This case study walks through a project commissioned in 2024 and now in stable operation for the better part of two years. The customer is a textile manufacturing group in southern Vietnam operating a facility with roughly 14,000 spinning spindles, with all the energy intensity that implies. The brief was straightforward: reduce electricity costs without compromising production reliability.

What's interesting about the project isn't the technology — the equipment is conservative, off-the-shelf for ZCForest's commercial range. What's interesting is the economics, which exceeded expectations enough that the customer commissioned a phase 2 within 14 months.

The starting point

The facility was running on a standard industrial tariff with significant time-of-day spread between peak and off-peak rates, plus a demand charge that was consistently a meaningful component of the monthly bill. Electricity represented one of the larger line items in the cost of goods, and the operations team had a clear mandate to reduce it.

The site had a substantial roof — much of it suitable for PV — but limited space for ground-mounted equipment. Production ran roughly six days a week with a single overnight shift handling maintenance and lighter operations.

The system we delivered

2.5 MWh
Storage capacity
1.8 MWp
Rooftop PV
1.0 MW
PCS power

The configuration was a containerised LFP storage system with bidirectional power conversion, paired with a rooftop PV system sized to cover the majority of daytime base load. The dispatch logic was straightforward: solar self-consumption first, surplus to battery, battery discharge during peak windows, and demand-charge management running in parallel as a constraint.

What the system actually did

  • Solar self-consumption covered the bulk of daytime production load directly, reducing daytime grid draw substantially.
  • Battery discharge during peak hours further reduced grid draw during the highest-tariff windows of the evening shift.
  • Demand-charge management trimmed the monthly demand peaks that previously drove a significant portion of the bill.
  • Off-peak charging refilled the battery overnight on the cheapest tariff slot.

The economics

The payback came in faster than the original financial model suggested. Several factors contributed: tariffs moved in a direction that favoured arbitrage; production ran consistently which kept the load profile predictable; and the demand-charge reduction proved larger than initially modelled.

Bottom line Total monthly electricity cost reduction was significantly better than the conservative original model. The customer reached payback well inside the originally-projected window, and commissioned a second phase at a sister facility 14 months later.

What we learned

Three observations that apply to similar projects:

  • Demand charges are often understated in initial models. Customers and integrators alike tend to model the energy arbitrage carefully and the demand-charge reduction loosely. In practice, the demand-charge component is often where the real money is.
  • Production-load consistency matters more than peak load. A predictable load profile makes for better dispatch optimisation than a higher but more variable one.
  • The "boring" engineering choices win. Conservative equipment, conservative dispatch logic, and conservative warranty terms produced a project that has run reliably for years and pays back faster than the spec sheet suggested. Excitement is not a feature.

If you have a similar profile

For industrial or commercial operations in Southeast Asia or South America with high electricity intensity, time-of-day tariff spread, and roof or yard space for PV, the playbook above is now reasonably well-tested. We'll happily run the numbers on any specific site — the easiest first step is a quick WhatsApp conversation about the load profile and tariff structure to confirm whether the rough economics work.