Abstract

Parallel restoration is a way to accelerate the black-start procedure of power systems following a blackout. An efficient sectionalizing scheme can reduce the restoration time of a system, taking into account the black-start ability, generation-load balance of subsystems, restoration time of branches, start-up time of generating units, and effects of dispatchable loads and faulted devices. Solving the sectionalizing problem is challenging since it needs to handle a large number of Boolean variables corresponding to the branches and nonlinear constraints associated with system topology. This paper investigates power system sectionalizing problem for parallel restoration to minimize the system restoration time (SRT). A novel sectionalizing method considering the restoration of generating units and network branches is proposed. Firstly, the minimum spanning tree (MST) algorithm is used to determine the skeleton network of a power system. Secondly, the number of subsystems is determined according to the number of black-start units. Based on the skeleton network, candidate boundary lines among subsystems are identified. Then, constraints are evaluated to identify feasible sectionalizing schemes. Except commonly used constraints on power balancing and black-start units, this paper also considers using dispatchable loads to meet the minimum output requirements of generating units. Finally, the sectionalizing scheme with the minimum SRT is selected as the final solution. The effectiveness of the proposed method is validated by the IEEE 39-bus and 118-bus test systems. The simulation results indicate that the proposed method can balance the restoration time of subsystems and minimize the SRT.

Highlights

  • Several major blackouts occurred worldwide in the past few decades, e.g., the 14 August 2003 blackout in the northern USA and Canada [1], the 4 November 2006 blackout in Western Europe [2], the30–31 July 2012 blackout in India [3] and the 31 March 2015 blackout in Turkey [4]

  • Compared with the matrix 0 = [0, 0, 0], the second element of Vb is larger than 0. It means that the dispatchable loads are not enough to balance the units’ minimum output during the start-up of generating units in subsystem 2

  • We have proposed a novel sectionalizing method for power system parallel restoration based on graph theory, considering the start-up time of generating units and the restoration time of branches

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Summary

Introduction

Several major blackouts occurred worldwide in the past few decades, e.g., the 14 August 2003 blackout in the northern USA and Canada [1], the 4 November 2006 blackout in Western Europe [2], the. During the start-up process, a generator cannot be controlled effectively since its control system is designed for use between minimum and maximum load [12] In this stage, dispatchable loads can be picked up to balance the output of restored units for system security. Since the MST is a spanning tree with the minimum total weight of edges in a graph, it can determine the skeleton network, which is a minimum adequate network connecting all available buses [30], with the minimum restoration time of the power system. The start-up time of generating units and the restoration time of branches are considered in the problem formulation, which help minimize the SRT.

Objective
Constraint on the Number of Subsystems
Minimum Output Constraint on Generating Units
Capacity Constraint on Generating Units
Constraint on Faulted Devices
The Proposed Method for Sectionalizing
Procedure of the Proposed Sectionalizing Method
Abstraction
Alocates generating unit locates at busbus
Suppose
Candidate
Constraint
Constraint Evaluation
Optimal Sectionalizing Schemes
Case Studies
IEEE 39-Bus Test System
Construct the Skeleton Network Based on MST
Generate Candidate Schemes
Evaluate Constraints
Determine the Optimal Sectionalizing Scheme
IEEE is the39-bus slowest
The reason is that it takes
Methods
IEEE 118-Bus Test System
Scenario
Scenario 2
The sectionalizing result ingraph
About the Objective Function
Remarks on Computational Time
Hybrid Renewable Energy System for Restoration
Findings
Conclusions
Full Text
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