Webinar Recap: Managing Rapid Electric Grid Growth and Transformation with Advanced Tools and Techniques
CEATI recently hosted a webinar on “Managing Rapid Electric Grid Growth and Transformation with Advanced Tools and Techniques.”
This session featured Bagen Bagen, Head of Network Reliability at Manitoba Hydro, Nelson Bacalao, Principal Consultant at Siemens PTI and Marc Lamoureux, Senior Product Manager at IFS Copperleaf. Together, they explored the latest strategies for aligning capital planning with technical grid analysis in the face of accelerating electrification and grid complexity.
The Challenge: Rapid Electrification & Investment Complexity
The electrical grid is experiencing unprecedented demands:
- 18× growth in EVs by 2030
- 7× increase in DERs and data center connections by 2030
- 3× rise in electricity demand by 2050
By 2030, 50+ million new heat pumps are projected in Europe alone. This explosive growth introduces technical challenges in capacity, resilience, and modernization—all will demand more agile and integrated investment planning. ERCOT in Texas projects that by the mid-2030s, there will be an approximately 75% increase in peak demand (150 GW) in the Permian Basin, driven by data centers and electrification. As electricity consumption and GW level load increases in all other markets, the complexity of decision making in capital allocation and technical analysis also escalates. This need presents significant challenges for companies navigating the electrification landscape.
Integrated Grid Planning: Technical and Capital Planning
Integrated Grid Planning focuses on tight integration between technical analysis and capital planning. The typical process involves:
- Identifying needs across areas like sustainment, decarbonization, and resilience
- Developing alternatives using simulations and probabilistic risk assessments
- Aligning capital investment based on value-centric prioritization
Effective investment planning involves evaluating multiple alternatives, not just the one that appears technically optimal. By considering a broader set of options, organizations can uncover more value-aligned and strategically sound solutions.
Maintaining end-to-end traceability from identified needs through to final investment decisions is also critical, particularly for regulatory defensibility. This transparency ensures decisions can be clearly justified. Furthermore, integrating technical and planning tools streamlines both regulatory compliance and portfolio optimization, enabling a more cohesive and efficient planning process.
Marc Lamoureux provides an overview of the benefits of integrating technical and capital planning:
Case Study 1: Manitoba Hydro’s Transmission Project Planning
Over the years, Manitoba Hydro has devoted significant effort to strategically and effectively develop and implement capital plans. Electric transmission presents unique challenges, including lengthy planning and construction timelines and substantial budget requirements.
Manitoba Hydro’s planning practice includes an annual update of a list of potential system issues, referred to as planning items. These items are identified through annual NERC compliance studies, operational practices, or asset management needs.
Once updated, the planning items are prioritized for technical studies aimed at identifying system needs, developing and comparing alternatives, and selecting or recommending a preferred option using a value-based approach known as the Corporate Value Framework (CVF). The CVF is also updated annually to optimize the capital investment portfolio and guide capital investment decisions based on evolving needs and market conditions.
Bagen Bagen spoke about the process Manitoba Hydro uses to evaluate transmission projects. He describes a two-stage evaluation for capital projects starting with a Network Reliability Evaluation Study (NRES) followed by a Network Reliability Facility Study (NRFS):
The NRES and NRFS studies use extensive simulations (load flow, short circuit, transient stability), followed by a CVF evaluation that balances many drivers, including reliability risk, safety risk, environmental impact, corporate responsibility, and financial value.
Manitoba Hydro is using the CVF with IFS Copperleaf Portfolio to compare both project alternatives and different types of projects. When prioritizing projects, each alternative is evaluated using the CVF that scores initiatives based on their net value. This approach ensures decisions are grounded in a consistent, value-driven methodology.
Once scored, portfolios can be optimized to deliver the greatest overall value while staying within financial and resource limitations. One example might be selecting five smaller projects that collectively generate more benefit than a single large one. This disciplined, value-maximizing approach enables more strategic investment decisions.
Bagen Bagen demonstrated how the CVF helps compare both project alternatives and different projects within a portfolio.
Manitoba Hydro has developed a suite of risk modeling tools, collectively referred to as the System Reliability/Risk Model (SRRM), designed to quantify the reliability and risk associated with the transmission system.
The SRRM simulates transmission system performance with and without proposed investments, evaluating the impact on reliability by analyzing both single and simultaneous component failures within the network.
Case Study 2: Siemens on Probabilistic Investment Modeling
The recent explosion in AI applications has flooded many utilities with requests to add new data centers. These data centers represent very large point loads that can have a significant impact on the electric grid.
Nelson Bacalao, Principal Consultant from Siemens PTI, discussed the evolution of planning for new data centers, emphasizing the shift from traditional analysis to a probabilistic assessment of decision impacts. The plans must comply with NERC TPL-001 standards while considering the economic implications of adding significant demand, such as the 1.3 GW required by a new data center.
Probabilistic-based integration system planning addresses this challenge. An analysis includes the costs associated with revenue not served and the reliability of input data, which has improved over time.
When planning for a 1.3 GW data center to be sited adjacent to a 523 MW load, the evaluation included:
- Using asset failure data and repair times in probabilistic network modeling
- Value of lost load (VoLL) used to monetize reliability benefits
- Investment options for building a new 50-mile line and/or upgrading substations
Nelson Bacalao went through the baseline case probabilistic analysis with the focus still on ensuring quality of service for customers while evaluating system expansion options:
Option 1 (new parallel line)
- Reduced reliability cost from $24M to $1.5M/year compared with the baseline
- Including the Net Present Value (NPV) of these reliability benefits as well as project costs, expropriation costs, vegetation management costs and environmental risk yields a net value of $130M and B/C ratio of 2
Option 2 (new parallel line and adding)
- Reduced reliability cost from $1.5M to $0.85M/year compared with option 1
- Increased costs of this project weren’t outweighed by the increase in reliability benefits
- Net value is $128M with a B/C ratio of 1.92
- A good example of diminishing returns compared to Option 1
These are practical examples of how combining reliability data from IFS Copperleaf with probabilistic system simulations creates a quantitative, transparent decision framework for capital planning.
Integrated planning, rooted in data-driven technical analysis and financial modeling, can transform the way utilities respond to the grid’s evolving needs.
As stakeholders—from regulators to customers—demand more transparent, resilient, and sustainable infrastructure investments, utilities must embrace tools and frameworks that ensure smart and defensible decisions.
Check out the full on-demand webinar for more details.