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Optimal And Decentralized Control Strategies For Inverter-Based Ac Microgrids, Michael D. Cook, Eddy H. Trinklein, Gordon Parker, Rush D. Robinett Iii, Wayne Weaver
Optimal And Decentralized Control Strategies For Inverter-Based Ac Microgrids, Michael D. Cook, Eddy H. Trinklein, Gordon Parker, Rush D. Robinett Iii, Wayne Weaver
Michigan Tech Publications
This paper presents two control strategies: (i) An optimal exergy destruction (OXD) controller and (ii) a decentralized power apportionment (DPA) controller. The OXD controller is an analytical, closed-loop optimal feedforward controller developed utilizing exergy analysis to minimize exergy destruction in an AC inverter microgrid. The OXD controller requires a star or fully connected topology, whereas the DPA operates with no communication among the inverters. The DPA presents a viable alternative to conventional P−ω/Q−V droop control, and does not suffer from fluctuations in bus frequency or steady-state voltage while taking advantage of distributed storage assets necessary for the high penetration of …
Docking Control Of An Autonomous Underwater Vehicle Using Reinforcement Learning, Enrico Anderlini, Gordon Parker, Giles Thomas
Docking Control Of An Autonomous Underwater Vehicle Using Reinforcement Learning, Enrico Anderlini, Gordon Parker, Giles Thomas
Michigan Tech Publications
To achieve persistent systems in the future, autonomous underwater vehicles (AUVs) will need to autonomously dock onto a charging station. Here, reinforcement learning strategies were applied for the first time to control the docking of an AUV onto a fixed platform in a simulation environment. Two reinforcement learning schemes were investigated: one with continuous state and action spaces, deep deterministic policy gradient (DDPG), and one with continuous state but discrete action spaces, deep Q network (DQN). For DQN, the discrete actions were selected as step changes in the control input signals. The performance of the reinforcement learning strategies was compared …
Closed Loop Energy Maximizing Control Of A Wave Energy Converter Using An Estimated Linear Model That Approximates The Nonlinear Froude-Krylov Force, Yaqzan Mohd Yaqzan
Closed Loop Energy Maximizing Control Of A Wave Energy Converter Using An Estimated Linear Model That Approximates The Nonlinear Froude-Krylov Force, Yaqzan Mohd Yaqzan
Dissertations, Master's Theses and Master's Reports
Wave energy converters (WECs) exploit ocean wave energy and convert it into useful forms such as electricity. But for WECs to be successful on a large scale, two primary conditions need to be satisfied. The energy generated must satisfy the network requirements, and second, energy flow from waves to the grid needs to be maximized. In this dissertation, we address the second problem. Most control techniques for WECs today use the Cummins' linear model to simulate WEC hydrodynamics. However, it has been shown that under the application of a control force, where WEC motions are amplified, the linear model diverges …
Optimization And Control Of Arrays Of Wave Energy Converters, Jianyang Lyu
Optimization And Control Of Arrays Of Wave Energy Converters, Jianyang Lyu
Dissertations, Master's Theses and Master's Reports
Wave Energy Converter Array is a practical approach to harvest ocean wave energy. To leverage the potential of the WEC array in terms of energy extraction, it is essential to have a properly designed array configuration and control system. This thesis explores the optimal configuration of Wave Energy Converters (WECs) arrays and their optimal control. The optimization of the WEC array allows both dimensions of individual WECs as well as the array layout to varying. In the first optimization problem, cylindrical buoys are assumed in the array where their radii and drafts are optimization parameters. Genetic Algorithms are used for …