In the quest to integrate more renewable energy into regional power grids, researchers have developed a novel approach to smooth out the fluctuations inherent in wind and solar power. This method, detailed in a recent study published in the journal *Wind Energy Science*, could significantly enhance the stability and efficiency of regional energy systems, offering a promising solution to one of the sector’s most pressing challenges.
The research, led by Y. Zhu from the Power Grid Planning and Research Center at Guizhou Power Grid Co., Ltd., introduces a load-power smoothing technique that leverages the concept of “one source with multiple loads.” This approach considers the proximity between energy sources and loads, as well as the correlation between their power fluctuations, to optimize the matching of wind and solar energy outputs with different loads.
“Our method aims to fully utilize the stable output from the low-frequency correlation of wind and solar energy, combined with energy storage, to significantly reduce the fluctuation rate of regional grid-connected loads,” explained Zhu. This innovative strategy not only promotes local absorption of source loads but also alleviates the pressure on the grid caused by the randomness and volatility of renewable energy sources.
The study employs advanced algorithms to achieve this optimization. Loads are initially clustered and divided based on power frequency division. The EEMD (Ensemble Empirical Mode Decomposition) algorithm is then applied to obtain wind and solar energy outputs with greater complementarity and smoother fluctuations. A load-tracking coefficient is used to compare the matching degree between wind–solar power output and different loads, selecting the most compatible load and output for source–load matching and smoothing.
To further enhance the system’s efficiency, the researchers utilized a gray-wolf-optimization (GWO) algorithm based on Tent chaotic mapping to optimize edge energy storage at different load sides. This dual approach minimizes overall grid-connected load-power fluctuations, ensuring a more stable and reliable energy supply.
The numerical results demonstrate the effectiveness of the proposed method. By integrating wind and solar energy outputs with compatible loads and optimizing energy storage, the fluctuation rate of regional grid-connected loads is significantly reduced. This not only improves the stability of the power grid but also enhances the commercial viability of renewable energy projects.
The implications of this research are far-reaching. As the energy sector continues to transition towards renewable sources, the ability to smoothly integrate wind and solar power into regional grids will be crucial. Zhu’s work provides a robust framework for achieving this goal, offering a practical solution that can be implemented by energy providers and grid operators worldwide.
“This research represents a significant step forward in the integration of renewable energy into regional power grids,” said a senior energy analyst who reviewed the study. “By addressing the challenges of fluctuation and volatility, it paves the way for a more stable and sustainable energy future.”
As the energy sector continues to evolve, the insights gained from this study will undoubtedly shape future developments in the field. The integration of advanced algorithms and energy storage optimization strategies offers a promising path forward, ensuring that renewable energy can be harnessed effectively and efficiently.