Probabilistic assessment of spinning reserve in isolated and interconnected generation systems

The assessment of spinning reserve requirement is an important aspect in short-term generation planning. A number of deterministic approaches are presently used to assess spinning reserve requirements in isolated and interconnected generating systems. The emphasis when using a deterministic approach to unit commitment and spinning reserve assessment is to minimise the total operating cost, and in doing so a system faces different degrees of risk throughout the day. Deterministic approaches do not take the stochastic behaviour of system components in its evaluation process in a consistent manner. A probabilistic approach can be utilised to recognise the stochastic nature of system components during spinning reserve assessment. The basic objective in using a probabilistic approach is to maintain the unit commitment risk equal to or less than a specified value throughout the day. This paper illustrates the spinning reserve assessment in isolated systems with numerical examples. A probabilistic approach for spinning reserve assessment in interconnected system is also presented in this paper. The technique, designated as the ‘two risks concept’, is a logical extension of a probabilistic technique utilised for spinning reserve assessment in isolated systems. The technique is developed on the basis of each area in a multi-area configuration fulfilling two different risk criteria.     

Evaluation of the marginal outage costs in generating systems using quantitative power system reliability techniques

Marginal outage costs are an important component of electricity spot prices. This paper describes a methodology based on quantitative power system reliability techniques for calculating these costs in generating systems. The proposed method involves the calculation of the incremental expected unserved energy at a given operating reserve and lead time and the multiplication of this value by the average cost of unserved energy of the generating system. The method is illustrated in this paper by calculating the marginal outage cost profile of a small reliability test system. The effects of selected modelling assumptions and the accuracy of a number of approximate methods for calculating the marginal outage cost are also examined. © 1998 John Wiley & Sons, Ltd.     

MMALE—A Methodology for Malware Analysis in Linux Environments

In a computer environment, an operating system is prone to malware, and even the Linux operating system is not an exception. In recent years, malware has evolved, and attackers have become more qualified compared to a few years ago. Furthermore, Linux-based systems have become more attractive to cybercriminals because of the increasing use of the Linux operating system in web servers and Internet of Things (IoT) devices. Windows is the most employed OS, so most of the research efforts have been focused on its malware protection rather than on other operating systems. As a result, hundreds of research articles, documents, and methodologies dedicated to malware analysis have been reported. However, there has not been much literature concerning Linux security and protection from malware. To address all these new challenges, it is necessary to develop a methodology that can standardize the required steps to perform the malware analysis in depth. A systematic analysis process makes the difference between good and ordinary malware analyses. Additionally, a deep malware comprehension can yield a faster and much more efficient malware eradication. In order to address all mentioned challenges, this article proposed a methodology for malware analysis in the Linux operating system, which is a traditionally overlooked field compared to the other operating systems. The proposed methodology is tested by a specific Linux malware, and the obtained test results have high effectiveness in malware detection.     

A Research Methodology for Studying Complex Service Systems

This article describes a research methodology for studying problems of analysis, and control in complex service systems. The proposed methodology is based upon the total systems point of view in the sense that the physical and decision-making aspects of the service system are considered and are related to environmental factors. An example is included to illustrate the methodology as a way to approaching real problems. While field studies may be expected to present challenges because of the identification, modeling, and data requirements which will arise in actual situations, the methodological plan presented here focuses attention on these requirements as an integral part of systems analysis.     

Interruptible load considerations in well-being analysis of interconnected systems

Adequate operating reserve is required in an electric power system in order to maintain a desired level of reliability throughout a given period of time. Interruptible load can be considered as a part of the system operating reserve if it is required. The inclusion of interruptible load in the assessment of unit commitment in interconnected systems is illustrated in this paper using a well-being framework. A technique is presented to determine the well-being indices of both isolated and interconnected systems with the inclusion of interruptible load. The impacts on the required number of committed units and the well-being indices of the amount of interruptible load and the corresponding interruption time are examined in this paper by application to a hypothetical system and to the IEEE-RTS. © 1998 John Wiley & Sons, Ltd.     

EOS: enterprise operating systems

A proposal for developing an enterprise operating system (EOS) for real-time monitoring and control of enterprise operations is presented. The proposed EOS will work on top of enterprise computer operating systems to control and monitor enterprise resources instead of just computer components. A set of requirements and functionalities are first identified. Next, a survey of previous relevant works is presented and results are compared to the requirements. The architectures of the envisioned EOS are then outlined and two examples are presented to illustrate the use of the EOS. The last part draws some conclusions and gives future perspectives.     

