近年來，全球面臨能源短缺的重大挑戰，促使各國紛紛投資於再生能源開發。智慧電網技術的發展成為各國關注的焦點，並驅動整體市場價值快速增長。本研究旨在運用量化研究方法，深入探討過去豐富的文獻及技術文件，以了解智慧電網領域議題的發展情況，並進一步研究市場參與者之間的知識流動特性。
本研究利用Web of Science文獻資料庫和Derwent Innovation專利資料庫作為資料來源，涵蓋了2009年至2023年的3,593篇科學文獻和33,024筆專利資料。首先，我們運用主路徑分析方法描繪學術領域的發展軌跡，並透過集群分析方法探索關注的焦點議題。接著，使用LDA主題模型來對專利技術進行分類，並通過專利引用關係構建了專利權人引證網絡、國家引證網絡以及產業引證網絡，從不同維度觀察知識傳遞中的關鍵角色。最後，我們利用上述分析結果取得相關變數，進行迴歸分析，以深入探究影響企業在技術知識網絡中地位的關鍵因素。
研究結果發現，科學文獻的發展可以分為三個階段，隨著時間推移，研究持續朝向應用普及化的方向發展。科學文獻和專利技術的焦點議題大致相符，但學術領域涵蓋更多管理議題和綜合性評估，而專利則反映實際應用情況，因此可相互參照。在技術知識網絡中，企業專利權人主要集中在能源管理、半導體、電子和通訊產業，其中超過半數來自美國。通過迴歸分析發現，跨產業知識向外擴散次數越多，企業在知識網絡中地位越高。此外，佈局無線技術並增加在該領域的專利數量也將對企業產生正向影響。智慧電網是當今熱門議題，然而有關知識流動的研究分析相對較少。本研究以學術和實務專利資料為基礎，旨在協助企業更全面地了解智慧電網知識的發展動態，以及影響知識網絡重要程度的關鍵因素，並為企業未來在智慧電網技術領域的知識管理和策略佈局提供參考依據。

In recent years, the world has grappled with energy shortages, prompting countries to heavily invest in renewable energy. Smart grid technology has emerged as a crucial global concern, fueling rapid market growth. To shed light on this, our study employs quantitative research methods, delving into extensive literature and technical documents. Our goal is to uncover the development trajectory, key focal points, and analyze interactions among participants in this field.
This study utilized the Web of Science and Derwent Innovation databases as data sources, collecting 3,593 scientific literature and 33,024 patents from 2009 to 2023. Firstly, we employed the main path analysis to track smart grid development in academia and used cluster analysis to identify focal issues. Then, through LDA topic modeling, we classified patent technologies and constructed patents citation, nation citation, and industry citation networks to examine brokerage roles in various dimensions. Subsequently, relevant variables from the previous analysis were used for regression analysis, identifying key factors influencing enterprise status in the technical knowledge network.
The findings indicate that the academic field's development can be segmented into three stages, with a current emphasis on universal applications. Popular topics in academia and technology application exhibit general alignment, but the academic domain encompasses more management issues and comprehensive evaluations, while patents reflect practical applications. Concerning the technical knowledge network, a significant portion of patent assignees hails from energy management, semiconductors, electronics, and communication industries, with over half originating from the United States, regression analysis reveals that cross-industry knowledge out diffusion enhances a company’s standing in the knowledge network. Furthermore, deploying wireless technology and increasing the number of patents in this field also yields positive impacts. Smart grid has emerged as a prominent topic in recent times. Despite its significance, there remains a scarcity of studies and reports that specifically delve into the crucial aspect of knowledge flow within this domain. This study is grounded in academic and practical patent data. Through our research, we aim to provide enterprises with a clearer understanding of smart grid knowledge development and the crucial factors that can enhance their impact within knowledge networks. Armed with this knowledge, enterprises can devise effective strategies and implement knowledge management practices to drive future growth.

曾俊嘉. (2020). 中國大陸智慧電網發展現況與趨勢. https://mic.iii.org.tw/aisp/ReportS?docid=CDOC20200520005
經濟部. (2022). 公布「十二項關鍵戰略行動計畫」全面推動淨零轉型目標 https://www.ndc.gov.tw/nc_27_36501
Abdallah, L., & El-Shennawy, T. (2013). Reducing Carbon Dioxide Emissions from Electricity Sector Using Smart Electric Grid Applications. Journal of Engineering, 2013.
