Flexible ESS Operation with Load Forecasting-Based Control

This case demonstrates adaptive ESS charge control using real-time load forecasting, preventing peak overruns and enabling stable, predictable battery operation even during sudden load fluctuations.

Challenges

Multiple Charge·Discharge Cycles to Maximize Profitability
Although frequent cycling is not ideal for battery longevity, the on-site ESS is operated with multiple charge·discharge cycles per day to maximize profitability, accelerating the break-even point and reducing electricity costs
Risk of Exceeding Peak Demand Due to Mid-Load Charging
Frequent charging throughout the day, including during mid-load hours, increases the risk of surpassing existing peak demand due to additional charging loads
Difficulty in Real-Time Load Response and Optimal Charging Decisions
There is a need to optimize charging without exceeding the current peak, while also being able to respond flexibly to sudden load fluctuations in real time

Solutions

Load Forecasting-Based Charge Optimization
Analyze load patterns and use real-time data to predict future demand, enabling the determination of optimal charging levels without exceeding existing peak limits
Visualized Charging Decisions for Operator Transparency
The system learns load behavior in a human-understandable format, allowing operators to anticipate ESS behavior and understand why charging is limited or maximized at any given time
Flexible Operation Strategy for Real-Time Load Fluctuations
Provide a method to cancel or override previously made charging decisions through continuous real-time load monitoring

Applications & Benefits

“By applying load forecasting-based operation technology to a large-scale ESS, we secured additional revenue while achieving both operational efficiency and profit stability through automated charging schedule integration and peak demand avoidance.”

Implemented in a 000MWh ESS, generating significant additional annual revenue
Automatically generates and integrates additional charging schedules without operator intervention
Monitors real-time load data, automatically cancels additional charging when there is a risk of surpassing peak demand, preventing potential revenue loss