为应对高比例新能源消纳，需要推进新能源与煤电的规划与运行，建立考虑不确定性场景生成的源网荷储柔性规划方法。首先用对抗神经网络方法生成春夏秋冬风光不确定性场景，在进一步分析新能源不确定性和煤电灵活性改造特性的基础上，建立考虑新能源与煤电的源网荷储长短期时间尺度双层随机规划模型，探究考虑新能源决策与煤电灵活性改造的源网荷储柔性规划方案，采用场景准确性指标和灵活性不足指标，探究不确定性场景生成方法和规划结果之间的相关性。最后，通过301节点实际算例系统验证所提方法的有效性。所提方案在夏秋季节午时调峰严峻时段深度调峰作用明显，可适应未来大规模新能源消纳，源网荷储经济性更优。

To cope with renewable energy consumption, renewable energy and coal fired flexible retrofit coordination is needed for planning and operation. A generator grid load energy storage flexible planning method is proposed containing renewable energy and coal fired flexible retrofit considering uncertainty scenarios generation. Existing work primarily focused on generator grid coordination, grid energy storage coordination, however, generator grid load energy storage coordinated planning is scarce under high proportional renewable energy integration. For drawbacks of current flexible planning issue，generative adversarial network method is firstly used to consider wind and solar uncertainty, analyze renewable energy uncertainty and coal fire flexible retrofit characteristic. On this basis, a long timescale and short timescale bi-level generator grid load energy storage stochastic planning model is built containing renewable energy and coal fire power units’ coordination. Scenarios accuracy indices and flexible deficiency indices are used to explore the relationship between uncertainty scenarios generation and planning results. Finally, the model is tested by the 301 nodes real system case, the effectiveness of the proposed method is verified. The results show, the proposed method is more effective in deep peak regulation at noon during summer and autumn, adaptable to reduce renewable energy curtailment and more economic in planning results.