Optimization and Implementation of Maintenance Schedule of Power Systems

Ph.DDOCTOR OF PHILOSOPH

Analysis of Subsea Energy Supply Systems for Improved Maintenance Using ANFIS and TOPSIS

The maintenance plan for the subsea energy supply system during the operation was optimized by firstly training the Adaptive Neuro-Fuzzy Inference System (ANFIS) model with historical data of process variables of the system such as voltage, current, power, and pressure in MATLAB software and then predicting the optimum output of the process using the trained model, which showed a good prediction of operational data after two cycles of computational analysis. The outputs from the trained model, coupled with expert opinions on historical data, were used to develop a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria algorithm to select the best maintenance strategy. The reliability-centred maintenance, with a performance score of 0.811, ranked best amongst the maintenance strategies under the studied scenario. The result shows that the procedure could be applied in condition monitoring of operational subsea energy supply systems to predict impending faults through deviation error and prevent failure by the application of an appropriate maintenance strategy. Keywords: ANFIS, TOPSIS, Maintenance plan, Fault prediction and Subsea power supply systems DOI: 10.7176/ISDE/12-2-02 Publication date: April 30th 202

Accumulator Charging Control with Piezoelectric Based on Fuzzy Algorithm Scheduling

Battery accumulator charging with pizoelectric takes considerable long time so that an energy harvester is needed by using in this study LTC 3588 circuit. However, by using the energy harvester, the pizoelectric cannot be used to charge 12 volt battery, thus a boost converter is needed. The output voltage is too small to increase by using the boost converter so that the output from the energy converter is used to charge four AA batteries. After the voltage of the four AA batteries as much as 4.7 volt is increased by using the boost converter, the batteries can be used to charge accumulator battery 12 volt. To charge the battery to accumulator, scheduling algorithm planted in microcontroller arduino is needed. By using the scheduling algorithm with fuzzy logic in the arduino microcontroller, the microcontroller is able to control schedule of accumulatro battery charging

Fuzzy Logic Based Smart Grid for Power System Application

Smart grid manages the innovation for modernizing power flow frameworks by exploitation circulated and PC based remote detecting, administration and robotization, and two-way correspondences. Potential edges of the innovation region unit that the great grid's focal administration can right now have the capacity to administration and work a few remote station, streamline the general quality use and operational speedily. Amid this paper, there is an inventive methodology for the great framework to handle vulnerability emerging from condition perception and support of force plant. The mentality utilizes optional versatile support advisor and a framework upkeep analyser for outlining/executing streamlined condition-based protection happenings, and together handles [2] operational dissimilarities happening in every station. The framework upkeep enhancer creates the starting support anticipates each station with multi objective enhancement by taking into consideration just the look or normal operational conditions.[2] Amid methodology, the station can experience ageing, administration movements, moving climate and payload components, and shaky estimations. Living on every host station, the upkeep advisor can survey the capacity of beginning support arranges; and gauge the obligation changes created by effective dissimilarities on the substation utilizing a hierarchal fuzzy framework. The consultant determination caution the preservation streamlining agent on regardless of whether a reoptimization of its support exercises should be started for meeting the general framework dependability request.[7]. Mean time between failure (MTBF) and mean time to failure (MTTF) are studied in this thesis and fuzzy logic is generate to find he MTTF and MTBF, such that the components that present in the grid may be maintained from time to time without any failure in the system

Modular reactors: What can we learn from modular industrial plants and off site construction research

New modular factory-built methodologies implemented in the construction and industrial plant industries may bring down costs for modular reactors. A factory-built environment brings about benefits such as; improved equipment, tools, quality, shift patterns, training, continuous improvement learning, environmental control, standardisation, parallel working, the use of commercial off shelf equipment and much of the commissioning can be completed before leaving the factory. All these benefits combine to reduce build schedules, increase certainty, reduce risk and make financing easier and cheaper.Currently, the construction and industrial chemical plant industries have implemented successful modular design and construction techniques. Therefore, the objectives of this paper are to understand and analyse the state of the art research in these industries through a systematic literature review. The research can then be assessed and applied to modular reactors.The literature review highlighted analysis methods that may prove to be useful. These include; modularisation decision tools, stakeholder analysis, schedule, supply chain, logistics, module design tools and construction site planning. Applicable research was highlighted for further work exploration for designers to assess, develop and efficiently design their modular reactors

