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Application: Battery Storage

7000-hour rule

“Grid-serving customer behavior” in the sense of the 7000-hour rule outlined in the German electricity grid charge regulations (StromNEV § 19) presents an opportunity for many businesses: Industrial companies that use battery storage units and practice smart internal energy management can benefit from considerable savings potential in certain circumstances.

The more uniform their reference curve is, the more favorable the conditions for large industrial companies seeking to obtain electricity. An even reference curve ensures the optimum, most economical utilization of energy supplier or grid operator networks and resources, because the entire infrastructure from generation to distribution to the end consumer connection must always be designed for maximum performance.

The more constant the supply, the better the economic utilization of the infrastructure. The metric used for this is the annual full-load hours (AFLH). It is calculated by dividing the total annual energy output by the full-load power. The theoretical optimum for this figure would be 8760 hours (i.e. the total number of hours annually in terms of energy economy). This would mean full utilization and a constant supply without any downtime.
In practice, the ‘magic’ limit of 7000 annual full load hours is the number from which the supplier considers an electricity consumer to serve the grid so well that it must no longer pay the published grid fees per kW and kWh included in the energy price for this reference year. As a rule, customers can save 80 to 90% of the total grid fees to be paid or agree on these individually with their grid operator. This rule is of particular interest when a storage system is used. In some cases, a storage system can pay for itself in less than a year if it allows customers to apply for these individual grid fees.

Flexible electricity marketing

Historically, prices for primary control power have been very volatile, meaning that storage operators are always looking for other similarly attractive business models. One very obvious approach would be to use the constant fluctuations in electricity prices in the grid in order to add value or earn money with storage management. Every electricity trader who sells electricity in a balancing group must “cover” these quantities in good time, i.e. buy the same amount of electricity in good time. This is done either through long-term, day-ahead, hour-ahead or even more short-term contracts. The volatility and inaccuracy of forecasts for renewable sources of energy in particular, as well as unforeseeable statistical fluctuations, can lead to short-term oversupply or bottlenecks, which are then reflected in major price fluctuations.

The more short-term electricity is traded, the greater the price fluctuations. The storage operator will then attempt to buy cheap electricity in good time, return it to the market at the most attractive prices available and exploit this difference as often as possible. Naturally, this can only be ensured by automatic control and marketing mechanisms. Recent studies have shown that this arbitrage or intraday trade cannot yet replace the still widespread model of primary control power. However, evolving market design and individualized tariff models could cause this to change rapidly.

Peak shaving

The fees for the use of the grid by large consumers typically comprise individual energy prices and service prices. The costs to be borne by the grid customer for the power are calculated based on the highest peak load drawn in a year. The energy prices refer to the power that is drawn from the grid. These fees are referred to as grid fees because they are used by the grid operator to pass on the costs of grid operation and expansion to all customers.
By using a storage system, a company can limit the maximum supply peaks within a year and thus save a considerable amount on power prices. In many cases, peak shaving is the economic basis for storage system use and therefore also the basis for refinancing.
This can impact industrial companies, but public works like municipal utilities can also reduce their own grid load by using a storage system.

We can use our proprietary simulation tool Peak Save to quickly create a detailed potential analysis for your company. We use your individual load profile as the basis for our analyses. You usually receive your load profile with a resolution of 15 minutes from your energy provider.

With the Peak Save analysis, you receive a comprehensive, vendor-neutral expert opinion with a recommendation for a storage system that has the optimum sizing parameters for the respective scenario or use case. Furthermore, the cost-effectiveness of this system is precisely predicted for the given application.
• Battery capacity required
• Power electronics required
• Investment costs
• Return on investment
• Electricity generation costs

Intelligent energy management

Energy management is an essential component of a state-of-the-art, sustainable energy supply. Innovative systems ensure the optimum use of self-generated energy. Auch der Verbrauch wird so gesteuert, dass Ihre Stromkosten ohne Komforteinbußen deutlich reduziert werden.Consumption is also managed to significantly reduce electricity costs without any loss of comfort or convenience.

The iEMS energy management developed by ju:niz Energy forms the interface between energy generation systems (e.g. photovoltaics) and storage systems on the one hand and the operational processes up to the integration of external systems (e.g. charging stations for electric cars) on the other hand. Intelligent and flexible control strategies optimize all energy flows and thus significantly improve overall economic efficiency and the environmental balance.

A growing share of renewable energy contributes to a more volatile price structure in the markets. Targeted trades make it possible to store electricity in a storage system temporarily when a surplus of renewable energy on the market drives prices down. Whenever there is an energy shortage, the storage system then releases this energy back to the grid and benefits from the price differences.

However, a storage system is only as good as its operational strategy. All ju:niz Energy storage systems use proprietary software. This allows the same kilowatt hour of storage to be used more than once and increases the profitability of the installed storage capacity. The integration of intelligent forecasting strategies allows for better utilization of installed capacity and performance while increasing the life of the storage system. Thanks to an intelligent preview, the charging state is always kept in the optimum operating range for as long as possible.