Interconnected Systems Research Articles

Security and Privacy in Networks and Multimedia

The digital era has significantly transformed the dissemination of information and business operations, creating an intricate web of interconnected systems [...]

Catalytic cracking of oleic acid to generate aviation kerosene using platinum–modified ZSM–5 nanosheets

AbstractBACKGROUNDA series of Pt@NZSM–5 and Pt/NZSM–5 nanosheets having different Si/Al ratios were prepared via an in situ synthesis and impregnation method, respectively, using C22H45–N+(CH3)2–C6H12–N+(CH3)2–C6H13 (C22–6–6) as the template agent. The oleic acid decarboxylation reaction was carried out using these materials under CO2 atmosphere and the oleic acid cracking mechanism was inferred from the product distribution of the C8‐C17 alkanes.RESULTSThe Pt@NZSM–5 and Pt/NZSM–5 was found to comprise thinner nanosheets and exhibited strong metal–substrate interactions. Pt@NZSM–5 nanosheets with a Si/Al molar ratio of 100 had thicknesses of only 8–9 nm along with a mesopore/micropore capacity ratio of 2.7, an acid content of 11 cm3/g STP and a high Pt0/PtOx ratio.CONCLUSIONThe Pt@NZSM‐5 and Pt/NZSM‐5 nanosheets had an interconnected hierarchical system and a large number of metal active sites that facilitated the decarboxylation of oleic acid. The Pt@NZSM–5 nanosheets demonstrated excellent catalytic activity during the cracking of oleic acid under a CO2 atmosphere, giving a yield of C8–C17 alkanes as high as 83.8% after 5 h at 320 °C. These Pt@NZSM–5 nanosheets also showed greater stability than the Pt/NZSM–5 specimens. © 2024 Society of Chemical Industry (SCI).

A new distributed robust H∞ control strategy for a class of uncertain interconnected large-scale time-delay systems subject to actuator saturation and disturbance

In the realm of large-scale systems, the complexity of controller design has long been exacerbated by the proliferation of decision variables and inherent conservatism. This study introduces a novel approach to address these challenges, presenting a new distributed robust controller design methodology tailored for large-scale systems grappling with disturbances, uncertainties, and actuator saturations. The primary objectives include reducing conservatism, minimizing decision variables, and significantly curtailing computation time. To surmount these hurdles, the research leverages descriptive and reciprocally convex methods, formulating the design procedure using linear matrix inequalities. This enables the adjustment of uncertain parameters and robust disturbance rejection, thereby ensuring stability in large-scale systems. Additionally, a feedback control law is proposed to accommodate saturation constraints and ensure the closed-loop system’s stability. Notably, the effectiveness of the proposed control scheme is demonstrated through the evaluation of a full-car active suspension system, which is partitioned into interconnected subsystems to a large-scale system. Comparative analyses underscore the superior performance and technical advancements offered by the proposed methodology over existing approaches.

Practicing the hegemony of non-hegemony: the pluriversal politics of the Neapolitan commons movement

ABSTRACT The concept of pluriversal politics, which encompasses the vast array of alternatives to ecologically destructive and colonial capitalism, is crucial for envisioning emancipatory futures. However, the diversity of the initiatives composing the pluriverse poses obstacles to the unity necessary to dismantle interconnected systems of oppression, thus creating an intrinsic dilemma between diversity and unity. This paper explores the navigation of this challenge within emancipatory and pluriversal projects, drawing on material from ethnographic research on the Neapolitan Commons movement. The case study illuminates how social movement actors achieve simultaneous unity and diversity through the grassroots-developed concept of ‘hegemony of non-hegemony.’ In the Neapolitan context, this framework allows diversity to thrive while maintaining essential unity, crucial for confronting economic and political powers. The findings underscore how grassroots, autonomous, and pluriversal degrowth practices can challenge capitalist growth dynamics through unity in diversity, hence suggesting the unnecessary nature of state-led, top-down, or uniformizing approaches.

