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This paper presents a high performance 4-layer communication architecture for a smart micro-grid testbed which consists of a 2 kVA Distributed Energy Resource (DER) inverter with PV and battery channels capable of advanced grid supportive and grid forming functions in the Process layer, a Raspberry Pi computer in the Interface layer, a customized Edge Intelligent Device (EID) in the Sub-station layer, and an end-to-end solar energy optimization platform (e-SEOP) in the Supervisory layer. The Raspberry Pi serves as a communication interface which communicates with the DER inverter using Serial Peripheral Interface (SPI) communication and talks to the EID using Modbus TCP/IP protocol. This paper provides a convenient and comprehensive solution to SPI and Modbus TCP/IP communication implementation in a smart micro-grid. The challenges of coordination between communication and system control and between different communication protocols have been addressed, which leads to a boost in the communication efficiency and makes the system highly scalable, flexible and adaptive. The proposed communication architecture as well as the micro-grid test bench have been validated through hardware experiments. The results indicate a reliable and efficient communication among different layers, which facilitates large-scale status monitoring of edge devices and coordinated control of the entire system.

This paper proposes a generalized design methodology of a robust controller to mitigate the impact of system uncertainty on controller stability and performance which includes steady-state error, disturbance rejection, high-frequency noise attenuation and speed of dynamic response. The first step is to select the weighting functions that bound the transfer functions for the entire range of uncertainty. The second step is to form mathematical representation for both robust stability and robust performance. The third step is to conduct the robust H-infinity controller synthesis to generate the full-order controller, and then carry out order reduction and recheck of the design objectives. The last step is to select an optimized controller based on the multi-dimensional Pareto Front algorithm. The proposed method has been firstly applied to the current controller design of a grid-connected inverter with variable grid impedance, and secondly to the voltage controller design of an LLC resonant DC/DC converter with variable resonant capacitance. The results indicate that the selected optimal H-infinity controller has an overall more satisfactory performance in terms of stability, steady-state error, disturbance/noise rejection capability and dynamic performance, compared with conventional PI and PR controllers when there is a large variation of system parameters.

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