Optimal investment plan for dynamic thermal rating using benders decomposition

Jabarnejad, Masood; Valenzuela, Jorge

doi:10.1016/j.ejor.2015.08.010

Cited by 22 publications

(13 citation statements)

References 14 publications

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“…The reliability of the joint operation of OTS and DLR is assessed in [48], where the authors showed that instead of degrading system reliability, the combined OTS and DLR topology can improve system reliability. Investment planning and transmission expansion problem using reconfigurable networks and DLR are studied in [49][39] [50]. C. RESEARCH GAP However, the current literature about the DLR enforcement with OTS in scheduling of power system network is based on deterministic modeling.…”

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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“…Constraints (1l)-(1m) and constraints (1n)-(1p) enforce the power flow and the capacity of each line in every hour of each representative day, respectively, where m l is a sufficiently large positive number (i.e., |m l | ≥ 2 • θ max [15]). The dynamic thermal capacity of any line equipped with DTR system is typically higher than its static thermal capacity [16] and thus the auxiliary variable ∆p lto and the constraints (1n)-(1p) are used to model this property. If any switchable line is closed (i.e., x lto = 1), constraint (1l)-(1m) and constraints (1n)-(1p) lead to p lto = y l • θ s(l)to − θ r(l)to and |p lto | ≤ p max l + ∆p lto , respectively; otherwise, constraints (1l)-(1m) are neutralized and constraints (1n)-(1p) lead to |p lto | = 0.…”

Section: The Proposed Dgandtp Modelmentioning

confidence: 99%

“…Given 365 vectors of historical observations pertaining to 365 daily 24-hour patterns of demands, wind power productions, (1-5),(2-6), (7)(8), , (11)(12)(13) (11-13), (15)(16), (16)(17), (26)(27)(28),(35-37),(36-37), (36-47),(39-48),(40-41), (56-58),(60-61)…”

Section: A the Clustering Algorithmmentioning

confidence: 99%

A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies

Dehghan

Amjady

Aristidou

2020

IEEE Systems Journal

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“…where U is a pre-determined uncertainty set, and definitions of the rest terms are the same with (7). O R denotes the value of (8), which is the sum of the first-stage decision costs and the worst-case second-stage decision costs.…”

Section: Distributionally Robust Opfmentioning

confidence: 99%

Risk-Based Distributionally Robust Optimal Power Flow With Dynamic Line Rating

Wang

Gao

Qiu

et al. 2018

IEEE Trans. Power Syst.

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In this paper, we propose a risk-based data-driven approach to optimal power flow (DROPF) with dynamic line rating. The risk terms, including penalties for load shedding, wind generation curtailment and line overload, are embedded into the objective function. To hedge against the uncertainties on wind generation data and line rating data, we consider a distributionally robust approach. The ambiguity set is based on second-order moment and Wasserstein distance, which captures the correlations between wind generation outputs and line ratings, and is robust to data perturbation. We show that the proposed DROPF model can be reformulated as a conic program. Considering the relatively large number of constraints involved, an approximation of the proposed DROPF model is suggested, which significantly reduces the computational costs. A Wasserstein distance constrained DROPF and its tractable reformulation are also provided for practical large-scale test systems. Simulation results on the 5-bus, the IEEE 118-bus and the Polish 2736-bus test systems validate the effectiveness of the proposed models.

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Optimal investment plan for dynamic thermal rating using benders decomposition

Cited by 22 publications

References 14 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

A Robust Coordinated Expansion Planning Model For Wind Farm-Integrated Power Systems With Flexibility Sources Using Affine Policies

Risk-Based Distributionally Robust Optimal Power Flow With Dynamic Line Rating

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