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• This paper proposes a bi-level Stackelberg low-carbon economic dispatch model with reward and penalty stepped carbon trading mechanism, horizontal and vertical integrated demand response, and dynamic supply and demand multi-energy pricing. • This paper also provides a multi-angle sensitivity analysis of the impact of different parameters of the stepped carbon trading mechanism on the operation of the CIES. • An innovative analysis of the impact of single and two-factor carbon interval length, carbon growth rate, and carbon base price on the CIES is presented. • The sensitivity analysis of horizontal integrated demand response is also carried out. • Through horizontal and vertical integrated demand response, the dynamic supply and demand multi-energy pricing of CIES is further improved. To solve the problem of coupled and coordinated dispatch of multi-energy between campus integrated energy system operator and users. A bi-level Stackelberg low-carbon economic dispatch model with horizontal and vertical integrated demand response and dynamic supply and demand multi-energy pricing (DSDMEP) is proposed. Firstly, the DSDMEP is established to effectively coordinate the interests of the upper CIESO and lower users. Secondly, the combined heat and power containing the power to gas and carbon capture system and the reward and penalty stepped carbon trading mechanism (SCTM) are introduced on the energy supply side to minimize carbon emissions. Then, the HVIDR is introduced to the users to increase the energy coupling and adjustable price characteristics of supply and demand. Finally, the results show that the proposed model compared to other scenarios has its carbon emissions reduced by 21.72%, the benefits of CIESO are increased by 27.86%, and the cost of the users is reduced by 6.9%. This paper also provides a multi-angle sensitivity analysis of the impact of different parameters of the SCTM on the operation of the campus integrated energy system (CIES), as well as a sensitivity analysis of the HVIDR and peak and valley electricity price difference. [ABSTRACT FROM AUTHOR]

• Carbon emission flows of distribution networks are traced considering power loss and reactive power. • Individuals and the overall customers are harmonized by the proposed low-carbon allocation method at the demond side. • The decarbonization potential of shared PVs and ESSs is exploited based on CEF calculation and carbon quota mechanism. • Optimal amounts and locations of shared PVs and ESSs are obtained via the proposed method with the limited investment. With the targets of carbon peaking and carbon neutrality, carbon emission reduction measures have become significant issues in new-type power systems. Distribution networks (DNs), which multiple power sources and flexible loads access to, play an essential role in exploiting the potential of reducing carbon emissions on the demand side. To achieve a global carbon emission reduction considering the carbon quota of each customer, shared photovoltaics (PVs) and energy storage systems (ESSs) are allocated with a centralized calculation and optimization conducted by DNs. To solve two key points in demand-side planning of shared PVs and ESSs in distribution networks, i.e., the accuracy of carbon emission flow (CEF) calculation and carbon quota-oriented optimization planning, this paper proposes a low-carbon oriented planning method for shared PVs and ESSs via CEF tracing. Firstly, a novel CEF calculation method is proposed based on the forward current sweep and backward voltage sweep algorithm, which considers the tracing of reactive power and power losses. Next, carbon emission index and economic index of allocating shared PVs and ESSs are defined. Subsequently, a bi-level optimization model is presented, considering the excess carbon emissions of each load based on carbon accounting and carbon quotas. Finally, the superiority of the proposed method is verified through a modified IEEE 33-node distribution network, and the effects of various investment constraints and carbon quotas are discussed. [ABSTRACT FROM AUTHOR]

• Integration of blockchain characteristics into the collaborative carbon emission reduction game model of both the supply and demand sides of electricity is proposed to encompass source control and terminal suppression. • Blockchain is utilized to trace electricity types within the electricity market and to quantify the carbon emissions generated by the demand side of electricity. • By incorporating blockchain, users can actively engage in individual-level carbon trading to control and reduce carbon emissions. • Blockchain facilitates enhanced carbon emission reduction efforts by the power supply side. The task of carbon emission reduction is severe in the power industry in China under the national goal of "carbon peaking and carbon neutrality". The current carbon reduction is mainly based on supply side, but the effect is limited. To solve this problem, this paper proposed a coordinated supply–demand carbon emission reduction strategy based on blockchain technology. Based on the carbon emission reduction of complementary thermal power and renewable energy under the carbon trading mechanism of power supply side, users are made to participate in the individual level carbon trading mechanism with the help of blockchain technology, and the carbon emission reduction in power demand side is guided through the market mechanism, thus forming a supply–demand collaborative carbon emission reduction strategy of source side control and terminal inhibition. By analyzing the decision changes of both the supply and demand sides of electricity before and after the introduction of blockchain, quantifying the influence of blockchain on electricity quantity, electricity price and users' utility in turn, and establishing the personal carbon trading mechanism supported by blockchain, a game model of two-side interaction between supply and demand was constructed. The simulation results show that the collaborative carbon emission reduction strategy based on blockchain gives full play to the potential of carbon reduction in power demand side, and the personal carbon trading mechanism can better inhibit terminal carbon emissions, which is conducive to the deep carbon emission reduction of the power industry. [ABSTRACT FROM AUTHOR]

• Proposed cooperative game model of hierarchical trans -regional electricity trading. • Analyzed the impact of carbon quota systems on trans -regional electricity trading. • Proposed a reasonable profit distribution scheme based on the Owen graph value. • Demonstrated that the formation of priori union can improve the profits of trans-regional electricity trading. • Under loose low-carbon demand policy, carbon quota sharing responsibility are more effective than producer responsibility. Trans-regional electricity trading is a meaningful way to optimize resource allocation and achieve carbon peak and carbon neutrality goals. In this paper, we construct the trans -regional electricity trading cooperative game models considering the impact of local microgrid integration. Based on the cooperative game theory with coalition and graph structures, the optimal mode of trans -regional electricity cooperation and the impact of different carbon quota systems on cooperation profits are studied. The profits obtained through the trans -regional electricity trading are reasonably distributed by the profit distribution scheme based on the Owen graph value. The theoretical and numerical simulation results demonstrate that the local microgrid and the bulk power grid form a priori union, and then participate in the trans -regional electricity trading can obtain more profits. In addition, when the low-carbon policy on the demand side of electricity becomes more relaxed, the implementation of a carbon quota shared responsibility between producers and consumers will be more effective than producer responsibility. Compared with the Myerson value, the profit distribution scheme based on the Owen graph value is more suitable for distributing the profits obtained through trans -regional electricity trading. [ABSTRACT FROM AUTHOR]