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The purpose of this paper is to study very fast transient overvoltages (VFTOs) in the secondary winding of air‐cored Tesla transformers and also study the resulting electric field stresses.

An exhaustive model based on Multi‐conductor Transmission Lines (MTLs) theory has been used. The governing telegraphist's equations have been solved by Finite Difference Time Domain (FDTD) method.

The results demonstrated that there are some overvoltages at the end and middle turns that should be considered in insulation design. The magnitudes of these overvoltages are several times more than the steady state value of the corresponding turn which cause very high electric field stresses.

The paper describes results obtained from an original and innovative implementation of FDTD method in transmission line modelling and is applied properly to air‐cored pulse transformers.

This paper aims to present the proposition of a new experimental method for obtaining very crucial data of the structural steel that is used in the tank of oil filled power transformers, namely, the volumetric losses and the magnetic permeability, both in function of the density of magnetic flux. Although these data are not usually available, they are fundamental for helping the transformer designer in avoiding the occurrence of hot spots in the transformer tank. The adoption of a conventional Epstein frame has restrictions because of the incompatibility between it and the samples of the steel.

The basis of the proposition is the same as that of the Epstein frame, with significant attention paid to the additional losses in the winding that creates the magnetic flux to the samples in the core. These losses can be significant and are created by the harmonics of current along the windings and are summed to the ohmic losses. For separating these winding losses from the magnetic losses, each sample is made as being the core of a toroidal 1:1 transformer. Thus, two tests with two identic of these toroidal transformers are necessary.

The proposed methodology is simple, because it is very similar to the classical tests of transformers (no-load and short-circuit tests). The process of separation of losses requires only a numerical fitting of curves for adjusting the winding losses as a function of the current amplitude, and the obtained results are coherent with the expected behavior of the magnetic losses and the magnetic permeability of a structural steel.

The method gives very approximate results in comparison to those obtained using the Epstein frame. The influences of the temperature and/or of the skin effect have not been evaluated.

Practical, real and thus confident data of structural steel, such as the magnetic permeability and the volumetric losses (hysteresis and Foucault), become available for the transformer designer to take actions for not only reducing the tank losses but also for avoiding the occurrence of hot spots through computer simulation.

The proposition is very new, as it allows to test steel samples with a size that does not fit to a usual Epstein frame. It takes into account the real influence of harmonic of currents in the losses along the winding of a classical Epstein frame, which has not been so far mentioned. It allows obtaining data of structural steel that had not been considered important until now.

In the context of a developing country, Indian buildings need further research to channelize energy needs optimally to reduce energy wastage, thereby reducing carbon emissions. Also, reduction in smart devices’ costs with sequential advancements in Information and Communication Technology have resulted in an environment where model predictive control (MPC) strategies can be easily implemented. This study aims to propose certain preemptive measures to minimize the energy costs, while ensuring the thermal comfort for occupants, resulting in better greener solutions for building structures.

A simulation-based multi-input multi-output MPC strategy has been proposed. A dual objective function involving optimized energy consumption with acceptable thermal comfort has been achieved through simultaneous control of indoor temperature, humidity and illumination using various control variables. A regression-based lighting model and seasonal auto-regressive moving average with exogenous inputs (SARMAX) based temperature and humidity models have been chosen as predictor models along with four different control levels incorporated.

The mathematical approach in this study maintains an optimum tradeoff between energy cost savings and satisfactory occupants’ comfort levels. The proposed control mechanism establishes the relationships of output variables with respect to control and disturbance variables. The SARMAX and regression-based predictor models are found to be the best fit models in terms of accuracy, stability and superior performance. By adopting the proposed methodology, significant energy savings can be accomplished during certain hours of the day.

This study has been done on a specific corporate entity and future analysis can be done on other corporate or residential buildings and in other geographical settings within India. Inclusion of sensitivity analysis and non-linear predictor models is another area of future scope.

This study presents a dynamic MPC strategy, using five disturbance variables which further improves the overall performance and accuracy. In contrast to previous studies on MPC, SARMAX model has been used in this study, which is a novel contribution to the theoretical literature. Four levels of control zones: pre-cooling, strict, mild and loose zones have been used in the calculations to keep the Predictive Mean Vote index within acceptable threshold limits.