In this study, virtual inertia control-based vehicle-to-grid (V2G) concept for the secondary load frequency control of AC islanded microgrids (MGs) is presented. Since autonomous modern power grids typically have much smaller inertia in comparison to conventional grids, a very fast and high-performance control plant is necessitated for controlling reserved power plants (e.g., batteries) to overcome any voltage and frequency instability. This issue can be solved by the short-term battery energy storage system, inverter, and proper inertia control technique. Because of the high cost of the battery energy storage system, utilization of controllable loads like electric vehicle (EV) to low-inertia modern power grids is presented for the decreasing of the needed capacity of the energy storage system. Hence, an optimal non-integer model predictive control is applied for the secondary frequency regulation in low-inertia stand-alone MGs with the V2G technology. Since the performance and accuracy of the applied non-integer controller are depended on its parameters’ value, a modified heuristic optimization algorithm is proposed for tuning the controller's parameters. In the end, the validity and feasibility of the proposed method are investigated by the model-in-the-loop experimental results.

中文翻译：

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基于逆变器的现代交流电网V2G技术中的最优非整数模型预测虚拟惯量控制


在本研究中，提出了基于虚拟惯性控制的车对电网（V2G）概念，用于交流孤岛微电网（MG）的二次负载频率控制。由于与传统电网相比，自主现代电网通常具有小得多的惯性，因此需要非常快速且高性能的控制设备来控制备用发电厂（例如电池）以克服任何电压和频率不稳定性。这个问题可以通过短期电池储能系统、逆变器和适当的惯量控制技术来解决。由于电池储能系统的成本较高，因此提出了利用电动汽车（EV）等可控负载到低惯量现代电网来降低储能系统所需容量。因此，采用最优非整数模型预测控制，采用V2G技术对低惯量独立电机进行二次调频。由于所应用的非整数控制器的性能和精度取决于其参数值，因此提出了一种改进的启发式优化算法来调整控制器的参数。最后，通过模型在环实验结果验证了所提方法的有效性和可行性。