Online Optimization for Networked Distributed Energy Resources with
Time-Coupling Constraints
Abstract
This paper proposes a Lyapunov optimization-based online
distributed (LOOD) algorithmic framework for active distribution
networks with numerous photovoltaic inverters and invert air
conditionings (IACs). In the proposed scheme, ADNs can track an active
power setpoint reference at the substation in response to
transmission-level requests while concurrently minimizing the utility
loss and ensuring the security of voltages. In contrast to conventional
distributed optimization methods that employ the setpoints for
controllable devices only when the algorithm converges, the proposed
LOOD can carry out the setpoints immediately relying on the current
measurements and operation conditions. Notably, the time-coupling
constraints of IACs are decoupled for online implementation with
Lyapunov optimization technique. An incentive scheme is tailored to
coordinate the customer-owned assets in lieu of the direct control from
network operators. Optimality and convergency are characterized
analytically. Finally, we corroborate the proposed method on a modified
version of 33-node test feeder.