Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 13, Issue 5, Pages 4072-4087Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2022.3145709
Keywords
Uncertainty; Schedules; Optimal scheduling; Load flow; Costs; Batteries; DC-DC power converters; Converter losses; convex optimization; energy storage; robust optimization; soft open~point
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Funding
- Northern Powergrid, U.K. as part of the Pragmatic Security Assessment NIA [NIA_NPG_029]
- Engineering and Physical Sciences Research Council (EPSRC) [EP/T021969/1]
- National Science Foundation of China (NSFC) [520616336103]
- Northern Powergrid, U.K. as part of the Enhanced Understanding of Network Losses Project
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Soft open points (SOPs) are power electronic devices that replace conventional open points in distribution networks, allowing control of active power flow and injection of reactive power. This paper presents a robust mixed-integer convex model for optimal scheduling of integrated energy storage (ES) and SOPs to ensure zero probability of constraint violation.
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.
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