In order to increase energy resilience and renewable energy use, the DoD is rapidly increasing the number of renewable microgrid projects at military installations. Meanwhile, energy markets are becoming more complex, demand response pricing is becoming commonplace, and increasing air quality concerns are limiting the deployment of diesel backup generators. The intersection of these complex drivers is creating a need for a next-generation control platform to efficiently manage the distribution of both on-grid and off-grid energy at DoD facilities, moving forward.
This project will demonstrate a new control approach which can efficiently optimize the interaction between any system of energy generation, storage, and consumption equipment. This new control architecture provides unprecedented control in improving energy resilience during disruptions, as well as substantially lowering the capital cost of backup power systems. The results of this project will clearly establish the capability of the control system to reduce microgrid life-cycle costs by 5%, reduce the installed cost for whole-building backup generation by 30%, and significantly improve the energy analysis capability available to DoD decision makers for optimizing energy use and planning new infrastructure projects.
Instead of traditional "fixed logic" algorithms which attempt to optimize individual pieces of equipment, based on limited feedback with other equipment, we instead propose a "micro-auctioning" control system. In this system, each energy asset is treated as a participant in an energy micro-economy at a DoD facility. By allowing all connected energy assets to bid with each other, all relevant information such as time-of-day pricing, energy disruptions, and changing energy needs can all be accounted for and autonomously optimized with near-perfect efficiency. This micro-auctioning system works in conjunction with our existing Halo/S sensor and control products and allows intelligent load shedding of energy consuming equipment such as HVAC and lighting, allowing complex controls strategies to be implemented autonomously or manually.
In addition to the low-level micro-auctioning architecture, several high-level software products are used in conjunction with it. These products are built with a genetic algorithm solver which optimizes the interactions between any number of participants. Using this optimizer, the software tools provide personnel with the ability to rapidly analyze hypothetical changes to the system in order to reduce utility costs, fine-tune energy resilience strategies, or plan new infrastructure projects.
Simple DoD installations with on-site renewable generation or demand response incentives can expect a minimum of 5% life-cycle savings using the micro-auctioning system over current state-of-the-art "fixed logic" control schemes. With an installed cost of $40,000 per MW of demand, implementing microauctioning controls on a typical simple microgrid can provide a 3-4 year simple payback. For more complex systems, lifecycle savings can be greater than 15% due to efficiency improvements, commissioning savings, and life improvement of storage equipment.
During energy disruptions, the system provides autonomous load shedding to accommodate a limited generation supply via mechanisms such as progressive HVAC comfort degradation, light level reductions, or other site-specific opportunities. Backup generation costs are reduced by at least 30% with the system, allowing more DoD buildings to apply whole-building backup generation to improve resilience. The micro-auctioning approach also provides a tremendous advantage over state-of-the-art competing control systems with its built-in analysis and simulation tools. These tools allow DoD decision makers to reduce utility costs through direct process, comfort, or scheduling changes, as well as plan more efficient future distributed energy projects.