  The large penetration of renewable resources has resulted in rapidly changing
net loads, resulting in the characteristic "duck curve". The resulting ramping
requirements of bulk system resources is an operational challenge. To address
this, we propose a distributed optimization framework within which distributed
resources located in the distribution grid are coordinated to provide support
to the bulk system. We model the power flow of the multi-phase unbalanced
distribution grid using a Current Injection (CI) approach, which leverages
McCormick Envelope based convex relaxation to render a linear model. We then
solve this CI-OPF with an accelerated Proximal Atomic Coordination (PAC) which
employs Nesterov type acceleration, termed NST-PAC. We evaluate our distributed
approach against a local approach, on a case study of San Francisco,
California, using a modified IEEE-34 node network and under a high penetration
of solar PV, flexible loads, and battery units. Our distributed approach
reduced the ramping requirements of bulk system generators by up to 23%.
