What do you need to profit from flexibility? | enspired

Five steps to market your flexible assets

One of the hottest topics in energy trading today is flexibility marketing. Energy providers and public utilities can and should make the most of their flexible assets to maximize their revenue potential and provide grid stability. The first decision they face is whether they should set up their own algo trading operations or go with a service provider who trades on their behalf. This decision can have major financial and operational impacts. 

Nearly every energy provider has flexible assets, which include most forms of power plants and energy storage facilities, as well as demand-side management and even electric vehicles. There are many options to profit from flexibility but the most common today are balancing and continuous intraday markets. For additional information, learn how the power market works in Europe.

Now comes the tricky part. If you plan to manage your own trading through third-party software, you have to understand that it’s not simply a plug-and-play scenario. And building your own software is even more complex. Successful trading operations require:

1. Market access
2. Automated trading setup
3. Data and quantitative analytics
4. People with the right skills
5. End-to-end organizational support for high-volume trading

1. Market access

To start trading on the intraday market, you need formal market access. This is not for the faint of heart, as the process can take four to six months and involves the following steps:

• Obtain an Energy Identification Code (EIC), market-specific codes (if applicable) as well as registration with the Agency for the  Cooperation of Energy Regulators (ACER) and national regulatory authorities. The energy market needs to know who you are!
• Apply for membership with a spot exchange (e.g. EPEX SPOT, Nord Pool), choose your markets, technical setup, and get trader licenses (even if trading is 100% automated).
• Find a clearing bank and apply for membership with the Central Counterparty (CCP) - set up accounts, post collaterals, and agree on limits.
• Register with Transmission System Operator(s) (TSOs) for balancing group(s), sign balancing contracts, provide expected MW & MWh, post collaterals, and implement market communication processes.
• Be prepared to sign lots of paperwork, from Know Your Customer (KYC) documents to Regulation on Energy Market Integrity and Transparency (REMIT) reporting services.

2. Automated trading setup

To take advantage of your flexibility, you need an automated trading solution. With an ever-growing number of products and increasing volatility, today's intraday market can't be managed effectively with manual trading. The majority of transactions on European markets now use APIs, with EPEX  reporting the share at 65% back in 2019 already. This means that a large portion of market participants are using algorithmic trading tools. Human traders simply can’t match the speed of a bot and won't be able to react fast enough when market conditions change.

Several components are needed to perform the core function of automated execution. In the case of purchased software, these are typically provided by the vendor. First of all, you’ll need an API interface to the exchange, which has been thoroughly conformance-tested and certified by the exchange. The intelligence of the system is provided by trading algorithms (codified trading strategies). These make the decision when to buy and sell how much at which price, taking into account influencing factors like market restrictions and technical constraints of the physical power assets. For risk management, you need volume and price limits as well as automated shutoff. Lastly, a user interface is required to monitor trading activities and to configure or customize trading models.

Whether you build or buy, a large number of interfaces is necessary. Automated trading relies on a wide variety of different systems, and since algorithms make decisions based on vast data volumes, you’ll need an interface for each data source. Additionally, your algo-trading system requires communication with your Energy Trading and Risk Managament (ETRM) system, with power plant management, with your scheduling system, and more. A customized internal dashboard helps you monitor and report results. Finally, you need a backtesting environment, fed with the necessary data and evaluation tools, to validate and test algorithms before they go live and make sure they behave as expected. 

3. Data and quantitative analytics

Algorithms are only as smart as the data that feeds them, and successful trading strategies need a big variety, starting with order book and price data. The data comes as part of the market access but needs to be fed to the algorithms. Purchased software supplies the interface, but if you build your own platform, you need to sort everything out yourself. Other fundamental data includes wind and solar forecasts, power consumption and load forecasts, import/export capacities, ancillary service data, and power plant availabilities. To boost algo performance even further, more advanced data may be employed, such as satellite images, infrared imaging of power plants, and magnetic field measurements of interconnectors for real-time grid data.

The key to successful trading is to identify signals that predict price trends, the reasons behind short-term price movements, and the volatility that can lead to significant loss or profit. A trader looks at data to explain market behavior, then forms and tests hypotheses. Why did markets trade up yesterday but stayed level today? Which drivers are causing prices to go up? Is this a valid signal? How often is it correct?

In order to accomplish this level of analysis with automated trading, you need quantiative data analytics. Markets change; a strategy that performs well today might lag behind tomorrow. Signals and the analyses behind them can represent a strong competitive advantage, which makes a system with the ability to process vast amounts of data and test potential signals indispensable to your trading setup.

4. People with the right skills

Automated trading solutions require a team of specialists with skills that the average energy company might not have in place.

Traders, freed from the repetitive work of manual execution, together with quantitative analysts, monitor algo behavior and watch the market in order to develop new strategies. They then work with algorithm developers and data scientists to test and implement these strategies. It’s important to understand that algo trading is a commitment to development: The markets are constantly changing, and trading strategies must evolve to match.

IT support is not such an issue for the trading software itself, since most are now delivered as SaaS, but all the interfaces must be supported and data must be stored, cleaned, aggregated, and made useful for algo development and backtesting.

Risk managers have to understand the difference between algo trading and manual trading so that risk management can be tailored in accordance with applicable policies and compliance frameworks.

Since trading algorithms tend to execute a much larger number of smaller trades than a human trader, the areas of finance and back office will face an increase in transactions that must be reconciled against data from the exchange, clearing, and nominations. They need to prepare for the extra workload in advance.

And finally, even though algo trading eliminated the need for a 24/7 whole trading team, someone still needs to be on call for dispatch and dealing with exchange outages.

5. End-to-end organizational support for high-volume trading

The listed steps require organizational support. Every process in the trading value chain must be aligned with algo tradin. Aspects like power plant dispatch, lead times, and nomination need to be evaluated and possibly re-engineered. A common pain point in algo trading is risk management, which requires precise policies to ensure compliances and effective mitigation methods.

The approval process for new algorithms is subject to very specific criteria, a thorough testing protocol, and a simulation environment. Last but not least, there’s the issue of Profit and Loss (PnL) and incentive structure. Who gets credit for the success of an algorithm?

What's the right flexibility marketing strategy for your business?

The decision of how to market your flexibilities should be made carefully and deliberately. While the advantages of trading on intraday markets are clear, it’s easy to underestimate the effort required and the impact it will have on your organization, especially when you choose to run your own trading infrastructure. As with anything, this isn't about a 100% wrong or right choice; it’s about the compromise between simplicity and control that is most aligned with your strategic goals. The table below gives an overview of available options.

In reality, you don’t necessarily have to trade everything the same way. Many companies use software for some cases but a service provider for others. Power, gas, both? Intraday-only or also balancing markets and auctions? All your assets or just certain ones? There are many ways to distribute your flexibility marketing to suit your needs.

As you can see, implementing algo trading in your organization, whether you purchase software or build your own, can get very complicated. If you are starting from scratch, the full cost can be around €1M/year or more. You’ll also need a team to support it: Enough traders/on-call dispatchers to ensure 24/7 coverage, plus IT resources, at the very least one quantitative analyst, and a data scientist.

One factor affecting the decision might not be so obvious: Providers of trading services are experienced traders themselves. As a result, they can offer valuable advice and knowledge exchange to their customers. This cooperative approach boosts the success of your flexibility marketing initiatives. Monetizing your flexible assets is a wise decision that can deliver significant added value to your organization.

Do you need help with your decision or want to learn more about our solution for revenue optimization?