TY - JOUR AU - Mezhoud, N. AU - Ayachi, B. AU - Amarouayache, M. PY - 2022/07/08 Y2 - 2024/03/28 TI - Multi-objective optimal power flow based gray wolf optimization method JF - Electrical Engineering & Electromechanics JA - Electrical Engineering & Electromechanics VL - IS - 4 SE - Power Stations, Grids and Systems DO - 10.20998/2074-272X.2022.4.08 UR - http://eie.khpi.edu.ua/article/view/254929 SP - 57-62 AB - <p><strong><em>Introduction.</em></strong> <em>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. <strong>Problem.</strong></em><em> The </em><em>optimal power flow </em><em>are non-linear and non-convex very constrained optimization problems.</em> <strong><em>Goal</em></strong> <em>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. </em><strong><em>Methodology. </em></strong><em>The </em><em>grey wolf optimization </em><em>algorithm is a </em><em>nature inspired </em><em>comprehensive optimization method, used to determine the optimal values of the continuous and discrete control variables. </em><strong><em>Practical value.</em></strong> <em>The effectiveness and robustness of the proposed</em> <em>method have been examined and tested on the standard IEEE 30-bus test system with multi-objective optimization problem.</em> <em>T</em><em>he <strong>results</strong> of proposed method have been compared and validated with hose known references published recently. <strong>Originality.</strong></em> <em>The results are promising and show the effectiveness and robustness of proposed approach.</em></p> ER -