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Inter-turn winding faults in five-phase ferrite-permanent magnet-assisted synchronous reluctance motors (fPMa-SynRMs) can lead to catastrophic consequences if not detected in a timely manner, since they can quickly progress into more severe short-circuit faults, such as coil-to-coil, phase-to-ground or phase-to-phase faults. This paper analyzes the feasibility of detecting such harmful faults in their early stage, with only one short-circuited turn, since there is a lack of works related to this topic in multi-phase fPMa-SynRMs. Two methods are tested for this purpose, the analysis of the spectral content of the zero-sequence voltage component (ZSVC) and the analysis of the stator current spectra, also known as motor current signature analysis (MCSA), which is a well-known fault diagnosis method. This paper compares the performance and sensitivity of both methods under different operating conditions. It is proven that inter-turn faults can be detected in the early stage, with the ZSVC providing more sensitivity than the MCSA method. It is also proven that the working conditions have little effect on the sensitivity of both methods. To conclude, this paper proposes two inter-turn fault indicators and the threshold values to detect such faults in the early stage, which are calculated from the spectral information of the ZSVC and the line currents.

Intra-day price spreads are of interest to electricity traders, storage and electric vehicle operators. This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast the German electricity price spreads between different hours of the day, as revealed in the day-ahead auctions. The four specifications of the density functions are dynamic and conditional upon exogenous drivers, thereby permitting the location, scale and shape parameters of the densities to respond hourly to such factors as weather and demand forecasts. The best fitting and forecasting specifications for each spread are selected based on the Pinball Loss function, following the closed-form analytical solutions of the cumulative distribution functions.

Finding a numerical method to model solute transport in porous media with high heterogeneity is crucial, especially when chemical reactions are involved. The phase space formulation termed the multi-advective water mixing approach (MAWMA) was proposed to address this issue. The water parcel method (WP) may be obtained by discretizing MAWMA in space, time, and velocity. WP needs two transition matrices of velocity to reproduce advection (Markovian in space) and mixing (Markovian in time), separately. The matrices express the transition probability of water instead of individual solute concentration. This entails a change in concept, since the entire transport phenomenon is defined by the water phase. Concentration is reduced to a chemical attribute. The water transition matrix is obtained and is demonstrated to be constant in time. Moreover, the WP method is compared with the classic random walk method (RW) in a high heterogeneous domain. Results show that the WP adequately reproduces advection and dispersion, but overestimates mixing because mixing is a sub-velocity phase process. The WP method must, therefore, be extended to take into account incomplete mixing within velocity classes.

The global increase in energy demand and exponential exhaustion of fossil recourses has favored the development of new systems of electricity production. Photovoltaic solar energy is undoubtedly one that has the highest application in housings, due to its simplicity and easy implementation. In this work, a new prototype of photovoltaic solar tracker with Arduino platform was developed. Feedback control system that allows carrying out solar tracking with two axes using a stepper motor and linear actuator was established through an electronic circuit based on photodiodes. Moreover, real construction of the prototype was carried out, where the effectiveness of the design and its capacity to draw a maximum benefit of an incident radiation can be observed, placing the panel perpendicularly to the received energy and improving its performance for its application in future installations in housings. Results obtained from the comparison between the developed prototype and a static panel oriented according to the latitude of the area, show about 18% energy gain.

The Galapagos Islands have been declared a World Heritage site due to their unique biodiversity, which makes them a living museum and a natural laboratory for humankind. However, to fulfill the energy needs of its habitants and foreign visitors, the islands have depended on fossil fuel energies that have produced levels of lead and chemical agents that are affecting the islands’ air quality, flora, and fauna. Therefore, zero-carbon initiatives have been created to protect the islands, wherein solar and wind power plants have been studied as reliable alternatives. In this way, Geographical Information Systems based on Multicriteria Decision Methods constitute a methodology that minimizes the destruction and disturbance of nature in order to assess the best location for the implementation of these alternative energy sources. Therefore, by exploring the geographical information along with the Analytical Hierarchical Processes and the Ordered Weighted Average methods, it was possible to identify the potential for solar power plants of 10 MW on each island; likewise, for wind power plants, it was found that the islands possess implementation potential that has been analyzed in the field, showing that the best location is on Baltra Island, but is not limited to it.

Results-based financing (RBF) programmes in the clean cooking sector have gained increasing donor interest over the last decade. Although the risks and advantages of RBF have been discussed quite extensively for other sectors, especially health services, there is limited research-documented experience of its application to clean cooking. Due to the sheer scale of the important transition from ‘dirty’ to clean cooking for the 4 billion people who lack access, especially in the Global South, efficient and performance-proven solutions are urgently required. This paper, undertaken as part of the work of the UKAid-funded Modern Energy Cooking Services (MECS) programme, aims to close an important research gap by reviewing evidence-based support mechanisms and documenting essential experiences from previous and ongoing RBF programmes in the clean cooking and other sectors. On this basis, the paper derives key strategic implications and learning lessons for the global scaling of RBF programmes and finds that qualitative key performance indicators such as consumer acceptance as well as longer-term monitoring are critical long-term success factors for RBF to ensure the continued uptake and use of clean cooking solutions (CCS), however securing the inclusion of these indicators within programmes remains challenging. Finally, by discussing the opportunities for the evolution of RBF into broader impact funding programmes and the integration of energy access and clean cooking strategies through multi-sector approaches, the paper illustrates potential steps to enhance the impact of RBF in this sector in the future.