Line Loss Interval Algorithm for Distribution Network with DG Based on Linear Optimization under Abnormal or Missing Measurement Data

Chen Liang, Chang Chen, Weizhou Wang, Xiping Ma, Yuying Li and Tong Jiang
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Chen Liang: Electric Power Research Institute of State Grid Gansu Electric Power Company, Lanzhou 730050, China
Chang Chen: State Key Laboratory of Alternative Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Weizhou Wang: Electric Power Research Institute of State Grid Gansu Electric Power Company, Lanzhou 730050, China
Xiping Ma: Electric Power Research Institute of State Grid Gansu Electric Power Company, Lanzhou 730050, China
Yuying Li: State Key Laboratory of Alternative Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Tong Jiang: State Key Laboratory of Alternative Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Energies, 2022, vol. 15, issue 11, 1-16

Abstract: Data collection is more difficult in distribution network than transmission networks since the structure of distribution networks is more complex. As a result, data could be partly abnormal or missing, which cannot completely describe the operation status of distribution network. In addition, access of distributed generation (DG) to distribution network further aggravates the variability of power flow in distribution network. The traditional deterministic line loss calculation method has some limitations in accurately estimating the line loss of distribution network with DG. A line loss interval calculation method based on power flow calculation and linear optimization is proposed, considering abnormal data collection and distribution network power flow variability. The linear optimization model is established according to sensitivity of line loss to the injected power and sensitivity of transmission power of first branch to the injected power. Introducing the scheduling information into the optimization model, a reliable line loss fluctuation interval can be obtained which actual line loss locates. The effectiveness of the proposed algorithm is verified in IEEE 33-bus distribution network system.

Keywords: abnormal data collection; power flow variability; line loss interval calculation; linear optimization model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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