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Artificial Intelligence, Inclusive Innovation, and Living Laboratories: Pathways to Sustainable Community Development

Introduction

Communities serve as the foundation of social, economic, and cultural development. They provide the environment where individuals share common goals and address challenges. Institutions play a crucial role in facilitating solutions through research and public service for these communities in facing complex issues such as environmental sustainability, social inequality, and economic transformation. Institutions, particularly higher education institutions and research organizations, act as catalysts for knowledge generation and innovation that contribute to community development.

In recent decades, the concept of sustainable development has emerged as a guiding framework for addressing present needs while ensuring the well-being of future generations. Sustainable development emphasizes the balanced integration of economic growth, environmental protection, and social inclusion. Achieving these objectives requires innovative approaches capable of responding to rapidly changing societal demands and technological advancements.

Innovation has become a critical driver of sustainable development by enabling new methods, products, and services that address societal challenges more effectively. Traditional innovation models, however, often focus primarily on technological advancement and economic competitiveness. Contemporary perspectives recognize that innovation should also create social value and promote equitable participation among diverse stakeholders. This shift has led to the emergence of inclusive innovation approaches, which seek to ensure that the benefits of innovation are accessible to all sectors of society.

The advancement of Artificial Intelligence (AI) has further transformed the innovation landscape. AI technologies offer unprecedented opportunities to improve decision-making, automate processes, analyze large volumes of data, and develop solutions to complex societal problems. AI has demonstrated potential in supporting sustainable development objectives. Sectors such as education, healthcare, agriculture, governance, and environmental management in its developments are significantly supported by AI. Nevertheless, concerns regarding accessibility, fairness, ethics, and participation highlight the importance of adopting inclusive innovation approaches when implementing AI-driven solutions.

One emerging framework that embodies the principles of inclusive innovation is the Living Laboratory (Living Lab) approach. Living Labs are user-centered, open-innovation ecosystems that facilitate collaboration among community members, researchers, institutions, government agencies, and industry partners. Through real-world experimentation and co-creation processes, Living Labs enable stakeholders to actively participate in the design, development, testing, and evaluation of innovative solutions. This approach promotes knowledge exchange, strengthens community engagement, and enhances the relevance and sustainability of innovation outcomes.

Given the increasing interest in leveraging Artificial Intelligence within inclusive innovation ecosystems, understanding the role of Living Labs in fostering sustainable and community-centered innovation has become an important area of research. Various studies have explored how Living Labs facilitate stakeholder collaboration, support AI-driven innovation, and contribute to sustainable development goals across different contexts and sectors.

To provide an understanding of these developments, this review examines five research articles that investigate the intersection of Artificial Intelligence, inclusive innovation approaches, and Living Laboratory frameworks. The selected studies offer insights into the theoretical foundations, implementation strategies, challenges, and outcomes associated with applying Living Lab principles to support sustainable and inclusive innovation. Through the analysis of these articles, this review seeks to identify emerging themes, best practices, and research gaps that may inform future initiatives and scholarly investigations in this evolving field.

Application of artificial intelligence in a digital platform for sustainability in the floating community in the Amazon Brazil

This study presents a model that integrates artificial intelligence (AI) to promote the sustainability of the floating community of Lake Catalão in the Amazon region of Brazil. Three significant factors are combined to understand and address critical challenges in the lake community. The study applies a mixed-methods approach to mapping various socio-environmental aspects and infrastructure. Nine AI-based prototype projects were developed for water quality monitoring, waste management, and environmental education. The development of these tools, in collaboration with the community, was a result of the study to ensure contextual relevance and social inclusion. The study also recommends enhancing public policies in areas such as contextualized education, basic infrastructure, the local economy, participatory governance, and technological innovation.

The WELL-E Approach to Data-Driven Inclusive Innovation: Working with and for the Canadian Dairy Industry

WELL-E is a digital living laboratory (Living Lab) co-created by two research facilities in Australia, which aims to involve real stakeholders to address their needs and create a positive impact on both society and the environment. The collaborative effort provides inclusive innovation through the integration of new knowledge and technologies into the dairy industry. This directly affects the target industry while ensuring consistent feedback that supports improvements in welfare development, sustainability, and reinforces the importance of stakeholder participation. The findings recommend exploring new ways of handling and analyzing data that could pave the way for new discoveries.

