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Abstract-This paper describes a distributed wireless network architecture for remote diagnosis and monitoring. Wind energy conversion system (WECS) is considered as the target application, where windmills are grouped into small clusters communicating with each other for the purpose of distributed diagnosis. The evaluation of this network is simulated to support effective communication needs required for fault detection and as a result to send an alarm or caution message to the remote monitoring station. However, as the sensitivity of application increases, strict requirements on availability, robustness, reliability and performance of network resources must be satisfied in order to meet industrial standards.

This paper considers a discrete-time scheduling method for the power balancing of a continuous-time DC microgrid system. A high-order dynamics and a resistor network are used for modelling the electrical storage unit and the DC bus of the centralized microgrid system, respectively. A PH (Port-Hamiltonian) formulation on graphs is employed to explicitly describe the microgrid topology. This modelling approach allows us to derive a discrete-time model which preserves the power and energy balance of the physical system. Next, a constrained economic MPC (Model Predictive Control) using the proposed control model is formulated for efficiently managing the microgrid operation. The systematic combination of the network modelling method and optimization-based control allows us to generate the appropriate power profiles. Finally, the benefits of the proposed approach are validated through simulation and comparison results over a particular DC microgrid elevator system under different scenarios and using real numerical data.

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