Abstract：［Objective］ The severity of flood disasters in underground powerhouses is increasing with the expansion of pumped storage power stations, and the current emergency drainage system of pumped storage power stations cannot meet the large discharge and high-lift demands during periods of abnormal water inflow. This paper proposes a phased parallel emergency drainage method for pumped storage power stations to address the problem of ineffective and slow drainage during underground facility floods. Furthermore, a multi-objective optimization model for emergency drainage is established to solve critical parameters in the drainage plan. ［Methods］ This paper proposes a multi-objective optimization method for emergency drainage in pumped storage power stations. First, based on the engineering characteristics of the underground powerhouses of pumped storage power stations, the emergency drainage process is divided into three stages: early, middle, and late. Second, emergency drainage methods are developed for each stage. During the early stage of drainage, for a small amount of accumulated water in the area above the top floor of the generator, submersible pumps and drainage pipelines are installed in the entrance tunnel to discharge the water to the exit of the tunnel. The middle stage of drainage focuses on draining the accumulated water from the generator floor; multiple drainage vehicles are connected in series to drain the water to the surface. Late-stage drainage is aimed at the accumulated water below the generator floor. A small volume floating pump is used to extract water from each layer, which is then drained to the generator floor. Here, a water storage tank is set up to temporarily store the water extracted by the floating pump; the water is drained in parallel through the entrance tunnel and the maintenance and leakage drainage pipes. Finally, the proposed drainage method is mathematically modeled to minimize drainage time and operating costs as objectives. Furthermore, the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) is employed to obtain the optimal solution for the drainage flow rate at each stage. ［Results］ The phased series-parallel comprehensive emergency drainage method proposed in this paper employs movable drainage equipment, enabling rapid deployment by onsite emergency rescue teams. In the case of a pumped storage power station, 34 drainage schemes are optimized, all of which meet the constraint conditions. Among them, the shortest emergency drainage time is about 52 h, and the minimum operating cost for drainage equipment is approximately 1.38 million RMB, providing a basis for selecting drainage schemes and procuring or customizing drainage equipment. ［Conclusions］ The optimal solution set of drainage flow rates corresponding to each drainage stage can be obtained by updating only the self-attribute data of the power station in the model input using the NSGA-Ⅱ-based multi-objective optimization model for emergency drainage of pumped storage power stations. This method reduces emergency drainage time and equipment operating costs while improving the emergency response level of flood accidents in pumped storage power stations.
[1] 逄立辉,于生波,房恩泽,等.抽水蓄能电站地下厂房洞室系统排水设计浅析[J].水电与抽水蓄能, 2020, 6(6):83-85. PANG L H, YU S B, FANG E Z, et al. Drainage design of underground powerhouse cavern system of pumped storage power station[J]. Hydropower and Pumped Storage, 2020, 6(6):83-85.(in Chinese) [2] 杨彩玲.地铁区间隧道应急排水设置研究[J].都市快轨交通, 2021, 34(4):128-131, 137. YANG C L. Emergency drainage of metro tunnels[J]. Urban Rapid Rail Transit, 2021, 34(4):128-131, 137.(in Chinese) [3] 王西敏.煤矿井下应急排水车的研究[J].机械管理开发, 2019, 34(4):32-33, 36. WANG X M. Research and application of underground emergency drainage vehicle in coal mine[J]. Mechanical Management and Development, 2019, 34(4):32-33, 36.(in Chinese) [4] 宫学东,陈威,朱亚坤.煤矿强排自动控制系统设计[J].工矿自动化, 2017, 43(5):75-78. GONG X D, CHEN W, ZHU Y K. Design of automatic control system of forced drainage of coal mine[J]. Industry and Mine Automation, 2017, 43(5):75-78.(in Chinese) [5] 邢启风.立井水害抢险排水的问题及解决方案[J].矿山机械, 2015, 43(9):141-142. XING Q F. Problems and solutions of emergency drainage for upright well flooding[J]. Mining&Mining Machinery, 2015, 43(9):141-142.(in Chinese) [6] 李栋.潜水泵接力排水技术在矿井抢险排水实践中的应用[J].机械管理开发, 2017, 32(10):62-63, 111. LI D. Application of relay drainage technique of submersible pump in emergency drainage of coal mine[J]. Mechanical Management and Development, 2017, 32(10):62-63, 111.(in Chinese) [7] 佟德利,潘菊芳,谢永兰,等.高扬程、大流量抽水泵技术现状及发展前景[J].水电与抽水蓄能, 2017, 3(4):32-37. TONG D L, PAN J F, XIE Y L, et al. Technology status and development prospects of high-lift and high flow pumps[J]. Hydropower and Pumped Storage, 2017, 3(4):32-37.(in Chinese) [8] 马永杰,云文霞.遗传算法研究进展[J].计算机应用研究, 2012, 29(4):1201-1206, 1210. MA Y J, YUN W X. Research progress of genetic algorithm[J]. Application Research of Computers, 2012, 29(4):1201-1206, 1210.(in Chinese) [9] 王一杰,王发信,王振龙,等.基于NSGA-Ⅲ的水资源多目标优化配置研究:以安徽省泗县为例[J].人民长江, 2021, 52(5):73-77, 85. WANG Y J, WANG F X, WANG Z L, et al. Multi-objective optimal allocation of water resources based on NSGA-Ⅲ algorithm in Sixian County, Anhui Province[J]. Yangtze River, 2021, 52(5):73-77, 85.(in Chinese) [10] WANG D S, TAN D P, LIU L. Particle swarm optimization algorithm:An overview[J]. Soft Computing, 2018, 22(2):387-408. [11] DONG J, DOU Z H, SI S Q, et al. Optimization of capacity configuration of wind-solar-diesel-storage using improved sparrow search algorithm[J]. Journal of Electrical Engineering&Technology, 2022, 17(1):1-14. [12] LI Y B, HUANG W X, WU R, et al. An improved artificial bee colony algorithm for solving multi-objective low-carbon flexible job shop scheduling problem[J]. Applied Soft Computing, 2020, 95:106544. [13] DENG W, ZHANG X X, ZHOU Y Q, et al. An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems[J]. Information Science, 2022, 585:441-453. [14] VERMA S, PANT M, SNASEL V. A comprehensive review on NSGA-Ⅱ for multi-objective combinatorial optimization problems[J]. IEEE Access, 2021, 9:57757-57791. [15] 吴云,曾超,杨侃,等.基于改进NSGA-Ⅱ算法的水资源多目标优化配置[J].人民黄河, 2020, 42(5):71-75. WU Y, ZENG C, YANG K, et al. Multi-objective optimal allocation of water resources based on improved NSGA-Ⅱ algorithm[J]. Yellow River, 2019, 42(5):71-75.(in Chinese) [16] 张志刚,马光文.基于NSGA-Ⅱ算法的多目标水火电站群优化调度模型研究[J].水力发电学报, 2010, 29(1):213-218. ZHANG Z G, MA G W. Study on optimal scheduling model of NSGA-Ⅱ alogorithm for system of hydro and thermal power plants[J]. Journal of Hydroelectric Engineering, 2010, 29(1):213-218.(in Chinese) [17] 顾清华,莫明慧,卢才武,等.求解约束高维多目标问题的分解约束支配NSGA-Ⅱ优化算法[J].控制与决策, 2020, 35(10):2466-2474. GU Q H, MO M H, LU C W, et al. Decomposition-based constrained dominance principle NSGA-Ⅱ for constrained many-objective optimization problems[J]. Control and Decision, 2020, 35(10):2466-2474.(in Chinese)
2023, Vol. 63 
