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A Progressive Period Optimal Power Flow for Systems with High Penetration of Variable Renewable Energy Sources

Author

Listed:
  • Zongjie Wang

    (Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA)

  • C. Lindsay Anderson

    (Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA)

Abstract

Renewable energy sources including wind farms and solar sites, have been rapidly integrated within power systems for economic and environmental reasons. Unfortunately, many renewable energy sources suffer from variability and uncertainty, which may jeopardize security and stability of the power system. To face this challenge, it is necessary to develop new methods to manage increasing supply-side uncertainty within operational strategies. In modern power system operations, the optimal power flow (OPF) is essential to all stages of the system operational horizon; underlying both day-ahead scheduling and real-time dispatch decisions. The dispatch levels determined are then implemented for the duration of the dispatch interval, with the expectation that frequency response and balancing reserves are sufficient to manage intra-interval deviations. To achieve more accurate generation schedules and better reliability with increasing renewable resources, the OPF must be solved faster and with better accuracy within continuous time intervals, in both day-ahead scheduling and real-time dispatch. To this end, we formulate a multi-period dispatch framework, that is, progressive period optimal power flow (PPOPF), which builds on an interval optimal power flow (IOPF), which leverages median and endpoints on the interval to develop coherent coordinations between day-ahead and real-time period optimal power flow (POPF). Simulation case studies on a practical PEGASE 13,659-bus transmission system in Europe have demonstrated implementation of the proposed PPOPF within multi-stage power system operations, resulting in zero dispatch error and violation compared with traditional OPF.

Suggested Citation

  • Zongjie Wang & C. Lindsay Anderson, 2021. "A Progressive Period Optimal Power Flow for Systems with High Penetration of Variable Renewable Energy Sources," Energies, MDPI, vol. 14(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2815-:d:554370
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    References listed on IDEAS

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    1. Simone Sperati & Stefano Alessandrini & Pierre Pinson & George Kariniotakis, 2015. "The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation," Energies, MDPI, vol. 8(9), pages 1-26, September.
    2. Phi-Hai Trinh & Il-Yop Chung, 2021. "Optimal Control Strategy for Distributed Energy Resources in a DC Microgrid for Energy Cost Reduction and Voltage Regulation," Energies, MDPI, vol. 14(4), pages 1-19, February.
    3. Lukas Held & Felicitas Mueller & Sina Steinle & Mohammed Barakat & Michael R. Suriyah & Thomas Leibfried, 2021. "An Optimal Power Flow Algorithm for the Simulation of Energy Storage Systems in Unbalanced Three-Phase Distribution Grids," Energies, MDPI, vol. 14(6), pages 1-34, March.
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    Cited by:

    1. Diego Larrahondo & Ricardo Moreno & Harold R. Chamorro & Francisco Gonzalez-Longatt, 2021. "Comparative Performance of Multi-Period ACOPF and Multi-Period DCOPF under High Integration of Wind Power," Energies, MDPI, vol. 14(15), pages 1-15, July.
    2. Ragab El-Sehiemy & Abdallah Elsayed & Abdullah Shaheen & Ehab Elattar & Ahmed Ginidi, 2021. "Scheduling of Generation Stations, OLTC Substation Transformers and VAR Sources for Sustainable Power System Operation Using SNS Optimizer," Sustainability, MDPI, vol. 13(21), pages 1-24, October.
    3. Juliano C. L. da Silva & Thales Ramos & Manoel F. Medeiros Júnior, 2021. "Modeling and Harmonic Impact Mitigation of Grid-Connected SCIG Driven by an Electromagnetic Frequency Regulator," Energies, MDPI, vol. 14(15), pages 1-21, July.
    4. Yaçine Merrad & Mohamed Hadi Habaebi & Siti Fauziah Toha & Md. Rafiqul Islam & Teddy Surya Gunawan & Mokhtaria Mesri, 2022. "Fully Decentralized, Cost-Effective Energy Demand Response Management System with a Smart Contracts-Based Optimal Power Flow Solution for Smart Grids," Energies, MDPI, vol. 15(12), pages 1-27, June.

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