A Botanic Garden As A Potential Social Leader In Education For Sustainable Development Through Computer-Mediated Communication

The study emphasizes the importance of botanical gardens, as humans experience a disconnect with the natural environment. It proposes computer-mediated communication (CMC) to expand knowledge sharing and encourage pro-sustainability actions in communities. A mixed-methods study was conducted in a botanical garden inside a university in the UK. The results show that staff and volunteers are encouraged to increase the use of CMC tools to enhance community engagement and information dissemination. Dependency on an institution is also identified as a challenge, as it is constrained by its regulations and organizational structures. The study recommends broadening the scope of the research and increasing linkages to provide greater visibility to the community.

A Living Lab Model for Elementary Informatics Education: Enhancing Sustainability Competencies Through Collaborative Problem-Solving, Computational Thinking, and Communication

The study introduces living lab-based collaborative approaches in various educational models amid ongoing rapid digital transformation. Students are encouraged to embrace these developments to equip themselves to address real-world problems. According to the findings, these living lab-based educational models are effective contributors to building sustainable and interconnected futures. The collaborative problem-solving and computational thinking skills of students are greatly enhanced through the use of these living labs that engage with real-life problems. The study suggests that future research should explore longitudinal effects, cross-contextual adaptability, and technological integration to continually enhance instructional effectiveness.

The Twin Transition in Higher Education: Bibliometric Insights Into Digital and Green Convergence

This study explores the convergence of digitalization and sustainability within higher education. The study employs a bibliometric analysis of a significant number of publications indexed in the Web of Science from 2006 to 2025 to map research trends, conceptual clusters, and collaboration networks. The findings reveal six interconnected domains that collectively support the development of a sustainable digital university ecosystem.

Conclusion

The five research articles explore different fields while introducing and applying the concept of the living laboratory. Collectively, these studies make significant contributions to the existing body of knowledge. The articles also demonstrate that direct collaboration among diverse stakeholders across various fields is a key factor in the success of the solutions developed to address identified challenges. Furthermore, the findings highlight that inclusive innovation and the continuous development of educational initiatives can foster more sustainable development.

References

Machado, A. L. S., & Marreiros, M. G. (2026). Application of artificial intelligence in a digital platform for sustainability in the floating community in the Amazon Brazil. Discover Sustainability, 7(1). https://doi.org/10.1007/s43621-026-02847-0

Vasseur, E., Hambly, H., Roche, S., & Diallo, A. B. (2026). The WELL-E Approach to Data-Driven Inclusive Innovation: Working with and for the Canadian Dairy Industry. Canadian Agri-food & Rural Advisory Extension and Education Journal, 1(1). https://doi.org/10.21083/caree.v1i1.8971

Beresford-Dey, M., Cooper, A., Crabb, M., Herd, K., & Syme-Smith, L. (2024). A botanic garden as a potential social leader in education for sustainable development through computer-mediated communication. The Living Lab, 1(1). https://doi.org/10.20933/40000106

Son, J., & Kim, S. (2025). A living lab model for Elementary Informatics education: Enhancing sustainability competencies through Collaborative Problem-Solving, Computational Thinking, and communication. Sustainability, 17(13), 5811. https://doi.org/10.3390/su17135811

Bulut, A., & Haçat, S. O. (2026). The Twin Transition in Higher Education: Bibliometric Insights into digital and green convergence. European Journal of Education, 61(1). https://doi.org/10.1111/ejed.70526

From Industrial Decline to Sustainable Renewal: Transforming Post-Industrial Landscapes for the Future

The continuous advancement of technology has significantly transformed human societies, economies, and the physical environment. Industrialization has contributed to economic growth and urban development across the world. However, these developments have also reshaped landscapes in regions dominated by mining, industry, and energy production. The decline of industrial and mining activities often leaves behind abandoned sites, degraded landscapes, and environmental problems.

