With the prevalence of cloud computing applications, cloud data centers (CDCs) are proliferating around the world. However, in the context of hybrid energy‑carbon markets environment, the high energy costs and environmental expenses caused by CDC operation are pressing CDC owners to restructure the future development of CDC in a more economical and low-carbon manner. The potential spatio-temporal transferability and reducibility of workloads provides CDCs with significant flexibility in their operations and thus may interact with the power grid as active demand users. Nonetheless, other than private data centers, public CDCs have no direct control over the workloads submitted by terminal cloud users. As such, this paper presents a bi-level model for CDC allocation planning, so as to incorporate cloud service-demand response (CS-DR) from the perspective of a hybrid electricity-carbon market. The upper level pertains to multi-domain resource collaborative planning model, which determines the optimum siting and sizing of CDCs as well as the incentive design for CS-DR program, with the objective of maximizing the total expected benefits of CDC. The lower level models correspond to the market clearing (electricity-carbon tariff model) of Independent system operator (ISO) and the decision-making of cloud users regarding CS-DR participation. The proposed model belongs to a bi-level mixed integer nonlinear programming problem with two non-convex lower levels, which can be intractable in mathematics. To solve such difficult problem, a hybrid solution method combining multiple linearization techniques and reformulation and decomposition (R&D) strategy based on column-and-constraint generation (C&CG) algorithm is developed. The proposed model is demonstrated on a modified IEEE 30-bus test case, and the simulation results verified the effectiveness of the proposed approach.

With the maturity of independent energy storage technology, the traditional evaluation method of independent energy storage effect has strong subjectivity and insufficient objectivity, which leads to the defects of evaluation results deviating from the reality. In view of the shortcomings of independent energy storage comprehensive evaluation such as single, incomplete, subjective, uncertain and random, this paper proposes a multi-characteristic comprehensive evaluation model of independent energy storage under multi-application scenarios, which can more comprehensively evaluate the comprehensive value of independent energy storage in the power market. Firstly, the single application scenario is extended to the multi-application scenario, and the multi-feature evaluation index system is established from the aspects of security, economy and environmental protection. Secondly, in order to better solve the evaluation uncertainty problem of decision makers, the cloud model is used to improve the subjective comprehensive evaluation method, which improves the problem that the traditional evaluation method is greatly affected by subjective preferences, and the uncertainty of the evaluation is visually represented by cloud droplets. The final simulation results show that independent energy storage has a high economy in the rental market and electricity energy market and other application scenarios, while in terms of environmental protection, independent energy storage has a strong role in promoting the absorption capacity of clean energy.

Sector coupling includes not only the coupling within energy sectors such as electricity, heat and gas, but also the coupling between energy sector and transportation sector, construction sector and industrial sector. This article introduces a method for measuring the development potential of clean energy based on sector coupling. First, the analysis model of electric energy substitution potential is constructed, the analysis object is determined, and the analysis object is quantified. On the basis of the definition of clean energy development potential, an IPAT model for electric energy substitution is constructed to realize the comprehensive evaluation of clean energy. Secondly, based on Markov theory to realize the sub-path calculation of the development potential of clean energy. Finally, based on the IPAT model and the decoupling theoretical model, this paper sets up three different alternative scenarios to make a more comprehensive prediction and analysis of the medium and long-term clean energy development potential, and applies the introduced measurement methods to the calculation of China’s clean energy development potential. The results show the effectiveness of the algorithm in the calculation of the development potential of clean energy based on sector coupling.