Generation System Reliability Research Articles

Adaptive Fuzzy Control for Variable Speed Variable Pitch Eind Turbines

Automatic control is crucial for the efficiency and reliability of wind power generation systems. Wind energy conversion systems have strong nonlinear multi variable with many uncertain factors and disturbances. A new method for estimating the optimal rotating speed at low wind speed is Proposed using fuzzy logic inference system. The method avoids the inaccuracy owmg to measunng the wind speed. Adaptive fuzzy controllers based on variable universe are employed to improve wind energy capture for variable speed, variable pitch wind turbines. The fuzzy algorithm keeps the form of rules and varies universe of discourse accordmg to the control error fme control accuracy can be achieved. The maximum power coefficient is realized by generator torque control at low wind speed, and also pitch angle is adjusted to keep rated output power at high wind speed. Simulation results verify the effectiveness of the proposed methods.

Alternative view on the mechanism of cardiac rhythmogenesis

Background: This article advances an hypothesis that there is duplication of the heart rhythmogenesis system. Methods and Results: The following article reviews available data and advances an hypothesis to suggest new ideas about the mechanisms of cardiac rhythm generation. The hypothesis is that along with the existence of an intracardiac pacemaker, the generator of cardiac rhythm exists in the central nervous system - in the efferent structures of the cardiac centre of the medulla oblongata. Originating in the medulla oblongata, neural signals in the form of brief bursts of pulses are conducted to the heart along the vagus nerves and, by interacting with the cardiac pacemaker structures, cause generation excitement in the heart in exact accordance with the frequency of the bursts. The intracardiac rhythm generator is a life-providing factor that maintains the heart pumping function when the central nervous system is in a stage of deep inhibition (e.g. under anaesthesia or when unconscious). The central generator is the factor that provides the heart with adaptive reactions in natural conditions of the organism. Conclusions: Multi-leveled organisation of the mechanisms responsible for rhythmogenesis guarantees reliability and functional perfection of the cardiac rhythm generation system.

Power sector development in India with CO2 emission targets: Effects of regional grid integration and the role of clean technologies

The power sector in India at present comprises of five separate regional electricity grids having practically no integrated operation in between them. This study analyses the utility planning, environmental and economical effects of integrated power sector development at the national level in which the regional electric grids are developed and operated as one integrated system. It also examines the effects of selected CO2 emission reduction targets in the power sector and the role of renewable power generation technologies in India. The study shows that the integrated development and operation of the power system at the national level would reduce the total cost including fuel cost by 4912 million $, total capacity addition by 2784 MW, while the emission of CO2, SO2 and NOx would be reduced by 231.6 (1.9%), 0.8 (0.9%), 0.4 (1.2%) million tons, respectively, during the planning horizon. Furthermore, the study shows that the expected unserved energy, one of the indices of generation system reliability, would decrease to 26 GWh under integrated national power system from 5158 GWh. As different levels of CO2 emission reduction targets were imposed, there is a switching of generation from conventional coal plants to gas fired plants, clean coal technologies and nuclear based plants. As a result the capacity expansion cost has increased. It was found that wind power plant is most attractive and economical in the Indian perspective among the renewable options considered (Solar, wind and biomass). Copyright © 2003 John Wiley & Sons, Ltd.

Adequacy assessment of power system generation using a modified simple genetic algorithm

This paper presents a new method for the assessment of generation system reliability. The proposed method is based on a modified version of the simple genetic algorithm. In this method, a genetic algorithm is used, not for its traditional objective of optimization, but as a search tool to truncate the probability state space and to track the most probable failure states. The genetic algorithm stores system states, in which there is generation deficiency to supply system maximum load, in a state array. The given load pattern is then convoluted with the state array to obtain adequacy indices. A state array is also used to obtain useful information about the contribution of different states and generation unit combinations to the probability of system failure.

Adequacy Assessment of Power System Generation Using a Modified Simple Genetic Algorithm

A new method for the assessment of generation system reliability is based on a modified version of the simple genetic algorithm (MSGA). A genetic algorithm (GA) is used not for its traditional objective of optimization but as a search tool to truncate the probability state space and to track the most probable failure states. The GA stores system states, in which there is generation deficiency to supply system maximum load, in a state array. The given load pattern is then convoluted with the state array to obtain adequacy indices. State array is also used to obtain useful information about the contribution of different states and generation unit combinations to the probability of system failure.

