摘要
【目的】随着双碳目标的深入推进,新能源发电与智算中心的协同发展成为优化能源结构、提升算力基础设施绿色化水平的关键路径。本文通过构建综合成本评估模型,探索AI驱动的新能源发电与智算中心协同选址方法,为降低碳排放、提升能源利用效率提供科学依据。【方法】提出了一种基于熵权法的新能源发电与智算中心协同选址成本分析方法,综合考虑建设成本、运营成本、环境成本以及政策支持和补贴等因素,构建成本评估模型,并通过熵权法确定各因素的权重系数,计算出各城市的综合成本,选出最优选址。【结果】分析结果表明,西部城市H凭借丰富的新能源资源、低廉的土地与运营成本、显著的环境成本优势(碳排放成本降低80%)以及积极的政策支持,综合成本最低为0.0355,显著优于东部城市E的0.8114和城市F的0.9941。新能源发电的高渗透率有效支撑了智算中心的绿色化运营,验证了协同发展的可行性与经济性。【结论】AI驱动的协同选址模式可加速“东数西算”工程与新能源基地的深度融合,推动算力产业从“高耗能”向“高效能”转型。研究为新能源与智算中心的区域协同布局提供了科学决策框架,未来需进一步结合AI技术优化动态调度与跨区域电网协同,为实现双碳目标及新型电力系统构建提供支撑。
[Objective]With the in-depth promotion of the carbon peaking and carbon neutrality target,the synergistic development of new energy generation and intelligent computing centers has become a key path to optimize the energy structure and enhance the greening level of arithmetic infrastructure.This paper explores the AI-driven synergistic siting method of new energy generation and intelligent computing centers by constructing a comprehensive cost assessment model to provide a scientific basis for reducing carbon emissions and enhancing energy use efficiency.[Methods]The study proposes a cost analysis method based on the entropy weight method for synergistic siting of new energy generation and intelligent computing centers,and builds a cost assessment model by comprehensively considering the construction cost,operation cost,environmental cost,and policy support and subsidy,and determines the weight coefficients of each factor through the entropy weight method,and calculates the comprehensive cost of each city,thereby selecting the optimal location.[Results]The analysis indicates that the western city H has the lowest comprehensive cost(0.0355),which is significantly better than the eastern cities E(0.8114)and F(0.9941)by virtue of abundant new energy resources,low land and operation costs,significant environmental cost advantages(80%reduction in the cost of carbon emissions),and active policy support.The high penetration of new energy generation effectively supports the green operation of intelligent computing centers,verifying the feasibility and economy of synergistic development.[Conclusion]The AI-driven synergistic site selection model can accelerate the deep integration of the‘East Counts,West Counts’project and the new energy base,and promote the transformation of the computing industry from‘high energy consumption’to‘high efficiency’.The study provides a scientific decision-making framework for the regional coordinated layout of new energy and intelligent computing centers,and in the future,it is necessary to further combine AI technology to optimize dynamic scheduling and cross-regional grid coordination,which will provide support for the realization of the carbon peaking and carbon neutrality goal and the construction of a new type of power system.
作者
杨淑琴
罗军
胡文森
YANG Shuqin;LUO Jun;HU Wensen(CHN Energy Digital Intelligence Technology Development(Beijing)Co.,Ltd.,Beijing 100013,China;CHN Energy Investment Group Co.,Ltd.,Beijing 100011,China)
出处
《电力科技与环保》
2025年第4期611-617,共7页
Electric Power Technology and Environmental Protection
关键词
新能源发电
智算中心选址
能源协同
成本分析
熵权法
new energy generation
intelligent computing center site selection
energy synergy
cost analysis
entropy weight method
