Day-ahead dispatch with carbon trading for multi-regulation participation and emission reduction considering multi-type energy storage

• Published in: International journal of electrical power & energy systems 2024-07, Vol.158, p.109942, Article 109942
• Main Authors: Zhang, Mingze, Li, Weidong, Yu, Samson S., Zhao, Junbo
• Format: Article
• Language: English
• Subjects: Low-carbon power dispatch; Multi-type energy storage; Regulation ancillary service; Renewable energy; Supply–demand balancing
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2024.109942

•A coordinated scheme of multiple ESSs is proposed to participate in multiple FCASs.•Energy-type, power-type, and composite-type ESSs are included in proposed model.•Day-ahead dispatch model is built with potential operation risks of power systems.•A new environmental factor is introduced in dispatch objective with CO2 emissions.•Optimal tradeoff of four goals in active power operations is achieved. In this work, a day-ahead dispatch optimization model with energy-type, power-type, and composite-type energy storage systems (ESSs) is established to participate in multiple frequency control ancillary services (FCASs), in wind-energy-integrated power systems. This model is designed to better handle the operational uncertainties of wind energy, mitigate operational risks and reduce carbon emissions. Leveraging the complementary features of different types of ESSs, the proposed operation strategies of regulation units can respond to multiple FCASs and achieve the optimal task allocation among different types of resources. Various uncertainty handling approaches are adopted to better cope with the randomness of step disturbances and wind power fluctuations. Furthermore, a new environmental factor is devised in the dispatch objective and the time-of-use carbon-price carbon emission trading (ToU-CET) and ladder-type CET (LT-CET) models are developed. They can incorporate dynamic carbon prices and leverage mechanisms to reduce carbon emissions during daily operations. The effectiveness of the proposed model is verified by case studies, and the decisions can help save energy and reduce carbon emissions in modern power systems with wind power generators with high security and reliability.