Large-scale energy storage is already contributing to the rapid decarbonization of the energy sector. When partnered with Artificial Intelligence (AI), the next generation of battery energy storage systems (BESS) have the potential to take renewable assets to a new level of smart operation, as Carlos Nieto, Global Product Line Manager, Energy Storage at ABB, explains.

The global energy sector is in a period of fundamental change, as governments and utility providers begin to make the shifts necessary to pivot to a smart new energy system designed to power our low carbon future more effectively.

This is being driven by the three Ds: decarbonization, decentralization, and digitalization, all of which bring huge opportunities, but also a number of challenges.

Despite the impact of the global pandemic, the share of renewables in global electricity generation was estimated to reach an all-time high of 30 percent in 20211, the result of global efforts to reduce emissions. However, the rising share of renewables, such as wind and solar, in the power mix also poses some limitations.

Solar, for example, will only generate electricity in line with how much sunshine there is and will not match the same profile of the electricity that a site is using. Used in silo, companies are left with having to top-up with electricity from the grid or waste any excess generated.

Adding further complexity is the opportunity for decentralization. The decentralized nature of renewable generation holds the potential for power users to not only produce much of the electricity they need locally, but to use an independent energy system, such as a microgrid, to become self-sufficient.

A microgrid can act as part of the wider grid while also being able to disconnect from it and operate independently, for example, in the event of a blackout, presenting a huge advantage for mission critical applications, where even a moment’s downtime can entail huge operational and financial implications.

However, while a decentralized approach makes for a more resilient and secure system, it must be carefully ‘synced’ to ensure stability and alignment between generation and demand, and the wider central network.

Achieving this and meeting decarbonization goals requires digitalization, in the form of energy management software (EMS). The most advanced EMS allows businesses to optimize the generation, supply, and storage of renewable generation according to their requirements, the market and other external factors. Some companies will even go beyond self-sufficiency and leverage a lucrative new revenue stream by reselling excess generation, not just back to utilities but direct to consumers or other businesses.

Before we reach that point, however, we need to focus on the most suitable framework for delivering this new layer of next-generation intelligence to the evolving energy system.

BESS: a new level of smart operation

The answer to many of the key challenges facing the energy transition lies in battery energy storage systems (BESS), which already form a central part of many businesses’ decarbonization strategies, enabling them to store excess energy and redeploy it as needed for seamless renewable integration.

When partnered with an EMS, monitoring and diagnostics, BESS allows operators to optimize power production by leveraging peak shaving, load-lifting, and maximizing self-consumption. These systems can also provide critical backup power, preventing potential revenue losses due to production delays and downtime.

But that’s not all. Beyond tackling decarbonization, applying Artificial Intelligence (AI) can take BESS to a new level of smart operation. Typically, staff members need to monitor everything from BESS status and solar and wind outputs through to weather conditions and market prices manually, but AI gives businesses the ability to constantly process and analyze these highly complex variables in real-time through machine learning, delivering a much more effective utility-scale energy storage operation.

An example of this can be found with the ABB AI module for BESS, which handles, analyzes and exploits machine data in real-time. This is used to generate a daily event listing (with a single car charging session considered an event) and a daily load profile. Based on the cumulative visibility of daily events and load profile, along with wider weather, seasonality and market intelligence, the module can forecast future supply and demand expectations. As a final step, a simulation that quantifies how closely the predictions resemble the real physical measures offers further validation.

For the utility provider, the insight afforded by technology like this could be a game-changer. Through predictive analytics, it will allow energy distributors to save and distribute resources better and prepare them for upcoming demand. It can also improve the customer journey by improving access to renewable energy at volume at lower costs. Further benefits come in the ability to identify and address issues before they escalate and anticipate similar failures or performance constraints.

BESS is already playing a central role in the eco-transition, as a way for utilities and businesses alike to save costs, generate revenue, and improve resilience and sustainability. By some estimates, the global energy storage industry could grow to reach upwards of 5000 GW by 20502.

But the truth is that BESS has the potential to do much more than it has so far. Armed with AI, it could become one of the most critical tools in transforming our world into one where cleanly generated electricity powers almost every aspect of our lives.