Standby Unit Research Articles

A dual-standby power source configuration scheme for micro grid in Pelagic Island

Realizing clean energy supply is important for the sustainable development of pelagic island. The volatility and randomness features of renewable energy generation may reduce power supply reliability, thus backup units is necessary in micro-grid in pelagic island. This paper proposed a dual-standby configuration scheme based on Sequence Operation Theory to achieve reliable power standby. Firstly, characteristics of standby units, micro gas turbine and diesel generator, are analyzed. Next, the probability distribution function models of wind, photovoltaic and load demand in pelagic island are established, and the reliability index of power shortage probability is calculated by Sequence Operation Theory. Then, the two-stage dual-standby control scheme to make full use of the complementary standby units is introduced and object function to minimize equivalent annual cost on the premise of satisfying probabilistic reliability index is modeled. Hybrid integer particle swarm algorithm is used to solve the problem. Finally, the proposed model for dual-standby configuration is applied to a pelagic island. The simulation results show that the proposed method can meet the load demand in both daily and extreme weather and achieve superior economy.

Vacation Policy for k-out-of-n Redundant System with Reboot Delay

Redundancy is a well-known concept for system resilience; k-out-of-n redundancy stipulates that a minimum number of functional components must be present for the system to function. Introducing a reboot delay acknowledges the temporal complexities of system recovery after a failure. A dynamic component is added by the vacation policy, which introduces strategic downtime for system components. This work predicts the performance measures of a multi-state system consisting of two subsystems A and B. Subsystem A follows the k-out-of-n: F policy and subsystem B has m working units and s warm standby units. The system is under the consideration of a single unreliable repairman who may go allow for vacation. There are two possibilities for a repairman’s vacation: if the system failed and the repairman is on vacation, in that case, if the repairman immediately returns from vacation, he/ she repairs the system but if the repairman does not return immediately from vacation, then the system takes a reboot action and when the repairman available, he/ she repairs the system. Failure and repair time of the units are expected to pursue an exponential distribution. In addition, the vacation time and reboot time regarding the failure of the units also pursue an exponential distribution. The concept of reboot and repairman’s vacation are incorporated to make the model more practical and versatile. The expressions for several performance measures such as availability, reliability, and MTTF are obtained with the help of the Markov process. Likewise, sensitivity analysis is done to study the impact of various parameters on system performance measures. The results are explained by taking numerical illustrations.

Time-domain computation of the reliability of standby systems with and without priority under general repair

In this paper, we consider a two-unit, non-identical cold standby system under general repair with or without priority. In the prioritized case, one unit in the system is designated to serve as standby only, that is, the standby unit is only utilized when the main unit has failed and is being repaired, whereas in the non-prioritized case, both units serve alternately as standby with each unit being put to standby mode when its repair is complete. The effect of each repair is modelled by a degree θ, 0≤θ≤1, where θ=0 means full repair (or full replacement) and θ=1 means minimal repair. For these cases, and for arbitrary distributions of the lifetimes and repair times of the units in the system, we obtain the reliability function in the time domain as opposed to the Laplace domain. Our functions utilize results from classical and generalized renewal theory results. We validated our formulas on various in-house standby configurations, as well as standby configurations occurring in coolant systems of nuclear power plants.

Exploring the synergistic effects of warm and cold standby units in availability modelling and assessment of complex series-parallel systems

Exploring the synergistic effects of warm and cold standby units in availability modelling and assessment of complex series-parallel systems

Understanding the Reliability of the Complex System Having Two Standby Units: A Transdisciplinary Approach

The main objective of this study is to thoroughly investigate the reliability of a complex system that consists of four components and two standby units. The complicated system is modeled using the Markov technique. The study formulates differential equations and solves them using a matrix method with the assistance of a computer program. Statistical methods, such as correlation and regression, are applied using SPSS software to understand the relationship between time and the reliability of this complex system. A statistical model is utilized to determine the system's reliability, identify potentially faulty components, and prioritize the protection of the most critical elements. The presentation of significant findings involves conducting a comprehensive analysis using tables and graphs created with Python programming language. The outcomes of this study aim to assist in identifying crucial units in various process industries, thereby facilitating the establishment of effective management policies and strategies for the optimal operation of complex and large-scale systems in the industry. This paper incorporates numerous disciplines, viewpoints, and methodologies to examine and enhance reliability in process industries. Reliability can indeed benefit from a matrix approach, which can be considered transdisciplinary. This study serves as both an introductory guide to reliability analysis for novice researchers and a survey highlighting the latest advancements in the field for experienced researchers.

