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Akbari E, Faraji Naghibi A, Veisi M, Shahparnia A, Pirouzi S. Multi-objective economic operation of smart distribution network with renewable-flexible virtual power plants considering voltage security index. Sci Rep 2024; 14:19136. [PMID: 39160297 PMCID: PMC11333721 DOI: 10.1038/s41598-024-70095-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 08/13/2024] [Indexed: 08/21/2024] Open
Abstract
This paper discusses the simultaneous management of active and reactive power of a flexible renewable energy-based virtual power plant placed in a smart distribution system, based on the economic, operational, and voltage security objectives of the distribution system operator. The formulated problem aims to specify the minimum weighted sum of energy cost, energy loss, and voltage security index, considering the optimal power flow model, voltage security formulation, and the operating model of the virtual power plant. The virtual unit includes renewable sources, like wind systems, photovoltaic, and bio-waste units. Flexibility resources include electric vehicle parking lot and price-based demand response. In the mentioned scheme, parameters of load, renewable sources, electric vehicles, and energy prices are uncertain. This paper utilizes the Unscented Transformation method for modeling uncertainties. Fuzzy decision-making is utilized to extract a compromised solution. The suggested approach innovatively considers the simultaneous management of active and reactive power of a virtual unit with electric vehicles and price-based demand response. This is performed to promote economic, operational, and network security objectives. According to numerical results, the approach with optimal power management of renewable virtual units is capable of boosting the economic, operation, and voltage security status of the network by approximately 43%, 47-62%, and 26.9%, respectively, to power flow studies. Only price-based demand response can improve the voltage security, operation, and economic states of the network by about 19.5%, 35-47%, and 44%, respectively, compared to the power flow model.
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Affiliation(s)
- Ehsan Akbari
- Department of Electrical Engineering, Mazandaran University of Science and Technology, Babol, Iran
| | - Ahad Faraji Naghibi
- Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
| | - Mehdi Veisi
- Department of Electrical Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, 66169-35391, Iran
| | | | - Sasan Pirouzi
- Department of Engineering, Semirom Branch, Islamic Azad University, Semirom, Iran.
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2
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Islam U, Alsadhan AA, Alwageed HS, Al-Atawi AA, Mehmood G, Ayadi M, Alsenan S. SentinelFusion based machine learning comprehensive approach for enhanced computer forensics. PeerJ Comput Sci 2024; 10:e2183. [PMID: 39145216 PMCID: PMC11323197 DOI: 10.7717/peerj-cs.2183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/18/2024] [Indexed: 08/16/2024]
Abstract
In the rapidly evolving landscape of modern technology, the convergence of blockchain innovation and machine learning advancements presents unparalleled opportunities to enhance computer forensics. This study introduces SentinelFusion, an ensemble-based machine learning framework designed to bolster secrecy, privacy, and data integrity within blockchain systems. By integrating cutting-edge blockchain security properties with the predictive capabilities of machine learning, SentinelFusion aims to improve the detection and prevention of security breaches and data tampering. Utilizing a comprehensive blockchain-based dataset of various criminal activities, the framework leverages multiple machine learning models, including support vector machines, K-nearest neighbors, naive Bayes, logistic regression, and decision trees, alongside the novel SentinelFusion ensemble model. Extensive evaluation metrics such as accuracy, precision, recall, and F1 score are used to assess model performance. The results demonstrate that SentinelFusion outperforms individual models, achieving an accuracy, precision, recall, and F1 score of 0.99. This study's findings underscore the potential of combining blockchain technology and machine learning to advance computer forensics, providing valuable insights for practitioners and researchers in the field.
