Virtualized RAN (vRAN) matches O-RAN Alliance specifications while transitioning towards virtualized functions on general-purpose computing platforms. However, the energy consumption of these systems remains a major concern. Although this issue has been addressed in the literature, previous works oversimplify routing decisions, overlook the benefits of flexible split choices, or neglect the energy consumption of the transport network. Additionally, most studies employing optimal solutions exhibit very limited scalability due to their high computational time. In this work, we present a comprehensive and efficient Mixed Integer Linear Programming model to minimize the energy consumption of O-RAN systems, addressing the limitations of current approaches. We also design and implement a synthetic data generator to evaluate our model across various network usage profiles, topologies, and reasonable-size networks. We achieved valuable insights and promising results in our evaluation. For example, our results show that when devices require high throughput, the transport network incurs significant energy costs and reduces the centralization rate. We also observed that hierarchical RAN topologies can achieve greater energy efficiency than ring topologies, with our approach enabling up to 15% more centralization while saving around 28% of energy and consuming at least one order of magnitude less time than other strategies.