A fuzzy-based approach for generation system reliability evaluation

Abstract A new method for calculating generation system reliability using fuzzy mathematics is presented here. In reliability evaluation of power systems, a membership function can be provided to represent the uncertainties and inaccuracies in the failure rates and repair rates of generating units. The basic unit addition recursive algorithm is modified to represent these uncertainties along with uncertainties in system load as fuzzy data. Loads are represented as clusters to overcome the difficulty of large computational time requirements. A computer program has been developed in C language to include all aforementioned factors. The program was tested with the IEEE Reliability Test System on an IBM RS/6000 workstation. Several cases were analyzed and results are presented. The algorithm developed computes reliability indices such as loss of load probability (LOLP) and the expected unserved energy (EWE) which are viewed as possibility distributions.

Well-being framework for composite generation and transmission system reliability evaluation

The basic objective of generation and transmission systems is to serve every major load point in the system as reliably and economically as possible. The probability of failure that is related to the load characteristics is important in the reliability study of generation and transmission systems. This paper describes a probabilistic method, designated as system well-being analysis, for evaluating the effect of peak load, load factor, load curtailment philosophy and percentage load curtailed. Contingency level selection, a dominant factor that influences the accuracy and efficiency of probability study, is also considered. This approach incorporates the conventional risk index as well as the accepted deterministic criteria identified as being in the healthy and marginal states. By including deterministic criteria in conjunction with probabilistic methods, well-being indices based on these criteria can be used by the system operator to alleviate the difficulties encountered in interpreting a single risk index. A technique for calculating the well-being indices in generation and transmission systems, together with the effects of individual load attributes, is illustrated by application to an educational test system designated as the RBTS.

Animated Monte Carlo simulation for teaching power generating system reliability analysis

This paper presents the GENAS simulation program which has been developed and used for educational purposes. The program is developed based on a combination of animation and Monte Carlo concepts to help students interactively and visually understand the random behavior and reliability performance of large electric power systems as a function of time. The GENAS program dynamically produces color moving pictures of the system as well as the numerical values of system reliability indices. This combination of animation and Monte Carlo techniques provides students with the information not generally available from conventional tools of reliability instruction.

Reliability analysis of electric utility SCADA systems

Electric utility SCADA systems must be highly reliable given the potential for the SCADA system to directly contribute to load curtailment. This paper presents an analysis of SCADA system reliability in terms of its expected, aggregate contribution to load curtailment on the power system. Expressing this aggregate in system minutes and applying an appropriate damage cost function then provides an annual cost measure of SCADA system reliability worth. A composite generation and transmission system reliability evaluation technique is used to perform the numerical analysis of the joint SCADA and power system model. This performs a Monte Carlo simulation and includes an optimal power flow for enumerating grid load curtailment states and analysis of SCADA system component connectivity to determine availability of SCADA control. The application of this analysis is illustrated in a comparison of two alternative SCADA architectures. Trans Power (New Zealand) has adopted a subtransmission SCADA architecture which utilises terminals operating off its national SCADA system. These terminals have replaced separate systems located in each area. The objective of the evaluation being to quantify the increased exposure to financial losses due to joint load curtailment.

Application of perturbation analysis to sensitivity computations of generating units and system reliability

Power generating units do not contribute equally to system reliability. The contribution or reliability importance of units can be determined by the sensitivity of system indices to input uncertainties. Units with high sensitivities are the primary candidates for system upgrades or improvements. This paper extends the infinitesimal perturbation analysis (IPA) to complex Monte Carlo based generating system reliability programs and computes system and unit sensitivity measures. Generating units are represented by 3- and 6-state models and various important system operating rules and policies are recognized. Results from a case study are presented and discussed.

Application of the state transition sampling technique to system reliability evaluation

Monte Carlo simulation is becoming an attractive alternative to analytical approaches for reliability evaluation in large electric power systems. Monte Carlo simulation is generally more flexible than an analytical technique when complex operating conditions and system considerations such as multi-derated states, chronology, reservoir operating rules, bus load uncertainty and weather effects need to be incorporated. Monte Carlo techniques are usually classified as being either a sequential or non-sequential method. The basic non-sequential Monte Carlo approach is known as the state sampling method in which the actual frequency of failure is estimated from the number of failures encountered during the simulation process. The actual frequency of failure can be more accurately obtained by using a sequential approach which models the component up and down cycles together with the system load. This paper presents and illustrates the application of the state transition sampling technique. This method can be used to estimate the actual frequency index without requiring an additional enumeration procedure or sampling the component up and down cycles and storing chronological information on the overall state of the system. In this approach the next system state is obtained by allowing a component to undergo transitions from its present state. The procedure focuses on transitions of the whole system rather than on component states or state durations. This technique is usually much faster than the traditional sequential simulation approach. The state transition sampling technique will be illustrated by application to generating capacity and composite generation and transmission system reliability assessment in a representative electric power system. © 1997 John Wiley & Sons, Ltd.

