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Article

Fiaz 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…

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.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 4
Type: Research Article
ISSN: 0332-1649

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Article

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…

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.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 35 no. 5
Type: Research Article
ISSN: 0332-1649

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Article

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…

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.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Content available
Article

E.N. Osegi

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…

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.

Details

Applied Computing and Informatics, vol. 17 no. 2
Type: Research Article
ISSN: 2634-1964

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Article

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…

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.

Details

Journal of Economic Studies, vol. 45 no. 1
Type: Research Article
ISSN: 0144-3585

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Article

Andrea Vocino

The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non‐independence of observations on standard…

Abstract

Purpose

The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non‐independence of observations on standard error parameter estimates. Using field data structured in the form of repeated measurements it is to be shown, in a two‐factor confirmatory factor analysis model, how the bias in SE can be derived when the non‐independence is ignored.

Design/methodology/approach

Three estimation procedures are compared: normal asymptotic theory (maximum likelihood); non‐parametric standard error estimation (naïve bootstrap); and sandwich (robust covariance matrix) estimation (pseudo‐maximum likelihood).

Findings

The study reveals that, when using either normal asymptotic theory or non‐parametric standard error estimation, the SE bias produced by the non‐independence of observations can be noteworthy.

Research limitations/implications

Considering the methodological constraints in employing field data, the three analyses examined must be interpreted independently and as a result taxonomic generalisations are limited. However, the study still provides “case study” evidence suggesting the existence of the relationship between non‐independence of observations and standard error bias estimates.

Originality/value

Given the increasing popularity of structural equation models in the social sciences and in particular in the marketing discipline, the paper provides a theoretical and practical insight into how to treat repeated measures and clustered data in general, adding to previous methodological research. Some conclusions and suggestions for researchers who make use of partial least squares modelling are also drawn.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 21 no. 1
Type: Research Article
ISSN: 1355-5855

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Book part

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…

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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Book part

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.

Details

Core-Periphery Patterns Across the European Union
Type: Book
ISBN: 978-1-78714-495-8

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Book part

Kenneth A. Couch, Gayle L. Reznik, Christopher R. Tamborini and Howard M. Iams

Data from the 1984 Survey of Income and Program Participation are linked to longitudinal records from the Social Security Administration to examine the relationship…

Abstract

Data from the 1984 Survey of Income and Program Participation are linked to longitudinal records from the Social Security Administration to examine the relationship between the long-term unemployment that prime-aged (ages 25–55) male workers experienced around the time of the 1980–1982 twin recessions with earnings, receipt of either Disability Insurance or Supplemental Security Income (DI-SSI) benefits, and mortality. Separate estimations are made for those who voluntarily and involuntarily left employment and the combined sample of these two groups. We find that 20 years later, long-term joblessness was associated with significantly lower earnings and higher likelihoods of the receipt of DI-SSI benefits as well as mortality.

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Article

Alicia Morgan Plemmons

The purpose of this study is to analyze how occupational licensing costs within a state affect the performance of self-employed firms, as measured through annual sales.

Abstract

Purpose

The purpose of this study is to analyze how occupational licensing costs within a state affect the performance of self-employed firms, as measured through annual sales.

Design/methodology/approach

This study utilizes an empirical approach to determine if there are additional effects on the annual sales for firms that are self-employed in high-cost states that are not explained through the individual estimations. Since the choice of self-employment is plausibly nonrandom, this study also uses a propensity score matching method to develop a matched subsample of self-employed and employee-maintaining firms. This selection methodology ensures that the set of self-employed and employee-maintaining firm observations are similar in all measurable attributes besides their regulatory environment and firm structure. Using this representative subsample, the empirical framework is repeated to reevaluate the effects of high occupational licensing fees on the sales of self-employed firms.

Findings

In both the unmatched and matched samples, there are significant, large, negative interactions representing a reduction in annual sales per employee within self-employed firms relative to employee-maintaining firms when located in states with above-average occupational licensing costs. The results using the matched subsamples are noticeably smaller in magnitude, which indicates that future policy assessments would benefit from ensuring that the sample pool, when dealing with self-employment, is limited only to firms under a common convex hull in order to not skew the size of results.

Originality/value

This study contributes new understanding of the financial relationship of self-employed firms and occupational licensing costs using firm-level observations of sales and firm structure. This has important policy implications for the development and evaluation of occupational licensing policies when considering effects on the self-employed.

Details

Journal of Entrepreneurship and Public Policy, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2045-2101

Keywords

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