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山西电力现货市场出清周期缩短至5分钟 价格信号频次提升3倍
Zhong Guo Neng Yuan Wang·2025-11-05 01:00

Core Insights - Shanxi Electric Power successfully completed the integration testing of the 15-minute and 5-minute real-time electricity spot market operation from September 1 to October 20, 2025, marking a shift to a higher frequency and more precise market operation [1] - Since its launch in April 2021, Shanxi's spot market has traded a cumulative electricity volume of 1.62 trillion kilowatt-hours, effectively optimizing the allocation of electricity resources through price signals [1] - The adjustment to a 5-minute clearing period allows for quicker and more accurate reflection of instantaneous supply and demand changes in the grid, providing clearer price signals for market participants [1][2] Market Development - The adjustment is in response to the rapid growth of renewable energy in Shanxi, with installed capacity increasing by 128.75% since the 14th Five-Year Plan, reaching 76.84 million kilowatts by September 2025, accounting for nearly 50% of the province's total installed capacity [2] - The previous 15-minute clearing period was inadequate for the new power system's real-time balancing requirements due to the volatility of renewable energy output and rapid changes in supply-demand relationships [2] - The upgrade involved comprehensive enhancements to nine core modules of the real-time market model management, ensuring compatibility of the clearing, measurement, and settlement systems [2] Technological Advancements - The implementation of a 5-minute clearing mechanism facilitates the participation of new market entities such as virtual power plants and distributed energy storage, allowing them to adjust their charging and discharging strategies based on more frequent price signals [2] - The average deviation rate of real-time power balancing has decreased by 20% after the system's upgrade, enhancing the precision and stability of grid operations [2] - Shanxi Electric Power aims to continue advancing electricity market construction and optimize resource allocation on a larger scale [2]