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基于IBBO-DP模型的水电机组负荷分配优化 被引量:3

Optimization of hydropower unit load distribution based on the IBBO-DP model
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摘要 针对水电机组传统负荷分配模型在运行时所面临的机组穿越振动区次数多、机组出力波动大的问题,该研究建立水电机组多目标多约束双层智能寻优模型。外层模型基于动态规划方法,构建多约束下机组组合优化模型;内层模型基于改进生物地理学算法,从种群个体适应度关系提出动态迁移模型,将混合交叉思想引入迁移算子自适应更新策略,同时以机组组合是否发生变化为判断条件建立机组出力波动约束,构建机组负荷分配优化模型。实例计算结果表明,与传统方法相比,所提模型收敛、寻优能力有明显提高,在负荷分配过程中可节省10.56%的耗水量,同时可有效平抑60.24%的机组平均出力波动幅度,并避免24次振动区穿越,大幅提升机组避振能力以及运行稳定性、可靠性,在水电机组实际运行过程中具有广泛的工程应用价值。 The traditional load distribution model of hydropower units has been confined to the"dimension explosion"in the calculation,due to the redundant constraints during operation,leading to the slow solution speed and low efficiency of the model.There are many times of units crossing the vibration zone,and a large fluctuation of unit output in the load distribution.In this study,a multi-objective multi-constraint double-layer intelligent optimization model was established for the hydropower units using the coupled dynamic programming(DP)and improved biogeography-based optimization(IBBO).The minimum water consumption in the process of load distribution was taken as the optimization objective,and the 15-minute duration was taken as the minimum load distribution period to calculate the short-term load distribution of hydropower units.A multi-constraint optimization model of the hydropower unit was constructed using the DP outer layer.The average fitness of the population was introduced into the inner layer using the IBBO.A dynamic migration model was then established from the relationship between the average fitness of the population and the individual fitness.The mixed crossover was introduced into the adaptive updating strategy of the migration operator.The unit load distribution optimization model was constructed using the unit output fluctuation constraints,according to the unit combination.Taking the data of demand load and generating head of a hydropower station on a certain day as an example,firstly,the iterative convergence times of the improved IBBO increased from 45-50 to 20 generations,and the traffic consumption was reduced by 1.28%and 1.82%,respectively,compared with the traditional IBBO and BBO,when the minimum traffic consumption was taken as the fitness function of the model.The convergence and optimization of the improved IBBO were outstandingly improved by the migration model and operator of the algorithm.Secondly,the IBBO-DP model saved 10.56%of water consumption,compared with the double-layer dynamic programming(DDP)model.The zero crossing of the vibration zone of the unit was achieved in 50 calculations on average,leading to the reduced 24 crossing of the vibration zone,compared with the DDP model.Finally,the IBBO-DP model effectively stabilized 60.24%of unit average output fluctuation amplitude,and 47.28%of unit output fluctuation ratio,compared with the DDP model,considering the constraint of unit output fluctuation.There was a great increase in the unit vibration avoidance,operation stability,and reliability in the process of load distribution of hydropower units.Consequently,the double-layer intelligent optimization model was constructed to consider the fluctuation constraint of unit output,and then a case study was used to verify the load distribution optimization of hydropower units,indicating a wide range of engineering applications for the actual operation of hydropower units.This finding can also provide a strong reference for the subsequent operation of hydro-photovoltaic complementary power generation.
作者 罗正亮 潘虹 李大成 冯方 郑源 Luo Zhengliang;Pan Hong;Li Dacheng;Feng Fang;Zheng Yuan(Energy and Electrical College of Hohai University,Nanjing 211100,China;China Power Construction Group Guiyang Survey,Design and Research Institute Co.,Ltd.,Guiyang 550000)
出处 《农业工程学报》 EI CAS CSCD 北大核心 2022年第6期213-220,共8页 Transactions of the Chinese Society of Agricultural Engineering
基金 国家重点研发计划政府间国际科技创新合作重点专项(2019YFE0105200) 华能集团总部科技项目‘澜沧江西藏段千万千瓦清洁能源基地建设水光互补关键技术研究(HNKJ20-H20)’ 国家自然科学基金(51809082)。
关键词 振动 优化 水电站 改进生物地理学算法 负荷分配 vibration optimization hydroelectric power plants improved biogeography-based optimization load distribution
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