REEN AI Technology Engine

How REEN AI Optimizes Renewable Ergon's Global Solar Portfolio

REEN AI is our in-house optimization layer that continuously analyzes production, market, and weather data across Taiwan, Singapore, California, and New Jersey to maximize stable output and manage downside risk.

Real-time data ingestion from site sensors, weather APIs, and grid signals
Forecasting engine for 5-year energy yield and price scenarios
Automated optimization recommendations for dispatch, maintenance, and hedging

For illustration only – no guarantee of performance or results.

REEN AI Core Engine

Site Telemetry (SCADA)

Weather & Irradiance Feeds

Market & Price Curves

Asset & Maintenance Data

Grid & Storage Controls

Investor Dashboard & Reporting

System Architecture

Multi-Layer Data Pipeline

From edge sensors to investor dashboards – a complete view of how REEN AI processes and optimizes across all operational sites.

Architecture Diagram

1 Edge Layer – Solar Sites

🇹🇼 Budai, Chiayi – 150 MW 🇸🇬 Kranji Reservoir – 120 MW 🇺🇸 Kern County – 100 MW 🇺🇸 New Jersey – 50 MW

Dual-axis trackers, inverters, sensors, and local controllers stream data every few seconds.

2 Data Pipeline

Ingestion & Normalization (SCADA, IoT, APIs)

Quality & Anomaly Detection

Time-Series Storage (kWh, kW, price, weather)

3 REEN AI Optimization Layer

Short-Term Forecasting (5-min to 24-hr)

Mid-Term Scenario Engine (1–5 years)

Optimization & Constraints (curtailment, tariffs, capacity limits)

Models run continuously to balance stability, yield, and risk within defined limits.

4 Action & Delivery Layer

Operational Actions

Setpoints to inverters Battery charging profiles Maintenance alerts

Investor Outputs

NAV & IRR updates Risk metrics ESG reporting

REEN AI Live Engine – Global Sites

1// Site configuration (read-only)

2site("Taiwan_Budai_Chiayi") = {

3 capacity_mw: 150,

4 realized_irr: 14.5,

5 efficiency: 0.94,

6 notes: "Multi-phase development, municipal PPAs"

9site("Singapore_Kranji_Reservoir") = {

10 capacity_mw: 120,

11 realized_irr_range: "12.4–13.8",

12 efficiency: 0.92,

13 notes: "Grid-tied solar, strong policy framework, stable demand"

14}

16site("California_Kern_County") = {

17 capacity_mw: 100,

18 realized_irr_range: "12.1–13.0",

19 efficiency: 0.89,

20 notes: "Utility-scale solar with long-term PPAs"

21}

23site("New_Jersey_East_Coast") = {

24 capacity_mw: 50,

25 realized_irr_range: "11.8–12.6",

26 efficiency: 0.91,

27 notes: "Commercial solar on-grid, strong incentives"

28}

30// Optimization cycle (illustrative only)

31REEN_AI.run_cycle(interval="5 min") {

32 ingest_telemetry();

33 update_forecasts(horizon_days=7);

34 recompute_optimal_dispatch();

35 push_signals_to_sites();

36 refresh_investor_metrics();

37}

Current Snapshot (Illustrative)

Region	Output %	Availability %
🇹🇼 Taiwan	96%	99%
🇸🇬 Singapore	93%	99%
🇺🇸 California	91%	98%
🇺🇸 New Jersey	92%	99%

Values shown are for illustration only and do not represent live or guaranteed performance.

Portfolio Performance

Regional REEN AI-Managed Sites

Global diversification with consistent, policy-backed frameworks.

🇹🇼

Taiwan

Budai, Chiayi

Capacity 150 MW

Realized IRR 14.5%

Efficiency 94%

Multi-phase development with municipal PPAs and coastal irradiance stability.

REEN AI: Curtailment & storm-risk optimization

Capacity (MW) 150

Realized IRR 14.5%

Efficiency 94%

🇸🇬

Singapore

Kranji Reservoir

Capacity 120 MW

Realized IRR 12.4% – 13.8%

Efficiency 92%

Grid-tied solar with strong policy support and stable demand.

REEN AI: Demand-matching and tariff optimization

Capacity (MW) 120

Realized IRR 12.4–13.8%

Efficiency 92%

🇺🇸

California

Kern County

Capacity 100 MW

Realized IRR 12.1% – 13.0%

Efficiency 89%

Utility-scale solar under long-term PPAs in high-insolation region.

REEN AI: Weather and curtailment risk management

Capacity (MW) 100

Realized IRR 12.1–13.0%

Efficiency 89%

🇺🇸

New Jersey

East Coast

Capacity 50 MW

Realized IRR 11.8% – 12.6%

Efficiency 91%

Commercial on-grid portfolio with robust incentives.

REEN AI: Capacity-factor smoothing and grid-event alerts

Capacity (MW) 50

Realized IRR 11.8–12.6%

Efficiency 91%

Built-In Risk Controls Around REEN AI

No Automated Trading

Optimization is advisory and rule-bound – no autonomous market transactions.

Human Review

Material set-point changes require human review and approval before execution.

Independent Verification

Performance verification and complete audit trail maintained independently.

SOC-Aligned Security

SOC-aligned security controls and role-based access throughout the platform.