Stochastic security-constrained unit commitment with wind power generation based on dynamic line rating

Park, Hyeongon; Jin, Young Gyu; Park, Jong–Keun

doi:10.1016/j.ijepes.2018.04.026

Cited by 49 publications

(18 citation statements)

References 29 publications

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“…The Big-M technique is applied to avoid the product of continuous variables and binary variables, which helps formulate the model as MILP format and reduce the computational burden. When u g,t is equal to 0, constraints (21) and (24) guarantee that there is no power output in this generator; otherwise, the power output can be injected to busbar 1 or busbar 2 based on the value of y g,t , which is restricted in (19)- (20) and 22- (23).…”

Section: Network-constrained Unit Commitment Frameworkmentioning

confidence: 99%

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

Liu

Xie

et al. 2019

IEEE Access

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The integration of large-scale stochastic renewable energy, the aging of transmission facilities, and the growth of load demand all contribute to the increasing congestion levels of transmission systems. Such factors pose considerable stress on the economical and secure operation of power systems and the accommodation of large-scale renewable energies. However, under the smart grid circumstance, some cutting-edge transmission technologies can bring potential cost-effective solutions to leverage the potential capacity of existing transmission infrastructures. Such technologies can help the utilities to deal with the rapid change of operating conditions of the power system in a more flexible manner. For example, the network topology optimization (NTO) technology can change the transmission topology based on the operating conditions, which increases the flexibility of the transmission system. Dynamic thermal rating (DTR) can evaluate the maximum transmission capacity of transmission lines dynamically according to the weather condition parameters around the conductor. These two cost-effective technologies are promising in improving the congestion mitigation performance and can contribute to the efficient utilization of transmission network-so they will bring potential economic and reliability benefits. This paper incorporates NTO and DTR in the network-constrained unit commitment (NCUC) framework to study their synergistic effect on the power system day-ahead schedule. Case studies are performed on a modified RTS-79 system. The numerical results verify that the coordination of NTO and DTR may help decrease the generation cost and wind power curtailment. INDEX TERMS Day-ahead scheduling, network-constrained unit commitment, network topology optimization, dynamic thermal rating, wind power curtailment. NOMENCLATURE A. INDICES g No-load cost for generator g.

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Section: Network-constrained Unit Commitment Frameworkmentioning

confidence: 99%

“…DTR is incorporated in SCUC framework in [22] to enhance the system security and obtain technical/economic performances. In [23], stochastic optimization is further applied in the SCUC model in the presence of wind power integration. DTR is validated to reduce the wind power spillage.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Xie

et al. 2019

IEEE Access

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“…It is also shown that system security can still be preserved while enforcing DLR in a security constrained UC problem [40]. DLR is applied in a stochastic security constrained UC formulation to capture wind power uncertainty [41]. The author in [42] used pre-specified DLR values in conjunction with network reconfiguration to reduce the uncertainty linked with renewable generation.…”

Section: Introductionmentioning

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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“…In terms of power system dispatching, DLR forecasting research makes it possible to consider this technology in the issue of day-to-day dispatching, so as to obtain a more economical dispatching scheme when the power market is deregulated. In [28], in the presence of wind energy integration, stochastic optimization is further applied to the security constraint unit commitment (SCUC) model. DLR has been verified to reduce wind power spillage.…”

Section: Introductionmentioning

confidence: 99%

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

et al. 2020

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Flexible AC transmission system (FACTS) controller play an essential role in increasing the penetration level of renewable energy resources owing to their ability in continuously controlling the active and reactive power flow in the network. This paper presents a probabilistic multi-objective optimization approach to obtain the optimal sizes and locations of static var compensators (SVCs) and thyristor-controlled series capacitors (TCSCs) in a power transmission network with high penetration level of wind generation. The objective of the problem is to maximize the system loadability while minimizing the network power losses and the installation cost of the FACTS controllers. In this study, the uncertainties associated with wind power generation and the correlated load demand are considered. The uncertainties are handled in this work using the points estimation method. Moreover, the dynamic line ratings (DLRs) of the transmission lines are considered in this work. In this case, the maximum transmission capacity of transmission lines is estimated dynamically according to the weather conditions. Considering the DLRs or transmission lines is expected to avoid unrealistic congestion in the network, and hence, improve its loadability. The optimization problem is solved using the multi-objective teaching-learning based optimization (MO-TLBO) algorithm to find the best locations and ratings for the FACTS controllers. Additionally, a technique based on the fuzzy decisionmaking approach is employed to extract one of the Pareto optimal solutions as the best compromise. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results demonstrate the effectiveness of the proposed approach and show that the maximum loadability limit of the study system increases when considering the DLR. This limit can be enhanced to 123.0% without FACTS controller and 137.0 % ,130 % and 132.0% by SVC, TCSC and (SVC-TCSC) respectively.

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Stochastic security-constrained unit commitment with wind power generation based on dynamic line rating

Cited by 49 publications

References 29 publications

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

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

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

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

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