A smart grids knowledge transfer paradigm supported by experts' throughput modeling artificial intelligence algorithmic processes

This paper presents an artificial intelligence algorithmic knowledge transfer approach to the models that have been developed throughout world for smart grid networks. Many nations are moving forward implement smarter ways generate, distribute and network energy, while others expecting leading countries take initiative then follow suit. Therefore, we theoretically identify three dimensions of experts' competencies—perception, judgment, decision choice supported by Throughput Model algorithms transfer. Integrating framework Deming Cycle (i.e., plan, do, check, act), propose Information Communication Technology (ICT) systems influence making towards implementation Smart Grids (SG). model was backed up with perspectives 32 global experts as surveyed using Carnegie Mellon Maturity questions analyzed results PLS validate findings compare them our enhanced from Deming's PDCA cycle. Our suggest these key decision-making components critical in explaining successful application planning, doing, checking/ acting, planning renewable energy technology well a greener environment.