Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Reliability analysis of structure with random parameters based on multivariate power polynomial expansion

A new method for calculating the failure probabilityof structures with random parameters is proposed based onmultivariate power polynomial expansion, in which te uncertain quantities include material properties, structuralgeometric characteristics and static loads. The structuralresponse is first expressed as a multivariable power polynomialexpansion, of which the coefficients ae then determined by utilizing the higher-order perturbation technique and Galerkinprojection scheme. Then, the final performance function ofthe structure is determined. Due to the explicitness of theperformance function, a multifold integral of the structuralfailure probability can be calculated directly by the Monte Carlo simulation, which only requires a smal amount ofcomputation time. Two numerical examples ae presented toillustate te accuracy ad efficiency of te proposed metiod. It is shown that compaed with the widely used first-orderreliability method （ FORM） and second-order reliabilitymethod （ SORM）, te results of the proposed method are closer to that of the direct Monte Carlo metiod,and it requires much less computational time.

Reliability Assessment Considering the Coordination of Wind Power, Solar Energy and Energy Storage

风光储联合发电系统并网后必须采取策略与系统之间实现协调调度与运行才可在保证可靠性的前提下最大化利用可再生能源，但现有的可靠性评估中还缺少对大规模风光储联合发电系统协调运行的考虑。针对此问题，基于序贯蒙特卡罗仿真方法，建立了风电、光伏和储能系统的发电可靠性评估模型，并提出了新的协调调度策略。模型综合考虑了风速、太阳光辐照度、环境温度以及2种新能源发电技术的能量变换特性和储能系统的充放电约束等因素。这些模型被应用到IEEERTS79中，通过在Matlab中编制程序进行仿真计算，考察不同的协调运行策略、联合发电系统容量配置以及储能特性对于系统裕度的影响。评估结果可为联合发电系统并网规划与设计提供参考。

A preventive opportunistic maintenance method for railway traction power supply system based on equipment reliability

Conventional maintenance mode for the traction power supply system(TPSS)is to perform scheduled regular maintenance activities for power supply equipment,while such maintenance mode may result in undue maintenance tasks and low efficiency due to different degradation processes of different sorts of equipment.To address this problem,this paper introduces a preventive opportunistic maintenance(POM)method for TPSS based on equipment reliability.Firstly,a POM model is established by considering the equipment reliability degradation process based on Weibull distribution.Then,by considering the total power outage time in the planned operation cycle of TPSS as the optimization objective,the optimal maintenance scheme of TPSS is formulated by iterative method of maintenance strategies.The proposed method is verified by introducing practical maintenance strategies and fault record data of the traction transformer,circuit breaker and disconnector in an actual TPSS of a railway administration.Results show that the presented method can make full use of the existing fault data to develop a POM scheme for TPSS.It can improve maintenance efficiency and reduce power outage time,providing guidance to formulate scientific maintenance strategies for TPSS.

Seismic reliability analysis of large electric power systems

Based on the De.Morgan laws and Boolean simplification, a recursive decomposition method is introduced in this paper to identify the main exclusive safe paths and failed paths of a network. The reliability or the reliability bound of a network can be conveniently expressed as the summation of the joint probabilities of these paths. Under the multivariate normal distribution assumption, a conditioned reliability index method is developed to evaluate joint probabilities of various exclusive safe paths and failed paths, and, finally, the seismic reliability or the reliability bound of an electric power system. Examples given in the paper show that the method is very simple and provides accurate results in the seismic reliability analysis.

Method of Electricity Supply Reliability Need Assessment for Multi-type Power Users Area

With electric power outage influence on different type users analyzed, indexes for assessing supply reliability need level is designed. Based on fuzzy evaluation method, a regional power supply reliability level assessment method which utilizes qualitative data is presented.

