Total asset management for utility network companies

Solving energy transition challenges through grid asset management

The energy transition is accelerating at full speed as renewable energy sources replace fossil-based energy production systems. The grid itself must be green to operate within the following ranges: We must meet our environmental, social and governance (ESG) goals and achieve carbon neutrality by 2050. These changes require energy utilities to holistically plan grid asset management while finding a new balance between strategic objectives.

Sustainable asset performance has become one of the key drivers of decision-making for asset planning and grid modernization business processes. New technologies enable smart grids to operate through AI-based digital twins. However, operators must balance intermittent renewable energy intake to produce controlled and stable output.

Balanced transition between old and new systems

The growing need to fulfill existing long-term contracts and new demands for industrial electrification pose new challenges to grid management. Finding the right balance requires load forecasting and simulation to avoid net congestion. Economic optimization must take into account new market dynamics and ensure stable operations.

Existing network assets are aging, and more intelligent asset management strategies are needed to maintain and replace the grid within tight budgets. Asset investment plans must find a balance between these systems while minimizing risk and carbon emissions.

To manage the grid of the future, utilities must move from traditional asset management to a holistic approach. These changes will expand insight so companies can take strategic and tactical actions to optimize operational network development and operational decisions.

Asset life cycle management

Holistic grid asset management adopts a lifecycle perspective across the entire asset lifetime to ensure a secure, reliable, and affordable network. Utilities must break down internal departmental walls between silos of grid planning, construction, operations, maintenance and replacement to achieve end-to-end visibility. You need to connect your underlying technology systems to create a single pane of glass for all operations. A shared data model across operating systems becomes the foundation for integration, simulation, prediction, and optimization by using generative AI models to drive next-generation business value.

The goal of asset management is to optimize capital expenditures (CapEx) and operating expenses (OpEx) in smooth transitions between planning periods. The following figure illustrates the complex planning and optimization objectives required to view the asset management life cycle holistically.

A top-down strategic approach for whole-life planning of asset investment portfolios aligned with future ESG objectives should be coupled with a bottom-up maintenance and replacement strategy for existing assets. Asset Investment Planning (AIP) uses project portfolio management and product lifecycle management to plan, prioritize, and execute asset expansion and replacement projects within available budget and resource capacity.

Real-time operational data provides a view of asset health that drives condition-based maintenance and replacement planning. This is the realm of enterprise asset management (EAM) for maintenance execution and asset performance management (APM) for strategy optimization. Traditionally, a disconnect at the tactical level has separated these planning and optimization methodologies. At the same time, operational risk management must respect health, safety and environment (HSE) management and process safety management to manage potentially hazardous operations. The maintenance repair and overhaul (MRO) spare parts strategy should be aligned with the asset strategy in terms of criticality and optimal inventory value.

Recognizing the complexity of planning with multidimensional goals for different time periods is the starting point for adopting a holistic view of asset management.

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