Processing Risk In Asset Management: Exploring The Boundaries Of Risk Based Optimization Under Uncertainty For An Energy Infrastructure Asset Manager

Abstract

In the liberalized energy market Distribution Network Operators (DNOs) are confronted with income reductions by the regulator. The common response to this challenge is the implementation of asset management, which can be regarded as systematically applying Cost Benefit Analysis (CBA) to the risks in the networks. In short, this is Risk Based Optimization (RBO). However, application of RBO is mostly limited to interventions on individual assets like upgrades, replacements and maintenance. Whether RBO is feasible for higher levels of aggregation like the portfolio of interventions or even the whole system was not clear. The unavoidable subjectivity and uncertainty associated with risk decision making could threaten the acceptance of decision outcomes. The experiments conducted in this research reveal that there are no fundamental barriers to risk based optimization of the whole system. Embracing uncertainty and subjectivity allows for relatively simple tools, as the tools do not need to be more accurate than our knowledge of the future. The condition for this to work is that the rational RBO decisions are embedded in a well-designed sociotechnical process. A systematic implementation of RBO on all levels (individual assets, portfolios of interventions and the whole system) results in a reduction of the total costs of the system (expenditure plus residual risk) of about 20%.Engineering Systems and Services, Section Energy & IndustryTechnology, Policy and Managemen