Line Switching Research Articles

Fault Line Selection of Small Current Grounding System Research Based on Zero Sequence Circuit Current Phase

Abstract This paper investigates fault line selection in small current grounding systems, focusing on the zero sequence current phase characteristics. Small current grounding systems, prevalent in medium voltage distribution networks, face challenges in fault detection due to minimal fault currents during single status phase grounding faults. Traditional methods relying on manual line switching and zero sequence voltage monitoring are inefficient and can induce overvoltage. This study categorizes fault line selection techniques into three approaches: steady-state fault information, transient information, and modern signal processing technology. The analysis of zero sequence currents in non-grounded systems reveals that fault line zero sequence currents equal the sum of system capacitive currents, flowing opposite to those in non-fault lines. Additionally, transient signal analysis shows that these signals provide more robust information for fault detection. MATLAB simulations validate the theoretical models, demonstrating that zero sequence current direction and amplitude effectively identify fault lines. The results confirm the efficacy of combining steady-state and transient signal analyses for accurate fault line selection, contributing to enhanced safety and reliability in power distribution networks. This research offers practical insights and tools for engineers, improving fault management and reducing potential economic losses in small current grounding systems.

Synergistic effect between denosumab and immune checkpoint inhibitors (ICI)? A retrospective study of 268 patients with ICI and bone metastases

BackgroundBone metastasis is a significant concern in advanced solid tumors, contributing to diminished patient survival and quality of life due to skeletal-related events (SREs). Denosumab (DMAB), a monoclonal antibody targeting the receptor activator of nuclear factor kappa-B ligand (RANKL), is used to prevent SREs in such cases. The RANK/RANKL axis, crucial in immunological processes, has garnered attention, especially with the expanding use of immune checkpoint inhibitors (ICI) in modern oncology. ObjectiveOur study aims to explore the potential synergistic antitumor effects of combining immunotherapy with denosumab, as suggested by anecdotal evidence, small cohort studies, and preclinical research. MethodsWe conducted a retrospective analysis using the IMMUCARE database, encompassing patients receiving ICI treatment since 2014 and diagnosed with bone metastases. We examined overall survival (OS), progression-free survival (PFS) and switch of treatment line based on denosumab usage. Patients were stratified into groups: without denosumab, ICI followed by denosumab, and denosumab followed by ICI. Survival curves and multivariate Cox regression analyses were performed. ResultsAmong the 268 patients with bone metastases, 154 received treatment with ICI alone, while 114 received ICI in combination with denosumab at some point during their oncological history. No significant differences were observed in overall survival (OS) or progression-free survival (PFS) between patients receiving ICI monotherapy and those receiving ICI with denosumab (p = 0.29 and p = 0.79, respectively). However, upon analyzing patients who received denosumab following ICI initiation (17 patients), a notable difference emerged. The group receiving ICI followed by denosumab exhibited a significant advantage compared to those without denosumab (154 patients) or those receiving denosumab before ICI initiation (72 patients) (p = 0.022). ConclusionThis retrospective investigation supports the notion of potential benefits associated with sequential administration of ICI and denosumab, although statistical significance was not achieved. Future studies, including prospective trials or updated retrospective analyses, focusing on cancers treated with first-line immunotherapy, could provide further insights into this therapeutic approach.

Reconfigurable origami-inspired multistable metamorphous structures.

Origami-inspired metamorphous structures can adjust their shapes and mechanical behaviors according to operational requirements. However, they are typically composed of nonrigid origami, where required facet deformation complicates actuation and makes them highly material dependent. In this study, we present a type of origami metamorphous structure composed of modular bistable units, each of which is a rigid origami. The elasticity within the origami creases and switching of mountain and valley crease lines enable it to have bistability. The resultant metamorphous structure has multistability, allowing it to switch among multifarious configurations with programmable profiles. This concept was validated by potential energy analysis and experiments. Using this concept, we developed a robotic limb capable of both lifting and gripping through configuration changes. Furthermore, we used the origami units to construct a metamaterial whose properties could change with the variation of configurations. These examples demonstrate the concept's remarkable versatility and potential for many applications.

