Search

In the context of the large-scale participation of renewable energy in market trading, this paper designs a cooperation mode of new energy power stations (NEPSs) and shared energy storage (SES) to participate in the power-green certificate market, which divides SES into physical energy storage and virtual energy storage. Secondly, combining the advantages of scenario generation and robust optimization (RO), a two-stage RO model with improved uncertainty interval is proposed to determine the optimal trading strategy. Then, to better align the distribution results of cooperative benefits with the actual contributions of NEPSs and SES, an entropy weight modified Shapley value benefit allocation strategy is constructed. Finally, the new energy base in Qinghai Province, China is chosen for simulation. The results show: (1) Adding energy storage and using two-stage RO are able to effectively improve the ability of NEPSs to resist uncertainty, which increases the revenue of the alliance by 22.8%. (2) The application of SES has better economic benefits than each member equipped with energy storage separately. Compared with the latter, the deviation penalty cost of the former is reduced by 66.4%, and the revenue is increased by 3.4%. (3) The proposed entropy weight modified Shapley value method embodies the important auxiliary role of SES more obviously. Based on this method, the overall satisfaction of the alliance increases by 12.6%. Generally speaking, the optimization model and benefit allocation strategy proposed in this paper can provide guidance for NEPSs and SES participating in power trading, and promote the low-carbon transformation of the power sector. [Display omitted] • Design a cooperation mode of new energy power stations and shared energy storage. • Divid the shared energy storage into physical energy storage and virtual energy storage. • Propose a two-stage robust optimization model with improved uncertainty interval. • Construct an entropy weight modified Shapley value-based benefit allocation strategy. • Select a new energy base as the simulation system for verifying the effectiveness and applicability. [ABSTRACT FROM AUTHOR]

• Design a hydrogen energy storage system-carbon capture and utilization system-based micro energy grid. • Proposed a carbon emission-green certificate equivalent interaction mechanism for multi-energy conversion and storage system. • Construct a two-stage optimal dispatching framework including day-ahead robust dispatching model and real-time rolling model. • Proposed an entropy-Shapley-based benefit allocation method considering multi-dimension impact factors. • Carried out the effectiveness and applicability analysis for the proposed dispatching scheme and benefit allocation strategy. To fully utilize the abundant renewable energy resources in county-level areas of China, this paper designs a novel structure of micro-energy grid integrating hydrogen energy storage (HES) system and carbon capture and utilization (CCU) system (HES-CCU-based MEG). And a carbon emission-green certificate equivalent interaction mechanism is established. Then, a two-stage optimal dispatching framework is proposed for mitigating the impact of uncertainty variables, including a day-ahead robust dispatching model and a real-time rolling optimization model. Thirdly, an entropy-Shapley-based benefit allocation method is constructed to allocate the benefits in dimensions of energy conservation, carbon emission reduction, and renewable power consumption among various devices. Finally, a micro-energy grid in Henan province, China, is selected as an example for case study. The results show that: (1) HES could transfer surplus renewable power and low-priced power to periods with high power prices, while CCU could achieves the cycle and utilization of CO 2 , leading to a decrease in power purchase costs and carbon emissions by 7.85% and 0.47%, respectively. (2) The two-stage optimal dispatching model gives full play to the flexibility adjustment ability of each device, mitigates the deviations caused by uncertainty variables, and formulates the optimal dispatching strategy. (3) The entropy-Shapley-based benefit allocation method could evaluate the contributions of each device in different dimensions, effectively, ensuring the rationality of benefit allocation results. Overall, the proposed model and method could utilize renewable energy resources in county-level areas, which is better to promote the clean and low-carbon transformation of the overall energy structure. [ABSTRACT FROM AUTHOR]