PowerUp

Exciting new capability added to our PowerUp Battery Insight® solution ! If you're managing a BESS fleet in North America, how much time do you and your team spend just figuring out which battery anomalies across your asset actually matter before any action is taken? For operators, that interpretation work eats into the same limited hours that need to also fix the problem. That’s where a tool like Decision Support Pack becomes valuable. Powered by Battery Insight® which provides earlier visibility into issues, it groups related findings into issues, quantifies the lost and at-risk energy with a directional financial read, and connects each issue to an action you can resolve in the workflows you already use. Early versions are already running on real asset data... happy to talk through what that looks like for your portfolio!

Decision Support Pack is personal for me. For years, I’ve heard the same challenge from BESS owners and operators: visibility isn’t enough. The harder part is deciding what matters most, what to do next, and where to spend limited time and budget. That’s what we built Decision Support Pack to address. It groups related findings into Issues, quantifies lost and at-risk energy capacity with estimated revenue impact, and turns them into prioritized Actions teams can track through resolution. Early versions are already running on real asset data. In customer previews, we’re hearing things like: “This provides the interpretation layer we’ve been doing manually” and “I’ll take this screen and share it with my team.” If you’re running BESS fleets, I’d be interested in how you handle this problem today.

Resolve hidden BESS anomalies to ensure predictable revenue. https://lnkd.in/gYW2Sftb

The Gulf is scaling storage at a pace few predicted it would. Across the Gulf, roughly 80 GWh of new storage is planned through 2030, with close to 48 GWh of that targeted in Saudi Arabia alone. And in most of these deals, owners are paid for keeping capacity available. So the money tracks one thing: whether the asset delivers what it promised, every day, for years. That is where it gets interesting. A battery can pass every dashboard check and still hold back capacity it is contracted to provide. None of it is a fault, so no alarms actually fire. It is the slow drift, the rack imbalance, and the thermal stress that build up between the alarms and show up first in your availability numbers, then in your revenue. The lenders see it too. As private capital moves in, the questions I hear most are how fast these batteries will degrade, and whether they will still perform at scale a decade into a 15-year contract. An owner who can answer with real operating evidence negotiates from a very different place than one holding only a spec sheet.

Ask an asset manager running a BESS fleet what makes the job hard, and it rarely comes down to a shortage of alarms. What it really comes down to is all of them arriving at the same time with no reliable way to tell which one actually needs the team's attention next. Findings compete with each other for the same limited team and the same limited hours. An asset manager can see a problem clearly and still have no easy way to decide whether it belongs at the top of the list or the bottom, let alone justify that call to the people asking why. Some of us have watched other infrastructure industries, such as telecom, move through this same shift before: first you instrument everything and catch problems early, and eventually the constraint stops being what you can see and becomes what you do about it. Getting that part right requires a way to turn findings into priorities, priorities into actions, and actions into a record of what changed. In this edition of our newsletter, we highlight our Chief Product Officer, Cedric Brehaut, who shares why we built Battery Insight® Decision Support Pack and the thinking behind it.

Neoen observed persistent inter-rack imbalance affecting one of its BESS assets, creating increasing operational risk and progressively reducing available energy capacity over time. PowerUp quantified the operational impact by estimating approximately ~23 MWh (~25% of nominal capacity) of unavailable energy at the asset level. Following recommended recalibration, approximately ~22 MWh of the estimated unavailable energy was recovered. This validated both the quantified operational impact and the effectiveness of the corrective action. Based on average local market prices during the observation period, the recovered energy represented a revenue loss of ~26,400€/month if left unresolved. This success story demonstrates how continuous quantification of imbalance-driven unavailable energy can support earlier operational intervention before losses materially accumulate. Download the full case study. https://lnkd.in/gT7py9zm/?utm_campaign=Q3-26:AllRegions%2526AllTitles&utm_source=linkedin&utm_medium=paid&utm_id=1158602764&hsa_acc=518322551&hsa_cam=1158602764&hsa_grp=893087084&hsa_ad=1555480044&hsa_net=linkedin&hsa_ver=3