Transmission expansion planning based on Pareto dominance considering load variation and wind power

This paper explores the impact of uncertainties related to load and renewable sources on the multi-objective transmission expansion planning (TEP) problem, considering the composite reliability and wind curtailment criteria. Many optimization methods have been used to solve the TEP problem with uncertainties, however, the reliability cost is incorporated into a single-objective function in addition to the investment cost. An improved multi-objective framework based on Pareto dominance is proposed to allow solving the TEP problem with simultaneous uncertainties and suitable computational effort. The investment cost is handled as one of the objective functions besides the expected curtailed wind energy and expected energy not supplied. In addition, the impact of composite failures in transmission lines and conventional generation is also represented. A multi-objective grey wolf algorithm is used to handle Pareto solutions based on Non-dominated Monte Carlo Simulation. A trade-off strategy between the investment cost, curtailed wind energy, and security criteria is established by using a fuzzy satisfying approach. The proposed methodology is assessed in a modified IEEE 24-bus test system and a practical Brazilian network. Simulation cases indicate the effectiveness of the proposed approach in finding multiple solutions under different planning criteria and uncertainties, which can provide comprehensive and realistic options to the system planner.