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This paper seeks to consider the design of small, naturally cooled, and high‐frequency (in excess of 10 kHz) inductors. Its purpose is to show that the design of such inductors can be obtained from the solution of a signomial program. In its most general form, the signomial program calls for minimising the total mass (or cost) of the inductor whilst ensuring the satisfaction of the inductance value together with constraints imposed by the copper fill‐factor, the allowed temperature rise, Kirchhoff's mmf law, and the core flux density.

The signomial program is solved using a sequential geometric programming (SGP) approach specifically tailored to the inductor design problem. In essence, SGP seeks a constrained minimum mass (or cost) solution by optimally setting the inductor geometry parameters, the air‐gap length, and the relevant electrical and magnetic quantities.

Design results reveal that including the inductor geometry parameters in the set of problem variables leads to significant savings in the inductor mass (or cost).

In cases where there are restrictions on the inductor weight, the optimal solution of the signomial program can be used for manufacturing inductors having cores with non‐standard sizes. In other applications where core dimensions are chosen from the manufacturer's database, the SGP approach can be used to complete the design by either maximising the inductance value or minimising the total loss whilst enforcing a given inductance value.

This work presents a first attempt to optimise an inductor design via signomial programming. The proposed solution methodology is based on SGP, but specifically adapted to the inductor design problem.

The purpose of this study is to address the efficiency of power losses representation while still reducing the computational burden of an optimal power flow (OPF) model in transmission expansion planning (TEP) studies.

A modified TEP model is formulated with inclusions of linearized approximation of power losses for a large-scale power system with renewable energy sources. The multi-objectives function determines the effect of transmission line losses on the optimal power generation dispatch in the power system with and without inclusion of renewable energy sources with emphasis on minimizing the investment and operation costs, emission and the power losses.

This study investigates the impact of renewable energy sources on system operating characteristics such as transmission power losses and voltage profile. Sensitivity analysis of the performance for the developed deterministic quadratic programming models was analyzed based on optimal generated power and losses on the system.

In the future, a comparison of the alternating current OPF and direct current (DC) OPF models based on the proposed mathematical formulations can be carried out to determine the efficiency and reduction of computation process of the two models.

This paper proposed an accurate way of computing transmission losses in DC OPF for a TEP context with a view of achieving a minimal computation time.

This paper addresses the following objectives: develop a modified DC OPF with a linearized approximation of power losses in TEP problem with large integration of RES. Investigate the impact of RES on system operating characteristics such as transmission power losses and voltage profile.

Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and conflicting with each other. This paper aims to treat the transformer design optimization (TDO) as a multiobjective problem (MOP), to minimize the manufacturing cost and the total owing cost, taking into consideration design constraints.

To deal with this optimization problem, a new method is proposed that combines the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) with differential evolution, also applying lognormal distribution for tuning the scale factor and the beta distribution to adjust the crossover rate (UPS-DELFBC). The proposed UPS-DELFBC is useful to maintain the adequate diversity in the population and avoid the premature convergence during the generational cycle. Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria.

Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria.

This paper develops a promising UPS-DELFBC approach to solve MOPs. The TDO problems for three different transformer specifications, with 160, 400 and 630 kVA, have been addressed in this paper. Optimization results show the potential and efficiency of the UPS-DELFBC to solve multiobjective TDO and to produce multiple Pareto solutions.

Energy commodities are characterised by rigid demand and high price volatility, linked to many variables such as climate factors, exchange rates, availability of resources. At the same time, the authorities often set prices, so wholesale energy companies need to create margins carefully by managing the procurement process and selecting appropriate tools to manage the risks associated with the volatility of energy prices. The purpose of this paper is to analyse and evaluate price and volume risks in the energy procurement process considering a “non-speculative” point of view, which is understudied in the literature review.

The paper adopts a quantitative approach to risk evaluation, based on accounting indicators, and applies it to a large Italian energy wholesale company.

A set of key risk indicators to measure price and volume risks is presented in the results, split into synthesis risk, unbalanced risks, modulation risks and risks derived from bilateral contracts. These indicators are applied to the case study, and each risk is prioritised and discussed.

This contribution is one of the first attempts to analyse energy procurement risks in a non-speculative approach. The proposed method allows: first, to evaluate and prioritise the three major types in the energy procurement process, second, to observe the trend of risk exposure, third, the performance measurement of the procurement process, and fourth, benchmarking activities if widely implemented in the energy sector.

The aim of this paper is to compare the performance of static VAR compensator (SVC) and unified power flow controller (UPFC) in dynamic economic dispatch (DED) problem. DED schedules the online generator outputs with the predicted load demands over a certain period so that the electric power system is operated most economically. During last decade, flexible alternating current transmission systems (FACTS) devices are broadly used for maximizing the loadability of existing power system transmission networks. However, based on the literature survey, the performance of SVC and UPFC incorporated in the DED problem and its cost–benefit analysis are not discussed earlier in any of the literature.

