Fuzzy Logic Control and Optimization in New Energy System Scheduling

The scheduling of New Energy (NE) systems is greatly affected by the volatility of renewable energy sources such as wind and solar power, and traditional control methods are difficult to cope with these uncertain factors. This article introduces Fuzzy Logic Control (FLC) and optimization strategies to improve the scheduling efficiency and stability of the system. This article first analyzes the difficulties in power grid scheduling caused by the volatility and uncertainty of renewable energy sources such as wind power and photovoltaics in NE system scheduling. Then, a scheduling model based on FLC is designed by introducing fuzzy rules and membership functions. This model fuzzifies input variables such as wind speed and light intensity through fuzzy rules, and evaluates the power generation status in real time by combining membership functions, and then dynamically adjusts the output power to cope with changes in NE power generation. Finally, by monitoring real-time fluctuations in power generation and dynamically adjusting scheduling strategies, precise matching between load demand and power generation capacity can be achieved. The fuzzy logic optimization scheduling model has significant advantages in dealing with NE fluctuations, with fast response and stable supply-demand matching. Tests have shown that output power fluctuations have been reduced by 20%, power supply stability has been improved by 18%, system efficiency has been optimized, and energy loss has been reduced by 12%, providing an efficient solution for NE scheduling. FLC and optimization strategies effectively respond to NE power generation fluctuations, accurately match power generation with demand, and improve scheduling efficiency and grid stability. This study verifies its high application value and provides strong support for the optimization of smart grid scheduling.