Abstract
We adopt in this paper a perspective of portfolios of real options, to propose a mixed integer linear programming model for multistage Transmission Network Expansion Planning. The model is then used to analyze three fundamental network building blocks - an independent design, a radial design, and a meshed design - seeking to develop network design insights, in particular regarding the joint value of postponement and other sources of operational flexibility. The results clearly point to the importance of explicitly incorporating uncertainty, adopting a multistage perspective, and addressing complex interactions between different sources of flexibility, in the design of transmission networks.

Abstract

Abstract
In biped locomotion, the energy minimization problem is a challenging topic. This problem cannot be solved analytically since modeling the whole robot dynamics is intractable. Using the inverted pendulum model, researchers have defined the Zero Moment Point (ZMP) target trajectory and derived the corresponding Center of Mass (CoM) motion trajectory, which enables a robot to walk stably. A changing vertical CoM position has proved to be crucial factor in reducing mechanical energy costs and generating an energy efficient walk [1]. The use of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) on a Fourier basis representation, which models the vertical CoM trajectory, is investigated in this paper to achieve energy efficient walk with specific step length and period. The results show that different step lengths and step periods lead to different learned energy efficient vertical CoM trajectories. For the first time, a generalization approach is used to generalize the learned results, by using a programmable Central Pattern Generator (CPG) on the learned results. Online modulation of the trajectory is performed while the robot changes its walking speed using the CPG dynamics. This approach is implemented and evaluated on the simulated and real NAO robot.

Abstract
In recent years the reassessment of remuneration schemes for renewable sources in several European countries has motivated the increase of wind power generation participation in electricity markets. Moreover, the continuous growth of wind power generation, as well as the evolution of wind turbines technology, suggests that wind power plants may participate in both energy and ancillary services markets with strategic behavior to improve their benefits. Thus, wind power generation with strategic behavior may have impact on market equilibrium and pricing. This paper evaluates the impact of a proportional offering strategy for wind power plants to participate in both energy and ancillary services markets. MASCEM (Multi-Agent System for Competitive Electricity Markets) is used to simulate and validate the impact of wind power plants in market equilibrium. A case study based on real and recent data for the Iberian market and its specific rules is simulated in MASCEM. © 2015 IEEE.

Abstract
The main goal of the ANTAREX project is to express by a Domain Specific Language (DSL) the application self-adaptivity and to runtime manage and autotune applications for green and heterogeneous High Performance Computing (HPC) systems up to the Exascale level. Key innovations of the project include the introduction of a separation of concerns between self-adaptivity strategies and application functionalities. The DSL approach will allow the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management.

Abstract
The need for efficient automation methods has prompted the rapid development in the field of Robotics. The development of intelligent robots leads to the ability of them becoming an operator highly efficient and able to adapt to a wide range of problems. Still, despite of the several robotic solutions available, the majority of current industrial robots do not use the Robotic Operative System (ROS) and have limitations in terms of autonomously correct errors during their tasks. An important aspect to consider when developing a new robot is the selection of the methodology for recognition of the objects to be handled. In this paper, it will be presented an approach with enough flexibility to be potentially applicable to different scenarios of object recognition and handling normally found in industrial environment. The main aim is for this application to be applied to pick and place routines in robotics. Moreover it will be presented one particular case study that used the proposed approach, the European Robotics Challenges (EUROC) - a challenge aiming to develop a robot for shop floor logistics and manipulation. Our proposed approach is based on the three tiers paradigm: 1-recognition/sensing tier, 2-effector tier and 3-the control tier and was built using the ROS framework. Since ROS is becoming one of the most useful tools in robotics nowadays, the possibility of using a methodology able to be expressed in ROS allows for the development of a standard approach to pick and place operations. Another advantage of our proposed pick and place approach is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to the insertion of an adaptive control tier in our methodology. The proposed approach can be valuable in the field of robotics and can be potentially applied in multiple tasks and it has already allowed us to advance to the next stage of the already mention challenge.