Smart Cities

17 pages, 4758 KiB

Open AccessArticle

QESIF: A Lightweight Quantum-Enhanced IoT Security Framework for Smart Cities

by Abdul Rehman and Omar Alharbi

Smart Cities 2025, 8(4), 116; https://doi.org/10.3390/smartcities8040116 - 10 Jul 2025

Smart cities necessitate ultra-secure and scalable communication frameworks to manage billions of interconnected IoT devices, particularly in the face of the emerging quantum computing threats. This paper proposes the QESIF, a novel Quantum-Enhanced Secure IoT Framework that integrates Quantum Key Distribution (QKD) with [...] Read more.

Smart cities necessitate ultra-secure and scalable communication frameworks to manage billions of interconnected IoT devices, particularly in the face of the emerging quantum computing threats. This paper proposes the QESIF, a novel Quantum-Enhanced Secure IoT Framework that integrates Quantum Key Distribution (QKD) with classical IoT infrastructures via a hybrid protocol stack and a quantum-aware intrusion detection system (Q-IDS). The QESIF achieves high resilience against eavesdropping by monitoring quantum bit error rate (QBER) and leveraging entropy-weighted key generation. The simulation results, conducted using datasets TON IoT, Edge-IIoTset, and Bot-IoT, demonstrate the effectiveness of the QESIF. The framework records an average QBER of 0.0103 under clean channels and discards over 95% of the compromised keys in adversarial settings. It achieves Attack Detection Rates (ADRs) of 98.1%, 98.7%, and 98.3% across the three datasets, outperforming the baselines by 4–9%. Moreover, the QESIF delivers the lowest average latency of 20.3 ms and the highest throughput of 868 kbit/s in clean scenarios while maintaining energy efficiency with 13.4 mJ per session. Full article

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31 pages, 2849 KiB

Open AccessArticle

A Semantic Link Network Model for Supporting Traceability of Logistics on Blockchain

by Xiaoping Sun, Sirui Zhuge and Hai Zhuge

Smart Cities 2025, 8(4), 115; https://doi.org/10.3390/smartcities8040115 - 9 Jul 2025

Viewed by 40

Abstract

Logistics transports of various resources such as production materials, foods, and products support the operation of smart cities. The ability to trace the states of logistics transports requires an efficient storage and retrieval of the states of logistics transports and locations of logistics [...] Read more.

Logistics transports of various resources such as production materials, foods, and products support the operation of smart cities. The ability to trace the states of logistics transports requires an efficient storage and retrieval of the states of logistics transports and locations of logistics objects. However, the restriction of sharing states and locations of logistics objects across organizations makes it hard to deploy a centralized database for supporting traceability in a cross-organization logistics system. This paper proposes a semantic data model on Blockchain to represent a logistics process based on the Semantic Link Network model, where each semantic link represents a logistics transport of a logistics object between two organizations. A state representation model is designed to represent the states of a logistics transport with semantic links. It enables the locations of logistics objects to be derived from the link states. A mapping from the semantic links into the blockchain transactions is designed to enable the schema of semantic links and the states of semantic links to be published in blockchain transactions. To improve the efficiency of tracing a path of semantic links on a blockchain platform, an algorithm is designed to build shortcuts along the path of semantic links to enable a query on the path of a logistics object to reach the target in logarithmic steps on the blockchain platform. A reward–penalty policy is designed to allow participants to confirm the states of links on the blockchain. Analysis and simulation demonstrate the flexibility, effectiveness, and efficiency of the Semantic Link Network on immutable blockchain for implementing logistics traceability. Full article

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14 pages, 3583 KiB

Open AccessArticle

Novel Machine Learning-Based Smart City Pedestrian Road Crossing Alerts

by Song-Kyoo Kim and I Cheng Chan

Smart Cities 2025, 8(4), 114; https://doi.org/10.3390/smartcities8040114 - 8 Jul 2025

Viewed by 225

Abstract

This paper presents a novel system designed to enhance pedestrian safety in urban environments by utilizing real-time video analysis and machine learning techniques. With a focus on the bustling streets of Macao, known for its high pedestrian traffic and complex road conditions, the [...] Read more.

