In an active distribution grid, renewable energy sources (RESs) such as photovoltaic (PV) and energy storage systems (e.g., superconducting magnetic energy storage (SMES)) can be combined with consumers to compose a microgrid (MG). The high penetration of PV causes high fluctuations of tie-line power flow and highly affects power system operations. This can lead to several technical problems such as voltage fluctuations and excessive power losses. In this paper, a fuzzy logic control based SMES method (FSM) and an optimized fuzzy logic control based SMES method (OFSM) are proposed for minimizing the tie-line power flow. Consequently, the fluctuations and transmission power losses are decreased. In FSM, SMES is used with a robust fuzzy logic controller (FLC) for controlling the tie-line power flow. An optimization model is employed in OFSM to simultaneously optimize the input parameters of the FLC and the reactive power of the voltage source converter (VSC) of SMES. The objective function of minimizing the tie-line power flow is incorporated into the optimization model. Particle swarm optimization (PSO) algorithm is utilized to solve the optimization problem while the constraints of the utility power grid, VSC, and SMES are considered. The simulation results demonstrate the effectiveness and robustness of the proposed methods.

中文翻译：

---

基于优化和模糊逻辑的SMES并网微电网联络线潮流控制方法

在主动配电网中，可将诸如光伏（PV）和能源存储系统（例如，超导磁能存储（SMES））之类的可再生能源（RESs）与用户结合起来组成微电网（MG）。PV的高渗透率会引起联络线功率流的大幅波动，并严重影响电力系统的运行。这可能会导致一些技术问题，例如电压波动和过多的功率损耗。本文提出了一种基于模糊逻辑控制的SMES方法（FSM）和一种优化的基于模糊逻辑控制的SMES方法（OFSM），以使联络线潮流最小化。因此，波动和传输功率损失减小了。在FSM中，SMES与鲁棒的模糊逻辑控制器（FLC）一起用于控制联络线潮流。在OFSM中使用优化模型来同时优化FLC的输入参数和SMES的电压源转换器（VSC）的无功功率。最小化联络线潮流的目标函数被纳入优化模型。在考虑公用电网，VSC和SMES约束的情况下，使用粒子群优化（PSO）算法解决了优化问题。仿真结果证明了所提方法的有效性和鲁棒性。在考虑公用电网，VSC和SMES约束的情况下，使用粒子群优化（PSO）算法解决了优化问题。仿真结果证明了所提方法的有效性和鲁棒性。在考虑公用电网，VSC和SMES约束的情况下，使用粒子群优化（PSO）算法解决了优化问题。仿真结果证明了所提方法的有效性和鲁棒性。