Modified Brain Storm Optimization for Load Adjustment Distribution State Estimation Using Correntropy

This paper proposes modified storm brain optimization (MBSO) for load adjustment distribution state estimation (DSE) using correntropy. Minimization of sum of square errors by a weighted least squares (WLS) method has a problem when outliers exit in measured values. This problem can be solved by correntropy. Practical equipment in distribution systems causes nonlinear characteristics in an objective function and evolutionary computation methods such as Particle Swarm Optimization (PSO), hybrid PSO (HPSO) and differential evolutionary PSO (DEEPSO) have been applied to DSE so far. However, there is still room for improvement on estimation accuracy. The proposed method is applied to a typical distribution model system. The results indicate that the proposed method can improve estimation accuracy than the conventional DEEPSO and original BSO based method.

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