Tuyen V. Vu

Robust adaptive droop control for DC microgrids

Abstract There are tradeoffs between current sharing among distributed resources and DC bus voltage stability when conventional droop control is used in DC microgrids. As current sharing approaches the setpoint, bus voltage deviation increases. Previous studies have suggested using secondary control utilizing linear controllers to overcome drawbacks of droop control. However, linear control design depends on an accurate model of the system. The derivation of such a model is challenging because the noise and disturbances caused by the coupling between sources, loads, and switches in microgrids are under-represented. This under-representation makes linear modeling and control insufficient. Hence, in this paper, we propose a robust adaptive control to adjust droop characteristics to satisfy both current sharing and bus voltage stability. First, the time-varying models of DC microgrids are derived. Second, the improvements for the adaptive control method are presented. Third, the application of the enhanced adaptive method to DC microgrids is presented to satisfy the system objective. Fourth, simulation and experimental results on a microgrid show that the adaptive method precisely shares current between two distributed resources and maintains the nominal bus voltage. Last, the comparative study validates the effectiveness of the proposed method over the conventional method.

An Alternative Distributed Control Architecture for Improvement in the Transient Response of DC Microgrids

Distributed secondary control plays an important role in dc microgrids, since it ensures system control objectives, which are power sharing and dc-bus voltage stability. Previous studies have suggested using a control architecture that utilizes a parallel secondary bus voltage and current sharing compensation. However, the parallel controllers have a mutual impact on each other, which degrades the transient performance of the system. This paper reports on an alternative distributed secondary control architecture and controller design process, based on small-signal analysis to alleviate the mutual effect of the current sharing and bus voltage compensation, and to improve the transient response of the system. Experimental results confirm the improved transient performance in the current sharing control and dc-bus voltage stability utilizing the proposed control architecture.

MPC-based power management in the shipboard power system

This paper represents the development of an intelligent control by applying model predictive control to the power management of a DC-based ship system. In a shipboard power system, the control approach should ensure optimal load sharing among generators while maintaining the DC bus voltage stability. Model predictive control is a promising optimal control which has been proven to be efficient and robust for dynamic systems. Model predictive control is applied in order to meet the load centric energy/power demand. It will provide a predictive and adaptive approach to energy/power management routines. The algorithm and method are presented and validated through simulation in MATLAB/Simulink and PLECS.

Predictive Control for Energy Management in Ship Power Systems Under High-Power Ramp Rate Loads

Electrical weapons and combat systems integrated into ships create challenges for their power systems. The main challenge is operation under high-power ramp rate loads, such as rail-guns and radar systems. When operated, these load devices may exceed the ships generators in terms of power ramp rate, which may drive the system to instability. Thus, electric ships require integration of energy storage devices in coordination with the power generators to maintain the power balance between distributed resources and load devices. In order to support the generators by using energy storage systems, an energy management scheme must be deployed to ensure load demand is met. This paper proposes and implements an energy management scheme based on model predictive control to optimize the coordination between the energy storage and the power generators under high-power ramp rate conditions. The simulation and experimental results validate the proposed technique in a reduced scale, notional electric ship power system.

Real-time distributed power optimization in the DC microgrids of shipboard power systems

Distributed control will play an important role in the shipboard power systems flexibility and will ensure the achievable system objectives. Distributed control has been widely used for low voltage DC microgrids. However, they are still limited to modeling the system for the power sharing solution instead of presenting an adequate configuration of distributed control in both power and energy control levels. In this paper, a practical power and energy management architecture for the ship power system is defined, and a real-time distributed optimization is developed based on particle swarm optimization for the power controller parameters optimization.

Model predictive control for power control in islanded DC microgrids

Islanded DC microgrid architecture and control have become popular recently. One of the main control architectures is the DC bus voltage following type, where a main generator controls the DC bus voltage and the others follow the bus voltage and the power commands. Conventionally, the power regulation in the following generators is often employed with the droop control method. The main problem of the droop control is the non-precise power sharing characteristic. One of the improvement approaches is to use PI controllers for correcting the power share. However, PI controllers do not provide optimal control. Thus, in this paper a new power control method utilizing model predictive control is proposed and applied in the power control for islanded DC microgrids. The algorithm and method are presented and validated through simulation in MATLAB/Simulink and PLECS.

A heuristic method for optimal energy management of DC microgrid

This paper proposes a sufficient method for the optimal operation and management of DC microgrids (MGs) in the presence of renewable energy sources (RESs), storage devices, and DC loads. The DC MG concept can not only exploit the distinguished features of DC distribution systems for feeding DC loads without the presence of AC-DC converters but also provide convenient connections for DC distributed generations (DGs) and storage devices for a more efficient, reliable, and low-cost operation of MGs. In order to build a robust approach for the DC MGs energy management, a powerful optimizer that relies on the crow search algorithm (CSA) is developed to obtain the optimal solution. Moreover, a two-stage modification approach is illustrated to avoid being trapped in the local minima of the optimization algorithm and to enhance the search capability of CSA. The feasibility and performance of the proposed method in DC MG applications are evaluated in three different scenarios using a notional test system. The results are compared with others optimization algorithms and corroborates the advantage of the CSA technique.

Distributed adaptive control design for cluster of converters in DC distribution systems

In this paper, we address the control design problem under the systems model uncertainty utilizing the adaptive control. First, the adaptive control based on the model reference adaptive control technique is presented. Subsequently, the adaptive control technique is applied to a multi-converter system to guarantee the bus-voltage stability and accurate current sharing. Simulation in MATLAB/Simulink is conducted to verify the effectiveness of the proposed control algorithm under typical scenarios including non-linear load change and network topology changes caused by converter failures.

Low-voltage ride-through for PV systems using model predictive control approach

This paper focuses on the use of model predictive control (M PC) to control a two-stage photovoltaic (PV) system in order to accomplish new grid code standards for low-voltage ride-through (LVRT). The PV system is composed by a DC/DC boost converter at the generator-side, followed by a two-level three-phase grid - tied inverter. The PVs voltage support function through reactive power injection is examined using the mentioned control technique, and a PV power-reference tracking system is implemented during the Voltage sag to avoid the activation of the overcurrent tripping mechanism. The system is modeled in Matlab/Simulink and PLECS in order to understand its operation, and to evaluate the effectiveness of the MPC proposed algorithm to fulfill LVRT requirements for PV Systems.

Seamless inverter control scheme for shore-to-ship application

This paper proposes a general seamless control scheme of inverter for the purpose of ship-to-shore connection by means of active islanding detection method. In the proposed system, the Sandia Frequency Shift (SFS) method combined with a frequency protection scheme is used to detect the islanding instant. The SFS parameter selection is performed using a new phase criterion proposed in the literature. and implemented to add more functionality to the control algorithm.