1. Novel Decision Support System for Underground Power Network Asset Management Asawin Rajakrom College of Art, Media and Technology 9 June 2007

2. Problem and Novelty Problem  Power system distribution network components are operating under diverse service conditions alongside with asset aging, whereas stakeholders demand for their own interests: minimum costs, minimum risks, maximum performances, maximum profits.  The developed decision support system will assist decision makers to come up with the solution that can balance costs, risks, and performance of considered assets. Novelty  Employing the knowledge engineering and heuristic reasoning to evaluate the costs, risks and performance associated with the distribution network assets  Application of object-oriented, CIM-XML in categorizing assets in the way to provide the information for costs, risks and performance evaluation

3. Methodologies Knowledge engineering  CommonKADS Classification and Assessment Template to categorize power system distribution network assets  CommonKADS Assessment Template to capture heuristic reasoning process in costs, risks and performance evaluation Categorizing format  Object oriented framework  CIM-XML Evaluation techniques  Fuzzy Inference System  Markov chain  Analytical Hierarchy Process

4. Risk Identification Risk Analysis Cost of Risks Investment Decision Risk Resolution Cost of Resolutions Risk events and impacts Drivers, probabilities, and total loss Actions to prevent risk Asset Management Decision Process

5. Inference FuzzificationDefuzzification Knowledge Base Expert KnowledgeField Data Subjective Objective InputsOutput Degree of feeder overload Degree of feeder overvoltage Degree of component aging under normal operating conditions Degree of direct applied forces Failure potential (likelihood) Asset conditions Component deterioration rates Interruption potential Risk/Performance Assessment Engine

6. Failure Modes Overheating Overvoltage Ageing Mechanical damage Cases Load current Ambient temperature Insulation Surroundings Fuzzy Sets Risk Evaluation FIS Risk Impacts Utility outage costs: repair costs, damage costs, penalty, etc. Customer outage costs: VoLL. Corporate image lost Sociological impact: Safety, public image, regulatory compliance, environment Crisp Risk Likelihood Cost of Risk

7. Discussion & Conclusion There exists expert knowledge for evaluating the costs, risks, and performance of power distribution system network assets. Asset condition in relation to years of service should be determined in order to predict the appropriate time of asset replacement (Fuzzy Markov Process is considered to be well-suited for the problem). Approach for evaluating the risk impact on stakeholders should be well-defined. Alternative decision criteria could be an incremental risk improvement versus cost spent for such improvement action.