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Affiliation(s)
- Umar Islam
- Computer Science, IQRA National University, Peshawar, Swat Campus, Pakistan
| | - Abeer Abdullah Alsadhan
- Department of Computer Science, Applied College, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | | | - Abdullah A. Al-Atawi
- Department of Computer Science, Applied College, University of Tabuk, Tabuk, Saudi Arabia
| | - Gulzar Mehmood
- Computer Science, IQRA National University, Peshawar, Swat Campus, Pakistan
| | - Manel Ayadi
- Information Systems Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Shrooq Alsenan
- Information Systems Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
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Rahideh A, Mallaki M, Najafi M, Ghasemi A. Multi-objective placement and sizing of energy hubs in energy networks considering generation and consumption uncertainties. Heliyon 2024; 10:e31843. [PMID: 38873666 PMCID: PMC11170191 DOI: 10.1016/j.heliyon.2024.e31843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 05/07/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
This paper presents the placement and sizing of energy hubs (EHs) in electricity, gas, and heating networks. EH is a coordinator framework for various power sources, storage devices, and responsive loads. For simultaneous modeling of economic, operation, reliability, and flexibility indices, the proposed scheme is expressed as a three-objective optimization in the form of Pareto optimization based on the sum of weighted functions. The objective functions of this problem respectively minimize the planning cost of EHs (equal to the total cost of construction of hubs and their expected operating cost), the expected energy loss of the mentioned networks, and the expected energy not-supplied (EENS) of these networks in the case of an N - 1 event. The problem is constrained by power flow equations and operation and reliability constraints of these network together with the EH planning and operation model, and flexibility constraints of the EHs. Then, to achieve unique optimal solution in the shortest possible time, a linear approximation model is extracted for the proposed scheme. Moreover, scenario-based stochastic programming (SBSP) is employed to model uncertainties of load, energy cost, renewable power, and accessibility of the mentioned network equipment. Finally, the obtained numerical results indicate the capability of the proposed scheme in enhancing the economic and flexibility situation of EHs and improving the reliability and operation status of energy networks along with achieving optimal planning and operation for EHs.
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Affiliation(s)
- Abdolhamid Rahideh
- Electrical Engineering Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran
| | - Mehrdad Mallaki
- Electrical Engineering Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran
| | - Mojtaba Najafi
- Electrical Engineering Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran
| | - Abdolrasul Ghasemi
- Electrical Engineering Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran
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4
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Moosanezhad J, Basem A, khalafian F, Alkhayer AG, Al-Rubaye AH, Khosravi M, Azarinfar H. Day-ahead resilience-economic energy management and feeder reconfiguration of a CCHP-based microgrid, considering flexibility of supply. Heliyon 2024; 10:e31675. [PMID: 38867951 PMCID: PMC11167308 DOI: 10.1016/j.heliyon.2024.e31675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 05/18/2024] [Accepted: 05/20/2024] [Indexed: 06/14/2024] Open
Abstract
Many challenges have emerged due to the intense integration of renewables in the distribution system and the associated uncertainties in power generation. Consequently, local management strategies are developed at the distribution level, leading to the emergence of concepts such as microgrids. Microgrids include a variety of heating, cooling, and electrical resources and loads, and the operators' aim is to minimize operation and outage costs. Since significant distribution system outages are typically caused by events such as earthquakes, floods, and hurricanes, microgrid operators are compelled to improve resilience to ensure uninterrupted service during such conditions. A mixed-integer linear programming model is designed in this paper to optimize the energy management and structural configuration of microgrids. This optimization aims to enhance resilience cost, minimizing operation and capital costs as well as power loss and pollution. To achieve these goals, several tools are implemented including reconfiguration, storages, combined cooling, heat and power units, wind turbines, photovoltaic panels, as well as capacitors. Four case studies are defined to prove the developed model efficiency. The first case study focuses on energy management in the microgrid for operation cost minimization. The second case study emphasizes the improvement of resilience alongside energy management, aiming at minimizing costs and enhance resilience. In the third case, the microgrid's reconfiguration capability is also added to the second case. Therefore, this case aims to optimize both energy and structural management within the microgrid to simultaneously enhance resilience and minimize operational costs. Finally, in the fourth case, the problem is studied in a multi-objective approach. By comparing the results, the resilience impact on the operation of microgrids is elucidated. By considering the resilience concept in microgrid operation and based on the results of case 2, it is found that the operating costs are increased by an average of 10.38 %. However, because of reducing resilience costs by an average of 13.91 %, the total cost is reduced by an average of 5.93 % in case 2 compared to case 1. Furthermore, when comparing cases 2 and 3, the reconfiguration effect can be determined. It can be observed that the operating costs are decreased by an average of 4.5 %. Moreover, the resilience cost is decreased by an average of 1.61 %, resulting in an overall reduction of the total objective function by an average of 2.43 % in case 3 compared to case 2.
