Generator Maintenance Scheduling Models in Power Systems. Integrated Cost Models for Generator Maintenance Strategy under Market Environment.
AuthorAl-Arfaj, Khalid A.
SupervisorDahal, Keshav P.
Generator maintenance scheduling
Genetic algorithm (GA)
Analytical Hierarchy Process (AHP)
Reliability Centred Maintenance (RCM)
Rights© 2009 Al-Arfaj, K. A. This work is licensed under a Creative Commons Attribution-Non-Commercial-Share-Alike License (http://creativecommons.org/licenses/by-nc-nd/2.0/uk).
InstitutionUniversity of Bradford
DepartmentDepartment of Computing
MetadataShow full item record
AbstractChange from a regulated to deregulated structure means that, the centralized maintenance system is not valid any more. In the surveyed published literature, there is not a single model which incorporates all maintenance cost components to analyze the effect of different maintenance strategies for generator companies (GENCOs). The work enclosed in this thesis demonstrates that there is a considerable requirement for accurately modelling cost components of the maintenance model, to be used in maintenance scheduling for deregulated power system, in order to attain a superior schedule with major financial and operational impact. This research investigates and models most cost factors that affect the maintenance activities of the deregulated GENCOs, and demonstrates the utilization of the developed cost models in maintenance scheduling. It also presents the data gathering process for the developed maintenance cost model. A generator maintenance scheduling model that considers direct and indirect maintenance costs, opportunity costs (i.e. loss of customer goodwill), effective maintenance strategies, failures, and interruptions is developed. A Genetic Algorithm (GA) based approach is employed to achieve maintenance schedules to various generators maintenance scenarios. An Analytical Hierarchy Process (AHP) approach is proposed for modelling customer goodwill. The maintenance model was redeveloped under the Reliability Centred Maintenance (RCM) strategy to analyze the effect of a maintenance strategy on maintenance costs. Case studies are presented to demonstrate the utilisation of the developed models.The investigation shows that the market prices, opportunity costs and maintenance strategy have an effect on the final maintenance schedule. The research demonstrates that the cost components are critical factors to achieve an effective maintenance schedule, and they must be considered and carefully modelled in order to reflect more realistic situation for maintenance scheduling of generator units in deregulation environment.
Showing items related by title, author, creator and subject.
A Fuzzy Criticality Assessment System of Process Equipment for Optimized Maintenance Management.Qi, Hong Sheng; Alzaabi, R.N.; Wood, Alastair S.; Jani, M. (2015-01)In modern chemical plants, it is essential to establish an effective maintenance strategy which will deliver ﬁnancially driven results at optimised conditions, that is, minimum cost and time, by means of a criticality review of equipment in maintenance. In this article, a fuzzy logic-based criticality assessment system (FCAS) for the management of a local company’s equipment maintenance is introduced. This fuzzy system is shown to improve the conventional crisp criticality assessment system (CCAS). Results from case studies show that not only can the fuzzy logic-based system do what the conventional crisp system does but also it can output more criticality classiﬁcations with an improved reliability and a greater number of different ratings that account for fuzziness and individual voice of the decision-makers.
Fuzzy criticality assessment for process equipments maintenanceQi, Hong Sheng; Liu, Q.; Wood, Alastair S.; Alzaabi, R.N. (2012)Criticality-based maintenance (CBM) is a prioritized approach to the maintenance of (industrial) process equipment. CBM requires personnel with a thorough knowledge of the process/equipment under scrutiny. In this paper a criticality assessment system that is implemented by a local company (which represents the expertise and knowledge of the company experts) is reviewed and fuzzy logic theory is applied to improve the system's capability and reliability. The quality of the fuzzy system is evaluated based on several case studies. The results show that the fuzzy logic based system does not only what the conventional system does, but also outperforms in terms of reliability and has a unique ranking capability.
Generator maintenance scheduling in power systems using metaheuristic-based hybrid approachesDahal, Keshav P.; Chakpitak, N. (2007)The effective maintenance scheduling of power system generators is very important for the economical and reliable operation of a power system. This represents a tough scheduling problem which continues to present a challenge for efficient optimization solution techniques. This paper presents the application of metaheuristic approaches, such as a genetic algorithm (GA), simulated annealing (SA) and their hybrid for generator maintenance scheduling (GMS) in power systems using an integer representation. This paper mainly focuses on the application of GA/SA and GA/SA/heuristic hybrid approaches. GA/SA hybrid uses the probabilistic acceptance criterion of SA within the GA framework. GA/SA/heuristic hybrid combines heuristic approaches within the GA/SA hybrid to seed the initial population. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the metaheuristic approaches and their hybrid for the test case study are discussed. The results obtained are promising and show that the hybrid approaches are less sensitive to the variations of technique parameters and offer an effective alternative for solving the generator maintenance scheduling problem.