Maintenance decision making

In any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on their our quality and experience, making the complex systems management planning, particularly in maintenance planning, a very difficult and subjective process, by tendentially diverting analysts from the main decisional aspects. In order to overcome these difficulties and subjectivities, this paper purposes a set of methodological guidelines based on fuzzy set theory to be applied in the planning processes, leading to optimized and more realistic results

A review of preventative maintenance on South African electricity sector

Abstract: Regardless of the overhaul outages planned with the aim of preventing failures on the energy plants in South Africa, it is witnessed not to be effective based on the production ratio outcomes. The production ratio as per the South African power enterprise is 80:10:10. The ratio is based on 80 % availability, a fixed 10% planned maintenance and 10 % unplanned maintenance. Consequently, the concept of preventative maintenance has become a buzz phrase amongst scholars and industry practitioners, even though, preventative maintenance is attaining a higher level of significance in well developed countries, such as America and China due to its ability to smoothening the energy sector. In Africa, particularly in South Africa the integration and adoption of the concept of preventative maintenance is phasing challenges. To date, over the past decades several studies have been led to investigate the benefit of preventative maintenance implementation in the energy sector at global level. However, very few investigative studies concerning the implementation and adoption of preventative maintenance in the South African energy generation sources have been conducted, hence the overall objective of this paper is to fill this gap by means of critically analyzing studies that were conducted or developed in the field of preventive maintenance over the past two decades. The outcome of the analysis of the existing literature on preventative maintenance clearly illustrates that there are flaws in the current body of knowledge related to a lack of sufficient studies in the context of South African electricity sector

Establishment of a novel predictive reliability assessment strategy for ship machinery

There is no doubt that recent years, maritime industry is moving forward to novel and sophisticated inspection and maintenance practices. Nowadays maintenance is encountered as an operational method, which can be employed both as a profit generating process and a cost reduction budget centre through an enhanced Operation and Maintenance (O&M) strategy. In the first place, a flexible framework to be applicable on complex system level of machinery can be introduced towards ship maintenance scheduling of systems, subsystems and components.;This holistic inspection and maintenance notion should be implemented by integrating different strategies, methodologies, technologies and tools, suitably selected by fulfilling the requirements of the selected ship systems. In this thesis, an innovative maintenance strategy for ship machinery is proposed, namely the Probabilistic Machinery Reliability Assessment (PMRA) strategy focusing towards the reliability and safety enhancement of main systems, subsystems and maintainable units and components.;In this respect, the combination of a data mining method (k-means), the manufacturer safety aspects, the dynamic state modelling (Markov Chains), the probabilistic predictive reliability assessment (Bayesian Belief Networks) and the qualitative decision making (Failure Modes and Effects Analysis) is employed encompassing the benefits of qualitative and quantitative reliability assessment. PMRA has been clearly demonstrated in two case studies applied on offshore platform oil and gas and selected ship machinery.;The results are used to identify the most unreliability systems, subsystems and components, while advising suitable practical inspection and maintenance activities. The proposed PMRA strategy is also tested in a flexible sensitivity analysis scheme.There is no doubt that recent years, maritime industry is moving forward to novel and sophisticated inspection and maintenance practices. Nowadays maintenance is encountered as an operational method, which can be employed both as a profit generating process and a cost reduction budget centre through an enhanced Operation and Maintenance (O&M) strategy. In the first place, a flexible framework to be applicable on complex system level of machinery can be introduced towards ship maintenance scheduling of systems, subsystems and components.;This holistic inspection and maintenance notion should be implemented by integrating different strategies, methodologies, technologies and tools, suitably selected by fulfilling the requirements of the selected ship systems. In this thesis, an innovative maintenance strategy for ship machinery is proposed, namely the Probabilistic Machinery Reliability Assessment (PMRA) strategy focusing towards the reliability and safety enhancement of main systems, subsystems and maintainable units and components.;In this respect, the combination of a data mining method (k-means), the manufacturer safety aspects, the dynamic state modelling (Markov Chains), the probabilistic predictive reliability assessment (Bayesian Belief Networks) and the qualitative decision making (Failure Modes and Effects Analysis) is employed encompassing the benefits of qualitative and quantitative reliability assessment. PMRA has been clearly demonstrated in two case studies applied on offshore platform oil and gas and selected ship machinery.;The results are used to identify the most unreliability systems, subsystems and components, while advising suitable practical inspection and maintenance activities. The proposed PMRA strategy is also tested in a flexible sensitivity analysis scheme

Development of an advanced artificial intelligent reliability analysis tool to enhance ship operations and maintenance activities

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