How Can Risk-Based Asset Management Enable Managers To Make Decisions Regarding the Lifecycle of Their Assets?

This audio was created using Microsoft Azure Speech Services.

As the energy sector undergoes massive electrification, the electric distribution industry faces challenges in managing the changing regulations and policies, integrating DER, adapting to the digital landscape, and dealing with the effects of climate change. To maximize the value extracted from assets, utilities must make informed decisions on where to spend resources and which actions to prioritize. Risk-based asset management addresses this question by focusing on the assets that carry the highest risk.

Utility companies face various risks, including natural disasters, vegetation, equipment failure, and cyber-attacks. A risk-based asset management approach assesses and monetizes these risks to build asset management programs that aim to reduce risk using the available resources, whether financial, human, or material. This approach results in better prioritization of maintenance and investment projects, improved network reliability and resiliency, and increased efficiency through Opex savings on maintenance costs and Capex sustaining deferral.

Calculating the cost of inaction for recognizing the value at risk on asset portfolio.

Schneider Electric’s risk framework is based on the CNAIM methodology, which calculates network asset KPIs such as the health index (HI), probability of failure (PoF), criticality index (CI), and consequence of failure (CoF). Data for the HI and PoF calculations can be sourced from various systems such as GIS, EAM, ERP, or ADMS. The CI and CoF are evaluated against four buckets of risk corresponding to the financial impact of asset failure on operation and maintenance costs, costs of non-delivered energy, safety costs, and environmental costs. The monetized risk is obtained by multiplying the PoF by the CoF, which changes year after year depending on asset aging curves.

Schneider Electric has also developed a mathematical solver that identifies the list of interventions allowing the highest risk reduction using the lowest amount of resources, where each intervention cost, necessary resources, and mitigated risk are defined within the solution.

As Electric Utilities recognize they are data-rich, risk-based asset management becomes more granular

Utilities can implement this framework easily using pre-defined templates, or an augmented version of CNAIM, but in both cases data readiness is a critical enabler. Utilities with clean data in their GIS system have a clear advantage in starting this process. Other data, like inspection records, historical maintenance data, telemetry data, load flow data, or Smart Meters data, from EAM, CMMS, ADMS, or AMI MDM, should not be neglected as they bring meaningful data to consolidate the asset model. Therefore, having the right data in place is a prerequisite to unlock the value of risk-based asset management.

The computed asset KPI can be used to unlock more value in other Utility systems. For instance, dispatchers and operators can decide the most performing operational scenario with the asset information within the ADMS. GIS engineers can superpose the asset risk layer on top of the standard network map, and field crews can be notified about risky assets in the neighborhood of their interventions.

Delivering tangible value across Electric Utilities organizations.

Schneider Electric recently helped a Canadian utility in Quebec state to justify their multi-year asset management plan, bringing evidence of the results that can be achieved with the granted budget and available resources. This utility managed to build a plan capable of reducing risk by CA$14 for every CA$1 invested in the plan.

In conclusion, a risk-based maintenance approach helps utilities comply with ISO 55000 concepts and philosophy. The CNAIM (or augmented version of CNAIM) methodology, specifically designed for distribution utilities, is useful for determining the most economical use of maintenance resources and maximizing the asset lifetime. Risk-based asset management is a journey, not a destination, that can begin as soon as the utility has a strong GIS data foundation.

written by Sebastien Michelin, Offer Manager, Asset Management, Marketing

Tags: , , , ,

Add a comment

All fields are required.

This site uses Akismet to reduce spam. Learn how your comment data is processed.