Robust flexibility needs assessment with bid matching framework for distribution network operators

• Published in: Sustainable Energy, Grids and Networks Vol. 34; p. 101069
• Main Authors: Hashmi, Md Umar, Koirala, Arpan, Ergun, Hakan, Van Hertem, Dirk
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2023
• Subjects: Bid matching; Chance constraint; Distribution system operator (DSO); Flexibility; Optimal power flow (OPF); Risk-based planning; Scenario generation; Zonal clustering; Distribution system operator (DSO); Optimal power flow (OPF); Zonal clustering; Risk-based planning; Bid matching; Scenario generation; Flexibility; Chance constraint
• ISSN: 2352-4677; 2352-4677
• DOI: 10.1016/j.segan.2023.101069

For market-based procurement of low-voltage flexibility, DSOs identify the amount of flexibility needed for resolving probable distribution network (DN) voltage and thermal congestion. A framework is required to avoid over or under-procurement of flexibility in the presence of uncertainty. To this end, we propose a scenario-based robust chance-constrained (CC) day-ahead flexibility needs assessment (FNA) framework. The CC level is analogous to the risk DSO is willing to take in flexibility planning. Multi-period optimal power flow is performed to calculate the amount of flexibility needed to avoid network issues. Future uncertainties are considered as multiple scenarios, which are utilized to solve the flexibility needs assessment optimal power flow (FNA-OPF) problem. The FNA tool calculates the temporal and locational ramp-up and ramp-down flexibility needs of the DN. We also propose a Pareto optimal mechanism for selecting CC level to reduce flexibility needs while reducing DN congestion. Zonal clustering of a DN feeder is performed using electrical distance as a measure, with spatial partitioning and silhouette coefficient. Further, a zonal and nodal bid matching algorithm is proposed, where alternate flexibility bids in the same zone are identified in case nodal matching is not exact, compared to the calculated FNA. The proposed bid matching algorithm assists the system operator in bid selection by avoiding rerunning power flow evaluations. The zonal and nodal bid matching leads to more than 43% additional reduction of probable network incidents compared to naive nodal bid matching. Furthermore, we also calculate FNA for a real German DN with 646 nodes and 331 consumers.