The transformation of industrial and mining landscapes is often viewed by governments primarily from an economic perspective rather than through social and environmental considerations. Many former mines, coal-fired power plants, factories, and industrial complexes occupy strategically important areas that can be repurposed to generate social, economic, and environmental benefits. Governments play an essential role in guiding the redevelopment of these post-industrial sites through environmental rehabilitation and adaptive reuse strategies. Such initiatives seek to reduce environmental risks, stimulate local economies, preserve industrial heritage, and improve land-use efficiency while minimizing the need for additional resource extraction.

Local communities also play a significant role in shaping the future of post-industrial landscapes. While many residents associate former industrial sites with environmental degradation and economic decline, others view them as valuable cultural assets. Community participation has therefore become an essential component of redevelopment efforts, helping address local needs and generate social value. Through stakeholder engagement, abandoned industrial areas can be transformed into recreational parks, tourism destinations, educational centers, and heritage sites that enhance community well-being and strengthen regional identity.

These redevelopment initiatives are closely aligned with sustainability goals and the principles of the circular economy. Instead of treating abandoned industrial sites as liabilities, they can serve as a foundation for a circular economy through infrastructure reuse and land regeneration. By converting degraded landscapes into productive assets, governments and communities can reduce environmental impacts while creating new economic opportunities. Such efforts contribute to sustainable urban development and promote responsible consumption and production practices.

The rehabilitation of post-industrial landscapes also supports the objectives of the United Nations Sustainable Development Goals (SDGs), particularly SDG 15: Life on Land. SDG 15 emphasizes the protection, restoration, and sustainable use of terrestrial ecosystems, the reduction of land degradation, and the promotion of biodiversity conservation. Restoring abandoned mines and industrial sites can improve ecosystem functions, enhance biodiversity, and create green spaces that benefit both people and the environment. Consequently, post-industrial landscape transformation has emerged as an important strategy for achieving environmental sustainability and fostering resilient communities.

To better understand the current state of knowledge in this field, this review presents five selected studies that highlight different perspectives and applications of post-industrial landscape transformation. Together, these papers demonstrate the potential of converting neglected industrial and mining areas into urban parks, heritage destinations, ecological reserves, and other multifunctional spaces that contribute to environmental sustainability and community development.

Recycling Energy Landscapes as Britain’s Coal Plants Close: What Are the Directions, Drivers and Justice Implications of Site Re-use?
Richard Cowell and Martin J. Pasqualetti

The study applies an assemblage-thinking approach to examine post-closure processes at phased-out coal-fired power station sites. This approach helps explain the dynamics and justice implications of energy transitions. The researchers utilize media reports, planning documents, and interviews to analyze factors influencing the future of these sites. The findings reveal several constraints affecting redevelopment, particularly the tendency to overlook existing heritage, ecological, and social values. The study suggests that these factors should be carefully assessed, as facility closures can trigger significant rescaling of energy assemblages and create challenges for future site redevelopment.

Decision-Making Processes for Parkification: Developing an Evaluation Framework Through the Transformation of Post-Industrial Sites into Urban Parks
Kawthar M. Alrayyan

Parkification is a development framework introduced in this study to provide a viable process for transforming post-industrial sites into urban parks. The research employs a mixed-methods approach involving document analysis, site visits, and interviews to develop and evaluate the parkification framework. The framework identifies three distinct trajectories that reflect the interactions of both formal and informal actors in redevelopment processes. This research contributes a new framework for analyzing urban regeneration and the transformation of industrial sites into sustainable urban environments.