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Affiliation(s)
- Jaber Moosanezhad
- Department of Management, Economics, and Accounting, Payame Noor University (PNU), Tehran, Iran
| | - Ali Basem
- Faculty of Engineering, Warith Al-Anbiyaa University, Karbala, 56001, Iraq
| | - farshad khalafian
- Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
| | - Alhussein G. Alkhayer
- Department of Electrical Engineering Techniques, Al-Amarah University College, Maysan, Iraq
| | - Ameer H. Al-Rubaye
- Department of Petroleum Engineering, Al-Kitab University, Altun Kupri, Iraq
| | - Mohsen Khosravi
- Faculty of Computer and Electrical Engineering, University of Gonabad, St. Ghafari, Gonabad, Iran
| | - Hossein Azarinfar
- Faculty of Computer and Electrical Engineering, University of Gonabad, St. Ghafari, Gonabad, Iran
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Candra O, Alghamdi MI, Hammid AT, Alvarez JRN, Staroverova OV, Hussien Alawadi A, Marhoon HA, Shafieezadeh MM. Optimal distribution grid allocation of reactive power with a focus on the particle swarm optimization technique and voltage stability. Sci Rep 2024; 14:10889. [PMID: 38740824 DOI: 10.1038/s41598-024-61412-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 05/06/2024] [Indexed: 05/16/2024] Open
Abstract
A structured approach to managing reactive power is imperative within the context of power systems. Among the restructuring initiatives in the electrical sector, power systems have undergone delineation into three principal categories: generation, transmission, and distribution entities, each of which is overseen by an independent system operator. Notably, active power emerges as the predominant commodity transacted within the electrical market, with the autonomous grid operator assuming the responsibility of ensuring conducive conditions for the execution of energy contracts across the transmission infrastructure. Ancillary services, comprising essential frameworks for energy generation and delivery to end-users, encompass reactive power services pivotal in the regulation of bus voltage. Of particular significance among the array of ancillary services requisite in a competitive market milieu is the provision of adequate reactive power to uphold grid safety and voltage stability. A salient impediment to the realization of energy contracts lies in the inadequacy of reactive power within the grid, which poses potential risks to its operational safety and voltage equilibrium. The optimal allocation of the reactive power load is predicated upon presumptions of consistent outcomes within the active power market. Under this conceptual framework, generators are afforded continual compensation for the provision of reactive power indispensable for sustaining their active energy production endeavors.
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Affiliation(s)
- Oriza Candra
- Department Teknik Elektro and Electrical Power Engineering Research Group, Universitas Negeri Padang, Padang, Indonesia
| | - Mohammed I Alghamdi
- Computer Science Department, Al-Baha University, Al-Baha City, Kingdom of Saudi Arabia
| | - Ali Thaeer Hammid
- Technical College of Engineering, Al-Bayan University, Baghdad, Iraq
- Department of Electronics Engineering, College of Engineering, University of Diyala, Baqubah, Diyala, 32001, Iraq
- Sumerian Scriptum Synthesis Publisher, Baqubah, Diyala Province, 32001, Iraq
| | | | - Olga V Staroverova
- Department of State and Municipal Finance, Plekhanov Russian University of Economics, Stremyanny Lane, 36, Moscow, Russian Federation, 117997
| | | | - Haydar Abdulameer Marhoon
- Information and Communication Technology Research Group, Scientific Research Center, Al-Ayen University, Nasiriyah, Thi-Qar, Iraq
- College of Computer Sciences and Information Technology, University of Kerbala, Karbala, Iraq
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Cui Q, Liu F. Decentralized restoration of distribution systems with coupling neighboring microgrids. Heliyon 2024; 10:e28344. [PMID: 38596084 PMCID: PMC11002040 DOI: 10.1016/j.heliyon.2024.e28344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 02/14/2024] [Accepted: 02/16/2024] [Indexed: 04/11/2024] Open
Abstract
In this study, a multi-agent system (MAS) is incorporated in a decentralized strategy to restore distribution systems while taking into account coupling neighboring microgrids (CNMGs). This provides modeling for renewable energy sources (RESs), electric vehicles (EVs), battery storage systems (BSS) and load. The desired and most favorable restoration path is found by the MAS, in which zone agents are dispersed across the distribution system. The MAS can also manage microgrids (MGs) overloaded as the unbalance operation of RESs, BSS, EVs, and load. This is realized by making a bridge between MGs and neighboring non-overloaded MGs. The suggested method adheres to voltage and power flow restrictions while operating according to expert system standards. The recommended approach is put to the test using a 33-bus radial distribution system. MATLAB calculations on agents and power flow are carried out in order to verify the validity of the choices made by agents. The proposed restoration plan is able to obtain the best power supply path with a low number of switching in the event of a fault so that the voltage magnitude is higher than 0.9 p.u. and free capacity is available for the distribution lines. The smart charging strategy of EVs reduces 93% of their turn off compared to the non-smart charging strategy. However, if the CNMG plan is established, all vehicles can be powered.
