Abnormal System Conditions Research Articles

IoT based monitoring of distribution transformer

As transformer does not have any rotating parts hence it is called as static device, therefore it does not have mechanical losses, but internal stresses arose from abnormal system conditions like Over currents due to overloading on Transformer and short circuits, The faults can cause mechanical and thermal stresses inside the transformer winding and its connecting terminals. Thus transformer must be protected from above stresses. The aim of this project is to obtain real time data of transformer from remote places with the help of Internet of Things[ IOT] and then designing and implementing a Global system of Mobile communication [GSM] based technology to measure overvoltage, load current, and winding temperature. By measuring the condition of Transformer will help us to point out an any abnormalities before any serious damage that in turn leads to a greater credibility and significant cost savings

Microgrid-Based Small Modular Reactor for a High-Renewable-Energy Penetration Grid in Ghana

Achieving the necessary energy balance entails the capacity to adapt both power supply and demand, which is known as flexible operation. At present, the Ghana National Commission on Culture depends on a combination of well-coordinated measures designed to uphold the system’s integrity when confronted with abnormal system conditions stemming from significant disturbances within the system. The set of coordinated measures comprises manual (controlled load shedding) and automatic (Special Protection Schemes, Under-Frequency Load Shedding, Over-Frequency Control Scheme, scheme against voltage collapse, etc.) steps to control important system parameters to keep the power system stable and cascading effects leading to major blackouts. Ghana’s system suffers from voltage and frequency degradation as a result of a mismatch of power supply and demand; to maintain grid stability and avoid power outages, a flexible operation is required for real-time supply and demand balancing. SMRs, with their load-following capability, can adjust their output to match the change in demand. This research proposes a microgrid-based design for a high-renewable-energy penetration grid in Ghana with the inclusion of an SMR for voltage stability.

Examination of fast frequency response capacity requirements considering frequency ride-through capabilities in distributed generators with legacy inverters

Given the rapid increase in inverter-based distributed generators (IBDGs), their response and subsequent impacts on power system stability during abnormal power system conditions are becoming important. Recent events have shown that an unexpected loss of IBDGs triggered by their outdated frequency ride-through (FRT) capability can occur, which in turn can lead to a power system frequency below the secure operation region. As FRT characteristics of IBDGs are dependent on their time of installation and capability to update FRT parameters, IBDGs with different ride-through characteristics are mixed within the power system. In this study, the potential impacts of FRT capabilities of IBDGs with legacy inverters have been investigated. The analysis was conducted considering the penetration level of IBDGs and complying with FRT characteristics. Furthermore, the required amount of fast frequency response resources, which are generally provided by battery energy storage systems, was evaluated along with the secure operating envelope that can aid in future power system planning. Case studies on modified New England 10-machine test system and Korean power system were conducted to validate the effectiveness of the analysis.

A Sequential Generation Redispatch Algorithm to Ensure Power System Small Signal Stability under Low-Frequency Oscillations

Generation rescheduling is a major action against abnormal system conditions such as small signal instability. The operating point of the power system impacts the small signal stability; therefore, this article proposes a novel sequential generation rescheduling model as a preventive control against low-frequency fluctuations. An optimal power flow (OPF) problem is utilized to determine the base operating point. Then, in the process of improving the small signal stability, the modal analysis specifies the system stability status in each step, and the proposed second-order convex redispatch model defines the optimal direction of generation rescheduling. Small signal stability is considered a constraint in this model. Using a sensitivity analysis, system generators and system buses are divided into two increasing and decreasing groups, which are included in the model according to their contribution coefficients in damping improvement. Finally, the alternating current (AC) power flow analysis provides the subsequent operating points. The redispatch model is solved using the quadratic programming algorithm, and the Newton algorithm is used to manage the nonlinear and nonconvex characteristics of the power flow model. The proposed method is simulated over the IEEE 9, 39, and 118 bus test systems. It is shown that the proposed method increases the damping of the power system from the unstable state to the desired condition by controlling the operating point.

