Generation System Reliability Evaluation Research Articles

Application of Generation Adequacy Analysis for Reliability Evaluation of a Floating Production Storage and Offloading Platform Power System

This paper proposes the application of generation adequacy analysis for reliability evaluation of an insulated power generation system that supplies a FPSO (Floating Production Storage and Offloading) oil and gas production platform. The frequency and duration method was adopted for generating system reliability evaluation. The historical reliability data of the floating production storage and offloading platform power system and the continuous Markov process are used to determine the generator’s reliability model. The load model was also based on the platform daily peak load variation curve. The system risk indexes were obtained using Monte Carlo simulation. Two system scenarios were simulated using different failure data for one of the generators and the software PowerFactory© has been used as a tool for this simulation. For a complete generation system modeling, frequency and duration methods were developed to calculate the probabilities, frequencies and duration of the system states. Numerical results are presented and discussed to demonstrate the applicability of the proposed method.

Reliability evaluation of composite generation and transmission systems via binary logistic regression and parallel processing

In power system planning studies that involve the search for optimal investments with low risks for the power grid, probabilistic reliability assessments provide very useful tools and indices. A challenge faced in the application of these tools is related to the computational effort demanded by the evaluation process, especially when the combined effects of failure of generation and transmission equipment are considered. In this context, the present work proposes a new method for efficient estimation of the main composite reliability indices by combining Binary Logistic Regression (BLR) technique, a machine learning tool used for binary data classification, with the non-Sequential Monte Carlo simulation (NS-MCS) method. In addition, a computational parallelization strategy is incorporated to the proposed method to improve even more the efficiency of the composite reliability assessment. The performance of the proposed approach is analyzed by evaluating composite reliability indices for the IEEE-RTS considering two different generation and load scenarios, in addition to a real large-scale power system. The results obtained are compared with those using the NS-MCS method in its conventional version.

Interval Reliability Evaluation of a Hybrid Energy Generation System With Energy Storage

To deal with the uncertainties of wind power and load residing in the power supply reliability model, an interval reliability evaluation method is proposed by combining the wind power generation and energy storage system (ESS). Firstly, the interval power supply reliability evaluation model, which belongs to an interval mixed integer program (IMIP), is established based on the interval variables. Secondly, the IMIP model is transformed into the deterministic optimization model under two extreme circumstances by utilizing the possibility degree theory of interval numbers. The maximum power supply probability, considering the wind power interval to meet the load demand interval, is sought by optimizing outputs of the ESS and generators, i.e., the upper boundary of the load shedding is the smallest. Finally, the states of wind turbines and generators are generated based on sequential Monte Carlo simulation, and the reliability of the hybrid energy generation system is evaluated by calculating the loss of load expectation, expected energy not supplied, and maximum power supply probability, which provides a basis for establishing interval optimal allocation model of energy storage. IEEE RTS-24 test system is utilized to verify the performance of the proposed method, and the model is solved by the CPLEX 12.7 solver. The simulation results demonstrate the effectiveness and applicability of the proposed method.

Reliability Evaluation of Photovoltaic System Considering Inverter Thermal Characteristics

The reliable operation of photovoltaic (PV) power generation systems is related to the security and stability of the power grid and is the focus of current research. At present, the reliability evaluation of PV power generation systems is mostly calculated by applying the standard failure rate of each component, ignoring the impact of thermal environment changes on the failure rate. This paper will use the fault tree theory to establish the reliability assessment method of PV power plants, model the PV power plants working in the variable environment through the hardware-in-the-loop simulation system, and analyze the influence of the thermal characteristics of the inverter’s key components on the reliability of the PV power plant. Studies have shown that the overall reliability of bus capacitors, inverters, and PV power plants is reduced by 18.4%, 30%, and 18.7%, respectively, compared to when the thermal characteristics of bus capacitors are not considered. It can be seen that thermal attenuation has a great influence on the reliability of the PV power generation system.