Examining the Evolution of Energy Storing in the Ecuadorian Electricity System: A Case Study (2006–2023)

Ensuring a balance between supply and demand is critical within electricity grids, requiring a supply composition that guarantees consistent service provision in the short and medium term. Between 2008 and 2017, Ecuador’s electricity generation capacity expanded significantly, with an investment of approximately USD 8150 million into harnessing the potential energy of water. This led to the construction of five high-capacity hydroelectric projects by 2017, contributing 33.4% of the sector’s energy output by 2023. However, it is important to note that if installed hydroelectric projects operate as run-of-river plants, with limited reservoir capacity, they can only regulate water use for electricity generation on an hourly basis. As of 2023, these run-of-river plants represent 68.8% of Ecuador’s total hydroelectric capacity within the National Interconnected System (SNI). Consequently, during periods of low inflows, supplementary energy from other power generation plants is necessary to prevent energy crises. This paper addresses the impact on energy storing for electricity generation resulting from the evolution of hydroelectric power plant entry from 2006 to 2023. This aspect has not been thoroughly examined in hydrothermal systems, which primarily focus on potential energy obtained from dams. Our approach involves a statistical analysis of hydroelectric dam reservoir operational levels. We further explore the influence on demand service within Ecuador’s electricity system, particularly during observed energy crises towards the end of 2023.

Optimization of Interconnected Natural Gas and Power Systems Using Mathematical Programs with Complementarity Constraints

The demand for thermal power generation from natural gas has increased globally due to its cleaner burning properties compared to other fossil fuels. Optimizing the gas flow through the network to meet this demand is challenging due to the nonconvex Weymouth equation constraining gas flow and nodal pressures in pipelines. Traditional methods for addressing this nonconvexity lead to significant approximation errors or high operational costs. This study poses the Weymouth constraint as a Mathematical Programming with Complementarity Constraints (MPCC) for an optimal gas flow problem. The complementarity constraints reformulate the discontinuous sign function using binary-behaving continuous variables. This MPCC-based approach avoids solving mixed-integer programming problems while enhancing the accuracy of conventional linear and second-order approximations. Testing the approach on various interconnected systems, including Colombia’s national gas transportation grid, demonstrated significant reductions in Weymouth approximation errors, thereby supporting effective optimization for interconnected networks.

Load Frequency Control Strategy of Interconnected Power System Based on Tube DMPC

Solar thermal power generation shares technical characteristics with traditional thermal power generation. This enables rapid adjustment of turbine generator output to meet the demands of the power grid load for frequency modulation. However, fluctuations in light intensity lead to variations in interconnected power system parameters, posing challenges for load frequency control (LFC). In this study, we propose a Robust Distributed Model Predictive Control (RDMPC) method. This method achieves system trajectory tracking by solving the nominal system optimization problem. It also flexibly adjusts the weights of different Tube models to determine the optimal control law using the standard Tube online combination with various gain values. Additionally, we incorporate the states of adjacent areas into the feedback control law to achieve effective coordination between these areas. Using MATLAB/Simulink, we simulated the power system in two areas. Compared to standard Tube DMPC, our proposed algorithm effectively mitigates the impact of light intensity, enhances adjustment speed, reduces frequency fluctuation, and demonstrates superior control effectiveness.

Observer‐based optimal fault‐tolerant tracking control for input‐constrained interconnected nonlinear systems with mismatched disturbances

SummaryThis paper investigates an observer‐based optimal fault‐tolerant tracking control problem for interconnected nonlinear systems with input constraints and mismatched disturbances via adaptive dynamic programming (ADP). Firstly, an augmented system consisting of tracking error and the reference trajectory is constructed, and then the original optimal tracking control problem is transformed into the optimal regulation control problem of the augmented system. An integral sliding‐mode‐based optimal fault‐tolerant control scheme is developed to eliminate the effect of actuator faults and guarantee the optimal control performance. Furthermore, a neural network‐based observer is designed to identify the completely unknown system dynamics based on the input‐output data, thereby relaxing the restriction on system dynamics. Subsequently, the modified Hamilton‐Jacobi‐Bellman equations are solved by using the ADP algorithm under a critic network framework. According to the Lyapunov approach, all signals in the closed‐loop augmented system are uniformly ultimately bounded. Finally, the effectiveness of the developed control scheme is demonstrated via simulation results.

Cyber‐attack and defense method for load frequency control in smart grid systems with electric vehicles