This paper presents a novel system designed to enhance pedestrian safety in urban environments by utilizing real-time video analysis and machine learning techniques. With a focus on the bustling streets of Macao, known for its high pedestrian traffic and complex road conditions, the proposed model alerts drivers to the presence of pedestrians, significantly reducing the risk of accidents. Leveraging the You Only Look Once algorithm, this research demonstrates how timely alerts can be generated based on risk assessments derived from video footage. The model is rigorously tested against diverse driving scenarios, providing robust accuracy in detecting potential hazards. A comparative analysis of various machine learning algorithms, including Gradient Boosting and Logistic Regression, underscores the effectiveness and reliability of the system. The key finding of this research indicates that dataset refinement and enhanced feature differentiation could lead to improved model performance. Ultimately, this work seeks to contribute to the development of smart city initiatives that prioritize safety through advanced technological solutions. This approach exemplifies a vision for more responsive and responsible urban transport systems. Full article

(This article belongs to the Special Issue Intelligent Control and Planning for Urban Network Efficiency and Safety Optimization)

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50 pages, 1773 KiB

Open AccessReview

Understanding Smart Governance of Sustainable Cities: A Review and Multidimensional Framework

by Abdulaziz I. Almulhim and Tan Yigitcanlar

Smart Cities 2025, 8(4), 113; https://doi.org/10.3390/smartcities8040113 - 8 Jul 2025

Viewed by 154

Abstract

Smart governance—the integration of digital technologies into urban governance—is increasingly recognized as a transformative approach to addressing complex urban challenges such as rapid urbanization, climate change, social inequality, and resource constraints. As a foundational pillar of the smart city paradigm, it enhances decision-making, [...] Read more.

Smart governance—the integration of digital technologies into urban governance—is increasingly recognized as a transformative approach to addressing complex urban challenges such as rapid urbanization, climate change, social inequality, and resource constraints. As a foundational pillar of the smart city paradigm, it enhances decision-making, service delivery, transparency, and civic participation through data-driven tools, digital platforms, and emerging technologies such as AI, IoT, and blockchain. While often positioned as a pathway toward sustainability and inclusivity, existing research on smart governance remains fragmented, particularly regarding its relationship to urban sustainability. This study addresses that gap through a systematic literature review using the PRISMA methodology, synthesizing theoretical models, empirical findings, and diverse case studies. It identifies key enablers—such as digital infrastructure, data governance, citizen engagement, and institutional capacity—and highlights enduring challenges including digital inequity, data security concerns, and institutional inertia. In response to this, the study proposes a multidimensional framework that integrates governance, technology, and sustainability, offering a holistic lens through which to understand and guide urban transformation. This framework underscores the importance of balancing technological innovation with equity, resilience, and inclusivity, providing actionable insights for policymakers and planners navigating the complexities of smart cities and urban development. By aligning smart governance practices with the United Nations’ sustainable development goals (SDG)—particularly SDG 11 on sustainable cities and communities—the study offers a strategic roadmap for fostering resilient, equitable, and digitally empowered urban futures. Full article

(This article belongs to the Collection Smart Governance and Policy)

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26 pages, 8474 KiB

Open AccessArticle

Centralised Smart EV Charging in PV-Powered Parking Lots: A Techno-Economic Analysis

by Mattia Secchi, Jan Martin Zepter and Mattia Marinelli

Smart Cities 2025, 8(4), 112; https://doi.org/10.3390/smartcities8040112 - 4 Jul 2025

Viewed by 389

Abstract

The increased uptake of Electric Vehicles (EVs) requires the installation of charging stations in parking lots, both to facilitate charging while running daily errands and to support EV owners with no access to home charging. Photovoltaic (PV) generation is ideal for powering up [...] Read more.

