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System modeling and optimization for islanded micro-grid using multi-cross learning-based chaotic differential evolution algorithm

Hemmati, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ijepes.2013.11.015
  3. Abstract:
  4. This paper presents a comprehensive operation model for micro-grids (MG) operating in the islanded mode. Various energy sources of a MG including diesel engine generator, micro-turbine, wind turbine and photovoltaic cell as well as battery storage and AC/DC rectifier/inverter are modeled in the proposed framework. Fuel costs, emission costs, and operation and maintenance (O&M) costs of these sources as well as their operating limits and characteristics are considered in the model. Furthermore, a new multi-cross learning-based chaotic differential evolution (MLCDE) algorithm is presented to solve the optimization problem of MG operation. The numerical results obtained from the proposed solution approach for three MG test cases with real-world data are compared with the results of several other recently published optimization methods. These comparisons confirm the validity of the developed approach
  5. Keywords:
  6. Differential evolution ; Micro-grid ; Optimal operation ; Renewable energy ; Stochastic search ; Chaotic search ; Micro grid ; Renewable energies ; Costs ; Diesel engines ; Digital storage ; Evolutionary algorithms ; Optimization ; Photovoltaic cells ; Electric power distribution
  7. Source: International Journal of Electrical Power and Energy Systems ; Vol. 56 , 2014 , pp. 349-360 ; ISSN: 01420615
  8. URL: http://www.sciencedirect.com/science/article/pii/S0142061513004730