The Energy Authority (TEA) provides power trading, gas trading, and portfolio management services to public power utilities across the United States. Serving municipals, joint action agencies, and an increasing number of electric cooperatives, TEA operates in nearly every organized U.S. power market.
Supporting public power entities across diverse markets requires a rigorous and adaptable analytical framework. Volatile commodity prices, evolving generation portfolios, renewable integration, load growth uncertainty, and extreme weather events all introduce material financial risk. To manage this complexity, TEA leverages Energy Exemplar’s PLEXOS® platform to conduct advanced risk analysis across both medium-term and long-term planning horizons.
Public power utilities must manage risk on multiple time horizons. In the midterm, exposure stems from commodity price volatility, load variability, renewable output fluctuations, and forced outages. And, in the long term, capital investment and retirement decisions must be made under uncertainty regarding fuel prices, demand growth, renewable penetration, and structural market changes.
Traditional deterministic modeling provides expected-value projections but does not quantify the range of possible outcomes. For TEA’s clients, this limitation constrained decision-making. Utilities required clear answers to critical questions:
To address these needs, TEA implemented a probabilistic modeling framework within PLEXOS® capable of simulating hundreds of correlated outcomes, quantifying downside risk, and evaluating portfolio resilience under extreme conditions.
Having established a robust stochastic framework for operational and hedge analysis, TEA recognized the need to apply the same risk discipline to long-term resource planning. This evolution brought probabilistic insight into 20-year investment decisions.
In the midterm horizon, TEA generates approximately 700 stochastic iterations of key variables, including:
Power prices
This iteration count balances computational efficiency with stable estimation of extreme outcomes.
Each stochastic draw produces a unique set of model inputs that are fed into utility-specific PLEXOS® models. Unique forced outage draws are incorporated into each simulation, allowing operational uncertainty to be reflected in dispatch outcomes.
PLEXOS® performs hourly dispatch optimization across all iterations, producing a distribution of financial results.
From these distributions of outputs such as net power costs, which includes generation costs, load purchases costs, and generation revenues for utilities operation within ISOs, TEA develops measurable risk metrics.
Risk is typically measured using “At-Risk”– the different between the 95th percentile outcome and the mean but also use expected shortfall which is the average of all iterations above the 95th percentile.
This framework enables utilities to evaluate both expected performance and downside exposure.
A primary application of midterm stochastic modeling is evaluating prospective financial power or natural gas hedges.
After generating the distribution of net power costs, TEA layers in proposed hedges and measures their impact on risk metrics. The objective is to determine whether the hedge narrows the cost distribution, reduces value at risk, or aligns with the utility’s risk tolerance.
Hedge effectiveness varies depending on existing generation structure and existing hedge positions. This distribution-based evaluation replaces intuition with quantitative evidence.
Long-term integrated resource planning (IRP) historically relied on deterministic modeling to identify optimal capacity additions or retirements over a 20-year horizon. Scenarios might reflect differing assumptions regarding:
While this approach supported expected cost comparison, it did not quantify financial variability across portfolios.
To enhance long-term decision-making, TEA extended its stochastic framework into IRP analysis.
To embed risk transparency directly into long-term planning decisions, TEA integrates stochastic simulation into its traditional IRP modeling process.
The enhanced workflow consists of:
This approach produces quantile ranges, mean outcomes, and outliers for each scenario, enabling direct risk-adjusted comparison.
By integrating stochastic simulation with PLEXOS® across both Medium-Term and Long-Term workflows, TEA delivers measurable value to public power clients:
Post-processing tools make complex modeling outputs accessible beyond technical modeling teams, supporting broader strategic and financial decision-making.
This integrated approach ensures that risk is quantified consistently across operational and planning horizons.
Public power utilities operate in markets defined by uncertainty. Commodity volatility, evolving resource mixes, and extreme events require disciplined, forward-looking analytics.
By integrating stochastic simulation with PLEXOS® across both medium-term operations and long-term resource planning, The Energy Authority has built a unified risk analytics framework. From hedge evaluation to IRP portfolio comparison and stress testing, TEA delivers risk-adjusted insight that strengthens financial resilience.
The result is a structured, data-driven approach that aligns strategic planning with quantified risk—enabling public power utilities to make confident decisions in an increasingly complex energy landscape.