@inproceedings{112bf9dc7c174519bd298458cc1aefb5,
title = "Optimised Scheduling Strategy for Source-Load-Storage Cooperation Considering Economic Efficiency",
abstract = "This research tackles the challenge of effectively managing the variable output of solar energy in electricity generation through the development of an optimized model for a Virtual Power Plant (VPP) integrating multiple microgrids (MMGs). The proposed approach introduces a real-time optimization method, incorporating provisions for designating a portion of the microgrid as a backup. The optimization model comprises two key phases: day-ahead planning and real-time adjustments. During the day-ahead planning phase, the objective is to optimize the VPP's profitability by determining optimal baseline and regulation capacity values for each hour of the subsequent day. Real-time adjustments aim to synchronize the VPP's electricity consumption with the dynamic regulation signal (RegD signal) at minimal cost. This real-time optimization process identifies the most efficient operational configurations for each microgrid and VPP resource. Simulation results validate the efficacy of this real-time optimization approach, showcasing its ability to enhance VPP revenue while upholding its crucial role in supporting grid frequency stability.",
keywords = "air-conditioning, demand-side response, solar energy, Virtual power plant",
author = "Xiaoxuan Zhang and Zheng Zhao and Jian Li",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 7th IEEE International Electrical and Energy Conference, CIEEC 2024 ; Conference date: 10-05-2024 Through 12-05-2024",
year = "2024",
doi = "10.1109/CIEEC60922.2024.10583766",
language = "English",
series = "Proceedings of 2024 IEEE 7th International Electrical and Energy Conference, CIEEC 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2349--2354",
booktitle = "Proceedings of 2024 IEEE 7th International Electrical and Energy Conference, CIEEC 2024",
address = "United States",
}