Carbon-emission Reduction of Hybrid Renewable Energy System Stochastic Day-Ahead Scheduling

Abstract

: In light of new energy policies, energy systems should face the challenge of mitigating CO 2 . Although environmental sustainability is a hot topic, Day-ahead (DA) scheduling is approached by prioritising the economic perspective, risking sub-optimal CO 2 emission. To highlight the current model limitation, this paper proposes an approach for minimising CO 2 during operation inspired by the Carbon Emission Flow (CEF) method, not revealed by cost optimisation. Although this approach assumes complete energy system control and is less likely to be used for real-world energy dispatching, such a tool creates awareness among stakeholders about the minimum CO 2 limit and the consequences of using specific components or external sources. For this purpose, CEF cost and emission results are compared with cost minimisation with/without CO 2 taxation, confirming that current optimisations objectives cannot achieve the lowest CO 2 emission level. The performances are compared with indices assessing sustainability with insights on dispatching strategies and system components that affect emissions and costs. Finally, to detect if the taxation strategy is suitable for reaching the lowest CO 2 in DA scheduling, a sensitivity analysis was carried out by increasing taxation prices up to 5-times, concluding it would increase costs without reaching the minimum set by the proposed approach.