Redundancy Optimization for a System Comprising One Operative Unit and N Warm Standby Units with Switching Time

Redundancy Optimization for a System Comprising One Operative Unit and N Warm Standby Units with Switching Time

Study on the Maximum Outgoing Line Count of 750 kV Substations and Exploration of a Bus Short-circuit Current Suppression Method

With the development and construction of new power systems, the power grid structure is becoming increasingly interconnected, and the issue of short-circuiting currents in UHV systems will gradually manifest over the next five years. Existing measures for short-circuit current control typically involve using standby units, lines, and main transformers. However, conventional measures are gradually unable to meet the control requirements, necessitating strict control of the network topology during the planning phase and the exploration of new technologies and methods to keep pace with the evolving era. This paper studies the maximum outgoing line count of 750 kV substations, providing theoretical references applicable to practical operations for planning departments. A conceptual method based on fast-switching technology to suppress the current during a short circuit at the 750 kV voltage level is proposed, establishing the groundwork for the practical implementation of high-speed switching technology in the 750 kV voltage-level power grid.

Post-traumatic stress in war veterans and secondary traumatic stress among parents of war veterans five years after the 2014 Israel-Gaza military conflict

ABSTRACT Secondary traumatic stress (STS) has been studied in therapists, spouses, and mainly in children of traumatised individuals. To date, the relationship between children’s posttraumatic stress disorder (PTSD) symptoms and their parents’ mental health outcomes have been understudied, and specifically, long term STS symptoms of parents of war veterans were not investigated. The current study examined PTSD symptoms among veterans of the 2014 Israel-Gaza war and STS among their parents, five years after the war. The control group consisted of veterans from combat military units who were on active duty at the time of the war but did not actively participate in the war (stand-by units) – providing a natural experiment condition. We found that PTSD symptoms were almost twice as high in the directly active war veterans (DAV, N = 32) group compared to the indirectly active war veterans (IAV, N = 26) group. Results showed that mothers had higher STS symptoms in general, and DAV PTSD symptoms correlated with their fathers STS symptoms. The current study provides novel evidence for: (a) subclinical PTSD symptoms in war veterans 5 years after the war, and (b) transmission of trauma from war veterans to their parents. The overall negative effect of sending a child to war on the parents are also discussed.

Component Criticality Analysis for Improved Ship Machinery Reliability

Redundancy in ship systems is provided to ensure operational resilience through equipment backups, which ensure system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems; hence, it is provided with a good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired blackouts is common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensuring a more robust maintenance and support platform for efficient ship operations. In this regard, a hybrid reliability and fault detection analysis using DFTA and ANN was conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of four marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate an overall low system reliability of less than 70 percent within the first 24 of the 78 operational months. Component criticality-using reliability importance measures obtained through DFTA was used to identify all components with more than a 40 percent contribution to subsystem failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Network classification. The ANN has identified a failure pattern threshold at about 200 kva, which can be attributed to overheating, hence establishing a link between component failure and generator performance.

Optimal switching and condition-based maintenance of cold standby systems subject to competitive failure and imperfect switchover

Cold standby redundant structures can improve system reliability and availability but are subjected to internal degradation and external shocks during operation. Thus, the switching process in a standby system is prone to failures. This study investigates the optimal switching and condition-based maintenance (CBM) decision of a two-unit cold standby system subject to mutually dependent competitive failure processes with an imperfect switchover. First, periodic switching and offline CBM policies under imperfect switchover are proposed; second, the reliability models of competitive failure—between soft failure caused by system degradation subject to nonfatal shock and hard failure caused by fatal shock—are established. An iterative model of the system state probability distribution is subsequently derived by analysing the characteristics of state transitions in alternate use and maintenance of the active and standby units. An analytical decision model is also established to minimise the average cost rate in a finite horizon to obtain the optimal switching period and maintenance threshold. Finally, a case study of a coal mine main ventilator system validates the proposed model.