Low power fluorine plasma effects on electrical reliability of AlGaN/GaN high electron mobility transistor

The new electrical degradation phenomenon of the AlGaN/GaN high electron mobility transistor（HEMT） treated by low power fluorine plasma is discovered. The saturated current, on-resistance, threshold voltage, gate leakage and breakdown voltage show that each experiences a significant change in a short time stress, and then keeps unchangeable. The migration phenomenon of fluorine ions is further validated by the electron redistribution and breakdown voltage enhancement after off-state stress. These results suggest that the low power fluorine implant ion stays in an unstable state. It causes the electrical properties of AlGaN/GaN HEMT to present early degradation. A new migration and degradation mechanism of the low power fluorine implant ion under the off-stress electrical stress is proposed. The low power fluorine ions would drift at the beginning of the off-state stress, and then accumulate between gate and drain nearby the gate side. Due to the strong electronegativity of fluorine, the accumulation of the front fluorine ions would prevent the subsequent fluorine ions from drifting, thereby alleviating further the degradation of AlGaN/GaN HEMT electrical properties.

Matlab Code to Assess the Reliability of the Smart Power Distribution System Using Monte Carlo Simulation

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. In this work, we develop a MATLAB code to examine the effect of the smart grid applications in improving the reliability of the power distribution networks via Monte Carlo Simulation approach. The system used in this paper is the IEEE 34 test feeder. The objective is to measure the installations of the Automatic Reclosers (ARs) as well as the Distributed Generators (DGs) on the reliability indices, SAIDI, SAIFI, CAIDI and EUE, and make comparisons with results from a previous study done by the authors using another approach. The MATLAB code should provide close results to the output of the previous research to verify its effectiveness.

A Practical Framework for Reliability and Quality Assessment of Power Systems

This paper presents a new practical framework for evaluating reliability levels associated with power system supply-demand balance. The framework has been developed as part of a recent major industry-supported research and development study. The novel framework is based on three metaphors (dimensions) representing the relationship between available generation capacities and required demand levels. The first metaphor defines whether or not the capacity exists, the second metaphor defines whether or not the capacity is needed, and the last metaphor defines whether or not the capacity can reach (delivered to) the demand. The eight possible combinations associated with the 0/1 (Yes/No) values of the three metaphors would, in turn, define a set of powerful system-wide performance quality measures relating to generation deficiency, redundancy, bottling, etc. Practical applications to a portion of the Saudi power grid are also presented for demonstration purposes. The work of the paper constitutes a new line of research in system reliability assessment where the derived system-wide performance quality indices are capable of addressing and revealing areas of deficiencies and bottlenecks as well as redundancies in the composite generation- demand structure of large-scale power grids. In addition, the sensitivities of the performance quality indices with respect to variations in the system operating parameters represent powerful information, which can be used to assess the level of degradation in the reliability measure or the performance quality index under consideration.

High-speed Railway External Power Supply Reliability Evaluation of Bayesian Network

Reliability evaluation is important in high speed railway external power supply design, based on probability reasoning bayesian network applied in high-speed railway external power supply reliability evaluation, establish the minimum cut and the minimum path of bayesian network model, quantitative calculation external power supply system in each element posterior probability, and the example analysis verified the feasibility and correctness of the above method. Using bayesian network bidirection reasoning technology, quantitative calculation the posterior probability of each element in external power supply system, realized the identification of weak link in external power supply. The research methods and the results of the study can be used in the scheme optimization design of high speed railway external power supply.

Probabilistic Issue of Reliability for Power Machinery Operating in Coal Fired Power Plants

The paper presents results of reliability analysis made for lignite fired 370 MW rated power units installed in the Belchatow Power Plant (Poland). The concept of standardized power unit and the method of a histogram with a set number of observations in each class were applied in a study. The study includes analysis of probability distributions of operation times and repair times for the main power unit components. Empirical probability distribution functions have been identified and their parameters estimated in the study. The final forecast includes an estimation of such reliability measures like expected operation time, expected failure rate, average repair time and expected annual failure duration.

Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.

Reliability Analysis of Hydraulic Transmission Oil Supply System of Power-Shift Steering Transmission with GO Methodology

GO methodology is a success-oriented method for system reliability analysis. There are components with multi-fault modes in repairable systems. It is a problem to use the existing GO method to make reliability analysis of such repairable systems. A new GO method for reliability analysis of such repairable systems with multifault modes was presented. Firstly, calculation equations of reliability parameters of operators which were used to describe components with multi-fault modes in reparable systems were derived based on Markov process theory. Then, this new GO method was applied in reliability analysis of a hydraulic transmission oil supply system( HTOSS) of a power-shift steering transmission at low and high speeds. Finally,Compared with fault tree analysis( FTA) and Monte Carlo simulation,the results show that this new GO method is correct and suitable for reliability analysis of repairable system with multi-fault modes.

