TY - JOUR
T1 - Multi-timescale Coordinated Distributed Energy Resource Control Combining Local and Online Feedback Optimization
AU - Zhan, Sen
AU - Morren, Johan
AU - van den Akker, W.F.
AU - van der Molen, Anne
AU - Paterakis, N.G.
AU - Slootweg, J.G. (Han)
PY - 2024/9
Y1 - 2024/9
N2 - Recently, online feedback optimization (OFO) emerges as a promising approach for real-time distribution grid management. OFO offers several advantages, including not requiring precise grid models or real-time load metering and demonstrating robustness against inaccurate problem data. However, one important limitation is that OFO does not consider the intertemporal relationships and short-term planning capabilities of assets, thus not harnessing the full potential of a variety of distributed energy resources (DER) such as batteries and electric vehicles. To address this limitation, this paper proposes a multi-timescale coordinated control framework. In the slower timescale, local optimization problems are solved to provide real-time OFO controllers with reference setpoints. The overall approach thereby maintains minimal model, computation, and communication requirements while enforcing grid limits. Case studies based on a 96-bus unbalanced low-voltage grid with a high DER penetration level and second-scale data demonstrate its effectiveness and solution quality benchmarked with a centralized optimal power flow approach.
AB - Recently, online feedback optimization (OFO) emerges as a promising approach for real-time distribution grid management. OFO offers several advantages, including not requiring precise grid models or real-time load metering and demonstrating robustness against inaccurate problem data. However, one important limitation is that OFO does not consider the intertemporal relationships and short-term planning capabilities of assets, thus not harnessing the full potential of a variety of distributed energy resources (DER) such as batteries and electric vehicles. To address this limitation, this paper proposes a multi-timescale coordinated control framework. In the slower timescale, local optimization problems are solved to provide real-time OFO controllers with reference setpoints. The overall approach thereby maintains minimal model, computation, and communication requirements while enforcing grid limits. Case studies based on a 96-bus unbalanced low-voltage grid with a high DER penetration level and second-scale data demonstrate its effectiveness and solution quality benchmarked with a centralized optimal power flow approach.
KW - Distribution grid management
KW - Local optimization
KW - Multiple timescales
KW - Online feedback optimization
KW - Primal–dual gradient projection
UR - http://www.scopus.com/inward/record.url?scp=85196973886&partnerID=8YFLogxK
U2 - 10.1016/j.epsr.2024.110836
DO - 10.1016/j.epsr.2024.110836
M3 - Article
SN - 0378-7796
VL - 234
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 110836
ER -