Kaitlyn J. Bunker

Optimization of grid-connected wind and battery energy storage system

This paper implements optimal control strategies in the scenario of a battery energy storage system connected to the electric grid together with a wind turbine. A simplified model for a battery is first developed, along with a state equation model of the system. Optimal control is used to minimize the difference between the actual battery power and the given reference power. The battery is connected to the grid through a buck converter, and the optimal control solution is used to calculate the necessary duty cycle to achieve the desired results. Inequality constraints are added to ensure that the simulation is a realistic model of the behavior of a battery. The control strategy is also demonstrated experimentally with a battery and sample grid system.

Microgrid frequency regulation using wind turbine controls

This paper proposes a control system that uses wind energy to regulate the frequency of an islanded microgrid. The model used in both computer and hardware simulation includes a scaled representation of a microgrid that uses a permanent magnet AC (PMAC) machine and a variable resistance load. The wind turbine is represented by a DC machine as the prime mover connected with a PMAC generator. As the microgrid load changes the frequency of the system changes and the proposed control system regulates power from the wind turbine as necessary to correct the frequency and maintain a nominal value. Results of both computer simulation and hardware implementation show that wind energy can be used to maintain microgrid frequency in islanded operation.

Optimal geometric control of Dc microgrids

Droop control is a common method used in power systems to share load between multiple sources. In a dc system, traditional droop control utilizes a linear relationship to determine the reference current for each source based on the changing bus voltage. This paper presents a method for finding a nonlinear droop relationship in order to optimize the source operation to meet a given objective. The method is implemented for an example dc microgrid system. Simulation and hardware-in-the-loop (HIL) results are presented.