Aghajani, G., Shayanfar, H., & Shayeghi, H. (2015). Presenting a Multi-Objective Generation Scheduling Model for Pricing Demand Response Rate in Micro-Grid Energy Management. Energy Conversion and Management, 106, 308-321.
Ahmed, S., Lee, Y., Hyun, S.-H., & Koo, I. (2018). Feature Selection–Based Detection of Covert Cyber Deception Assaults in Smart Grid Communications Networks Using Machine Learning. IEEE Access, 6, 27518-27529.
Avi, G., Cuong, N., Cheyney, O. F., Nelson, H., & David, A. W. (2021). Nist Framework and Roadmap for Smart Grid Interoperability Standards, Release 4.0. In: Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD.
Bader, K. (2013). How to Benefit from Cross-Industry Innovation? A Best Practice Case. International journal of innovation management, 17(06), 1340018.
Bahmani-Firouzi, B., & Azizipanah-Abarghooee, R. (2014). Optimal Sizing of Battery Energy Storage for Micro-Grid Operation Management Using a New Improved Bat Algorithm. International Journal of Electrical Power & Energy Systems, 56, 42-54.
Batagelj, V. (1991). Some Mathematics of Network Analysis. Network Seminar, Department of Sociology, University of Pittsburgh,
Batagelj, V. (2003). Efficient Algorithms for Citation Network Analysis. arXiv preprint cs/0309023.
Bayindir, R., Colak, I., Fulli, G., & Demirtas, K. (2016). Smart Grid Technologies and Applications. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 66, 499-516.
Blei, D. M. (2010). Introduction to Probabilistic Topic Models.
Boari, C., Molina‐Morales, F. X., & Martínez‐Cháfer, L. (2017). Direct and Interactive Effects of Brokerage Roles on Innovation in Clustered Firms. Growth and Change, 48(3), 336-358.
Braeken, A., Kumar, P., & Martin, A. (2018). Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks. Energies, 11(8), Article 2085.
Cavalieri, S., Cantali, G., & Susinna, A. (2022). Integration of Iot Technologies into the Smart Grid. Sensors, 22(7), 2475.
Chao, Y., Donghua, Z., Xuefeng, W., Fujin, Z., & Xiaofan, H. (2017). Technical Topic Analysis in Patents: Sao-Based Lda Modeling. Library and Information Service, 61(3), 86.
Chehri, A., Fofana, I., & Yang, X. (2021). Security Risk Modeling in Smart Grid Critical Infrastructures in the Era of Big Data and Artificial Intelligence. Sustainability, 13(6), 3196.
Chen, C., & Hicks, D. (2004). Tracing Knowledge Diffusion. Scientometrics, 59(2), 199-211.
Cho, R. L., Liu, J. S., & Ho, M. H.-C. (2019). Autonomous Vehicle Technology Development: A Patent Survey Based on Main Path Analysis. 2019 Portland International Conference on Management of Engineering and Technology (PICMET),
De Rassenfosse, G., Jaffe, A., & Raiteri, E. (2019). The Procurement of Innovation by the Us Government. PloS one, 14(8), e0218927.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to Conduct a Bibliometric Analysis: An Overview and Guidelines. Journal of Business Research, 133, 285-296.
Dragičević, T., Siano, P., & Prabaharan, S. S. (2019). Future Generation 5g Wireless Networks for Smart Grid: A Comprehensive Review. Energies, 12(11), 2140.
Ericsson, G. N. (2010). Cyber Security and Power System Communication-Essential Parts of a Smart Grid Infrastructure. IEEE Transactions on Power Delivery, 25(3), 1501-1507.
European, C., Directorate-General for, R., & Innovation. (2006). European Smartgrids Technology Platform : Vision and Strategy for Europe’s Electricity Networks of the Future. Publications Office.