The Effectiveness of the Squared Error and Higgins-Tsokos Loss Functions on the Bayesian Reliability Analysis of Software Failure Times under the Power Law Process

Reliability analysis is the key to evaluate software’s quality. Since the early 1970s, the Power Law Process, among others, has been used to assess the rate of change of software reliability as time-varying function by using its intensity function. The Bayesian analysis applicability to the Power Law Process is justified using real software failure times. The choice of a loss function is an important entity of the Bayesian settings. The analytical estimate of likelihood-based Bayesian reliability estimates of the Power Law Process under the squared error and Higgins-Tsokos loss functions were obtained for different prior knowledge of its key parameter. As a result of a simulation analysis and using real data, the Bayesian reliability estimate under the Higgins-Tsokos loss function not only is robust as the Bayesian reliability estimate under the squared error loss function but also performed better, where both are superior to the maximum likelihood reliability estimate. A sensitivity analysis resulted in the Bayesian estimate of the reliability function being sensitive to the prior, whether parametric or non-parametric, and to the loss function. An interactive user interface application was additionally developed using Wolfram language to compute and visualize the Bayesian and maximum likelihood estimates of the intensity and reliability functions of the Power Law Process for a given data.

The Reliability Evaluation Method Study of Power System Communication Networks in Case of Ice Storm

This paper is divided into two cases to study the communication transmission equipment reliability in the state of the ice storm, according to the huge losses of power system communication caused by the ice storm. For the nodes or links which are not affected by the ice storm, we use the calculation with “the mean time between failures (MTBF)” and “the mean time to repair” (MTTR) to put forward the calculation methods;for the OPGW cable which influenced greater in ice storm, we use the fiber excess length and the elongation of fiber optic cable. It obtains all the paths of the network through improved adjacency matrix method, and then it uses binary decision diagram to obtain the overall reliability of the network. By testing the network nodes and links using “N-1” inspection, the key nodes and key links can be obtained. Finally, considering the importance degree of network transmission business, the reliability evaluation method of power system communication network based on the risk theory in the case of the ice storm has been put forward, and the example to verify that the method can provide the basis for the reliability assessment of the power system communication in the case of the ice storm has been given.

Reliability of Power System Integrated with Wind Generation Considering Carbon Tax

This paper proposes a method to evaluate the reliability of power system with different capacities of wind power while considering carbon tax. The proposed method is a hybrid approach which combines Frequency and Duration (F&D) method and Monte Carlo Simulation (MCS) method. MCS method is used to achieve a model to simulate the random status of power system. Also, the proposed method is applied on the IEEE 14-bus test system to investigate the effects of integrating different capacities of wind energy to the reliability of power system with considering carbon tax.

Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using Game Theory (GT) and Neural Networks (NN). Also, due to the stochastic behavior of power markets and generators’ forced outages, Monte Carlo Simulation (MCS) is used for reliability evaluation. Generation reliability focuses merely on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using GT, two outcomes are considered: cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. Loss of Load Expectation (LOLE) is used as the reliability index and the results show generation reliability in cooperation market is better than non-cooperation outcome.

Modelling Complete Power Outage Data Using Reliability

Data on time between complete power outages, Time between Failure (TBF) in Uyo were considered. Trend test and serial correlation test were conducted graphically for the data. The tests proved that the data were identically and independently distributed (iid). Summary statistics of the data showed that complete power outage occurred 416 times between the year 2014 and 2018. The maximum likelihood estimation method was used to estimate the parameters of Weibull 2-parameter, Normal, Lognormal 2-parameter and exponential distributions. The values of Kolmogorov-Smirnov, Anderson Darling and Chi-Square statistics were used to determine the best fit distributions. A model for the computation of reliability of electric power was then proposed.

Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids——An interview with Zhou Xiaoxin, chief scientist of "973 Program"

At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a project of "973 Program". Mr. Zhou, the chief engineer of China Electric Power Research Institute(CEPRI) and an academician of Chinese Academy of Sciences, is the chief scientist in charge of this research project.