Power Portfolios: Reducing Risk and Optimizing Value, Sustainability

February 8, 2024

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The reality of weather as the new fuel driving power market volatility necessitates an active approach to energy portfolio risk management. In a recent Portfolio Management webinar, Scott Wrigglesworth, Vice President of Operations & Strategy for Ascend Analytics, and Dr. Carlos Blanco, Managing Director of Risk Management & ESG for Ascend Analytics, discuss how Ascend active portfolio management facilitates well-informed decisions that optimize value over time, reduce financial risk, and improve the ability to monitor progress toward environmental goals.

Key Takeaways

Traditional power portfolio management practices, that focus only on physical volumes, expose organizations to greater financial risk. Ascend active portfolio management reveals value opportunities and/or reduces risk, resulting in more stable cash flows, more confidence in measuring progress toward environmental goals, and rate stability.

  • Today’s power portfolios must capture the value of 24x7 carbon-free and hourly nodal emissions, especially as hourly pricing eventually becomes applicable for megawatt-hour (MWh) credits or carbon tonnes associated with energy products.
  • With weather as the new fuel, optimally managing portfolios requires assessing multiple risk dimensions over different periods using high-resolution energy resource management tools, such as Ascend Analytics’ PowerSIMM™ software platform, that capture meaningful uncertainty in ways that surpass traditional risk models.
  • Using long-term flow metrics, such as Gross Margin at Risk, provides critical value by facilitating sound power portfolio management decisions that derive from insights into financial, environmental, and physical risks over time.

Ascend Active Portfolio Management – The New Lens as Weather Becomes the Fuel Driving Power Market Volatility

In today’s energy industry, weather poses serious challenges to traditional energy risk management models. Traditional portfolio management practices often focus solely on physical volumes, in which stakeholders seek a 'net position zero' where long and short positions are matched on a volumetric basis. Risk management practices in this context usually take the form of complementary portfolio elements such as hedges, offtake agreements, or power purchase agreements (PPAs). While 'net position zero' approaches may provide a balanced physical position, they are not optimal from a financial risk or environmental perspective, both of which are critical in the context of the energy transition.

Ascend active portfolio management moves beyond a simple focus on physical risk and seeks to reduce risks related to financial and environmental goals. This approach requires rigorously modelling key uncertainties and ever-evolving market dynamics to provide analytics that allow for timely and well-informed decisions regarding power portfolio management. Using this approach, organizations can quickly understand inefficiencies in their portfolio structures, and make decisions that bring them closer to aligning with budget or environmental expectations. As Mr. Wrigglesworth noted, Ascend active portfolio management produces several benefits, including more stable cash flows, more confidence in the ability to monitor progress toward environmental goals and more stable electric rates.  

The Importance of Capturing Meaningful Uncertainty

Optimally managing the physical and financial components of energy portfolios requires an assessment of multiple risk dimensions over different periods. Increasingly, organizations must answer critical questions that go beyond physical position, including those related to earnings and cost fluctuation over time, financial forecast uncertainty, counterparty credit exposure, potential collateral calls, the financial implications of extreme weather events, and risks related to failure to meet clean energy objectives. Effectively answering these uncertainty-related questions requires a higher-resolution analytic lens, often in the form of energy resource planning and risk management software, than the one offered by traditional portfolio risk management models.

Using the Ascend Analytics PowerSIMM software platform, for example, organizations can capture meaningful uncertainty in ways that surpass traditional models. According to Dr. Blanco, four components prove particularly important in capturing meaningful uncertainty:  

  • Realistic, integrated, and verifiable scenarios that integrate key fundamental drivers of supply and demand inclusive of the effects of weather, renewables, load, and price.
  • An accurate representation of the main attributes of physical and financial portfolios, such as assets, contracts, hedges, operational constraints, and physical constraints.
  • The use of dynamic risk simulations that incorporate power portfolio responses to more extreme market and weather conditions.
  • An integrated analysis that dynamically captures the response to principal risk factors such as weather or commodity price swings across the portfolio.