AbstractThe latest advancements in Vehicle‐to‐Grid (V2G) technology enable Electric Vehicles (EVs) to contribute to Frequency Regulation (FR), mitigating the impact of uncertain power fluctuations in renewable resources. However, diverse cyber‐attacks pose threats to the Load Frequency Control (LFC) system and smart grid infrastructure, compromising their accuracy and reliability. This research paper focuses on the effects of cyber‐attacks on frequency regulation in a smart grid system that relies on a communication network. The study proposes a two‐area system and a modified IEEE‐39 bus three‐area system, incorporating intermittent solar photovoltaic and wind turbine sources, traditional conventional sources, and electric vehicles. To ensure frequency stabilization and tie‐line power, the researchers introduce a cascade FOPIDN‐(1+TD) controller. Its parameters are optimized using a novel Quasi Opposition Arithmetic Optimization Algorithm (QOAOA). The proposed approach's dynamic response is compared with other commonly used controllers, demonstrating its effectiveness in maintaining stability. The article focuses on the LFC system and presents a novel approach involving a cyber‐physical model. It introduces a method for detecting and defending against cyber‐attacks using deep learning, specifically utilizing the Long‐Short‐Term‐Memory (LSTM) network. The effectiveness of the proposed defense strategy is demonstrated through experiments conducted on both a two‐area interconnected power system and the IEEE‐39 bus system. The outcomes indicate that the suggested defense mechanism effectively maintains acceptable levels of power system frequency and tie‐line power during cyber‐attacks. Additionally, the validity of the controller's performance is verified through real‐time analysis using Hardware‐In‐The‐Loop (HIL) simulation with the OPAL‐RT platform.

Model following adaptive control for nodes in complex dynamical network via the state observer of links

Geometrically, a complex dynamical network (CDN) can be regarded as the interconnected system composed of the node subsystem (NS) and the link subsystem (LS) coupled with each other. Guided by this idea, in order to achieve the goal of each node following asymptotically its own reference target in a CDN, this paper investigates the model following adaptive control (MFAC) problem of NS via the dynamics of links, which implies that the LS plays the important dynamic auxiliary role in the MFAC realization of nodes. Meanwhile, we focus on the condition that the links state information is unavailable, due to sensor practical application and measurement cost constraints. To obviate this restriction, we construct the asymptotical state observer for the LS. Next, to achieve the control goal of this paper, an appropriate Lyapunov candidate function is selected, by which the MFAC scheme for NS is synthesized based on the state observer of LS. Finally, the simulation example is performed to demonstrate the theoretical results in this paper.

Decentralized adaptive tracking control for interconnected nonlinear systems with unmodeled dynamics and input delays

This paper focuses on the decentralised adaptive tracking control problem for nonstrict-feedback interconnected nonlinear systems with unmodeled dynamics and input delays. To identify the unstructured uncertainties, a novel broad learning system (BLS) approximation technique is introduced in this study to solve it. On this basis, a nonlinear state observer is designed to estimate the unmeasurable state variables. A dynamic signal is introduced to deal with the effect of unmodeled dynamics, and the appropriate error transformation is utilised to handle the effect of input delays. The decentralised adaptive tracking control strategy is proposed to the considered interconnected nonlinear systems using the design procedures of backstepping control with command filter. The semi-globally uniformly ultimately boundedness (SGUUB) stability and the tracking performance of the whole closed-loop systems could be guaranteed by using the Lyapunov approach. Finally, simulation results are provided to validate the present theoretical claims.

Decentralized asymptotic tracking control for time‐varying interconnected nonlinear systems with prescribed performance

AbstractThis article studies decentralized adaptive asymptotic tracking control of time‐varying interconnected nonlinear systems. To address the obstacles caused by interactions and these unknown time‐varying parameters, a smooth function and a bound estimation approach are introduced. Additionally, by means of a class of funnel functions and barrier Lyapunov function approach, a prescribed performance control strategy is constructed, allowing tracking accuracy and the settling time to be predetermined in accordance with control requirements, without relying on initial conditions or design parameters. Particularly, reasoned proofs have been given to confirm that the presented control method not only guarantees the prescribed transient performance, but also achieves the asymptotic tracking without requiring knowledge of high‐order derivatives of the reference signal. Ultimately, the efficiency of our approach is verified by simulation results.

Decentralized asymptotic tracking control for time‐varying interconnected nonlinear systems with prescribed performance

Decentralized asymptotic tracking control for time‐varying interconnected nonlinear systems with prescribed performance

GC-MS profiling of organic pollutants and physicochemical, histological, microbiological analyses of water and fish samples from Canton Sarajevo (Bosnia and Herzegovina) rivers

<p>Continuous monitoring of the water quality in Canton Sarajevo is one of the top priorities necessary for water management, pollution control and conservation efforts in the region. This study presents a comprehensive assessment of water quality in the interconnected river systems of Miljacka and Zeljeznica, employing a multianalytical approach. Water and fish samples were collected at three sites and analysed for the presence of microorganisms, heavy metals and organic pollutants. Physicochemical parameters were examined to understand the rivers’ overall health and ecologic condition. Histopathological analysis of fish species native to these two rivers served as a bioindicator of environmental stressors. In general, there were less anthropogenic pressures found at Site 1 – Kozija ćuprija (river Miljacka – upstream from the city of Sarajevo) and 3 (river Zeljeznica – downstream from the city of Sarajevo). Site 2 – Otoka (river Miljacka, city center) had the highest concentrations of lead, ammonia, orthophosphates and BOD5, as well as total coliform bacteria. This may be linked to the runoff from sewage. The detected histopathological changes are probably associated with the combined microorganisms and organic pollutants, among which plasticizers, emulsifiers, solvents, surfactants and additives were detected by GC-MS.</p>

