Interpreting recent power quality surveys to define the electricalenvironment

Recent AC power line monitoring projects have enabled a better understanding of the typical electrical environment within which sensitive electronic equipment must be able to operate. Voltage variations caused by utility protective and regulation devices, as well as variations caused by load equipment, contribute to the total power quality picture. Regardless of the origin of these variations, the load equipment must be able to operate with some degree of immunity. This paper presents a combined assessment of data from three of the most recent power quality surveys. Results of this assessment suggest that load equipment with reasonable voltage regulation and interruption ride-through will withstand the majority of recorded power line variations. A detailed analysis of monitor capabilities and limitations is presented, along with a discussion of the interpretation of power line variations recorded at different monitoring locations     

Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks

Distributed generation (DG) are critical components for active distribution system (ADS). However, this may be a serious impact on power system due to their volatility. To this problem, interactive load and battery storage may be a best solution. This paper firstly investigates operation characteristics of interactive load and battery storage, including operation flexibility, inter-temporal operation relations and active-reactive power relations. Then, a multi-period coordinated activereactive scheduling model considering interactive load and battery storage is proposed in order to minimize overall operation costs over a specific duration of time. The model takes into accounts operation characteristics of interactive load and battery storage and focuses on coordination between DGs and them. Finally, validity and effectiveness of the proposed model are demonstrated based on case study of a medium-voltage 135-bus distribution system     

Solar grid parity - [power solar]

Wherever you are in the world, solar-powered electricity is much more expensive than all the alternatives. Yet in the last few decades, huge progress has been made in solar's cost and efficiency, while the full price of conventional power has only risen. Will it ever be possible for solar power to match the costs of our current electricity generation? The author gauges the likelihood.     

用电形势缓和后电力负荷管理系统的应用取向

2006年,我国供用电形势将进一步趋于缓和,负荷管理系统的主要功能——负荷控制功能将逐步弱化。在新的用电形势下,供电企业不能放松对负荷管理系统的管理,必须及时转变应用方向和管理重点,更好地发挥系统所具有的功能,为电力客户和电力营销管理提供如下服务:一是与客户共享系统记录的信息,为客户提供个性化的优质服务;二是加强用电异常的监测和处理,及时发现并处理计量故障和窃电行为;三是充分利用扩展功能,以科技自主创新推进电力营销现场管理水平的提高。     

Reliability centered planning for distributed generation considering wind power volatility

This paper investigates a stochastic planning model to minimize the lifecycle cost of distributed generation (DG) systems under the energy reliability criterion, namely the loss-of-load probability. In particular, our study focuses on the DG system penetrated by renewable wind technology. The optimization is formulated to determine the wind turbine capacity and their placement in the DG system with the intent to minimize the capital, operational and environmental costs. Statistical moments including mean and variance are utilized to characterize the wind power volatility and the load uncertainty. Genetic algorithm combined with heuristic search is used to find the best sitting and sizing of the distributed energy recourses. Our study is among the first attempts in the literature to model and optimize DG system based on continuous probabilistic theory. The moment methods are shown to be effective in characterizing the stochastic behavior of wind power and load dynamics. Case studies are provided to demonstrate the application and performance of the planning method.     

Simultaneous optimization of the adjustable parameters in multimachine power systems

This paper considers a novel approach to simultaneous optimization of the adjustable parameters of all the stabilizers in multimachine power systems to obtain the best dynamic performance. It is based on frequency domain analysis using the domain-separation method, Nyquist's stability criterion, and the frequency criterion of quality. With the proposed technique, the condition for stability of the system and the range of variation of the adjustable gains can be determined. In addition, the values of the adjustable parameters can be selected for the best system dynamic response. The method is especially effective for complex system investigations.     

Fault analysis through power quality metering

The combination of continuous power and energy monitoring with disturbance detection is a very cost-effective way to ensure that unpredictable power quality disturbances, such as those caused by lightning, can be recorded and analysed. The information such a system provides can result in substantial savings for demand penalties and equipment costs. For industrial power systems, the value added by intelligent power monitoring is very high. A good power quality monitoring system is essential to pulp and paper mills, and fills the need for the wide spectrum of information that is required to keep the costs down and the plant running smoothly. The use of such a system at the Mead Publishing Paper Division plant in Rumford, Maine, is discussed     

Multiobjective optimal thermal power dispatch

A multiobjective thermal power dispatch problem is formulated using noncommensurable objectives such as operating costs and minimal emission. A sensitivity measure is chosen whereby the effects of variations in the nominal conditions describing a given multiobjective problem can be measured and incorporated as a performance index to be minimized. A nonlinear programming problem provides the framework for examining the objective constraint level in an ε-constant form of the multiobjective optimization problem. The dispersion index is chosen as the sensitivity measure for the investigation of the effects of random variations in the model parameters of the optimal solution. A sensitivity trade-off is exploited for the multiobjective problem that represents the trade-off between sensitivity and objective level. Validity of the method has been demonstrated by analysing a three-generator sample system.     

