基于模型预测控制的光伏-混合储能系统并网微电网电能质量提升与功率管理

The weather-dependent nature of renewable energy sources poses challenges in supplying consistent power and the usages of power electronics devices gives rise to power quality issues by introducing harmonics at the point of common coupling (PCC) in a grid interactive system. This paper presents a grid connected photovoltaic (PV) system equipped with hybrid energy storage system (HESS) aimed at addressing these issues. The primary objective of this paper is to ensure a continues, high quality power supply to the loads, while achieve seamless power transfer among the generation, storage and consumption. To achieve this, the power converters are controlled using a finite control set-model predictive control (FCS-MPC) algorithm, resulting in optimal power management. In addition, a modified leaky least mean square (MLLMS) algorithm is applied to the three-phase voltage source converter (VSC), improving the system's ability to extract the fundamental components of load current, allowing for rapid adaptation to dynamic operational conditions and mitigating harmonic distortion. In order to achieve proper management of the hybrid energy storage system, an active power balancing strategy, which incorporates the State of Charge (SoC) levels of the available storage devices, is adopted for effective control of the DC-DC converters within the system. The system was modeled and simulated in MATLAB/Simulink considering various load and PV generation conditions, proving its capability to operate under various extremes. The experimental validation of a laboratory scale prototype indicates the possibility of enhanced power quality and efficient energy management that is essential for modern grid-interactive microgrids.