The increased uptake of Electric Vehicles (EVs) requires the installation of charging stations in parking lots, both to facilitate charging while running daily errands and to support EV owners with no access to home charging. Photovoltaic (PV) generation is ideal for powering up EVs, both for environmental reasons and for the benefit it creates for Charging Point Operators (CPOs). In this paper, we propose a centralised V1G Smart Charging (SC) algorithm for EV parking lots, considering real EV charging dynamics, which minimises both the EV charging costs for their owners and the CPO electricity provision costs or the related CO₂ emissions. We also introduce an innovative SC benefit-splitting algorithm that makes sure SC savings are fairly split between EV owners. Eight scenarios are described, considering costs or emissions minimisation, with and without a PV system. The centralised algorithm is benchmarked against a decentralised one, and tested in an exemplary workplace parking lot in Denmark, that includes includes 12 charging stations and one PV system, owned by the same entity. Reductions of up to 11% in EV charging costs, 67% in electricity provision costs for the CPO, and 8% in CO₂ emissions are achieved by making smart use of a 35 kWp rooftop PV system. Additionally, the SC benefit-splitting algorithm successfully ensures that EV owners save money when adopting SC. Full article

(This article belongs to the Section Energy and ICT)

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33 pages, 2091 KiB

Open AccessReview

Blockchain and Smart Cities: Co-Word Analysis and BERTopic Modeling

by Abderahman Rejeb, Karim Rejeb, Heba F. Zaher and Steve Simske

Smart Cities 2025, 8(4), 111; https://doi.org/10.3390/smartcities8040111 - 1 Jul 2025

Viewed by 443

Abstract

This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic [...] Read more.

This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic and technological evolution of blockchain in urban environments. The co-word analysis reveals blockchain’s foundational role in enabling secure and interoperable infrastructures, particularly through its integration with IoT, edge computing, and smart contracts. These systems underpin critical urban services such as transportation, healthcare, energy trading, and waste management by enhancing data privacy, authentication, and system resilience. The application of BERTopic modeling further uncovers a shift from general technological exploration to more specialized and sector-specific applications. These include real-time mobility systems, decentralized healthcare platforms, peer-to-peer energy exchanges, and blockchain-enabled drone coordination. The results demonstrate that blockchain increasingly supports cross-sectoral innovation, enabling transparency, trust, and circular flows in urban systems. Overall, the current study identifies blockchain as both a technological backbone and an ethical infrastructure for smart cities that supports secure, adaptive, and sustainable urban development. Full article

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25 pages, 2409 KiB

Open AccessArticle

A Study on Imbalances in Urban Internal Spatial Capacity Allocation Based on High-Precision Population and Land Value Distribution Data

by Peiru Wu, Maojun Zhai and Lingzhu Zhang

Smart Cities 2025, 8(4), 110; https://doi.org/10.3390/smartcities8040110 - 1 Jul 2025

Viewed by 326

Abstract

In the context of intelligent and fine-grained urban governance, the coordinated configuration of spatial capacity and locational value has become a key proposition for optimizing urban resource utilization. Using Shanghai as a case study, this paper represents spatial capacity with population density and [...] Read more.

In the context of intelligent and fine-grained urban governance, the coordinated configuration of spatial capacity and locational value has become a key proposition for optimizing urban resource utilization. Using Shanghai as a case study, this paper represents spatial capacity with population density and locational value with land values. By quantifying the degree of spatial mismatch between population density and land values, the study reveals the imbalance between spatial capacity and locational value. First, the research calibrates the population grid data to obtain the population distribution within the study area; subsequently, a composite land value prediction model is constructed to compute the land value distribution across the study region; finally, the spatial mismatch index is calculated using the regression residual method to quantify the degree to which population density deviates from land values. The results indicate that there is a significant spatial mismatch between population density and land values in Shanghai, which unveils an imbalance in the allocation of spatial capacity within the city. This framework can be integrated into smart city digital twins and real-time monitoring platforms, providing 100 m resolution decision support for spatial resource optimization. Full article

