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Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units

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  • Hemmati, Reza
  • Saboori, Hedayat
  • Saboori, Saeid

Abstract

Renewable resources, especially wind power, are widely integrated into the power systems nowadays. Managing uncertainty of the large scale wind power is often known as one of the most challenging issues in the power system operation scheduling. Additionally, energy storage systems (ESSs) have been widely investigated in the power systems owing to their valuable applications, especially renewable energy smoothing and time shift. In this paper, a stochastic unit commitment (UC) model is proposed to assess the impact of the wind uncertainty impact on ESSs and thermal units schedule in UC problem. Wind uncertainty is modeled based on the two measures. First, the wind penetration level is changed with respect to the basic level. Second, the wind forecasting error is modeled through a normal probability distribution function with different variances. The ESSs are modeled based on several technical characteristics and optimally scheduled considering different levels of the wind penetration and forecasting accuracies. The proposed formulation is a stochastic mixed integer linear programming (SMILP) and solved using GAMS software. Simulation results demonstrate that the wind uncertainty have a considerable impact on operation cost and ESSs schedule while proposed optimum storage scheduling through the stochastic programming will reduce the daily operational cost considerably.

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  • Hemmati, Reza & Saboori, Hedayat & Saboori, Saeid, 2016. "Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units," Renewable Energy, Elsevier, vol. 95(C), pages 74-84.
    • Handle: RePEc:eee:renene:v:95:y:2016:i:c:p:74-84
    DOI: 10.1016/j.renene.2016.03.054
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    2. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Parastegari, Moein, 2019. "An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids," Renewable Energy, Elsevier, vol. 130(C), pages 1049-1066.
    3. Hemmati, Reza & Saboori, Hedayat & Jirdehi, Mehdi Ahmadi, 2016. "Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution," Renewable Energy, Elsevier, vol. 97(C), pages 636-645.
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    5. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    6. Jannik Schütz Roungkvist & Peter Enevoldsen, 2020. "Timescale classification in wind forecasting: A review of the state‐of‐the‐art," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 757-768, August.
    7. Mehrjerdi, Hasan, 2020. "Modeling and optimization of an island water-energy nexus powered by a hybrid solar-wind renewable system," Energy, Elsevier, vol. 197(C).
    8. Hemmati, Reza & Saboori, Hedayat & Saboori, Saeid, 2016. "Stochastic risk-averse coordinated scheduling of grid integrated energy storage units in transmission constrained wind-thermal systems within a conditional value-at-risk framework," Energy, Elsevier, vol. 113(C), pages 762-775.
    9. Kim, H.Y. & Kim, M.K., 2017. "Optimal generation rescheduling for meshed AC/HIS grids with multi-terminal voltage source converter high voltage direct current and battery energy storage system," Energy, Elsevier, vol. 119(C), pages 309-321.
    10. Hemmati, Reza & Saboori, Hedayat & Siano, Pierluigi, 2017. "Coordinated short-term scheduling and long-term expansion planning in microgrids incorporating renewable energy resources and energy storage systems," Energy, Elsevier, vol. 134(C), pages 699-708.
    11. Xu, Xiao & Hu, Weihao & Cao, Di & Huang, Qi & Liu, Zhou & Liu, Wen & Chen, Zhe & Blaabjerg, Frede, 2020. "Scheduling of wind-battery hybrid system in the electricity market using distributionally robust optimization," Renewable Energy, Elsevier, vol. 156(C), pages 47-56.
    12. Saboori, Hedayat & Hemmati, Reza, 2017. "Maximizing DISCO profit in active distribution networks by optimal planning of energy storage systems and distributed generators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 365-372.
    13. Abdul Rauf & Mahmoud Kassas & Muhammad Khalid, 2022. "Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-27, September.

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