A Parameter Optimization Design Method for Single-Phase Dual Active Bridge AC-DC Converter

The single-stage dual active bridge (DAB) AC-DC converter has the advantages of high power density, low cost, and simple control; it has a broad potential for application in the field of onboard chargers (OBC). However, the lack of fast and accurate quantitative parameter optimization design methods in single-stage DAB AC-DC converters limits the overall efficiency of the converter. Based on the above problem, in order to improve the overall operating efficiency of the converter by optimizing the parameter transformer ratio and power inductance, this paper proposes a parameter design method considering a multi-timescale strategy by combining the steady-state analysis model of the converter in the line cycle and switching cycle and step-by-step reducing its design space through the constraints on the parameters. The first step is to obtain a safe design space for the parameters under the converter’s transmitted power and current stress constraints. The second step obtains the optimization design space of the parameters under the optimization of conduction loss and switching loss of the converter. Finally, the optimal parameters are determined by the loss analysis model. The proposed parameter optimization method entirely takes into account the steady-state characteristics of the DAB AC-DC converter during the line cycle, and the step-by-step constraints greatly accelerate the parameter design process. In addition, the proposed parameter optimization design method applies to all types of single-stage DAB AC-DC converters, which can be well applied to engineering practice.

Fingerprint Based Circuit Breaker

In the current scenario, the process of requesting staff personnel to switch off electric lines for repair or maintenance poses a significant risk of miscommunication, potentially endangering human life. This paper presents a novel system designed to mitigate this risk by offering a secure mechanism for line switching. The system employs a fingerprint sensor for authentication to restrict access, ensuring that only authorized personnel can operate the lines. Upon requesting access through the fingerprint sensor, if the fingerprint matches the stored record, the system grants access, enabling the line to be switched on/off as necessary. An LCD display provides real-time feedback on access status—whether access is granted or denied. Additionally, a relay is utilized to connect or disconnect the load, indicating its status as on or off in accordance with the system's operation. A microcontroller orchestrates all system tasks and must be programmed to respond to authorized user requests. Overall, this proposed system aims to minimize human error and enhance safety for electric line maintenance personnel

Optimized Unsymmetrical Per-Phase Droop for Soft Line Switching of Reconfigurable Unbalanced Inverter-Based Islanded Microgrid

Optimized Unsymmetrical Per-Phase Droop for Soft Line Switching of Reconfigurable Unbalanced Inverter-Based Islanded Microgrid

The Post-Buckling Behavior of a Beam Constrained by Nonlinear Springy Walls

Abstract The post-buckling behavior of a beam that is subjected to lateral constraints is of relevance to a range of medical and engineering applications, such as endoscopic examination of internal organs, the insertion of a guidewire into an artery in-stent procedures, root growth, deep-drilling, and more. In this paper, we address a disconnect between the existing literature and the reality of these systems, in which the lateral constraints are flexible and experience nonlinear deformations. As a step towards bridging this gap, we consider a beam undergoing planar deformations that is laterally constrained by a nonlinear springy wall, i.e., a wall that is laterally pushed by the beam against a nonlinear spring. Based on a simplified mathematical model, we obtain closed-form analytical solutions, which provide valuable insights and intuition. For example, we show that important features of the behavior, such as the transition from point contact to line contact and switching to the next mode, are dictated solely by a non-dimensional force, regardless of all other parameters of the system, and that the full description of the behavior is possible by means of two non-dimensional quantities that describe the relative stiffness of the nonlinear spring compared to that of the beam. The results also highlight the fundamental differences between the behavior with a stiffening spring or with a softening spring, such as the number of attainable modes and the monotonicity of the overall force–displacement relation. These results are then validated by experiments.

Transmission line switching spread modelling of synchrophasor smart grid network with load uncertainty inspired by epidemic model: a study of reliability and vulnerability

ABSTRACT Monitoring and controlling of transmission lines become easier in real time with synchrophasor measurements technology. Phasor Measurement Units (PMUs) provide the time-stamped synchrophasor data of the system buses and transmission lines with a high reporting rate. In this paper, a mathematical model is implemented that allows the simulation of the characteristics of the spread of transmission line switching with load variations. In the model, the transmission lines are divided into three parts defined as susceptible, infected and recovered transmission lines inspired from epidemic model. In this paper, Reliability Test System (RTS − 1979) is divided into three zones to simulate the line switching spread behaviour with load variation for reliability and vulnerability analysis of the synchrophasor smart grid network. The anomaly exists with synchrophasor measuring devices due to cyber intrusion in communication network or failure of devices makes the system observable with the characterization of vulnerable behaviour of transmission lines.

