TY - JOUR
T1 - Hierarchical predictive control scheme for distributed energy storage integrated with residential demand and photovoltaic generation
AU - Lampropoulos, I.
AU - Garoufalis, P.
AU - van den Bosch, P.P.J.
AU - Kling, W.L.
PY - 2015
Y1 - 2015
N2 - A hierarchical control scheme is defined for the energy management of a battery energy storage system which is integrated in a low-voltage distribution grid with residential customers and photovoltaic installations. The scope is the economic optimisation of the integrated system by employing predictive control techniques. The approach is based on hierarchical decomposition of the optimisation problem in the time domain by composing a three-level scheduling and control scheme, that is, day-ahead, intra-hour, and real-time, where the initial and final states of each sub-problem are chosen as coordination parameters. The day-ahead and the intra-hour problems address the interactions with electricity markets during the scheduling phase. The real-time algorithm is able to adapt the operation of the battery system according to updated information about market conditions, residential demand, and local generation, and subject to the network capacity and other technical constraints. The simulation scenarios address the interactions with the day-ahead auction and the imbalance settlement system in the Netherlands.
AB - A hierarchical control scheme is defined for the energy management of a battery energy storage system which is integrated in a low-voltage distribution grid with residential customers and photovoltaic installations. The scope is the economic optimisation of the integrated system by employing predictive control techniques. The approach is based on hierarchical decomposition of the optimisation problem in the time domain by composing a three-level scheduling and control scheme, that is, day-ahead, intra-hour, and real-time, where the initial and final states of each sub-problem are chosen as coordination parameters. The day-ahead and the intra-hour problems address the interactions with electricity markets during the scheduling phase. The real-time algorithm is able to adapt the operation of the battery system according to updated information about market conditions, residential demand, and local generation, and subject to the network capacity and other technical constraints. The simulation scenarios address the interactions with the day-ahead auction and the imbalance settlement system in the Netherlands.
KW - valorisation
U2 - 10.1049/iet-gtd.2014.0908
DO - 10.1049/iet-gtd.2014.0908
M3 - Article
SN - 1751-8687
VL - 9
SP - 2319
EP - 2327
JO - IET Generation, Transmission & Distribution
JF - IET Generation, Transmission & Distribution
IS - 15
ER -