Journal of Guangdong University of Technology ›› 2017, Vol. 34 ›› Issue (04): 72-77.doi: 10.12052/gdutxb.160108

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Cascade Reservoirs Operation Optimization Based on Crisscross Optimization Algorithm

Wang Lang, Meng An-bo, Li Jin-bei, Wei Ming-lei   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2016-08-20 Online:2017-07-09 Published:2017-07-09

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Abstract:

An optimal operation model for hydropower station is characterized by multiple constraints, high-dimension, nonlinearity, and difficult model solution. To surmount these problems, a Crisscross optimization (CSO) algorithm is presented to solve the model. Crisscross optimization algorithm searches the global optimum using a dual cross search mechanism, which can improve the ability of the global optimization searches via the organic integration of the two crossover operators by competition. On the one hand, the cross and vertical cross two can enhance the global search capability and avoid the local optimal problem. On the other hand, the golden mean is generated by the two crossover operators and the dominant solution generated by the competition, which can quickly converge to the global optimum. A case study reveals that Crisscross optimization algorithm performs better in global optimization ability and stability compared with the standard particle swarm optimization algorithm, the genetic algorithm, the expectation-maximization algorithm, and it can be effectively applied to the optimal operation of cascade reservoirs.

Key words: crisscross optimization algorithm, operation optimization, cascaded reservoirs

CLC Number: 

  • TV697.1

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