Winter Grid Tariffs Are Coming: How to Turn Cost Spikes into Profit

Grid tariffs in a nutshell

In essence, grid tariffs are the fees used to cover the cost of operating and maintaining the electricity network. They are determined by each network operator (transmission and distribution) within a framework set by the Energy Markets Inspectorate (Energimarknadsinspektionen in Sweden), which regulates allowed revenues, ensures the tariffs reflect the costs of providing network services, and encourages efficient use of the grid.

Grid tariffs are generally divided into two main cost components: the energy fee and the power fee. The energy fee is charged based on the total amount of energy consumed over time, measured in kilowatt-hours (kWh). The power fee reflects the cost of peak demand – the highest level of power an energy asset draws from the grid during a given period.

As the days grow colder and darker, it becomes more expensive to utilize the electricity grid.

Why winter times cause concerns

As the days grow colder and darker, it becomes more expensive to utilize the electricity grid. The electricity demand is higher, the grid stress is more significant, and naturally, DSOs push higher tariffs to reduce the risk of overloading the network. These rising costs raise uncertainties for BESS owners, who need to adapt their operation to account for more cost variability and potential loss of profits.

Understandably, some BESS owners are also reluctant to participate in power intensive markets like wholesale (day-ahead and intraday) and mFRR, where the revenue potential is high – but where high power usage risks costing more than it earns. This grows especially worrying in the more expensive winter months.

The answer to the tariff headache

While grid tariffs have been tricky to account for in the past, it is now being handled with precision thanks to the latest technology. With highly advanced algorithms controlling battery systems, tariffs are carefully incorporated into the trading strategy. In essence, this means a wide range of data and calculations – including historical power data, grid tariff prices, peak structures, and expected peaks – is combined with variable market data already used in optimization: weather forecasts, behavioral models, market depth, and more.

Consequently, by training algorithms this way, the BESS volumes can be allocated with accuracy to whichever market minimizes grid tariff exposure while maximizing profits.

How algorithms unlock value

So how does it all work in practice? A 1 MW/MWh BESS, trading only on FCR, can be used as a basic illustrative example of how grid tariffs affect trading decisions. Two optimization models are tested: One that ignores grid tariffs and one that accounts for them. The analysis is run for several different grid tariffs and different months, assuming full knowledge about market clearing prices and an optimization horizon of one month.

How a tariff-aware optimization impacts trading allocation in the FCR markets.

As shown above, there is a clear difference in market allocation between the two models. When grid tariffs are included in the decision-making, the volume allocated to more energy-intensive markets such as FCR-N decreases, while more volume is shifted to FCR-D markets.

As FCR-D prices have, in recent times, been trending below FCR-N prices, this leads to a decrease in revenue. However, tariff-induced costs are reduced even more, resulting in an increase in profit as shown in the graph below.

With grid tariffs incorporated in the trading decisions, revenue is deliberately reduced to allow for a greater cost reduction, ultimately generating more profit.

Turning trading complexity into clarity

While the FCR markets are useful for illustrating the concept of tariff-aware optimization, other markets require even more advanced modeling to unlock profit. Wholesale markets (day-ahead and intraday) demand careful consideration of the power fee, where the cost is often set by the highest power peak(s) over a full month.

By using algorithmic models accounting for the potential value a full month of trading within a given peak can bring, traders can be proactive when deciding how much power to utilize in a given day – striving for the most profitable outcome for the month as a whole. Ideally, this “optimal peak” is set early in the month: too low, and they lose potential revenue; too high, and they risk never recuperating the cost.

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In wholesale markets, the “optimal peak” of the power fee is ideally set early in the month. Too low, and potential revenue is lost. Too high, and the initial cost may never be recovered.

In the mFRR markets, complexity grows further. In the mFRR EAM (Energy Activation Market), uncertainties around when and how many times an asset will be activated come into play and make peak tariff costs especially hard to anticipate. Managing these variables to optimally balance revenues and costs requires sophisticated pricing strategies and operational flexibility beyond what most actors today can offer, but can be unlocked with algorithmic trading.

The forefront of energy trading

The energy trading landscape is crowded with actors who share similar ideas, but who vary in their ability to deliver long-term results. One thing, however, is certain: The actors with the most advanced algorithms, capable of predicting and capturing maximum value from grid tariff patterns, will gain an upper hand – creating greater stability and profitability for their partners as the days turn darker and colder.

As a key component of its market-leading algorithms, Flower has long included grid tariffs in its trading strategy. The benefits are well-established: increased profits, greater precision in asset optimization, and an improved overall business case for BESS owners.

Get in touch to learn how Flower can maximize the value of your battery systems.