We hear from the co-founder and CEO of optimiser Suena Energy, Dr. Lennard Wilkening, about the evolution of BESS asset management in Europe, including the impact of artificial intelligence (AI).
Wilkening will be giving a presentation on Day Two of the upcoming Battery Asset Management Summit Europe 2025 in Rome on 2-3 December, hosted by our publisher Solar Media.
In this Q&A, he discusses battery energy storage system (BESS) asset management best practice, how AI is pushing its evolution and, of course, Italy’s recent MACSE auction, which will likely feature prominently in discussions at the two-day event.
This follows a Q&A we published earier this week with another event speaker, Stefano Cavriani, founder and director of Italy-based optimiser Ego Energy.
Enjoy 12 months of exclusive analysis
- Regular insight and analysis of the industry’s biggest developments
- In-depth interviews with the industry’s leading figures
- Annual digital subscription to the PV Tech Power journal
- Discounts on Solar Media’s portfolio of events, in-person and virtual
Or continue reading this article for free
Energy-Storage.news: How has BESS asset management best practice in Europe evolved in the past three years?
Wilkening: Best practice in European BESS asset management has evolved from manual heuristics to fully data- and AI-driven lifecycle optimisation. Today, leading operators work with integrated optimisation layers that combine high-resolution asset data, real-time degradation cost models and market forecasts—for example, adjusting dispatch decisions dynamically when marginal degradation costs rise or when intraday spreads widen unexpectedly.
AI now links technical and commercial realities: it identifies the cycles that generate true long-term value, prevents harmful micro-cycling, and even predicts availability impacts before they occur. This shift has turned BESS from static assets into continuously optimised, self-learning energy portfolios.
What is your current approach to maximising returns from your BESS, and what key performance indicators drive your operational decisions?
We maximise returns by running our BESS like high-frequency energy trading portfolios: our AI engine processes real-time plant data, live order-book signals and market forecasts to execute over 50,000 trading decisions per day with millisecond precision. KPIs such as marginal degradation cost per cycle, simulated efficiency losses, revenue per MWh moved and available flexibility determine every dispatch decision.
How do you balance profitable market participation with preserving battery cell health, and what role do optimisation technologies play in this decision-making process?
We balance profitability and cell health by letting AI quantify the real degradation cost of every potential trading action in real time. Our optimisation engine simulates state of health (SoH) impact, efficiency losses and marginal wear before each cycle—in milliseconds—so the system only executes trades where revenue clearly exceeds degradation cost.
This prevents harmful micro-cycling, protects long-term performance and extends asset lifetime by several years, while still capturing high-value volatility across all markets. In practice, AI turns the health-versus-profit trade-off into a transparent, data-driven decision rather than a guess.
How do you view the current state of risk-sharing between parties in the European BESS industry, and how will this evolve over time?
We see that the market is increasingly discovering new hedging constructs which, in terms of risk, lie somewhere between full profit-sharing and a long-term tolling agreement.
Thus, floors, floors & caps, swap products, or partial tolling will dominate the service agreements between operators and traders. In partnership with RWE, suena is now offering our FlexFloor product that provides the security of a floor while still adding the merchant revenues.
What are your views on the MACSE auction and how winning project owners will need to approach asset management?
From the BESS investor’s view, a capacity market is obviously attractive, adding a rather riskless and usually long-term revenue stream to the ancillary and wholesale markets and increasing the bankability of the investment.
However, with the unexpected low results of the first MACSE auction we see the necessity to develop a thorough stacking strategy and partnering with an optimiser who is trading with a strong AI engine even bigger.
With our 10 years of R&D experience in the field of BESS optimisation, four of which are as multi-market traders in the German renewable energy & BESS market, suena will offer optimising services in the Italian market from 2027.
How does the BESS asset management question differ for standalone versus co-located projects?
For standalone BESS, asset management focuses on pure market optimisation—capturing spreads, frequency products and volatility with minimal constraints.
In co-located projects, however, the challenge becomes a multi-asset optimisation problem: AI must jointly forecast generation, model curtailment risks, and decide when storage should shift, absorb or arbitrage energy to maximise total site value.
This requires tighter integration of weather forecasts, real-time plant data and trading models. In practice, you’re not managing a battery anymore—you’re orchestrating an integrated energy system where the interactions create most of the economic value.