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1 – 10 of over 8000Fiaz Ahmad, Kabir Muhammad Abdul Rashid, Akhtar Rasool, Esref Emre Ozsoy, Asif Sabanoviç and Meltem Elitas
To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman…
Abstract
Purpose
To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman filter (UKF) and newly developed algorithm, termed Improved unscented Kalman Filter (IUKF) for IEEE-30, 33 and 69-bus radial distribution networks for load variations and bad data for two measurement noise scenarios, i.e. 30 and 50 per cent are shown.
Design/methodology/approach
State estimation (SE) plays an instrumental role in realizing smart grid features like distribution automation (DA), enhanced distribution generation (DG) penetration and demand response (DR). Implementation of DA requires robust, accurate and computationally efficient dynamic SE techniques that can capture the fast changing dynamics of distribution systems more effectively. In this paper, the UKF is improved by changing the way the state covariance matrix is calculated, to enhance its robustness and accuracy under noisy measurement conditions. UKF and proposed IUKF are compared under the cummulative effect of load variations and bad data based on various statistical metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Per cent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance Index (J) for three radial distribution networks. All the simulations are performed in MATLAB 2014b environment running on an hp core i5 laptop with 4GB memory and 2.6 GHz processor.
Findings
An Improved Unscented Kalman Filter Algorithm (IUKF) is developed for distribution network state estimation. The developed IUKF is used to predict network states (voltage magnitude and angle at all buses) and measurements (source voltage magnitude, line power flows and bus injections) in the presence of load variations and bad data. The statistical performance of the coventional UKF and the proposed IUKF is carried out for a variety of simulation scenarios for IEEE-30, 33 and 69 bus radial distribution systems. The IUKF demonstrated superiority in terms of: RMSE; MAD; MAPE; and overall performance index J for two measurement noise scenarios (30 and 50 per cent). Moreover, it is shown that for a measurement noise of 50 per cent and above, UKF fails while IUKF performs.
Originality/value
UKF shows degraded performance under high measurement noise and fails in some cases. The proposed IUKF is shown to outperform the UKF in all the simulated scenarios. Moreover, this work is novel and has justified improvement in the robustness of the conventional UKF algorithm.
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Amin Helmzadeh and Shahram M. Kouhsari
The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the…
Abstract
Purpose
The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the proposed method is to minimize the sum of squared errors (SSE) due to mismatches between simulation results and corresponding field measurements. Assuming that the network configuration is known, a limited number of erroneous branch parameters will be detected and corrected in an optimization procedure.
Design/methodology/approach
Proposing a novel formulation that utilizes network voltages and last modified admittance matrix of the simulation model, suspected branch parameters are identified. These parameters are more likely to be responsible for large values of SSE. Utilizing a Gauss-Newton (GN) optimization method, detected parameters will be modified in order to minimize the value of SSE. Required sensitivities in optimization procedure will be calculated numerically by the real time simulator. In addition, by implementing an efficient orthogonalization method, the more effective parameter will be selected among a set of correlated parameters to avoid singularity problems.
Findings
Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high efficiency of the proposed optimization method.
Originality/value
Incorrect branch parameter detection and correction procedures are investigated in real time simulators.
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Fiaz Ahmad, Akhtar Rasool, Esref Emre Ozsoy, Asif Sabanoviç and Meltem Elitas
The purpose of this paper is to propose successive-over-relaxation (SOR) based recursive Bayesian approach (RBA) for the configuration identification of a Power System. Moreover…
Abstract
Purpose
The purpose of this paper is to propose successive-over-relaxation (SOR) based recursive Bayesian approach (RBA) for the configuration identification of a Power System. Moreover, to present a comparison between the proposed method and existing RBA approaches regarding convergence speed and robustness.
Design/methodology/approach
Swift power network configuration identification is important for adopting the smart grid features like power system automation. In this work, a new SOR-based numerical approach is adopted to increase the convergence speed of the existing RBA algorithm and at the same time maintaining robustness against noise. Existing RBA and SOR-RBA are tested on IEEE 6 bus, IEEE 14 bus networks and 48 bus Danish Medium Voltage distribution network in the MATLAB R2014b environment and a comparative analysis is presented.
Findings
The comparison of existing RBA and proposed SOR-RBA is performed, which reveals that the latter has good convergence speed compared to the former RBA algorithms. Moreover, it is robust against bad data and noise.
Originality value
Existing RBA techniques have slow convergence and are also prone to measurement noise. Their convergence speed is effected by noisy measurements. In this paper, an attempt has been made to enhance convergence speed of the new identification algorithm while keeping its numerical stability and robustness during noisy measurement conditions. This work is novel and has drastic improvement in the convergence speed and robustness of the former RBA algorithms.
