<p>The weather environment has a significant impact on the reliability of a power system due to its effect on the system failure mechanisms of overhead circuits and on the operational ability of an electric power utility. The physical stresses created by weather increase the failure rates of transmission or distribution lines operating in adverse weather conditions, resulting in increased coincident failures of multiple circuits. Exceptionally severe weather can cause immense system damages and significantly impact the reliability performance. Recognition of the pertinent weather impacts clearly indicates the need to develop appropriate models and techniques that incorporate variable weather conditions for realistic estimation of reliability indices.</p> <p>This thesis illustrates a series of multi-state weather models that can be utilized for predictive reliability assessment incorporating adverse and extremely adverse weather conditions. The studies described in this thesis are mainly focused on the analyses using the three state weather model. A series of multi-state weather models are developed and utilized to assess reliability performance of parallel redundant configurations. The application of weather modeling in reliability evaluation is illustrated using a practical transmission system. The thesis presents an approach to identify weather specific contributions to system reliability indices and illustrates the technique by utilizing a test distribution system. The analysis of a range of reliability distributions with regard to major event day segmentation is presented.</p><p>The research work illustrated in this thesis clearly illustrates that reliability indices estimated without recognition of weather situations are unrealistic and that at minimum the three state weather model should be applied in reliability evaluation of systems residing in varying weather environments. The conclusions, concepts and techniques presented in this thesis should prove useful in practical application.</p>

<p>The weather environment has a significant impact on the reliability of a power system due to its effect on the system failure mechanisms of overhead circuits and on the operational ability of an electric power utility. The physical stresses created by weather increase the failure rates of transmission or distribution lines operating in adverse weather conditions, resulting in increased coincident failures of multiple circuits. Exceptionally severe weather can cause immense system damages and significantly impact the reliability performance. Recognition of the pertinent weather impacts clearly indicates the need to develop appropriate models and techniques that incorporate variable weather conditions for realistic estimation of reliability indices.</p> <p>This thesis illustrates a series of multi-state weather models that can be utilized for predictive reliability assessment incorporating adverse and extremely adverse weather conditions. The studies described in this thesis are mainly focused on the analyses using the three state weather model. A series of multi-state weather models are developed and utilized to assess reliability performance of parallel redundant configurations. The application of weather modeling in reliability evaluation is illustrated using a practical transmission system. The thesis presents an approach to identify weather specific contributions to system reliability indices and illustrates the technique by utilizing a test distribution system. The analysis of a range of reliability distributions with regard to major event day segmentation is presented.</p><p>The research work illustrated in this thesis clearly illustrates that reliability indices estimated without recognition of weather situations are unrealistic and that at minimum the three state weather model should be applied in reliability evaluation of systems residing in varying weather environments. The conclusions, concepts and techniques presented in this thesis should prove useful in practical application.</p>

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Society relies more and more on a continuous supply of electricity. However, while underinvestments in reliability lead to an unacceptable number of power interruptions, overinvestments result in too high costs for society. To give incentives for a socioeconomically optimal level of reliability, quality regulations have been adopted in many European countries. These quality regulations imply new financial risks for the distribution system operator (DSO) since poor reliability can reduce the allowed revenue for the DSO and compensation may have to be paid to affected customers.This thesis develops a method for evaluating the incentives for reliability investments implied by different quality regulation designs. The method can be used to investigate whether socioeconomically beneficial projects are also beneficial for a profit-maximizing DSO subject to a particular quality regulation design. To investigate which reinvestment projects are preferable for society and a DSO, risk-based methods are developed. With these methods, the probability of power interruptions and the consequences of these can be simulated. The consequences of interruptions for the DSO will to a large extent depend on the quality regulation. The consequences for the customers, and hence also society, will depend on factors such as the interruption duration and time of occurrence. The proposed risk-based methods consider extreme outage events in the risk assessments by incorporating the impact of severe weather, estimating the full probability distribution of the total reliability cost, and formulating a risk-averse strategy. Results from case studies performed show that quality regulation design has a significant impact on reinvestment project profitability for a DSO. In order to adequately capture the financial risk that the DSO is exposed to, detailed risk-based methods, such as the ones developed in this thesis, are needed. Furthermore, when making investment decisions, a risk-averse strategy may clarify the benefits or drawbacks of a project that are hard to discover by looking only at the expected net present value. / QC 20110530

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