Abstract
The design of the switched reluctance machine involves several variables that impact the performance of the machine in different ways. The topology, polar arcs, internal and external diameter, number of turns and core length are some of the parameters that must be determined at the design stage. The effect of geometric parameters on performance is different for each switched reluctance machine topology, so this study is dedicated to establishing a sensitivity analysis for two popular topologies, a three-phase 6/4 and a four-phase 8/6. The performance results are estimated through finite element simulations and the dimensional effects analysis is performed using statistical software. The results show the dimensions with the greatest effect on the average torque value and total losses on the machine and can be useful to support the choices made during the design and optimization of this type of machine.

Abstract
A considerable amount of research within the last few decades has been focusing on controllers for switched reluctance motor drives and how they affect the torque ripple. Despite all its potentials, there are still major concerns and obstacles to overcome concerning the dependency of the magnetic characteristic of the switched reluctance motor. This work targets these concerns by proposing an initial study of the fundamentals of a drive scheme using a finite set model predictive control for a switched reluctance motor through an asymmetric bridge converter. The implementation of this scheme is the main contribution of this paper. The method uses the dynamic model of the motor to estimate the future behavior of the current for each converter state. A cost function then evaluates which switching state minimizes the current error and applies it to the motor. Some simulation results illustrate the technique. Simulation results show the good performance of the method with fast and accurate transient response. © IFIP International Federation for Information Processing 2020.

Abstract
Purpose The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance. Design/methodology/approach In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements. Findings The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model. Originality/value The proposed approach can be applied to any problem as long as experimental/computational results can be obtained and will deliver the best approximation model to the available data set.

Abstract

Abstract
The large-scale deployment of smart home technologies will unlock the flexibility of prosumers, which in turn will be transformed into electricity market services by aggregators. This paper proposes a new network-constrained bidding optimization strategy to coordinate the participation of aggregators of prosumers in the day-ahead energy and secondary reserve markets. This bidding optimization strategy consists of a decentralized approach based on the alternating direction method of multipliers, where aggregators negotiate with the distribution system operator to obtain network-constrained energy and secondary reserve bids. For a case study of 2 aggregators and 1 distribution system operator, the results show that the network-constrained bidding strategy computes cost-effective and network-feasible energy and secondary reserve bids, as opposed to a network-free bidding strategy. In addition, the network-constrained bidding strategy preserves the independent roles of aggregators and the distribution system operator, and the data privacy of all agents.

Abstract
Over the past few decades, much has been done globally to make final energy consumption more sustainable, integrating more renewable resources. In Europe, there are many directives and regulations that imposes to the states ambitious targets on the promotion of renewable energies and energetic efficiency among others. Portugal has not only fulfilled all the goals but has also exceeded them. This is the case with the integration of renew ables in electricity consumption, which is currently rated at 53 %, with the prospect of reaching 80% in 2030. In this scenario, it is important to encourage the energy production from the solar resource as the country has optimal conditions for this purpose. This research assess the existing Portuguese potential for floating photovoltaic systems and its integration in the power grid. Another aim of this study is to sizing and assesses the energetic potential of floating solar power plant in Gouvaes dam, included in the Tamega hydroelectric complex in under construction in northern Portugal belong to Iberdrola Company.