The Unit Commitment Problem With AC Optimal Power Flow Constraints

Castillo, Anya; Laird, Carl D.; Silva-Monroy, Cesar A.; Watson, Jean‐Paul; O’Neill, Richard P.

doi:10.1109/tpwrs.2015.2511010

Cited by 83 publications

(43 citation statements)

References 29 publications

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“…see [44], can be incorporated within the proposed global solution algorithm for the UC-AC formulation. Relative to our local method for the unit commitment with AC transmission constraints [45], we observe that our global solution algorithm locate the same solution to 6-Bus, a slightly improved solution to RTS-79, and a significantly improved solution to IEEE-118mod.…”

Section: B Globally Optimal Unit Commitment Schedulesmentioning

confidence: 82%

Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints

Liu

Laird

Scott

et al. 2019

IEEE Trans. Power Syst.

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We propose a novel global solution algorithm for the network-constrained unit commitment problem incorporating a nonlinear alternating current model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage optimization-based bounds tightening, secondorder cone relaxations, and piecewise outer approximations to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.

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Section: B Globally Optimal Unit Commitment Schedulesmentioning

confidence: 82%

Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints

Liu

Laird

Scott

et al. 2019

IEEE Trans. Power Syst.

Self Cite

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“…Clearly, it isn't down to earth to assess the majority of the mixes. Besides, a large number of the mixes are prohibited because of lacking accessible limit i.e., they are said to be infeasible and there is commonly some example in beginning request of the units so it isn't important to assess all conceivable unit mixes [7]. Consequently, heuristic systems are utilized to create mixes of transitional or minimal units which are characterized by a pursuit go.…”

Section: B Dynamic Programming Methodsmentioning

confidence: 99%

A Novel way out to Unit Commitment Problem utilizing Evolutionary Particle Swarm Optimization

Chinda

2019

IJRTE

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This paper differentiates the shows of three Unit Commitment strategies, three of which are the essential arrangement techniques for taking care of the Unit Commitment Problem named Priority List and Dynamic Programming strategies. The third strategy is the Evolutionary Particle Swarm Optimization method which has been applied productively to a plentiful blend of streamlining issues. Various regions in control frameworks require understanding at least one nonlinear streamlining emergencies. In spite of the way that systematic techniques may experience moderate intermingling and the scourge of dimensionality, heuristics-based swarm knowledge can be a capable substitute. Evolutionary Particle Swarm Optimization (EPSO), some portion of the swarm insight family, is known to adequately take care of enormous scale nonlinear improvement issues. This paper introduces the exit plan for Unit Commitment Problem by methods for EPSO system. A calculation was created to achieve an exit plan to the Unit Commitment Problem utilizing EPSO procedure. The adequacy of the calculation is tried on three generating units and the cultivated results utilizing the three techniques are thought about for complete working expense.

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“…For the sake of brevity, this section only addresses the technical constraints to represent dynamic ramp rate limits. However, including these equations in a complete UC formulation is straightforward, i.e., only extra constraints should be added to include, for example, AC power flows [21], or the units' startup and shutdown power trajectories [22].…”

Section: Problem Formulationmentioning

confidence: 99%

Dynamic ramping model including intraperiod ramp-rate changes in unit commitment

Correa-Posada¹,

Morales-España

Dueñas

et al. 2017

2017 IEEE Power &Amp; Energy Society General Meeting

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The Unit Commitment Problem With AC Optimal Power Flow Constraints

Cited by 83 publications

References 29 publications

Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints

Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints

A Novel way out to Unit Commitment Problem utilizing Evolutionary Particle Swarm Optimization

Dynamic ramping model including intraperiod ramp-rate changes in unit commitment

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