Security constrained AC dynamic transmission expansion planning considering reactive power requirements

Abstract

The Transmission Network Expansion Planning problem (TNEP) can be modeled either as a static, a pseudo-dynamic, or a dynamic problem. Most of the existing formulations do not include reactive power planning within the TNEP problem, leading to sub-optimal designs leading to higher system costs in reality. This paper proposes a dynamic (multi-stage) non-convex formulation that optimizes the addition of transmission circuits and reactive power compensation devices, accounting for operational costs including losses. The planning is done considering security constraints using an AC model. As there are no similar research works to benchmark the outcomes, the results were compared with those obtained from the static and pseudo-dynamic approaches, showing that the proposed approach provides more economical solutions. It is also shown that better solutions are obtained when Reactive Power Planning (RPP) is considered in the problem formulation. An improved Differential Evolution (DE) and Continuous Population Based Incremental Learning (PBILc) hybrid solution method (IDE-PBILc) is proposed which drastically improves calculation time and robustness. Comparisons with two different state-of-the-art metaheuristics are performed for validation. The results were obtained for the Garver 6-bus, IEEE 24-bus, and the IEEE 118-bus systems. Even though in this work uncertainties are not considered, the proposed approach could be of particular use when studying systems with high renewable energy penetration scenarios, due to its computational efficiency.