Fadlullah, Z. M., Fouda, M. M., Kato, N., Shen, X. M., & Nozaki, Y. (2011). An Early Warning System against Malicious Activities for Smart Grid Communications. IEEE Network, 25(5), 50-55.
Fan, M., & Zhang, X. (2019). Consortium Blockchain Based Data Aggregation and Regulation Mechanism for Smart Grid. IEEE Access, 7, 35929-35940.
Fouda, M. M., Fadlullah, Z. M., Kato, N., Lu, R. X., & Shen, X. M. (2011). A Lightweight Message Authentication Scheme for Smart Grid Communications. IEEE Transactions on Smart Grid, 2(4), 675-685.
Gould, R. V., & Fernandez, R. M. (1989). Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks. Sociological methodology, 89-126.
Granovetter, M. S. (1973). The Strength of Weak Ties. American journal of sociology, 78(6), 1360-1380.
Grossman, J. H., Reid, P. P., & Morgan, R. P. (2001). Contributions of Academic Research to Industrial Performance in Five Industry Sectors. The Journal of Technology Transfer, 26(1-2), 143-152.
Gunduz, M. Z., & Das, R. (2020). Cyber-Security on Smart Grid: Threats and Potential Solutions. Computer Networks, 169, 107094.
Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2011). Smart Grid Technologies: Communication Technologies and Standards. IEEE Transactions on Industrial Informatics, 7(4), 529-539.
Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2012). A Survey on Smart Grid Potential Applications and Communication Requirements. IEEE Transactions on Industrial Informatics, 9(1), 28-42.
Hui, H., Ding, Y., Shi, Q., Li, F., Song, Y., & Yan, J. (2020). 5g Network-Based Internet of Things for Demand Response in Smart Grid: A Survey on Application Potential. Applied Energy, 257, 113972.
Hummon, N. P., & Dereian, P. (1989). Connectivity in a Citation Network: The Development of DNA Theory. Social Networks, 11(1), 39-63.
IEA. (2022). Smart Grids. IEA. https://www.iea.org/reports/smart-grids
inteGRIDy. (2021). Integridy Project Reaches Its End with the Launch of Innovative Energy Solutions Validated across 10 Pilot Sites https://www.integridy.eu/content/final-press-release-integridy-project-reaches-its-end-launch-innovative-energy-solutions
Jang, S. (2017). Cultural Brokerage and Creative Performance in Multicultural Teams. Organization Science, 28(6), 993-1009. http://www.jstor.org/stable/45149573
Japan for Sustainability. (2010). Four Areas in Japan Begin Own Next-Generation Energy and Social System Projects. Japan for Sustainability. https://www.japanfs.org/en/news/archives/news_id030369.html
Je, S.-M., Woo, H., Choi, J., Jung, S.-H., & Huh, J.-H. (2022). A Research Trend on Anonymous Signature and Authentication Methods for Privacy Invasion Preventability on Smart Grid and Power Plant Environments. Energies, 15(12), 4363.
Jha, I., Sen, S., & Kumar, R. (2014). Smart Grid Development in India—a Case Study. 2014 Eighteenth National Power Systems Conference (NPSC),
Jiang, J., & Qian, Y. (2017). Defense Mechanisms against Data Injection Attacks in Smart Grid Networks. IEEE Communications Magazine, 55(10), 76-82.
Kadushin, C. (2004). Introduction to Social Network Theory. Boston, Ma.
Khan, R., & Khan, S. U. (2017). Design and Implementation of Upnp-Based Energy Gateway for Demand Side Management in Smart Grid. JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 8, 8-21.
Kim, J., & Park, H. I. (2011). Policy Directions for the Smart Grid in Korea. IEEE Power and Energy Magazine, 9(1), 40-49.
Kumar, P., Lin, Y., Bai, G. D., Paverd, A., Dong, J. S., & Martin, A. (2019). Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 21(3), 2886-2927.
Kurt, M. N., Yılmaz, Y., & Wang, X. (2018). Distributed Quickest Detection of Cyber-Attacks in Smart Grid. IEEE Transactions on Information Forensics and Security, 13(8), 2015-2030.
Leten, B., Belderbos, R., & Van Looy, B. (2007). Technological Diversification, Coherence, and Performance of Firms. Journal of Product Innovation Management, 24(6), 567-579.
