Under the new power system construction and the rapid development of the new generation of Artificial Intelligence (AI), the continuous growth of computing demand has placed high requirements on the stability, reliability and green electricity ratio, creating a structural contradiction with the new power system dominated by wind and solar energy, making computing-power synergistic development imperative. This paper studies the connotation, development situation, key technologies and challenges of computing-power synergy. It first expounds the basic concepts and connotation of computing-power synergistic development and reviews its development situation. Then, it systematically examines key technical paths from five aspects, namely, computing load forecasting, highly reliable power supply, green power direct supply, spatiotemporal scheduling and market trading. Finally, it discusses the challenges and future development trends of computing-power synergy. The research results aim to provide a certain theoretical basis and application guidance for the development of computing-power synergy, and serve as a reference for relevant practitioners.

The computing-power synergy has emerged as a central topic in new infrastructure construction for the artificial intelligence era, evolving from industry practice into a national top-level design. This paper begins by defining the concept of computing-power synergy, deconstructing it into three logical dimensions: spatio-temporal synergy, technical synergy, and market synergy. It then analyzes and evaluates the standardization requirements for computing-power synergy. Finally, a standard system framework is proposed, encompassing seven sub-systems such as general foundations, technical support, market transactions, and inspection and evaluation. The findings aim to provide a technical reference for the planning of computing-power synergy standards.

Amid the rise of computing-power synergy on the national agenda, grid enterprises offering external computing-power services must innovate their business and scheduling models. Adopting a “power-carbon-computing” perspective, this study proposes a composite-token-based business model, defines a four-dimensional attribute structure (computing specifications, green rights, migratability, and interruptibility), and formulates a multiplicative-factor pricing model. Full-chain costs and profits are compared on a per-GPU-hour basis across three models: whole-card leasing, pure computing-power tokens, and composite tokens. A token routing algorithm is then developed, weighting power price as the primary signal and renewable output as a secondary one. Customers receive discounts by relinquishing node-fixation or task-continuity rights, while the enterprise monetizes this flexibility through coordinated scheduling to preserve its margin. A GPU-as-a-Service (GPUaaS) model and a phased implementation roadmap are also presented, providing a reference for grid enterprises to develop differentiated computing-power operations.

With the rapid development of digital economy and Artificial Intelligence (AI) industry, the demand for computing power shows explosive growth. The contradiction between the high energy consumption of data centers and the pressure of new energy consumption in new power systems is increasingly prominent. As an important path to solve the spatial-temporal supply and demand mismatch between computing power and power and achieve the green and low-carbon development goals, computing-power synergy has attracted extensive attention from industry and academia. Firstly, this paper expounds the core concept and development background of computing-power synergy, and systematically sorts out the policy orientation, technical progress and application situation at home and abroad. Secondly, it discusses in depth the key technologies of AI-empowered computing-power synergy from four dimensions: multi-element time series intelligent prediction, 4D spatial-temporal joint scheduling, adaptive migration of heterogeneous computing power, and quantitative evaluation of multi-dimensional value. Then, it introduces China Mobile’s technical layout and practical exploration in this field, and analyzes the application effects with one typical case: Shanghai-Anhui-Xinjiang cross-domain computing-power synergy. Finally, it summarizes the current challenges and prospects the future development direction.

The synergy between computing and power,as a key paradigm for the deep integration of digital and energy infrastructure, is increasingly serving as a driver for sustainable computing development and renewable energy integration. China’s computing-power synergy ecosystem has initially established a comprehensive industrial chain system encompassing “new energy power generation, energy storage regulation, grid transmission, intelligent computing centers, and application scenarios.” The coordinated development of green computing and the “source-grid-load-storage-computing” framework is becoming a prominent trend. However, it faces challenges including spatial misalignment between computing resource allocation and energy distribution, inadequate coordination mechanisms between computing and power scheduling, underdeveloped standardization and market mechanisms, and an insufficient supply of interdisciplinary talent. To address the aforementioned issues, the paper proposes a series of recommendations, including the enhancement of strategic planning and standardization frameworks, the fostering of collaborative innovation across the “source-grid-load-storage-computing” ecosystem, and the establishment of an integrated innovation ecosystem combining industry, academia, research, and application. These measures aim to promote the coordinated optimisation of computing capacity and power resources, and to foster the high-quality, integrated development of the digital economy and the energy system.

The relationship between computing infrastructure and power systems is evolving from unidirectional supply and consumption toward bidirectional coordination. Traditional energy-efficiency evaluation frameworks centered on Power Usage Effectiveness (PUE) can no longer adequately accommodate this trend. Research progress on multi-dimensional energy efficiency evaluation metrics for computing-power synergy is systematically reviewed. The challenges posed by emerging technologies, including liquid cooling and wide-area scheduling in computing power networks, to conventional evaluation paradigms are analyzed, and the evolution and limitations of domestic and international standard systems for compute-electricity collaboration are summarized. Literature analysis indicates that harmonizing heterogeneous measurement dimensions and standardizing dynamic evaluation are central research issues, while benefit allocation and responsibility attribution under multi-stakeholder coordination mechanisms require further investigation. The development of graded standards for computing-load flexibility and interface protocols for joint computing-power dispatch represents an important direction for advancing the standardization of computing-power synergy.

