Droop control in DQ coordinates for fixed frequency inverter-based AC microgrids

This paper presents a proof-of-concept for a novel dq droop control technique that applies DC droop control methods to fixed frequency inverter-based AC microgrids using the dq0 transformation. Microgrids are usually composed of distributed generation units (DGUs) that are electronically coupled to each other through power converters. An inherent property of inverter-based microgrids is that, unlike microgrids with spinning machines, the frequency of the parallel-connected DGUs is a global variable independent from the output power since the inverters can control the output waveform frequency with a high level of precision. Therefore, conventional droop control methods that distort the system frequency are not suitable for microgrids operating at a fixed frequency. It is shown that the proposed distributed droop control allows accurate sharing of the active and reactive power without altering the microgrid frequency. The simulation and hardware-in-the-loop (HIL) results are presented to demonstrate the efficacy of the proposed droop control. Indeed, following a load change, the dq droop controller was able to share both active and reactive power between the DGUs, whereas maintaining the microgrid frequency deviation at 0% and the bus voltage deviations below 6% of their respective nominal values

Optimal Mission Planning of Autonomous Mobile Agents for Applications in Microgrids, Sensor Networks, and Military Reconnaissance

As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. This thesis explores solutions in determining optimal mission plans around the applications of autonomous mobile microgrids and resource scheduling with UGVs and UAVs. Optimal network connections, energy asset locations, and cabling trajectories are determined in the mobile microgrid application. The resource scheduling applications investigate the use of a UGV to recharge wireless sensors in a wireless sensor network. Optimal recharging of mobile distributed UAVs performing reconnaissance missions is also explored. With genetic algorithm solution approaches, the results show the proposed methods can provide reasonable a-priori mission plans, considering the applied constraints and objective functions in each application. The contributions of this thesis are: (1) The development and analysis of solution methodologies and mission simulators for a-priori mission plan development and testing, for applications in organizing and scheduling power delivery with mobile energy assets. Applying these methods results in (2) the development and analysis of reasonable a-priori mission plans for autonomous mobile microgrids/assets, in various scenarios. This work could be extended to include a more diverse set of heterogeneous agents and incorporate dynamic loads to provide power to

UNMANNED GROUND VEHICLE (UGV) DOCKING, CONNECTION, AND CABLING FOR ELECTRICAL POWER TRANSMISSION IN AUTONOMOUS MOBILE MICROGRIDS

Autonomous Mobile Microgrids provide electrical power to loads in environments where humans either can not, or would prefer not to, perform the task of positioning and connecting the power grid equipment. The contributions of this work compose an architecture for electrical power transmission by Unmanned Ground Vehicles (UGV). Purpose-specific UGV docking and cable deployment software algorithms, and hardware for electrical connection and cable management, has been deployed on Clearpath Husky robots. Software development leverages Robot Operating System (ROS) tools for navigation and rendezvous of the autonomous UGV robots, with task-specific visual feedback controllers for docking validated in Monte-Carlo outdoor trials with a 73% docking rate, and application to wireless power transmission demonstrated in an outdoor environment. An “Adjustable Cable Management Mechanism” (ACMM) was designed to meet low cost, compact-platform constraints for powered deployment and retraction by a UGV of electrical cable subject to disturbance, with feed rates up to 1 m/s. A probe-and-funnel AC/DC electrical connector system was de- veloped for deployment on UGVs, which does not substantially increase the cost or complexity of the UGV, while providing a repeatable and secure method of coupling electrical contacts subject to a docking miss-alignment of up to +/-2 cm laterally and +/-15 degrees axially. Cabled power transmission is accomplished by a feed-forward/feedback control method, which utilizes visual estimation of the cable state to deploy electrical cable without tension, in the obstacle-free track of the UGV as it transverses to connect power grid nodes. Cabling control response to step-input UGV chassis velocities in the forward, reverse, and zero-point-turn maneuvers are presented, as well as outdoor cable deployment. This power transmission capability is relevant to diverse domains including military Forward-Operating-Bases, disaster response, robotic persistent operation, underwater mining, or planetary exploration

Postdisaster electric power recovery using autonomous vehicles

This paper presents an architecture for the development of mobile microgrids using autonomous vehicles for the recovery of electrical power in postdisaster scenarios. The goal is to facilitate the integration of the different disciplines involved and address interrelated challenges in interaction between the disparate components of the system and the physical world. The architecture described in this paper has emerged through a combination of hardware development and experimental studies. The proposed layout will create an autonomous mobile microgrid system consisting of a team of ground robots capable of navigating in a disaster-affected area, making electrical connections, and supplying and controlling the electrical power needed by the loads in the area. This system has the scalability characteristics of an ad hoc system and can reconfigure itself depending on the changes in demanded performance of the microgrid