Novel Analysis between Two-Unit Hot and Cold Standby Redundant Systems with Varied Demand

Decisive applications, such as control systems and aerial navigation, require a standby system to meet stringent safety, availability, and reliability. The paper evaluates the availability, reliability, and other measures of system effectiveness for two stochastic models in a symmetrical way with varying demand: Model 1 (a two-unit cold standby system) and Model 2 (a two-unit hot standby system). In Model 1, the standby unit needs to be activated before it may begin to function; in Model 2, the standby unit is always operational unless it fails. The current study demonstrates that the hot standby system is more expensive than the cold standby system under two circumstances: a decrease in demand or the hot standby unit’s failure rate exceeding a predetermined threshold. The cold standby system’s activation time is at most a certain threshold, and turning both units on at once is necessary to handle the increasing demand. In that case, the hot standby will be more expensive than the cold standby system. The authors used semi-Markov and regenerative point techniques to analyze both models. They collected actual data from a cable manufacturing plant to illustrate the findings. Plotting several graphs and obtaining cut-off points make it easier to choose the standby to employ.

Mean residual lifetime assessment approach for a multi-state standby system

In this paper, a new MRL assessment approach for a multi-state standby system is considered. The three-state system is backed up with a binary cold standby unit. Given that the system is at a specific state at time t, obtaining the MRL is worth considering in conducting the maintenance and repair plans of the system. For different degradation rates and time points, MRL results are examined. An HCTMP is considered for the degradation. Therefore, when the system is observed to be at its perfect state, the MRL decrease with an increase in all the failure rates of the system. However, when the system is observed to be at its partial state, the MRL is not affected by the increase in the failure rate pertained to the perfect state. The MRL when the system has known to be failed before time t and backed up with the standby unit increases with the time increase whereas the MRL when the system is at its perfect(or partial) state is constant when time increases. Moreover, cost evaluation of the system is analyzed. The results are supported with numerical examples and graphical representations.

Reliability and Cost-Benefit Efficient in a Two-Dissimilar- Unit with Warm Unit Standby Case Subject to Arbitrary Repair and Replacement

Reliability and Cost-Benefit Efficient in a Two-Dissimilar- Unit with Warm Unit Standby Case Subject to Arbitrary Repair and Replacement

Reliability analysis of N-policy vacation based FTC system subject to standby switching failures

The paper is aimed to investigate the reliability metrics of a multi-unit fault-tolerant control (FTC) system wherein the units are subject to failure and those are repairable by two heterogeneous servers. Server 1 remains permanently available for essential service of failed units, whereas server 2 goes on vacation and renders service based on the N-policy threshold, which may also provide optional and essential services. Server 1 may break down at a steady rate during its servicing period but immediately gets repaired and resume servicing the failed units. When the working unit fails, the available warm standby unit holds responsibility for the smooth operation of the system. The transition of standby units to operational mode may be unsuccessful with switching failure probability. We develop a Markovian model to obtain the steady-state probabilities. We explore computational and sensitivity analysis of different performance measures for various variability of the parameters

Exploring the Synergistic Effects of Warm and Cold Standby Units in Availability Modeling and Assessment of Complex Series-Parallel Systems

Exploring the Synergistic Effects of Warm and Cold Standby Units in Availability Modeling and Assessment of Complex Series-Parallel Systems

Comparative analysis between serial systems with cold standby units

Comparative analysis between serial systems with cold standby units

A new dynamic model to optimize the reliability of the series-parallel systems under warm standby components