RELIABILITY EVALUATION OF COMPOSITE SYSTEM WITH AGING FAILURE

Reliability is concerned with the system capability of survival. In the past forty years, customer expectations have been increasing in response to evolving new technologies. As part of these evolutions, they are demanding from their suppliers: products with higher quality, low initial cost, improved customer support and products that are easy and inexpensive to maintain. For a supplier to survive, succeed and be profitable in todays market, It must do the following: a) Constant improvement in the quality of the products. b) Minimization of the cost. c) Be flexible and responsive to the customers requirement. This deals with reliability evaluation of combined generation and transmission system known as composite system. It describes a technique calculate composite system reliability with aging failure. The reliability evaluation deals with the a) Calculation of aging failure rate & aging repair rate of all Components of the system. b) Calculation of EENS value of all Components of the system by performing Reliability Analysis using SKMS PTW 6.5.

Analytical model for fast reliability evaluation of composite generation and transmission system based on sequential Monte Carlo simulation

This paper proposes an analytical reliability evaluation (RE) model for composite generation and transmission system (CGTS) based on the sequential Monte Carlo simulation (MCS) method. The main idea is to partition the chronological system state sequence produced by sequential MCS into a set of mutually exclusive events based on the law of total probability. An analytical model is developed by extracting the component reliability parameters (CRPs) from system reliability index calculation formula of each mutually exclusive event. Once the proposed model is established, system reliability indices with variable CRPs can be obtained directly, rather than repeatedly performing the time-consuming sequential MCS process. In addition, sensitivity coefficients of system reliability indices with respect to CRPs can be obtained using the developed analytical model. A 4-unit generation system, the CGTS of IEEE-RTS system and a 91-bus power system are used for case study to validate the correctness and effectiveness of the proposed analytical RE model.

Reliability evaluation of tidal and wind power generation system with battery energy storage

This paper presents a method for reliability evaluation of a hybrid generation system of wind and tidal powers with battery energy storage. Such a system may widely exist in coastal areas and islands in the future. A chronological multiple state probability model of tidal power generation system (TPGS) considering both forced outage rate (FOR) of the TPGS and random nature of tidal current speed is developed. In the evaluation of FORs of TPGS and WPGS (wind power generation system), the delivered power related failure rates of power electronic converters for TPGS and WPGS are considered. A chronological power output model of battery energy storage system (BESS) is derived. A hybrid system of tidal and wind generation powers with a BESS is used to demonstrate the effectiveness of the presented method. In case studies, the effects of various parameters on the system reliability are investigated.

Reliability Evaluation of a Tidal Power Generation System Considering Tidal Current Speeds

This paper presents a reliability evaluation method for a tidal power generation system (TPGS) with a doubly-fed induction generator (DFIG). The key to the method is the modeling of the tidal current speed-dependent failure rates of the rotor side converter (RSC) and grid side converter (GSC). The models for calculating the rotor currents through the RSC and GSC and the rotor current state related failure rates are presented. Based on the Wakeby distribution of tidal current speed, a multistate discrete probability distribution technique for rotor current is developed. Case studies are described using tidal current speed data from four coastal sites in North America. The results indicate that the failure rates of the RSC, GSC, and the entire TPGS vary with tidal current speeds and the probability distributions of tidal current speed. The TPGS suffers a much higher failure risk in the super-synchronous mode than in the idle and subsynchronous modes. The failure rate of the RSC is much higher than that of the GSC. The change trends in the failure rates of RSC and GSC in the operation modes are different. The probability distributions of tidal current speed have significant impacts on the reliability of the TPGS.

Study the Influence of the Implementation of Demand Side Management on Generation System Reliability

At present, the influence of implementing demand side management on generation system reliability was studied by more and more academics. Demand side management can improve energy efficiency and reduce the maximum load demand, which is equivalent to an indirect increase in power generation capacity of the system, thus can improve the reliability of generation system. This paper firstly introduced the reliability index system of generation system, then the reliability analysis model which includes generation capacity model and load model was respectively built, and then the non-sequential Monte Carlo simulation method applied in generation system reliability evaluation was analyzed. Secondly, adopted the simulation to quantify and set the IEEE reliability testing system RTS (Reliability Test System) as an example to analyze the effect of demand side management on generation system reliability evaluation, the analysis results show that the implementation of DSM can improve the energy utilization and reliability of generation system, thus the system can be more secure, economic and reliable to supply electric power for electricity users.

