Day-Ahead Scheduling of Power System Incorporating Network Topology Optimization and Dynamic Thermal Rating

Liu, Yanlin; Hu, Bo; Xie, Kaigui; Wang, Lingfeng; Xiang, Yingmeng; Xiao, Ruosong; Kong, Dezhuang

doi:10.1109/access.2019.2904877

Cited by 44 publications

(19 citation statements)

References 40 publications

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“…The coordination of OTS and DLR with other technologies is recently studied only by few authors. In [46] OTS and DLR along with bussplitting mechanism is incorporated in a day-ahead scheduling process for improved integration of renewable generation resources. The authors in [47] presented a network-constrained direct current optimal power flow problem by jointly enforcing OTS and DLR.…”

Section: B Related Workmentioning

confidence: 99%

Exploiting the Inherent Flexibility in Transmission Network for Optimal Scheduling, Wind Power Utilization, and Network Congestion Management

et al. 2021

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Owing to the economic, social, and political problems in the expansion of transmission infrastructure, novel transmission topologies are in demand to efficiently utilize the existing infrastructure. On the other hand, there is a tremendous increase in wind power generation around the globe. One of the main challenges hindering the penetration of large-scale wind power generation is the network congestion due to limited network capacity. To address these two issues, this study develops a co-optimized optimal transmission switching (OTS) and dynamic line rating (DLR) model to optimize system resources by mitigating network congestion and maximizing wind power accommodation. This new concept of exploiting the inherent flexibility in transmission network is named as flexible transmission dynamic line rating (FTDLR), which deploys OTS in coordination with DLR as a control tool to utilize existing assets. A twostage stochastic unit commitment framework is used to deploy the proposed FTDLR model, which is used to dynamically increase the line capacity based on the meteorological parameters and at the same time optimally select candidate lines to be switched off from the network. A comprehensive analysis is performed to characterize the FTDLR performance on system operation cost, network congestion, and wind power curtailment. The proposed FTDLR model is further tested as a part of contingency analysis where both generator failure and transmission line outages are considered. Test results performed on the IEEE 24-bus network demonstrate that by using FTDLR, the service operator could substantially reduce system dispatch cost, improve wind power accommodation, and relieve network congestion. The scalability and feasibility of the FTDLR optimization problem is validated on the larger network of the IEEE 118-bus system.

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Section: B Related Workmentioning

confidence: 99%

Exploiting the Inherent Flexibility in Transmission Network for Optimal Scheduling, Wind Power Utilization, and Network Congestion Management

et al. 2021

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“…Due to its significant impacts on various aspects of network, graph topology has drawn the attention of engineering communities including power system community during the last two decades. The role of network topology is investigated for a few power system problems such as synchronization [45], flexibility of transmission lines for day-ahead scheduling [46], and the patterns of attacks to power networks [47]. Recently, graph symmetry, described by automorphism groups, has been leveraged in literature to address important network behaviors such as its controllability [63], robustness [60], and synchronization [48].…”

Section: A State Of the Artmentioning

confidence: 99%

Cyber-Security Constrained Placement of FACTS Devices in Power Networks From a Novel Topological Perspective

et al. 2020

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Optimal placement of flexible AC transmission systems (FACTS) devices and the cybersecurity of associated data exchange are crucial for the controllability of wide area power networks. The placement of FACTS devices is studied in this paper from a novel graph theoretic perspective, which unlike the existing approaches, purely relies on topological characteristics of the underlying physical graphs of power networks. To this end, the maximum matching principle (MMP) is used to find the set of required FACTS devices for the grid controllability. In addition, the cyber-security of the most critical data related to the FACTS controllers is guaranteed by introducing the concept of moderated-k-security where k is a measure of data obscurity from the adversary perspective. The idea of moderated-k-symmetry is proposed to facilitate the arrangement of the published cyber graph based on a permutation of nodes within the symmetry group of the grid, called generator of automorphism. It is then verified that the published cybergraph can significantly obscure the data exchange over the cyber graph for adversaries. Finally, a similarity is observed and demonstrated between the set of critical nodes attained from the symmetry analysis and the solution of the FACTS devices placement that further highlights the importance of symmetry for the analysis and design of complex power networks. Detailed simulations are applied to three power networks and analyzed to demonstrate the performance and eligibility of the proposed methods and results.

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“…In this segment, all the network variables are calculated, not just the previously selected ones. For example, in power flow calculation, equations (18) and (19) are changed to (27) and (28), respectively.…”

Section: Post-optimization Calculations In Segmentmentioning

confidence: 99%

Tractable Stochastic Unit Commitment for Large Systems During Predictable Hazards

Mohammadi

2020

IEEE Access

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Many foreseeable natural hazards, including extreme weather events, lead to an outage of multiple transmission lines. Although such outages can be predicted in advance, there is a great deal of uncertainty in these predictions. To appropriately use the failure estimations in power system scheduling, this paper formulates a stochastic unit commitment (SUC) problem with explicit modeling of the predicted outages. The formulated problem, however, is extremely computationally-demanding, as the uncertainty is placed on the binary status of transmission lines. This paper, then, develops a computationally efficient algorithm to solve the formulated SUC for large-scale systems. The algorithm employs generation shift factors to enable rapid calculation of power flows. Additionally, flow canceling transactions are used to model multiple line outages without having to recalculate shift factors. Finally, critical constraints are iteratively detected and added to the problem. This approach substantially reduces the size of the problem, which helps computational tractability. The effectiveness of the developed algorithm is demonstrated through simulation studies on the Texas 2000-bus test system. The algorithm is used to minimize the lost load during a hypothetical hurricane. The results show that the algorithm is computationally tractable and can effectively identify a preventive dispatch, leading to a substantial reduction in power outages.

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Day-Ahead Scheduling of Power System Incorporating Network Topology Optimization and Dynamic Thermal Rating

Cited by 44 publications

References 40 publications

Exploiting the Inherent Flexibility in Transmission Network for Optimal Scheduling, Wind Power Utilization, and Network Congestion Management

Exploiting the Inherent Flexibility in Transmission Network for Optimal Scheduling, Wind Power Utilization, and Network Congestion Management

Cyber-Security Constrained Placement of FACTS Devices in Power Networks From a Novel Topological Perspective

Tractable Stochastic Unit Commitment for Large Systems During Predictable Hazards

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