DEVELOPMENT OF AN ENERGY MANAGEMENT SYSTEM FOR SMART BUILDINGS WITH THE INTERNET OF THING FOR SUPPORTING THE AUTOMATED DEMAND RESPONSE

Abstract

This research focused on the development of demand-side management technology, which is an Automated Building Energy Management System with the Internet of Thing (IoT) so-called aBEMS-IoT for the reservation of the DR program to stabilize the power quality and stability of the grid network. The aBEMS-IoT components can be classified into three main parts; the first is controlling devices (Hardware), and the second is a data processing and monitoring system (Software), and the third is the communication system. After the aBEMS-IoT was developed, it was implemented in the target building, such as the building of the Post Engineering office, to find out the technical capability. The two performance tests were performed, which consisted of the laboratory test and the actual building integrated with aBEMS-IoT test. Both of them were tested under the assumed DR program for maintaining the grid voltage and network stability. The results of this research can be classified into two parts; the first part shows the capability of the aBEMS-IoT, and the second part is the impact of demand response using the aBEMS-IoT for flattening the duck curve. The analyzed results of the first part indicated that the aBEMS-IoT could effectively manage the load following the assumed DR program. The response time from the control to the end devices until the process finish, it took about 650 ms and the load power which was controlled by the aBEMS-IoT in case of the actual system, it was able to connect (load building) and to disconnect (Load clipping) following the assumed DR program. The aBEMS-IoT is the technology for balancing supply and demand by managing the demand side, and it will be the solution for Smart Grid or Microgrid, which will take the grid stability, power quality, resiliency, and reliability. The second part is the load flow dynamic simulation of the demand side management by using the aBEMS-IoT under the assumed Demand Response program for stabilizing power quality and flattening the duck curve. The result of the research indicated that the aBEMS-IoT was able to operate following the control signal of load aggregator for maintaining the power quality and flattening the duck curve. During the daytime, when overvoltage occurred, the controllable load was building to increase power demand for stabilizing the grid voltage as controlled by load aggregator. On the other hand, in the evening time, the peak load was clipped by the aBEMS-IoT for decreasing the load demand. Finally, the demand-side technology, such as aBEMS-IoT is able to maintain the power quality in the acceptable range and also to flatten the duck curve. Demand response and demand-side management technology will be key parameters for the reliability and stability of the grid network.

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