Integrating flexible assets into trading portfolios: from optionality to strategy

We're entering an era of dynamic strategy in energy portfolio management, with flexible assets leading the charge. Technologies such as pumped hydro, demand response and, more crucially, batteries allow energy producers to bank energy when prices are low and sell when prices are high.

While this could become a lucrative area for traders, it's key that portfolio managers understand the optimisation logic for flexible assets, as well as the risks associated with trading in this environment.

We'll take a look at how linking flexible assets to full-portfolio optimisation strategies can help traders achieve more successful trading outcomes.

We aim to define the role of flexibility for portfolio managers and to show integration methods useful for profitable trading strategies.

Role of flexibility in portfolios

We can view flexibility as a connection between the stability of a portfolio and the volatility of supply and demand.

Optionality and responsiveness

Flexibility allows traders to make trading moves without being obligated to do so, which can be a benefit in volatile energy markets. We can look at them the same way we might look at financial options: the asset holds value both at its current price and its future potential.

Speed to market is crucial: automated decision-making eradicates human decision-making time, making moves before the market and conditions change.

Enhancing agility

Rather than just reacting to market events, agility enables traders to influence the market they trade in. This can be done by using strategies such as dynamic rebalancing, which draws on data detailing weather forecasting, geopolitics and demand surges. Advanced analytics enable decision-making without human intervention, automating dispatch to make moves when market conditions are ideal without traders slowing down the process. Agile portfolios enable these moves across a few markets through strategies known as cross-commodity hedging.

Combining assets with market exposure

Flexibility allows asset revenues to be combined with market revenues, such as grid services, day-ahead wholesale and time arbitrage. Combining multiple assets, for example, solar and wind, allows variability to be smoothed out and enables structural hedging.    

Forward hedges plus storage

Profit can be increased by optimising both capacity and energy. This is done via value stacking, forward hedging evaluation, intraday market data and market exposure.

Foresight is at the heart of these strategies: assets are optimised against forward contracts, but allow wiggle room for hedges in the face of changing conditions. We can lock in base revenue rather than play it safe on tail risk, as forward hedges can stabilise, while allowing some flexibility thanks to the counterbalance of battery storage.

Optimisation strategies

There is no obligation to buy or sell energy when dealing with flexible assets and so strategy optimisation is the link between hypothetical models and the genuine trades that take place.

 Scenario-based decisions

Traditional forecasting methods have no real place in flexible scenarios. This is because energy markets are too volatile and subject to movement.

One type of forecasting that is more appropriate is

Stochastic programming, which uses multiple price paths and Monte Carlo simulations instead of one forecasted price curve, to identify more relevant trading strategies.

We can generate these models to identify price spikes using fundamental and meteorological data, such as renewable generation, regional demand shifts and weather forecasts.

Dynamic allocation

Asset allocation has to change and evolve with market volatility. We implement dynamic allocation strategies such as Model Predictive Control, which recalculates a strategy based on refreshed, real-time data.

AI can also be utilised, with algorithms developed from information gleaned from market behaviour. Risk management strategies can utilise data such as Conditional Value at Risk or Value at Risk to adjust to volatile events.

Risk considerations

Flexible energy assets can smooth volatility in renewable energy generation, but utilising flexible energy entails accepting and overcoming financial risks, technological constraints and market saturation.

Technology constraints

Legacy IT infrastructure isn't able to keep up with the real-time data exchange required by trading portfolios dealing with flexible assets, for example, to respond to the intraday or ancillary service markets. Batteries are subject to limitations related to state of charge (SOC) and degradation.

Market saturation

When renewable energy generation is high, numerous flexible assets charge simultaneously, causing congestion on the local network. The ancillary services market can also become saturated, with quick reserve solutions all bidding for the same grid requirements.

Strategic implications

We can leverage the volatility of the flexible assets market by identifying short-term price hikes or negative pricing periods and linking them directly to assets.

We can also participate in multiple markets, including ancillary and wholesale markets, in a move called multi-market revenue stacking.

Competitive advantage

Only trading firms that can operate at automated, algorithmic speed can remain competitive. This is usually achieved by utilising AI or machine learning, which can monitor and act on market signals Holistic portfolios optimise behind-the-meter assets, virtual power plants (VPPs) and wholesale contracts, which creates a stronger, aggregated offering.

Portfolio evolution

Portfolio evolution goes through three distinct phases. Firstly, volumetric management, which balances supply. Next, AI technology bids over multiple intraday, day-ahead and ancillary markets. Lastly, all assets aggregate to create a unified Virtual Power Plant.