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20 pages, 1050 KiB

Open AccessArticle

AI-Driven Sentiment Analysis for Discovering Climate Change Impacts

by Zeinab Shahbazi, Rezvan Jalali and Zahra Shahbazi

Smart Cities 2025, 8(4), 109; https://doi.org/10.3390/smartcities8040109 - 1 Jul 2025

Viewed by 299

Abstract

Climate change presents serious challenges for infrastructure, regional planning, and public awareness. However, effectively understanding and analyzing large-scale climate discussions remains difficult. Traditional methods often struggle to extract meaningful insights from unstructured data sources, such as social media discourse, making it harder to [...] Read more.

Climate change presents serious challenges for infrastructure, regional planning, and public awareness. However, effectively understanding and analyzing large-scale climate discussions remains difficult. Traditional methods often struggle to extract meaningful insights from unstructured data sources, such as social media discourse, making it harder to track climate-related concerns and emerging trends. To address this gap, this study applies Natural Language Processing (NLP) techniques to analyze large volumes of climate-related data. By employing supervised and weak supervision methods, climate data are efficiently labeled to enable targeted analysis of regional- and infrastructure-specific climate impacts. Furthermore, BERT-based Named Entity Recognition (NER) is utilized to identify key climate-related terms, while sentiment analysis of platforms like Twitter provides valuable insights into trends in public opinion. AI-driven visualization tools, including predictive modeling and interactive mapping, are also integrated to enhance the accessibility and usability of the analyzed data. The research findings reveal significant patterns in climate-related discussions, supporting policymakers and planners in making more informed decisions. By combining AI-powered analytics with advanced visualization, the study enhances climate impact assessment and promotes the development of sustainable, resilient infrastructure. Overall, the results demonstrate the strong potential of AI-driven climate analysis to inform policy strategies and raise public awareness. Full article

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31 pages, 3093 KiB

Open AccessReview

A Comprehensive Review of IoT Standards: The Role of IEEE 1451 in Smart Cities and Smart Buildings

by José Rita, José Salvado, Helbert da Rocha and António Espírito-Santo

Smart Cities 2025, 8(4), 108; https://doi.org/10.3390/smartcities8040108 - 30 Jun 2025

Viewed by 452

Abstract

The increasing demand for IoT solutions in smart cities, coupled with the increasing use of sensors and actuators and automation in these environments, has highlighted the need for efficient communication between Internet of Things (IoT) devices. The success of such systems relies on [...] Read more.

The increasing demand for IoT solutions in smart cities, coupled with the increasing use of sensors and actuators and automation in these environments, has highlighted the need for efficient communication between Internet of Things (IoT) devices. The success of such systems relies on interactions between devices that are governed by communication protocols which define how information is exchanged. However, the heterogeneity of sensor networks (wired and wireless) often leads to incompatibility issues, hindering the seamless integration of diverse devices. To address these challenges, standardisation is essential to promote scalability and interoperability across IoT systems. The IEEE 1451 standard provides a solution by defining a common interface that enables plug-and-play integration and enhances flexibility across diverse IoT devices. This standard enables seamless communication between devices from different manufacturers, irrespective of their characteristics, and ensures compatibility via the Transducer Electronic Data Sheet (TEDS) and the Network Capable Application Processor (NCAP). By reducing system costs and promoting adaptability, the standard mitigates the complexities posed by heterogeneity in IoT systems, fostering scalable, interoperable, and cost-effective solutions for IoT systems. The IEEE 1451 standard addresses key barriers to system integration, enabling the full potential of IoT technologies. This paper aims to provide a comprehensive review of the challenges transducer networks face around IoT applications, focused on the context of smart cities. This review underscores the significance and potential of the IEEE 1451 standard in establishing a framework that enables the harmonisation of IoT applications. The primary contribution of this work lies in emphasising the importance of adopting the standards for the development of harmonised and flexible systems. Full article

