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The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

The psychological analysis of strategic management issues has gained a great deal of momentum in recent years. Much can be learned by entering the black box of strategic thinking of senior executives and bring new insights on how they see, make sense of, and interpret their everyday strategic experiences. This chapter will focus on a powerful cognitive mapping tool called the Repertory Grid Technique and demonstrate how it has been used in the strategy literature along with how a new and more refined application of the technique can enhance the elicitation of complex strategic cognitions for strategy and Board of Directors research.

Culture is a central concept broadly studied in social anthropology and sociology. It has been gaining increasing attention in economics, appearing in research on labor market discrimination, identity, gender, and social preferences. Most experimental economics research on culture studies cross-national or cross-ethnic differences in economic behavior. In contrast, we explain laboratory behavior using two cultural dimensions adopted from a prominent general cultural framework in contemporary social anthropology: group commitment and grid control. Groupness measures the extent to which individual identity is incorporated into group or collective identity; gridness measures the extent to which social and political prescriptions intrinsically influence individual behavior. Grid-group characteristics are measured for each individual using selected items from the World Values Survey. We hypothesize that these attributes allow us to systematically predict behavior in a way that discriminates among multiple forms of social preferences using a simple, parsimonious deductive model. The theoretical predictions are further tested in the economics laboratory by applying them to the dictator, ultimatum, and trust games. We find that these predictions are confirmed overall for most experimental games, although the strength of empirical support varies across games. We conclude that grid-group cultural theory is a viable predictor of people’s economic behavior, then discuss potential limitations of the current approach and ways to improve it.

An unreliable supply of grid electricity has a strong negative impact on industrial and commercial profitability as well as on household activities and government services that rely on electricity supply. This unreliable grid electricity could be a result of technical and security factors affecting the grid network. Therefore, this study aims to investigate the effects of technical and security factors on the transmission and distribution of grid electricity in Uganda.

This study used the ordinary least squares (OLS) and autoregressive distributed lag (ARDL) models to examine the effects of technical and security factors on grid electricity reliability in Uganda. The study draws upon secondary time series monthly data sourced from the Uganda Electricity Transmission Company Limited (UETCL) government utility, which transmits electricity to both distributors and grid users. Additionally, data from Umeme Limited, the largest power distribution utility in Uganda, were incorporated into the analysis.

The findings revealed that technical faults, failed grid equipment, system overload and theft and vandalism affected grid electricity reliability in the transmission and distribution subsystems of the Ugandan power grid network. The effect was computed both in terms of frequency and duration of power outages. For instance, the number of power outages was 116 and 2,307 for transmission and distribution subsystems, respectively. In terms of duration, the power outages reported on average were 1,248 h and 5,826 h, respectively, for transmission and distribution subsystems.

This paper investigates the effects of technical and security factors on the transmission and distribution grid electricity reliability, specifically focusing on frequency and duration of power outages, in the Ugandan context. It combines both OLS and ARDL models for analysis and adopts the systems reliability theory in the area of grid electricity reliability research.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

This paper aims to reduce the impact of disordered charging of large-scale electric vehicles (EVs) on the grid. EV is great significance for environmental protection, energy conservation and emission reduction to replace fuel vehicles with EVs. However, as a kind of random mobile load, large-scale integration into the power grid may lead to power quality problems such as line overload, line loss increase and voltage reduction. This paper realizes the orderly charging of electric vehicles and the safe operation of the distribution network by optimizing the dispatching scheme.

This paper takes the typical IEEE-33 node distribution system as the research object, adopts the improved particle swarm optimization algorithm and takes the minimum operation cost, the minimum environmental pollution, the minimum standard deviation of daily load, the minimum peak valley difference of load, the minimum node voltage offset rate and the minimum system grid loss rate as the optimization objectives.

Controlling the disordered charging of large-scale electric vehicles by optimizing the dispatching algorithm can realize the full consumption of renewable energy and the safe operation of the power grid.

Results show that the proposed scheme can realize the transfer of charging load in time and space, so as to stabilize the load fluctuation of distribution grid, improve the operation quality of power grid, reduce the charging cost of users and achieve the expected research objectives.

Despite South Africa’s ailing electrical grid, substantial renewable energy (RE) integration is planned for the country. As grid-integrated RE affects all grids differently, this study aims to develop an adaptable grid code-guided renewable power plant (RPP) control real-time simulation testbed, tailored to South African grid code requirements to study grid-integrated RE’s behaviour concerning South Africa’s unique conditions.

The testbed is designed using MATLAB’s Simulink and live script environments, to create an adaptable model where grid, RPP and RPP guiding grid codes are tailorable. This model is integrated with OPAL-RT’s RT-LAB and brought to real-time simulation using OPAL-RT’s OP4510 simulator. Voltage, frequency and short-circuit event case studies are performed through which the testbed’s abilities and performance are assessed.

