A Multi-objective Transmission Expansion Model Considering Renewable Energy Resources for Alternating Current Power Systems

A new Transmission Network Expansion Planning (TEP) problem based on alternating current (AC) network aiming at optimizing system operation is proposed in this paper. TEP based on AC model (AC-TEP) can provide more accurate planning results compared to that based on direct current model (DC-TEP). In this paper, a multi-objective AC-TEP issue is analyzed dealing with investment problem and uncertainty problem. A multi-objective evolutionary algorithm (MOEA) based on an enhanced inverted generational distance indicator (AR-MOEA), is used to handle the multi-objective TEP. In this paper, IEEE-24 bus test system and China 52-bus system are utilized to perform the numerical analysis. To prove the superiority of AR-MOEA algorithm, the obtained results are compared with that of MOEA based on decomposition (MOEA/D). The results confirm the superior performance of AR-MOEA for solving multi-objective TEP problem, and validate the applicability and capability of AC-TEP model to cope with middle and larger power systems.