Evaluating and optimizing the operation of the hydropower system in the Upper Yellow River: A general LINGO-based integrated framework

The hydropower system in the Upper Yellow River (UYR), one of the largest hydropower bases in China, plays a vital role in the energy structure of the Qinghai Power Grid. Due to management difficulties, there is still considerable room for improvement in the joint operation of this system. This paper presents a general LINGO-based integrated framework to study the operation of the UYR hydropower system. The framework is easy to use for operators with little experience in mathematical modeling, takes full advantage of LINGO’s capabilities (such as its solving capacity and multi-threading ability), and packs its three layers (the user layer, the coordination layer, and the base layer) together into an integrated solution that is robust and efficient and represents an effective tool for data/scenario management and analysis. The framework is general and can be easily transferred to other hydropower systems with minimal effort, and it can be extended as the base layer is enriched. The multi-objective model that represents the trade-off between power quantity (i.e., maximum energy production) and power reliability (i.e., firm output) of hydropower operation has been formulated. With equivalent transformations, the optimization problem can be solved by the nonlinear programming (NLP) solvers embedded in the LINGO software, such as the General Solver, the Multi-start Solver, and the Global Solver. Both simulation and optimization are performed to verify the model’s accuracy and to evaluate the operation of the UYR hydropower system. A total of 13 hydropower plants currently in operation are involved, including two pivotal storage reservoirs on the Yellow River, which are the Longyangxia Reservoir and the Liujiaxia Reservoir. Historical hydrological data from multiple years (2000–2010) are provided as input to the model for analysis. The results are as follows. 1) Assuming that the reservoirs are all in operation (in fact, some reservoirs were not operational or did not collect all of the relevant data during the study period), the energy production is estimated as 267.7, 357.5, and 358.3×108 KWh for the Qinghai Power Grid during dry, normal, and wet years, respectively. 2) Assuming that the hydropower system is operated jointly, the firm output can reach 3110 MW (reliability of 100%) and 3510 MW (reliability of 90%). Moreover, a decrease in energy production from the Longyangxia Reservoir can bring about a very large increase in firm output from the hydropower system. 3) The maximum energy production can reach 297.7, 363.9, and 411.4×108 KWh during dry, normal, and wet years, respectively. The trade-off curve between maximum energy production and firm output is also provided for reference.

黄河上游水电系统（Upper Yellow River, UYR）是中国规模最大的水电基地之一，在青海电网的能源结构中发挥着至关重要的作用。受限于运维管理难度，该系统的联合调度仍存在较大优化空间。本文提出了一套基于LINGO的通用集成框架，用于研究黄河上游水电系统的调度运行。该框架面向缺乏数学建模经验的运行人员，具备良好的易用性，可充分发挥LINGO的各项性能优势（如求解能力与多线程能力），并将用户层、协调层与基础层三层架构整合为一套鲁棒高效的集成解决方案，可作为数据与场景管理及分析的有效工具。本框架具备通用性，仅需少量修改即可迁移至其他水电系统，且可通过丰富基础层功能实现扩展。

本文构建了多目标优化模型，用于权衡水电调度中的发电量总量（即最大发电量）与供电可靠性（即保证出力）。通过等价变换，该优化问题可借助LINGO软件内嵌的非线性规划（Nonlinear Programming, NLP）求解器求解，包括通用求解器、多起点求解器与全局求解器。研究通过仿真与优化两种手段验证了模型的准确性，并对黄河上游水电系统的调度运行进行了评估。本次研究共纳入当前已投运的13座水电站，其中包含黄河干流上两座关键性蓄水水库：龙羊峡水库与刘家峡水库。研究采用2000-2010年的多年历史水文数据作为模型输入开展分析，结果如下：
1) 假设所有水库均处于投运状态（实际研究时段内部分水库未投运或未完整采集相关数据），青海电网在枯水年、平水年、丰水年的发电量预计分别为267.7×10^8千瓦时、357.5×10^8千瓦时与358.3×10^8千瓦时。
2) 若实施该水电系统联合调度，其保证出力可达3110兆瓦（可靠性100%）与3510兆瓦（可靠性90%）。此外，降低龙羊峡水库的发电量可显著提升整个水电系统的保证出力。
3) 枯水年、平水年、丰水年的最大发电量分别可达297.7×10^8千瓦时、363.9×10^8千瓦时与411.4×10^8千瓦时。本文同时提供了最大发电量与保证出力之间的权衡曲线以供参考。