(This article belongs to the Section Internet of Things)

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26 pages, 4037 KiB

Open AccessArticle

Sustainability Assessment Framework for Urban Transportation Combining System Dynamics Modeling and GIS; A TOD and Parking Policy Approach

by Ahad Farnood, Ursula Eicker, Carmela Cucuzzella, Govind Gopakumar and Sepideh Khorramisarvestani

Smart Cities 2025, 8(4), 107; https://doi.org/10.3390/smartcities8040107 - 30 Jun 2025

Viewed by 324

Abstract

Urban transportation systems face increasing pressure to reduce car dependency and greenhouse gas emissions while supporting sustainable growth. This study addresses the lack of integrated modeling approaches that capture both spatial and temporal dynamics in transport planning. It develops a novel framework combining [...] Read more.

Urban transportation systems face increasing pressure to reduce car dependency and greenhouse gas emissions while supporting sustainable growth. This study addresses the lack of integrated modeling approaches that capture both spatial and temporal dynamics in transport planning. It develops a novel framework combining System Dynamics (SD) and Geographic Information Systems (GIS) to assess the sustainability of Transit-Oriented Development (TOD) strategies and parking policies in two brownfield redevelopment sites in Montreal. The framework embeds spatial metrics, such as proximity to transit, parking availability, and active transportation infrastructure into dynamic feedback loops. Using scenario analysis, the study compares a baseline reflecting current norms with an intervention scenario emphasizing higher density near transit, reduced parking ratios, and improved walkability and bike infrastructure. The results suggest that aligning TOD principles with targeted parking limits and investments in active mobility can substantially reduce car ownership and emissions. While primarily conceptual, the model provides a foundation for location-sensitive, feedback-driven planning tools that support sustainable urban mobility. Full article

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24 pages, 875 KiB

Open AccessReview

Implementing Digital Sovereignty to Accelerate Smarter Mobility Solutions in Local Communities

by Anthony Jnr. Bokolo

Smart Cities 2025, 8(4), 106; https://doi.org/10.3390/smartcities8040106 - 29 Jun 2025

Viewed by 297

Abstract

Achieving a climate neutral economy by 2050 in Europe in line with the European Green Deal places specific responsibility on the transportation sector, which contributes to greenhouse gas (GHG) emissions. For the transportation domain to reduce its GHG emissions, there is need to [...] Read more.

Achieving a climate neutral economy by 2050 in Europe in line with the European Green Deal places specific responsibility on the transportation sector, which contributes to greenhouse gas (GHG) emissions. For the transportation domain to reduce its GHG emissions, there is need to advance urban mobility solutions in local communities via the use of data in all modes of transportation. Accordingly, to intelligently improve mobility solutions, huge amounts of data are needed from citizens in local communities to improve mobility services. However, the access, usage, and ownership of data in the transportation sector continue to be hindered due to issues including privacy, security, and trust concerns, among others. However, to improve smarter mobility solutions, there is a need for clarification of digital sovereignty, which today hinders data flow among different actors in the transportation sector. Therefore, research is needed to provide an approach that enables digital sovereignty while providing innovative mobility services and applications to citizens. Accordingly, this article carried out a systematic review to explore how to maintain digital sovereignty to improve urban mobility services in local communities. Based on grounded theory and a literature review, this study explores the factors that influence digital sovereignty from local communities’ point of view. More importantly, a policy framework is proposed to improve sovereign data usage control for citizens. Additionally, recommendations for achieving digital sovereignty are presented to foster data ecosystem business opportunities for mobility service providers and to increase data autonomy, trust, and transparency for citizens. Full article

