Quantized Gradient Multiplier based Energy Management with Limited Data Communication

The expansion of smart grids and increased participation of energy management programs have to deal with the large amount of data transferring, processing, and storage. Large amount of data increases the cost of communication and possibly data loss. Updating the communication protocols to accommodate the increased memory size and computational processing incurs additional expenditure for implementation. This paper developed a Quantized Gradient Multiplier (QGM) based energy management algorithm with limited data communication. This method is studied on IEEE 13-bus and 15-bus network. The simulation results are compared with the Lagrangian Multiplier method and show that the QGM based energy management performs better with the reduced energy data set. Thereby, the suggested method benefits to the load aggregators in a real-time energy market operation with limited energy data communication.