Optimal Generator Start-Up Strategy for Bulk Power System Restoration

Sun, Wei; Liu, Chen‐Ching; Zhang, Li

doi:10.1109/tpwrs.2010.2089646

Cited by 229 publications

(170 citation statements)

References 20 publications

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“…In such cases, it is impossible to produce network partitions such that the generation-load difference of each partition is a positive value. Even though the proposed network partitioning strategy tries to find a cut-set that maximizes the minimum generation-load difference of all possible partitions e (11,12) , e (12,14) , e (15,17) , e (17,18) , e (22,23) , e (23,24) , e (30,38) } rather than producing some partitions with positive generationload differences and the rest with large negative generationload differences, certain partitions can still result in negative generation-load differences. In such cases, transmission system operators can either decide to repartition with a reduced α(v i ) value or not to restore non-critical loads in the partitions with negative generation-load difference as they can be restored after the synchronization of the partitions.…”

Section: Discussionmentioning

confidence: 99%

“…This work utilizes the method proposed in [18] as it groups generators in such a way to accelerate the cranking task. In [18], the generator start-up sequencing is formulated as a mixed integer linear programming problem based on a 4-step transformation by introducing new decision variables. This linear formulation has led to an optimal solution to the generator start-up sequencing problem.…”

Section: A Initializationmentioning

confidence: 99%

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Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Ganganath

Wang

Xu³

et al. 2018

IEEE Trans. Ind. Inf.

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Abstract-After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of partitioning process. The second step ensures the satisfaction of modelled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39-and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

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Section: Discussionmentioning

confidence: 99%

Section: A Initializationmentioning

confidence: 99%

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Ganganath

Wang

Xu³

et al. 2018

IEEE Trans. Ind. Inf.

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“…A higher value of represents a higher degree of importance of the particular load. Table I lists the load importance generally is used for load restoration studies [26]. The term is the capacity of ith load.…”

Section: Objective Functionmentioning

confidence: 99%

Load restoration methodology considering renewable energies and combined heat and power systems

Alwan¹,

Farhan²

2018

IJET

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Outages and faults cause problems in interconnected power system with huge economic consequences in modern societies. In the power system blackouts, black start resources such as micro combined heat and power (CHP) systems and renewable energies, due to their selfstart ability, are one of the solutions to restore power system as quickly as possible. In this paper, we propose a model for power system restoration considering CHP systems and renewable energy sources as being available in blackout states. We define a control variable representing a level of balance between the distance and importance of loads according to the importance and urgency of the affected customer. Dynamic power flow is considered in order to find feasible sequence and combination of loads for load restoration.

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“…Ref. [40] formulates the starting sequence of generators as a mixed integer linear programming problem, using the transformation technique on the nonlinear generation capability curves. However, it is not suitable for large-scale power systems due to the computational limitations of this method.…”

Section: Unit Start-up Sequence Optimizationmentioning

confidence: 99%

Power system restoration: a literature review from 2006 to 2016

Liu

Fan

Terzija

2016

J. Mod. Power Syst. Clean Energy

237

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Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network reconfiguration and load restoration. Some emerging methods and key techniques are also discussed in the context of the integration of variable renewable energy and development of the smart grid. There is a long way to go to achieve automatic self-healing in bulk power systems because of its extreme complexity. However, rapidly developing artificial intelligence technology will eventually enable the step-by-step dynamic decision-making based on the situation awareness of supervisory control and data acquisition systems (SCADA) and wide area measurement systems (WAMS) in the near future.

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Optimal Generator Start-Up Strategy for Bulk Power System Restoration

Cited by 229 publications

References 20 publications

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Load restoration methodology considering renewable energies and combined heat and power systems

Power system restoration: a literature review from 2006 to 2016

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