Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Self-adaptive learning based particle swarm optimization
Information Sciences: an International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper suggests a new stochastic framework based on 2 m+1 point estimate method PEM to solve the mid-term generation scheduling SMGS problem. The new formulation makes use of an adaptive modified bat algorithm and a novel self-adaptive wavelet mutation strategy for the establishment of new robust algorithm for the present problem. In addition, this work improves the modeling process of wind-thermal system in the MGS problem by considering the possible uncertainties when scheduling the generators of power system of the problem. The proposed model can concurrently capture the uncertainty effect of load and wind speed variations. The feasibility and efficiency of the proposed method is examined using two test systems.