Progress in Stimuli-Responsive Biomaterials for Treating Cardiovascular and Cerebrovascular Diseases.

Cardiovascular and cerebrovascular diseases (CCVDs) describe abnormal vascular system conditions affecting the brain and heart. Among these, ischemic heart disease and ischemic stroke are the leading causes of death worldwide, resulting in 16% and 11% of deaths globally. Although several therapeutic approaches are presented over the years, the continuously increasing mortality rates suggest the need for more advanced strategies for their treatment. One of these strategies lies in the use of stimuli-responsive biomaterials. These "smart" biomaterials can specifically target the diseased tissue, and after "reading" the altered environmental cues, they can respond by altering their physicochemical properties and/or their morphology. In this review, the progress in the field of stimuli-responsive biomaterials for CCVDs in the last five years, aiming at highlighting their potential as early-stage therapeutics in the preclinical scenery, is described.

Qualification of Hydraulic Analysis Models for Optimal Design of Water Distribution Systems

The hydraulic analysis of water distribution systems (WDSs) is divided into two approaches, namely, a demand-driven analysis (DDA) and a pressure-driven analysis (PDA). In DDA, the basic assumption is that the nodal demand is fully supplied irrespective of the nodal pressure, which is mainly suitable for normal operating conditions. However, in abnormal conditions, such as pipe failures or unexpected increases in demand, the DDA approach may cause unrealistic results, such as negative pressure. However, despite these realistic hydraulic analysis approaches for WDSs being emphasized in the design process, this consideration was lacking in the design aspect. Therefore, in this study, the designs by the DDA-based design model and PDA-based design model are compared, and their design characteristics are analyzed to identify the efficiency of the WDSs design under abnormal system conditions. The developed PDA model was applied to three networks (a well-known benchmark system and a real-life WDN), and the results showed that the proposed model is superior to other reported models when dealing with negative pressure under abnormal conditions. In addition, the optimal design of WDN considered PDA is presented, and the optimal construction cost is decreased to increase the percentage of PDA.

Trustworthy Enhancement for Cloud Proxy based on Autonomic Computing

Aiming to improve Internet content accessing capacity of the system, cloud proxy platforms are used to improve the visiting performance in network export environment. Limited by complexity of cloud proxy system, trustworthy guarantee of cloud system becomes a difficult problem. Considering the self-government of autonomic computing, it could enhance cloud system trustworthy and avoids system management security and reliable problems brought by complex construction. Based on the idea of self-supervisory, a mechanism to enhance security of cloud system was proposed in this paper. First, a trustworthy autonomous enhancement framework for virtual machines was proposed. Second, a method to extract linear relationship of monitoring items in the virtual machine based on ARX model was put forward. According to the mapping relation between monitoring items and system modules, an abnormal module positioning technology based on Naive Bayes classifier was developed to realize self-sensing of abnormal system conditions. Finally, security threats of virtual machines including malicious dialogue and buffer memory of hot attacks were tested through experiments. Results showed that the proposed trustworthy enhancement mechanism of virtual machines based on autonomic computing could achieve trustworthy enhancement of virtual machines effectively and provide an effective safety protection for the cloud system.

Widely linear least mean kurtosis‐based frequency estimation of three‐phase power system

We propose a widely linear (augmented) least mean kurtosis (WL-LMK) algorithm for robust frequency estimation of three-phase power system. The negated kurtosis-based algorithms are most celebrated for their computational efficiency and strong robustness against wide range of noise signals which can overcome the inherent performance degradation faced by the well-known minimum mean square error-based algorithms in noisy environments. The proposed widely linear LMK estimation technique utilises all second-order statistical information in the complex domain C for processing of non-circular complex-valued signals. The three-phase power system signal, modelled through Clarke's αβ transformation, is circular for balanced and non-circular for unbalanced systems, based on which, the proposed WL-LMK algorithm is able to achieve improved frequency estimation under unbalanced and other abnormal system conditions. Its estimation performance is evaluated for several cases that encounter in the day-to-day operation of power system. It is observed from simulation studies of synthetic and real-world power system data that the proposed WL-LMK algorithm exhibits superior estimation performance as compared to the standard linear complex LMK (CLMK) and the widely linear least mean square (WL-LMS) algorithms.

