Climate change is worsening across the region, exacerbating the energy crisis, while traditional centralized energy systems struggle to meet people’s needs. Globally, countries are actively responding to this dual challenge of climate change and energy demand. In September 2020, China introduced a dual carbon target of “Carbon peak and carbon neutrality”. Since then, it has consistently encouraged and supported innovative research on carbon reduction and energy conservation through its resource policies. Distributed energy systems (DESs) are gaining favor in various countries due to their promising applications in energy and environmental realms, particularly in light of current imperatives for energy conservation, emission reduction, and relevant policies. This paper provides a retrospective analysis of recent research and applications of DESs, conducts a systematic classification and statistical overview of DES implementations, and offers insightful recommendations and future prospects for the advancement of DESs.

This paper presents a comprehensive study on optimizing wind farm efficiency by controlling wake effects using the WFSim dynamic simulation model. Focusing on five key factors—yaw wind turbine position, yaw angle, wind farm spacing, longitudinal wind turbine spacing, and yaw rate—we qualitatively analyze their individual and combined impact on the wind farm’s wake behavior and mechanical load. Through a quantitative approach using the orthogonal test method, we assess each factor’s influence on the farm’s overall power output. The findings prioritize the following factors in terms of their effect on power output: yaw wind turbine position, yaw angle, wind farm spacing, longitudinal spacing, and yaw rate. Most significantly, this study identifies optimal working conditions for maximizing the wind farm’s average power output. These conditions include a wind turbine longitudinal spacing of 7.0D, a wind farm spacing of 15.0D, a yaw angle of 30°, and a yaw rate of 0.0122 rad/s, with the first and second rows of turbines in a yaw state. Under these optimized conditions, the wind farm’s average power output is enhanced to 35.19 MW, marking an increase of 2.86 MW compared to the farm’s original configuration. Additionally, this paper offers an analysis of wake deflection under these optimal conditions, providing valuable insights for the design and management of more efficient wind farms.