Electricity market equilibrium of nonlinear power systems with reactive power control

The impact of reactive power control on the electricity market equilibrium is investigated. The effects of limitations on the reactive power generation and absorption, and load power factor adjustments, are examined using a novel electricity market equilibrium model that solves large-scale nonlinear power systems with asymmetric strategic firms. The algorithm implemented employs the linear supply function theory for bid-based pool markets. AC power flow analysis is used to represent the electricity network, incorporating variable price-responsive active and reactive load demands. The significance of the reactive power modeling in the electricity market equilibrium is demonstrated using the IEEE 14-bus and IEEE 118-bus systems. It is shown that variations on the reactive power in the system result in different market outcomes, as incentives are given to the strategic generating firms to alter their bidding strategies. The convergence characteristics of the IEEE 118-bus system are graphically presented and discussed to demonstrate the superior computational performance of the proposed algorithm in producing results under strict binding constraints and heavy transmission congestion conditions.     

双碳目标下电网异址双活调控中心负载均衡控制方法

在大型电网中,调控中心异址双活模式可全面提升系统容灾性能,实现主备一体化运维。然而异址多中心模式会增加能源消耗水平,给当前电网双碳目标的实现带来挑战。目前调控中心间负载分配策略并没有综合考虑能源成本、数据传输成本和排队延迟。调控中心考虑由可再生能源直接供电,并提出了一种新颖的工作负载管理框架,通过智能调度决策了解数据传输成本和排队延迟,采用整体方法来解决成本最小化和可再生能源消纳问题,即实现双碳目标。将工作负载分配问题表述为非合作博弈,并设计了一种基于纳什均衡的智能博弈负载分配框架,以最小化运营成本。该框架同时考虑能源和网络成本最小化,且同时满足工作负载性能目标。利用详细的模型来获得影响运营成本和工作负载性能的一组综合特征,包括调控数据中心计算和冷却功率、托管性能干扰、分时电价、可再生能源、净计量、高峰需求、调控数据中心排队延迟,以及调控数据中心间数据传输所涉及的成本。通过仿真表明,所提出的方法可以比现有方法更有效地降低运营成本,验证了其有效性。     

小型离网风力发电系统逆变器控制研究

针对风力发电系统受环境影响较大,如风速变化影响导致发电机输出电压的不稳定与系统启动瞬间及负载突变对电能影响,进而破坏用电设备的问题,重复控制具有静态性能佳,而PI控制有动态性能好的优点,采用重复+PI控制策略,解决逆变直流侧电压波动、系统启动瞬间、负载突变引起的电压波形畸变,提高系统的动、静态性能,减少电压谐波含量,进而改善输出电能质量.通过仿真验证控制策略的优越性,明显改善输出电能的质量,使电压谐波控制在1.5%内.     

Hilbert-Huang变换及其在电力系统中的应用

通过综述国内外Hilbert-Huang变换及其相关端点效应、模态混叠、筛分停止准则等问题的研究现状,讨论了该变换的特点。详细分析了Hilbert-Huang变换在电力系统设备故障检测与故障诊断、电力系统振荡分析、电能质量检测和负荷预测等方面的应用现状。最后,对其在电力系统中的应用进行了展望,认为Hilbert-Huang变换可以联合其他方法克服本身缺点,并根据电力系统信号的特点,更有效地应用于电力系统。     

A heuristic approach to load shedding scheme

The authors describe some of the present problems which exist in the operation of power systems, and how an expert system can be utilized to enhance the performance of the system by implementing load shedding as one of alternatives in the restoration of a large-scale power system. The proposed method is part of an integrated package of power system restoration which helps a system operator recognize bottlenecks in the operation of the system and develop strategies for providing reliable service to customers. The governing rules for load shedding are introduced, and the proposed approach is implemented on a six-bus and the IEEE 30-bus system     

基于最优小波包基分解的暂态电能质量分类方法

对屯能质量暂态扰动进行正确的识别分类是改善电能质量的前提,而电能质量扰动特征向量的提取又是电能质量扰动识别分类中的关键步骤。提出基于最优小波包熵特征的特征提取方法．对采样信号进行小波包分解及时域预处理并选取最优小波包基．计算各尺度下信号的最佳小波包子空间的熵值,归一化处理后,把同尺度下的熵值和作为特征量,再将所有尺度下的特征量按尺度分解顺序依次组合在一起．形成最终的特征向量并作为神经网络的输入构建神经网络识别系统．对暂态电能质量信号进行识别。系统负荷投切和电容器充电的仿真结果表明．该方法能快速有效地区分暂态脉冲和振荡暂态。     

Cost analysis of a power system using probabilistic optimal power flow with energy storage integration and wind generation

This paper examines the storage application and its optimal placement for the social cost and transmission congestion relief of wind integration. Probability density functions (PDFs) are used to characterize the uncertainties of wind speed and load. A probabilistic optimal power flow (POPF) is developed using two-point estimation which incorporates the storage system either as a variable load or as a variable generator. Storage systems are optimally placed and adequately sized using a particle swarm optimization (PSO) to minimize the sum of operation and congestion costs over a scheduling period. A technical assessment framework is developed to enhance the efficiency of wind integration and evaluate the economics of storage technologies and conventional gas-fired alternatives. The proposed method is used to carry out a cost-benefit analysis for the IEEE 24-bus system and determine the most economical technology. Optimal storage distribution and its potential to relieve the transmission congestion are evaluated for higher wind penetration levels.     

