来降低解空间;在第2阶段,利用安全分析等工具在收缩后的解空间内计算最优的分区方案。提出的算法可分阶段进行,因此具有很好的在线应用前景。针对IEEE标准系统和海南电网进行了深入的数值仿真研究,证明了模型和算法的有效性。     

Optimizing service restoration in distribution systems based on scheduling of crews considering priorities of loads

The service restoration to sound sections within a short period as much as possible, performed after the permanent fault occurs in a distribution system, is significant for maintaining power supply reliability. This paper proposes an efficient method to find service restoration procedures based on fault searching and the optimal work scheduling of crews, considering the power supply priorities of loads and the probability of occurrence of faults. The proposed method is composed of two-stage problems to reduce the outage sections efficiently: (i) the problem to find a series of searching procedures for unknown fault locations in the first stage and (ii) the optimization problem of work schedules of crews in the second stage. In the first stage, the order of operation of switches opened for searching for the fault direction is determined, constituting the searching tree. After that, the proposed optimization method can efficiently solve the work scheduling problem by formulating it as a mixed-integer linear programming problem in the second stage. The computational experiments using a large-scale distribution system model with many remote and manual switches show that the proposed method can provide efficient service restoration procedures within a reasonable computational time.     

Comparison of Centralized and Decentralized Systems in Power System Restoration

This paper proposes a multiagent approach to decentralized power system restoration for distribution system networks and presents a comparison of centralized and decentralized systems for power system restoration. Numerous studies have been conducted on power system restoration problems. From the viewpoint of system structures, this research can be divided into two categories: centralized systems and decentralized systems. In this study, we solve a power system restoration problem for a power distribution network by two different methods: mathematical programming (MIP) and the proposed multiagent‐based method (MAS). The proposed multiagent system consists of several distributing substation agents (DSAGs) and load agents (LAGs). An LAG corresponds to the customer load, and a DSAG supplies electricity to the LAG. From the simulation results, it can be seen that the proposed system can reach the right solution by making use of only local information and that the solution quality is better than that of the centralized system (MIP). This means that the proposed multiagent restoration system is a promising approach to larger scale distribution networks.     

Blackstart capability planning for power system restoration

Blackstart capability is essential for power system restoration following a blackout. System restoration planners determine the restoration sequences to provide cranking power from blackstart units (BSUs) to non-blackstart units (NBSUs), pick up critical loads, and energize the necessary transmission paths. This paper proposes a new algorithm for optimization of the restoration actions. An optimal search algorithm is proposed to determine the plan to crank NBSUs through the selected paths of transmission lines. Assuming that the generation capability of a BSU is constant, the method is used to optimize the overall system MWHr generation capabilities from NBSUs. To reduce the computational complexity of system restoration planning, a new generator model is proposed that results in a linear integer programming (IP) formulation. Linearity of the IP problem formulation ensures that the global optimality is achieved. The optimal power flow (OPF) is used to examine the feasibility of planned restoration actions. Test cases from the IEEE 39-bus system, ISO New England system, and Duke-Indiana system are used to validate the proposed algorithm. Numerical simulations demonstrate that the proposed method is computationally efficient for real-world power system cases.