Optimally tuned cascaded FOPI-FOPIDN with improved PSO for load frequency control in interconnected power systems with RES

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

Optimally tuned cascaded FOPI-FOPIDN with improved PSO for load frequency control in interconnected power systems with RES

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

EDUCATIONAL AND PROFESSIONAL PROGRAMS FOR WAR VETERANS AND MEMBERS OF THEIR FAMILIES: ENSURING SUCCESSFUL INTEGRATION INTO UKRAINIAN SOCIETY

The author researched and conducted an analysis that points to the critical importance of developing and implementing effective integration programs for veterans aimed at ensuring their successful transition to civilian life and active participation in society. Aspects including education, professional development, work opportunities, social integration, psychological support and assistance to families are clarified, systematized and analyzed as components of a large and interconnected system. It has been determined that an individualized and flexible approach is critical to the successful integration of veterans, taking into account their unique needs and experiences. It is noted that systemic solutions, especially the involvement of different sectors of society, are seen as successful and adaptive responses to the complex tasks and challenges faced by veterans. The research is substantiated, supporting the need for continuous improvement and adaptation of integration programs to the rapid changes in today's world. The relevance and necessity of developing and implementing comprehensive programs for veterans, which take into account their unique needs and promote full integration into society, are emphasized.

EDUCATIONAL AND PROFESSIONAL PROGRAMS FOR WAR VETERANS AND MEMBERS OF THEIR FAMILIES: ENSURING SUCCESSFUL INTEGRATION INTO UKRAINIAN SOCIETY

The author researched and conducted an analysis that points to the critical importance of developing and implementing effective integration programs for veterans aimed at ensuring their successful transition to civilian life and active participation in society. Aspects including education, professional development, work opportunities, social integration, psychological support and assistance to families are clarified, systematized and analyzed as components of a large and interconnected system. It has been determined that an individualized and flexible approach is critical to the successful integration of veterans, taking into account their unique needs and experiences. It is noted that systemic solutions, especially the involvement of different sectors of society, are seen as successful and adaptive responses to the complex tasks and challenges faced by veterans. The research is substantiated, supporting the need for continuous improvement and adaptation of integration programs to the rapid changes in today's world. The relevance and necessity of developing and implementing comprehensive programs for veterans, which take into account their unique needs and promote full integration into society, are emphasized.

Road to Efficiency: V2V Enabled Intelligent Transportation System

Intelligent Transportation Systems (ITSs) have grown rapidly to accommodate the increasing need for safer, more efficient, and environmentally friendly transportation options. These systems cover a wide range of applications, from transportation control and management to self-driving vehicles to improve mobility while tackling urbanization concerns. This research looks closely at the important infrastructure parts of vehicle-to-vehicle (V2V) communication systems. It focuses on the different types of communication architectures that are out there, including decentralized mesh networks, cloud-integrated hubs, edge computing-based architectures, blockchain-enabled networks, hybrid cellular networks, ad-hoc networks, and AI-driven dynamic networks. This review aims to critically analyze and compare the key components of these architectures with their contributions and limitations. Finally, it outlines open research challenges and future technological advancements, encouraging the development of robust and interconnected V2V communication systems in ITSs.

Road to Efficiency: V2V Enabled Intelligent Transportation System

Intelligent Transportation Systems (ITSs) have grown rapidly to accommodate the increasing need for safer, more efficient, and environmentally friendly transportation options. These systems cover a wide range of applications, from transportation control and management to self-driving vehicles to improve mobility while tackling urbanization concerns. This research looks closely at the important infrastructure parts of vehicle-to-vehicle (V2V) communication systems. It focuses on the different types of communication architectures that are out there, including decentralized mesh networks, cloud-integrated hubs, edge computing-based architectures, blockchain-enabled networks, hybrid cellular networks, ad-hoc networks, and AI-driven dynamic networks. This review aims to critically analyze and compare the key components of these architectures with their contributions and limitations. Finally, it outlines open research challenges and future technological advancements, encouraging the development of robust and interconnected V2V communication systems in ITSs.