The rapid evolution of artificial intelligence technology has driven a sharp rise in the load on computing infrastructure

represented by data centers. Currently

the expansion of green power supply and computing scale in China faces challenges of spatial resource mismatch and temporal supply-demand misalignment. Consequently

electricity- computing power synergy has emerged not only as the key to supporting green computing with green power but also as an inevitable path for the deep integration of China’s “East Data

West Computing” and “West-East Power Transmission” national projects. This paper first elucidates the connotation and evolutionary path of electricity-computing power synergy

identifying two key scientific problems: mapping and representation of heterogeneous electricity-computing resources

and joint minimization of energy entropy and information entropy. Subsequently

a six-layer technical architecture spanning entity

sensing

simulation

decision

execution

and incentive layers is constructed. Based on this framework

the paper proposes core research directions for key technologies

including mapping representation and electrical equivalent modeling of computing-electricity resources

establishment of coupled digital twins and simulation deduction

collaborative resource regulation and online optimization-based decision-making

grid integration and reliable spatiotemporal migration of heterogeneous computing power

as well as incentive-compatible mechanisms and trusted trading in multi-dimensional markets. Finally

the paper systematically reviews current research status and practices in electricity- computing power synergy across multiple spatial scales

ranging from efficient energy use within data centers to park-level multi-energy complementarity

regional supply- demand coordination

and wide-area joint dispatching

and provides an outlook on the future development trends of key technologies.