Li-Ion BESS Dispatch Control for Peak Clipping and Load Shifting
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Solution Overview
Problem
The aging electrical power grid in the U.S. faces reliability issues due to increasing electricity demand, with existing infrastructure not adequately designed to manage peak power demand, leading to risks of blackouts, and there is a need for a shift in consumption patterns to align with generation capabilities, which existing demand response programs struggle to address effectively.
Innovation Solution
A system and method for energy storage dispatch optimization using a computer-implemented model that optimizes the charge-discharge profile of battery energy storage systems (BESS) based on power demand data, incorporating peak-clipping and load-shifting strategies, and event-based demand response to minimize total cost factors, including environmental impact, and maximize energy cost savings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing demand response programs are implemented, then electricity consumption patterns are adjusted, but the programs struggle to effectively address peak power demand management and grid reliability issues
Solution Approach 1:
The patent implements dynamic dispatch control strategies that continuously adjust energy storage system operations based on real-time grid conditions, demand patterns, and pricing signals. The system transitions from static demand response programs to dynamic optimization that adapts to changing conditions, enabling effective peak demand management while maintaining grid reliability through flexible, real-time control adjustments
Solution Approach 2:
The system changes operational parameters of energy storage systems based on varying grid conditions, including state of charge thresholds, charge/discharge rates, and dispatch timing. By dynamically adjusting these parameters rather than using fixed rules, the system effectively addresses peak power demand while maintaining reliability across different operating scenarios
2Productivity
If energy storage systems operate without optimization, then they can provide basic energy storage, but they fail to maximize cost savings and extend lifespan
Solution Approach 1:
The patent implements feedback mechanisms where the dispatch control system continuously monitors energy storage system state (charge level, power output/input), grid conditions, and cost parameters. This feedback enables real-time optimization of charge/discharge decisions to maximize cost savings while incorporating constraints that protect system lifespan, balancing productivity improvement with device complexity management through intelligent control algorithms
3Productivity
If peak power demand is not managed, then electricity consumption follows generation patterns, but the aging infrastructure cannot accommodate escalating demand, increasing blackout risk
Solution Approach 1:
The system performs preliminary charging of energy storage systems during off-peak hours when generation capacity is sufficient and costs are lower. This advance preparation enables the stored energy to be discharged during peak demand periods, effectively increasing consumption capacity during critical times without requiring immediate generation capacity expansion that would strain the aging infrastructure and cause blackouts
Data Source
AI summary
A system applies optimal peak-clipping (PC) and load-shifting (LS) control strategies of a Li-ion BESS at a large industrial facility with and without enrollment in the electrical utility company's event-based DR program. The optimally sized BESSs and discounted payback periods are determined for both control strategies with and without event-based DR enrollment. Additional optimization can be performed to reduce an environmental impact of using the BESS. Comparisons between the PC and LS control strategies' operations show that for the same sized Li-ion BESS with DR enrollment, the LS control strategy achieves more revenue in DR events and by leveraging the energy-price arbitrage.