The proposed method enhances economic stability and resource allocation in energy storage, suggesting better outcomes through carbon trading.
Suppose only the initial investment cost of energy storage is focused on, while the full life cycle benefits (such as carbon trading benefits, capacity electricity cost savings, etc.) are ignored. In that case, it will lead to the optimization results deviating from reality. Therefore, a green power energy storage resource optimization allocation method considering stepwise carbon trading is designed. The wind power data is analyzed in detail at multiple scales by using wavelet packet decomposition. A stepped carbon trading mechanism is introduced. Combined with free carbon quotas and actual carbon emissions, the transaction amount of carbon emission rights is calculated. Considering factors such as system economy, power supply reliability, and the rate of wind and solar power curtailment comprehensively, a multi-objective function is established. Considering the actual output of wind and solar power units, output constraints are set. Construct a resource optimization allocation model. The experimental results show that the economic benefits of the proposed method are more stable. The power shortage rate and wind and solar power curtailment rate of the system load are only 5% and 10%, respectively, which can improve the comprehensive utilization rate of energy.
No takes yet. Share an insight, caveat, or question.
Zhang et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: