Abstract
A novel faults analysis method with multiple PV grid-connected inverters for distribution systems is proposed. The aforesaid proposed method Inverter Matrix Impedance Current Vector (IMICV) employs symmetrical components combined with a matrix denominated of Inverter Matrix Impedance and with a vector denominated Impedance-Current Vector which are formed by inspection. This matrix and this vector are used to solve a linear system of equations where the following post-fault variables are: current in substation, the voltage at the fault point and voltages in the PV grid-connected nodes. A comparison of results obtained using the new method with the results of the professional software ANAFAS validates the method proposed. Computer simulations show that the proposed method for classical shunt faults analysis is efficient, accurate and easy to program.

Abstract

Abstract
Selecting quality improvement projects among a variety of mutually competing ones is characterised by prioritisation. In practice, this is often done by the rule of thumb, following a single attribute criterion or by subjective preferences of individual stakeholders of a project team. An approach to track systematically nonconformities and to identify those critical ones that should be prioritised based on multi-attribute criteria is presented. The approach is introduced and its purpose is explained. After the background of relevant topics is given, the method's importance in research and for practitioners is derived. Steps of the approach are portrayed and an application case of a mature industrial company, integrated in the supply-chain of the automotive industry, is presented. Elements of quality tools and techniques are used as attributes, namely failure mode and effect analysis and Pareto diagram. Results based on industrial data indicate that the use of this approach contributes to support informed and structured prioritisation decisions, which foster a more efficient improvement of future quality-based projects.

Abstract
The optimization and simulation of power systems continues to be an area of concern for electricity companies and researchers worldwide namely considering the development of electricity markets and competition in the generation activity Therefore generation companies are devoting an increasing attention to market issues justifying the development of models to help them preparing bidding strategies to the day-ahead market. In this context, agent-based models have been reported as a complement to optimization and equilibrium models when the problem is too complex to be analyzed by traditional approaches. This paper details an Agent-Based Model for an electricity market considering a detailed modeling for hydro stations and presents some preliminary results taking the Iberian Electricity Market as an example.

Abstract
Photovoltaic (PV) solar power capacity is growing in several countries, either concentrated in medium/large size solar parks or distributed by the medium and low voltage grid. Solar power forecasting is a key input for supporting grid management, participation in the electricity market and maintenance planning. This paper proposes a new forecasting system that is a hybrid of different models, such as electrical and statistical models, as well as different Numerical Weather Prediction (NWP) sources. The time horizon is 48 hours ahead. The proposed model was operationalized and tested in a real PV installation located in North Portugal with 16 kW.

Abstract
Chord progressions are widely used in music. The automatic generation of chord progressions can be challenging because it depends on many factors, such as the musical context, personal preference, and aesthetic choices. In this work, we propose a penalty function that encodes musical rules to automatically generate chord progressions. Then we use an artificial immune system (AIS) to minimize the penalty function when proposing candidates for the next chord in a sequence. The AIS is capable of finding multiple optima in parallel, resulting in several different chords as appropriate candidates. We performed a listening test to evaluate the chords subjectively and validate the penalty function. We found that chords with a low penalty value were considered better candidates than chords with higher penalty values.