From Extraction to Engagement: Post-Mining Transition and Science Communication in Lousal, Portugal
Mounir Sabeh Affaki

This paper highlights the importance of heritage preservation, social participation, and environmental accountability in post-mining transitions. To examine these dynamics, the study employs a combination of qualitative methods, including documentary analysis, site visits, and interviews, to assess post-closure activities at mining sites. The findings reveal a narrative asymmetry in which two contrasting perspectives emerge. The exhibits emphasize the technological progress and innovations associated with the mining industry, while socio-environmental consequences and post-extractive futures are communicated primarily through incidental verbal narratives. As a result, the latter perspective receives less attention than the former, limiting efforts to promote environmental stewardship. The study therefore emphasizes the need for curated narratives that incorporate critical public perspectives to support a just and green transition.

Opportunities for Australia’s Regional Development: Lessons from the Integrated Rehabilitation of Co-located Coal Mines and Power Plants in Europe
Yuliang Jiang, Elisa Palazzo, and Simit Raval

The transition to green energy is accelerating the decommissioning of coal mines and coal-fired power plants; however, the sustainable rehabilitation of these sites remains uncertain. Addressing this gap, the study examines European coal mines and power plants using an evaluation framework to analyze rehabilitation practices and future redevelopment plans. The results reveal five cross-case lessons derived from commonly observed deficiencies. The study also proposes five context-specific recommendations aimed at addressing these shortcomings and improving future rehabilitation outcomes.

Opportunities for Social Sustainability Through Local Governance of Mine and Quarry Restoration (Focus on Restoration End-Uses)
Grace N. Tully et al.

This study focuses on the social dimensions of mining and quarrying industry life cycles. The researchers analyze planning documents from local governments and conduct interviews with government officials to identify governmental influences on restoration processes and long-term site outcomes. The findings indicate that governments are well positioned to guide site restoration and determine how local communities can benefit from redevelopment initiatives. However, the paper also highlights shortcomings in existing regulatory frameworks and limitations in the resources available to support restoration efforts effectively.

Conclusion

The transition and environmental remediation of former industrial and mining sites remain complex and insufficiently understood. The five studies reviewed demonstrate several common factors that influence the success of restoration and redevelopment efforts. Government involvement, community participation, and the prospects of the circular economy emerge as recurring themes across the literature. Environmental awareness and sustainability considerations are likewise emphasized throughout the studies. These findings suggest that further research is needed to better understand the scope, complexity, and long-term implications of post-industrial landscape transformation for sustainable development.

References

Cowell, R., & Pasqualetti, M. J. (2026). Recycling energy landscapes as Britain’s coal plants close: What are the directions, drivers and justice implications of site re-use? Energy Research & Social Science, 134, 104635. https://doi.org/10.1016/j.erss.2026.104635

Alrayyan, K. M. (2025). Decision-making processes for parkification: Developing an evaluation framework through the transformation of post-industrial sites into urban parks. Cities, 169, 106601. https://doi.org/10.1016/j.cities.2025.106601

Affaki, M. S. (2026). From extraction to engagement: Post-mining transition and science communication in Lousal, Portugal. The Extractive Industries and Society, 27, 101930. https://doi.org/10.1016/j.exis.2026.101930

Jiang, Y., Palazzo, E., & Raval, S. (2025). Opportunities for Australia’s regional development: Lessons from the integrated rehabilitation of co-located coal mines and power plants in Europe. Landscape and Urban Planning, 268, 105564. https://doi.org/10.1016/j.landurbplan.2025.105564

Tully, G. N., Holt, O., Yellishetty, M., Farrelly, M. A., Whittle, D., & Bach, P. M. (2025). Opportunities for social sustainability through local governance of mine and quarry restoration. The Extractive Industries and Society, 25, 101797. https://doi.org/10.1016/j.exis.2025.101797

Is Industry 5.0 Really the Next Industrial Revolution? Insights from Five Recent Studies

The history of industrial development has been marked by a series of technological revolutions that have transformed production systems, economic activities, and social structures. The First Industrial Revolution introduced mechanized production through water and steam power, replacing many manual manufacturing processes. The Second Industrial Revolution expanded industrial capabilities through the adaptation of electricity, mass production, and assembly-line manufacturing. The Third Industrial Revolution, often referred to as the Digital Revolution, integrated electronics, computers, and automation into industrial operations. More recently, Industry 4.0 emerged as the fourth stage of industrial transformation, characterized by the convergence of digital technologies and intelligent systems within production environments.

