SFLA approach to solve PBUC problem with emission limitation

Venkatesan, T.; Sanavullah, M. Y.

doi:10.1016/j.ijepes.2012.09.006

Cited by 40 publications

(38 citation statements)

References 24 publications

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“…Eq. (9) shows that the sum of the generation and the spinning reserve lies within the range of the minimum and the maximum generation capacities, and is zero when the unit stops. Eqs.…”

Section: Unit Ramp Rate Constraints [23]mentioning

confidence: 97%

“…This part has six systems to test the MIQP and MILP algorithms of the Self-Scheduling (SS) problem, including the 10-generator unit 24-hour system, 20-generator unit 24-hour system, 40-generator unit 24-hour system, 60-generator unit 24-hour system, 80-generator unit 24-hour system, and 100-generator unit 24-hour system. In addition, the MILP algorithm is compared with the shuffled frog leaping algorithm (SFLA) by Venkatesan and Sanavullah [9]. (2) The second part examines the effects of the introduction of the carbon tax on the emissions, profit and output of the GENCO in two cases by simulating a 10-generation unit 24-hour system.…”

Section: Simulation Analysesmentioning

confidence: 99%

“…In order to perform a simulation on the same conditions in Venkatesan and Sanavullah [9], the system total reserve was assumed to be 10% of the system total load, namely S t R ¼ 10%P t D . The linear parameters were L ¼ 6 and N Di ¼ 10.…”

Section: Simulation Analysesmentioning

confidence: 99%

“…To check the robustness of this method, Table 3 compares the results between the MILP algorithm and the SFLA algorithm presented by Venkatesan and Sanavullah [9]. For comparison purposes, the price in Venkatesan and Sanavullah [9] is employed, in unit of Rs/MWh.…”

Section: Self-scheduling Of Genco Without Considering a Carbon Taxmentioning

confidence: 99%

“…By introducing weighting factors, other studies report [8] weighted GENCO's profits, Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/caor generation costs, and emissions in order to establish a selfscheduling model. Last but not least [9], a multi-objective GENCO self-scheduling has been proposed by simultaneously applying the generating profit and pollution emissions as objective functions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Self-scheduling of a power generating company: Carbon tax considerations

Liu

Chevallier

Zhu

2016

Computers & Operations Research

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“…Eq. (9) shows that the sum of the generation and the spinning reserve lies within the range of the minimum and the maximum generation capacities, and is zero when the unit stops. Eqs.…”

Section: Unit Ramp Rate Constraints [23]mentioning

confidence: 97%

Section: Simulation Analysesmentioning

confidence: 99%

Section: Simulation Analysesmentioning

confidence: 99%

Section: Self-scheduling Of Genco Without Considering a Carbon Taxmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Self-scheduling of a power generating company: Carbon tax considerations

Liu

Chevallier

Zhu

2016

Computers & Operations Research

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Modified hybrid forecast model considering chaotic residual errors for dam deformation

Wei

Yuan

et al. 2018

Struct Control Health Monit

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Summary Dam deformation is double effected by the internal and external environments, showing high nonlinear characteristics. Information mining of dam prototype observation data and effective components contained in the residual sequence is limited in conventional dam deformation forecast models. In order to fully explore the complex nonlinear relationship between dam deformation and environmental factors, modified hybrid forecast model considering chaotic residual errors is proposed on the combination of shuffled frog leapfrog algorithm and chaos theory in this study. Hybrid models are established on the basis of dam deformation prototype observation data, and modified hybrid forecast model is established by determining the optimal weight of each hybrid model with shuffled frog leapfrog algorithm. Considering the chaotic characteristics contained in the residual sequence of modified hybrid forecast model, residual sequence is analyzed and forecasted by chaos theory. By superimposing the residual forecast value with the forecast value of modified hybrid forecast model, modified hybrid forecast model considering chaotic residual errors is established. Example shows that, compared with conventional models, the proposed model is better in fitting precision and convergence speed, and forecast capability is significantly improved by considering the effective components contained in the residual sequence, which presents a new method of the deformation forecast for other hydraulic structures.

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