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

• An effective operation model is proposed for islanded micro-grids (MGs).
• A new optimization algorithm is presented to solve MG optimization problem.
• A new binary handling procedure is proposed for MG unit commitment problem.
• The proposed approach is extensively compared with 21 recent optimitation methods.
• The comparisons confirm the validity of the developed approach.

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.