The synergistic development of computing power and electricity is a crucial integration point for optimizing energy resource allocation and ensuring the efficient operation of computing infrastructure in the deep advancement of the “East Data, West Computing” project. By selecting two national computing hub nodes—Ulanqab in Inner Mongolia and Qingyang in Gansu Province—a comparative analysis framework was constructed across five dimensions: green power supply mechanisms, energy efficiency levels, business models, industrial ecosystems, and policy innovation. The study found that Ulanqab has developed a “resource-adaptive” model characterized by water-saving cooling and lifecycle energy efficiency management, whereas Qingyang pioneered a “institution-innovative” model centered on green power aggregation and direct supply. These two models represent typical pathways for computing-power synergy in water-scarce and green-power-abundant regions, respectively. Based on the comparative findings, systematic optimization recommendations were proposed, including unified planning, standardized construction, and market mechanism innovation, providing theoretical reference and practical insights for the large-scale promotion of computing-power synergy.

Against the backdrop of global energy restructuring and surging computing demand, computing-power coordination has evolved from technical collaboration into a national strategy. This paper explores its core connotation and strategic value, and examines structural mismatches across spatial layout, time sequence and institutional mechanisms in China. It further reviews policy-oriented development models adopted by the United States, the European Union and Japan. Considering China’s national realities, the study puts forward an institutional restructuring framework covering integrated planning, market-based mechanisms, unified technical standards, pilot demonstrations and international cooperation. The outcomes are intended to facilitate the sound development of computing-power coordination and the refinement of relevant policy systems.

In 2026, China has designated computing-power synergy as a key new infrastructure project, highlighting the urgent need to resolve the contradiction between surging computing demand and energy constraints. Based on defining the connotations of computing-power synergy and the computing power economy, this study reviews the current development status and structural contradictions of China’s computing power economy, dissects the core development logic from four dimensions—energy-information integration, industrial coordination, policy drive, and regional coordination—and proposes five optimization paths: building a national integrated computing power network, deepening the computing-power synergy mechanism, improving the standard system, strengthening technological innovation and talent cultivation, and optimizing policy incentive mechanisms, with a view to providing theoretical insights and practical guidance for the high-quality development of the digital economy.

The implementation of computing-power synergy policies faces systemic obstacles such as multi-departmental coordination failure, cross-regional institutional barriers, and a lack of implementation safeguards. Industrial development is simultaneously constrained by insufficient collaboration in the “communication-power” industrial chain, techno-economic bottlenecks, and a supply-side shortage of interdisciplinary talent. Drawing on new institutional economics and industrial ecosystem theory, this study constructs a “three-dimensional, four-layer” analytical framework to systematically identify key barriers across the three dimensions of “policy-industry-talent” and their interaction mechanisms. Based on publicly available policy documents, industry statistics, and typical case analysis, it reveals core issues such as the degree of policy coordination, cross-regional connection costs, and the effectiveness of market incentives. This paper puts forward implementation paths centered on enterprise self-optimization, market-oriented industrial coordination and lightweight local supporting services, and improves industrial chain coordination and enterprise independent talent training strategies adapted to the distributed computing power characteristics of the communications industry.

Currently, the financing difficulties of Small and Medium-sized Enterprises (SMEs) are externally manifested as “financing difficulty” but at the core lie “financing expensiveness”. The essence of “financing expensiveness” lies in the high-cost nature of risk pricing mechanisms under the traditional financial model, forcing financial institutions to adopt “discriminatory interest rates” against SMEs to cover potential risks. From the perspective of “financial structure synergy”, this paper proposes reconstructing the risk pricing model through two-way digital empowerment. To alleviate the SMEs’ financing difficulties, it is essential to systematically advance the digitalization of risk management in financial institutions to reduce risk identification costs, and support the digital transformation of SMEs’ operations to provide a basis for risk pricing, thereby replacing group-based discriminatory pricing with personalized precision pricing. Finally, fintech platforms offer a scalable new paradigm for such personalized pricing through ecological models. From the perspective of risk pricing costs, this study provides a novel theoretical explanation and a systematic pathway for resolving SMEs’ financing difficulties.

Chinaattaches great importance to the protection of the rights and interests of persons with disabilities. The report of the 20th National Congress of the Communist Party of China (CPC) pointed out the need to improve the social security system and care service system for people with disabilities, and promote the comprehensive development of the disability cause. During the 14th Five Year Plan period, the construction of information accessibility has gradually been promoted, focusing on solving the difficulties faced by people with disabilities in using intelligent technology, providing more comprehensive, caring, and direct intelligent products and services for people with disabilities, and achieving significant results in promoting the high-quality development of the disability affairs. During the 15th Five Year Plan period, in the new situation of rapid development of information technologies such as artificial intelligence models, brain computer interfaces, and embodied intelligence, the construction of information accessibility needs to further improve its positioning, plan ahead, go deep and practical, and help the programs of people with disabilities move towards a higher and newer stage.

The urban digital base is the core support for the overall digital transformation, accelerating the upgrading and evolution towards platformization, intelligence, and security resilience. By clarifying the connotation of urban digital infrastructure, analyzing the representative paths, typical models, and development trends of urban infrastructure construction in various regions, extracting the operational mechanism of infrastructure, and focusing on key issues throughout the entire cycle of “planning, construction, management, operation, evaluation, and investment”, systematic policy recommendations are proposed. Aiming to use the digital base as an engine to drive the refinement of urban governance, digitalization of the economy, and inclusiveness of people’s livelihoods, and to promote its transition from “basic support” to “value engine”.