4.7 Article

Wind-thermal power system dispatch using MLSAD model and GSOICLW algorithm

Journal

KNOWLEDGE-BASED SYSTEMS
Volume 116, Issue -, Pages 94-101

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2016.10.028

Keywords

Power system dispatch; Wind power; Profit; Downside risk; Optimization algorithm

Funding

  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources [LAPS16004]
  2. North China Electric Power University
  3. National Natural Science Foundation of China [51277080]
  4. Hubei Collaborative Innovation Center for High-efficient Utilization of Solar Energy, Hubei University of Technology [HB-SZD2014001]
  5. China Postdoctoral Science Foundation [2016M602296]
  6. Electric Power Research Institute of Yunnan Power Grid [057000KK52140018]
  7. Energy Innovation Programme Office (EIPO) through the National Research Foundation and Singapore Economic Development Board

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The decision support model of mean-lower semi-absolute deviation (MLSAD) and the optimization algorithm of group search optimizer with intraspecific competition and levy walk (GSOICLW) are presented to solve Wind-thermal power system dispatch. MLSAD model takes the profit and downside risk into account simultaneously brought by uncertain wind power. Using a risk tolerance parameter, the model can be converted to a single-optimization problem, which is solved by an improved optimization algorithm, GSOICLW. Afterwards, both the model and the algorithm are tested on a modified IEEE 30-bus power system. Simulation results demonstrate that the MLSAD model can well solve wind-thermal power system dispatch. The study also verifies GSOICLW obtains better convergent dispatching solutions, in comparison with other evolutionary algorithms, such as group search optimizer and particle swarm optimizer. (C) 2016 Elsevier B.V. All rights reserved.

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