Application of sequential Monte Carlo simulation to evaluation of distributions of composite system indices

The reliability of composite generation and transmission systems with time varying loads at each bus can be effectively assessed using the sequential Monte Carlo simulation method. This method can also provide information on the distributions of the adequacy indices, which is not possible with other nonsequential approaches. The approach presented uses an annual chronological load curve for each load bus and a sequential Monte Carlo approach for composite system reliability assessment. The paper presents the basic sequential simulation technique and illustrates its application to obtain distributions of the various composite system indices for the IEEE reliability test system.

Economic Valuation of Generation System Reliability using Customer Outage Costs in India

Economic Valuation of Generation System Reliability using Customer Outage Costs in India

A NEW METHOD FOR RELIABILITY EVALUATION OF POWER GENERATING SYSTEMS

ABSTRACT This paper presents a new power generating system reliability evaluation model which performs like a Monte Carlo based reliability model but without using random number generators or probability distribution of system components. The proposed method is based on a class of Petri Nets known as timed state machine Petri Nets (TSMPNs). The method is simple, flexible, accurate, and extremely fast. A comparison of results from the new model with those from conventional Monte Carlo based reliability techniques shows the fidelity of the model and its potential usefulness in power system reliability studies.

Assessing the impact of operating constraints and operating policy on the reliability level of a generation system

This paper presents a chronological stochastic method for evaluating the reliability of a generation system, taking operating considerations into account. A sequential Monte Carlo production simulation is used to evaluate the risk level associated with the chronological operation of the system over a year. The approach is based on a combination of a weekly deterministic unit commitment and an hour-by-hour simulation of the system response to unit outages that are not yet known at the beginning of the week. It enables to deal with important aspects in actual system operation: time dependent constraints, energy limited units and start-up delays of thermal units. It can be used to assess the influence of the operating constraints and the operating policy on the reliability level of a generation system. The method is applied to a test case related to a single system and extended to a second text case involving two interconnected systems sharing their operating reserve.

96/03885 Comparison of unit addition and fast Fourier transform methods for generation system reliability evaluation

96/03885 Comparison of unit addition and fast Fourier transform methods for generation system reliability evaluation

Integrated Analysis of Customer Value of Generation System Reliability in India

An analytical framework that integrates generation resource outage characteristics and customer value of electricity supply is developed to represent and evaluate reliability of the power system in north India. The composite outage cost function is estimated to be of log-linear form based on the regression analysis of data obtained through extensive customer field surveys in the region. The research illustrates that potentially higher direct outage costs have been displaced by relatively lower adaptive response investments to counteract the impact of interruptions. The implicit reliability of the country`s generation capacity plan through 2000, used along with the outage cost estimates, gives an interrupted energy value, a customer-value-based reliability index, of 2.30 Rupees per kilowatt-hour not served in 1990 ($US 1990 = Rupees 17.50). The outage cost-based reliability planning criterion provides an optimal level of reliability equivalent of 9.1% loss of load probability (LOLP). A comparison reveals that the generation capacity program is unreliable in the beginning but becomes overly reliable toward the later years of the plan.

Comparison of unit addition and fast Fourier transform methods for generation system reliability evaluation

Several methods have been proposed to improve the efficiency of convolution of generating unit probability distributions, since this is the most basic step in reliability and production cost studies. These methods can be broadly classified into those based on discrete convolution and others based on approximations using continuous distributions. The traditional approach to discrete convolution is based on unit addition algorithms. Another approach transforms this convolution into discrete Fourier domain, where the Fourier transform of the system can be obtained by the product of the Fourier transform of the unit probability distributions. The objective of this paper is to provide a comparison between unit addition algorithm and the Fast Fourier Transform method of building capacity outage probability tables.

96/00593 Reliability and economic analysis of a power generation system including a photovoltaic system

96/00593 Reliability and economic analysis of a power generation system including a photovoltaic system

95/06103 Evaluation of generation system reliability indices by fast transform techniques

95/06103 Evaluation of generation system reliability indices by fast transform techniques