Transmission Line Parameter Estimation using Synchrophasor Data

abstract: Transmission line parameters play an important role in state estimation, dynamic line rating, and fault analysis. Because of this, several methods have been proposed in the literature for line parameter estimation, especially using synchrophasor data. However, success of most prior research has been demonstrated using purely synthetic data. A synthetic dataset does not have the problems encountered with real data, such as invariance of measurements and realistic field noise. Therefore, the algorithms developed using synthetic datasets may not be as effective when used in practice. On the other hand, the true values of the line parameters are unknown and therefore the algorithms cannot be directly implemented on real data. A multi-stage test procedure is developed in this work to circumvent this problem. In this thesis, two popular algorithms, namely, moving-window total least squares (MWTLS) and recursive Kalman filter (RKF) are applied on real data in multiple stages. In the first stage, the algorithms are tested on a purely synthetic dataset. This is followed by testing done on pseudo-synthetic datasets generated using real PMU data. In the final stage, the algorithms are implemented on the real PMU data obtained from a local utility. The results show that in the context of the given problem, RKF has better performance than MWTLS. Furthermore, to improve the performance of RKF on real data, ASPEN data are used to calculate the initial estimates. The estimation results show that the RKF algorithm can reliably estimate the sequence impedances, using ASPEN data as a starting condition. The estimation procedure is repeated over different time periods and the corresponding results are presented. Finally, the significance of data drop-outs and its impact on the use of parameter estimates for real-time power system applications, such as state estimation and dynamic line rating, is discussed. To address the problem (of data drop-outs), an auto regressive integrated moving average (ARIMA) model is implemented. The ability of this model to predict the variations in sequence impedances is demonstrated.Dissertation/ThesisMasters Thesis Electrical Engineering 201

CDMA Slotted Aloha Mac Protocol for ABR Traffic Over Satellite Links.

The design of a packet radio network with a large number of terminals and a single hub station involves the use of two basically different types of communication channels and channel architectures. One type of channel is a broadcast channel used to transmit data from the hub station to the terminals. Transmitting data from a single hub station to a large number of terminals (one to many) is a relatively simple problem. This channel architecture is almost always configured in a simple time division multiplexed (TOM) mode. The other type is transmitting data from terminals to a single hub (many to one) which is much more challenging problem. In general the choice of multiple access protocol for a particular application should depend on two primary factors: (1) The traffic characteristic of the data network of interest (2) The state of technology development at the time the network is deployed. In this thesis we investigate the combination of two multiple access schemes, slotted Aloha and DS- CDMA spread spectrum protocol (DS-CDMA slotted Aloha) over LEO satellite link in the uplink from terminals to the satellite. In this protocol the channel is divided into time slots. Each user is assigned a time slot equal to the packet transmission. Prior to transmission each user randomly choose unique code sequence different from other users. After transmission the unsuccessful packets should be re-transmitted after a random time delay. The simulation is done by an OPNET package in the presence of LEO satellite system with non-real time traffic type (ABR traffic). The investigation includes the throughput performance of the DS-CDMA slotted Aloha, Packet loss ratio, and the bit errors in the packet transmission in the presence of MAl, AWGN and the error correction mechanism. The simulation shows high throughput performance is obtained against other conventional narrowband protocols such as pure Aloha and slotted Aloha protocols due to the capability of the spread spectrum technique to increase the channel capacity. The simulation also shows an improvement in the throughput performance by implementing the error correction mechanism

Live Prefetching for Mobile Computation Offloading

The conventional designs of mobile computation offloading fetch user-specific data to the cloud prior to computing, called offline prefetching. However, this approach can potentially result in excessive fetching of large volumes of data and cause heavy loads on radio-access networks. To solve this problem, the novel technique of live prefetching is proposed in this paper that seamlessly integrates the task-level computation prediction and prefetching within the cloud-computing process of a large program with numerous tasks. The technique avoids excessive fetching but retains the feature of leveraging prediction to reduce the program runtime and mobile transmission energy. By modeling the tasks in an offloaded program as a stochastic sequence, stochastic optimization is applied to design fetching policies to minimize mobile energy consumption under a deadline constraint. The policies enable real-time control of the prefetched-data sizes of candidates for future tasks. For slow fading, the optimal policy is derived and shown to have a threshold-based structure, selecting candidate tasks for prefetching and controlling their prefetched data based on their likelihoods. The result is extended to design close-to-optimal prefetching policies to fast fading channels. Compared with fetching without prediction, live prefetching is shown theoretically to always achieve reduction on mobile energy consumption.Comment: To appear in IEEE Trans. on Wireless Communicatio

STUDY ON EFFECT OF UPFC DEVICE IN ELECTRICAL TRANSMISSION SYSTEM: POWER FLOW ASSESSMENT

The power transfer capability of electric transmission lines are usually limited by large signals ability. Economic factors such as the high cost of long lines and revenue from the delivery of additional power gives strong intensive to explore all economically and technically feasible means of raising the stability limit. On the other hand, the development of effective ways to use transmission systems at their maximum thermal capability. Fast progression in the field of power electronics has already started to influence the power industry. This is one direct out come of the concept of FACTS aspects, which has become feasible due to the improvement realized in power electronic devices in principle the FACTS devices should provide fast control of active and reactive power through a transmission line. The UPFC is a member of the FACTS family with very attractive features. This device can independently control many parameters. This device offers an alternative mean to mitigate transmission system oscillations. It is an important question is the selection of the input signals and the adopted control strategy for this device in order to damp power oscillations in an effective and robust manner. The UPFC parameters can be controlled in order to achieve the maximal desire effect in solving first swing stability problem. This problem appears for bulky power transmission systems with long transmission lines. In this paper a MATLAB Simulink Model is considered with UPFC device to evaluate the performance of Electrical Transmission System of 22 kV and 33kV lines. In the simulation study, the UPFC facilitates the real time control and dynamic compensation of AC transmission system. The dynamic simulation is carried out in conjunction with the N-R power flow solution sequence. The updated voltages at each N-R iterative step are interpreted as dynamic variables. The relevant variables are input to the UPFC controllers

How Much Attention Should we Pay to Mosquitoes?

Mosquitoes are a major global health problem. They are responsible for the transmission of diseases and can have a large impact on local economies. Monitoring mosquitoes is therefore helpful in preventing the outbreak of mosquito-borne diseases. In this paper, we propose a novel data-driven approach that leverages Transformer-based models for the identification of mosquitoes in audio recordings. The task aims at detecting the time intervals corresponding to the acoustic mosquito events in an audio signal. We formulate the problem as a sequence tagging task and train a Transformer-based model using a real-world dataset collecting mosquito recordings. By leveraging the sequential nature of mosquito recordings, we formulate the training objective so that the input recordings do not require fine-grained annotations. We show that our approach is able to outperform baseline methods using standard evaluation metrics, albeit suffering from unexpectedly high false negatives detection rates. In view of the achieved results, we propose future directions for the design of more effective mosquito detection models

Software integration testing based on communication coverage criteria and partial model generation

This paper considers the problem of integration testing the components of a timed distributed software system. We assume that communication between the components is specified using timed interface automata and use computational tree logic (CTL) to define communication-based coverage criteria that refer to send- and receive-statements and communication paths. The proposed method enables testers to focus during component integration on such parts of the specification, e.g. behaviour specifications or Markovian usage models, that are involved in the communication between components to be integrated. A more specific application area of this approach is the integration of test-models, e.g. a transmission gear can be tested based on separated models for the driver behaviour, the engine condition, and the mechanical and hydraulical transmission states. Given such a state-based specification of a distributed system and a concrete coverage goal, a model checker is used in order to determine the coverage or generate test sequences that achieve the goal. Given the generated test sequences we derive a partial test-model of the components from which the test sequences are derived. The partial model can be used to drive further testing and can also be used as the basis for producing additional partial models in incremental integration testing. While the process of deriving the test sequences could suffer from a combinatorial explosion, the effort required to generate the partial model is polynomial in the number of test sequences and their length. Thus, where it is not feasible to produce test sequences that achieve a given type of coverage it is still possible to produce a partial model on the basis of test sequences generated to achieve some other criterion. As a result, the process of generating a partial model has the potential to scale to large industrial software systems. While a particular model checker, UPPAAL, was used, it should be relatively straightforward to adapt the approach for use with other CTL based model checkers. A potential additional benefit of the approach is that it provides a visual description of the state-based testing of distributed systems, which may be beneficial in other contexts such as education and comprehension