Case study results show the following. The testbed accurately represents grid code voltage and frequency requirements. RPP point of connection (POC) conditions are consistently recognized and tracked, according to which the testbed then operates simulated RPPs, validating its design. Short-circuit event simulations show the simulated wind farm supports POC conditions relative to short-circuit intensity by curtailing active power in favour of reactive power, in line with local grid code requirements.

To the best of the authors’ knowledge, this is the first design of an adaptable grid code-guided RPP control testbed, tailored to South African grid code requirements in line with which RPP behavioural and grid integration studies can be performed.

This article seeks to introduce the concept of the Grid‐GMPLS control plane architecture with focus on new services, models, and interoperability issues of Grid‐GMPLS (G²MPLS) and GMPLS control planes. The purpose of this activity is to design, implement and test extensions of the GMPLS Control Plane that can enable the paradigm of a G²MPLS network.

The approach deploys extended GMPLS implementations aiming to facilitate bandwidth provisioning to Grid users.

G²MPLS is a Network Control Plane architecture that implements the concept of Grid Network Services. GNS is a service that allows the provisioning of network and Grid resources in a single‐step through a set of integrated procedures. By providing a unified network/Grid infrastructure the control plane can adapt to the demands of applications having intensive requirements on both computational and network resources.

The project delivers the prototype implementation of G²MPLS. Consideration should be given to involving the vendors of the optical equipment in the development process to incorporate the project findings into their operating systems.

The G²MPLS protocol stack has been designed to be compatible with the ASON/GMPLS architecture. This could lead to possible integration of Grids in the existing operational networks, by overcoming the current limitations of Grids running over dedicated networks with their own administrative procedures.

The paper provides the description of Grid Network Infrastructures with a common and transversal Control Plane approach based on G²MPLS, in which Grid resources and optical network resources are both controlled by the same Control Plane, seamlessly spanning the different Control and Management domains of the network.

The aim of this paper is to assess the ability of a stress-blended eddy simulation (SBES) turbulence model to predict the performance of a three-straight-bladed vertical axis wind turbine (VAWT). The grid sensitivity study is conducted to evaluate the simulation accuracy.

The unsteady Reynolds-averaged Navier–Stokes equations are solved using the computational fluid dynamics (CFD) technique. Two types of grid topology around the blades, namely, O-grid (OG) and C-grid (CG) types, are considered for grid sensitivity studies.

With regard to the power coefficient (Cp), simulation results have shown significant improvements of predictions using compared to other turbulence models such as the k-e model. The Cp distributions predicted by applying the CG mesh are in good agreement with the experimental data than that by the OG mesh.

The current study provides some new insights of the use of SBES turbulence model in VAWT CFD simulations.

The SBES turbulence model can significantly improve the numerical accuracy on predicting the VAWT performance at a lower tip speed ratio (TSR), which other turbulence models cannot achieve. Furthermore, it has less computational demand for the finer grid resolution used in the RANS-Large Eddy Simulation (LES) “transition” zone compared to other hybrid RANS-LES models.

To authors’ knowledge, this is the first attempt to apply SBES turbulence model to predict VAWT performance resulting for accurate CFD results. The better prediction can increase the credibility of computational evaluation of a new or an improved configuration of VAWT.

To focus on grid generation which is an essential part of any analytical tool for effective discretization.

This paper explores the application of the possibility of unstructured triangular grid generation that deals with derivationally continuous, smooth, and fair triangular elements using piecewise polynomial parametric surfaces which interpolate prescribed R³ scattered data using spaces of parametric splines defined on R² triangulations in the case of surfaces in engineering sciences. The method is based upon minimizing a physics‐based certain natural energy expression over the parametric surface. The geometry is defined as a set of stitched triangles prior to the grid generation. As for derivational continuities between the two triangular patches C⁰ and C¹ continuity or both, as per the requirements, has been imposed. With the addition of a penalty term, C² (approximate) continuity can also be achieved. Since, in this work physics‐based approach has been used, the grid is analyzed using intersection curves with three‐dimensional planes, and intrinsic geometric properties (i.e. directional derivatives), for derivational continuity and smoothness.

The triangular grid generation that deals with derivationally continuous, smooth, and fair triangular elements has been implemented in this paper for surfaces in engineering sciences.

This paper deals with the important problem of grid generation which is an essential part of any analytical tool for effective discretization. And, the examples to demonstrate the theoretical model of this paper have been chosen from different branches of engineering sciences. Hence, the results of this paper are of practical importance for grid generation in engineering sciences.

The paper is theoretical with worked examples chosen from engineering sciences.