Industry 4.0 refers to the integration of cyber-physical systems, the Internet of Things (IoT), artificial intelligence (AI), cloud computing, big data analytics, and advanced automation into industrial processes. These technologies enable real-time monitoring, autonomous decision-making, and seamless communication among machines within industrial systems. By creating highly connected and data-driven manufacturing environments, Industry 4.0 has significantly enhanced operational efficiency, productivity, flexibility, and product customization across various industries.

The advancements associated with Industry 4.0 have accelerated innovation in both manufacturing and service industries. Digital twins, machine learning applications, and smart factories have improved resource utilization and production efficiency. Organizations have leveraged these technologies to enhance operational performance and competitiveness. Furthermore, the increasing availability of digital infrastructure has facilitated greater collaboration among stakeholders within industrial ecosystems.

Despite its numerous benefits, Industry 4.0 has also generated significant challenges for society and industry. The extensive reliance on automation and intelligent technologies has raised concerns regarding workforce adaptation, cybersecurity, data privacy, and digital governance. Additionally, critics argue that the technology-centered approach of Industry 4.0 may overlook broader human and sustainability considerations that are essential for sustainable development.

These concerns have contributed to the emergence of Industry 5.0, a new industrial paradigm that seeks to complement technological advancement with human-centered values. Industry 5.0 emphasizes collaboration between humans and intelligent machines while promoting societal well-being. Such interactions contribute to improved productivity and economic growth. Rather than focusing solely on efficiency and automation, Industry 5.0 recognizes the importance of human-centered innovation, resilience, and sustainability. This shift reflects a growing recognition that future industrial systems must balance technological progress with social and environmental objectives.

Given the increasing attention toward Industry 5.0, a growing body of research has explored its principles, applications, opportunities, and challenges across various industrial contexts. To contribute to this discussion, this article reviews and analyzes five recent research articles on Industry 5.0.These studies examine the characteristics, technological advancements, and implementation challenges associated with Industry 5.0. Collectively, the reviewed articles provide a comprehensive perspective on the current state of Industry 5.0 research and its potential role in shaping the future of industry.

Fostering well-being in Industry 5.0 through managerial behaviours and enabling technologies

The study explores specific managerial behaviors and technologies that effectively support the new objectives during the transition to Industry 5.0. A systematic literature review and thematic analysis were conducted to identify well-being-centered managerial behaviors and their enabling technologies that facilitate the transition. The study reveals that human well-being is a driver of productivity, which leads to sustainable competitiveness. The study conceptualizes technology as a consequence of human-centered design. The study also recommends examining the broader societal context down to finer details, including society, managerial behavior in companies, and current human experiences.

Identifying harmony between industrial engineering and environmental sustainability in South Africa

The study focuses on the relationship between industrial engineering (IE) and environmental sustainability (ES). Due to its sporadic literature showing a limited consensus, the study bridges the gap between IE and ES for sustainable comparative advantage (SCA). The study conducted an interview where thematic analysis was performed after the collection of data. The results show that both IE and ES complement each other in knowledge domains. This indicates synergy between IE and ES which can create transdisciplinary knowledge for SCA. Further study on the literature domains and transdisciplinary knowledge in the context of societal challenges.

Industry 5.0 technologies to enable innovation in the era of twin transition: A case study on the nexus between SMEs and regulators

The study examines the role of regulators and their expectations regarding the transition to Industry 5.0. Although previous research has recognized the influence of regulators, limited attention has been given to resource-constrained small and medium enterprises (SMEs). An exploratory mixed-method approach was applied using a qualitative case study of an SME that is currently integrating Industry 5.0-enabling technologies. The results show that regulatory factors, such as human values, social acceptance, and ethical principles, influence the organizational adoption of Industry 5.0 technologies. The findings provide preliminary insights into the role of regulators and offer practical implications for supporting the twin transition of resource-constrained organizations.

