This work proposes a modular concept to build
optimal power flow (OPF) models for distribution networks
containing various emerging technologies under diverse ownership
structures, to efficiently deal with evolving technology
capabilities and information sharing or privacy constraints. This
concept will support any typical OPF application (e.g., optimal
dispatch of a given asset without violating grid constraints)
by coordinating between grid module and technology module
without the need to recreate various modeling elements as
technology capability changes due to innovation. Moreover, the
modularity of the proposed concept enables achieving system
level objectives without sharing detailed information on module
level objectives and constraints among modules. To achieve this,
the proposed work develops a gradient-descent algorithm which
builds upon the literature on the state-of-the-art power flow
approximation. The proposed concept is demonstrated with two
case studies of i) controllable loads and ii) battery energy storage
system (BESS) on an actual large-scale distribution grid.
Revised: January 19, 2021 |
Published: August 6, 2020
Citation
Hanif S., M.E. Alam, and B.A. Bhatti. 2020.A Modular Optimal Power Flow Method for Integrating New Technologies in Distribution Grids. In IEEE Power & Energy Society General Meeting (PESGM 2020), August 2-6, 2020, Montreal, Canada, 1-5. Piscataway, New Jersey:IEEE.PNNL-SA-149018.doi:10.1109/PESGM41954.2020.9281907