Interconnected Systems Research Articles

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.

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

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.

Machine learning for water-energy-food-ecosystems nexus policy

Machine learning for water-energy-food-ecosystems nexus policy Dr Janez Sušnik, from the IHE Delft Institute for Water Education and NEXOGENESIS Coordinator, guides us through the use of machine learning for improving policy advice in the water-energy-food-ecosystems nexus. Water, energy, and food (WEF) form a coherent interconnected system often referred to as the WEF nexus (Hoff, 2011). The WEF nexus interacts strongly with ecosystems, forming the wider WEFE nexus. Ecosystems provide the ‘base’ of the WEFE nexus, helping ensure the quantity, quality, timing, and accessibility of WEF resources, for example, by providing services including water purification, contributing freshwater provisioning, pollution reduction and control; maintaining healthy landscapes, contributing towards crop growth for food and energy crops; biodiversity providing pollinating insects for crop production and; forest and floodplain ecosystems provide biomass that as act as a global carbon sink and oxygen supply (Bell et al. 2016; Martinez- Hernandez et al. 2017).

A proposed design for security system for nuclear waste warehouses against terrorists attack

A physical protection system (PPS) is one of the principal systems used in nuclear facilities for protection against terrorist attacks and the possibility of bombing, sabotage, and theft. This paper introduces the design of an advanced security system for nuclear waste warehouses against stealth terrorist attacks. This research paper takes a more original approach in addressing how a nuclear facility can detect and respond to a security incident. It does so through an interconnected security system that simultaneously practical and distinctive way. This PPS design allows the security system to achieve its main goals of detection and delay functions during any incident. Additionally, it places the intruder under attack from a successive defensive system which grants the response forces additional time to arrive and neutralize the threat completely.The proposed design of the security system will include dual-side infrared rays, high-intensive sound barriers, an intensive flashlight barrier, an electric chock system, and a smart camera surveillance system. Three consecutive processes, detection, deterrence, and defense will be operated around the waste storage building. This idea can be implemented by establishing an early detection system to detect any intrusion by terrorist attackers through a protected area surrounding the storage facility. The next step is deterring the attackers from completing their mission by placing an advanced deterrence system and putting delay elements along the path of their attack on the waste storage to complicate the mission. Then the defense system is operating to prevent terrorist progress. Finally, an evaluation process of the overall security system which has been designed by using EASI program is performed to verify the accepted level of physical protection, keep the security system component valid and updated, and follow procedures, rules and requirements of the nuclear regulatory authority at the national level and meet IAEA concept and recommendations at the international level.

Using Behavioural Biometrics and Machine Learning in Smart Gadgets for Continuous User Authentication Purposes

In the ever-evolving realm of technology, the identification of human activities using intelligent devices such as smartwatches, fitness bands, and smartphones has emerged as a crucial area of study. These devices, equipped with inertial sensors, gather a wealth of data and provide insights into users' movements and behaviors. These data not only serve practical purposes, but also hold significant implications for domains such as healthcare and fitness tracking. Traditionally, these devices have been employed to monitor various health metrics such as step counts, calorie expenditure, and real-time blood pressure monitoring. However, recent research has shifted its focus to leveraging the data collected by these sensors for user authentication purposes. This innovative approach involves the utilization of Machine Learning (ML) models to analyze the routine data captured by sensors in smart devices employing ML algorithms, which can recognize and authenticate users based on their unique movement patterns and behaviors. This introduces a paradigm shift from traditional one-time authentication methods to continuous authentication, adding an extra layer of security to protect users against potential threats. Continuous authentication offers several advantages over its conventional counterparts. First, it enhances security by constantly verifying a user's identity through their interaction with the device, thereby mitigating the risk of unauthorized access. Second, it provides a seamless and nonintrusive user experience, eliminating the need for repetitive authentication prompts. Moreover, it offers robust protection against various threats such as identity theft, unauthorized access, and device tampering. The application of continuous authentication extends beyond individual devices and encompasses interconnected systems and networks. This holistic approach ensures a comprehensive security across digital platforms and services. The experiments demonstrate that the logistic regression model achieves an accuracy of 82.32% on the test dataset, highlighting its robustness for binary classification tasks. Additionally, the random forest model outperforms with a 92.18% accuracy, emphasizing its superior capability in handling complex feature interactions. In the study, the sequential neural network achieved an accuracy of 92% on the HAR dataset, outperforming traditional machine learning models by a significant margin. The model also demonstrated robust generalization capabilities with a minimal drop in performance across various cross-validation folds.

Automatic Generation Control in Renewables-Integrated Multi-Area Power Systems: A Comparative Control Analysis

Electrical load dynamics result in system instability if not met with adequate power generation. Therefore, monitoring and control plans are necessary to avoid potential consequences. Tie-line-bias control has facilitated power exchange between interconnected areas to cope with load dynamics. However, this approach presents a challenge, as load variation in either area leads to frequency deviations and power irregularities in each of the interconnected areas, which is undesirable. The load frequency control loop method is used to address this issue, which utilizes area control errors. This study focuses on the control of inter-area oscillations in a six-area power system under the effect of renewable energy sources. It evaluates the area control errors in response to changes in load and the penetration of renewable energy into the system. To mitigate these errors efficiently, an adaptive-PID controller is proposed, and its results are compared with PI and PID controllers optimized with heuristic and meta-heuristic algorithms. The findings demonstrate the superiority of the proposed controller over traditional controllers in mitigating tie-line power errors and frequency deviations in each area of the interconnected power system, thus helping to mitigate inter-area oscillations and restore system stability.