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Affiliation(s)
- Qi Cui
- The College of Economics and Management, Shenyang Agricultural University, Shenyang 111000, LiaoNing, China
| | - Feng Liu
- The College of Economics and Management, Shenyang Agricultural University, Shenyang 111000, LiaoNing, China
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Yuan T, Mu Y, Wang T, Liu Z, Pirouzi A. Using firefly algorithm to optimally size a hybrid renewable energy system constrained by battery degradation and considering uncertainties of power sources and loads. Heliyon 2024; 10:e26961. [PMID: 38590876 PMCID: PMC10999815 DOI: 10.1016/j.heliyon.2024.e26961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 02/03/2024] [Accepted: 02/22/2024] [Indexed: 04/10/2024] Open
Abstract
In this paper, the planning of a hybrid system of wind turbine units, photovoltaic panels, and battery storage is presented by taking into account the limitation of the storage degradation. The scheme minimizes the construction and maintenance cost of power sources and storage equipment. The constraints of the problem include the operating model of the mentioned elements, the limitation of the number of the mentioned elements, the limitation of the storage degradation, and the power balance in the hybrid system. This scheme is subject to uncertainties of the demand and output power generation of wind turbines and photovoltaics, which are modeled using a scenario-based stochastic optimization. The problem has a mixed-integer non-linear structure, and the paper adopts the firefly algorithm to solve the problem. The contributions of the paper include considering the degradation model of the battery, presenting a stochastic modelling for planning the islanded system, and taking into account the uncertainties of load and renewable power. Finally, based on the numerical results, a low planning cost is obtained for the hybrid system in the case of using renewable resources. Batteries are capable of providing flexibility for the hybrid system so that they can cover oscillations of renewable power with respect to the load. The firefly algorithm can find a reliable optimal solution. Stochastic modeling raises the planning cost of the islanded system in comparison to the deterministic model, but it yields a more reliable solution. The battery degradation model incurs no additional costs in system planning, although it offers a far more precise representation of the battery's behavior.
