Edge AI that keeps optimizing even when the internet doesn't.
GridMind AI runs forecasts 4 hours ahead, every 15 minutes, on-edge. Reduces diesel 18-40% in hybrid PV+BESS+Genset systems. Battle-tested in 693+ sites across 18 countries since 1991.
Diesel saving is a design figure for a hybrid PV+BESS+Genset site — what a given site gets depends on its load, how the PV and battery are sized, and how much the generator ran before. The forecast error above is measured at live sites.
3 gaps every microgrid operator faces today
Current EMS solutions miss the mark in three specific ways. GridMind AI was built to close each gap.
Reactive, not predictive
No forecasting. No tariff-aware dispatch. Operators react to load swings instead of anticipating them — missing TOU peaks and demand charge optimization.
Vendor lock-in
Cross-brand devices (Huawei, Sungrow, BYD, Leonics) cannot work together. Each vendor's app sees only its own equipment — fragmented operations, multiple dashboards.
No auditable carbon data
Raw energy data exists, but isn't converted into auditable carbon metrics. ESG reports become manual spreadsheet exercises. CBAM compliance is out of reach.
Four things the system does for your site — every 15 minutes
Each one closes a gap you are paying for today — and they reinforce each other in one loop that keeps running 24/7, even with no connection to the cloud.
Your existing inverters keep working
You see the next 4 hours before they happen
Every kWh is stored and used at the cheapest hour
Your carbon report is ready when the auditor asks
Keep the inverters you already own
Adopting the platform does not mean re-buying your fleet, and it does not tie your next purchase to one supplier. Adding a device is a configuration file — no code change, no integration project.
You act on the next 4 hours, not the last 5 minutes
Every 15 minutes the system projects solar generation and site load 4 hours ahead, then dispatches battery and genset against that projection — automatically, on site, with no operator in the loop.
Fewer genset starts, less wasted charge
- The battery charges before a cloud front arrives — not after output has already dropped.
- The genset does not start for a dip that will last ten minutes.
- Export and curtailment are decided ahead of the limit, not corrected after it.
The peak is shaved before it forms
- Demand charge is set by one 15-minute peak a month — the system reserves battery capacity for it in advance.
- Capacity is not spent early on a rise that does not matter.
- When the genset does run, it runs at an efficient load point instead of as a reflex.
Internet went down 6 hours at Sabah, Malaysia.
A cloud-dependent EMS site running in parallel — vs GridMind AI on edge. The difference is measured in liters of diesel.
Cloud-Dependent EMS
- AI optimization stopped working
- 22 optimization cycles lost
- 120 liters of diesel wasted
- Dispatch fell back to manual operation
GridMind AI · Edge
- AI kept running — 100% continuous
- 0 optimization cycles lost
- 0 liters of diesel wasted
- Dispatch fully autonomous on edge
Edge AI isn't an optional feature. It's the new baseline for clean energy in ASEAN — where internet is unreliable, but customers still need 24/7 optimization.
On-grid too — cuts TOU cost and Maximum Demand, recomputed every 15 minutes
A rule-based EMS is lookahead-free — it hoards the battery because it cannot know when solar will refill it. GridMind AI predicts solar and load hours ahead: it discharges into the morning peak, lets free midday solar refill, and holds one flat import cap all evening. Same hardware, more value per kWh of battery.
Linfox-class site · 300 kWp PV · 750 kW / 1,566 kWh BESS · TOU 4.18 / 2.60 THB/kWh. Midday PV refills the battery to 90%, which then discharges into the evening peak to hold grid import down — protecting the Maximum Demand charge.
Source: Solar Insight Pro 15-minute simulation (GridMind ON), a representative clear-sky weekday. Illustrative of dispatch behaviour — not a measurement of a specific installed site.
Dynamic Peak Shaving
Smart TOU Arbitrage
PV Double-Cycling
Demand Charge Protection
Self-Learning Bias Correction
Explainable Decisions
Source: GridMind production measurement across 3 sites live 24/7 in Thailand and the Philippines (2026), plus a full-year 15-minute simulation of a 300 kWp / 1,566 kWh on-grid site against an auto-tuned rule-based EMS, at measured forecast-error levels.
On the identical site, GridMind AI extracts 55% more energy from the same battery and buys 149 MWh/year less peak-rate power — while holding Maximum Demand equal. Forecast-driven dispatch simply uses the asset you already paid for, better.