Li, H., Lin, X., Yang, H., Liang, X., Lu, R., & Shen, X. (2013). Eppdr: An Efficient Privacy-Preserving Demand Response Scheme with Adaptive Key Evolution in Smart Grid. IEEE Transactions on Parallel and Distributed Systems, 25(8), 2053-2064.
Li, H. W., Lu, R. X., Zhou, L., Yang, B., & Shen, X. M. (2014). An Efficient Merkle-Tree-Based Authentication Scheme for Smart Grid. IEEE Systems Journal, 8(2), 655-663.
Li, W. T., Yuen, C., Ul Hassan, N., Tushar, W., Wen, C. K., Wood, K. L., Hu, K., & Liu, X. (2015). Demand Response Management for Residential Smart Grid: From Theory to Practice. IEEE Access, 3, 2431-2440.
Li, X., Liang, X., Lu, R., Shen, X., Lin, X., & Zhu, H. (2012). Securing Smart Grid: Cyber Attacks, Countermeasures, and Challenges. IEEE Communications Magazine, 50(8), 38-45.
Li, Y., & Wang, Y. (2014). State Summation for Detecting False Data Attack on Smart Grid. International Journal of Electrical Power & Energy Systems, 57, 156-163.
Liang, H., Wang, J.-J., Xue, Y., & Cui, X. (2016). It Outsourcing Research from 1992 to 2013: A Literature Review Based on Main Path Analysis. Information & Management, 53(2), 227-251.
Liang, X., Li, X., Lu, R., Lin, X., & Shen, X. (2013). Udp: Usage-Based Dynamic Pricing with Privacy Preservation for Smart Grid. IEEE Transactions on Smart Grid, 4(1), 141-150.
Liu, H., Ning, H. S., Zhang, Y., & Yang, L. T. (2012). Aggregated-Proofs Based Privacy-Preserving Authentication for V2g Networks in the Smart Grid. IEEE Transactions on Smart Grid, 3(4), 1722-1733.
Liu, J. S., Lu, L. Y., & Ho, M. H.-C. (2019). A Few Notes on Main Path Analysis. Scientometrics, 119, 379-391.
Liu, J. S., Lu, L. Y., & Ho, M. H.-C. (2020). A Note on Choosing Traversal Counts in Main Path Analysis. Scientometrics, 124, 783-785.
Liu, J. S., Lu, L. Y. Y., Lu, W.-M., & Lin, B. J. Y. (2013). Data Envelopment Analysis 1978–2010: A Citation-Based Literature Survey. Omega, 41(1), 3-15.
Liu, Y., Yuen, C., Huang, S. S., Ul Hassan, N., Wang, X. M., & Xie, S. L. (2014). Peak-to-Average Ratio Constrained Demand-Side Management with Consumer's Preference in Residential Smart Grid. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 8(6), 1084-1097.
Liu, Y., Yuen, C., Yu, R., Zhang, Y., & Xie, S. L. (2016). Queuing-Based Energy Consumption Management for Heterogeneous Residential Demands in Smart Grid. IEEE Transactions on Smart Grid, 7(3), 1650-1659.
Liwen, F., Huiru, Z., & Sen, G. (2012). An Analysis on the Low-Carbon Benefits of Smart Grid of China. Physics Procedia, 24, 328-336.
Long, Y., Wang, Y., & Pan, C. (2018). Incentive Mechanism of Micro-Grid Project Development. Sustainability, 10(1), 163.
Lu, R. X., Liang, X. H., Li, X., Lin, X. D., & Shen, X. M. (2012). Eppa: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications. IEEE Transactions on Parallel and Distributed Systems, 23(9), 1621-1631.
Luo, S., Du, Y., Liu, P., Xuan, Z., & Wang, Y. (2015). A Study on Coevolutionary Dynamics of Knowledge Diffusion and Social Network Structure. Expert Systems with Applications, 42(7), 3619-3633.
Ma, J., Chen, H. H., Song, L., & Li, Y. (2015). Residential Load Scheduling in Smart Grid: A Cost Efficiency Perspective. IEEE Transactions on Smart Grid, 7(2), 771-784.