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

The power system is gradually becoming an AC/DC hybrid MES (multi-energy system) with hydrogen energy. Due to the uncertainty of reactive power demand of load in MES and the multi-time scale characteristics of different energy flow transmission. It will lead to difficulties in reactive power coordination within the entire MES. Secondly, in response to this problem, this paper first establishes a MES cluster hybrid power flow equation formed by AC/DC and hydrogen transmission channels. The reactive power voltage fluctuation characteristics of AC/DC systems under MES cluster interconnection channel energy exchange, system energy conversion and renewable energy output fluctuation are analysed. Then according to the MES cluster hybrid power flow calculation. The main factors affecting the voltage reactive power of the AC system are studied, and the reactive power model based on electrothermal conversion, hydrogen storage and multi-energy transmission channels is established. Finally, proposed an algorithm for generating the safety and stability boundary of pipe network pressure. It’s used to construct the safe and stable boundary of the system pipe network. based on the actual operational data of multi-energy power system. The simulation model of reactive power dynamic optimization control for multi-energy interconnected systems is established

MODCEL-MHUS: a comprehensive multilayer hydrodynamic unified simulation for stormwater, sanitary sewer systems, and urban surface.

Numerous countries and regions have embraced implementing a separate sewer system, segregating sanitary and storm sewers into distinct systems. However, the functionality of these systems often needs to improve due to irregular interconnections, resulting in a mixed and malfunctioning system. Sewage collection is crucial for residential sanitation, but untreated collection significantly contributes to environmental degradation. Analyzing the simultaneous operation of both systems becomes vital for effective management. Using mathematical tools for precise and unified diagnosis and prognosis becomes imperative. However, municipal professionals and companies need more tools specifically designed to evaluate these systems in a unified way, mapping all the hydraulic connections observed in practice. This study proposes a unified simulation method for stormwater and sanitary sewer urban systems, addressing real-world scenarios and potential interferences. The primary goal is to develop a simulation method for both systems, considering system interconnections and urban layouts, involving hydrodynamic and water quality simulations. The practical application of this method, the Multilayer Hydrodynamic Simulation Method (MODCEL-MHUS), successfully identifies issues in urban water networks and suggests solutions, making it a valuable tool for urban water management and environmental engineering professionals.

Collaborative Planning and Comprehensive Evaluation Method for Energy Storage System and Flexible Interconnection in Distribution Networks Considering Island Operation

Introduction: When the superior power grid fails and loses power, due to the traditional single power supply radial grid structure of low-voltage substation areas, all loads in the lowvoltage substation area will lose power, causing a poor electricity consumption experience for low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in distribution networks, considering island operation, is proposed. Method: This method integrates GFM-ESS and flexible interconnections, taking islanding operations into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed. The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly, minimizing the annual comprehensive cost and the annual power outage load are the objective functions. A bilevel programming model for GFM-ESS and flexible interconnection of lowvoltage distribution networks, considering island operation, has been established. Moreover, a comprehensive evaluation method based on the analytic hierarchy process for proposed lowvoltage distribution network structural schemes is introduced. An evaluation index system is established to assess the rationality of these proposed network structural planning schemes. Finally, the superiority of the proposed collaborative planning method is verified through a comparative analysis of three planning methods. Result: The proposed collaborative planning method can effectively ensure the continuous power supply of low-voltage distribution networks under the fault scenario of the upper power network. Conclusion: Moreover, the rationality of the results obtained from the proposed collaborative planning method is verified through a comprehensive evaluation method of grid structure schemes based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine which two areas are optimal for grid planning. result: The superiority of the proposed collaborative planning method was verified by comparative analysis of three planning methods. And the rationality of the proposed collaborative planning method results was verified by the comprehensive evaluation method of grid structure schemes based on analytic hierarchy process.

Quantized control for interconnected PDE systems via mobile measurement and control strategies

This paper deals with the Rϵ-stabilization for interconnected partial differential equation systems (IPDESs) by mobile measurement and control strategies. First, compared to the static measurement and control strategies, the mobile ones are employed to improve the dynamic response of the closed-loop system, while reducing the number of sensors and actuators effectively. Moreover, considering the constrained transmission channel bandwidth, the hysteresis quantizer with an adjustable parameter is introduced to save the communication resources in the network, while can balance the quantization effect and the control performance by adjusting the parameter. Further, the output quantization controller is designed to ensure that the closed-loop system is Rϵ-stable, which converges to a given interval in finite time. Finally, a simulation example of chemical non-isothermal tubular reactors is provided to illustrate the validity of the presented design method.