Analyses and Forecasting of Smart Grid Technological Dynamics

Purpose: this paper analyzes and forecasts medium- to long-term dynamics of Smart Grid technology developments considering both patent activity and socio-economic (demand-side issues and requirements of economy and power system) factors. Methods: for the analysis of Smart Grid patent data (IIP, USPTO, and WIPO patent databases used) we apply syntactic semantic analysis of texts in natural languages and logistic curve-based method. We propose Exactus Patent system for intelligent full-text search and analysis of patents (results verified with Thomson Innovation and TotalPatent patent search systems). For interpretation of revealed dynamics and forecasting of future conditions we identify key long-term socio-economic factors drivers for Smart Grid development. Elements of C. Christensen (disruptive innovations) and G. Dosi (technological trajectories) theories were applied. Results: the study reveals a fast technological transformation within the Smart Grid domain due to the long-term socio-economic factors such as rise of renewables; energy efficiency and energy security issues; environmental constraints and shift of values; requirements for accelerated grid construction (in developing economies) and grid modernization (in developed ones); ongoing economy-wide digitalization. Due to the limited economic effects of Smart Grid roll-outs (considering major requirements of economic agents and society) and considering progressions of patent dynamics, authors forecasts technology stagnation (in terms of number of patents growth) by the end of 2010-s as end of Gartner`s hype development stage. Conclusions and Relevance: a foreseen change in dynamics of Smart Grid technology development is interpreted as a manifestation of sinusoidal fluctuations in technology development for disruptive technologies (supported with OECD data). A longer cycle (in comparison with other disruptive technologies) is interpreted as consequence of technology and industry specifics (capital intensity, long-term R&D, etc.), as well as powerful influence of key socio-economic factors. A new growth period (with less impressive growth pace) and appearance of new generations of technology would become possible in 2020s after development of new business models, monetization schemes and better alignment of Smart Grid technologies and functionality to stakeholders` interests, values and society requirements. This allows authors to correct G. Dosi theory, considering iterative nature of socio-economic corrections of technology trajectories.

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