TY - JOUR
T1 - A Robust Mixed-Integer Convex Model for Optimal Scheduling of Integrated Energy Storage - Soft Open Point Devices
AU - Sarantakos, Ilias
AU - Peker, Meltem
AU - Zografou-Barredo, Natalia Maria
AU - Deakin, Matthew
AU - Patsios, Charalampos
AU - Sayfutdinov, Timur
AU - Taylor, Phil C.
AU - Greenwood, David
N1 - Funding Information:
This work was supported in part by Northern Powergrid, U.K. as part of the Pragmatic Security Assessment NIA under Project NIA-NPG-029, and as part of the Enhanced Understanding of Network Losses Project; in part by the Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/T021969/1; and in part by the National Science Foundation of China (NSFC) under Grant 520616336103, under NSFC-EPSRC Collaborative Research Initiative in Sustainable Power Supply, as part of the Multi-energy Control of Cyber- Physical Urban Energy Systems (MC2) Project. Paper no. TSG-00690-2021.
Publisher Copyright:
IEEE
PY - 2022
Y1 - 2022
N2 - Soft open points (SOPs) are power electronic devices which can replace conventional normally open points in distribution networks. SOPs enable full control of active power flow between the interconnected feeders and can inject reactive power at each node to which they are connected. SOPs integrated with energy storage (ES) have been recently proposed to realize both spatial and temporal flexibility in active distribution networks. The flexibility provided by integrated ES-SOP devices will allow network operators to run their networks closer to their limits, but only if there is appropriate management of the uncertainty arising from demand and renewable generation. The only existing model of an ES-SOP uses nonconvex nonlinear equations, neglects uncertainty, and represents converter losses in an oversimplistic manner. This paper presents a robust mixed-integer convex model for the optimal scheduling of integrated ES-SOPs to ensure a zero probability of constraint violation. Losses of the subsystems comprising the ES-SOP are modeled using a proposed binary-polynomial model, enabling efficient scheduling of the energization state of subsystems to reduce no-load losses. The ES-SOP is considered in this paper to be owned by the network operator to: 1) manage power flow constraints, 2) minimize cost of losses, and 3) maximize arbitrage profit.
AB - Soft open points (SOPs) are power electronic devices which can replace conventional normally open points in distribution networks. SOPs enable full control of active power flow between the interconnected feeders and can inject reactive power at each node to which they are connected. SOPs integrated with energy storage (ES) have been recently proposed to realize both spatial and temporal flexibility in active distribution networks. The flexibility provided by integrated ES-SOP devices will allow network operators to run their networks closer to their limits, but only if there is appropriate management of the uncertainty arising from demand and renewable generation. The only existing model of an ES-SOP uses nonconvex nonlinear equations, neglects uncertainty, and represents converter losses in an oversimplistic manner. This paper presents a robust mixed-integer convex model for the optimal scheduling of integrated ES-SOPs to ensure a zero probability of constraint violation. Losses of the subsystems comprising the ES-SOP are modeled using a proposed binary-polynomial model, enabling efficient scheduling of the energization state of subsystems to reduce no-load losses. The ES-SOP is considered in this paper to be owned by the network operator to: 1) manage power flow constraints, 2) minimize cost of losses, and 3) maximize arbitrage profit.
KW - Converter losses
KW - convex optimization
KW - energy storage
KW - robust optimization
KW - soft open-point
UR - http://www.scopus.com/inward/record.url?scp=85123795373&partnerID=8YFLogxK
U2 - 10.1109/TSG.2022.3145709
DO - 10.1109/TSG.2022.3145709
M3 - Article
AN - SCOPUS:85123795373
SN - 1949-3053
VL - 13
SP - 4072
EP - 4087
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 5
ER -