Accelerated developments of renewable energy production technologies and their integration to existing AC microgrids have led to the emergence of several new inverters control schemes. The recently introduced proportional resonant (PR) controllers have the ability to precisely track AC quantities and are increasingly used in grid supporting inverters, especially for current control loops which are at the heart of power transfers. In this paper, the PR-controller action is analyzed and an enhancement is proposed. It is shown that the classical implementation is particularly sensitive to high frequency noises coming from measurements and relocating the proportional action (RPA) on the feedback path can overcome this issue. The proposed improvement was evaluated using bit-true simulations in the Matlab/Simulink®environment. Obtained results show good noise and overshoot suppression using the proposed PR-controller with RPA.

Multi-rate (MR) simulation is necessary for a system which contains both large and small time constraints. In the traditional MR real-time simulation of MMC, only the MMC valves are implemented on FPGA with a small time-step, while the rest parts are implemented on central processing units (CPU) with a large time-step. This paper presents a fully FPGA based MR real-time simulation of two MMC terminals. The FPGAs are decoupled by the stubline, and are parallelly simulated. Each FPGA is assigned with one MMC terminal, and its time-step can be flexibly chosen. The decoupled FPGAs can run asynchronously with their own model, which only communicate via the stubline without the synchro between them. Thus, the real-time simulation of a multi-terminal MMC-HVDC grid can be easily achieved while the accuracy of the simulation is also guaranteed. The real-time simulation results of the proposed methodology are provided.

In this paper, we study the performance of multi-tier integrated fiber-wireless (FiWi) smart grid communications infrastructures based on low cost, simple, and reliable next-generation passive optical network (PON) with quality-of-service (QoS) enabled wireless local area networks (WLANs) in terms of capacity, latency, and reliability. We study the coexistence of human-to-human (H2H), e.g., triple-play traffic and machine-to-machine (M2M) traffic originating from wireless sensors operating on a wide range of possible configurations. Our analysis enables the quantification of the maximum achievable data rates of both event- and time-driven wireless sensors without violating given upper delay limits of H2H traffic. By using experimental measurements of real-world smart grid applications, we investigate the impact of variable H2H traffic loads on the sensor end-to-end delay performance. The obtained results show that a conventional Ethernet PON may cause a bottleneck and increase the delay for both H2H and M2M traffic. In contrast, by using a 10 G-EPON or wavelength division multiplexing (WDM) PON, the bottleneck arises in the wireless network. Furthermore, we study the interplay between time- and event-driven nodes and show that the theoretical upper bound of time-driven sensors decreases linearly as a function of the number of sensors, whereas with event-driven sensors, the upper bound decrease is nonlinear and more pronounced.

Plug-in electric vehicles (PEVs) have great potential of being the alternative for the next-generation of transportation. Uncoordinated PEV charging, however, may put a significant pressure on the distribution grid. In this paper, on a modified IEEE-13 Node distribution network of 342 residential customers, we propose a converged fiber-wireless infrastructure based on EPON, WiMAX, wireless mesh network and sensor technologies to support coordinated charging of PEVs. To measure the performance of both the communications and power system perspectives of proactive scheduling algorithms and proposed reactive control protocols, our recently developed hybrid co-simulator based on OMNeT++ and OpenDSS is used. Co-simulation results show that the proposed low-cost communications infrastructure enables to efficiently schedule PEV chargings and quickly stabilize the voltage in a stress scenario.