Distribution Network Scheduling Model Taking Into Account Power Generation Prediction of New Energy and Flexible Loads
DOI:
https://doi.org/10.13052/dgaej2156-3306.4028Keywords:
Distributed energy, particle swarm optimization algorithm, mechanical well, flexible load, distribution network, wind powerAbstract
The distribution network’s stable operation is vital for consumers. The short-term high load of wind power grid connection and irrigation well groups pose an overload risk for the distribution network (DN). Therefore, a DN scheduling model based on improved particle swarm optimization (PSO) algorithm is proposed in this paper. This model predicts wind power generation and calculates the load of the well groups using a Monte Carlo algorithm. An improved PSO algorithm, based on Pareto optimality, is used to search for multi-objective optimal solutions in DN scheduling. This model controls the operation status of the wells achieving an intelligent DN scheduling. When the number of wells were 300 and 500, the total load of the DN model after power scheduling was reduced by 23.5% and 28.5%, respectively, when compared to unregulated scheduling. This intelligent DN scheduling model is crucial for improving the power system’s scheduling efficiency and reliability.
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