远景田庆军：源网荷储是能源转型的必由之路，AI储能将重塑电力系统格局

Core Insights - The article emphasizes the importance of the synergy between source, grid, load, and storage (源网荷储) as the future of energy transition, highlighting the need for AI storage to drive industry transformation [2][5]. Group 1: Industry Trends - The evolution of the power system will follow two key paths: the implementation of numerous source-grid-load-storage projects, some operating in off-grid modes, and the deepening of electricity market reforms, which will introduce uncertainties for renewable energy asset revenues [3]. - As of August, the cumulative installed capacity of wind and solar power reached 1.7 billion kilowatts, with a target of 3.6 billion kilowatts by 2035, indicating a significant growth opportunity of 1.9 billion kilowatts [2]. Group 2: AI Storage Solutions - AI storage is defined by two main components: the "trading agent," which functions like an electricity trader with capabilities in power forecasting, trading control, and real-time market perception, and the "networking agent," which acts as a power dispatcher ensuring stable grid operation [5]. - The transition from traditional power dynamics of "source following load" to "source-load interaction" is crucial, promoting intelligent interaction and optimization among power sources, grids, loads, and storage [5]. Group 3: Challenges and Barriers - Despite strong national policies supporting the development of source-grid-load-storage systems, challenges such as inconsistent technical standards, difficulties in grid access, and an underdeveloped market mechanism remain significant barriers to project implementation [6]. - Four major market issues were identified: forced high ratios of abandoned electricity due to surplus power, lagging market mechanisms limiting project flexibility, lack of transparency in electricity pricing, and high technical and management difficulties affecting operational efficiency [6]. Group 4: Future Outlook - The key to addressing the core challenges of source-grid-load-storage lies in possessing "full-chain system integration capabilities," which includes understanding both the energy system and intelligent manufacturing [7]. - AI storage is projected to be a critical technological pathway for solving the synergy challenges, with a focus on integrating trading and networking agents to establish sustainable profit models and enhance system value [7][8].