Predictive battery analytics in the energy sector

Battery storage is an elementary component of the energy sector. However, they are complex systems that require special attention. The overriding goal of many operators is therefore to maximize the profit possible from storage without taking on additional risk. This is where battery analytics can help.

Today, more than 25 GWh of stationary battery storage systems have already been installed worldwide. It is estimated that installed capacity will grow to up to 900 GWh by 2030. Battery storage is ideally suited to meet the challenges of the energy transition for a number of reasons. Unlike most other power plant technologies, battery storage systems can not only deliver energy, but also store it. And all this in a unique reaction time of only a few milliseconds. These properties are not only theoretically suitable for numerous use cases, both front-of-the-meter and behind-the-meter.

In practice, however, in addition to the still high acquisition costs, numerous new challenges arise due to the complexity of batteries and their aging behavior. Three of these challenges are the increasing complexity due to multi-use applications, warranty management and battery oversizing. It is precisely these difficulties that can be addressed by battery analytics – making battery storage an even more attractive technology.

Marktübersicht stationäre Energiespeicher


Low profitability and long payback period – multi-use applications are key
The low profitability and long payback period of battery storage are two of the fundamental challenges facing operators. High acquisition costs and fluctuating energy prices that are difficult to forecast, complemented by falling prices on the primary control reserve market in recent years, make the issue explosive. It is clear to many operators: without multi-use applications it will not work.

In particular, the complex ageing behaviour of batteries makes it difficult to optimise the most profitable operating strategy across different uses. Many operators therefore either shy away from multi-use applications or operate multi-use, but without being aware of the aging costs. Continued use of the TWAICE Operating Strategy Planner solution can add value to the customer in a number of ways.

Taking battery aging into account in operational strategy planning helps the operator to better balance between different strategies and schedules. This allows them to choose the optimal operating strategy for their business case between expected revenue and battery life.

For different operating modes, the operator can directly incorporate an estimate of the aging cost per cycle and energy quantity into his market-side optimization and pricing. This makes it easier to identify profitable transactions and increase the profitability of different types of operations such as intraday trading or primary control power.
In addition, the operator receives the security of being able to use the storage for the selected strategy for the planned period of time – the risk of premature storage failure can thus be minimized.

More efficient warranty management through battery analytics

Integrators have the task of having to bundle a large number of supplier guarantees into one system guarantee for the end customer. This is not only in the form of a conventional product guarantee (the storage unit no longer functions), but usually also in the form of a performance guarantee (the storage unit delivers a certain performance over a certain period of time, for example it still has at least 80% of the State of Health after ten years [SoH]). In the event of damage, battery analytics provide the integrator with all the necessary data at the touch of a button, enabling him to process the damage efficiently, minimise risks and thus save money.

Storage operators also have the option of setting warnings to prevent operation of the battery storage outside the warranty conditions or fundamentally harmful handling. For example, particularly high temperatures, particularly many cycles, but also certain discharge depths can be avoided.
As a provider of predictive battery analytics, TWAICE creates trust as a neutral authority and thus the necessary basis for partnerships with Munich Re on insurance services and TÜV on residual value determinations.

Oversizing of batteries and resource-intensive development – optimizing storage with simulation models

However, there is potential for optimisation not only in operation, but already in development. The keyword oversizing is probably known to every battery engineer. In order to ensure that the batteries deliver the agreed power over the entire service life, the storage units are designed to be larger than actually necessary due to the expected ageing or the associated – but unpredictable – loss of capacity. Combined with resource-intensive development, oversizing leads to battery development that is more costly than it should be.

Battery simulation models, such as those contained in the TWAICE Battery Model Library, are ideally suited for optimally designing storage systems depending on the load profile, performance and storage capacity. In this way, the cost of capital can be significantly reduced. Battery analytics and stress factor analysis can be used to closely monitor storage devices that are already in use. Conclusions from the analyses help operators to design the next generation of storage systems even better.

The future of the energy sector is now inconceivable without batteries. Although they are complex, they do not have to represent non-transparent risks. With the help of holistic battery analytics, players along the value chain – operators, owners and project developers of battery storage systems – can meet their challenges and optimally design and operate the storage systems, thereby generating the maximum yield from the storage systems.