A Power-Control based Transactive Energy Mechanism for HVACs in Grid-Interactive Buildings

Transactive Energy (TE) based control has gained a greater momentum in the past decade in terms of popularity and implementation. By granting consumers with different degree of freedom in choosing their comfort level, TE has shown great potential to be more successful in demand response in comparison with its counterparts like Direct Load Control (DLC) and Price Responsive Control (PRC). The complexity of implementation of TE is very well described in many of the demonstrations like Olympic Peninsula Project and AEP GridSmart Project. One of the conundrums that is faced by TE implementation is the price discovery which is a part and parcel of the market mechanism involved in the TE operations. The aforementioned projects followed a procedure of deriving price graphically and directly as a function of the indoor present temperature and consumer comfort level with no regard for the dynamics of room temperature on power consumption. Thus, the procedure fails to capture the temperature-power-price relationship which otherwise can establish a common context in terms of power that can put HVAC to work with other DERs. This research aims at defining the relationship between set-temperature in the room and power consumed by introducing a regression model of linear order which is analyzed and validated to determine its suitability for TE optimization. Further, a comparison between Particle Swarm Optimization (PSO) and fmincon method is drawn out as a part of demonstrating the application of optimization algorithms on the proposed model.