Short-term hydro-scheduling using Hopfield neural network

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Short-term hydro-scheduling using Hopfield neural network

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An approach based on the Hopfield neural network is proposed for short-term hydro-scheduling. The purpose of short-term hydro-scheduling is to determine the optimal amounts of generated powers for the hydro-units in the system for the next N (N = 24 in this work) hours in the future. The proposed approach is basically a two-stage solution method. In the first stage, a Hopfield neural network is developed to reach a preliminary generation schedule for the hydro-units. Since some practical constraints may be violated in the preliminary schedule, a heuristic rule based search algorithm is developed in the second stage to reach a feasible suboptimal schedule which satisfies all practical constraints. The proposed approach is applied to hydroelectric generation scheduling of the Taiwan power system. It is concluded from the results that the proposed approach is very effective in reaching proper hydro-generation schedules.

Inspec keywords: scheduling; hydroelectric power stations; optimisation; power system analysis computing; power system planning; Hopfield neural nets

Other keywords: feasible suboptimal schedule; heuristic rule based search algorithm; two-stage solution method; short-term hydro-scheduling; power system; Taiwan; hydroelectric power generation; Hopfield neural network

Subjects: Optimisation; Power system planning and layout; Hydroelectric power stations and plants; Optimisation techniques; Power engineering computing; Neural computing techniques

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