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Indexed by:会议论文

Date of Publication:2017-01-01

Included Journals:CPCI-S

Page Number:798-808

Key Words:Stochastic dynamic programming; Distributed parallel computation; MPI; Multithread

Abstract:Stochastic dynamic programming (SDP) is widely adopted in a long-term optimal operation of large-scale hydropower systems. In this paper we propose a distributed parallel stochastic dynamic programming algorithm based on Message Passing Interface (MPI) and a peer-to-peer parallel paradigm (DPSDPoM). To deal with the disadvantages of redundancy in communications and memory-consumption during calculation in the peer-to-peer parallel paradigm, we propose a DPSDPoM with multithread algorithm (DPSDPoM-MT) which reduces costs between processes in each machine. The two algorithms are compared through the optimization scheduling of three reservoirs on Lancang Jiang Dam Cascade using time-elapse and memory consumption. Experimental results demonstrate that the improved algorithm can reduce computing time and alleviate memory consumption effectively.