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Renewable energy and energy storage are essential technologies for decarbonizing energy systems. Expansion planning of the two technologies considering source‐side carbon responsibility has been well studied. However, expansion planning considering both source‐side and load‐side carbon responsibility, which may simultaneously stimulate the carbon reduction potential of source and load, has been rarely studied. To fill this research gap, this paper proposes a bi‐layer wind turbine generator (WTG) and demand‐side battery (DSB) coordinated planning framework considering wind power and load uncertainties. Moreover, a novel source‐load bilateral carbon trading (BCT) mechanism based on the Aumann–Shapley method is proposed to stimulate the WTG and DSB configuration. In the bi‐layer planning framework with BCT mechanism, WTG and DSB capacity planning with the two‐stage stochastic optimization are conducted in the upper and lower layer, respectively. Finally, test results on a modified IEEE 24‐bus system demonstrate that the proposed framework with BCT mechanism can effectively motivate the planning configuration of WTG and DSB and carbon mitigation. Compared with the models with unilateral carbon trading mechanisms, the proposed model has advantages in stimulating configuration of WTG and DSB, reducing carbon emissions, and balancing source‐load economic burden from carbon trading. [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]