Isabel Martón

Onshore wind farms maintenance optimization using a stochastic model

Abstract A specific feature of wind power generation is the stochastic behavior of wind velocity which determines the energy produced, and also influences the turbine degradation process due to the stochastic load suffered by the wind turbine. Thus, wind turbines present a degradation process more complex than the equipment that work under stationary conditions.The selection of a maintenance strategy, that comprises the date to perform a maintenance activity, the maintenance frequency and the duration of such activity have a great influence on the operational cost, that determines the plant viability. Wind velocity probability distribution can be obtained from daily wind data measurements, and by Monte Carlo sampling, it is possible to estimate the power generated. This generation has an associated cost due to the loss of production during maintenance.This work is focused on finding the best maintenance strategy that minimizes the total cost and maximizes the annual energy produced of a wind turbine considering the maintenance frequency as a decision variable.

Ageing PSA incorporating effectiveness of maintenance and testing

This paper proposes a new approach to Ageing Probabilistic Safety Assessment (APSA) modelling, which is intended to be used to support risk-informed decisions on the effectiveness of maintenance management programs and technical specification requirements of critical equipment of Nuclear Power Plants (NPP) within the framework of the Risk Informed Decision Making according to R.G. 1.174 principles. This approach focuses on the incorporation of not only equipment ageing but also effectiveness of maintenance and efficiency of surveillance testing explicitly into APSA models and data. An example of application is presented, which centres on a critical safety-related equipment of a NPP in order to evaluate the risk impact of considering different approaches to APSA and the combined effect of equipment ageing and maintenance and testing alternatives along NPP design life. The risk impact of the several alternatives is quantified and the results shows that such risk depends largely on the model parameters, such as ageing factor, maintenance effectiveness, test efficiency.

Evaluation of risk impact of changes to surveillance requirements addressing model and parameter uncertainties

This paper presents a three steps based approach for the evaluation of risk impact of changes to Surveillance Requirements based on the use of the Probabilistic Risk Assessment and addressing identification, treatment and analysis of model and parameter uncertainties in an integrated manner. The paper includes also an example of application that focuses on the evaluation of the risk impact of a Surveillance Frequency change for the Reactor Protection System of a Nuclear Power Plant using a level 1 Probabilistic Risk Assessment. Surveillance Requirements are part of Technical Specifications that are included into the Licensing Basis for operation of Nuclear Power Plants. Surveillance Requirements aim at limiting risk of undetected downtimes of safety related equipment by imposing equipment operability checks, which consist of testing of equipment operational parameters with established Surveillance Frequency and Test Strategy.

Optimization of test and maintenance of ageing components consisting of multiple items and addressing effectiveness

There are many models in the literature that have been proposed in the last decades aimed at assessing the reliability, availability and maintainability (RAM) of safety equipment, many of them with a focus on their use to assess the risk level of a technological system or to search for appropriate design and/or surveillance and maintenance policies in order to assure that an optimum level of RAM of safety systems is kept during all the plant operational life. This paper proposes a new approach for RAM modelling that accounts for equipment ageing and maintenance and testing effectiveness of equipment consisting of multiple items in an integrated manner. This model is then used to perform the simultaneous optimization of testing and maintenance for ageing equipment consisting of multiple items. An example of application is provided, which considers a simplified High Pressure Injection System (HPIS) of a typical Power Water Reactor (PWR). Basically, this system consists of motor driven pumps (MDP) and motor operated valves (MOV), where both types of components consists of two items each. These components present different failure and cause modes and behaviours, and they also undertake complex test and maintenance activities depending on the item involved. The results of the example of application demonstrate that the optimization algorithm provide the best solutions when the optimization problem is formulated and solved considering full flexibility in the implementation of testing and maintenance activities taking part of such an integrated RAM model.

Evaluation of risk impact of changes to Completion Times addressing model and parameter uncertainties

Abstract This paper presents an approach and an example of application for the evaluation of risk impact of changes to Completion Times within the License Basis of a Nuclear Power Plant based on the use of the Probabilistic Risk Assessment addressing identification, treatment and analysis of uncertainties in an integrated manner. It allows full development of a three tired approach (Tier 1–3) following the principles of the risk-informed decision-making accounting for uncertainties as proposed by many regulators. Completion Time is the maximum outage time a safety related equipment is allowed to be down, e.g. for corrective maintenance, which is established within the Limiting Conditions for Operation included into Technical Specifications for operation of a Nuclear Power Plant. The case study focuses on a Completion Time change of the Accumulators System of a Nuclear Power Plant using a level 1 PRA. It focuses on several sources of model and parameter uncertainties. The results obtained show the risk impact of the proposed CT change including both types of epistemic uncertainties is small as compared with current safety goals of concern to Tier 1. However, what concerns to Tier 2 and 3, the results obtained show how the use of some traditional and uncertainty importance measures helps in identifying high risky configurations that should be avoided in NPP technical specifications no matter the duration of CT (Tier 2), and other configurations that could take part of a configuration risk management program (Tier 3).