Phase angle error‐based maximum correntropy adaptation for frequency estimation of three‐phase power system

A robust technique based on maximum correntropy criterion (MCC) is proposed for frequency estimation in an unbalanced power system using error in phase angle. This is achieved by replacing the magnitude error used in the standard cost function of the MCC with the phase error and by extending the concept of the augmented (widely linear) complex statistics for the processing of unbalanced voltages and other abnormal system conditions. The idea emanates from the facts that: (i) useful information is primarily conveyed over the phase in power system frequency estimation, and (ii) the performance degradation of the well-known minimum mean squared error criterion based adaptive filters in impulsive noise environments can be overcome by the MCC due to the non-quadratic and higher order moments imbedded in its cost function. The proposed phase error-based MCC method also utilises all the second-order information within the complex valued system voltage through the Clarke's transformation. Simulation studies conducted using both synthetic and experimental data verify that the proposed algorithm provides better estimations compared to the considered algorithms.

Domain Adaptation for One-Class Classification: Monitoring the Health of Critical Systems Under Limited Information

The failure of a complex and safety critical industrial asset can have extremely high consequences. Close monitoring for early detection of abnormal system conditions is therefore required. Data-driven solutions to this problem have been limited for two reasons: First, safety critical assets aredesigned and maintained to be highly reliable and faults are rare. Fault detection can thus not be solved with supervised learning. Second, complex industrial systems usually have long lifetime during which they face very different operating conditions. In the early life of the system, the collected data is probably not representative of future operating conditions, making it challenging to train a robust model. In this paper, we propose a methodology to monitor the systems in their early life. To do so, we enhance the training dataset with other units from a fleet, for which longer observations are available. Since each unit has its own specificity, we propose to extract features made independent of their origin by three unsupervised feature alignment techniques. First, using a variational encoder, we impose a shared probabilistic encoder/decoder for both units. Second, we introduce a new loss designed to conserve inter-point spacial relationships between the input and the learned features. Last, wepropose to train in an adversarial manner a discriminator on the origin of the features. Once aligned, the features are fed to a one-class classifier to monitor the health of the system. By exploring the different combinations of the proposed alignment strategies, and by testing them on a real case study, a fleet composed of 112 power plants operated in different geographical locations and under very different operating regimes, we demonstrate that this alignment is necessary and beneficial.

ANALISIS PEMASANGAN FILTER PASIF DAN AKTIF TERHADAP KANDUNGAN HARMONISA DAN RUGI-RUGI DAYA GARDU DISTRIBUSI KA 2085 DI PT. PLN (Persero) DISTRIBUSI BALI RAYON MENGWI

Operation of nonlinear loads can cause harmonic distortion in the voltage and current waveforms that result in abnormal electrical system condition. Content THD (Total Harmonics Distortion) an excess flow can cause power quality systems become worse, thus causing the system power factor is lower. Active filter and Passive filter which aims to reduce harmonics that arise. Analysis THD simulation and measurement results in accordance with IEEE 519-2014 and analysis designing of a passive filter and active filter is right to suppress harmonic distortion. The analysis shows that the installation of active filters causes the current and voltage THD contents to comply with the standard IEEE 519-2014 standards is ?12% and 5%. The use of passive and active filters can reduce THDi content to 8.45% and 3.07%, respectively. While for THDv decreased respectively to 3.68% and 3.45% which already meet the IEEE 519-2014 standards. Power losses decreased respectively to 4.36 kW and 3.86 kW. Installation of active filters is better for reducing THD (Total Harmonics Distortion) and power losses in KA 2085 transformers.

