CAISO Strengthens Reliability and Planning with PLEXOS®

Balancing Innovation and Reliability Across California's Renewable Future

The California Independent System Operator (CAISO) manages roughly 80% of California’s electricity demand, operating one of the most complex and renewable-rich power systems in the world. As California accelerates its clean energy goals, CAISO sits at the center of this transformation, responsible for ensuring that system reliability keeps pace with rapid change.

With more than half the state’s installed capacity now coming from variable energy resources (VERs) such as solar, wind, and battery storage, maintaining balance across the grid has become increasingly challenging. Traditional resource adequacy frameworks were built around predictable thermal generation and do not account for the rapid, weather-driven swings, duration limits, and operational constraints that now shape system reliability.

To ensure reliability in an evolving landscape, CAISO uses Energy Exemplar’s PLEXOS® to guide constructive rule reforms and evaluate the future of its resource fleet.

Reliability in a Rapidly Changing Grid 

California’s generation portfolio has changed dramatically in recent years. Solar and wind power now dominate daytime production, while storage resources are essential to meeting evening demand after solar generation drops. This shift has created new operational planning complexities for CAISO, including:

• Timing Mismatch: Solar output peaks at midday, but reliability risk rises after sunset when demand remains high. Managing this “net-peak” period requires precise coordination of battery dispatch and imports, which are limited to around 5,500 MW during tight evening hours despite high transmission capacity.
• Managing Localized Resource Adequacy: Twenty-eight Local Regulatory Authorities (LRAs), including the California Public Utilities Commission (CPUC), apply differing resource adequacy (RA) methodologies, resulting in inconsistent capacity accreditation across the state.
• Outdated Default Rules: CAISO’s existing counting rules, adopted in 2006 for a thermal-dominated fleet, no longer capture the performance and availability characteristics of today’s weather-dependent and duration-limited resources, resulting in capacity values that do not accurately reflect real system reliability.
• Rising Uncertainty: Weather conditions, hydrology, and forced outages introduce significant variability that deterministic models struggle to capture.

To plan effectively for reliability, CAISO needs a modern, probabilistic modeling framework capable of representing real-world uncertainty, integrating renewable behavior, and aligning capacity value with system risk.

Traditional RA approaches credit capacity based on installed MW rather than confirming performance during the hours of highest risk, and deterministic methods cannot capture the extreme weather events, hydrology shifts, and correlated renewable output patterns that increasingly shape system adequacy.

Because uncertainty in weather, hydrology, outages, and long-term resource evaluation can compound and reveal reliability challenges years before they appear in operations, CAISO requires probabilistic modeling and forward-looking scenario analysis to accurately assess system adequacy.

A Modern Resource Adequacy Framework with PLEXOS® 

CAISO leveraged PLEXOS® to completely redesign its resource adequacy modeling approach, moving from static assumptions to dynamic, probabilistic analysis that mirrors real operating conditions. The organization has used PLEXOS® for over two decades and continues to expand its use to support a more advanced planning and policy function.

Advanced Probabilistic Modeling

CAISO developed a stochastic modeling environment in PLEXOS® to capture a full range of operating conditions across the grid. This included:

• 500 unique scenario profiles, each combining randomized load, solar, wind, hydro, and outage data derived from 25 years of historical variability.
• 8,760-hour dispatch simulations for each case to measure system performance, loss-of-load events, and reliability metrics across an entire year.
• Monthly model snapshots aligned with CAISO’s monthly RA framework, ensuring consistency between planning and operations.

This approach allowed CAISO to test the system under hundreds of realistic conditions. It not only quantified how much capacity was available, but also when and how reliably it performs.

Modernized Resource Accreditation

CAISO is using PLEXOS® to evaluate several updated accreditation methods as analytical inputs to its proposed RA design, which LRAs, including the CPUC, continue to determine final accreditation methodologies. These approaches include:

• Expected Output in Risk Hours – Measuring resource availability during defined high-risk periods.
• Average Effective Load Carrying Capacity (ELCC) – Applying consistent ELCC values across all resource types.
• Marginal ELCC – Assessing incremental reliability contributions from each resource.
• Slice-of-Day Framework – Dividing the day into 24 “slices,” with capacity values determined by observed production exceedance levels.

These methods help align capacity valuation with how resources actually perform during critical periods, and the resulting analysis provided monthly ELCC values for solar and wind, hydrology-adjusted ELCC for hydro resources, and updated derates for thermal plants, creating a more accurate and transparent view of how each technology supports reliability.

Updated Default Rules and Planning Margins

PLEXOS® simulations now underpin CAISO’s proposed approach to default rules and planning reserve margin (PRM) methodologies. These refinements ensure consistent, data-driven standards across the balancing area and provide a shared analytics foundation for all LRAs. By grounding these updates in probabilistic analysis, CAISO can better align planning margins and default rules with observed reliability risk rather than static assumptions.

Looking Ahead with Scenario Planning

CAISO also uses PLEXOS® for multi-year scenario analysis. Looking five, ten, and fifteen years ahead, the organization aims to understand how portfolio evolution affects system adequacy. Long-term scenario analysis is essential because rapid changes in resource mix, weather patterns, and generator retirements can create reliability gaps years before they appear in operations. These studies evaluate:

• The grid’s ability to meet reliability targets as wind, solar, and storage overtake thermal capacity.
• The reliability impacts of natural gas retirements, which currently provide critical flexibility during the evening ramp.
• The adequacy of ramping and duration attributes needed to maintain reliability through the clean energy transition.
  
  

A Data-Driven Approach to Reliability 

Through its use of PLEXOS®, CAISO has gained a powerful, data-based understanding of how different resources perform under stress and how best to plan for an evolving grid.

• Improved Accuracy and Insight
  PLEXOS® enables CAISO to simulate realistic system conditions and evaluate how resources behave during critical hours. This produces more accurate measures of Effective Load Carrying Capability (ELCC) and helps operators understand the true reliability contribution of each technology across time and geography.
• Better Coordination and Policy Alignment
  Modeling outputs now inform decision-making with state and local partners, including the CPUC and the California Energy Commission (CEC). These insights shape procurement policies, guide storage dispatch strategies, and align planning across multiple agencies.
• Transparency and Consistency
  CAISO’s updated framework replaces outdated static assumptions with clear, evidence-based metrics. Probabilistic analysis provides a transparent view of system performance and enables consistent capacity accreditation across all regulatory authorities.
• Confidence in the Clean Energy Transition
  With PLEXOS®, CAISO can assess how future resource portfolios perform under different market and weather conditions. This forward-looking capability ensures California’s energy transition proceeds with the same focus on reliability that has long defined CAISO’s mission.

Building a Reliable Clean Future

CAISO’s use of PLEXOS® represents a major step forward in how system operators can plan for a renewable grid. By moving from static planning to probabilistic, data-driven modeling, CAISO can anticipate risk, quantify uncertainty, and make informed decisions with confidence. This forward-looking modeling capability allows CAISO to identify future reliability needs early and guide coordinated planning across agencies.

With this modern approach, CAISO continues to lead the industry by demonstrating that reliability and evolving resource portfolios can be addressed together through better modeling, strong insight, and smarter planning.