An ADMM-based Coordination and Control Strategy for PV and Storage to Dispatch Stochastic Prosumers: Theory and Experimental Validation
For power system operators and prosumers, this provides a validated distributed coordination method for PV and storage, though the contribution is incremental as it combines existing MPC and ADMM techniques.
The paper proposes a two-layer control framework combining real-time MPC (10s) and ADMM-based coordination (5min) to dispatch stochastic prosumption (PV+battery) according to a day-ahead energy trajectory. Experimental validation on a real building (101 kW load, 350 kW peak, 82 kW PV, 560 kWh battery) demonstrates feasibility, but no quantitative performance numbers (e.g., tracking error, cost savings) are reported.
This paper describes a two-layer control and coordination framework for distributed energy resources. The lower layer is a real-time model predictive control (MPC) executed at 10 s resolution to achieve fine tuning of a given energy set-point. The upper layer is a slower MPC coordination mechanism based on distributed optimization, and solved with the alternating direction method of multipliers (ADMM) at 5 minutes resolution. It is needed to coordinate the power flow among the controllable resources such that enough power is available in real-time to achieve a pre-established energy trajectory in the long term. Although the formulation is generic, it is developed for the case of a battery system and a curtailable PV facility to dispatch stochastic prosumption according to a trajectory at 5 minutes resolution established the day before the operation. The proposed method is experimentally validated in a real-life setup to dispatch the operation of a building with rooftop PV generation (i.e., 101 kW average load, 350 kW peak demand, 82 kW peak PV generation) by controlling a 560 kWh/720 kVA battery and a 13 kW peak curtailable PV facility.