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In this paper voltage stability is analysed based not only on the voltage deviations from the nominal values but also on the number of limit violating buses and severity of voltage limit violations. The expression of the actual state of the system as a numerical index like severity, aids the system operator in taking better security related decisions at control centres both during a period of contingency and also at a highly stressed operating condition. In contrary to conventional N – 1 contingency analysis, Northern Electric Reliability Council (NERC) recommends N – 2 line contingency analysis. The decision of the system operator to overcome the present contingency state of the system must blend harmoniously with the stability of the system. Hence the work presents a novel N – 2 contingency analysis based on the continuous severity function of the system. The study is performed on 4005 possible combinations of N – 2 contingency states for the practical Indian Utility 62 bus system. Static VAr Compensator is used to improve voltage profile during line contingencies. A multi- objective optimization with the objective of minimizing the voltage deviation and also the number of limit violating bus with optimal location and optimal sizing of SVC is achieved by Particle Swarm Optimization algorithm.

Contingency analysis (CA) is a well-known function in power system planning and operation. In accordance with CA results, the system operator dispenses information regarding static security of the power system (overloads and/or voltage outside tolerable limits). However, classic CA with remedial action schemes cannot distinguish safe operating regimes from potentially dangerous ones in terms of voltage (in)stability. In fact, voltage instability is considered as one of the major threats leading to power system insecurity. Therefore, in this study an enhanced contingency analysis (ECA) is presented where the classical CA is extended with static voltage analysis based on the modal analysis. The article presents a dedicated methodology for the proposed ECA tool, with special emphasis on the analysis of corrective measures provided by the system operator, intended for enhancing power system security (regulation transformer action, distributed generation and energy storage). Also the influence of the load model was analyzed by simulation and the main conclusions are presented. The study demonstrated the advantages that distributed generation resources and energy storage can provide in the context of voltage stability. Also, the simulations acknowledged the importance of correct load modeling, since over or under estimation of a certain load-type component can result in too optimistic or too pessimistic power system operation limits.

Drawing upon contingency theory, we analyze the antecedents and performance consequences of chief strategy officer (CSO) presence in top management teams (TMTs). We argue that strategic and structural complexity affects the decision to have a CSO in the TMT and its effect on firm performance. The results of a sample of S&P 500 firms over a five-year period reveal that diversification, acquisition activity, and TMT role interdependence are positively associated with CSO presence. However, we also find that the structural choice to have a CSO in the TMT does not significantly affect a firm's financial performance. This first systematic analysis of CSO presence informs research on CSOs and contributes to the emerging literature on TMT structure.

Purpose – This paper aims to assess the links among these supply chain constructs by conducting a full-scale systematic review of all supply chain management (SCM) literature reviews published in ten leading logistics, SCM and operations management journals from 1989 to 2012. Collaboration and integration are as central to SCM as risk and performance management. Design/methodology/approach – The authors apply content analysis to execute the systematic literature review on the sample of 103 articles, supplemented by contingency analysis. These approaches guarantee a replicable, rigorous and transparent research process and minimize researcher bias. The analytical categories required for the content analysis are defined along the constructs of collaboration/integration and risk/performance. Findings – As can be expected, the review highlights the key role of the two constructs in SCM. In this light, the research claims to provide statistical evidence of a link between the constructs of collaboration/integration and risk/performance, most notably between collaboration and performance, information sharing and rewards sharing, as well as integration and supply chain performance. Research limitations/implications – The study assesses the link between the constructs of collaboration/integration and risk/performance through research embedded in literature reviews, pinpointing research gaps and potential future research directions in the field. Contributing to SCM theory building, a thorough review provides statistical proof of the link between collaboration/integration and risk/performance. Originality/value – Although numerous literature reviews have been conducted in the past on the SCM constructs of collaboration/integration and risk/performance, no full review of literature reviews aiming to test a theoretical link in the here presented form has yet been undertaken to the authors’ knowledge.

The ongoing replacement of synchronous machine generators (SMs) with converter-interface generators (CIGs) is raising the voltage unbalance of power systems, affecting power quality and grid stability. This paper focuses on a key power quality index for power systems, i.e., the voltage unbalance factor. The purpose of this work is twofold. First, it presents the generalization of a three-phase power flow algorithm developed by University of Padova, named PFPD_3P, to assess the voltage unbalance factors of power systems supplied by CIGs. In particular, it is demonstrated that CIGs can be modelled as three-phase PV/PQ constraints embedding their positive-, negative- and zero-sequence admittances. Then, the concept of three-phase contingency analysis is introduced. Indeed, for static security evaluation, the classical single-phase contingency analysis may no longer be sufficient, as it lacks power quality computations, e.g., voltage/current unbalance factors. Numerical simulations evaluating the unbalance factors due to different generation mix scenarios and contingencies are tested on the Italian extra-high-voltage/high-voltage (EHV/HV) grid. The choice of this network relies on its representativeness, as CIGs are the majority of new installations in the Italian generation mix.

