Acumen AI Strategies

Energy Toolbase's Acumen AI offers several key strategies, each tailored to specific energy optimization objectives:

1. Stacking (DCM & EA): This advanced strategy combines peak shaving and energy arbitrage. The engine addresses poor forecasts by incorporating a peak shaving "insurance" through the maintenance of a higher State of Charge (SOC). This approach supports effective peak shaving but may impact energy arbitrage potential.
2. Demand Charge Management (DCM): When dealing with demand charges, Acumen AI concentrates on reducing demand without giving energy charges much consideration. The goal is to effectively lower demand, minimizing costs associated with demand-based pricing structures.
3. Energy Arbitrage (EA): This strategy focuses on leveraging price differentials between peak and off-peak periods. While it doesn't directly encourage peak shaving, the strategy aims to prevent the establishment of new peak demand levels through charging activities. This strategy enables you to capitalize on price disparities and optimize energy utilization.
4. Solar PV Self Consumption: Focusing on optimizing the consumption of self-generated solar energy, this strategy aims to reduce reliance on the grid by consuming the PV-generated energy on-site. The Acumen AI tailors its decisions to facilitate increased self-consumption, thereby minimizing energy imports and grid-related costs.

Informed Decision-making

A clear understanding of our Acumen AI strategies empowers users to make informed decisions about energy storage and utilization. Whether the objective is demand charge reduction, energy arbitrage optimization, or a blend of strategies, Acumen AI capabilities are designed to align with these objectives.