Voltage stability constrained optimal dispatch in deregulated power systems

Voltage stability is a challenging problem for independent system operators because of less regulation in power flow patterns and more intensive use of available transmission facilities in deregulated power systems. An equitable and effective scheme for rescheduling pool generation and adjusting contract transactions is proposed in order to ensure adequate voltage stability margin (VSM). A linear optimisation methodology with the objective of minimising the social benefit loss because of generation rescheduling and transaction curtailment is formulated with consideration of the static functional operating constraints and VSM requirements with respect to normal condition and contingencies, and then solved by a linear programming technique. Since the pattern of load increase is difficult to be predicted in new market environment, the system load-ability of the locally closest bifurcation is computed and used as the VSM in the proposed method. The effectiveness of the proposed method has been verified using a modified 39-bus New England test system. A study on the effects of post-contingency corrective capability of the system on social benefit loss and voltage stability performance is also presented.     

CAMAC programming for PDP-11 computers: A modular,multiuser approach

A user-friendly CAMAC handling software concept for multitask environments is presented. The CAMAC modules are handled like all the other devices, with all the multiuser capabilities of the operating system. The concept is implemented under the RSX-11M operating system and results in effective and modular software. The system serves typically a few thousands of events in a second; the actual speed depends on many factors. In small and medium size systems the concept has several advantages; the test applications are supported mainly on macro (machine code) level and with some limitations on system level.     

Economic dispatch using an efficient real-coded genetic algorithm

The authors present a new formulation of the economic dispatch (ED) problem considering more practical constraints and nonlinear characteristics than previous works in the area. The proposed formulation includes ramp rate limits, prohibited operating zones, system spinning reserve, valve loading effects, multiple fuel options, which usually be found simultaneously in realistic power systems. To solve the ED formulation, an efficient real-coded genetic algorithm (RCGA) with arithmetic-average-bound crossover and wavelet mutation is presented. To show the effectiveness of the solution method, it is applied to five test systems having non-convex solution spaces and compared with some of the most recently published approaches. The obtained results reveal the performance of the proposed RCGA.     

A rule-based,object-oriented framework for operating flexible manufacturing systems

A methodology for operating a flexible manufacturing system (FMS) is presented which consists of a decomposition of the problem, where heuristics, rules, and simulation are integrated to make the control decisions needed for random FMS's. Expert systems are used to make operating decisions, to choose heuristics, and make operating policies. Multiple passes of discrete-event simulation are employed to evaluate decision alternatives. Object-oriented programming provides a suitable environment to implement the integrative framework     

Multi-criteria optimisation-based dynamic scheduling for controlling FMS

This study deals with controlling flexible manufacturing systems (FMS) operating in volatile production environments. Most studies that address this issue use some sort of adaptive scheduling that enables the FMS to cope with the randomness and variability efficiently. The methods presented in the literature are usually based on heuristics and use simple dispatching rules. They do not consider changing the decision criteria dynamically as the system conditions change. In contrast to previous studies, the present study focuses on developing a control mechanism for dynamic scheduling that is based on incremental optimisation. This means that each time a scheduling decision is made, the local optimisation problem is solved such that the next jobs to be processed on machines are selected. The objective function (dominant decision criterion) for this optimisation problem is selected dynamically based on production order requirements, actual shop-floor status and system priorities. The proposed multi-criteria optimisation-based dynamic scheduling methodology was evaluated and compared with some known scheduling rules/policies. The results obtained demonstrate the superiority of the suggested methodology as well as its capability to cope with a multi-criteria environment.     

An analytical framework for reliability growth of one-shot systems

In this paper, we introduce a new reliability growth methodology for one-shot systems that is applicable to the case where all corrective actions are implemented at the end of the current test phase. The methodology consists of four model equations for assessing: expected reliability, the expected number of failure modes observed in testing, the expected probability of discovering new failure modes, and the expected portion of system unreliability associated with repeat failure modes. These model equations provide an analytical framework for which reliability practitioners can estimate reliability improvement, address goodness-of-fit concerns, quantify programmatic risk, and assess reliability maturity of one-shot systems. A numerical example is given to illustrate the value and utility of the presented approach. This methodology is useful to program managers and reliability practitioners interested in applying the techniques above in their reliability growth program.     

Well-being analysis for composite generation and transmission systems based on pattern recognition techniques

A new methodology to evaluate well-being indices for a composite generation and transmission system, based on non-sequential Monte Carlo simulation and pattern recognition techniques, is presented. To classify the success operating states into healthy and marginal, an artificial neural network based on group method data handling techniques is used to capture the patterns of these state classes, during the beginning of the simulation process. The idea is to provide the simulation process with an intelligent memory, based on polynomial parameters, to speed up the evaluation of the operating states. The proposed methodology is applied to the IEEE reliability test system (IEEE-RTS), to the IEEE-RTS-96 and to a configuration of the Brazilian South-Southeastern system.     

System dynamic performance: Robust stabilization of controls over a range of operating conditions

This paper presents a novel approach to analyse stability robustness of controls in power systems over a range of operating conditions. The controls considered include exciters, power system stabilizers, and governors. The analytical basis for the approach is presented. The robustness framework for power systems is formulated. Numerical results for a sample test system are obtained and compared with those obtained by conventional techniques.     