Contingency analysis plays an important role in assessing the static security of a network. Its purpose is to check whether a system can operate safely when some elements are out of service. In a real-time application, the computational time required to perform the calculation is paramount for operators to take immediate actions to prevent cascading outages. Therefore, the numerical performance of the contingency analysis is the main focus of this current research. In power flow calculation, when solving the network equations with a sparse matrix solver, most of the time is spent factorizing the Jacobian matrix. In terms of computation time, the symbolic factorization is the costliest operation in the LU (Lower-upper) factorization process. This paper proposes a novel method to perform the calculation with only one symbolic factorization using a full Newton–Raphson-based generic formulation and modular approach (GFMA). The symbolic factorization retained can be used during the iterations of any power flow contingency scenario. A computer study demonstrates that reusing the same symbolic factorization greatly reduces computation time and improves numerical performance. Power system security assessment under N-1 and N-2 contingency conditions is performed for the IEEE standard 54-bus and 108-bus to evaluate the numerical performance of the proposed method. A comparison with the conventional power flow method shows that the time required for the analysis is shortened considerably, with a minimum gain of 228%. The comparative analysis demonstrates that the proposed solution has better numerical performance for large-scale networks.

Battery energy storage systems (BESSs) have become integral components of grid modernization because of their ability to provide system stabilization in the presence of high levels of renewable generation. Specifically, the dynamic response capabilities of BESSs can be a valuable tool in ensuring reliability and security of the grid during contingencies. This paper explores the utilization of BESSs in improving the contingency response of the SRP power system by providing selection criteria that enable a viable and cost-effective solution from a planning perspective. In particular, this study focuses on optimal BESS selection from a list of actual queued projects to enhance system stability by maintaining voltage and mitigating fault impacts. Additionally, the work involves generating both normal and abnormal operational scenarios for varying loads and renewable generation profiles of the system to capture diverse sources of uncertainty. A comprehensive reliability planning approach is adopted to identify the worst-case scenarios and ensure network robustness by optimizing BESS operations under these conditions. The results obtained by applying the proposed methodology to a 2500+-bus real-world system of SRP indicates that with as few as four strategically selected BESS units, the system is able to effectively mitigate more than 90% of under-voltage violations and approximately 75% of over-voltage violations.

An interview-informed synthesized contingency analysis (IISCA; Hanley et al. in J Appl Behav Anal 47:16–36, 2014) and related skill-based treatment process can result in socially valid outcomes for clients exhibiting severe challenging behavior when implemented by professionals and then transferred to parents (e.g., Santiago et al. in J Autism Dev Disord 46:797–811, 2016). However, many families do not have access to professionals trained to implement functional analyses or function-based treatments (Deochand & Fuqua Behav Anal Pract 9:243–252, 2016). Experimenters in the present study coached three parents of children with autism exhibiting severe challenging behavior through implementing an IISCA and resulting skill-based treatment process through distance-based collaborative consulting. All parents achieved differentiated functional analyses, taught their children to emit functional replacement skills, and reduced challenging behavior relative to baseline.

Thailand has entered into an aging society since the year 2000. Using the 2017 Survey of the Older Persons in Thailand collected by National Statistical Office of Thailand, this study uses cross tabulation, random forest with variable importance measure and lasso logistic regression to examine factors that have effects on the elderly’s decision to remain in the labor market after retirement. This study reveals that these following variables: age, education level, healthcare eligibility, marital status, health condition, total assets, gender, residential type, percent of elderly in the household, and number of children have strong influences on an elderly’s desire to continue work. By knowing which factors contribute to the elderly wish to continue work in the market, this research allows for future prediction of the labor market that can accommodate elderly in Thailand. Our final models of random forest and lasso logistic regression provide prediction accuracy of 68.19 and 69.58 percent on the elderly’s desire to work, respectively. This study has a significant impact as policymakers can utilize our models in predicting elderly’s desire to work after retirement age and design a labor market that can accommodate elderly in Thailand in the future.