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25 pages, 7855 KiB

Open AccessArticle

Latency-Sensitive Wireless Communication in Dynamically Moving Robots for Urban Mobility Applications

by Jakub Krejčí, Marek Babiuch, Jiří Suder, Václav Krys and Zdenko Bobovský

Smart Cities 2025, 8(4), 105; https://doi.org/10.3390/smartcities8040105 - 25 Jun 2025

Viewed by 423

Abstract

Reliable wireless communication is essential for mobile robotic systems operating in dynamic environments, particularly in the context of smart mobility and cloud-integrated urban infrastructures. This article presents an experimental study analyzing the impact of robot motion dynamics on wireless network performance, contributing to [...] Read more.

Reliable wireless communication is essential for mobile robotic systems operating in dynamic environments, particularly in the context of smart mobility and cloud-integrated urban infrastructures. This article presents an experimental study analyzing the impact of robot motion dynamics on wireless network performance, contributing to the broader discussion on data reliability and communication efficiency in intelligent transportation systems. Measurements were conducted using a quadruped robot equipped with an onboard edge computing device, navigating predefined trajectories in a laboratory setting designed to emulate real-world variability. Key wireless parameters, including signal strength (RSSI), latency, and packet loss, were continuously monitored alongside robot kinematic data such as speed, orientation (roll, pitch, yaw), and movement patterns. The results show a significant correlation between dynamic motion—especially high forward velocities and rotational maneuvers—and degradations in network performance. Increased robot speeds and frequent orientation changes were associated with elevated latency and greater packet loss, while static or low-motion periods exhibited more stable communication. These findings highlight critical challenges for real-time data transmission in mobile IoRT (Internet of Robotic Things) systems, and emphasize the role of network-aware robotic behavior, interoperable communication protocols, and edge-to-cloud data integration in ensuring robust wireless performance within smart city environments. Full article

(This article belongs to the Special Issue Smart Mobility: Linking Research, Regulation, Innovation and Practice)

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25 pages, 11137 KiB

Open AccessArticle

Driving Equity: Can Electric Vehicle Carsharing Improve Grocery Access in Underserved Communities? A Case Study of BlueLA

by Ziad Yassine, Elizabeth Deakin, Elliot W. Martin and Susan A. Shaheen

Smart Cities 2025, 8(4), 104; https://doi.org/10.3390/smartcities8040104 - 25 Jun 2025

Viewed by 368

Abstract

Carsharing has long supported trip purposes typically made by private vehicles, with grocery shopping especially benefiting from the carrying capacity of a personal vehicle. BlueLA is a one-way, station-based electric vehicle (EV) carsharing service in Los Angeles aimed at improving access in low-income [...] Read more.

Carsharing has long supported trip purposes typically made by private vehicles, with grocery shopping especially benefiting from the carrying capacity of a personal vehicle. BlueLA is a one-way, station-based electric vehicle (EV) carsharing service in Los Angeles aimed at improving access in low-income neighborhoods. We hypothesize that BlueLA improves grocery access for underserved households by increasing their spatial-temporal reach to diverse grocery store types. We test two hypotheses: (1) accessibility from BlueLA stations to grocery stores varies by store type, traffic conditions, and departure times; and (2) Standard (general population) and Community (low-income) members differ in perceived grocery access and station usage. Using a mixed-methods approach, we integrate walking and driving isochrones, store data (n = 5888), trip activity data (n = 59,112), and survey responses (n = 215). Grocery shopping was a key trip purpose, with 69% of Community and 61% of Standard members reporting this use. Late-night grocery access is mostly limited to convenience stores, while roundtrips to full-service stores range from 55 to 100 min and cost USD 12 to USD 20. Survey data show that 84% of Community and 71% of Standard members reported improved grocery access. The findings highlight the importance of trip timing and the potential for carsharing and retail strategies to improve food access. Full article