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Aref Gholizadeh Manghutay, Mehdi Salay Naderi and Seyed Hamid Fathi
Heuristic algorithms have been widely used in different types of optimization problems. Their unique features in terms of running time and flexibility have made them superior to…
Abstract
Purpose
Heuristic algorithms have been widely used in different types of optimization problems. Their unique features in terms of running time and flexibility have made them superior to deterministic algorithms. To accurately compare different heuristic algorithms in solving optimization problems, the final optimal solution needs to be known. Existing deterministic methods such as Exhaustive Search and Integer Linear Programming can provide the final global optimal solution for small-scale optimization problems. However, as the system grows the number of calculations and required memory size incredibly increases, so applying existing deterministic methods is no longer possible for medium and large-scale systems. The purpose of this paper is to introduce a novel deterministic method with short running time and small memory size requirement for optimal placement of Micro Phasor Measurement Units (µPMUs) in radial electricity distribution systems to make the system completely observable.
Design/methodology/approach
First, the principle of the method is explained and the observability of the system is analyzed. Then, the algorithm’s running time and memory usage when applying on some of the modified versions of the Institute of Electrical and Electronics Engineers 123-node test feeder are obtained and compared with those of its deterministic counterparts.
Findings
Because of the innovative method of step-by-step placement of µPMUs, a unique method is developed. Simulation results elucidate that the proposed method has unique features of short running time and small memory size requirements.
Originality/value
While the mathematical background of the observability study of electricity distribution systems is very well-presented in the referenced papers, the proposed step-by-step placement method of µPMUs, which shrinks unobservable parts of the system in each step, is not discussed yet. The presented paper is directly applicable to typical problems in the field of power systems.
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In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting…
Abstract
In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting (STLF). A HTM Spatial Pooler (HTM-SP) stage is used to continually form sparse distributed representations (SDRs) from a univariate load time series data, a temporal aggregator is used to transform the SDRs into a sequential bivariate representation space and an overlap classifier makes temporal classifications from the bivariate SDRs through time. The comparative performance of HTM on several daily electrical load time series data including the Eunite competition dataset and the Polish power system dataset from 2002 to 2004 are presented. The robustness performance of HTM is also further validated using hourly load data from three more recent electricity markets. The results obtained from experimenting with the Eunite and Polish dataset indicated that HTM will perform better than the existing techniques reported in the literature. In general, the robustness test also shows that the error distribution performance of the proposed HTM technique is positively skewed for most of the years considered and with kurtosis values mostly lower than a base value of 3 indicating a reasonable level of outlier rejections.
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Yanwu Zhai, Haibo Feng, Haitao Zhou, Songyuan Zhang and Yili Fu
This paper aims to propose a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on the ground using the Stereo–inertial…
Abstract
Purpose
This paper aims to propose a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on the ground using the Stereo–inertial measurement unit (IMU) system. This method reparametrizes the pose according to the motion characteristics of TWIP and considers the impact of uneven ground on vision and IMU, which is more adaptable to the real environment.
Design/methodology/approach
When TWIP moves, it is constrained by the ground and swings back and forth to maintain balance. Therefore, the authors parameterize the robot pose as SE(2) pose plus pitch according to the motion characteristics of TWIP. However, the authors do not omit disturbances in other directions but perform error modeling, which is integrated into the visual constraints and IMU pre-integration constraints as an error term. Finally, the authors analyze the influence of the error term on the vision and IMU constraints during the optimization process. Compared to traditional algorithms, the algorithm is simpler and better adapt to the real environment.
Findings
The results of indoor and outdoor experiments show that, for the TWIP robot, the method has better positioning accuracy and robustness compared with the state-of-the-art.
Originality/value
The algorithm in this paper is proposed for the localization and mapping of a TWIP robot. Different from the traditional positioning method on SE(3), this paper parameterizes the robot pose as SE(2) pose plus pitch according to the motion of TWIP and the motion disturbances in other directions are integrated into visual constraints and IMU pre-integration constraints as error terms, which simplifies the optimization parameters, better adapts to the real environment and improves the accuracy of positioning.
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Mohammad Kamal Abuamsha and S. Shumali
The study aims at estimating the shadow economy (SE) using the method of demand for currency in Palestine for the period 2008–2018 by studying the relationship between a group of…
Abstract
Purpose
The study aims at estimating the shadow economy (SE) using the method of demand for currency in Palestine for the period 2008–2018 by studying the relationship between a group of variables that affect the ratio of money traded outside the banking system to the money supply in the broad sense.