MacRoberts, M. H., & MacRoberts, B. R. (1989). Problems of Citation Analysis: A Critical Review. Journal of the American Society for information Science, 40(5), 342-349.
Mansfield, E. (1991). Academic Research and Industrial Innovation. Research Policy, 20(1), 1-12.
Mármol, F. G., Sorge, C., Ugus, O., & Pérez, G. M. (2012). Do Not Snoop My Habits: Preserving Privacy in the Smart Grid. IEEE Communications Magazine, 50(5), 166-172.
McDaniel, P., & McLaughlin, S. (2009). Security and Privacy Challenges in the Smart Grid. IEEE Security & Privacy, 7(3), 75-77.
Mehmood, M. Y., Oad, A., Abrar, M., Munir, H. M., Hasan, S. F., Muqeet, H. A. u., & Golilarz, N. A. (2021). Edge Computing for Iot-Enabled Smart Grid. Security and Communication Networks, 2021, 1-16.
Miller, D. J. (2006). Technological Diversity, Related Diversification, and Firm Performance. Strategic Management Journal, 27(7), 601-619.
Minh, Q. N., Nguyen, V.-H., Quy, V. K., Ngoc, L. A., Chehri, A., & Jeon, G. (2022). Edge Computing for Iot-Enabled Smart Grid: The Future of Energy. Energies, 15(17), 6140.
Mohsenian-Rad, A.-H., Wong, V. W., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010). Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid. IEEE Transactions on Smart Grid, 1(3), 320-331.
Mollah, M. B., Zhao, J., Niyato, D., Lam, K.-Y., Zhang, X., Ghias, A. M., Koh, L. H., & Yang, L. (2020). Blockchain for Future Smart Grid: A Comprehensive Survey. IEEE Internet of Things Journal, 8(1), 18-43.
Motevasel, M., & Seifi, A. R. (2014). Expert Energy Management of a Micro-Grid Considering Wind Energy Uncertainty. Energy Conversion and Management, 83, 58-72.
Muzumdar, A., Modi, C., & Vyjayanthi, C. (2022). Designing a Blockchain-Enabled Privacy-Preserving Energy Theft Detection System for Smart Grid Neighborhood Area Network. Electric Power Systems Research, 207, 107884.
Nawaz, A., Hafeez, G., Khan, I., Jan, K. U., Li, H., Khan, S. A., & Wadud, Z. (2020). An Intelligent Integrated Approach for Efficient Demand Side Management with Forecaster and Advanced Metering Infrastructure Frameworks in Smart Grid. IEEE Access, 8, 132551-132581.
Ozkanli, O., & Akdeve, E. (2006). Cluster and Innovation as Regional Development.
Pearl, M. (2007). Creating a Competitive Edge: The Value of Cross‐Industry Knowledge. Business Strategy Series.
Pinney, J. W., & Westhead, D. R. (2006). Betweenness-Based Decomposition Methods for Social and Biological Networks. Interdisciplinary statistics and bioinformatics, 25, 87-90.
Programme, U. N. E. (2021). Emissions Gap Report 2021. United Nations.
Qing, Z. (2012). The Research on Influence of Industrial Clusters on Regional Economic Development. IERI Procedia, 3, 206-212.
Quintana-García, C., & Benavides-Velasco, C. A. (2008). Innovative Competence, Exploration and Exploitation: The Influence of Technological Diversification. Research Policy, 37(3), 492-507.
Radoglou-Grammatikis, P. I., & Sarigiannidis, P. G. (2019). Securing the Smart Grid: A Comprehensive Compilation of Intrusion Detection and Prevention Systems. IEEE Access, 7, 46595-46620.
Rajagopalan, A., Swaminathan, D., Alharbi, M., Sengan, S., Montoya, O. D., El-Shafai, W., Fouda, M. M., & Aly, M. H. (2022). Modernized Planning of Smart Grid Based on Distributed Power Generations and Energy Storage Systems Using Soft Computing Methods. Energies, 15(23), 8889.