Source: full-year 15-minute Solar Insight Pro simulation of the same site — rule-based EMS (fixed peak-shaving target) vs GridMind AI (forecast-driven), at measured forecast-error levels.
The solar saved nothing on demand charge — the peak was at 21:45
Without storage, this C&I site hit its monthly maximum demand at 21:45 in all twelve months — after sunset. Adding solar moved the demand charge by exactly zero. Every baht of reduction came from the battery, and how much came from deciding when to use it.
| Configuration | Demand charge / year | vs no PV |
|---|---|---|
| No PV | 917,962 | — |
| PV only | 917,962 | no change |
| PV + BESS · rule-based EMS | 813,490 | −104,471 (−11.4%) |
| PV + BESS · GridMind AI | 620,654 | −297,307 (−32.4%) |
Same battery, same inverter, same tariff — only the decision-maker changed. GridMind AI took 192,836 THB/year more off the demand charge than the rule-based EMS, a 23.7% lower bill on identical hardware.
How much of this transfers to your site depends on when your peak falls. A plant that peaks at midday gets much of the reduction from PV directly. This one peaked after dark — which is exactly where storage and forecast-driven dispatch do all of the work.
Source: full-year 15-minute Solar Insight Pro simulation — assumed load profile of about 500 kW, Solcast irradiance at Bang Bo, Samut Prakan, 1 Jan – 31 Dec 2025, at the site's TOU maximum-demand rate. Simulated figures for a separate site from the 300 kWp study above — not metered results, and not to be read together.
GridMind AI Dashboard — what the operator sees
The AI's forecast and its grid-import cap are drawn on the same chart as reality — so every dispatch decision is visible and auditable, not a black box.
| Horizon | Solar kW | Load kW | Grid kW |
|---|---|---|---|
| +15 min | 612 | 301 | 0 |
| +30 min | 571 | 322 | 0 |
| +1 h | 468 | 359 | 0 |
| +2 h | 236 | 418 | 182 |
| +4 h | 21 | 598 | 360 ● |
09:00 DISPATCH Morning discharge 103 kW — refill forecast OK
10:30 CHARGE PV surplus → BESS 415 kW (headroom reserved)
13:45 HOLD SoC 90% — reserving for 16:30–22:00 window
13:45 CAP Evening shave line = 360 kW (recomputed)
How to read it: the black stepped line is the grid-import cap GridMind promised for the peak window — recomputed every 15 minutes from the AI forecast — and the red Grid line rides exactly on it through the evening. The morning discharge at 09:00 was taken because the dotted forecast showed midday surplus would refill the battery for free. Illustrative dashboard on a simulated on-grid day — not a live screenshot of a specific installed site.
693+ sites · 18 countries · 35 years
Selected projects where GridMind AI runs in production today.
TNBES Off-Grid Hybrid
GridMind AI keeps optimizing dispatch — even during the 6-hour internet outage of May 2025. Reduced diesel by 35%.
BCP Solar Rooftop
GridMind AI optimizes TOU dispatch and demand charge reduction for a Bangkok C&I site on MEA tariff.
Iririki Island Resort
NODEX with 10× Power Nodes + Storage Nodes. GridMind AI manages BESS arbitrage across resort load profile.
35 years of ASEAN microgrid data — tuned to sites like yours
- ✓ 35-year proprietary dataset — since 1991, across 693+ sites in 18 countries. No competitor has this depth for ASEAN climate and tariff conditions.
- ✓ Hardware + Software full-stack — we make the BESS, the PCS, the inverter AND the AI. End-to-end ownership — no integration friction.
- ✓ Thailand-rooted, ASEAN-tuned — deep knowledge of TOU MEA/PEA, BOI tax depreciation (150% × 3yr), AFA, Ft, Demand Charge. Not generic global software.
- ✓ Off-grid first — designed for sites where internet is unreliable. Edge AI is the baseline, not an optional add-on.
- ✓ Standards & certifications — ISO 9001:2015 · ISO 14001 · UL1741SA · IEC62477-1 · CSA22.2 · IEEE 1547-2018 DER · TGO/IEA · CBAM · T-VER
Track record cloud-only EMS can't match
Questions your procurement team will ask — answered
Your next site — proof of value in 4 weeks.
Free 60-minute Technical Workshop. By the end you'll have: pilot scope (up to 3 devices), deployment plan, draft quote — plus a free Solar Insight Pro feasibility report.