Open AccessTSO and DSO with large‐scale distributed energy resources: A security constrained unit commitment coordinated solution
Author(s) -
Nawaz Aamir,
Wang Hongtao,
Wu Qiuwei,
Kumar Ochani Manesh
Publication year - 2020
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12233
Subject(s) - particle swarm optimization , power system simulation , distributed generation , electric power system , differential evolution , computer science , mathematical optimization , hierarchy , transmission (telecommunications) , operator (biology) , optimization problem , computational complexity theory , transmission system , scale (ratio) , distributed computing , power (physics) , engineering , reliability engineering , renewable energy , algorithm , electrical engineering , mathematics , telecommunications , quantum mechanics , physics , repressor , chemistry , biochemistry , transcription factor , market economy , economics , gene
Summary Modern power system requires optimally coordinated operation between transmission and distribution systems due to large‐scale integration of distributed energy resources (DERs). Commonly, transmission system operator (TSO) solves its own cost optimization problem and evaluates required targets for each distribution system operator (DSO). Thus, TSO problem becomes more complex and highly scaled with increase in number of connected distribution systems, which requires more computational time and resources. Therefore, this paper proposed a method to reduce computational burden on TSO and solve coordinated security constrained unit commitment (C‐SCUC) problem by involving a coordinator in upper level hierarchy. Coordinator is required to solve system‐wide problem to adjust targets for transmission system (TS) and all distribution systems (DS). Besides, TSO and DSO only need to solve their own cost optimization problems. In this paper, we have proposed analytical target cascading (ATC) along with hybridized particle swarm optimization with differential evolution (PSO‐DE) for solving increased complexity of the coordinated problem. ATC provides coordination between transmission and distribution sections of power system while hybrid PSO‐DE provides better accuracy of optimization in ATC layers. For evaluation of efficacy of proposed method, this paper has taken IEEE 118‐bus system as TS and IEEE 33‐bus system as DS. Results has depicted that proposed method could help TSO in reducing computational resources and improving computational time.