Abstract
Regarding the microgrid with large-scale electric vehicle (EV) energy storage systems working at the vehicle-to-grid (V2G) mode, uncertain factors (e.g., the number of EVs feeding the microgrid shifts frequently) make the system unfixed, leading to the fact that it is difficult to precisely determine the real-time droop coefficients of the system, thereby degrading the performance of the traditional inverter control strategies that rely on the droop coefficients. To solve the problem, this paper proposes an errorless-control-targeted double control loop (DCL) technique based on robust MPC to control the microgrid with EV energy storage systems without using droop coefficients. Firstly, the structure of the DCL method is developed, with each component in the structure detailed. Compared to the traditional control strategies, the novel one regards the frequency, voltage, and currents as the control objectives instead of active/inactive power. It deserves to be mentioned that the frequency and voltage are regulated by proportional-integral controllers, while the currents are regulated by the finite control set model predictive control (FCS-MPC) method. Secondly, the impacts of system parameter uncertainties on the prediction accuracy of the FCS-MPC controller are analyzed clearly, illustrating that it is necessary to develop effective techniques to enhance the robustness of the controller. Thirdly, sliding mode observers (SMO) based on a novel hyperbolic function are constructed to detect the real-time disturbances, which can be used to generate voltage compensations by using automatic disturbance regulators. Then, the voltage compensations are adopted to establish a modified predicting plant model (PPM) used for the FCS-MPC controller. By using the proposed SMO-based disturbance detection and compensation techniques, the MPC controller gains a strong robustness against parameter uncertainties. Finally, a simulation is conducted on a microgrid system to verify the effectiveness of the proposed techniques, and the obtained results are compared with the traditional virtual synchronous machine (VSG) strategy relying on droop coefficients.
Highlights
Nowadays, the microgrid which contains distributed generation and energy storage is one of the most promising power generation and supply systems because it has the advantages of high flexibility, eco-friendliness and sustainability [1,2]
We propose a novel double control loop (DCL) strategy based on robust model predictive control (MPC) theory to achieve errorless frequency and voltage regulation for the microgrids with uncertain electric vehicle (EV) energy storage systems
The simulation was conducted on a microgrid system of which parameters are given in Table 2 to verify the effectiveness of the proposed errorless-control-targeted technique based on the robust MPC controller
Summary
The microgrid which contains distributed generation (e.g., photovoltaic, wind, and tidal generation, etc.) and energy storage (e.g., batteries and super-capacitors, etc.) is one of the most promising power generation and supply systems because it has the advantages of high flexibility, eco-friendliness and sustainability [1,2]. When the microgrid operates at the island mode (see Figure 1), it needs to independently supply power for the local DC/AC loads, such as electric vehicles (EVs), household and industrial electric apparatuses, etc. Among those loads, EVs are special because they have rechargeable energy storage systems (RESS), and as a result, they can feed the DC-bus of the microgrid when the other types of loads are heavy. In this case, the performance of the traditional control strategies based on droop control will decline unless the real-time droop coefficients cannot be provided
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