This paper formulates the efficient and feasible participation of distributed energy resources (DERs) in complex electricity services as a centralized nonlinear optimization problem first. This problem is then re-stated using the novel energy/power transformed state space. It is shown that the DER dynamics in closed-loop can be made linear in this new state space. The decision making by the DERs then becomes a distributed model predictive control problem and it forms the basis for deriving physically implementable convex market bids. A multi-layered interactive optimization for clearing the distributed bids by higher layer decision makers, such as market aggregators, is posed and shown to lead to near-optimal system-level performance at the slower market clearing rates. A proof-of-concept example is illustrated involving close to one hundred heterogeneous controllable DERs with real consumption data of a distribution feeder in Texas, contributing to automatic generation control (AGC).