Design/methodology/approach
The study has adopted analytical and descriptive research methods to estimate SE in Palestinian territories. The data has been obtained from the inflation reports issued by the Palestinian Monetary Authority for ten years, from 2008 to 2018. A standard model was constructed using EViews version 8 for statistical data processing after converting the annual data to quarterly data.
Findings
The authors demonstrated that the size of the SE in Palestinian territories has varied over time, and the annual average of its size during the study period reached about $1764.893 (in millions). This amount constitutes about 15.5% of the gross domestic product. The study provides recommendations for reducing the size of the SE in Palestinian territories.
Practical implications
The current study shows that shadow economics could significantly matter for economic policy design by policymakers.
Originality/value
This study deals directly with Tanzi’s “estimation of shadow economy in Palestinian territories” concept and its impact on economic policies.
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Roberto Dell’Anno, Adriana AnaMaria Davidescu and Nguling’wa Philip Balele
The purpose of this paper is to estimate the Tanzanian shadow economy (SE) from 2003 to 2015 and test the statistical relationships between the SE and its potential causes and…
Abstract
Purpose
The purpose of this paper is to estimate the Tanzanian shadow economy (SE) from 2003 to 2015 and test the statistical relationships between the SE and its potential causes and indicators.
Design/methodology/approach
The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, the authors adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005.
Findings
The SE ranges from 52 to 61 per cent of official GDP and slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics.
Research limitations/implications
Given the challenges facing estimation of the SE (e.g. small sample size, exogenous estimate to calibrate the model, meaning of the latent variable), quantification of SE should be considered to be rough measures.
Practical implications
To lower the size of the SE, the government needs to keep inflation and unemployment stable over time, to reduce government spending because it creates pressure on tax collection due to the limited tax base.
Originality/value
This is the first study specifically focused on Tanzanian SE based on the MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to the worldwide context.
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Amy Hageman and Cass Hausserman
This paper uses two studies to examine taxpayers' knowledge of tax incentives for charitable giving and also explores the consequences of this knowledge on charitable giving…
Abstract
This paper uses two studies to examine taxpayers' knowledge of tax incentives for charitable giving and also explores the consequences of this knowledge on charitable giving decisions. The first study surveys 600 US taxpayers to establish a baseline understanding of how making a charitable contribution affects taxpayers. In the second study, we conduct an experiment with 201 US taxpayers in which we manipulate the knowledge of taxpayers by providing an educational intervention; we also measure, if, how much is donated in a hypothetical scenario under various tax deductibility conditions. The first study indicates fewer than half of participants understand the basic principles of how charitable donations affect tax liability. Our second study reveals that a short educational video is extremely effective at improving taxpayers' understanding and helping them accurately estimate the tax benefit associated with charitable giving. However, through moderated mediation analysis, we also show that participants who received this educational intervention and accurately estimated the tax benefits in turn decreased their charitable giving. We conclude that the majority of US taxpayers do not understand whether they benefit from certain deductions and may be overestimating the benefit they receive from charitable giving, resulting in giving more than they intend.
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Maria Adelaide Pedrosa da Silva Duarte and Marta Cristina Nunes Simões
European Union (EU) central and eastern economies have gone through a process of structural change since 1989, when the post-communist transition started. This process was…
Abstract
European Union (EU) central and eastern economies have gone through a process of structural change since 1989, when the post-communist transition started. This process was afterwards reinforced by the three EU enlargement waves that took place in 2004, 2007 and 2013. Though exhibiting low levels of aggregate productivity, this group of countries joined the EU with higher levels of human capital than the southern member states, an advantage that should have accelerated real convergence towards the EU15. However, evidence to date suggests that the convergence process came to a halt in 2007–2008 when massive capital inflows stopped, highlighting the fragilities of the growth strategies implemented so far. In these peripheral countries, structural change has been characterised by an expanding services sector alongside growing income inequality. The two strands of literature on these issues highlight that: (a) an expanding services sector may not be detrimental for growth, quite the opposite, depending on services composition and on the capacity of services sub-sectors to incorporate information and communication technologies (ICTs); and (b) inequality is negatively related to growth through the fiscal policy, socio-political instability, borrowing constraints to investment in education and endogenous fertility channels and positively through the savings channel and incentives. We analyse the nexus between structural change, inequality and growth in this group of countries highlighting income inequality as a potential mechanism that connects the other two variables. We provide a descriptive quantitative analysis of the profiles of structural change and income inequality in our sample and apply dynamic panel methods to investigate the existence of causality among services sector expansion, inequality and aggregate productivity considering a maximum period between 1980 and 2010.
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