<p style='text-indent:20px;'>Redundancy allocation problem (RAP) is a common technique for increasing the reliability of systems. In this paper, a new model for the RAP is introduced that takes into account the warm standby and mixed strategy, the model dynamics, and the type of the strategy in redundancy allocation problems. A recursive formula is first obtained for the reliability function in the dynamic warm standby and mixed redundancy strategies that leverages the success mode analysis and works for any arbitrary failure-time distribution. Failure rates for warm standby units change before and after their replacement with a damaged unit, and, therefore, the reliability function in warm standby varies with time (i.e., the model is dynamic). Although dynamic models are commonplace in practice, they are more challenging to assess than static models, which have been mainly considered in the literature. An optimization problem is then formulated to select the best redundancy strategy and redundancy levels. Genetic algorithm and particle swarm optimization are leveraged to solve the problem. Finally, the efficiency of the presented method is verified through a numerical example. The experimental results verify that the proposed model for RAP significantly improves the system reliability, which can be of vital importance for system designers.</p>

Reliability prediction used dynamic Bayesian networks for redundant system with time‐lag correlation

AbstractIn the reliability prediction process of a redundant system, active units and standby units are assumed independent generally. Due to the interaction among units, failure of the active unit gives the standby unit a potential interior shock, then the standby unit fails after a period of operation. Therefore, the correlation between the active unit and the standby unit is triggered by the failure of the active unit and also has time‐lag. In this paper, a correlation estimated method with two parameters is proposed based on cross‐correlation analysis, where the two parameters are time‐lag interval and time‐lag correlation coefficient, the discriminant conditions of independent, simultaneous correlation and time‐lag correlation are given. Subsequently, the Conditional Probability Table (CPT) of Dynamic Bayesian Network (DBN) is updated by adding time‐lag intervals and time‐lag correlation coefficients. Then, DBN is optimized into Time‐lag Dynamic Bayesian Network (TDBN). Meanwhile, the modeling process and calculated method of TDBN are given. To reduce the complexity of TDBN, the maximum time‐lag correlation coefficient and the time‐lag interval corresponding are regarded as the main parameters to estimate time‐lag correlation. Finally, through the simulation analysis and the case of Chinese train control system (CTCS‐3), it could be seen that the reliability prediction of TDBN is more accurate than DBN, TDBN improves the reliability prediction accuracy of train and driver interface module to 0.8135 either.

Reliability analysis of captive power plant system where the working of standby unit depends on connecting unit

Captive power plants usually operate parallel to the gridline to overcome the losses associated with power failures. While the connectivity of the power plant and gridline highly depends on the functioning of the electrical breaker. This study reveals the importance of connecting device breakers in a captive power plant to operate the system at full or reduced capacity and safer it from reverse feeding. Using semi-Markov processes reliability model is developed for steam turbine generators interconnected with gridline by an electric breaker. The expressions are formed for reliability measures like mean time to system failure, availability, busy period, and profit using regenerative point techniques. Also, these measures are evaluated numerically using an actual dataset belonging to a captive power plant. Graphical plotting shows a decline in profit with increasing the failure rates of turbine generators, gridline, and working probability of breaker. The revenue per unit uptime of the system is forecasted to get productive profit with different failure rates of the power generator.

Maintenance modeling for balanced systems subject to two competing failure modes

Many 1-out-of n pairs: G balanced systems experience two competing failure processes, but the complex failure mechanisms present challenging issues in maintenance modeling. This paper formulates a maintenance policy optimization model for balanced systems composed of multiple functionally-exchangeable units. A unit may fail due to the hard failure caused by a self-failure mechanism, or shock failures due to abrupt or sudden stress from the external environment, whichever occurs first. Once a unit fails, the symmetric component stops working immediately to be a standby unit to keep the system balanced. When there are at least two standby units in the balanced system, dynamically reallocating the two units on positions is a feasible way to increase the probability of the system running. Moreover, the repair and replacement actions are properly performed to avoid the system being out of balance. More units on operation will increase the system operational cost, but fewer units may induce system failure. Thus, there is a trade-off between the number of working units and the system average maintenance cost. The objective of this work is to find the optimal number of operating units to minimize the maintenance cost per unit time. An illustrative example is used to demonstrate the effectiveness of the proposed policy, where a sensitivity analysis illustrates how the cost parameters affect the system maintenance cost.