Industry 5.0 through the lens of ergonomics and sustainability: Mapping the territory

The study investigates the paradigm shift from techno-centric to human-centric systems in support of resilience and sustainability. Using a systematic literature review and bibliometric analysis, the study examines the interrelationships among ergonomics, sustainability, and Industry 5.0. The findings reveal a fragmented body of literature with limited integration of ergonomics and sustainability within the Industry 5.0 framework.

Industry 5.0: revolution or repackaging? unveiling the ambiguities of the new industrial era

The study critically examines the current state of knowledge on Industry 5.0 and the ambiguities that persist in the literature from a socio-technical perspective. Using a bibliometric systematic review framework, the authors conduct a systematic, critical, and reflective analysis of the concept. The findings highlight important nuances in the key elements of Industry 5.0 and question whether it constitutes a distinct industrial revolution. The study argues that, compared with previous industrial revolutions, Industry 5.0 lacks the transformative characteristics necessary to justify such a classification. It further proposes a framework that situates the core elements of Industry 5.0 within the context of Industry 4.0 and outlines a research agenda for future investigations.

Conclusion

The reviewed studies suggest that Industry 5.0 has emerged as a prominent theme in contemporary industrial research. However, the current body of evidence remains insufficient to fully substantiate its claimed contributions and justify its recognition as a distinct industrial revolution. While researchers from various disciplines have increasingly incorporated Industry 5.0 principles into their work, the concept continues to exhibit substantial overlap with Industry 4.0. This disconnect between conceptual aspirations and empirical evidence highlights the need for further research to clarify the role, significance, and practical implications of Industry 5.0 across different disciplinary contexts.

References

Piccarozzi, M., Caboni, F., & Bruni, R. (2026). Fostering well-being in Industry 5.0 through managerial behaviours and enabling technologies. Technological Forecasting and Social Change, 226, 124600. https://doi.org/10.1016/j.techfore.2026.124600

Roopa, M., & Siriram, R. (2026). Identifying harmony between industrial engineering and environmental sustainability in South Africa. Sustainable Futures, 11, 101695. https://doi.org/10.1016/j.sftr.2026.101695

Cerchione, R., Petruzzelli, A. M., Papa, A., & Sicardi, V. (2026). Industry 5.0 technologies to enable innovation in the era of twin transition: A case study on the nexus between SMEs and regulators. Technological Forecasting and Social Change, 230, 124761. https://doi.org/10.1016/j.techfore.2026.124761

Arshi, T., Rawal, P., Virmani, N., Lahri, V., & Jagtap, S. (2026). Industry 5.0 through the lens of ergonomics and sustainability: Mapping the territory. Sustainable Futures, 11, 101805. https://doi.org/10.1016/j.sftr.2026.101805

Sott, M. K. (2026). Industry 5.0: revolution or repackaging? unveiling the ambiguities of the new industrial era. Sustainable Futures, 11, 101699. https://doi.org/10.1016/j.sftr.2026.101699

Advancements in Electrical Power Grid Development: A Review of Five Key Studies on Vulnerability, Fault Detection, and Renewable Integration

Electricity is an important commodity in modern society. All modern households, commercial industries and critical infrastructure requires electrical energy supply to function effectively. As a result, electricity has become an essential resource for economic growth, technological development and social progress.

Delivering electrical energy to consumers requires complex infrastructure and systematic processes. Electricity is produced in distant generating power plants using various energy sources. From power plants, it is transmitted through high-voltage transmission lines although dangerous the power transfer efficiency is significant. It is then reduced to lower voltage and distributed to the consumers. The interconnected structure that enables this entire process is known as the electrical power grid.

The electrical power grid is considered one of the most sophisticated engineering systems ever developed. It consists of numerous devices, facilities and plants including a central command that controls and monitors the system. These components must operate together in a coordinated manner to ensure reliable electricity delivery. Over the years, significant improvements have been introduced in power system design, operation, protection, and control. These advancements have contributed to higher reliability, improved efficiency, and greater system stability. Nevertheless, the power grid continues to face new challenges as electrical demand increases and system requirements become more complex.

