• Energy Research

In this paper, a renewable energy integration facility (REIF) with photovoltaic (PV) distributed generation resources for micro-grid applications is studied. In grid-tied operation, the PV system together with the grid supply the power to the local loads while the surplus energy is fed back to the grid. In stand-alone mode, a gas micro-turbine is operated as a master to establish the common AC bus voltage to which the PV inverters can synchronize The experimental results demonstrate the stable operation of the REIF under various generation and load conditions. The power quality can meet the IEEE Standard 1547. Furthermore, the responses of the REIF under different fault conditions are investigated. Relevant protection mechanisms are then developed, providing insights into the fault protection for the future grid.

In this paper, a renewable energy integration facility (REIF) with photovoltaic (PV) distributed generation resources for micro-grid applications is studied. In grid-tied operation, the PV system together with the grid supply the power to the local loads while the surplus energy is fed back to the grid. In stand-alone mode, a gas micro-turbine is operated as a master to establish the common AC bus voltage to which the PV inverters can synchronize The experimental results demonstrate the stable operation of the REIF under various generation and load conditions. The power quality can meet the IEEE Standard 1547. Furthermore, the responses of the REIF under different fault conditions are investigated. Relevant protection mechanisms are then developed, providing insights into the fault protection for the future grid.

In renewable energy systems, fluctuating outputs from energy sources and variable power demand may deteriorate the voltage quality. In this paper, a model predictive control strategy without using any proportional-integral-derivative (PID) regulators is proposed. The proposed strategy consists of a model predictive current and power (MPCP) control scheme and a model predictive voltage and power (MPVP) control method. By controlling the bidirectional dc-dc converter of the battery energy storage system based on the MPCP algorithm, the fluctuating output from the renewable energy sources can be smoothed while stable dc-bus voltage can be maintained. Meanwhile, the ac/dc interlinking converter is controlled by using the MPVP scheme to ensure stable ac voltage supply and proper power flow between the microgrid and the utility grid. Then, a system-level energy management scheme is developed to ensure stable operation under different operation modes by considering fluctuating power generation, variable power demand, battery state of charge, and electricity price. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation based on a 3.5-MW PV-wind-battery system with real-world solar and wind profiles.

In renewable energy systems, fluctuating outputs from energy sources and variable power demand may deteriorate the voltage quality. In this paper, a model predictive control strategy without using any proportional-integral-derivative (PID) regulators is proposed. The proposed strategy consists of a model predictive current and power (MPCP) control scheme and a model predictive voltage and power (MPVP) control method. By controlling the bidirectional dc-dc converter of the battery energy storage system based on the MPCP algorithm, the fluctuating output from the renewable energy sources can be smoothed while stable dc-bus voltage can be maintained. Meanwhile, the ac/dc interlinking converter is controlled by using the MPVP scheme to ensure stable ac voltage supply and proper power flow between the microgrid and the utility grid. Then, a system-level energy management scheme is developed to ensure stable operation under different operation modes by considering fluctuating power generation, variable power demand, battery state of charge, and electricity price. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation based on a 3.5-MW PV-wind-battery system with real-world solar and wind profiles.

Predictive control has attracted much attention and has been widely used in power electronics and electric drives. However, further developments for applications in the field of renewable energy systems are still under investigation. In this paper, the principles of predictive control are studied with a focus on model predictive control (MPC) and vector-sequence-based predictive control (VPC). Based on these techniques, two control strategies for flexible power supply are developed. They are implemented in the most promising renewable energy systems, namely solar photovoltaic (PV) systems and wind generators, respectively. The experimental results based on a laboratory prototype show that the active and reactive powers supplied by the PV and wind generator can be controlled flexibly with excellent steady-state and transient performance. As the penetration level of the renewable energy sources in electricity network continues to rise, predictive control tends to be an attractive and powerful technique for power electronics converters in renewable energy systems.

Predictive control has attracted much attention and has been widely used in power electronics and electric drives. However, further developments for applications in the field of renewable energy systems are still under investigation. In this paper, the principles of predictive control are studied with a focus on model predictive control (MPC) and vector-sequence-based predictive control (VPC). Based on these techniques, two control strategies for flexible power supply are developed. They are implemented in the most promising renewable energy systems, namely solar photovoltaic (PV) systems and wind generators, respectively. The experimental results based on a laboratory prototype show that the active and reactive powers supplied by the PV and wind generator can be controlled flexibly with excellent steady-state and transient performance. As the penetration level of the renewable energy sources in electricity network continues to rise, predictive control tends to be an attractive and powerful technique for power electronics converters in renewable energy systems.

Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted.