Remote Switching Research Articles

Even a small button can lead to “morbidity and mortality” case in equine anaesthesia-tracheal rupture caused by a faulty hoist remote-control switch

Even a small button can lead to “morbidity and mortality” case in equine anaesthesia-tracheal rupture caused by a faulty hoist remote-control switch

Pattern-based Remote Switch for Domestic and Technological Operations

Abstract: This research explores the development of a remote-control system for domestic appliances using user-drawn patterns on a grid, aiming to provide an intuitive and accessible control method. The system is designed around a 3x3 grid of infrared (IR) LEDs and receivers that detect patterns drawn by the user with a finger or stylus. Each grid coordinate is mapped to a specific action, such as turning lights on or off or adjusting the speed of a fan. The detected patterns are transmitted to a NodeMCU ESP8266 microcontroller, which decodes the patterns and activates the corresponding appliance through Wi-Fi commands and relays. The innovative aspects of this system include its simple and intuitive interaction method, allowing users to define custom patterns for various actions, which enhances personalized control. The pattern-based interaction is particularly beneficial for individuals with limited dexterity or mobility, offering an accessible alternative to traditional remote controls. This project demonstrates the potential of combining hardware components, such as IR LEDs and receivers, with embedded C programming to create a user-friendly and efficient home automation solution. The proposed system not only simplifies the user experience but also provides a flexible and customizable interface for controlling domestic appliances.

Load restoration of electricity distribution systems using a novel two‐stage method

AbstractThis paper proposes a new comprehensive load restoration (LR) method for electrical distribution networks. Since two main technologies of switching equipment are there in the modern distribution networks, namely manual switches (MSs) and remote‐controlled switches (RCSs), this article has benefited from this concept effectively. A two‐stage algorithm that provides the system operators with the ability to recover part of the loads in the shortest possible time by RCSs is proposed. After this step, the remaining loads will be restored by a combination of MSs and RCSs. The other strength of this algorithm is to provide accurate and practical solutions so that the sequence of switching actions is clearly defined. Also, using an innovative index called expected weighted energy not supplied as the objective function of the main problem will ensure the operators recover the maximum amount of load in the shortest time possible. This novel method was applied on a sample standard IEEE distribution test network. The simulation results proved the effectiveness of this proposed method.

A three-level robust scenario-based model for resilience-oriented placement of remote-controlled switches in distribution networks

This paper introduces an innovative strategy to improve the resilience of Distribution Networks (DN) following natural disasters. The approach involves a multi-stage model for the strategic placement of Remote-Controlled Switches (RCS) to expedite fault isolation and service restoration. The model integrates various resilience enhancement techniques, such as network reconfiguration and microgrid formation, throughout the pre-disaster, disaster progression, and post-disaster phases. To mitigate uncertainties related to line failures and ensure planning robustness, a novel three-level Robust Scenario-based Model (RSM) is introduced. The RSM optimizes the strategic RCS placement to enhance System Performance Criteria (SPC) in response to anticipated line failure scenarios, considering individual line vulnerabilities and disaster severity. Subsequently, the model identifies the most critical failures from each predicted scenario based on RCS placements and then recalibrates the placements to enhance DN resilience against both anticipated and critical failures. The RSM is formulated as a mixed-integer linear programming problem to maximize SPC by allocating resources optimally to serve maximum weighted loads while adhering to structural and operational constraints. The effectiveness and validity of the proposed model are demonstrated through case studies conducted on a modified IEEE 33-bus test system and a modified real DN.

Embedded components design strategy framework for fused deposition modeling system

This paper proposed a framework for 3D printing of embedded objects specifically for the Fused Deposition Modeling (FDM) system. The main problem revolves around the difficulty of the additive manufacturing process to fully manufacture a product that can be used immediately after the printing process, thus creating the need for embedded component design to be utilized in the process. The framework was utilized to reduce components and assemblies to improve product design. To ensure environmental sustainability, the framework emphasizes materials used to make recyclable items. Design Process Flow, Design Knowledge, Key Enabling Technologies, and Design Application were used to create a four-layered design framework to tackle embedded product design challenges. The framework’s robustness and effectiveness were compared using three case studies: electric shaver, remote control and nintendo switch. The framework proposed a blade-interchangeable product for the electric shaver. In the second case study (remote control) the cover’s flexibility with similar sizes makes it reusable. In the third case study (nintendo switch), every part is interchangeable with numerous styles and designs, allowing the user to autonomously change to the desired pattern without external support. With its various features, the framework shows potential in reducing development time, cost, and resources to aid the embedded component design strategy and printing for the FDM process.

Machine learning optimization for hybrid electric vehicle charging in renewable microgrids

Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources, reducing greenhouse gas emissions. This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable microgrids with a reconfigurable structure based on remote switching of tie and sectionalizing. The method utilizes Gaussian Process (GP) for modeling hybrid electric vehicle (HEV) charging demand. To counteract HEV charging effects, two scenarios are explored: coordinated and intelligent charging. A novel optimization method inspired by the Krill Herd Algorithm (KHA) is introduced for the complex problem, along with a self-adaptive modification to tailor solutions to specific situations. Simulation on an IEEE microgrid demonstrates efficiency in both scenarios. The predictive model yields a remarkably low Mean Absolute Percentage Error (MAPE) of 1.02381 for total HEV charging demand. Results also reveal a reduction in microgrid operation cost in the intelligent charging scenario compared to coordinated charging.

Hierarchical supramolecules composed of starch-based nanocluster aggregates with light-responsive mechanical strain for remotely rapid and precise actuation

Hierarchical supramolecular systems, characterized by nanoscale sensitivity and macroscopic tangible changes, offer promising perspectives for the design of remotely controllable, rapid, and precise actuation materials, serving as a potential substitution for non-intelligent and complex actuation switches. Herein, we reported on the disassembly of orderly and rigid starch helical covalent structures, and their subsequent reassembly into a hierarchical supramolecular gel composed of nanocluster aggregates, integrating supramolecular interactions of three different scales. The incorporation of photo-sensitive FeIIITA, a complex of trivalent iron ions and tannic acid, significantly enhances the photo-responsive strain capacity of the hierarchical supramolecular gel. The supramolecular gel exhibits its features in a rapid light-responsive rate of hardness and viscosity, enabling the actuation of objects within 22 s under light exposure when employed as a remote actuation switch. Meanwhile, this actuation mechanism of the hierarchical supramolecular gel also has a promising perspective in precise control, identifying and actuating one of the two objects in distances of 0.8 mm even smaller scales. Our work provides a reliable reference for replacing complex actuation switches with intelligent materials for remote, rapid, and accurate actuation, and offers valuable insights for actuation in harsh and vacuum outdoor environments.

Eco-Friendly Energy Efficient Classrooms and Sustainable Campus Strategies: A Case Study on Energy Management and Carbon Footprint Reduction

This research paper presents a comprehensive study on energy management and carbon footprint reduction in an educational institutional campus. It focuses on implementing energy-efficient technologies and practices to minimize energy consumption and environmental impact. The study encompasses four cases, each addressing different aspects of energy use in a university setting, including the installation of LED lighting, programmable remote switches, and high-efficiency air conditioning systems. The methodology involves a detailed analysis of energy consumption patterns, using smart energy meters and theoretical calculations. Case I establishes a baseline energy consumption, while subsequent cases implement energy-saving measures. Case II involves replacing traditional tube lights with energy-efficient LED lights, resulting in considerable energy savings. Case III extends these savings further by integrating programmable remote switches mapped with student timetables. Finally, Case IV proposes the replacement of older air conditioning units with 25 SEER models, leading to significant reductions in energy use. The results highlight the effectiveness of these interventions. Case II achieves a 66.67% energy saving, while Case III yields up to 77.78% energy saving in lighting and 33.34% in air conditioning. In Case IV, the adoption of high-efficiency air conditioners can result in a 52% energy saving during teaching weeks. The economic benefits of these measures are substantial, with cost savings per classroom ranging from 7.65% in Case II to 53.46% in Case IV. Moreover, the environmental impact of these energy conservation techniques is substantial. The study reports reductions in carbon emissions from 14.71metric tons of carbon dioxide equivalent (MT CO2e) in base Case I to 6.85 MT CO2e in Case IV. The overall carbon emission reductions for Cases II, III, and IV are 7.61%, 36.37%, and 53.43%, respectively. This study demonstrates the profound impact of integrated energy management strategies in reducing the carbon footprint and energy consumption in educational institutions, offering a model for sustainable and economically viable operations.