The growing consumption of electricity has created a need for further improvements in power system operation and planning. At the same time, modern power systems are integrating larger amounts of renewable energy resources. These developments introduce additional operational uncertainties and technical challenges. Engineers must therefore develop more precise methods for monitoring, controlling, and optimizing power system performance. Continuous improvement is necessary to maintain reliability and support future energy requirements.

Despite the need for innovation, testing new strategies directly on actual power systems can be difficult and potentially dangerous. Electrical grids operate under strict reliability and safety requirements. Any unsuccessful modification may lead to equipment damage, power interruptions, financial losses, or safety hazards. Furthermore, conducting large-scale experiments on operational power systems can be expensive and time-consuming. These limitations make it impractical to evaluate every proposed improvement through direct implementation. Consequently, researchers and engineers often rely on simulation techniques to investigate system behavior and assess the feasibility of new approaches.

Simulation has become an essential tool in modern power system research. It provides a controlled environment in which different operating conditions can be studied without affecting real-world infrastructure. Researchers can analyze system performance, evaluate control strategies, investigate fault conditions, and predict system responses under various scenarios. The continuous advancement of computational capacity has significantly enhanced the capabilities of simulation tools. Modern computers can process large datasets and perform complex calculations with high speed and accuracy. These capabilities allow researchers to construct detailed mathematical models that closely represent empirical system behavior. The success of simulation-based research has also been supported by the availability of standardized test systems and modeling frameworks. Many of these resources are documented in publications and repositories in the Institute of Electrical and Electronics Engineers (IEEE). Such resources provide researchers with reliable platforms for validating methodologies and comparing results across different studies. Thus, simulation has become a widely accepted approach for evaluating proposed solutions before their potential implementation in real-world power systems.

This reviews five research studies that focus on the development and assessment of different techniques for improving power system performance. The selected studies explore various modeling approaches, optimization methods, and combinations of analytical techniques. Each proposed method is evaluated through simulation-based analysis. Mathematical formulations are used to establish theoretical foundations, while statistical measures are employed to assess performance and effectiveness. Through a comparative examination of these studies, this paper seeks to determine the level of success achieved by the proposed models. The findings may provide valuable insights into current developments in power system research and contribute to a better understanding of emerging approaches for electrical grid improvement.

A Boundary-Compensated Partition-Based Parallel Graph Neural Network for Weak-Bus Identification in Interconnected Power Grids

The study highlights the limitations of two methods, namely conventional full-graph neural networks for large-scale power grids and direct graph partitioning techniques used for identifying weak buses in the system. Boundary regions that are not covered by the model may become vulnerable, and their susceptibility may remain undetected. To address this limitation, the paper proposes a boundary-compensated partition-based parallel graph neural network framework for the identification of weak buses. The IEEE 57-bus benchmark, together with mechanism-based node and branch vulnerability labels, was used to evaluate the proposed method. The analytical framework successfully captures weak buses within the power system. Furthermore, local aggregation, boundary transmission, and corridor-driven vulnerability propagation were identified as key indicators of weak buses. However, the study limits its validation to a medium-scale benchmark rather than demonstrating scalability across large-scale power systems.

A Novel Hybrid Platform Based on Deep Learning for Fault Detection and Localization in a Smart Distribution Grid

Rapid and accurate fault detection and localization are essential for ensuring the reliability of smart transmission systems. Traveling-wave (TW) methods provide high fault-location accuracy under strict operating conditions, whereas data-driven models are generally more robust but often exhibit lower precision. The paper proposes a unified and modular framework that integrates the TW analytical method with a one-dimensional convolutional neural network (1D-CNN) model, allowing the strengths of both approaches to complement each other. The key contribution of this study is an adaptive decision strategy that combines the outputs of the TW method and the 1D-CNN model to generate a more accurate and reliable fault-location estimate. The framework’s performance is systematically evaluated using standard detection and localization metrics. The hybrid methodology enhances both accuracy and robustness, demonstrating its potential as a solution for advanced monitoring and protection in modern power grids.