Risk reduction in special protection systems by using an online method for transient instability prediction

Special protection systems (SPS) are designed to detect abnormal system conditions and initiate corrective action to mitigate the consequence of the abnormal conditions and provide acceptable system performance. Most of SPS are designed based on offline simulations. This may result in additional risk when system conditions differ from the offline simulations. To solve this problem, an online algorithm is proposed in this paper to predict transient instability based on the measurements of phasor measurement units (PMU). This algorithm is employed to design a generator rejection scheme (GRS) which acts according to the online instability prediction. The proposed GRS is implemented on a test system; WSCC 9-bus system. Also, the power plant instability risk is calculated with the old GRS decided based on offline simulations and with the proposed GRS. Comparison between the results of the risk assessment reveals the effect of the proposed GRS on risk reduction.

Testing of complex IEC 61850 based substation automation systems

The integration of multifunctional intelligent substation devices (ISDs), in complex substation or power plant automation systems, requires the development of methods and tools for their testing that will ensure the correct operation of protection, control, monitoring, recording and metering functions, under normal and abnormal system conditions. The new IEC 61850 standard for communication networks and systems in substations allows the development of high-speed peer-to-peer communications based distributed applications, based on multicast of status changes or sampled analogue values. This paper details the requirements for the testing of complex substation automation systems. The testing methods need to correspond to the functional hierarchy of the substation automation system. Functional element testing, integration and system testing are discussed. Systems with Substation Bus only, and with both Process Bus and Substation Bus, are considered. A method for the testing of both types of system is proposed, based on a specific order of system components testing. Solutions for the testing of the individual components of the IEC 61850 based system, as well as for the testing of distributed applications, are described at the end of the paper.

Risk-based reconfiguration of safety monitoring system using dynamic Bayesian network

To prevent an abnormal event from leading to an accident, the role of its safety monitoring system is very important. The safety monitoring system detects symptoms of an abnormal event to mitigate its effect at its early stage. As the operation time passes by, the sensor reliability decreases, which implies that the decision criteria of the safety monitoring system should be modified depending on the sensor reliability as well as the system reliability. This paper presents a framework for the decision criteria (or diagnosis logic) of the safety monitoring system. The logic can be dynamically modified based on sensor output data monitored at regular intervals to minimize the expected loss caused by two types of safety monitoring system failure events: failed-dangerous (FD) and failed-safe (FS). The former corresponds to no response under an abnormal system condition, while the latter implies a spurious activation under a normal system condition. Dynamic Bayesian network theory can be applied to modeling the entire system behavior composed of the system and its safety monitoring system. Using the estimated state probabilities, the optimal decision criterion is given to obtain the optimal diagnosis logic. An illustrative example of a three-sensor system shows the merits and characteristics of the proposed method, where the reasonable interpretation of sensor data can be obtained.

Blackouts and relaying considerations - Relaying philosophies and the future of relay systems

This paper addresses the broad question of relaying philosophies, modes of operation of relays under abnormal system conditions, the categories of their failure modes, and advances made possible by modern technology in computer relays, adaptive relaying, and the use of wide-area measurements for improved protection and the ability to mitigate wide-area outages. It is hoped that this discussion will lead to a dialogue among system planners, relay engineers, and operating personnel to explore the realities of relay system performance under stressed system conditions and to adapt solutions made possible by new technological innovations

Protective relaying considerations for standby generation systems

Engine-driven generators installed primarily to serve as a standby power source during a utility outage are increasingly being used for peak shaving or load control through continuous parallel operation or a closed-transition transfer with the electric utility grid. The higher capacity requirements of mission-critical standby systems, such as those in hospitals and data centers, have led to the parallel operation of a large numbers of generators on a common standby bus. These applications require a more sophisticated electrical protection than the traditional standby operation, both to satisfy the utility interconnection requirements and to protect the generator(s) from abnormal system conditions. A great deal has already been published on the topic of generator and utility intertie protection, most of it directed primarily at turbine-driven units and utility-scale installations. This paper will discuss the protective relaying of generators and utility interconnections from the perspective of a standby application, and identify the unique considerations for selecting and setting some of the common protective relay elements, considering the issues which are not fully addressed in the traditional references. The topics covered by this paper include the accommodation of loading transients, the preservation of the standby mission, and the protection of low voltage generators.

