Enhancing utility efficiency with grid-connected ESS algorithm
Cutting-Edge ESS AI Algorithm for Enhanced Power Reserve Management
Customer profile:Â
Utility company
Challenge:Â
Maintaining power reserve over 20 MW while maximizing revenue from discharging when reserve forecast falls below the threshold.
Goal:Â
Optimize ESS operation for profitability using AI.
Solution:Â
DARE Data Analysis to design cutting-edge grid-connected ESS algorithm
Algorithm applications:
1. TPCP (Trading Period Capacity Payment) Algorithm: Applied during November to February for efficient capacity management and revenue optimization.
2. Arbitrage vs Peak Cut Analysis: Identifying the best revenue-maximizing option by analyzing peak forecasts and tariff data.
Results:
Enhanced Revenue Generation: Previously, the ESS remained underutilized with manual arbitrage. Now, our algorithm empowers the utility to optimize operations and generate substantial revenue.
Efficient ESS Management: Ensuring the power reserve stays above the desired 20 MW while capitalizing on additional revenue opportunities.
Data-Driven Decision-Making: Accurate insights lead to better-informed decisions for increased profitability.