Short-term generating unit maintenance scheduling in a deregulated power system using a probabilistic approach

Billinton, R.; Abdulwhab, A.

doi:10.1049/ip-gtd:20030401

Cited by 37 publications

(20 citation statements)

References 9 publications

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“…The problem of how to coordinate unit maintenance outages among different generation producers should be considered to ensure the system reliability and social benefit [31,32]. In addition, this paper mainly analyses the UMS problem based on a poolbased energy market, how to extend the proposed approach to a hybrid market with bilateral contracts, energy and ancillary services market and how to coordinate maintenance scheduling of generating units, and transmission lines remain for future research.…”

Section: Discussionmentioning

confidence: 99%

Optimal maintenance scheduling of power producers considering unexpected unit failure

Feng

Wang

2009

IET Gener. Transm. Distrib.

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A novel unit maintenance scheduling (UMS) problem formulation for a generation producer is presented, to maximise its benefit while thoroughly considering the risk associated with unexpected unit failures. First, the unit failure is characterised by a more practical bathtub-shaped failure behaviour from the modified superposed power law process. Its parameters are estimated from the historical data by solving a nonlinear least-squaresfitting problem via Gauss -Newton iteration method. On the basis of the unit failure analysis, the new UMS formulation is solved by a combination of linear programming and genetic algorithms (GAs), and its impact on the producer's benefit is analysed in detail, including expected profit of selling energy, expected renewal cost of damaged components and maintenance cost. Compared with the current models, the proposed UMS model takes into consideration the influences of market factors as well as unexpected unit failures to strike the right balance between profits and costs related with potential unit failures. Numerical examples on a four-unit producer are utilised to demonstrate the effectiveness of the proposed scheme. NomenclatureThe main mathematical symbols used in this paper are classified as follows:maintenance cost at period t E Profit (t) expected energy-selling profit at period t E Renewal (t) expected renewal cost at period t h( j, t, x j ) failure rate of unit j at period t p m (t) probability of unit operating state m at period t P m ( j, t) generation of unit j in unit operating state m at period t

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Section: Discussionmentioning

confidence: 99%

Optimal maintenance scheduling of power producers considering unexpected unit failure

Feng

Wang

2009

IET Gener. Transm. Distrib.

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“…In the risk leveling method that was first introduced in [3] and [4], generating units are sorted according to their capacities; in addition, the applicable maintenance times associated with each unit are sorted according to the reliability index. Then the largest unit is selected to go on outage in the most reliable time interval.…”

Section: Risk Leveling Methodsmentioning

confidence: 99%

Reliability-based maintenance scheduling of generating units in restructured power systems

Fotuhi‐Firuzabad¹,

Aminifar²,

Shahzadeh³

2014

Turk J Elec Eng & Comp Sci

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Maintenance scheduling of generating units in restructured power systems is a collaborative and interactive process between independent system operators (ISOs) and generating companies (GENCOs). The ISO should comply with GENCO maintenance preferences subject to targeted system reliability levels. This process might be multistage since the admission of all initial unit outage requests may threaten system reliability. Hence, the ISO accepts some proposals and determines alternatives for the remaining units. The GENCOs are then allowed to confirm the alternatives or revise them. In this paper the ISO problem of generating unit maintenance scheduling is tackled. The objective function is to minimize the deviation of awarded schedule from the requested schedule, as measured in MW weeks. A novel and effective optimization technique is developed to solve the problem at hand. In the proposed methodology, risk leveling and dynamic programming optimization algorithms are concurrently utilized to lessen the computation burden and enhance the solution process. The effectiveness of the proposed method and its applicability to real-life systems are verified by examining the generation section of the IEEE reliability test system (IEEE-RTS). The performance of the new method is also compared with that of the individual risk leveling approach.

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“…After combining corresponding coefficients for each variable and transferring the constant term to the right-hand side of (28), a simple form for Benders cuts is given as follows: (29) where is interpreted as the increment/decrement of the objective (22) with respect to transmission maintenance . Similarly, is interpreted as the marginal increment/decrement of the objective (22) with respect to generation at base case.…”

Section: Hourly Network Security Check Subproblemmentioning

confidence: 99%

“…In [29], authors considered the outage coordination of generators and transmission lines. The proposed model was based on traditional load flow and deterministic operating criteria.…”

Section: Introductionmentioning

confidence: 99%

Coordination of Midterm Outage Scheduling With Short-Term Security-Constrained Unit Commitment

Yong

Shahidehpour

et al. 2009

IEEE Trans. Power Syst.

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The proposed model solves the coordinated generation and transmission maintenance scheduling with security-constrained unit commitment (SCUC) over the scheduling horizon of weeks to months. The model applies the Lagrangian relaxation technique to decompose the optimization problem into subproblems for generation maintenance scheduling, transmission maintenance scheduling, and short-term SCUC. The decomposition and cooperation strategy is applied to the first two subproblems for the scheduling of generation and transmission maintenance. The SCUC solution is based on the mixed integer programming (MIP) technique. The optimal hourly results for maintenance scheduling, generation unit commitment, and transmission flows are obtained using a chronological load curve. Effective strategies are applied for accelerating the convergence of the hourly solution. The numerical examples demonstrate the effectiveness of the proposed model. Index Terms-Generation and transmission maintenance scheduling, Lagrangian relaxation, mixed integer programming, security-constrained unit commitment.

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Short-term generating unit maintenance scheduling in a deregulated power system using a probabilistic approach

Cited by 37 publications

References 9 publications

Optimal maintenance scheduling of power producers considering unexpected unit failure

Optimal maintenance scheduling of power producers considering unexpected unit failure

Reliability-based maintenance scheduling of generating units in restructured power systems

Coordination of Midterm Outage Scheduling With Short-Term Security-Constrained Unit Commitment

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