Improving V2G Systems Performance with Low-Pass Filter and Fuzzy Logic for PV Power Smoothing in Weak Low-Voltage Networks

The rapid integration of photovoltaic (PV) energy into weak low-voltage networks presents significant challenges to grid stability and power quality, highlighting the need for effective power smoothing methods. This paper proposes and evaluates three fuzzy logic-enhanced power smoothing techniques—V2GGlide (low-pass filter), V2GSUN (moving average filter), and V2GSmooth (ramp rate filter)—integrated with a lithium-ion battery energy storage system. The methods were tested under three distinct state-of-charge (SoC) conditions. Results show that V2GGlide achieved the highest variance reduction (22.24%) at high SoC levels, providing superior performance in mitigating power fluctuations and ensuring stable grid output. V2GSUN demonstrated consistent effectiveness, achieving variance reductions of up to 17.82% under low SoC conditions, making it well-suited for systems with intermediate storage availability. V2GSmooth exhibited balanced performance across all SoC levels, combining efficient energy delivery with reduced battery degradation, particularly at lower SoC levels. The proposed methods were validated under real-world conditions in a low-voltage microgrid laboratory connected to a public distribution network, confirming their practical applicability for enhancing PV energy integration and grid stability.