Research on Reliability Evaluation Methods of Composite Generation and Transmission System

The basic mathematical method for power system reliability evaluation was indicated, the simple and complex system was respectively introduced, several methods of reliability analysis of simple was given in this paper, and the reliability evaluation indexes system and methods of composite generation and transmission system was analyzed, then focused on state enumeration method applied in the reliability assessment of system, the detailed example analysis was given and the adequacy reliability indexes were computed in detail. Finally, the current reliability evaluation and status of composite generation and transmission system was summarized simply and its reliability evaluation algorithm steps applied in current actual engineering projects was given.

Accelerated State Evaluation and Latin Hypercube Sequential Sampling for Composite System Reliability Assessment

This paper proposes improvements in the sequential Monte Carlo (MC) simulation based approaches for reliability evaluation of composite generation and transmission systems. The main idea is to compute a threshold load level to facilitate the process of state evaluation, which is very time-consuming mainly due to optimal power flow computations. Two main sampling techniques namely random sampling (RS) and Latin Hypercube sampling (LHS) are applied to the proposed sequential MC simulation technique. Their performances in terms of simulation time as well as solution accuracy are compared. Case studies using the IEEE Reliability Test System (IEEE RTS) are utilized to demonstrate the performance of the proposed approach. Reliability indices including loss of load probability, expected unserved energy, loss of load frequency and duration are estimated. It is shown that the proposed approach considerably reduces the computational requirements during state evaluation, and that the application of LHS can further decrease the simulation time and required sample size to reach convergence.

Reliability Evaluation of Generation and Transmission Systems Considering the Effects of Wind Farm

Because wind energy fluctuates randomly, the output power of wind turbine generators is uncertain. The reliability of power systems including wind generation is analyzed in this paper. In this paper, the reliability model of wind generators and the model of transmission network are combined by considering the sequential and autocorrelation of wind speed, the output power function and the forced outage of wind units. Then a reliability evaluation model of generation and transmission system, in which the system security constraints are satisfied, is built and the objective function is LSC. Taking IEEE-RTS96 system as an example, the reliability index which can reflect the effects of wind farms is calculated. The result provides the scientific reference for connecting wind farms to power systems.

A Fast Contingency Screening Technique for Generation System Reliability Evaluation

In most existing reliability evaluation techniques, the stopping rules applied for contingency enumeration are either a given number of states with the highest probabilities or the states up to a specified failure order. However, the probability of a high order outage state may be larger than that of a low order outage state due to different reliabilities of the failed components. On the other hand, a low probability state with high outage capacity may have larger impact on system reliability than a high probability state with low outage capacity. These effects have not been considered in the existing techniques for contingency filtering or screening. A fast contingency screening technique (FCST) for generation system reliability evaluation is proposed in this paper. In this technique, contingency states are searched and ranked based on the severity coefficients determined by both state probabilities and outage capacities of the failed units. Several severity coefficients for a unit are defined and examined based on reliability and capacity factors. The replaceable neighboring states of a state and the minimum set of the neighboring states are defined to further reduce computation time. The merits of the proposed techniques and severity coefficients are validated by evaluating the East-China Power Grid.

Dependable Capacity Evaluation of Wind Power and Solar Power Generation Systems

Integration of renewable energy sources, such as wind power and solar power, into the generation system can enhance country's energy security. These alternative energy help diversify sources of primary energy used to produce electricity. However, the biggest disadvantage of using these types of renewable energy power plants is that it might reduce power system reliability because these intermittent renewable energy sources have low dependable capacity. This paper aims to evaluate the dependable capacity of wind power and solar power generation systems. It considers uncertainties due to intermittent wind speed, solar irradiance, ambient temperature, and unavailability of their corresponding generators. Additionally, load uncertainty is also taken into account. The dependable capacity of the wind power and solar power generation systems are determined from the principle of generation system reliability evaluation. The reliability index such as Loss of Load Probability (LOLP) will be used as a key indicator to dene the dependable capacity

Incorporating multiple correlations among wind speeds, photovoltaic powers and bus loads in composite system reliability evaluation

This paper presents a composite generation and transmission system reliability evaluation method incorporating multiple correlations among wind speeds, insolations and bus/regional load curves. The proposed method can accurately model any probability distribution and all the correlations between wind speeds, between solar insolations, between load curves, between wind speeds and solar insolations, between wind speeds and load curves, and between solar insolations and load curves. The IEEE-Reliability Test System (RTS) with additional two wind farms and two PV power stations is used to demonstrate the application of the presented method in composite system reliability evaluation.