(This article belongs to the Special Issue Cost-Effective Transportation Planning for Smart Cities)

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18 pages, 1606 KiB

Open AccessArticle

Comparative Analysis of Traffic Detection Using Deep Learning: A Case Study in Debrecen

by João Porto, Pedro Sampaio, Peter Szemes, Hemerson Pistori and Jozsef Menyhart

Smart Cities 2025, 8(4), 103; https://doi.org/10.3390/smartcities8040103 - 24 Jun 2025

Viewed by 291

Abstract

This study evaluates deep learning models for vehicle detection in urban environments, focusing on the integration of regional data and standardized evaluation protocols. A central contribution is the creation of DebStreet, a novel dataset that captures images from a specific urban setting under [...] Read more.

This study evaluates deep learning models for vehicle detection in urban environments, focusing on the integration of regional data and standardized evaluation protocols. A central contribution is the creation of DebStreet, a novel dataset that captures images from a specific urban setting under varying weather conditions, providing regionally representative information for model development and evaluation. Using DebStreet, four state-of-the-art architectures were assessed: Faster R-CNN, YOLOv8, DETR, and Side-Aware Boundary Localization (SABL). Notably, SABL and YOLOv8 demonstrated superior precision and robustness across diverse scenarios, while DETR showed significant improvements with extended training and increased data volume. Faster R-CNN also proved competitive when carefully optimized. These findings underscore how the combination of regionally representative datasets with consistent evaluation methodologies enables the development of more effective, adaptable, and context-aware vehicle detection systems, contributing valuable insights for advancing intelligent urban mobility solutions. Full article

(This article belongs to the Section Smart Transportation)

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47 pages, 5201 KiB

Open AccessArticle

Mitigation of Voltage Magnitude Profiles Under High-Penetration-Level Fast-Charging Stations Using Optimal Capacitor Placement Integrated with Renewable Energy Resources in Unbalanced Distribution Networks

by Pongsuk Pilalum, Radomboon Taksana, Noppanut Chitgreeyan, Wutthichai Sa-nga-ngam, Supapradit Marsong, Krittidet Buayai, Kaan Kerdchuen, Yuttana Kongjeen and Krischonme Bhumkittipich

Smart Cities 2025, 8(4), 102; https://doi.org/10.3390/smartcities8040102 - 23 Jun 2025

Viewed by 416

Abstract

The rapid adoption of electric vehicles (EVs) and the increasing use of photovoltaic (PV) generation have introduced new operational challenges for unbalanced power distribution systems. These include elevated power losses, voltage imbalances, and adverse environmental impacts. This study proposed a hybrid objective optimization [...] Read more.

The rapid adoption of electric vehicles (EVs) and the increasing use of photovoltaic (PV) generation have introduced new operational challenges for unbalanced power distribution systems. These include elevated power losses, voltage imbalances, and adverse environmental impacts. This study proposed a hybrid objective optimization framework to address these issues by minimizing real and reactive power losses, voltage deviations, voltage imbalance indexes, and CO₂ emissions. Nineteen simulation cases were analyzed under various configurations incorporating EV integration, PV deployment, reactive power compensation, and zonal control strategies. An improved gray wolf optimizer (IGWO) was employed to determine optimal placements and control settings. Among all cases, Case 16 yielded the lowest objective function value, representing the most effective trade-off between technical performance, voltage stability, and sustainability. The optimized configuration significantly improved the voltage balance, reduced system losses, and maintained the average voltage within acceptable limits. Additionally, all optimized scenarios achieved meaningful reductions in CO₂ emissions compared to the base case. The results were validated with an objective function

(F_{b e s t})

as a reliable composite performance index and demonstrated the effectiveness of coordinated zone-based optimization. This approach provides practical insights for future smart grid planning under dynamic, renewable, rich, and EV-dominated operating conditions. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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Smart Cities, Volume 8, Issue 4 (August 2025) – 15 articles

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