A MILP model for optimal switch placement to enhance power distribution system performance in normal and hurricane conditions

Severe hurricanes can inflict significant damages in the order of several times the common network failures on both the distribution companies and consumers. Network reconfiguration and condition-based switching are the common actions for enhancing distribution network performance in both normal and emergency conditions. In this paper, a novel approach is presented for simultaneous improvement in resiliency, reliability, and power losses. A practical strategy is proposed by considering the coordination between load restoration and repair of damaged lines in optimal switch placement problems. The use of both remote-controlled switches (RCS) and manual switches (MS) as well as considering practical constraints related to line repair and load restoration leads to the increased number of decision variables and consequently the degraded performance of meta-heuristic methods to obtain the global optimum solutions, especially for larger scale networks. Therefore, the proposed approach uses the exact method of MILP to solve the optimization problem. In this context, the uncertainty related to damage status and repair time of lines during High-Impact Low-Probability (HILP) events is the main challenge in linear modeling of the problem for which new methods are provided in the study. The programming is coded in MATLAB and tested on a modified IEEE 33-bus network.

Smart airbag vest with integrated light turn signaling and location tracking

Research on road safety is continuously developing with the applications of sensors and technologies. Another area that draws the attention of the developers for road safety are in the road accident response. As the number of riders and cyclists increase, so do the accidents particularly at night where visibility is limited. This study presents a method of integration of inflatable safety vests for riders with light emitting diode LED signaling strips embedded in its front and back, and sensors to send the location of the rider when an accident happens. The LED strips are controlled using a wireless remote switch to make the rider more visible other than that embedded in the motorcycle or bicycle. The airbag will activate once an accident occurs and or the rider is detached from the motorcycle. A force-sensitive resistor (FSR) is used as a triggering device attached to the vest when an accident happens where a global positioning system (GPS) module will send the location and a map to a specific mobile number for response. Three trials were conducted to test the functionality of the LED lights for signaling. The device functioned well, that both the left, right, and standby mode were activated. The functionality of the location tracker is also tested in three different locations. The FSR was triggered and it gave the exact location by sending the coordinates and a link to view it on google maps with an average transmit and receive time of 3 seconds. It is recommended that the prototype be developed using light-weight materials and batteries.

Networked Microgrids: A Review on Configuration, Operation, and Control Strategies

The increasing impact of climate change and rising occurrences of natural disasters pose substantial threats to power systems. Strengthening resilience against these low-probability, high-impact events is crucial. The proposition of reconfiguring traditional power systems into advanced networked microgrids (NMGs) emerges as a promising solution. Consequently, a growing body of research has focused on NMG-based techniques to achieve a more resilient power system. This paper provides an updated, comprehensive review of the literature, particularly emphasizing two main categories: networked microgrids’ configuration and networked microgrids’ control. The study explores key facets of NMG configurations, covering formation, power distribution, and operational considerations. Additionally, it delves into NMG control features, examining their architecture, modes, and schemes. Each aspect is reviewed based on problem modeling/formulation, constraints, and objectives. The review examines findings and highlights the research gaps, focusing on key elements such as frequency and voltage stability, reliability, costs associated with remote switches and communication technologies, and the overall resilience of the network. On that basis, a unified problem-solving approach addressing both the configuration and control aspects of stable and reliable NMGs is proposed. The article concludes by outlining potential future trends, offering valuable insights for researchers in the field.

A high-performance triboelectric nanogenerator with dual nanostructure for remote control of switching circuit.

Preparing nanostructured surfaces has been considered an effective method to improve the output of triboelectric nanogenerators (TENGs), but how to quickly prepare materials with a nanostructured surface for TENGs has always been a challenge. Here, polypropylene nanowires and electrospun nylon 11 nanofibers were successfully prepared through a simple and time-saving method with a high success rate. Compared with a flat TENG, the output performance of a dual nanostructured TENG is enhanced by more than 5 times. After 1H,1H,2H,2H-perfluorooctyl trichlorosilane was assembled on the surface of the polypropylene film, the dual nanostructured TENG achieved the maximum output with the short-circuit current, output voltage, and charge density of 63.3 μA, 1135 V and 161.5 μC m-2, respectively. Compared with a planar structured TENG, the short-circuit current and output voltage were enhanced by about 18 times, and the charge density was increased by about 36 times. In addition, the TENG showed good working stability with almost no decrease in output after continuous operation for 193 000 cycles. The electricity generated by this TENG can successfully light up 1280 LEDs and continuously power a multi-functional electronic watch. Finally, the triboelectric signal generated by this TENG was used to control an optocoupler switch, indicating good application prospects in a remote control switching circuit.

