Solving Energy Transportation Cost Using Mixed Integer Non-Linear Programming

Analysis of the energy transportation cost has a wide range of scope nowadays. Satisfying the demand for minimum cost is a great challenge for the power system. The planning and modeling of the production system should put forward the objectives of greenhouse gas emission reduction and promote the deployment of renewable energy. These objectives are designed to achieve significant energy savings in the future. In this work, a mixed integer non-linear programming is used to minimize the energy transportation cost using commercial software GAMS. The obtained results show the effectiveness of the proposed method.

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