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Affiliation(s)
- Tianmeng Yuan
- Tangshan Power Supply Company State Grid Jibei Electric Power Co.Ltd, Tangshan, 063000, Hebei, China
| | - Yong Mu
- Tangshan Power Supply Company State Grid Jibei Electric Power Co.Ltd, Tangshan, 063000, Hebei, China
| | - Tao Wang
- Tangshan Power Supply Company State Grid Jibei Electric Power Co.Ltd, Tangshan, 063000, Hebei, China
| | - Ziming Liu
- Tangshan Power Supply Company State Grid Jibei Electric Power Co.Ltd, Tangshan, 063000, Hebei, China
| | - Afshin Pirouzi
- Department of Engineering, Semirom Branch, Islamic Azad University, Semirom, Iran
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8
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Chen R, Ouyang M, Zhang J, Masoudinia F. Is exponential stability achievable in singular perturbed delayed systems with time-varying parameters? A comprehensive analysis. Heliyon 2024; 10:e27424. [PMID: 38515658 PMCID: PMC10955236 DOI: 10.1016/j.heliyon.2024.e27424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 02/20/2024] [Accepted: 02/28/2024] [Indexed: 03/23/2024] Open
Abstract
The present article conducts an investigation into the phenomenon of exponential stability within singular perturbed delayed systems, incorporating time-varying parameters. Singularly perturbed systems serve as essential tools in modeling intricate systems characterized by multiple time scales, wherein one subsystem exhibits significantly faster evolution than the others. The presence of small delays introduces complexities, influencing both state derivatives and delays, further accentuating the intricacies of the system. Drawing upon the principles of singular perturbation theory, the article introduces a novel approach to analyzing the stability of these complex systems, eschewing the conventional assumption of exponential stability in the fast subsystem. Within the scope of this study, we propose a rigorous stability analysis, utilizing Linear Matrix Inequality (LMI) methods, while considering time-varying parameters that exert substantial influence on the system's dynamics. The proposed methodology enables the exploration of system stability beyond conventional assumptions, imparting valuable insights into the behavior of singular perturbed delayed systems amidst varying conditions. Through extensive numerical simulations, the effectiveness and robustness of the approach are validated, illuminating the stability properties of these intricate systems. Comparative studies with existing techniques, which assume exponential stability in the fast subsystem, demonstrate the distinct advantages and uniqueness of the presented approach. The findings underscore the significance of accounting for time-varying parameters in achieving a comprehensive understanding of the exponential stability inherent in singular perturbed delayed systems. This research makes substantial contributions to the field of system stability analysis, particularly in the context of singular perturbed delayed systems featuring time-varying parameters. The originality of our approach lies in introducing a comprehensive analysis framework that overcomes the limitations of existing methodologies. By integrating a novel stability analysis method based on Linear Matrix Inequalities (LMIs), we offer a fresh perspective on achieving exponential stability in such complex systems. Significantly, our work addresses a critical gap in current literature by challenging the assumption of exponential stability in the fast subsystem, a key feature of singularly perturbed systems. Through a meticulous examination of time-varying parameters, we unveil their profound impact on system dynamics, thus enriching the understanding of stability behaviors. The potential real-world applications of our findings span diverse fields, ranging from engineering to mathematical modeling. Performance metrics are a key focal point of our research. Numerical simulations employing our proposed LMIs serve as a robust benchmark, demonstrating the superior stability achieved in comparison to existing methods. This performance-driven evaluation ensures the practical applicability and reliability of our analysis approach across various scenarios.
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Affiliation(s)
- Ran Chen
- School of Electronic Science and Engineering, Hunan University of Information Technology, Changsha, 410151, China
| | - Min Ouyang
- Wuling Power Corporation LTD., Changsha, 410004, China
| | - Jinju Zhang
- School of Computer & Communication Engineering, Changsha University of Science & Technology, Changsha 410004, China
| | - Fatemeh Masoudinia
- Department of Electrical Engineering, Sofyan Branch, Islamic Azad University, Sofyan, Iran
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Huang Y. Smart home system using blockchain technology in green lighting environment in rural areas. Heliyon 2024; 10:e26620. [PMID: 38434014 PMCID: PMC10906148 DOI: 10.1016/j.heliyon.2024.e26620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 01/10/2024] [Accepted: 02/16/2024] [Indexed: 03/05/2024] Open
Abstract
Currently, with the rapid development of smart home technology, the demand for establishing efficient and sustainable smart home systems in rural areas is increasing. However, in rural environments, the effective management and intelligent control of green energy face many challenges. To address these issues, this work aims to design a smart home system based on blockchain technology to achieve efficient energy management and intelligent control in a green lighting environment in rural areas. The main goals include improving the performance and safety of the system to meet the lighting needs of rural areas and promote sustainable development. The system comprises two primary components: the home gateway and cloud services. These components encompass functions like data monitoring and transmission, cloud storage, and remote control. The work also introduces the structural interaction, user node interaction, and the data security transmission scheme of the smart home system. Ultimately, the system's effectiveness is confirmed through simulation experiments. The results demonstrate that the system achieves the lowest latency when the transaction arrival rate is 40tps and the block size is 10. Additionally, the access control scheme based on the Hyperledger Fabric consortium chain can efficiently handle access requests for smart home resources and meet the practical application requirements within an appropriate range of security parameters. The main research conclusion is that the designed smart home system based on blockchain technology has achieved significant results in improving performance and security. This not only provides reliable lighting solutions for rural areas, but also provides important theoretical and practical guidance for the future development of smart home systems. The direction of future work includes further optimizing system performance, expanding the scope of application, and exploring more advanced blockchain technology applications in the field of smart homes. This will provide more possibilities and innovative directions for the development of future smart home systems.