Reinforcement-Learning-Based Proactive Control for Enabling Power Grid Resilience to Wildfire

Industrial electric power grid operation subject to an extreme event requires decision-making by human operators under stressful conditions. Decision making using system data informatics under adverse dynamic events, especially if forecasted, should be supplemented by intelligent proactive control. Power transmission system operation during wildfires requires resiliency-driven proactive control for load shedding, line switching, and resource allocation considering the dynamics of the wildfire and failure propagation to minimize the impact on the system. However, the possible number of line and load switching in an extensive industrial system during an event make traditional prediction-driven and stochastic approaches computationally intractable, leading operators to often use pre-planned or greedy algorithms. In this work, we model and solve the proactive control problem as a Markov decision process and introduce an integrated testbed for spatio-temporal wildfire propagation and proactive power-system operation. Our approach allows the controller to provide setpoints for all generation fleets in the power grid. We evaluate our approach utilizing the IEEE test system mapped onto a hypothetical terrain. Our results show that the proposed approach can help the operator to reduce load outage during an extreme event. It reduces power flow through lines that are to be de-energized, and adjusts the load demand by increasing power flow through other lines.

Power System Operation Mode Calculation Based on Improved Deep Reinforcement Learning

Power system operation mode calculation (OMC) is the basis for unit commitment, scheduling arrangement, and stability analyses. In dispatch centers at all levels, OMC is usually realized by manually adjusting the parameters of power system components. In a new-type power system scenario, a large number of new energy sources lead to a significant increase in the complexity and uncertainty of a system structure, thus further increasing the workload and difficulty of manual adjustment. Therefore, improving efficiency and quality is of particular importance for power system OMC. This paper first considers generator power adjustment and line switching, and it then models the power flow adjustment process in OMC as a Markov decision process. Afterward, an improved deep Q-network (improved DQN) method is proposed for OMC. A state space, action space, and reward function that conform to the rules of the power system are designed. In addition, the action mapping strategy for generator power adjustment is improved to reduce the number of action adjustments and to speed up the network training process. Finally, 14 load levels under normal and N-1 fault conditions are designed. The experimental results on an IEEE-118 bus system show that the proposed method can effectively generate the operation mode under a given load level, and that it has good robustness.

Control strategies for active distribution networks based on soft open point

The application of SOP instead of traditional tie line switches in distribution networks can im-prove the controllability, flexibility, and renewable energy accommodation of the distribution grids. Compared with traditional tie line switches, SOP have high costs and large land occupation. When power transfer is not considered, the location and capacity of SOP can be optimized through planning algorithms to reduce the overall costs. However, the main function of tie line switches is power transfer. If SOP as alternative devices do not meet this requirement, their ex-tensive application will be restricted. Therefore, this paper designs the direct current volt-age-power smooth switching control strategy, phase angle pre-synchronization control strategy, and voltage support control strategy based on the parallel structure of SOP and tie line switches to ensure stable operation during the power transfer process, through this complete control strategy, smooth switching can be achieved to keep the DC voltage stable during the switching process, effectively suppress the impulse current and maximize the utilization of SOP capacity Simulations on the SIMULINK plat-form verify the feasibility of the control strategies.

Optimal scheduling of BESS for congestion management considering reliability and OTS

The present research explores transmission congestion control in Battery based Energy Storage Systems (BESS) integrated grids using Optimal Transmission Switching (OTS). The oversimplification of underlying assumptions in prior OTS-based congestion management strategies leads to excessive line switching which is undesirable. Hence, a novel reliability constrained alternating current optimal power flow (AC-OPF) based OTS is presented to mitigate the line congestion in the BESS integrated grids. The suggested approach is solved to acquire the OTS solution for 24 h time frame with the primary goal of minimising generating costs subjected to ac power flow equality, BESS, reliability, and transmission congestion constraints. The proposed approach makes use of the integer variable to represent the transmission switching operations and is solved by using a mixed-integer non-linear programming (MINLP) solver. The inclusion of reliability constraints ensures the system reliability by limiting the value of load failure probability to a pre-specified limit. The feasibility of this approach is validated by testing it on a standard IEEE test system for various loading scenarios. The results exhibit that coordinated charging/discharging of BESS supports reducing the number of lines switchings required for congestion management compared to the existing approaches, substantially.

Tracking the EMT-like phenotype switching during targeted therapy in melanoma by analyzing extracellular vesicle phenotypes

Melanoma continues to be a leading cause of mortality among skin cancers. Despite advancements in targeted therapy, patients frequently develop resistance, leading to disease progression within a year. This resistance may result from the epithelial-to-mesenchymal transition (EMT)-like phenotype switching of melanoma cells. Tracking EMT-related phenotypic changes on extracellular vesicles (EVs) has potential to inform early about response to targeted therapy and melanoma progression. However, the knowledge on protein biomarkers carried by melanoma EVs involved in the EMT-like process remains unexplored. Herein, we present a biosensor integrating surface-enhanced Raman scattering and alternating current electrohydrodynamics-induced nanomixing enhancement, for sensitive detection of EMT-associated biomarkers on EV surfaces during targeted therapy. This biosensor successfully tracks the EMT-like phenotype switching in melanoma cell lines treated with mitogen-activated protein kinase inhibitor (MAPKi). Longitudinal monitoring of patients who receive MAPKi therapy and develop resistance, our biosensor shows its ability to identify the EMT-like phenotype switching on circulating EVs. This ability potentially can be leveraged to predict the development of resistance to targeted therapy, allowing for timely intervention and personalized treatment strategies.

Coordinated Optimization of Emergency Response Resources in Transportation-Power Distribution Networks Under Extreme Events

The proliferation of electric vehicles (EVs) and the increasing interdependence across power distribution networks (DNs) and transportation networks (TNs) have increased the complexity and vulnerability of the two systems in extreme circumstances. As the interdependence of two infrastructures tightens over time, it is viewed as a dire necessity to strengthen the resilience of the coordinated transportation-power distribution networks (TDNs) against natural disasters. This paper constructs a coordinated optimization method of TN traffic link reversing, DN line switching, and fast charging pile management, to improve the TDN performance in the emergency response stage after disasters. A dynamic TN model and a multi-period DN model are integrated in TDN modeling to capture flow propagations and state variations among time intervals. The coordinated optimization for TDN emergency response is designed as a mixed-integer nonlinear programming (MINLP) problem with high-order objective functions and nonlinear constraints to minimize TN travel costs and DN active and reactive power shortages. An accuracy-aware adaptive piecewise linearization approach combined with Gray code-based encoding is utilized to improve the computational efficiency for solving the TDN optimization problem. Numerical simulations show that the TDN performance is enhanced by coordinating various DN and TN resources, as compared with those of separate and conventional topology controls. The proposed TDN solution method has significantly reduced the computation time for managing extreme conditions while guaranteeing the accuracy of the results as compared with those of the nonlinear model and the linearized model by uniform piecewise linearization.

Joint Topology and State Estimation Using TTU Monitoring Data Considering Three-Phase Imbalance

A grand challenge for operators to develop optimal controls at the distribution level lies in how to obtain the real-time network topology and operation state in lack of specialized high precision monitoring devices, especially with high penetration of distributed renewable energy. Driven by this motivation, this paper proposes a novel topology and operation state joint estimation framework based on the monitoring data from transformer terminal units (TTUs). In the framework, the bottom layer generates an equivalent network model and nodal voltage and current measurements with synchronized phase angles from the distribution network and the voltage and power measurement data from TTU. The middle layer formulates, linearizes and solves an optimization problem to fit the model with the measurements. A global piecewise linearization method is proposed to convert the original mixed integer quadratically constrained program (MIQCP) problem into a mixed integer linear program (MILP) problem. In the top layer, the line switch states and feeder power flows are estimated with the solution of the optimization problem. Case studies are conducted in test systems to verify the accuracy, efficiency and robustness of the proposed framework and show that the proposed framework yields obvious advantages over the existing approaches on the estimation accuracy when using TTU measurements.

Transmission Congestion Management via Node-Breaker Topology Control

A novel topology control algorithm is proposed here to reduce congestion and overloads, thereby improving security margins in a power network. The proposed heuristic relies on normalized squares of the line currents as a direct indicator of transmission line loading. The sensitivity of this measure with respect to breaker positions forms the basis of the proposed heuristic to select switching actions for a reconfigured network topology that reduces the congestion and overloads while holding generation dispatch essentially fixed. While many prior works have examined this class of problem for line switching actions (i.e., topology changes that insert or remove branches), bus-bar switching actions (topology changes that merge or split nodes/buses) have received less research focus. Here, both line switching and bus-bar switching are implemented using a detailed node-breaker representation of the network. The algorithm adopts a novel form of the AC power flow that allows sparse calculation and reduced computation time. Case studies demonstrate that the proposed approach efficiently reduces congestion and overloads in the base case and in contingency situations.

Resilience-oriented placement of multi-carrier microgrids in power systems with switchable transmission lines

Extreme events such as floods, hurricanes, earthquakes, and wildfires pose significant threats to the uninterrupted supply of electricity to consumers, as they can cause the failure of numerous power system components. The resilience of a power system is defined by its ability to withstand extreme events and continue meeting demand. While the placement of multi-carrier microgrids (MGs) in power systems can impact resilience, the literature lacks research on resilience-oriented placement. This paper aims to address this gap by proposing a resilience-oriented placement strategy for multi-carrier MGs, utilizing switchable transmission lines to enhance the resilience of power systems. The study focuses on a heat-power-hydrogen MG that obtains gas from a gas network, exchanges power with the main power system, and incorporates combined heat and power (CHP), electrolyzer, and thermal storage. The developed model employs a stochastic mixed-integer linear programming (MILP) approach, ensuring the attainment of the global optimum. Resilience is evaluated using the metric of expected load not supplied (ELNS). The results demonstrate that when the bus connected to the MG is isolated, the MG generates electricity through its CHP unit to meet local demand, reducing the total demand shed in the power system and improving system resilience. Specifically, the MG reduces ELNS from 4955.48 MWh to 2356.64 MWh, indicating a remarkable 52% improvement in ELNS. Furthermore, the study shows that transmission line switching further decreases ELNS from 2356.64 MWh to 848.68 MWh. Several experiments are conducted to analyze the sensitivity of power system resilience to the number of MGs, the MG-power system exchange limit, and the limit on gas import from the gas network.

Construction of redundant communications to enhance safety against communication interruptions during robotic remote surgery

It is important to ensure the redundancy of communication during remote surgery. The purpose of this study is to construct a communication system that does not affect the operation in the event of a communication failure during telesurgery. The hospitals were connected by two commercial lines, a main line and a backup line, with redundant encoder interfaces. The fiber optic network was constructed using both guaranteed and best-effort lines. The surgical robot used was from Riverfield Inc. During the observation, a random shutdown and restoration process of either line was conducted repeatedly. First, the effects of communication interruption were investigated. Next, we performed a surgical task using an artificial organ model. Finally, 12 experienced surgeons performed operations on actual pigs. Most of the surgeons did not feel the effects of the line interruption and restoration on still and moving images, in artificial organ tasks, and in pig surgery. During all 16 surgeries, a total of 175-line switches were performed, and 15 abnormalities were detected by the surgeons. However, there were no abnormalities that coincided with the line switching. It was possible to construct a system in which communication interruptions would not affect the surgery.

Application of the Wave Channels Method to Analyze the Switching Overvoltages in Energizing a High-voltage Cable Line

A study of cable line failures shows that a large number of faults occur in the connecting and terminal couplings of 110--500 kV power lines. Overvoltages caused by operational switching in the substation switchgear circuits contribute to the total number of failures. The switching overvoltage amplitude and frequency depend on the parameters of the source, switched circuits, and switching moment. The aim of the study is to identify the network and switched circuit parameters affecting the maximum overvoltage excited by energizing a 400 kV cable line and to determine the degree of their influence. The following factors are considered: switching phase, cable line length, source inductance, and line residual charge. The analysis was carried out by the wave channels method. To achieve this goal, an analysis model was developed in the EMTP-RV software environment, which made it possible to calculate the electromagnetic transients excited by cable line switching. The model has been verified with respect to the surge propagation velocity along a coaxial wave channel. Overvoltage calculations have shown that the switching phase and the line charge availability in the pre-switching operation mode have the most significant effect on the overvoltage value. The obtained study results apply to high-voltage electrical networks containing cable lines. The study results made it possible to quantify the degree to which the considered factors influence the overvoltages excited by switching 400 kV cable lines and to assess possible exceeding of the values permitted by the relevant standards, which will make it possible to have a preventive influence on the number of failures.

Fostering restoration and power delivery efficiency by distributed generators and line switches in electricity distribution network

ABSTRACT The distribution of power is being faced with challenges during and after extreme weather events. This contingent might cause a partial or full power blackout in the distribution territory. Hence, the restoration of the service is one of the key concerns of the utilities. A strategy is adopted to felicitate the power restoration process by the deployment of distributed generators (DGs) and line switches. A fuzzy-based system model is proposed to allocate line switches considering the impact of wind-driven extreme weather and the fault frequency character of the lines. The study further recommends an arrangement of dispatchable DGs in the sections of the distribution grid. A particle swarm optimization-based model is proposed for suitable capacity and location assessment of the DGs to foster the restoration of supply avoiding voltage and frequency disturbances in the developed sections of the grid. The results are further verified with the application of the grasshopper optimization algorithm on the multipurpose composite objective function. The proposed DG allocation approach escalates the network power loss reduction by 95.10%, improvement in average voltage stability level by 6.46%, and loadability margin enhancement by 37.37% when the DGs are operated in grid-connected mode. Moreover, power supply reliability is restored with successive employment of DG units. The proposed approach has been tested on an Indian 28-bus power distribution network. The outcome of the proposed approach is compared with existing DG allocation methods. The experiment confirms the credential of the proposed approach with better value addition in multiple objectives.