Markov State Model for Optimization of Maintenance and Renewal of Hydro Power Components

Welte, Thomas Michael; Vatn, Jørn; Heggset, J.

doi:10.1109/pmaps.2006.360311

Cited by 35 publications

(22 citation statements)

References 7 publications

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“…The deterioration process often accelerates as the operating time increases until reaching the remaining useful life. The expectation of the distribution of states in degradation prediction models presents features similar to those of exponential distributions [71]. The maximum displacement measurements of the Corumbá IV HPP by sensors follow this exponential behavior, which was used to calculate the sojourn times for the transition probabilities in the Markov Model.…”

Section: Degradation Model Inputsmentioning

confidence: 96%

Bearing Diagnostics of Hydro Power Plants Using Wavelet Packet Transform and a Hidden Markov Model with Orbit Curves

Pino

Ribas

Guimarães

2018

Shock and Vibration

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The contribution of a medium-sized hydro power plant to the power grid can be either at base load or at peak load. When the latter is the most common operation mode, it increases the start and stop frequency, intensifying the hydro turbine components' degradation, such as the guide bearings. This happens due to more frequent operation in transient states, which means being outside the service point of the machines' nominal condition, consisting of speed, flow, and gross head. Such transient state operation increases the runner bearings' mechanical vibration. The readings are acquired during the runner start-ups and filtered by a DC component mean value and a wavelet packet transform. The filtered series are used to estimate the relationship between the maximum orbit curve displacement and the accumulated operating hours. The estimated equation associated with the ISO 7919-5 vibration standards establishes the sojourn times of the degradation states, sufficient to obtain the transition probability distribution. Thereafter, a triangular probability function is used to determine the observation probability distribution in each state. Both matrices are inputs required by a hidden Markov model aiming to simulate the equipment deterioration process, given a sequence of maximum orbit curve displacements.

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Section: Degradation Model Inputsmentioning

confidence: 96%

Bearing Diagnostics of Hydro Power Plants Using Wavelet Packet Transform and a Hidden Markov Model with Orbit Curves

Pino

Ribas

Guimarães

2018

Shock and Vibration

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“…In principle, it is possible to give an economic value to the maintenance results, and a cost-balance can be done. According to (Welte et al, 2006) the objective of scheduling and optimization of maintenance models is to find the maintenance and renewal strategy where the total costs of repair, inspections, production losses and other consequences are minimal.…”

Section: Maintenance Objectivesmentioning

confidence: 99%

Maintenance Optimization Approaches for Condition Based Maintenance: a review and analysis

Machado

Haskins

2016

INCOSE International Symp

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This study contains a preliminary review of recent maintenance optimization applications, collected from different industries. The idea is to meet and discuss promising approaches, implementation aspects and critical elements, in order to provide guidance for further research. Starting from a set of applications, analyzed under a systems engineering approach, the study proposes a conceptual map to represent the ontology of condition‐based maintenance programs and suggests some guidelines for developing an implementation plan.

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“…[5] presented deterministic and stochastic maintenance optimization approaches for wind turbines and nuclear power plants. [6] determined a deterioration model using a Markov chain and optimized the maintenance costs for hydro power plants using a Monte Carlo simulation. [7] and [8] take into account the influence of seasonality and weather on optimal maintenance.…”

Section: Introductionmentioning

confidence: 99%

Optimization of power generation and maintenance for a wind turbine under stochastic climatic conditions

Hajej¹,

Rezg²,

Chelbi³

2015

2015 International Conference on Industrial Engineering and Systems Management (IESM)

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This paper presents an optimal integrated energy production and maintenance policy for a wind turbine under stochastic climate conditions. A mathematical cost model is developed in order to determine, for a given random demand over a finite horizon and a required service level, the amount of energy to be produced and periodic preventive maintenance to be performed on the wind turbine. The model takes into account the influence of stochastic climatic conditions on the wind turbine failure rate. Costs related to operations and maintenance are considered along with energy storage capacity. Obtained numerical results illustrate the use of the proposed model.

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Markov State Model for Optimization of Maintenance and Renewal of Hydro Power Components

Cited by 35 publications

References 7 publications

Bearing Diagnostics of Hydro Power Plants Using Wavelet Packet Transform and a Hidden Markov Model with Orbit Curves

Bearing Diagnostics of Hydro Power Plants Using Wavelet Packet Transform and a Hidden Markov Model with Orbit Curves

Maintenance Optimization Approaches for Condition Based Maintenance: a review and analysis

Optimization of power generation and maintenance for a wind turbine under stochastic climatic conditions

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