AI 中文总结
研究海上风电热力增强中完美端点预测的价值，通过将信号嵌入循环平稳马尔可夫决策过程，利用分位数傅里叶回归状态求解线性规划，得出不同时长端点预测对降低年度增强成本的效果及相关结论。
AI 中文摘要
预测价值不仅取决于准确性，还取决于运行模型可用的信息结构。我们研究了一种用于海上风电热力增强的仅当前端点的诊断预测：在时刻t，控制器观测到当前净需求状态z_t和一个完美的未来目标z_{t+h}，但未观测到中间路径或更早的端点消息。与滚动路径预测不同，这些端点信息集在h中不嵌套。我们使用从ISO新英格兰负荷和海上风电数据估计的分位数傅里叶回归状态，将信号嵌入到循环平稳马尔可夫决策过程中，并针对h = 1,..., 6求解年度状态-动作频率线性规划。一小时的端点预测使年度增强成本降低8.07%，而六小时的端点预测使其降低2.28%。成本降低曲线表明，对于单步爬坡决策，单个更远的端点可操作性较低，但这并不意味着更长的滚动预测价值更低。
英文摘要
Forecast value depends not only on accuracy but also on the information structure available to the operating model. We study a diagnostic current-endpoint-only forecast for offshore-wind thermal firming: at hour t, the controller observes the current net-demand state z_t and one perfect future target z_{t+h}, but not the intermediate path or earlier endpoint messages. Unlike rolling path forecasts, these endpoint information sets are not nested in h. We embed the signal in a cyclostationary MDP using quantile Fourier regression states estimated from ISO New England load and offshore wind data, and solve annual state-action-frequency LPs for h = 1, . . . , 6. A one-hour endpoint forecast reduces annual firming cost by 8.07%, while a six-hour endpoint reduces it by 2.28%. The decreasing profile shows that a single farther endpoint is less actionable for a one-step ramping decision, without implying that longer rolling forecasts are less valuable.
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