<p>Electrical production in Sweden today is mainly from nuclear and hydro power. However, there is large increase in renewable energy like wind power and the installed new capacity goals are large. Several electrical production sources are important for the sustainability of the energy system. Maintenance is an approach for keeping a system sustainable. The importance of structured maintenance for reliable electrical production systems triggers the development of qualitative and quantitative maintenance management methods. Examples of these methods are Reliability-Centered Maintenance (RCM) which is a structured qualitative approach that focuses on reliability when planning maintenance, and Reliability Centered Asset Management (RCAM) which is a development of RCM into a quantitative approach with the aim to relate preventive maintenance to total maintenance cost and system reliability.</p><p>This thesis presents models, as applications of RCAM, based on the methods of Life Cycle Cost (LCC) and mathematical optimization, applied to wind and nuclear power plants. Both deterministic and stochastic approaches have been used and the proposed models are based on the <em>Total Cost</em> model, which summarizes costs for maintenance and production loss, and the <em>Aircraft </em>model, which is an opportunistic maintenance optimization model. Opportunistic maintenance is preventive maintenance performed at opportunities. The wind power applications in this study show on different ways to cover costs of condition monitoring systems (CMS) and further on economic benefits of these when uncertainties of times to failure are included in the model. The nuclear power applications show on that the optimization model is dependent on the discount rate and that a high discount rate gives more motivation for opportunistic replacements. When put into a stochastic framework and compared to other maintenance strategies it is shown that an extended opportunistic maintenance optimization model has a good overall performance, and that it, for high values of the constant cost of performing maintenance, is preferable to perform opportunistic maintenance. The proposed models, applied to wind and nuclear power plants, could be extended and adapted to fit other components and systems.</p> / Reliability and cost centered maintenance methods

Electrical production in Sweden today is mainly from nuclear and hydro power. However, there is large increase in renewable energy like wind power and the installed new capacity goals are large. Several electrical production sources are important for the sustainability of the energy system. Maintenance is an approach for keeping a system sustainable. The importance of structured maintenance for reliable electrical production systems triggers the development of qualitative and quantitative maintenance management methods. Examples of these methods are Reliability-Centered Maintenance (RCM) which is a structured qualitative approach that focuses on reliability when planning maintenance, and Reliability Centered Asset Management (RCAM) which is a development of RCM into a quantitative approach with the aim to relate preventive maintenance to total maintenance cost and system reliability. This thesis presents models, as applications of RCAM, based on the methods of Life Cycle Cost (LCC) and mathematical optimization, applied to wind and nuclear power plants. Both deterministic and stochastic approaches have been used and the proposed models are based on the Total Cost model, which summarizes costs for maintenance and production loss, and the Aircraft model, which is an opportunistic maintenance optimization model. Opportunistic maintenance is preventive maintenance performed at opportunities. The wind power applications in this study show on different ways to cover costs of condition monitoring systems (CMS) and further on economic benefits of these when uncertainties of times to failure are included in the model. The nuclear power applications show on that the optimization model is dependent on the discount rate and that a high discount rate gives more motivation for opportunistic replacements. When put into a stochastic framework and compared to other maintenance strategies it is shown that an extended opportunistic maintenance optimization model has a good overall performance, and that it, for high values of the constant cost of performing maintenance, is preferable to perform opportunistic maintenance. The proposed models, applied to wind and nuclear power plants, could be extended and adapted to fit other components and systems. / Reliability and cost centered maintenance methods