Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

被引:1
作者
Dai, Xinliang [1 ]
Guo, Yi [2 ,4 ]
Jiang, Yuning [3 ]
Jones, Colin N. [3 ]
Hug, Gabriela [2 ]
Hagenmeyer, Veit
机构
[1] KIT, Inst Automat & Appl Informat, D-76344 Karlsruhe, Germany
[2] Swiss Fed Inst Technol, Power Syst Lab, Zurich, Switzerland
[3] Ecole Polytech Fed Lausanne, Automat Control Lab, Lausanne, Switzerland
[4] Empa, Urban Energy Syst Lab, Dubendorf, Switzerland
基金
瑞士国家科学基金会;
关键词
Data preservation; Distributed nonlinear model predictive control; Flexibility aggregation; Integrated transmission and distribution; systems; Multiperiod AC optimal power flow; POWER-FLOW; OPTIMIZATION;
D O I
10.1016/j.epsr.2024.110627
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a real -time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power -energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control ( & Oslash;c ) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power -energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework's effectiveness and applicability in real -world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.
引用
收藏
页数:8
相关论文
共 36 条
[1]   Large Scale Multi-Period Optimal Power Flow With Energy Storage Systems Using Differential Dynamic Programming [J].
Agarwal, Aayushya ;
Pileggi, Larry .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2022, 37 (03) :1750-1759
[2]  
Babaeinejadsarookolaee S, 2021, Arxiv, DOI arXiv:1908.02788
[3]   Distributed MPC for Efficient Coordination of Storage and Renewable Energy Sources Across Control Areas [J].
Baker, Kyri ;
Guo, Junyao ;
Hug, Gabriela ;
Li, Xin .
IEEE TRANSACTIONS ON SMART GRID, 2016, 7 (02) :992-1001
[4]   OPTIMAL SIZING OF CAPACITORS PLACED ON A RADIAL-DISTRIBUTION SYSTEM [J].
BARAN, ME ;
WU, FF .
IEEE TRANSACTIONS ON POWER DELIVERY, 1989, 4 (01) :735-743
[5]   NETWORK RECONFIGURATION IN DISTRIBUTION-SYSTEMS FOR LOSS REDUCTION AND LOAD BALANCING [J].
BARAN, ME ;
WU, FF .
IEEE TRANSACTIONS ON POWER DELIVERY, 1989, 4 (02) :1401-1407
[6]   A Shapley value-based Distributed AC OPF Approach for Redispatch Congestion Cost Allocation [J].
Bauer, Rebecca ;
Dai, Xinliang ;
Hagenmeyer, Veit .
PROCEEDINGS OF THE 2023 THE 14TH ACM INTERNATIONAL CONFERENCE ON FUTURE ENERGY SYSTEMS, E-ENERGY 2023, 2023, :109-113
[7]   Inner and outer approximations of polytopes using boxes [J].
Bemporad, A ;
Filippi, C ;
Torrisi, FD .
COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS, 2004, 27 (02) :151-178
[8]   Strong NP-hardness of AC power flows feasibility [J].
Bienstock, Daniel ;
Verma, Abhinav .
OPERATIONS RESEARCH LETTERS, 2019, 47 (06) :494-501
[9]  
Dai XL, 2024, Arxiv, DOI arXiv:2402.01001
[10]   Hypergraph-Based Fast Distributed AC Power Flow Optimization [J].
Dai, Xinliang ;
Lian, Yingzhao ;
Jiang, Yuning ;
Jones, Colin N. ;
Hagenmeyer, Veit .
2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, 2023, :4572-4579