Home > Asset Management > Risk-Cost Modelling Study Identifies 96% Reduction in Total Risk Cost for UK Power Station

Risk-Cost Modelling Study Identifies 96% Reduction in Total Risk Cost for UK Power Station

Two male technicians wearing a hard hat, safety glasses and hi-vis jacket are standing outside inspecting a piece of pipework.
Location

United Kingdom

Sectors
  • Onshore
  • Power Station
Services
  • Asset Management Consultancy
  • Risk-Cost Modelling Study
  • Spares Analysis

Project Background

Penspen’s client owns and operates several power stations in the UK, providing necessary capacity to meet increasing demands for electricity. Our client engaged Penspen’s Asset Management Consultancy to conduct a risk-cost modelling assessment on a critical gas asset at one of its natural gas power stations, with the objective of quantifying operational and safety risk exposure and identifying economically optimal mitigation strategies.

Services

The study focused on understanding how failure modes, maintenance strategy, and spare parts availability could impact asset availability, safety performance, and long-term revenue loss over a 10‑year operating horizon.

  • Two critical components — the ESD valve and associated PLC — were identified as dominant contributors to unscheduled downtime and consequential losses.
  • Without intervention, these risks exposed the asset to nearly £9million in lost revenue over the modelled lifetime.
  • By optimising maintenance intervals and implementing targeted spares holding strategies, projected losses were reduced to under £500,000, representing a 96% reduction in total cost risk.

Result

Penspen’s data-driven optimisation approach increased labour and spares investment by approximately £72,000, while potentially reducing effect-related losses by £9million. This represents a step change improvement in asset risk profile, with safety and operational criticality reduced by more than 60% compared to baseline conditions.

Beyond immediate financial benefit, the study proactively identified obsolescence and management of change risks, enabling our client to plan future interventions with confidence and avoid reactive decision making under failure conditions. This engagement demonstrates how targeted risk-cost modelling and spares optimisation can convert latent operational risk into quantified investment decisions, improving availability, safety performance, and lifecycle value across critical energy infrastructure

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