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In the trend of power system decarbonization, wind power and energy storage planning studies are in full swing. Incentives for wind power and energy storage development are important research topics. However, most studies have proposed incentives from an energy perspective, and few focus directly on incentives from a carbon perspective. To this end, this paper proposes a novel unified bus carbon intensity incentive mechanism from the carbon perspective. A two-stage Stackelberg game wind storage planning model that considers the proposed carbon incentive mechanism is constructed. In the first stage, the carbon flow of the entire system is obtained following economic dispatch based on the carbon emission flow theory. In the second stage, a Stackelberg game wind-storage planning model is constructed to model the game between the power generation company and the power grid company. Through simulation analyses of these cases, the proposed incentive mechanism can effectively guide the construction of wind turbines and energy storage at the best buses. Additionally, by comparing the proposed incentive with the existing incentive mechanisms, this paper finds that the proposed incentive mechanism can achieve a higher carbon reduction effect with a similar total investment in wind turbines and energy storage. [ABSTRACT FROM AUTHOR]

Introducing carbon trading is an essential way to decarbonize the power system. Many existing studies mainly consider source-side unilateral carbon trading (UCT). However, there are still rare studies considering source-load bilateral carbon trading (BCT). The effect of source-load BCT on system-wide carbon mitigation is worth studying. To fill this research gap, a hierarchical low-carbon economic-dispatch model with source-load BCT based on the Aumann–Shapley method was proposed. In the first layer, economic-dispatch was conducted to minimize the power-generation costs and source-side carbon-trading costs. Then, based on the carbon-emission flow (CEF) theory, the actual load carbon emissions can be obtained and passed to the second layer. At the second layer, the demand-response optimization was performed to minimize the load-side carbon-trading costs. Finally, the proposed model was tested on the modified New England 39-bus and IEEE 118-bus systems using the MATLAB/YALMIP platform with the Gurobi solver. The results indicate that the proposed model can effectively facilitate peak-load shifting, wind-power consumption, and carbon mitigation. Furthermore, compared with the models only considering source-side or load-side UCT, the proposed source-load BCT model has obvious advantages in carbon mitigation. [ABSTRACT FROM AUTHOR]

The decarbonization of the power system forces the rapid development of electric energy storage (EES). Electricity consumption is the fundamental driving force of carbon emissions in the power system. However, the current EES capacity planning research that considers the load-side carbon emission responsibility is still limited. To fill this research gap, this paper proposes a carbon incentive mechanism while considering load-side carbon emission responsibility. Additionally, a bi-level optimal capacity planning model of the load-side EES based on carbon emission flow (CEF) theory is proposed. The upper level obtained the bus carbon intensities through the optimal economic dispatch and passed them to the lower level. Considering the carbon incentive mechanism, the lower level optimized the EES capacity. Finally, the model was tested by MATLAB/Gurobi in the modified IEEE-39 bus power system. The results show that under the stimulation of the carbon incentive mechanism, the bi-level optimal capacity planning model of the load-side EES could effectively promote peak shaving, valley filling, and carbon reduction. Furthermore, compared with the two existing EES subsidy policies, the proposed carbon incentive mechanism is verified to be more conducive to reducing system carbon emissions. [ABSTRACT FROM AUTHOR]