Adaptive Demand Management Platform (ADM)

Electric utilities do not have the generation capacity to deal with spikes in electricity demand and use the wholesale electricity market to balance their load. Since demand is often fueled by temperature, wholesale electricity prices spike as utilities attempt to balance load. Typically, any electric grid user would pay some percentage of their whole electricity costs for their peak demand so large energy users such as factories or manufacturing plants among others, are well aware of the opportunity to reduce costs by managing peak demand. Blue Ocean Energy, LLC (BOE) identified a gap in the market for a Demand Response product and therefore, we are developing our Adaptive Demand Management Platform (ADM). Blue Ocean Energy understands the Air Force’s organizational environment, and their needs for efficient energy management, optimization, and costs savings since it is a significant energy user. Our proposal is focused on an innovative and unique approach to peak demand optimization through a platform able to dynamically ingest data from multiple smart thermostats and adjust and predictively adapt the functioning of HVAC (heating, ventilation and air conditioning ) units, resulting in significant energy and costs savings. The ADM is an energy management platform developed by BOE that provides continuous optimal zonal thermal comfort in different indoor spaces while automatically optimizing energy consumption (minimizing simultaneous runtimes). It consists of thermostats, a gateway and a cloudbased software with machine learning (ML) algorithms controlling each individual thermostat in a facility. Our smart thermostats collect realtime data on ambient parameters and send it to our cloud systems. There, our machine learning algorithms analyze data with the objective of minimizing the simultaneous runtimes (SRT) of the facility’s HVAC units remotely controlling them. The algorithms minimize SRT utilizing (1) Learning, (2) Predictive and (3) Deadband flexibility (DBF) features to achieve this objective. We use load shifting to manage demand (kW), avoiding Simultaneous Run Time (SRT) of the units in order to reduce peak demand costs. The key point, essence of the ADM, is that using the same amount of energy (kWh) could achieve significant savings by simply “shifting” operations of the units, thus decreasing peak demand charges (kW).