Maintenance Scheduling of Transmission Systems Considering Coordinated Outages

Moslemi, Niki; Kazemi, Mostafa; Abedi, Seyed Mostafa; Khatibzadeh-Azad, Hadi; Jafarian, Mohammad

doi:10.1109/jsyst.2017.2664586

Cited by 13 publications

(4 citation statements)

References 20 publications

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“…In (11), F k,l,t refers to the power flow of line l in the scenario k at hour t while F Rate,l indicates the maximum active power which can be transferred by the line l.…”

Section: Problem Formulation Of Coordinated Optimization a Objementioning

confidence: 99%

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Risk-Based Coordination of Maintenance Scheduling and Unit Commitment in Power Systems

et al. 2020

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The line random failure caused by multiple uncertainties has become a non-negligible factor which influences the safe operation of power systems. In this paper, a risk-based coordination model of maintenance scheduling and unit commitment is established and the objective is to minimize the total operation cost consisting of the maintenance cost, generation cost and risk cost. A random generation method is proposed to obtain line failure scenarios based on arbitrary failure rate functions. In the base case, security constraints must be satisfied while the potential overflow caused by line outages is calculated in contingency scenarios. In order to handle this mixed integer quadratic programming, a solving strategy based on three-layer iterations is applied. In the exterior iterative layer, Lagrangian relaxation technology is used to coordinate the maintenance scheduling and the risk-based unit commitment until the maintenance schedule is available for the optimized unit commitment plan. In other two iterative layers, Benders decomposition method is adopted to the further problem decomposition. In the middle layer, iterations between the unit commitment sub-problem and the risk-based dispatch sub-problem are used to guarantee the optimality of risk-based unit commitment. In interior iterations, the feasibility of unit commitment plan is checked by an optimal load shedding model. Case studies are performed on a 6-bus test system and a 118-bus test system. Results show that the total operation cost decreases by coordination while the system operating risk can be effectively controlled.

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“…In (11), F k,l,t refers to the power flow of line l in the scenario k at hour t while F Rate,l indicates the maximum active power which can be transferred by the line l.…”

Section: Problem Formulation Of Coordinated Optimization a Objementioning

confidence: 99%

“…A relaxation induced algorithm has been proposed to efficiently search an acceptable near-optimal solution. Reference [11] has studied the method coordinating maintenance plans for all elements in a transmission bay. Results showed that the level of coordination increased with the decline of element failure probabilities.…”

Section: Introductionmentioning

confidence: 99%

Risk-Based Coordination of Maintenance Scheduling and Unit Commitment in Power Systems

et al. 2020

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“…Due to the uncertain nature of the power generation by renewable sources [1] and demand profiles within the MG, it poses a challenge on managing the operation of MGs. To overcome this challenge, the related advancement has been achieved on supporting MG owners to decide whether or not to use ESDs, optimizing the size of ESDs [3,4,5], and scheduling the charge and discharge times for these ESDs [6,17]. In general, ESDs could improve the reliability and power quality of a MG.…”

Section: ( )mentioning

confidence: 99%

“…By combining the computed operation cost in (15) - (17) with the steady state information in (18) to (23), the overall cost for PV system can be calculated by Equation (24):…”

Section: B Lower Layer (Asset Maintenance Model)mentioning

confidence: 99%

Joint Optimization of Operation and Maintenance Policies for Solar-Powered Microgrids

Mahani

Liang

Parlikad

et al. 2019

IEEE Trans. Sustain. Energy

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received the Ph.D. degree in reliability engineering and asset management from the University of Cambridge, U.K., in 2016. Currently, he is a research associate at the Distributed Information and Automation Laboratory at the University of Cambridge. His research interests include stochastic process, predictive maintenance, maintenance optimization and reliability of power equipment. Ajith Kumar Parlikad received the Ph.D. degree in manufacturing

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Multi-area transmission maintenance scheduling for two-level markets

Cai

Zhang

et al. 2023

Energy Reports

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Maintenance Scheduling of Transmission Systems Considering Coordinated Outages

Cited by 13 publications

References 20 publications

Risk-Based Coordination of Maintenance Scheduling and Unit Commitment in Power Systems

Risk-Based Coordination of Maintenance Scheduling and Unit Commitment in Power Systems

Joint Optimization of Operation and Maintenance Policies for Solar-Powered Microgrids

Multi-area transmission maintenance scheduling for two-level markets

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