Rhee, Y., Yoon, S., & Park, H. (2022). Exploring Knowledge Trajectories of Accounting Information Systems Using Business Method Patents and Knowledge Persistence-Based Main Path Analysis. Mathematics, 10(18), 3349.
Samadi, P., Mohsenian-Rad, H., Schober, R., & Wong, V. W. (2012). Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design. IEEE Transactions on Smart Grid, 3(3), 1170-1180.
Samadi, P., Mohsenian-Rad, H., Wong, V. W., & Schober, R. (2013). Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid. IEEE Transactions on Smart Grid, 4(2), 1007-1016.
Saxena, N., & Choi, B. J. (2015). State of the Art Authentication, Access Control, and Secure Integration in Smart Grid. Energies, 8(10), 11883-11915.
Saxena, N., Choi, B. J., & Lu, R. X. (2016). Authentication and Authorization Scheme for Various User Roles and Devices in Smart Grid. IEEE Transactions on Information Forensics and Security, 11(5), 907-921.
Serrat, O., & Serrat, O. (2017). Social Network Analysis. Knowledge solutions: Tools, methods, and approaches to drive organizational performance, 39-43.
Shah, G. A., Gungor, V. C., & Akan, O. B. (2013). A Cross-Layer Qos-Aware Communication Framework in Cognitive Radio Sensor Networks for Smart Grid Applications. IEEE Transactions on Industrial Informatics, 9(3), 1477-1485.
Sharma, S., Bhattacharjee, S., & Bhattacharya, A. (2018). Probabilistic Operation Cost Minimization of Micro-Grid. Energy, 148, 1116-1139.
Shaukat, N., Ali, S. M., Mehmood, C. A., Khan, B., Jawad, M., Farid, U., Ullah, Z., Anwar, S. M., & Majid, M. (2018). A Survey on Consumers Empowerment, Communication Technologies, and Renewable Generation Penetration within Smart Grid. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 81, 1453-1475.
Shiau, W.-L., Dwivedi, Y., & Tsai, C.-H. (2015). Supply Chain Management: Exploring the Intellectual Structure. Scientometrics, 105.
Suh, Y., & Jeon, J. (2019). Monitoring Patterns of Open Innovation Using the Patent-Based Brokerage Analysis. Technological Forecasting and Social Change, 146, 595-605.
Tightiz, L., & Yang, H. (2020). A Comprehensive Review on Iot Protocols’ Features in Smart Grid Communication. Energies, 13(11), 2762.
Tightiz, L., Yang, H., & Piran, M. J. (2020). A Survey on Enhanced Smart Micro-Grid Management System with Modern Wireless Technology Contribution. Energies, 13(9), 2258.
U.S. Department of Energy. (2022). Biden-Harris Administration Launches $10.5 Billion Investment to Strengthen America’s Electric Grid. U.S. Department of Energy.
Valente, T. W., & Rogers, E. M. (1995). The Origins and Development of the Diffusion of Innovations Paradigm as an Example of Scientific Growth. Science communication, 16(3), 242-273.
Viswanath, S. K., Yuen, C., Tushar, W., Li, W. T., Wen, C. K., Hu, K., Chen, C., & Liu, X. (2016). System Design of the Internet of Things for Residential Smart Grid. IEEE WIRELESS COMMUNICATIONS, 23(5), 90-98.
Walther, O., & Reitel, B. (2013). Cross-Border Policy Networks in the Basel Region: The Effect of National Borders and Brokerage Roles. Space and polity, 17(2), 217-236.
Wang, Z. W. (2017). An Identity-Based Data Aggregation Protocol for the Smart Grid. IEEE Transactions on Industrial Informatics, 13(5), 2428-2435.
Wood Mackenzie. (2009). The Smart Grid in 2010: Market Segments, Applications and Industry Players. Wood Mackenzie. https://www.woodmac.com/our-expertise/focus/Power--Renewables/smart-grid-in-2010/
Wu, D., & Zhou, C. (2011). Fault-Tolerant and Scalable Key Management for Smart Grid. IEEE Transactions on Smart Grid, 2(2), 375-381.
Yu, D., & Sheng, L. (2020). Knowledge Diffusion Paths of Blockchain Domain: The Main Path Analysis. Scientometrics, 125(1), 471-497.