主配微网共谱“协奏曲” 为用电增保障添绿意

Core Insights - The article discusses the development of a new type of power grid system that enhances electricity reliability, expands green energy usage, and optimizes user experience through the construction of strong main networks and innovative solutions like "self-healing distribution networks" and "smart microgrids" [1] Group 1: Self-Healing Distribution Networks - In Shandong, the State Grid Qingdao Power Supply Company has established a panoramic self-healing system that extends the self-healing capability of the distribution network from feeders to substation busbars, improving electricity reliability [2] - The new system allows for concurrent handling of multiple incidents, significantly enhancing emergency response capabilities during complex faults, reducing the time to restore power from hours to under 3 minutes [2] - The system can diagnose fault types within 30 seconds and automatically generate optimal load transfer strategies, streamlining the restoration process [2] Group 2: Smart Microgrids - Smart microgrids are being developed to promote green energy usage in rural areas, playing a crucial role in the transition to low-carbon living [3] - In Shanxi, a pilot project in Zhuangshang Village has resulted in a solar power generation capacity of 220,000 kWh per year, enabling local households and facilities to utilize green electricity [3] - In Tianjin, a village-level smart microgrid integrates solar power, energy storage, and charging facilities, doubling the village's renewable energy capacity and supporting local tourism and heating needs [3] Group 3: Advanced Technologies for Grid Integration - The integration of distributed renewable energy sources has led to challenges such as voltage limits and multi-level grid coordination, necessitating the development of new technologies [4] - A demonstration project in Shandong has implemented diverse grid connection methods to alleviate voltage issues and enhance stability for high proportions of renewable energy [4] - The Tianjin company has adopted a collaborative model that utilizes real-time data and AI algorithms to optimize energy distribution and support regional energy needs [4]