Multi-objective optimal power flow based gray wolf optimization method

Abstract

Introduction. One of predominant problems in energy systems is the economic operation of electric energy generating systems. In this paper, one a new evolutionary optimization approach, based on the behavior of meta-heuristic called grey wolf optimization is applied to solve the single and multi-objective optimal power flow and emission index problems. Problem. The optimal power flow are non-linear and non-convex very constrained optimization problems. Goal is to minimize an objective function necessary for a best balance between the energy production and its consumption, which is presented as a nonlinear function, taking into account of the equality and inequality constraints. Methodology. The grey wolf optimization algorithm is a nature inspired comprehensive optimization method, used to determine the optimal values of the continuous and discrete control variables. Practical value. The effectiveness and robustness of the proposed method have been examined and tested on the standard IEEE 30-bus test system with multi-objective optimization problem. The results of proposed method have been compared and validated with hose known references published recently. Originality. The results are promising and show the effectiveness and robustness of proposed approach.

Keywords

• optimization
• power networks
• optimal power flow
• emission index
• grey wolf optimization