考虑综合需求响应的电热系统调度

随着综合能源中电、热负荷不断增长以及热电联产(CHP)装置、风机等电源迅速发展,弃风现象愈发严重。为解决弃风问题,提出考虑电、热综合需求响应的优化模型。首先,在负荷侧分析电、热负荷的可调度价值,对电负荷建立实时电价模型,并采用价格型需求响应进行调整;其次,采用自回归滑动平均(ARMA)模型描述热负荷的传输延迟特性,并考虑模糊性供热舒适度,使得热负荷具有一定的弹性,即热力需求响应,通过2种响应模式对电、热负荷进行调整可增大风电上网空间;然后,在源侧增加电锅炉和储热装置,增加系统的灵活性,解耦CHP“以热定电”的刚性需求;最后,以系统的日运行费用与弃风成本最小为目标,在Matlab中调用CPLEX对模型进行求解。算例表明,所提方法可显著提升风电消纳能力,降低系统运行成本,提高能源利用效率。     

Toward a practical performance index for predicting voltagecollapse in electric power systems

Voltage collapse is generally caused by either of two types of power system disturbances: load variations; and contingencies. A number of performance indices intended to measure the severity of the voltage collapse problem have been proposed in the literature. However, few of these performance indices can answer questions such as: “can the system withstand another 100 MVar increase on bus 11?” This paper presents a new performance index that provides a direct relationship between its value and the amount of load demand that the system can withstand before collapse. One of the features that distinguishes the proposed performance is its development in the load-demand space and its ability to answer questions such as: “can the system withstand a simultaneous increase of 70 MW on bus 2 and 50 MVAr on bus 6?” This feature makes the performance index readily interpretable to operators. Moreover, the computation involved in the proposed performance index is relatively inexpensive in comparison with those required in existing solutions. Simulation results on the IEEE 39-bus system and a 234-bus power system are presented with promising results     

Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods

Predicting full load electrical power output of a base load power plant is important in order to maximize the profit from the available megawatt hours. This paper examines and compares some machine learning regression methods to develop a predictive model, which can predict hourly full load electrical power output of a combined cycle power plant. The base load operation of a power plant is influenced by four main parameters, which are used as input variables in the dataset, such as ambient temperature, atmospheric pressure, relative humidity, and exhaust steam pressure. These parameters affect electrical power output, which is considered as the target variable. The dataset, which consists of these input and target variables, was collected over a six-year period. First, based on these variables the best subset of the dataset is explored among all feature subsets in the experiments. Then, the most successful machine learning regression method is sought for predicting full load electrical power output. Thus, the best performance of the best subset, which contains a complete set of input variables, has been observed using the most successful method, which is Bagging algorithm with REPTree, with a mean absolute error of 2.818 and a Root Mean-Squared Error of 3.787.     

Design and modeling of SMES based SAPF for pulsed power load demands

In this article, a Superconducting Magnetic Energy Storage (SMES) based Shunt Active Power Filter (SAPF) topology is proposed to compensate high power pulsating load demands in a power system. The SMES based SAPF is designed and modeled to realize as an efficient compensator for the compensation of pulsed power load demands. The conventional SAPF is efficient to mitigate the power quality problems in a power system unless there is high power pulsating load demands, transient conditions or power fluctuations. Particularly, a Modified Synchronous Reference Frame (MSRF) control algorithm has been implemented to generate proper switching signals for the three-phase Voltage Source Converter (VSC) of the SMES based SAPF. In the simulation, it has been seen that the SAPF is incompetent under high power pulsating load demands whereas the SMES based SAPF has shown excellent performance under such load conditions. Moreover, a comparative analysis has been made between the conventional SAPF and the SMES based SAPF under pulsating load conditions, to check the effectiveness of the SMES based SAPF. The performance of the proposed system is presented by using Sim Power System (SPS)/MATLAB Simulink and real-time digital simulator laboratory (RTDS-Lab).     

电力短期负荷时间序列混沌特性分析的技术改进

电力短期负荷具有混沌特性。通过深入研究其混沌吸引子的形状、关联维数及最大Lyapunov指数,发现这些混沌特征数对电力短期负荷预测具有重要意义。在相空间重构的基础上,经研究发现电力短期负荷二维相图两坐标间延迟时间为8时,其混沌吸引子能得到最好的再现;对计算关联维数的G-P算法中关键参数的选取提出了简单易行的方法,使该算法更易于操作;对计算最大Lyapunov指数的小数据量方法做进一步改进,提出了一套固定参数,并用Henon系统数据验证了该方法的有效性。用上述改进方法进一步分析了电力短期负荷的混沌特性。