Today, due to many advantages, especially meeting the growing electricity consumption and decreasing environmental pollution, smart grid has attracted worldwide attention. Recently, a lot of researches have been carried out to expand and solvesmart grid challenges. Smart gridsconsist of many computer and control units in which data exchange between units is necessary. So, one of the main challenges in smart grid is the high volume of transmitted and stored data.In transmission, the high volume of data causes some problems such as data delay and interference, excessive power consumption, network traffic, and need for extra bandwidth. In storage, we deal with lack of storage space. An efficient way to solve this challenge is data compression.In this thesis, compression methods and their advantages and disadvantages have been investigated, with emphasis on Compressed Sensing. The reason is the low calculations for data compression and the efficiency for electrical signals. Also in this thesis, a model of smart grid consisted of wind turbines, solar panels, and battery banks connected to a DC bus is considered. In this model, a local sliding mode controller hasbeen considered for each wind and solar generator. Due to its limitations, a control algorithm for the battery bank hasbeen proposed. Furthermore, in the smart grid model, a model predictive supervisory controller has been considered and a general algorithm for its operation has been proposed. The aim of supervisory controller is determination of the reference power for each generator, based on the load demand, environmental conditions, price of electricity, rated powers, and the limitations of each generator. The purpose of local controllers is to ensure each generator follows the power reference determined by the supervisory controller, if possible. Otherwise, generators should produce the maximum allowable power. In each sampling time of supervisory controller, part of smart grid data is sent to the supervisory controller and monitoring unit. The supervisory controller needs data to allocate proper power reference to each generator.The monitoring unit uses data to monitor environmental conditions and the proper functioning of smart grid. The volume of data that is transmitted from the smart grid model to supervisory and monitoring units is high; thus, by proposing two units, data acquisition and compression unit and analysis unit,the smart grid model has beenmodified for applying compression algorithms. Then, the compression algorithms have been performed on transmitted data. The simulation results show that using compressed sensing, the volume of transmitted and stored datahas been extremely reduced, while electrical signals have been reconstructed with high precision. The supervisory controller has shown satisfactory performance as well. Key Words: Smart Grid, Compressed Sensing, DataAcquisition andCompression unit,DataAnalysis Unit, Supervisory Controller