Work design and analysis for space-based manufacturing: a case analysis of initial design issues

The purpose of the present research was to investigate the nature of potential manufacturing tasks humans may execute in a space environment. The success of space-based manufacturing (SBM) is suggested to be a precursor to permanent human presence in space. A working hypothesis for this study was that human work in the SBM environment would be substantially different from terrestrial manufacturing work. To investigate this hypothesis, a case analysis approach was developed that employed a function allocation and task analysis of a representative SBM process: the production of tailored industrial crystals. This research approach was chosen as the current state of engineering design for SBM is in the conceptual and early flow sheeting phases of a system life cycle. Results of the task analysis and function allocation process suggest response to corrective maintenance functions and to abnormal system conditions should be allocated to humans as opposed to automation. These results are discussed in relation to human factors engineering challenges associated with long-duration human presence in an SBM environment.

The dynamic representation of protection systems

This paper presents a dynamic model of a protection system based on a differential feeder protection along with the primary power system. A commercially available relay is modelled and its functions explained. A general primary power system model structure that includes a fully integrated protection system model is discussed. The protection system model contains dynamic models of both the relays and the transducers. A technique will be described for developing an accurate dynamic model of a numerical protection relay using actual microprocessor codes from a commercially available relay. Finally, the practical application of the analysis under abnormal system conditions is demonstrated. Different faults are applied to the internal and the external regions of the feeder, and the response of the relays examined.

Testing the Impact of Instrumentation Location and Reliability on Ecological Interface Design: Fault Diagnosis Performance

Ecological Interface Design (EID) is a recent philosophy for designing the visual displays of human-machine interfaces. An EID interface displays the higher-order relations and properties of a work domain so that adaptive operator problem solving is better supported for both normal and abnormal system conditions. Previous empirical studies of EID have assumed that the raw data required to derive and communicate the higher-order information would be available and reliable. The present research empirically evaluates the impact of having incomplete data on the effectiveness of an EID interface, compared to a more traditional piping and instrumentation interface. The research also addresses recent criticism directed at previous empirical studies of EID is also addressed. Results suggest that diagnostic performance using an ecological interface is compromised only when the interface is supported by a minimal set of instrumentation. However, an ecological interface supported by maximal instrumentation, on average, leads to the best diagnostic performance.

Model-based communicative acts: human-computer collaboration in supervisory control

Supervisory control environments can be characterized as dynamic, complex, uncertain, and risky. The cognitive demands placed on human supervisory controllers are driven by the continual need for situation assessment (including active information seeking), active goal-setting and planning, and anticipatory as well as reactive control actions and compensating for abnormal system conditions. One way to improve the human-machine system is with intelligent support systems that provide context-sensitive displays, dialogue, and resources for activity management. The Georgia Tech Mission Operations Cooperative Assistant (GT-MOCA) is an example of such a system for NASA satellite ground control. The design of GT-MOCA is based on (1) principles of human-computer cooperative problem solving, partly derived from an analysis of human communication literature, (2) empirical study of the use of an existing real-time expert system for satellite ground control, and (3) the OFMspert architecture which provides dynamic intent inferencing organized around the operator function model. GT-MOCA provides three major resources for cooperative support: interactive graphics of system components, an inspectable and interactive visualization of current activity requirements, and message lists organized around major communicative functions such as advice and various types of alerts. This paper focuses on the representation of the communicative acts that are the underpinning of these message lists and details how such acts are integrated into the operator function model of activity. An analysis of GT-MOCA with respect to human communication literature and an empirical evaluation of GT-MOCA show that it does support relevant and timely interaction with human problem solvers and does provide some performance benefits.