Optimization Decision-Making Method for Distribution System Restoration Considering the Interdependency Between Power and Water Distribution Systems

doi:10.12204/j.issn.1000-7229.2021.03.007

Abstract

Abstract:

When an outage event occurs, coordinating local distributed generators to restore critical loads is an effective way to enhance the resilience of the power distribution system (PDS). PDS and water distribution system (WDS) are two kinds of lifeline infrastructures with interdependency in a city. If we establish the restoration strategy without enough consideration of the interdependency between the two systems, the lifeline infrastructures may not work properly. This paper analyzes the interdependency between PDS and WDS firstly. On this basis, authors formulate the distribution system restoration method considering the interdependency between PDS and WDS as a mixed-integer linear program (MILP) through several linear approximation methods. The objective function is maximizing the number of restored critical loads, and the operational characteristic of PDS, WDS, and the interdependent components are taken into account. The method is tested in an integrated power and water system. The result shows that the proposed method can restore more critical loads and make the allocation of limited generation resources optimally.

Key words: resilience, distribution system restoration, interdependency of power and water distribution systems, linear approximation

CLC Number:

TM712

LI Muyin, CAO Zhiyuan, LI Jiaxu, MA Jiajun, XU Yin, LIU Jiayu, ZHANG Qiqi. Optimization Decision-Making Method for Distribution System Restoration Considering the Interdependency Between Power and Water Distribution Systems[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(3): 54-60.

Figures/Tables 8

Fig.1 The interdependency between PDS and WDS

Fig.2 Piecewise linearization method

Fig.3 Algorithm flowchart

Fig.4 Topology of the PDS and WDS

Fig.5 Restoration result according to coupling model

Table 1 Restoration result of two methods

Fig.6 Comparison of objective function value between two models under different scenarios

Fig.7 Comparison of pump power consumption

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