Data-Driven Physics-Informed LSTM for Voltage Regulation in Active Distribution Networks

The integration of renewable energy sources, particularly photovoltaic (PV) generation, into the power grid creates challenges in voltage regulation due to the distributed nature of these energy sources. Several control methods have been developed, but each has its own limitations. Droop control operates locally, central optimal power flow requires full network observability and control, and multi-agent deep reinforcement learning (MADRL) methods involve long training times and significant algorithmic complexity. The paper proposes the Optimal Historical Selection and Forecasting (OHSF) scheme, which combines a physics-informed long short-term memory (LSTM) network with an online sensitivity-based correction loop for medium-voltage active distribution networks. The results demonstrate reduced average voltage deviations across all PV buses in simulations of modified IEEE 33-bus and 69-bus test systems, while also achieving significantly shorter training times.

MISSA-BPNN-Based Surrogate Model for Wind-Induced Stress Prediction in Vulnerable Regions of Transmission Towers

Stress monitoring of transmission towers under strong wind conditions remains challenging. Conventional contact-based sensors are complex to install, difficult to maintain, and prone to damage. Recent advances in non-contact displacement measurement technologies, such as laser measurement and machine vision, have created new opportunities for structural monitoring. The paper proposes a wind-induced stress surrogate model based on a Multi-Strategy Improved Sparrow Search Algorithm and a Backpropagation Neural Network (MISSA-BPNN) to identify structurally vulnerable regions of transmission towers. The results demonstrate the successful identification of vulnerable regions in the transmission towers analyzed. This method provides a new approach for monitoring transmission line infrastructure.

Short circuit current limitation using series reactors in 20 kV distribution feeder

Short-circuit faults produce extremely high fault currents that can cause significant damage to electrical equipment. These faults can be severe and may significantly reduce system reliability. One method of limiting fault-related damage is the installation of a series reactor, also known as a current-limiting reactor (CLR). The study uses ETAP simulation software based on IEC 60909 standards to evaluate the effects of four types of short-circuit faults: three-phase faults, single-line-to-ground faults, line-to-line faults, and double-line-to-ground faults. The results confirm that series reactors can significantly reduce fault currents, thereby minimizing potential damage to electrical equipment.

Conclusion

The five recently published research articles focus on different aspects of the power grid. The first article focuses on system vulnerability, the second presents a new fault-detection method, the third addresses voltage regulation challenges associated with renewable energy integration, the fourth examines the structural assessment of transmission towers, and the fifth discusses the protection of power equipment and transmission lines against faults and their rapid recovery. Collectively, these studies complement one another and contribute to the development of a more robust and stable power grid.

References

Qin, J., Zhang, Z., Li, F., Xue, Y., Si, Y., & Su, L. (2026). A Boundary-Compensated Partition-Based parallel graph neural network for Weak-Bus identification in interconnected power grids. Energies, 19(11), 2630. https://doi.org/10.3390/en19112630

Souhe, F. G. Y., Ekemb, G., Mbey, C. F., Kakeu, V. J. F., & Boum, A. T. (2026). A novel hybrid platform based on deep learning for fault detection and localization in a smart distribution grid. Journal of Electrical and Computer Engineering, 2026(1). https://doi.org/10.1155/jece/8886698

Hein, H., Yu, H., Yu, L., & Deng, Z. (2026). Data-Driven Physics-Informed LSTM for voltage regulation in active distribution networks. Energies, 19(11), 2609. https://doi.org/10.3390/en19112609

Wang, F., Zhang, T., Tang, Y., & Liu, Y. (2026). MISSA-BPNN-Based Surrogate Model for Wind-Induced Stress Prediction in Vulnerable Regions of Transmission towers. Processes, 14(11), 1785. https://doi.org/10.3390/pr14111785

Siregar, R. H., Farras, A., & Syahrizal, S. (2026). Short circuit current limitation using series reactors in 20 kV distribution feeder. Journal Geuthee of Engineering and Energy (JOGE), 5(1), 62–74. https://doi.org/10.52626/joge.v5i1.94