In the rapidly evolving landscape of energy systems, the integration of renewable energy sources has become a strategic priority, particularly in China with its ambitious “carbon peaking and carbon neutrality” goals. However, this shift has introduced significant challenges, notably the increased unpredictability and volatility in power grid operations. Daren Li, a researcher at State Grid Wenzhou Electric Power Supply Company, is at the forefront of addressing these issues with groundbreaking research published in the journal ‘Inventions’.
Li’s work focuses on the aggregation and evaluation of flexibility resources in new power systems, a critical aspect of ensuring grid stability and efficiency. As the penetration of new energy sources like wind and solar increases, traditional power grid dispatching methods struggle to keep up. “The randomness and volatility of power grid operations have become increasingly serious,” Li explains, highlighting the need for innovative solutions.
The core of Li’s research lies in the development of a multi-time scale flexible resource aggregation method. This method categorizes flexibility resources—such as distributed power supplies, energy storage systems, and controllable loads—based on their response time scales. By doing so, Li aims to enhance the economic operation and advanced user-side response strategies of new power systems.
One of the key innovations in Li’s approach is the use of an improved Minkowski aggregation algorithm. This algorithm allows for the precise quantification of regulation capabilities across different time scales, from seconds to days. “The advantage of this method is that it can optimize the response according to different system requirements and ensure the highest matching and fastest response speed to the system requirements,” Li states, underscoring the method’s potential to revolutionize power grid scheduling.
The implications of this research are vast. For energy providers, the ability to accurately aggregate and utilize flexibility resources means improved grid stability, reduced peak loads, and lower investment costs. This could lead to more efficient and cost-effective power distribution, benefiting both consumers and energy companies.
Moreover, Li’s work addresses the “dimensional disaster” problem, where the sheer scale and heterogeneity of flexible resources make traditional aggregation methods inefficient. By clustering resources based on response time scales, Li’s method provides a more manageable and accurate approach to resource management.
The commercial impact of this research is significant. Energy companies can leverage Li’s findings to optimize their grid operations, reduce costs, and enhance service reliability. This could lead to a more robust and resilient energy infrastructure, capable of meeting the demands of a rapidly evolving energy landscape.
As the energy sector continues to evolve, research like Li’s will be crucial in shaping future developments. By providing a more scientific and reasonable flexible resource allocation scheme, Li’s work offers a pathway to a more stable and efficient power grid. This could pave the way for further innovations in energy management, benefiting both the industry and consumers alike.
