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Reliability assessment for electrical power generation system based on advanced Markov process combined with blocks diagram
Faculty
Engineering
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohammed Abdelfattah Mohamed Farahat
Staff Zu Site
Abstract In Staff Site
Journal:
International Journal of Electrical and Computer Engineering (IJECE) International Journal of Electrical and Computer Engineering (IJECE)
Volume:
Keywords :
Reliability assessment , electrical power generation system
Abstract:
This paper presents the power generation system reliability assessment using an advanced Markov process combined with blocks diagram technique. The effectiveness of the suggested methodology is based on HL-I of IEEE_EPS_24_bus. The proposed method achieved the generation reliability and availability of an electrical power system using the Markov chain which based on the operational transition from state to state which represented in matrix. The proposed methodology has been presented for reliability performance evaluation of IEEE_EPS_24_bus. MATLAB code is developed using Markov chain construction. The transition between probability states is represented using changing the failure and repair rates. The reduced number of generation system are used with Markov process to assess the availability, unavailability, and reliability for the generation system. Additionally, the proposed technique calculates the frequency, time duration of states, the probability of generation capacity state which get out of service or remained in service for each state of failure, and reliability indices. A considerable improvement in reliability indices is found with using blocks diagram technique which is used to reduce the infinity number of transition states and assess the system reliability. The proposed technique succeeded at achieving accurate and faster reliability for the power system.
Author Related Publications
Mohammed Abdelfattah Mohamed Farahat, "A New Approach for Short-Term Load Forecasting Using Curve Fitting Prediction Optimized by Genetic Algorithms", IEEE, 2010
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Mohammed Abdelfattah Mohamed Farahat, "Short-Term Load Forecasting Using Curve Fitting Prediction Optimized by Genetic Algorithms", SAP journals, 2012
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Mohammed Abdelfattah Mohamed Farahat, "The Using of Curve Fitting Prediction Optimized by Genetic Algorithms for Short-Term Load Forecasting", Praise Worthy Prize, 2012
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Mohammed Abdelfattah Mohamed Farahat, "A New Artificial Neural Network Approach with Selected Inputs for Short Term Electric Load Forecasting", Praise Worthy Prize, 2008
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Mohammed Abdelfattah Mohamed Farahat, "Factors Affecting the Life Time of the Electric Joints", Cairo University, 2010
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Department Related Publications
Hytham Saad Mohamed Ramadan, "Optimal blade pitch control for enhancing the dynamic performance of wind power plants via metaheuristic optimisers", IET Electric Power Applications, 2017
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Mohammed Salah Aldin Abdelsadek, "A new fault type identification technique based on fault generated high frequency transient voltage signals", JEE, 2012
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Attia Abdelaziz Hussien Ali, "Capacitor allocations in radial distribution networks using cuckoo search algorithm", The Institution of Engineering and Technology, 2014
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Mohamed Abdelfattah Hessien Anany Refaee, "Steady State Modeling and ANFIS Based Analysis of Doubly – Fed Induction Generator", Michael Faraday IET International Summit–2015, MFIIS(2015), 2015
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Ahmed Mohamed Othman Abdelmaksoud, "Particle Swarm Optimization and Genetic Algorithm for Convex and Non-convex ED", International Review of Electrical Engineering (IREE), 2014
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