Energy Storage Management is Teamwork — The Role of the Optimizer

Energy storage management is a complex process that requires collaboration between different entities. Four key units function within this framework:

1. Storage Owner — providing infrastructure and investing in development.
2. Trading Company — responsible for energy trading in wholesale markets.
3. BSP (Balancing Service Provider) — an entity providing system services, which in current market conditions can generate 2-3 times greater profits than ordinary arbitrage in the energy market.
4. Optimizer — a unit dealing with algorithmic management of trading orders in the System Services Market and Energy Arbitrage.

In this article, we will focus on the role of the optimizer, which plays a key function in storage management, combining technical, economic, and operational aspects to achieve the best financial results (over 40% better compared to an optimal but fixed operation plan).

The Role of the Optimizer

The optimizer is the entity responsible for efficient energy storage management through intelligent control of its operation. Its task is to maximize profits through:

1. Optimizing orders for Fixing 1 and Fixing 2 — the day-ahead market, where decisions are made about which hours the storage should charge or discharge.
2. Optimizing orders for system services — in this area we deal with auctions, so the offer may not be accepted (which is not necessarily negative, because by setting a price, we ensure a minimum revenue in that hour).
3. Reoptimization — divided into two cases:

• Forced — when the TSO activates the storage or fails to activate it contrary to planned assumptions, which requires strategy adjustment through additional energy trading in the intraday market.
• Economic — when market conditions favor correcting the storage operation schedule, e.g., shifting the charging cycle by 15 minutes can generate additional profit.

 

Why is the Optimizer’s Role Complicated?

The optimizer’s role is not easy as it requires considering many technical, economic, and market factors, and additionally, this must be done at every moment in time.

Technical Parameters of the Storage

The optimizer must take into account the technical specification of the storage, including:

• Charging and discharging efficiency.
• Minimum activation time.
• Maximum capacity and net power.
• Warranty agreements with the manufacturer, which may limit the maximum number of daily cycles.
• Continuous monitoring of the storage’s state of charge to avoid overcharging or excessive discharging.

Limitations of Trading Companies and BSP

Optimization requires cooperation with trading entities that may have their own operational constraints:

• If the trading company or BSP do not have automatic orders in the intraday market, the response time to market changes is delayed.
• Lack of automation in submitting offers for system services causes a loss of flexibility in reoptimization, especially if the trading company or BSP cannot trade energy at night (due to the absence of traders).

Energy Price Prediction for Coming Days

Decisions made by the optimizer must consider price forecasts.

• Trading is done day-ahead, but today we must decide in what state we want to end the day. This means the necessity to look at least one day into the future to ensure the best results for the next day.

Price Prediction for Balancing Services Reservation

The balancing services market is more complex than the energy market:

• Upward and downward reservation prices are different – unlike the price for energy.
• There isn’t just one system service; here we have FCR, aFRR, and mFRRd.
• These additional market dimensions require detailed modeling and prediction of various scenarios.

Real-time Operation

The optimizer must work in real-time:

• The algorithm constantly monitors the market and storage status.
• It recalculates optimal decisions in response to changes.
• It must immediately react to activations or lack of assumed activation by the TSO and to changing intraday prices to not miss opportunities.
• Additionally, it must consider potential Calling Periods in the Capacity Market if the storage won an auction and the TSO announces such a period.

Amount of Data Processed by the Optimizer

Every day, the optimizer analyzes huge amounts of data, including:

• Energy prices in the day-ahead and intraday markets.
• Auctions for system services and their results.
• Storage state of charge and technical parameters.
• Weather conditions (important for renewables, which affect energy prices).
• Historical price patterns and predictions of future values.

The number of possible scenarios that the optimizer must consider is comparable to the number of all possible chess games, meaning that the optimizer algorithm plays all possible chess games every day and must choose the best strategy against a sometimes unpredictable opponent, which is the market.

Summary

Effective energy storage management is not a simple matter and requires close cooperation between many entities and an advanced approach to optimization. The key role is played by the optimizer, which combines technical, economic, and market aspects, making decisions in real-time and maximizing profits from various segments of the energy market.

At VESS, a group of experts is involved in creating and daily improving strategies depending on market conditions and adapting them to the characteristics of the storage and trading company. Our mission is to be a bridge between storage owners and the BSP and trading company to bring the storage greater revenue (sometimes even 40% more than a simple strategy). Through advanced analyses, we help our clients not only choose operationally the best strategies but also predict what the potential profit from energy storage will be over the next 15 years.