Theory and laboratory demonstrations on the use of a nematic liquid-crystal phase modulator for controlled turbulence generation and adaptive optics

We discuss the use of liquid-crystal phase modulators (LCPM's) both as a repeatable disturbance test source and as an adaptive optics corrector. LCPM's have the potential to induce controlled, repeatable, dynamic aberrations into optical systems at low cost, low complexity, and high flexibility. Because they are programmable and can be operated as transmissive elements, they can easily be inserted into the optical path of an adaptive optics system and used to generate a disturbance test source. When used as wave-front correctors they act as a piston-only segmented mirror and have a number of advantages. These include low operating power requirements, relatively low cost, and compact size. Laboratory experiments with a Meadowlark LCPM are presented. We first describe use of the LCPM as a repeatable disturbance generator for testing adaptive optics systems. We then describe a closed-loop adaptive optics system using the LCPM as the wave-front corrector. The adaptive optics system includes a Shack-Hartmann wave-front sensor operated with a zonal control algorithm.     

Loading and control policies for a flexible manufacturing system

An experimental investigation of operating strategies for a computer-controlled flexible manufacturing system is reported. The system is a real one, consisting of nine machines, an inspection station and a centralized queueing area—all interconnected by an automatic material-handling mechanism. The operating strategies considered involve policies for loading (allocating operations and tooling to machines) and real-time flow control. A detailed simulation was employed to test alternatives. The results are different from those of classical job shop scheduling studies, showing the dependence of system performance on the loading and control strategies chosen to operate this flexible manufacturing system. Loading and control methods are defined that significantly improve the system's production rate when compared to methods which were previously applied to the system. Finally, some conclusions are presented concerning the control of these automated systems.     

A power quality monitoring system: a case study in DSP-basedsolutions for power electronics

Programmable digital signal processors (DSPs) are emerging as the processors of choice in monitoring and control of high-end power electronics systems. This paper adopts a case study approach to illustrate a development methodology for DSP-based solutions. The unique features of DSP chips that make them ideal for real-time applications are highlighted. Power electronics systems where DSPs have been used are indicated. A case study in which a DSP-based solution was developed for a power quality monitoring application is presented. Through the case study, the issues involved in adopting a system architecture, selecting a DSP, and developing software for an application are discussed. The methodology described in this paper presents broad guidelines which can be intelligently applied to develop DSP-based solutions to meet specific requirements     

A Methodology to Describe Operating Characteristics of Assembly Systems

A methodology for describing the operating characteristics of low volume (small lot) assembly systems is presented in this paper. Analytical models indicate that the deterministic assembly system is equivalent to a flow shop. A numerical approximation technique is applied to develop measures of performance for probabilistic systems. Results include identification of metering stations which control work flow and of potential inconsistencies between productivity and flow-time objectives. The impacts of scheduling policies that determine the intervals at which “mainframes” are launched into assembly, and the due dates for parts, are investigated. The strategy of setting due dates for parts is shown to have a significant influence over work-in-process levels and schedule performance in probabilistic systems.     

Engineering system co-design with limited plant redesign

Rather than designing engineering systems from the ground up, engineers often redesign strategic portions of existing systems to accommodate emerging needs. In the redesign of mechatronic systems, engineers typically seek to meet the requirements of a new application via control redesign only, but this is often insufficient and physical system (plant) design changes must be explored. Here, an integrated approach is presented for the redesign of mechatronic systems involving partial plant redesign that avoids costly complete redesign. Candidate plant modifications are identified using sensitivity analysis, and then an optimization problem is solved that minimizes redesign cost while satisfying system requirements. This formal methodology for Plant-Limited Co-Design (PLCD) is demonstrated using a robotic manipulator design problem. The PLCD result costs significantly less than the full redesign, and parametric studies illustrate the tradeoff between redesign cost and performance. It is shown that the proposed sensitivity analysis results in the lowest cost limited redesign.     

Analysis and solution to the single-level batch production smoothing problem

Many companies use mixed-model production systems running under the Just-in-Time philosophy in order to efficiently meet customer demands for a variety of products. Such systems require demand be stable and production sequence be leveled. The production smoothing problem aims at finding level schedules in which the appearances of products are dispersed over the horizon as uniformly as possible. In this paper, the production smoothing problem is extended to a more general manufacturing environment where a single machine can be identified as either the final or the bottleneck stage of the system and products may have arbitrary non-zero setup and processing time requirements on this single machine. An optimization model is built for the problem and a two phase solution methodology is developed. The first phase problem is shown to be NP-hard and a parametric heuristic procedure is proposed for its solution. In contrast, the second phase problem is shown to be efficiently solvable and currently available solution methods are adopted from the literature. A computational study is designed to test the proposed two phase solution methodology and also the parametric heuristic procedure. Computational results show that the proposed two phase solution methodology enables effective and efficient control of the studied manufacturing system, and the heuristic procedure developed for the first phase problem is time efficient and promises near optimal solutions for a variety of test instances.