Integration of a Smart Remote Controlling System with Electrical Appliances in Order to Optimize the Usage and to Develop an Energy Efficient System

Electricity is a powerful tool and must needed recourse of energy of all time in life existence since its invention. Its optimum utilization is a need of the era where various measures are taken on controlling methods by some enforced and imposed ways, we discuss a smart system which works to control unnecessary wastage of resources by keeping a time-to-time check on the system can be collaborated with a smart alert system. The idea is to not to control the usage but to curb the wastage for the optimum and efficient use of the available resources. In this project we proposed a smart system in which a signal will be send to mobile phone first if there is no human presence detected. After getting alert of human absence, electrical appliances can be switched OFF through mobile phone. This Idea is helpful when at the same working time some rooms are in use and some rooms are unused. So, by remote controlled switching of the appliances, electricity can be saved. This control can be done from the 25-20 meters range so in this case no need to approach the room manually to operate the switches. The objective of the project is to model a system to optimize the use of available resources for meeting the energy needs by saving energy while it is not under use. In this way a huge amount of energy can be saved. This will not only reduce the electricity bill but it will promote the optimum utilization of energy sources. Remote controlling of electrical appliances through a smart mobile system also restates the human nature of laziness in switching OFF appliances while they are not in use so it has a wide use in domestic’s field also.

Towards an interpretable data-driven switch placement model in electric power distribution systems: An explainable artificial intelligence-based approach

The fault management process is facilitated by equipping power distribution systems with automated devices, especially remote-controlled switches (RCSs). Although RCS plays a key role in improving the system's reliability, it imposes significant investment, installation, and maintenance costs. Hence, RCSs should be optimally located in distribution feeders for the highest profit. In previous works, reliability-oriented mathematical optimization models have been formulated to reach this goal. However, the number of test solutions exponentially grows with the problem size to find the globally optimal solution. This paper uses machine learning to propose a scalable and easy-to-implement model for optimal switch placement in real power distribution systems. At first, the features of candidate points for installing RCSs are introduced. Then, a learning model is applied to deeply explore the relationship between these features and optimal locations for installing RCSs. After training, the learning-based surrogate model directly determines the optimal RCS placement strategy in real power distribution systems by leveraging knowledge gained from past experiences. Simulation results demonstrate that the proposed surrogate model is approximately 29 times faster than the integer programming-based mathematical model, without a significant loss of accuracy, when implemented on a modified 11 kV network connected to Bus 4 of the Roy Billiton test system. This paper also employs explainable artificial intelligence (XAI) tools to select the most important features, where the Hamming loss is decreased by approximately 5%.

Fueling the seaport of the future: Investments in low‐carbon energy technologies for operational resilience in seaport multi‐energy systems

AbstractThe ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios.

Protection system planning in distribution networks with microgrids using a bi-level multi-objective and multi-criteria optimization technique

Microgrids are able to improve several features of power systems, such as energy efficiencies, operating costs and environmental impacts. Nevertheless, microgrids’ protection must work congruently with power distribution protection to safely take all advantages. This research contributes to enable their protection by proposing a bi-level method to simultaneously solve the allocation and coordination problems, where the proposed scheme also includes local protections of distributed energy resources. The uncertainties associated with generation and loads are categorized by the k-means method, as well. The non-dominated sorting genetic algorithm II is employed in the upper-level task to solve the protection and control devices allocation problem with two opposing objectives. In the lower-level task, a genetic algorithm ensures their coordination. Protection devices include reclosers and fuses from the network, and directional relays for the point of common coupling of microgrids, while control devices consist of remote-controlled switches. In contrast to related works, local devices installed at the point of coupling of distributed generation units are considered as well, such as voltage-restrained overcurrent relays and frequency relays. The optimal solution for the decision-maker is achieved by utilizing the compromise programming technique. Results show the importance of solving the allocation and coordination problems simultaneously, achieving up to $25,000 cost savings compared to cases that solve these problems separately. The integrated strategy allows the network operator to select the optimum solution for the protective system and avoid corrective actions afterward. The results also show the viability of the islanding operation depending on the decision maker's criteria.

Implementation of Remote Control for the AM 524 Antenna Amplifier Unit System in SAC Chambers

