Optimal scheduling of power systems with wind and solar power generation considering carbon trading and energy storage cost
- DOI
- 10.2991/978-94-6463-262-0_34How to use a DOI?
- Keywords
- carbon trading; energy storage; optimization scheduling
- Abstract
In the context of the sustainable development of low-carbon power, in order to reduce carbon emissions in the power generation process of the power industry, carbon trading mechanism is introduced into the power system optimization scheduling, and electric energy storage is introduced to improve the power system flexibility to promote the consumption of new energy. This paper firstly analyzes carbon trading cost model of thermal power unit. Then, an optimal scheduling model aiming at the lowest total cost is constructed, which comprehensively considers the conventional thermal power unit operation cost, energy storage operation cost, carbon trading cost, wind-photovoltaic operation cost and various system constraints. Finally, through the analysis of simulation examples, it is verified that energy storage and carbon trading can effectively optimize the energy structure and reduce the system carbon emissions.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Kai Guo AU - Rulei Han AU - Yuqiang Wang AU - Chen Gao AU - Kai Yin PY - 2023 DA - 2023/10/09 TI - Optimal scheduling of power systems with wind and solar power generation considering carbon trading and energy storage cost BT - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023) PB - Atlantis Press SP - 302 EP - 310 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-262-0_34 DO - 10.2991/978-94-6463-262-0_34 ID - Guo2023 ER -