面向洞庭湖生态需水的三峡水库蓄水期优化调度研究

为减轻三峡水库蓄水对洞庭湖生态系统的不利影响,本文建立了以洞庭湖最小生态需水满足度和三峡水电站发电量最大为目标的水库优化调度模型。调度模型耦合支持向量回归技术构建了洞庭湖水位变化的主要驱动因素与最小生态需水满足度关系,采用混沌遗传算法对模型进行求解。开展了不同典型年下三峡水库蓄水期优化调度研究,结果表明:优化调度后,平水年洞庭湖最小生态需水满足度由常规调度的85.40%提高至89.44%,三峡水电站发电量增加3.09%;丰水年常规调度即可满足洞庭湖最小生态需水要求,优化后发电量增加5.85%;枯水年洞庭湖最小生态需水满足度由65.58%提高至66.42%,发电量增加3.42%。研究成果可为通过三峡水库优化调度改善洞庭湖生态环境提供理论基础和具体方案的参考。

Three Gorges reservoir optimal operation in its storage period for ecological water demands by Dongting Lake

To mitigate adverse effects caused by impoundment of the Three Gorges reservoir (TGR), a reservoir optimization model for improving the satisfaction of minimum ecological water demands (SMEWD) by the Dongting Lake and increasing the TGR power output has been developed in this work. This optimization model couples a water level prediction method using support vector regression (SVR) and is solved with a chaos-genetic algorithm (CGA). The results show that both the SMEWD and the power output were significantly improved via optimization of the TGR operation. In an average year, the satisfaction was increased from 85.40% to 89.44%, and the power output increased by 3.09%; In a wet year, conventional operation was able to meet the minimum ecological demands with an increase of 5.85% in the output; In a dry year, the satisfaction was increased from 65.58% to 66.42% with the output increased by 3.42%. This study demonstrates that improvement on the ecological environment of river-connected lakes can be achieved by optimizing reservoir operation.