A Holistic Framework for Integrated Grid Planning: Balancing Load Growth, Aging Infrastructure, and Climate-Driven Risk

Company (PG&E), these challenges are prominent due to the convergence of aging infrastructure, rapid load growth from widespread electric vehicle (EV) adoption and data center development, and escalating climate-related threats such as wildfires. In response, PG&E developed a holistic Integrated Grid Planning (IGP) framework that facilitates system planning for electric distribution, substation, and transmission systems.

This paper outlines the methodology, process design, and implementation of PG&E’s IGP framework. The primary objective of the IGP framework is to establish a risk-informed, datadriven, and capital-efficient investment plan that aligns long-term system needs with near-term operational priorities. The framework attempts to address traditional fragmentation in utility’s investment planning practices by integrating asset condition assessments, asset intervention eligibility and benefit estimation, risk modelling, investment bundling, and capacity/load forecasting into a single decision-support platform.

Each year, PG&E conducts an annual refresh of its multi-year Integrated Grid Plan by assessing asset and investment risk across five categories: reliability, capacity, safety, wildfire, and financial. These risk scores are calculated based on a combination of historical performance, asset condition data, and forward-looking forecasts. Investments are created and bundled based on the eligible assets within a defined investment zone. The value of each investment is calculated using the aggregated asset risk mitigation and the corresponding asset intervention cost, as well as investment-based valuation methodologies. This process establishes a quantitative basis for comparing investment options.

These investment values are then used in a value-driven prioritization model designed to optimize decision-making in multi-year investment plans. Optimization techniques are applied Internal to identify high-value projects and determine the ideal time to execute on these projects. This optimization step considers various practical constraints including available capital, and with requirements to align with regulatory and strategic objectives. The result is a transparent and systematic investment roadmap that balances cost efficiency with operational constraints and strategic objectives.

A key achievement of PG&E’s approach is the collaborative development of the risk models and supporting datasets across multiple business units. Cross-functional teams from the Asset

Knowledge Management team (AKM), Distribution and Transmission Capacity Planning,

(Information Technology) IT, Asset Strategy (Distribution, Substation, Transmission),

Enterprise and Operational Risk Management team, and Risk and Data Analysis team worked jointly to define asset eligibility criteria, quantify intervention costs and benefits, and validate critical assumptions. This cross-department coordination ensures that the IGP outcomes are not only technically sound, but are also aligned with enterprise goals as related to resilience, affordability, and decarbonization.

A case study—Megabundling at Templeton 2113—demonstrates IGP’s practical benefits. By consolidating multiple interventions into a single, coordinated operation, PG&E achieved substantial unit cost reduction as well as significant reduction in outage duration, illustrating how integrated planning improves efficiency and customer experience.

Challenges included data quality gaps, and system integration limitations. This paper explores these challenges, strategies to address them, and lessons learned from initial deployment. By embedding data-driven decision models and structured value assessments into grid planning,

PG&E’s IGP approach sets a precedent for transparent, technically robust capital allocation and demonstrates how utilities can modernize planning using quantitative, scalable methodologies.