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Affiliation(s)
- Ying Huang
- College of Art & Design, Putian University, Fujian, China
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Khosravi M, Azarinfar H, Sabzevari K. Design of infinite horizon LQR controller for discrete delay systems in satellite orbit control: A predictive controller and reduction method approach. Heliyon 2024; 10:e24265. [PMID: 38312572 PMCID: PMC10835271 DOI: 10.1016/j.heliyon.2024.e24265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/26/2023] [Accepted: 01/05/2024] [Indexed: 02/06/2024] Open
Abstract
In the realm of satellite orbit control, powerful controller design plays a pivotal role in minimizing fuel consumption and ensuring orbit stability. This article introduces an advanced approach to the design of a Linear Quadratic Regulator (LQR) controller with an infinite horizon, tailored for discrete delay systems. The proposed methodology integrates predictive control with a reduction method, aiming for optimality while addressing performance and system constraints. Formulating the control problem as a quadratic program, the predictive control method generates a sequence of control inputs using a reducing horizon strategy. Stability analysis, employing Lyapunov-Krasovsky functions and linear matrix inequalities, yields delay-independent conditions for exponential convergence. A numerical example showcases the controller's effectiveness in maintaining orbit and reducing fuel consumption, underlining its capacity to achieve control objectives despite uncertainties and time delays. This research contributes to robust control strategies in satellite orbit systems, enhancing control performance and operational efficiency.
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Affiliation(s)
| | | | - Kiomars Sabzevari
- Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran
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11
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Nozari H, Szmelter-Jarosz A, Ghahremani-Nahr J. Analysis of the Challenges of Artificial Intelligence of Things (AIoT) for the Smart Supply Chain (Case Study: FMCG Industries). SENSORS (BASEL, SWITZERLAND) 2022; 22:s22082931. [PMID: 35458916 PMCID: PMC9026436 DOI: 10.3390/s22082931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 04/01/2022] [Accepted: 04/09/2022] [Indexed: 05/07/2023]
Abstract
In today's competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization's activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies. "Artificial Intelligence of Things (AIoT)", which means using the Internet of Things to perform intelligent tasks with the help of artificial intelligence integration, is one of these expected innovations that can turn a complex supply chain into an integrated process. AIoT innovations such as data sensors and RFID (radio detection technology), with the power of artificial intelligence analysis, provide information to implement features such as tracking and instant alerts to improve decision making. Such data can become vital information to help improve operations and tasks. However, the same evolving technology with the presence of the Internet and the huge amount of data can pose many challenges for the supply chain and the factors involved. In this study, by conducting a literature review and interviewing experts active in FMCG industries as an available case study, the most important challenges facing the AIoT-powered supply chain were extracted. By examining these challenges using nonlinear quantitative analysis, the importance of these challenges was examined and their causal relationships were identified. The results showed that cybersecurity and a lack of proper infrastructure are the most important challenges facing the AIoT-based supply chain.
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Affiliation(s)
- Hamed Nozari
- Department of Industrial Engineering of Central Tehran Branch, Islamic Azad University, Tehran 1469669191, Iran;
| | - Agnieszka Szmelter-Jarosz
- Department of Logistics, Faculty of Economics, University of Gdańsk, ul. Armii Krajowej 119/121, 81-824 Sopot, Poland
- Correspondence:
| | - Javid Ghahremani-Nahr
- Faculty Member of ACECR, Development and Planning Institute, Tabriz 5154837693, Iran;
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