This project demonstrated advanced microgrid control technologies capable of improving energy efficiency, expanding use of renewables, and increasing energy security for the Department of Defense (DoD). The microgrid control system (MCS) technologies were analyzed via a field demonstration at Marine Corps Air Ground Combat Center (MCAGCC) Twentynine Palms, California, as well as multiple laboratory tests with the field data, to validate the technology’s performance and expected operational costs. The ability of the technology to improve the energy efficiency, enable renewable integration, increase energy security, and reduce operational cost was evaluated by comparing system performance to a baseline of the Twentynine Palms site operation.
The MCS technology addresses the complexity of electrical demand, heat and power generation, and power distribution challenges through the use of dynamic real-time algorithms and an energy management dashboard for the microgrid operator. The MCS uses these algorithms to facilitate optimal dispatch of distributed energy resources (DERs), electrical load shedding, intentional islanding capability, and electrical load / energy management to manage and control the complicated interactions among heat and electrical power generation, power demand, and power distribution and delivery.
DERs such as renewable energy sources within the microgrid are equipped with local controllers that regulate real power, reactive power, frequency, and/or voltage. Intelligent electric devices (IEDs) located elsewhere in the microgrid provide system loading, voltage, and frequency information and carry out switching operations. The MCS implements a centralized, supervisory control layer. It polls all resources, executes central control algorithms, and sends resulting control commands back to each resource.
During unit commitment and optimal dispatch, 100% of the renewable energy resources were used all the time. By adjusting the heat versus electrical outputs of the combined heat and power (CHP), 2-4% efficiency is possible in a conservative estimate. Larger increases are possible with more assets. The project also demonstrated that a sizable amount of electric load can be dropped instantly by managing the building loads. Depending on the number of buildings participating, a 10% reduction of aggregated loads is possible in a few seconds to 10-15 minutes timescale without tripping the whole building or sacrificing too much comfort.
With the current configuration of minimal assets, a Savings to Investment Ratio (SIR) of 6.6 and Annualized Internal Rate of Return (AIRR) of 13% is achievable. These can be increased to SIR of 11-12 and AIRR of 16% with a larger number of microgrid assets. Building load management helps in energy surety, but it does not yield high AIRR because communication and other controls may need to be put in place, which will add to the cost. Optimal dispatch with load management does however yield a reasonable SIR of around 4 with AIRR of 11%. Using all available renewables for optimal dispatch leads to fewer emissions. A savings of around 21,410 tonnes of CO2 emissions, 165 tonnes of SO2 emissions, and 45 tonnes of NOx emissions is expected per year based on full utilization of available renewable assets.
This project had a relatively seamless implementation and system integration during the demonstration phase due to excellent camaraderie and support provided by the Base engineers and members of the Energy Service Provider (Johnson Controls, Inc.). Some of the lessons learned in this project that can aid future implementation of the technology include: the inability to export excess power generated by its DERs to the outer grid, lack of variable pricing schemes, inability to do continuous set-point control of diesel gensets due to U.S. Environmental Protection Agency regulations, unavailability of state-of-the-art solar inverters, and non-operational assets like the fuel cell.