A new three-stage method for solving unit commitment problem

Khanmohammadi, Sohrab; Amiri, Mohsen; Haque, M. Tarafdar

doi:10.1016/j.energy.2010.03.049

Cited by 52 publications

(13 citation statements)

References 32 publications

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“…The algorithm proposed in this paper is applied to respectively simulate the monthly UC with 10, 20, 40, 60, 80, and 100 units connected to the same transmission section. The units parameters of the 10-unit system are detailed in [21] when the total load of each period is shown in Figure 5. Both the capacities of positive and negative spinning reserves are 10% of the predicted total load.…”

Section: Simulationmentioning

confidence: 99%

Monthly Unit Commitment Model and Algorithm with Renewable Energy Generation Considering System Reliability

Zhu

Liu

Zhai

et al. 2019

Mathematical Problems in Engineering

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With the sustained growth in renewable energy penetration, it is important to incorporate the interval prediction information of the wind and photovoltaic power into the monthly unit commitment model and introduce the system reliable rate as an indicator to measure the system reliability, which make an important contribution to deal with the volatility and randomness of the wind and photovoltaic power and ensure the economy and reliability of the monthly unit commitment. To enhance the practicality of the model and improve the solving ability, the multiobjective function composed by operating cost and reliable rate is transformed into a single-objective function by using the evaluation function based on geometric weighting method. An adaptive genetic algorithm (AGA) is used to solve the above problem when the prohibiting inbreeding strategy is adopted to replace the mutation operator, avoiding the hybridization between close relatives and containing the diversity of the population. Finally, the testing systems verify the validity and accuracy of the proposed model and algorithm.

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Section: Simulationmentioning

confidence: 99%

Monthly Unit Commitment Model and Algorithm with Renewable Energy Generation Considering System Reliability

Zhu

Liu

Zhai

et al. 2019

Mathematical Problems in Engineering

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show abstract

“…The number of particles and the maximum iterations are 20 and 200 respectively. The traditional BPSO [53], GA [53], an adaptive PSO (APSO) [73], a binary programming (BP) [73], a two-stage based genetic algorithm (TSGB) [74], an improved IPSO [75], a three stage method B.SMP and A. SMP [76], and a hybrid harmony search (HHS) [77] are all compared in Table 6. Again, it is confirmed from Table 6 that…”

Section: Parameter Settings Of Some Bpso Variantsmentioning

confidence: 99%

A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem

Yang

Niu

et al. 2017

Knowledge-Based Systems

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“…PROBLEM FORMULATION There are two sub sections where the modeling of thermal generation [14], [16] and solar generation [5] have been carried out.…”

Section: Introductionmentioning

confidence: 99%

A PSO Based Solution Methodology for Short Term Hybrid Generation Scheduling Problem

Tiwari¹,

Dwivedi²,

M.P³

2017

IJET

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A new three-stage method for solving unit commitment problem

Cited by 52 publications

References 32 publications

Monthly Unit Commitment Model and Algorithm with Renewable Energy Generation Considering System Reliability

Monthly Unit Commitment Model and Algorithm with Renewable Energy Generation Considering System Reliability

A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem

A PSO Based Solution Methodology for Short Term Hybrid Generation Scheduling Problem

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