In the rapidly evolving landscape of modern technology, particularly in telecommunications and pervasive computerization across diverse sectors, the value of information has soared, becoming the linchpin of success in politics and business alike. With the majority of information now flowing through various computing devices, safeguarding them from unauthorized interception has assumed paramount importance. A critical threat in this context emanates from unintentional electromagnetic emissions generated by these devices. Under favorable conditions, these emissions can be exploited by unauthorized entities to reconstruct processed information, a phenomenon known as electromagnetic infiltration. Such emissions, correlated with useful information and conducive to its reconstruction, are termed revealing emissions, with the enabling process labelled as electromagnetic information leakage. This article presents the design and construction of a remote control system for managing antenna amplifier blocks within the AM 524 antenna system, dedicated to investigating information leakage from multimedia devices. The system facilitates remote switching of the five inputs on antenna amplifiers GX 525, GX 526, and GX 527 from a PC, utilizing specialized software. The authors provide an overview of the AM 524 antenna system, elucidate the design concept behind the remote control system, and highlight the central component—the ADAM 6052 module. Additionally, the article introduces the controlling software. It encompasses the device’s construction, including component details, connection schematics, and images of the assembled system, along with a verification process confirming its operational accuracy. Furthermore, the article outlines the application of the proposed solution in assessing the effectiveness of shielding within SAC chambers, employing the measurement methodology specified in accordance with the EN 50147-1:1996 standard. This additional information underscores the practical utility and relevance of the presented remote control system in the context of electromagnetic shielding evaluation for secure environments. Additionally, to assess the effectiveness of the proposed commutator solution, measurements were conducted to evaluate the shielding efficiency of the SAC chamber using a modified coaxial cable. The results of the shielding efficiency of the SAC chamber measurements for the proposed and classical solutions are also presented.

Untethered kirigami soft robots with programmable locomotion

Kirigami can induce shape transformations in planar and nonplanar geometry by rational cut design, significantly increasing the kinematics degree of freedom. Here, we exploit kirigami metamaterials and hard-magnetic actuation to design untethered soft robots. The kirigami soft robot, consisting of slit perforated kirigami patterns with embedded hard-magnetic disks in each facet, exhibits modularity, scalability, and programmable locomotion. By varying the magnetization arrays, the kirigami soft robots show diverse static and dynamic behaviors, which are systematically studied by experiments and FEM. We demonstrate multi-module soft robots with programmable locomotion, where directional locomotion is generated by a synergistic effect and circular motion is realized by the asymmetric pattern. Active and passive environmental adaptabilities and multifunctionalities are shown, including passing over gaps, active obstacle avoidance, moving over various substrates, carrying loads, remote circuit switches, and amphibious motions by bistability. This work paves the way to design untethered soft robots with programmable motions and multifunctionalities.

Enhancing distribution system resilience against extreme disasters considering sequential action of multi-type switches

With the increasing frequency and intensity of extreme disasters, enhancing distribution system (DS) resilience has been an urgent need for smart grid. Among various resilience enhancement measures, network reconfiguration is the most commonly used one. Multiple switches are involved in distribution network reconfiguration, e.g., circuit breakers (CBs), fuses (FUs), remote-controlled switches (RCSs), and manual switches (MSs). According to the characteristics of various switches, it is vital to establish an analytical switch action model for generating feasible and effective DS resilience enhancement strategies. In this paper, an analytical model is developed to characterize the automatic tripping process of switches under multiple faults caused by extreme disasters. A novel DS resilience enhancement method is further proposed, which considers the sequential actions of multiple types of switches to enhance the prevention and rapid restoration capability of DSs against extreme disasters. Before the strike of a disaster, the topology of DS is reconfigured based on RCSs, MSs, and CBs to improve the survivability of loads. The automatic tripping process of CBs and FUs is simulated when faults occur. After the disaster, the DS is reconfigured based on RCSs and CBs after events to isolate faults and restore critical loads. The proposed method is formulated as a mixed-integer linear programming (MILP) problem, which can be efficiently solved using commercial solvers. Case studies conducted on the modified IEEE 123-bus test systems demonstrate the effectiveness of the proposed method for DS resilience enhancement.

Robust post-disaster repair crew dispatch for distribution systems considering the uncertainty of switches

After natural disasters’ strike, the remote-controlled switch plays a key role in network reconfiguration to restore the critical load. However, the status of these switches is hardly acquired in case of cyber malfunctions. This paper proposes a robust repair crew dispatch approach for distribution systems considering the uncertainty of remote-controlled switches. The proposed approach is formulated as a tri-level robust optimization model to obtain the repair crew dispatch strategy applicable to possible fault scenarios. The system operator determines the repair crew dispatch scheme at the first level. At the second level, the real-time status of switches under different combinations of faults and repair processes is modeled and the worst fault scenario is calculated. Based on the real-time status of switches, the operator utilizes distributed generators and network reconfiguration to restore loads. A nested column-and–constraint generation (NC&CG) algorithm is customized for the proposed robust model to achieve the optimal solution. Simulation results on the IEEE-33 node distribution test system and the IEEE 123-node system show the proposed approach can effectively reduce the maximum system loss and the NC&CG algorithm can significantly reduce the computing time.