The placement of Virtual Network Functions (VNF) in distributed data centers is an important problem to solve for the next generation cloud based telecom architectures. This is because where to place the VNFs and how to route the traffic in the physical network impacts the energy consumption of the cloud infrastructure, the resiliency of the service chains and the SLA with the tenants. For network operators, it is important to minimize the operational costs of their infrastructure, provide robustness of the placement and routing in order to cope with potential hardware failures and imprecise resource demand specifications. In this paper, we develop a new optimization model for the green multi-period VNF placement and traffic routing problem, where different service chain configurations exist over time. The model is formulated as a Mixed Integer Linear Program (MILP), considers latency due to network propagation and VNF processing and provides different protection methods for the NFV traffic routing to cope with link failures. By applying Soyster's robustness principle, the model yields a network configuration that can cope with load that deviates from the expected demand. Because the MILP is complex to solve, we develop a fast variable fixing heuristic. In our numerical evaluation, we use the virtualized Evolved Packet Core and study the energy cost of different robustness levels and protection schemes for VNF service flow routing.