Shaping the Future of Power Systems Planning: Innovative Modeling Approaches
Hyperbolic load forecasts. Indefinite coal retirement delays. Restarting long-idled nuclear plants. These are just a few of the factors that have slammed the resource planning space in recent months. Across the country, utilities are upending their long-term resource plans and developing new approaches to evaluate resource needs. As these factors compound, utilities, and the consumer and environmental advocates that engage with them, are running into new challenges in the power system planning space. Our existing tools for resource planning, forecasting load, and evaluating the impact of weather on high renewable energy systems are not keeping up with changes in the industry and they are being stretched to their limits. New planning methods are needed to meet the moment, and balance our overlapping objectives related to reliability, emissions, cost, equity, and other policy goals.
As technical experts supporting intervening parties in resource planning proceedings across the country, GridLab and its network of experts have wrestled with these challenges. Our new ongoing multipart series, “Innovate: Alternative Modeling Approaches to Inform Power System Planning”, showcases innovative modeling approaches to address the increasing complexity of power system planning.
What is power systems planning?
Electricity and grid planners use a variety of software tools to plan for various aspects of the power system. This planning has grown increasingly complex as the electric industry faces resource scarcity, load growth, increased weather risk, and the introduction of renewable energy sources. This new landscape has stretched current planning methods and modeling tools to their capacity as multiple objectives—reliability, emissions, cost, equity, land use—must be considered.
Key challenges in power systems planning
Power system planning is growing increasingly complex due to the integration of variable renewable energy, storage, and evolving load growth and weather patterns. Existing planning tools struggle to manage this complexity and balance multiple objectives such as reliability, emissions, cost, equity, and land use. Additionally, growing uncertainties around technology costs, fuel prices, and weather impacts add further challenges. Many current planning approaches overemphasize least-cost optimization and focus on the capacity expansion or portfolio design step. This has the potential to overlook other desirable solutions that may not be strictly the least-cost solution but balance other priorities more evenly (such as emissions or resource diversity). A solution that is not simply least-cost, but might have other desirable attributes, such as resource diversity or lower emissions, may be overlooked. Given the length of regulatory proceedings, assumptions that go into the portfolio design step are quickly outdated. However, once the “bread is baked,” we tend to spend a majority of our time debating these outdated modeling outputs due to the lack of nimbleness and efficiency of the modeling process. The bread is baked, so to speak, utilizing the wrong recipe from the outset. Finally, the complexity of these models can reduce transparency between utilities and stakeholders, making effective decision-making more difficult.
What are the new approaches?
The INNOVATE series is an ongoing initiative to highlight new modeling approaches aimed at overcoming current limitations to portfolio modeling and resource planning with a particular eye towards enhancing model efficiency, flexibility, and iteration based on modeling outputs.
Article 1 in the series introduces current trends, challenges, and opportunities for modeling the future grid, drawing from reviews of recent utility integrated resource plans (IRPs).
Article 2 focuses on a new approach developed by Telos Energy. Their paper, “Rethinking the role of capacity expansion modeling: An alternative approach for reliable and economic portfolio design under uncertainty,” aims to better integrate risk and uncertainty into portfolio design, recognizing the limitations of capacity expansion modeling.
Article 3, “Iterative portfolio optimization: an essential tool for reliable and clean electricity planning,” developed by Sylvan Energy Analytics, addresses the challenges of incorporating complex planning considerations, including resource adequacy and policy requirements, in capacity expansion models. The approach uses a type of roundtrip modeling that guarantees convergence of the model, even under multi-objective planning in which planners are balancing reliability, emissions, and other key constraints.
How can we leverage these approaches?
While no single tool will entirely upend the existing resource planning modeling approach, these new approaches provide opportunities for advocates and regulators to better evaluate modeling proposals and quickly iterate through their own resource planning exercises. In some cases, this could enable us to bypass the resource intensive process of iterating through capacity expansion runs. In other cases, we could avoid constant manual tweaking of inputs and converge on optimal solutions more efficiently.
The “Innovate” modeling series offers valuable insights into addressing the limitations of current power system planning tools and methods. The series promotes the use of innovative modeling approaches to better manage the uncertainties and complexities of the modern electric grid and emphasizes the need for more flexible, transparent, and collaborative planning processes.
All articles in the series can be found at: