面向中期梯级水电规划的蓄水存量估值框架：Portland General Electric系统研究
A Carryover Storage Valuation Framework for Medium-Term Cascaded Hydropower Planning: A Portland General Electric System Study
AI总结：
针对梯级水电中期规划中蓄水存量未来价值难以量化的问题，提出基于最大发电量模型、LMWV提取和解析线性约束的估值框架，并在Portland General Electric系统验证有效。
摘要：
梯级水电（CHP）的中期规划旨在确定水库中适当的蓄水存量水平，以优化可用水资源的利用。该优化力求最大化当前时期的水力发电量（即即时收益）加上未来时期的潜在水力发电量（即未来价值）。因此，在中期CHP规划中，恰当量化蓄水存量中蕴含的未来价值，对于实现即时收益与未来价值之间的均衡权衡至关重要。为此，本文提出了一个量化蓄水存量未来价值的框架，包含三个主要步骤：i）构建模型，计算给定蓄水存量水平在未来时期能够提供的最大可能水力发电量；ii）对所构建模型应用先分区后提取算法，提取每个水库蓄水存量的隐含区位边际水价值（LMWV）；iii）基于提取出的LMWV制定一套解析规则，以有效计算未来价值。这些规则可作为易处理的混合整数线性约束无缝集成到中期CHP规划模型中，从而恰当量化未来价值，并且易于可视化，可为CHP运营者提供有价值的洞见。最后，在Portland General Electric的一个CHP系统上的数值结果证明，所提出框架能够有效确定适当的蓄水存量价值，从而为中期CHP规划提供支持。
英文摘要：
Medium-term planning of cascaded hydropower (CHP) determines appropriate carryover storage levels in reservoirs to optimize the usage of available water resources. This optimization seeks to maximize the hydropower generated in the current period (i.e., immediate benefit) plus the potential hydropower generation in the future period (i.e., future value). Thus, in the medium-term CHP planning, properly quantifying the future value deposited in carryover storage is essential to achieve a balanced trade-off between immediate benefit and future value. To this end, this paper presents a framework to quantify the future value of carryover storage, which consists of three major steps: i) constructing a model to calculate the maximum possible hydropower generation that a given level of carryover storage can deliver in the future period; ii) extracting the implicit locational marginal water value (LMWV) of carryover storage for each reservoir by applying a partition-then-extract algorithm to the constructed model; and iii) developing a set of analytical rules based on the extracted LMWV to effectively calculate the future value. These rules can be seamlessly integrated into medium-term CHP planning models as tractable mixed-integer linear constraints to quantify the future value properly, and can be easily visualized to offer valuable insights for CHP operators. Finally, numerical results on a CHP system of Portland General Electric demonstrate the effectiveness of the presented framework in determining proper carryover storage values to facilitate medium-term CHP planning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
