Large interruptions of power supply in the transmission system have considerable impact on modern society. The goal for the transmission system operator (TSO) is to prevent and mitigate such events with optimal decisions in design, planning, operation and maintenance. Identifying critical power components for system reliability provides one important input to this decision-making. This thesis develops quantitative component reliability importance indices applicable for identifying critical components in real transmission systems. Probabilistic models with component failure statistics are combined with detailed power system models evaluated with the AC power flow technique. In the presented method each system component is assigned three importance indices based on outage events expected probability and consequence to (i) reduced system security margin, (ii) interrupted load supply and (iii) disconnected generation units. By ranking components by each of the three interests, a more complete view of the risks to system reliability can be assessed than if, as traditionally, only (ii) is modelled. The impact on security margin is studied in well established critical transfer sections (CTS) supervised by the TSO. TSOs set the CTSs limits [MW] based on deterministic security criteria, with regard to thermal, voltage level, and system stability limits, and the CTSs' condition at post-contingency state is in the method used as an indicator of the system security margin. The methodology is extended with three indices modified to quantify the component importance for common-cause events initiated by acts of sabotage. The developed methods are applied on a significant part of the Great Britain transmission system, modelling 7000 components and 107 substation layouts. The study includes several load demand scenarios, 200 million initiating outage events and non-functioning protection equipment. The resulting component ranking provides an important input to the TSO's decision-making, and could be implemented as a complement to the existing deterministic N-1 criterion. With the methods applied a TSO can perform further and more detailed assessments on a few critical components in order to enhance system reliability for equipment failures and strengthen the system vulnerability against sabotage. / QC 20110920

Microgrids are new challenging power systems under development. This report presents a feasibility study of microgrid development. This is an essential task before implementing microgrid systems. It is extremely important to know the number and size of distributed energy resources (DERs) needed and it is necessary to compare investment costs with benefits in order to evaluate the profitability of microgrids. Under the assumption that a large number of DERs improves the reliability of microgrids an optimization problem is formulated to get the accurate mix of distributed energy resources. Uncertainty in physical and financial parameters is taken into account to model the problem considering different scenarios.  Uncertainty takes place in load demanded, renewable energy generation and electricity market price forecasts, availability of distributed energy resources and the microgrid islanding. It is modeled in a stochastic way. The optimization problem is formulated firstly as a mixed-integer programming solved via branch and bound and then it is improved formulating a two stage problem using Benders’ Decomposition which shortens the problem resolution. This optimization problem is divided in a long-term investment master problem and a short-term operation subproblem and it is solved iteratively until it reaches convergence. Bender’s Decomposition optimization problem is applied to real data from the Illinois Institute of Technology (IIT) and it gives the ideal mix of distributed energy resources for different uncertainty scenarios. These distributed energy resources are selected from an initial set. It proves the usefulness of this optimization technique which can be also applied to different microgrids and data. The different solutions obtained for different scenarios are explained and analyzed. They show the possibility of microgrid implementation and determine the most favorable scenarios to reach the microgrid implementation successfully.  Reliability is a term highly linked to the microgrid concept and one of the most important reasons of microgrid development. Thus an analysis of reliability importance is implemented using the importance index of interruption cost (  ) in order to measure the reliability improvement of developing microgrids. It shows and quantifies the reliability improvement in the system.

<p>Maximum asset performance is one of the major goals for electric power system managers. To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficiently and effectively way, which is the aim of several maintenance methods such as the Reliability Centered Maintenance method (RCM). Furthermore, this necessitates the determination of the optimal balance between preventive and corrective maintenance to obtain the lowest total cost.</p><p>This thesis proposes methods for defining the importance of individual components in a network with respect to total interruption cost. This is a first step in obtaining an optimal maintenance solution. Since the methods consider several customer nodes simultaneously, they are especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major results are three component reliability importance indices, which are applied in two case studies. The first case study is based on a network in the Stockholm area. The second case study is performed for one overhead line system in the rural parts of Kristinehamn. The application studies demonstrate that the indices are possible to implement for existing electrical networks and that they can be used for maintenance prioritization. Consequently these indices constitute a first step in the overall objective of a maintenance optimization method.</p><p>The computations of the indices are performed both with analytical and simulation based techniques. Furthermore, the indices can be used to calculate the component contribution to the total system interruption cost. The approach developed for the importance indices can be utilized in any multi-state network that can be measured with one performance indicator.</p>

Maximum asset performance is one of the major goals for electric power distribution system operators (DSOs). To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficient and effective way. Furthermore, this necessitates the determination of the optimal balance between pre¬ventive and corrective maintenance, which is the main problem addressed in the thesis. The balance between preventive and corrective maintenance is approached as a multiobjective optimization problem, with the customer interruption costs on one hand and the maintenance budget of the DSO on the other. Solutions are obtained with meta-heuristics, developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The methods deliver a Pareto border, a set of several solutions, which the operator can choose between, depending on preferences. The optimization is built on component reliability importance indices, developed specifically for power systems. One vital aspect of the indices is that they work with several supply and load points simultaneously, addressing the multistate-reliability of power systems. For the computation of the indices both analytical and simulation based techniques are used. The indices constitute the connection between component reliability performance and system performance and so enable the maintenance optimization. The developed methods have been tested and improved in two case studies, based on real systems and data, proving the methods’ usefulness and showing that they are ready to be applied to power distribution systems. It is in addition noted that the methods could, with some modifications, be applied to other types of infrastructures. However, in order to perform the optimization, a reliability model of the studied power system is required, as well as estimates on effects of maintenance actions (changes in failure rate) and their related costs. Given this, a generally decreased level of total maintenance cost and a better system reliability performance can be given to the DSO and customers respectively. This is achieved by focusing the preventive maintenance to components with a high potential for improvement from system perspective. / QC 20100810

Maximum asset performance is one of the major goals for electric power system managers. To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficiently and effectively way, which is the aim of several maintenance methods such as the Reliability Centered Maintenance method (RCM). Furthermore, this necessitates the determination of the optimal balance between preventive and corrective maintenance to obtain the lowest total cost. This thesis proposes methods for defining the importance of individual components in a network with respect to total interruption cost. This is a first step in obtaining an optimal maintenance solution. Since the methods consider several customer nodes simultaneously, they are especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major results are three component reliability importance indices, which are applied in two case studies. The first case study is based on a network in the Stockholm area. The second case study is performed for one overhead line system in the rural parts of Kristinehamn. The application studies demonstrate that the indices are possible to implement for existing electrical networks and that they can be used for maintenance prioritization. Consequently these indices constitute a first step in the overall objective of a maintenance optimization method. The computations of the indices are performed both with analytical and simulation based techniques. Furthermore, the indices can be used to calculate the component contribution to the total system interruption cost. The approach developed for the importance indices can be utilized in any multi-state network that can be measured with one performance indicator. / QC 20101130