Here, the DED problem is solved applying ABC algorithm incorporating SVC and UPFC. The following conditions are investigated with the incorporation of SVC and UPFC into DED problem: the role of SVC and UPFC for improving the power flow and voltage profile and the approximate analysis on cost recovery and payback period with SVC and UPFC in DED problem.

The incorporation of FACTS devices reduces the generation cost and improves the stability of the system. The percentage cost recovered with FACTS devices is estimated approximately using equated monthly installment (EMI) and non-EMI scheme. It is clear from the illustrations that the installation of FACTS devices is profitable after a certain period.

In this research work, the generation cost with FACTS devices is only taken into account while calculating the profit. The other benefits like congestion management, cost gained due to land and cost due to stability issues are not considered. For future work, these things can be considered while calculating the benefit.

The originality of the work is incorporation of FACTS devices in DED problem and approximate estimation of recovery cost with FACTS devices in DED problem.

The purpose of this paper is to focus on two major areas of concern for the Photovoltaic (PV) system, i.e. power quality and maximum power point tracking (MPPT). Novel control strategies have been proposed for both these issues, and their respective superiorities over the existing techniques have been established. On the other hand, as far as MPPT is concerned, two limitations are found in the available techniques. One is the inability of effective MPPT in dynamic conditions where the environmental parameters changes very rapidly. Second one is the ineffective tracking of global maxima under partial shading conditions.

Here, modified Kalman filtering approach has been applied for estimating the reference current of active power filter, incorporated for power quality improvement. The proposed Kalman algorithm introduces a weighted matrix, which advances the estimated values of state variables. This paper presents a simple and enhanced model-based (MB) MPPT algorithm that has the capability of tracking MPPT effectively in both these working conditions. The proposed MB algorithm uses the mathematical modelling, and based on precised estimation of parameters, it pre-determines the MPP analytically.

It has been tested successfully for dynamic variations of insolation, temperature and partial shading, where all these three parameters are rigorously varied over the full scale of practical values. The results have been also investigated experimentally and compared with the simulated one. A close matching of both the results has been shown through the plots, which validates the effectiveness of proposed algorithms.

This research paper is part of the original research work carried out in Lab. Simulated results are obtained in MATLAB/Simulink platform, whereas these are further validated experimentally on 2-KW panel constituted with all types of commercial products, namely, mono, poly and thin-film.

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.

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.

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.

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.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

This study aims to look at the effects of the Israeli occupation on the mental health of Palestinians and examine the link between political oppression and the occurrence of mental health disorders. It argues that, as human rights violations in Palestine are connected to psychological distress, the root causes of social suffering need to be considered in order not to pathologize Palestinians. The purpose of this paper lies in connecting the mental health discourse with a human rights approach to better understand this connection within the context of political violence.

The paper presents the viewpoint and perspectives of the authors on significant mental health issues in Palestine. The methodology is based on a literature review of the de-politicization of the mental health discourse and on the theoretical framework of a human rights approach. At the base of this discourse lies the demand for social justice and professional solidarity.

The study highlights that to truly understand social suffering in Palestine, it needs to be related to the prevalence of human rights violations, which in turn have a conceivable impact on the mental health well-being of individuals. It advocates for a shift from a de-contextualized, de-politicized and individualistic approach to mental health to acknowledging the importance of the social and political context in which trauma develops. It further illustrates how the adaptation of a human rights approach can strengthen demands of social justice and oppose the victimization of Palestinians.

The value of the works lies in putting the prevalence of mental health disorders in Palestine in relation to human rights violations as a consequence of the ongoing Israeli occupation and in highlighting the role that international organizations play in the de-politicization of the mental health discourse.

The purpose of this study is to investigate how board characteristics impact the governance, environmental and ethics disclosure. Board characteristics such as board size, gender diversity, board independence, CEO/chair duality and board meeting are included.

This study is based on a sample of 82 companies listed in the SBF120 between 2012 and 2017. A number of econometric techniques are used such as generalized least squares to test the panel regressions.

Board independence, board gender diversity and board meetings have a positive and significant influence on governance, environmental and ethics disclosure. Board size is positively and significantly associated only with corporate environmental disclosure. The adoption of Global Reporting Initiatives (GRI, G4) has not affected or biased the corporate governance (CG), environmental and ethics disclosure.

This study adds to the literature on management reporting behavior and ethics and contributes to the extant CG literature by offering new evidence on the disclosure of good CG practices as well as environmental and ethics behavior. This study offers new insights about the potential influence of board characteristics on such specific disclosure practices focusing “during the optional period of GRI4 and after their mandatory adoption”.