Generation System Reliability Research Articles

A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment

This paper proposes a continuous time Markov chain (CTMC) based sequential analytical approach for composite generation and transmission systems reliability assessment. The basic idea is to construct a CTMC model for the composite system. Based on this model, sequential analyses are performed. Various kinds of reliability indices can be obtained, including expectation, variance, frequency, duration and probability distribution. In order to reduce the dimension of the state space, traditional CTMC modeling approach is modified by merging all high order contingencies into a single state, which can be calculated by Monte Carlo simulation (MCS). Then a state mergence technique is developed to integrate all normal states to further reduce the dimension of the CTMC model. Moreover, a time discretization method is presented for the CTMC model calculation. Case studies are performed on the RBTS and a modified IEEE 300-bus test system. The results indicate that sequential reliability assessment can be performed by the proposed approach. Comparing with the traditional sequential Monte Carlo simulation method, the proposed method is more efficient, especially in small scale or very reliable power systems.

Adaptive Fuzzy Logic based MPPT Control for PV System Under Partial Shading Condition

Partial shading causes power loss, hotspots and threatens the reliability of the Photovoltaic generation system. Moreover characteristic curves exhibit multiple peaks. Conventional MPPT techniques under this condition often fail to give optimum MPP. Focusing on the afore mentioned problem an attempt has been made to design an Adaptive Takagi-Sugeno Fuzzy Inference System based Fuzzy Logic Control MPPT.The mathematical model of PV array is simulated using in MATLAB/Simulink environment.Various case studies related to inhomogeneous insolation and temperature has been investigated. For justifying the efficacy of the proposed MPPT technique a comparative analysis has been done with two popular MPPT techniques.

Design optimization and optimal control of grid-connected and standalone nearly/net zero energy buildings

Abstract Nearly/net zero energy buildings (nZEBs) have attracted increasing attention particularly when high and complex performance is required in terms of energy-saving, indoor thermal comfort, environmental friendliness and grid-friendliness. However, there is no exact approach at present for the design and control of buildings to achieve the nearly/net zero energy target. This is mainly due to the complex interplay of energy production/consumption/storage systems as well as the automatically and manually controlled systems/elements in the highly integrated buildings. This paper therefore presents a comprehensive review on the issues related to the design and control of these buildings, i.e. the effects of climate/site on design, design optimization methods, uncertainty and sensitivity analysis for robust design and system reliability, efficient and optimal control of high efficient generation systems and energy storage systems for alleviating/shifting the peak load, model predictive control for fast responses to smart grid, and adoption of advanced smart technologies. An outline of the progress of nZEBs is presented by summarizing the internationally known nZEBs identified including 30 case studies on the design strategies applied and the actual building performance. This review could also support the future development of methods that address the design and control of buildings with a holistic view.

An Improved Optimal Capacity Ratio Design Method for WSB/HPS System Based on Complementary Characteristics of Wind and Solar

The reliability and economic value of wind and solar power generation system with energy storage are decided by the balance of capacity distribution. The improved capacity balance matching method is proposed in this paper, which not only utilizes the complementary characteristics of the wind and solar power generation system sufficiently but also reduces the charge and discharge times of the battery. Therefore, the generation reliability is improved and the working lifetime of the whole system is lengthened. Consequently, the investment of the battery energy storage is reduced as well as the whole cost is decreased. The experimental result was presented to verify the effectiveness of the improved optimal capacity ratio design method.

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.

Electric power system design and analysis for FLNG vessel

The electrical reliability of the power generation and distribution system of Floating Liquefied Natural Gas vessels has been analyzed according to the operating modes using Electrical Transient Analysis Program in this paper. Electricity is used for the topside processes, cargo pumps for off-loading, thrusters for heading control and marine equipment. It is very important to improve the safety, efficiency, and stability of the electrical power system for successful operation. The voltage variation of the high and the low voltage bus shall be within the primitive limitation range at normal operation loads both in steady state and in the transient state. The power system was simulated and compared with class rule for design verification.

