Short-Term Hydroscheduling with Discrepant Objectives Using Multi-Step Progressive Optimality Algorithm

Authors

  • Chuntian Cheng,

    1. Respectively Professor (Cheng), Ph.D. Student (Shen), Ph.D. Lecturer (Wu), Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian 116024 China
    Search for more papers by this author
  • Jianjian Shen,

    1. Respectively Professor (Cheng), Ph.D. Student (Shen), Ph.D. Lecturer (Wu), Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian 116024 China
    Search for more papers by this author
  • Xinyu Wu,

    1. Respectively Professor (Cheng), Ph.D. Student (Shen), Ph.D. Lecturer (Wu), Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian 116024 China
    Search for more papers by this author
  • Kwok-wing Chau

    1. (Chau) Department of Civil & Structural Engineering, Hong Kong Polytechnic University, Hong Kong, China
    Search for more papers by this author

  • Paper No. JAWRA-11-0040-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.

(E-Mail/Cheng: ctcheng@dlut.edu.cn).

Abstract

Cheng, Chuntian, Jianjian Shen, Xinyu Wu, and Kwok-wing Chau, 2012. Short-Term Hydroscheduling with Discrepant Objectives Using Multi-step Progressive Optimality Algorithm. Journal of the American Water Resources Association (JAWRA) 48(3): 464-479. DOI: 10.1111/j.1752-1688.2011.00628.x

Abstract:  With increase in the number and total capacity of hydropower plants in power systems, optimality algorithms with a single objective are not suitable for optimizing the operation of complex hydropower systems to meet complex demands. Hydropower plants should prioritize discrepant objectives, such as peak regulation and maximizing generation during solving of optimal operation problems of hydropower systems. In this article, we present a multi-step progressive optimality algorithm (MSPOA) for the short-term hydroscheduling (STHS) problem to improve the quality of optimal solutions and enhance the convergence speed of progressive optimality algorithm (POA). In MSPOA, the original problem is first decomposed into a sequence of problems with the longer time steps. Next, the problem with the longest time step is solved, and the optimal solution is used as the initial solution for the problem with the second longest time step. This process proceeds until the original problem with the shortest time step is solved. The proposed discrepant-objective method and solution technique are tested for two types of hydroelectric systems. The results show that MSPOA can give better solutions and cost less time than POA due to enlarging feasible range of decision variables and reducing the number of computational stages. Discrepant objectives among hydropower plants can express the operation characteristics of complex hydropower systems more accurately than unique objective or multiple objectives.

Ancillary