Abstract
The system of symmetrical components (012-system) can be used to simulate symmetrical and asymmetrical operation of power systems. However, the classical literature of Power Systems Analysis does not present one equivalent circuit in 012-system to two-simultaneous faults where there are a single-line-to-ground fault and a bolted line-to-line fault. This paper presents the equations and the new equivalent circuit mentioned. In addition, we present a comparison of results between the proposed approach and the output of the commercial software ANAFAS, which validates the methodology. We find evidence that the new equivalent circuit developed can substitute the equivalent circuits used to calculate a single line-to-ground fault and a bolted line-to-line fault.

Abstract
This article identifies and classifies the key obstacles to wind energy development, in order to better understand these barriers and provide guidelines to help public managers to develop and share new energy policies. The methodology used was a case study with documentary research, carried out through an analysis of the Global Wind Report - Annual Market Update, 2009 to 2013, published by Global Wind Energy Council - GWEC. The results showed a significant occurrence of technological and operational obstacles, especially concerning electricity grids. The results lead to the conclusion that the biggest issue for wind energy development is concentrated in technological and operational obstacles, especially concerning the management of transmission networks. In addition, the results indicate the possibility of countries, with common obstacles, to improve their energy policies in partnership, or share their successful expertises.

Abstract
This paper presents a comparative study on various implementation techniques of Unified Power Flow Controller (UPFC) in load flow algorithms. The comparison is done among; decoupled technique, comprehensive technique, load injection technique, pi load injection technique, indirect technique, and matrix partitioning technique. The merits and demerits of these techniques are presented. Beside these techniques, the paper presents a developed UPFC model based only on current injection approach. The model is implemented in Newton-Raphson current injection load flow method (NR-CIM). This model addresses the main drawbacks of previous techniques. Test results are presented using IEEE standard systems which demonstrate the effectiveness of the developed model.

Abstract
The EU megagrid is foreseen to exploit the very large resource of solar energy in southern Europe and of wind power in northern Europe. Microgrids with enhanced control capabilities can integrate and coordinate local distributed resources enhancing the resilience of the EU megagrid and providing local restoration capabilities. The future modeling challenges of microgrids and in particular the shift to distributed control, enhancing further the microgrids resilience, are highlighted. © 2015 IEEE.

Abstract
This paper deals with integrating energy storage systems (ESS) into existing electricity markets. We explain why ESS increase flexibility of power systems and energy markets and why more flexible systems and markets are desirable, particularly in a context of high integration of variable renewable energy sources (RES). The Dutch electricity markets are introduced as the case studies. As opposing to the existing literature, we focus on implementation of a dual technology ESS, which we believe is more beneficial than a single ESS. To show this, we introduce an optimal control model, in which the goal is to maximize the revenues of the dual technology energy storage system applied into two different energy markets, assuming the selling and buying electricity prices are exogenous. Subsequently, we introduce our model, using a simple strategy and present its results, showing the impact of the devices nominal rating on the potential revenues.

Abstract
In this paper a Distribution State Estimator (DSE) tool suitable for real-time monitoring in poorly characterized low voltage networks is presented. An Autoencoder (AE) properly trained with Extreme Learning Machine (ELM) technique is the "brain" of the DSE. The estimation of system state variables, i.e., voltage magnitudes and phase angles is performed with an Evolutionary Particle Swarm Optimization (EPSO) algorithm that makes use of the already trained AE. By taking advantage of historical data and a very limited number of quasi real-time measurements, the presented approach turns possible monitoring networks where information of topology and parameters is not available. Results show improvements in terms of estimation accuracy and time performance when compared to other similar DSE tools that make use of the traditional back-propagation based algorithms for training execution.