Development of a stochastic simulation–optimization model for planning electric power systems – A case study of Shanghai, China

In this study, a stochastic simulation–optimization model (SSOM) is developed for planning electric power systems (EPS) under uncertainty. SSOM integrates techniques of support-vector-regression (SVR), Monte Carlo simulation, and inexact chance-constrained programming (ICP) into a general framework. SVR coupled Monte Carlo technique is used to predict the electricity consumption amount; ICP is effective for reflecting the reliability of satisfying (or risk of violating) system constraints under uncertainty. The SSOM can not only predict the electricity demand exactly, but also allows uncertainties presented as interval values and probability distributions. The developed SSOM is applied to a real-case study of planning the EPS of Shanghai, with an objective of minimizing system cost and under constraints of resources availability and environmental regulations. Different scenarios associated with SO2-emission policies are analyzed. Results are valuable for (a) facilitating predicting electricity demand, and generating useful solutions including the optimal strategies regarding energy sources allocation, electricity conversion technologies, and capacity expansion schemes, (b) resolving of conflicts and interactions among economic cost, electricity generation pattern, SO2-emission mitigation, and system reliability, and (c) identifying strategies for improving air quality in Shanghai through analyzing the economic and environmental implications associated with SO2-emission reduction policies.

Modeling Large-Scale Wind Farms for Reliability Analysis Considering Wake Effect

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

Evaluation of Redundancy for Power Generating Unit in a Cogeneration Power Plant

Redundancy system is very useful to enhance the performance and reliability of the power generation system of a cogeneration plant. However, the associated operating cost of redundancy system is very high. The common redundancies used in a cogeneration power plant are public utility and generator set. In order to select the best redundancy options which incurs minimum operating cost, it is required to evaluate the cost of different redundancy options. In this paper, net present value model (NPV) is developed to evaluate the cost of redundancy considering availability and reliability of the cogeneration system. Two steps applied to evaluate the redundancy cost of the cogeneration system. The first step is predicting the number of failures and downtime hours using availability and reliability analysis because redundancy is frequently used when the system failed. The second step is evaluating the cost of redundancy using NPV model. The results indicate that the use of public utility as redundancy option is costly compared to generator set option for long period of time. The major operation cost of public utility is contributed by the maximum demand charge cost which is about 57.9% of the total cost of redundancy. The study will be useful as a guide for the cogeneration operation to evaluate and select the redundancy option.

Multiobjective Optimization of Renewable Energy Penetration Rate in Power Systems

Nowadays, multi-source systems based on renewable energy technologies become the key to a sustainable energy supply infrastructure against the rising cost and the pollutant nature of fossil primary energy used in conventional power plant. However, the cost of renewable energy technologies and the reliability of a multi-sources generation system are generally conflicting with each other. This paper presents a multiobjective formulation to allow optimizing simultaneously both the annualized renewable energy cost the system reliability defined as the renewable energy - load disparity (RELD). This later takes into account the lack of energy as well as the exceed weighted by a penalty factor. The optimization is reach by acting on the penetration rate of each type of renewable generation technologies in order to satisfy a certain load curve. In order to solve this problem, this work suggests to use the fast and elitist multiobjective genetic algorithm: NSGA-II. A case study shows that the use of diversified resources allows to handle the RELD and to decrease the exceed renewable energy (RERE) and load energy notsupplied (LENS).

Optimization of production and maintenance problem: Case study of wind turbine power generation

W turbine system reliability is a critical factor in the success of a wind energy project. Consequently, maintenance is a crucial issue for such projects. In this paper, an integrated production and periodic maintenance policy with minimal repair at failures is proposed for a hybrid power generation system. We seek to establish an optimal integrated electricity production and maintenance plan over a finite planning horizon. It is important to do so according to the wind speed profile in order to guarantee that a random power demand (consumption) is satisfied given a target service level. In the context of energy planning, many researchers presented several techniques and methods which provide solutions to the multi-objective optimization problem for energy planning decisions. They have observed that Analytical Hierarchy Process (AHP) is the most popular technique followed by outranking techniques Promethee and Electre. Regarding renewable power generation systems reliability, some researchers studied the factors that contribute to the reliability deterioration of such systems; they concluded that in a significant part of the year, seasonal and spatial variability of wind, and to a lesser extent that of solar energy can yield low availability leading to an increase in unserved energy. Based on these literature reviews, we propose in this talk an integrated production-maintenance policy for wind turbine power generation. In fact, our approach consists in determining the best combination of energy production and maintenance effort, which minimizes the total cost while satisfying a random demand during a finite horizon with a given service level. This study is inspired from the background work, which models the influence of the production rate on the degradation level of the production system, and consequently on the maintenance strategy. A numerical example illustrates the use of the developed mathematical model.

