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Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk
This paper presents the mean-variance (MV) model to solve power system reactive power dispatch problems with wind power integrated. The MV model considers the profit and risk simultaneously under the uncertain wind power (speed) environment. To describe this uncertain environment, the Latin hypercube sampling with Cholesky decomposition simulation method is used to sample uncertain wind speeds. An improved optimization algorithm, group search optimizer with intraspecific competition and lévy walk, is then used to optimize the MV model by introducing the risk tolerance parameter. The simulation is conducted based on the IEEE 30-bus power system, and the results demonstrate the effectiveness and validity of the proposed model and the optimization algorithm.
Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk
This paper presents the mean-variance (MV) model to solve power system reactive power dispatch problems with wind power integrated. The MV model considers the profit and risk simultaneously under the uncertain wind power (speed) environment. To describe this uncertain environment, the Latin hypercube sampling with Cholesky decomposition simulation method is used to sample uncertain wind speeds. An improved optimization algorithm, group search optimizer with intraspecific competition and lévy walk, is then used to optimize the MV model by introducing the risk tolerance parameter. The simulation is conducted based on the IEEE 30-bus power system, and the results demonstrate the effectiveness and validity of the proposed model and the optimization algorithm.
Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk
Yuanzheng Li (author) / Mengshi Li (author) / Qinghua Wu (author)
2014
Article (Journal)
Electronic Resource
Unknown
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