Four Key Metrics for Active Portfolio Management

Dr. Blanco discussed four key metrics for management of power supply and production risk. The first, Gross Margin at Risk (GM@R), as illustrated in Figure 2, serves as a 'flow' metric, which offers meaningful long-term insights that facilitate well-informed real-time decision-making. Often requiring millions of calculations to produce distributions that meaningfully capture the variability of an energy portfolio, GM@R provides an hourly or even sub-hourly view of everything that takes place within the different portfolio component levels. This metric allows stakeholders to evaluate and understand the risk-reward trade-offs of incremental portfolio changes, such as the addition of PPAs or hedges, and to design optimal hedges that meet financial and environmental goals.

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Figure 2: Gross Margin at Risk (illustrative)

Dr. Blanco introduced mark-to-market (MtM) and Value-at-Risk as the second and third risk metrics. Short-term risk metrics such as MtM or 'fair market value', which value portfolio positions relative to current forward market value prices or variability in these prices over a limited window of days, respectively. Because MtM and Value-at Risk are value metrics that don’t consider cash flows over time and delivery conditions of physical settlement, their of secondary priority to Gross Margin at Risk. However, a more useful approach involves the use of hybrid or cumulative portfolio metrics, which examine cumulative value and flow exposures up to a point in time, and which can combine prior-to-delivery and during-delivery portfolio impacts to account for potential changes. Dr. Blanco noted that Ascend helps customers develop and implement custom hybrid and cumulative metrics, including potential future exposure profiles, potential margin call profiles, and potential financial reserve level variability profiles. Finally, Dr. Blanco discussed stress tests and scenario analyses, as shown in Figure 3, which model plausible shocks to key power portfolio drivers to evaluate both the severity, in terms of impact on the portfolio, and likelihood of occurrence.

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Figure 3: Scenarios incorporate plausible shocks to key portfolio drivers

Navigating the Efficient Frontier – Maximizing Return, Reducing Risk

To provide an example of how Ascend active power portfolio management can provide a differentiated high-resolution lens to asset future risk and return, Mr. Wrigglesworth provided an example independent power producer (IPP) case study that presented three solar+storage scenarios, including a merchant resource, a PPA, and a 'block+' resource that sold block and attribute elements in separate transactions. As shown in Figure 4, the comparison of risk and return for each resource provides an idea of the 'efficient frontier' as it relates to value, with Ascend active portfolio management realizing the preferred risk return levels of the upper lefthand corner. Figure 5 provides an alternate view of the same portfolios, allowing risk to be viewed as the distance between the expected result and the tail of the distribution.

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Figure 4: Efficient frontier in solar+storage scenarios

 

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Figure 5: Probability distribution of Year 1 range of margin uncertainty

Ultimately, Mr. Wrigglesworth encouraged energy industry stakeholders to think deeply about whether their models can meet today's energy portfolio management challenges. "Do your tools use traditional risk management principles or are they dealing with higher-resolution hourly and sub-hourly views?" he asked. "Are you considering changes in the market that will transpire over time? Do you have the tools needed to understand how changes made today will impact you down the road?"

PowerSIMM™ Portfolio Manager: Optimal Portfolio and Risk Management

PowerSIMMenables users to make portfolio management decisions that increase cash flow certainty, improve position analysis, and optimize hedge design across physical, financial, and REC portfolios. By integrating physical dimensions of weather and asset operations concurrently with market price dynamics, PowerSIMM captures both market expectations and fundamental variables of demand, supply, and transmission flows to determine optimal hedge strategies, and maximize value and mitigate risk.

About Ascend Analytics

Ascend Analytics, an innovative leader at the forefront of the energy transition, offers advanced software and consulting services that capture the evolving and real-time dynamics of energy markets. The company provides its customers with optimized and comprehensive decision analysis that covers everything from long-term planning to real-time operations in the electric power supply industry.

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