A bi‐layer stochastic coordinated planning framework for wind‐battery power systems considering bilateral carbon trading

Abstract

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.

A bi-layer wind-CCUS-battery expansion stochastic planning framework considering a source-load bilateral carbon incentive mechanism based on the carbon emission flow theory

“…Case 1: source-load BCI, i.e., the carbon emissions responsibility of the generators is shared equally by the power generation side and the load side, with each side bearing 50% of the carbon emissions responsibility (Nan et al, 2022a;Nan et al, 2022b).…”

“…The detailed parameters of each generator such as generator type, capacity, cost coefficient, can carbon emission intensity are shown in Table 1 (Zimmerman et al, 2011;Nan et al, 2022a). The parameters of the WTG, CCUS and DSB to be planed are shown in Tables 2 (Mei et al, 2021;Zhong et al, 2021;Sun et al, 2022b;Gowd et al, 2023).…”

“…Designing carbon trading incentive mechanism only on one side cannot fully stimulate the carbon reduction potential of both sides. Nan et al (2022a); Nan et al (2022b). also established two-side carbon trading mechanisms, but did not consider the effect of CCUS on carbon emission reduction.…”

Tri‐layer low‐carbon distributed optimization of integrated energy systems based on hybrid games under stochastic scenarios

“…Refs. [12] and [13] combined the GCT mechanism with a flexible load‐demand response model to propose an optimization model that considers the benefits of green certificates and effectively improves system efficiency and new energy consumption. CET considers whether the total carbon emissions in the system exceed the given carbon quotas.…”