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.

Copula-ARMA Model for Multivariate Wind Speed and Its Applications in Reliability Assessment of Generating Systems

The dependence between wind speeds in multiple wind sites has a considerable impact on the reliability of power systems containing wind energy. This paper presents a new method to generate dependent wind speed time series (WSTS) based on copulas theory. The basic feature of the method lies in separating multivariate WSTS into dependence structure and univariate time series. The dependence structure is modeled through the use of copulas, which, unlike the cross-correlation matrix, give a complete description of the joint distribution. An autoregressive moving average (ARMA) model is applied to represent univariate time series of wind speed. The proposed model is illustrated using wind data from two sites in Canada. The IEEE Reliability Test System (IEEE-RTS) is used to examine the proposed model and the impact of wind speed dependence between different wind regimes on the generation system reliability. The results confirm that the wind speed dependence has a negative effect on the generation system reliability.

The Improvement on Wind Power Generation System Reliability based on Cluster Management

The Improvement on Wind Power Generation System Reliability based on Cluster Management

Reliability Assessment of Power Generation System With Wind Farm

The reliability of power generation system with wind farm is evaluated based on Monte-Carlosimulation, and in the reliability assessment the randomness of wind speed and power load, failure rate ofwind turbine generator(WTG) and conventional generator are take into account. Monte-Carlo simulationused in power generation system with wind power need large sample size and has low efficiency. So thispaper proposes an improved Monte Carlo method (IMC) based on the combination of Latin HypercubeSampling and Cholesky decomposition, this IMC method is effective to improve sample values coverage ofrandom variables input spaces and the sampling efficiency. The calculation and analysis of improvedIEEE-RTS 79 reliability test systems show that the proposed Assessment algorithm is effective.

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.

Maintenance Scheduling of Composite Generation and Transmission Systems Using Multi-Objective Evolutionary Optimization

Reducing the overall cost and improving the reliability are two primary but often conflicting objectives for composite generation and transmission system . Scheduling of appropriate preventive maintenance requires optimization among multiple objectives. In this paper, a systematic and integrated methodology with three functional blocks is proposed. In the first block, the stochastic deterioration process of individual components is formulated as a continuous-time Markov model, in which transition rates incorporate the influences of the aging of components and two (minor and major) maintenance extents. Reliability of a composite generation and transmission system is dependent upon its topology as well as its load and generation profiles, and is evaluated in the second block. In the third block, Pareto-based multi-objective evolutionary algorithm is proposed because of its proven ability to search towards the optimum among a large number of potential solutions for providing a holistic view of conflicting relationships among multiple objectives. The proposed approach is applied to the IEEE reliability test system (IEEE-RTS), and the reliability, maintenance and failure costs of the entire IEEE-RTS are optimized. The successful application to IEEE-RTS demonstrates its potential of handling complex systems.

Development of a FPGA Based Real-Time Power Analysis and Control for Distributed Generation Interface

Energy coming from renewable sources has become very important nowadays, mainly because of their negligible contribution to greenhouse gas generation. A problem that then arises is how to integrate these new sources into a traditional power grid, in such a manner as to maximize the efficiency and reliability of this new distributed generation (DG) system. The hardware to do that is generally a voltage source inverter (VSI) that supplies a common load, as in single-phase residential and commercial applications. The optimizing process requires, of course, the usual power analysis. This paper presents the development and the experimental evaluation of a power control system for a single-phase grid-connected VSI including the power analysis using as processor for the control implementation a field-programmable gate array (FPGA) circuit. New hardware structures of adaptive linear neural networks (ADALINE) allow the implementation of power control algorithms and have also permitted the real-time analysis of the high-order harmonics without increasing the implementation area of the FPGA circuit. These features are ideal for novel DG power electronics interfaces that could be used not only for active power dispatch but also for harmonics and reactive power compensation. Simulation and experimental results of the proposed fixed and variable frequency schemes are included to confirm their validity.