Generation System Reliability Evaluation Incorporating Correlations of Wind Speeds With Different Distributions

This paper presents a Monte Carlo based generation system reliability evaluation method that can accurately model correlations between multiple wind speeds following different probability distributions. The assumption of normal distribution in the traditional correlation matrix method is eliminated. Applications to the Weibull, Burr, lognormal and gamma distributions which are popular for wind speed representation are analyzed in detail. The reliability evaluation procedure considering correlations of wind speeds following different distributions is developed. The IEEE-RTS with four additional wind farms whose wind speeds follow different types of distributions is used to demonstrate the application of the presented method in generation system reliability evaluation.

Power estimation and reliability evaluation of municipal waste water and self-excited induction generator-based micro hydropower generation system

This paper presents power estimation and reliability evaluation of the micro hydro power generation system based on municipal waste water. Self-excited induction generator was used in the developed power plant, situated at IIT (BHU) campus, Varanasi, India. The hydro potential of the waste water flowing through sewage system of the Banaras Hindu University has been determined for annual flow duration and daily flow duration curves by ordering the recorded waste water from maximum to minimum flows. This paper estimates output power and determines reliability indices like: failure rate, repair rate, MTTF, MTTR and MTBF of the MWW-based developed generation plant. Design parameters of the SEIG with suitable values of the capacitor have been used and recommended for improvement of the power generation quality and reliability of the system.

Adequacy equivalent development of composite generation and transmission systems using network screening

Reliability evaluation of a large composite generation and transmission system involves extensive and time-consuming calculations. Application of reliability equivalent networks therefore seems necessary in the reliability evaluation of large power systems. An approach is presented to develop an adequacy equivalent of a composite system using network screening. In the proposed method, a power system is divided into two portions designated as the study area and the external area. The goal is to find the adequacy equivalent of the external area in order to facilitate extensive reliability studies in the study area. The elements in the external area are ranked or screened based on their impacts on power flows in the tie lines between the two areas. Owing to their less impact, the lower ranked elements are considered to be involved in a network reduction technique. Simulation studies are conducted on the IEEE-RTS-96 and the performance of the developed procedure is thoroughly discussed.

Incorporating wind power in generating system reliability evaluation

Wind is regarded as an important energy source, and its integration into existing electric power systems dominated by conventional generating sources introduces many technical and business challenges. One important technical challenge is to incorporate wind power reliability considerations in the reliability assessment techniques presently used by electric power utilities to assess the adequacy of the overall generating capacity to serve the future load requirements. The development of comprehensive reliability evaluation techniques will become even more important for the next generation of power systems as wind power penetration levels continue to increase. This paper illustrates how the wind data at a particular site can be utilized to create wind power models and applied in generating capacity adequacy assessment. The developed concepts are applied to two published reliability test systems considering various factors, and the reliability impacts of energy storage, wind dependence on multiple wind farms, wind capacity credit and the replacement of conventional generation by wind power are illustrated.

Population-Based Intelligent Search in Reliability Evaluation of Generation Systems With Wind Power Penetration

Adequacy assessment of power-generating systems provides a mechanism to ensure proper system operations in the face of various uncertainties including equipment failures. The integration of time-dependent sources such as wind turbine generators (WTGs) makes the reliability evaluation process more challenging. Due to the large number of system states involved in system operations, it is normally not feasible to enumerate all possible failure states to calculate the reliability indices. Monte Carlo simulation can be used for this purpose through iterative selection and evaluation of system states. However, due to its dependence on proportionate sampling, its efficiency in locating failure states may be low. The simulation may thus be time-consuming and take a long time to converge in some evaluation scenarios. In this paper, as an alternative option, four representative population-based intelligent search (PIS) procedures including genetic algorithm (GA), particle swarm optimization (PSO), artificial immune system (AIS), and ant colony system (ACS) are adopted to search the meaningful system states through their inherent convergence mechanisms. These most probable failure states contribute most significantly to the adequacy indices including loss of load expectation (LOLE), loss of load frequency (LOLF), and expected energy not supplied (EENS). The proposed solution methodology is also compared with the Monte Carlo simulation through conceptual analyses and numerical simulations. In this way, some qualitative and quantitative comparisons are conducted. A modified IEEE Reliability Test System (IEEE-RTS) is used in this investigation.