Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape

Abstract

The distribution and deployment of energy storage systems on a larger scale will be a key element of successfully managing the sustainable energy transition by balancing the power generation capability and load demand. In this context, it is crucial for researchers and policy makers to understand the underlying knowledge structure and key interaction dynamics that could shape the future innovation trajectory. A data-driven approach is used to analyze the evolving characteristics of knowledge dynamics from static, dynamic and future-oriented perspective. To this end, a network analysis was performed to determine the influence of individual knowledge areas. Subsequently, an interaction trend analysis based on emergence indicators was conducted to highlight the promising relations. Finally, the formation of new knowledge interactions is predicted using a link prediction technique. The findings show that ensuring the energy efficiency is a key issue that has persisted over time. In future, knowledge areas related to digital technologies are expected to gain relevance and lead the transformative change. The derived insights can assist R&D managers and policy makers to design more targeted and informed strategic initiatives to foster the adoption of energy storage solutions.

Frontiers of Energy Storage Technologies

“…At present, the relevant research regarding the research frontier of energy storage technology has two main characteristics: on the one hand, the analysis of the frontier research on energy storage technology relies more on expert experience [10][11][12][13][14]; on the other hand, bibliometric-based analysis of the research frontier focuses on specific techniques such as liquid air energy storage [15], thermal energy storage [16][17][18][19], biomass [20], hydrogen energy [21], and lithium-ion batteries [22,23]. In recent years, a limited number of studies have applied bibliometric methods to analyze the frontiers of energy storage technology through either publication or patent data [24][25][26]. However, regarding the development of energy storage technology systems that has occurred over the past decade, research on applying the integrated tool of "bibliographic coupling and sliding window" to frontier identification in the field of energy storage technology is relatively limited.…”

“…Baumann et al [24] analyzed the patent trends of three energy storage technologies and proposed tools and methods for developing exploratory evaluation blueprints in technology fields. Song [26] adopted a data-driven approach to analyze energy storage technology's dynamic knowledge evolution characteristics from static, dynamic, and future-oriented perspectives.…”

Balanced-Scorecard-Based Evaluation of Knowledge-Oriented Competencies of Distributed Energy Investments

“…For distributed energy projects to succeed, investors must have knowledge-oriented competencies [5]. Distributed energy investments are projects that involve complex processes, especially in the current uncertain environment [6].…”

Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption

“…Currently, the capacity of energy storage systems takes an increasing share in the total installed capacity of the energy system. The areas of the application of energy storage systems are extensive today; they can be used in power supply systems of enterprises, systems of filling stations for electric vehicles, as well as system-wide energy storage systems for optimizing renewable energy sources, and an increase in the total capacity of energy storage systems increases their overall efficiency [1]. This is primarily due to the rapid development and integration of renewable energy sources based on solar and wind, which are characterized by an inconsistent power generation.…”