Integrated Day-Ahead Scheduling Considering Active Management in Future Smart Distribution System

Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optim...

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Bibliographic Details
Published in:IEEE transactions on power systems Vol. 33; no. 6; pp. 6049 - 6061
Main Authors: Gao, Hongjun, Wang, Lingfeng, Liu, Junyong, Wei, Zhenbo
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Active control
active management
Capacitor banks
column-and-constraint generation algorithm (CCG)
Communications systems
Constraint modelling
Electronic devices
Energy management
integrated scheduling
Load flow
Load modeling
Mixed integer
mixed integer second-order cone programming (MISOCP)
Optimization
Power flow
relaxed power flow model (RPFM)
Robustness
Robustness (mathematics)
Scheduling
Smart distribution system
Stability
Stochastic processes
stochastic robust model
System effectiveness
Uncertainty
Wind power
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optimally control the active management elements to increase the economic and technical performance of future smart distribution systems. This paper focuses on an integrated day-ahead scheduling scheme that is formulated as a mixed integer second-order cone programming problem to obtain the optimal solution by means of the relaxed power flow model (RPFM). The detailed technical constraints for all the elements are accommodated based on the RPFM-based optimization method. Meanwhile, active management cost and punishment cost of wind power curtailed and customer energy not supplied are also considered in the design objectives of this paper. In order to address the uncertainties, a stochastic robust optimization method is first introduced to decide the active management elements (including capacitor bank, electrical storage system, controllable load, and switch) as the robust decision scheme. Afterwards, the column-and-constraint generation algorithm is applied to solve the proposed stochastic robust two-stage optimization model. Numerical results based on the IEEE 33-bus, PG&E 69-bus, and practical 152-bus systems are obtained to verify the effectiveness of the proposed method.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2018.2844830