i-EMS

Next-Generation AI-Driven Energy Management (iEMS)

Moving beyond traditional monitoring (CEMS), our iEMS leverages advanced AI algorithms to predict power generation and System Marginal Price (SMP). This enables data-driven automation for revenue improvement and long-term equipment optimization.

AI Forecasting SMP Prediction Charging / Discharging Timeline Predictive Maintenance Integrated Dashboard VPP Ready Architecture
Forecast Error Target
≤ 8%
MAPE Based
Revenue Improvement
10~20%
Annual Gain
Battery Life Extension
10~20%
Asset Life Optimization
Maintenance Cost Saving
30~50%
Preventive Maintenance Based

1. Overview

iEMS is designed to move energy operation from simple monitoring to intelligent prediction, automated scheduling, anomaly anticipation, and strategic decision support. By combining generation forecasting, SMP analysis, SOC-based control, and asset-health monitoring, operators can make faster and more profitable decisions across multiple sites.

2. Core Strategic Benefits

Profit Maximization

  • Reduces generation forecast error to below 8%
  • Secures settlement incentives through better forecast accuracy
  • Improves annual revenue by approximately 10~20%

Asset Optimization

  • Extends battery life by 10~20%
  • Reduces maintenance cost by 30~50%
  • Supports proactive preventive maintenance cycles

Operational Automation

  • Minimizes labor cost through daily automated scheduling
  • Supports real-time correction and operational adjustment
  • Improves repeatability of site operations

Future Scalability

  • Built on microservice architecture
  • Supports future VPP (Virtual Power Plant) integration
  • Accumulates long-term data assets for AI enhancement

Integrated Dashboard

Home Dashboard

Real-time operation status and AI forecast summary

Real-time
Current Output
229
kW
Forecast Accuracy
98.7%
Forecast
Total Charge
31.2k
MWh
Total Discharge
1,276
kWh
Forecast Actual

AI Forecast Bar Chart

JanFebMarAprMayJunJulAug

Generation Forecast

Forecast vs. Actual comparison analysis

7 Days 14 Days 1 Month Data

Forecast vs. Actual Bar Chart

Day 7Day 8Day 9Day 10Day 12Day 13Day 15Day 16
63%
MAPE
XLS
Excel Download

SMP Forecast

48-hour forecast line and confidence band

48h 7 Days 14 Days Data
Base Low High Load Low Load

48h Forecast Line / Confidence Band

19:0023:0003:0007:0011:0015:0019:00
CSV
CSV Download

AI Charge / Discharge Schedule

Automatic scheduling based on SOC and SMP

Auto Optimization

Charging / Discharging Timeline

7 AM8 AM9 AM10 AM12 PM2 PM4 PM6 PM8 PM
Charge Start
08:30 ▼
Discharge Start
17:00 ▼
Scenario
Lowest Cost ▼
85%
SOC
PDF
Export PDF Schedule

Smart Operations & Predictive Intelligence

1. AI-Powered Forecasting & Scheduling

  • Uses an ensemble of LSTM, XGB, and Prophet models
  • Forecasts daily and next-day generation with target MAPE ≤ 8.0%
  • Analyzes real-time SMP fluctuations and SOC conditions
  • Automatically generates profitable charging-discharging timelines

2. Predictive Maintenance & Anomaly Detection

  • Monitors BMS rack voltage deviation and PCS temperature trends
  • Calculates risk score on a 0–100 scale
  • Detects early failure signs before breakdown occurs
  • Predicts battery replacement timing using SOH tracking

3. Integrated Dashboard

  • Provides intuitive UI for multiple plant operation management
  • Compares Forecast vs. Actual in real time
  • Supports rapid operational decision-making
  • Unifies monitoring, analytics, and report output in one environment

Customizable Strategy: One-Click AI Presets

1. Revenue-First Mode

  • Focuses discharge on peak SMP periods to maximize short-term revenue
  • Effective for aggressive profit capture and faster ROI
Best For: rapid ROI, aggressive revenue capture

2. Equipment-First Mode

  • Uses conservative DoD operation to protect battery life
  • Suitable for minimizing SOH degradation and maintenance risk
Best For: long-term asset health, maintenance risk reduction

3. Balanced Mode(AI Recommended)

  • Balances profitability and equipment lifespan
  • Provides sustainable high-efficiency performance in standard operation
Best For: standard operation, sustainable efficiency

4. Profit Simulation

  • Compares Aggressive / Standard / Conservative scenarios
  • Visualizes expected profit differences before strategy execution
Best For: decision support before execution

Operational Value

iEMS combines AI forecasting, SMP-driven optimization, predictive maintenance, and scenario-based scheduling to help operators improve profitability while maintaining long-term system reliability and asset health.

Integrated Energy Management System

i-GRID

AI-DRIVEN ENERGY DATA PLATFORM

Next-Generation AI-Driven GRID (iGRID)

iGRID is an intelligent AI-powered energy and power data platform designed to transform complex operational data into actionable insights for utilities, industrial facilities, substations, and smart infrastructure environments.

Smart Grid Operations Substation Monitoring Energy Management Systems Predictive Maintenance AI Operational Analytics Real-time Event Analysis

1. Overview

iGRID is an intelligent AI-powered energy and power data platform designed to transform complex operational data into actionable insights for utilities, industrial facilities, substations, and smart infrastructure environments. By integrating real-time field data from SCADA, EMS, IoT devices, meters, sensors, and operational databases, iGRID enables organizations to monitor, analyze, predict, and optimize power system operations through advanced Artificial Intelligence technologies.

iGRID is built to bridge the gap between traditional power infrastructure and next-generation AI services. The platform provides centralized visibility of operational assets, supports intelligent event analysis, and delivers data-driven decision-making capabilities for engineers, operators, and management teams.

With scalable architecture and flexible deployment options including on-premise and private cloud environments, iGRID is suitable for mission-critical infrastructures that require high reliability, security, and operational continuity.

Applied Domains

Smart Grid Operations
Substation Monitoring
Energy Management Systems
Industrial Power Facilities
Renewable Energy Integration
Predictive Maintenance
AI-based Operational Analytics
Real-time Alarm & Event Analysis
Power Quality Monitoring
Asset Performance Optimization

2. Key Benefits of iGRID

Intelligent Operational Visibility

iGRID consolidates fragmented operational data into a unified intelligent platform, enabling operators and engineers to gain comprehensive visibility across power systems, substations, and industrial facilities in real time.

AI-Driven Data Analytics

The platform utilizes advanced AI technologies to analyze large-scale operational datasets, identify patterns, detect anomalies, and generate meaningful insights that improve operational efficiency and reduce response time.

Real-Time Monitoring & Event Detection

iGRID continuously monitors live operational data streams and provides rapid detection of abnormal conditions, system events, and equipment anomalies before they escalate into critical failures.

Secure & Flexible Deployment

iGRID supports on-premise, private cloud, and hybrid deployment models, allowing organizations to maintain operational security, data sovereignty, and compliance requirements for critical infrastructures.

3. iGRID Vision

iGRID aims to become the next-generation intelligent energy data platform that empowers organizations to achieve safer, smarter, and more sustainable power system operations through AI-driven innovation and operational intelligence.

iGRID Platform Introduction