An approach to address probabilistic assumptions on the availability of safety systems for deterministic safety analysis

Abstract There is an attempt nowadays to provide a more comprehensive and realistic safety assessment of design and operation of Nuclear Power Plants. In this context, innovative approaches are being proposed for safety assessment of nuclear power plants design including both design basis conditions and design extension conditions. An area of research aims at developing methods for combining insights from probabilistic and deterministic safety analyses in Option 4, also called realistic approach, from the International Atomic Energy Agency specific safety guide. The development of Option 4 or realistic approach involves the adoption of best estimate computer codes, best estimate assumptions on systems availability and best estimate of initial and boundary conditions for the safety analysis. This paper focusses on providing the fundamentals and practical implementation of an approach to integrate PSA-based probabilistic models and data, which incorporate best estimate assumptions on the availability of safety systems, into Option 4. It is presented a practical approach to identify relevant, i.e. most probable, configurations of safety systems and to assess the associated occurrence probability of each configuration using PSA models and data of a NPP, which is based on the use of a Pure Monte Carlo method. An example of application is provided to demonstrate how this approach performs. The case study focusses on an accident scenario corresponding to the initiating event “Loss Of Feed Water (LOFW)” for a typical three-loops Pressurized Water Reactor (PWR) NPP.

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

The reliability, availability and maintainability (RAM) modelling of safety equipment has long been a topic of major concern. Some RAM models have focused on explicitly addressing the effect of component degradation and surveillance and maintenance policies, searching for an optimum level of the safety component RAM by adjusting surveillance and maintenance related parameters. As regards the reliability contribution, these components normally have two main types of failure mode that contribute to the probability of failure on demand (PFD): (1) by demand-caused and (2) standby-related failures. The former is normally associated with a demand failure probability, which is affected by the degradation caused by demand-related stress. Surveillance testing therefore not only introduces a positive effect, but also an adverse one, which it compensates by performing maintenance activities to eliminate or reduce the accumulated degradation. This paper proposes a new model for the demand failure probability that explicitly addresses all aspects of the effect of demand-induced stress (mostly test-induced stress), maintenance effectiveness (PAS or PAR model) and test efficiency. A case study is included on an application to a typical motor-operated valve in a nuclear power plant.

Evaluation of risk impact of completion time changes combining PSA and DSA model insight and human reliability analysis

Abstract Although in risk screening of equipment structures, systems and components, changes can be accomplished directly using RG 1.174, a plant change may also include changes to human actions. Human reliability analysis is an integral part of probabilistic safety assessment modeling. Using best estimate codes can identify unknown accident sequences as well as quantify more realistic probabilities of human error. This paper proposes a three-step approach to evaluate the risk impact of changes to completion time within nuclear power plant technical specifications, using a probabilistic safety assessment model refined by a best-estimate safety analysis and human reliability analysis. A case study is presented focusing on a completion time change of the residual heat removal system of a nuclear power plant using a level 1 low power and shutdown probabilistic safety assessment. Thus, the application case shows that the change could be accepted from a risk viewpoint, in particular, because of the risk increase imposed by extending the completion time is partially compensated by the risk decrease due to the human error probability reduction since the stress level is reduced.

RELAP5 Simulation of PKL Facility Experiments under Midloop Conditions

Nuclear power plant risk has to be quantified in full power and in other modes of operation. This latter situation corresponds to low power and shutdown modes of operation in which the residual heat removal (RHR) system is required to extract the heat generated in the core. These accidental sequences are great contributors to the total plant risk. Thus, it is important to analyze the plant behavior to establish the accident mitigation measures required. In this way, PKL facility experimental series were undertaken to analyze the plant behavior in other modes of operation when the RHR is lost. In these experiments, the plant configurations were changed to analyze the influence of steam generators secondary side configurations, the temperature inside the pressurizer, and the inventory level on the plant behavior. Moreover, different accident management measures were proposed in each experiment to reach the conditions to restart the RHR. To understand the physical phenomena that takes place inside the reactor, the experiments are simulated with thermal-hydraulic codes, and this makes it possible to analyze the code capabilities to predict the plant behavior. This work presents the simulation results of four experiments included in PKL experimental series obtained using RELAP5/Mod3.3.

Parameter Estimation of a Reliability Model of Demand-Caused and Standby-Related Failures of Safety Components Exposed to Degradation by Demand Stress and Ageing That Undergo Imperfect Maintenance

The authors are grateful to the Spanish Ministry of Science and Innovation for the financial support received (Research Project ENE2016-80401-R) and the doctoral scholarship awarded (BES-2014-067602). The study also received financial support from the Spanish Research Agency and the European Regional Development Fund.