Abstract
This paper addresses the bidding problem faced by an aggregator of small prosumers, when participating in the day ahead energy market. A two-stage stochastic optimization model is proposed to support the aggregator in the definition of optimal and robust demand and supply bids. Stochastic programing is used to deal with uncertainty of end-users' behavior, outdoor temperature, electricity demand and PV generation. The proposed approach was compared to other benchmark strategy, using a case study of 1000 prosumers from the Iberian market.

Abstract
Simple statistical models were developed to relate available meteorological data with daily river discharge (RD) for rivers not influenced by melting of ice and snow. In a case study of the Vouga River (Portugal), the RD could be determined by a linear combination of the recent (P (R)) and non-recent (P (NR)) atmospheric precipitation history. It was found that a simple linear model including only P (R) and P (NR) cannot account for low RD. The model was improved by including non-linear terms of precipitation that accounted for the water loss. Additional improvement of the models was possible by including average monthly air temperature (T). The best model was robust when up to 60% of the original data were randomly removed. The advantage is the simplicity of the models, which take into account only P (R), P (NR) and T. These models can provide a useful tool for RD estimation from current meteorological data.

Abstract
In this paper, we investigate the optical modulation characteristics of a resonant tunnelling diode (RTD) oscillator. This preliminary work on the first RTD-PD oscillators with an optical window available from the iBROW project demonstrate that this device can effectively be used to accomplish amplitude and frequency modulation with light injection.

Abstract
In this paper an innovative, hierarchical, four-level optimization framework is proposed to model the optimal participation of Electric Vehicle Aggregators (EVAs) in day-ahead and real-time energy and regulation markets in conjunction with the optimal real-time charging management of the EV fleet. The scope of the framework is to incorporate in an integrated approach all the conjugated optimization tasks that an EVA should follow for cost-efficient and reliable market participation as well as for successful electric vehicles smart charging in real-time that will satisfy the EV owners. The PJM market design is modeled and a case study with 1000 PHEVs, represented by an EVA, is presented for one operating day. In the base case the EVA participates in the regulation market by following the dynamic regulation control signal. The base case is compared with one where the EVA follows the traditional regulation control signal and one where the EV fleet behaves in real-time differently than initially expected. The presentation of the main functionalities of the framework highlight its ability to model and evaluate the performance of the EV charging process in second-by-second time resolution in a market environment.

Abstract

Abstract
?Finite element analysis is widely used in engineering, and has for some time been used in modelling the behaviour of an induction motor. Limitations and challenges of this approach will be addressed over a case-study commercial 0,37 kW, 4-pole squirrel-cage induction motor simulated using two-dimensional software FEMM. A few notes on the consideration of rotor skew and harmonic distortion in such a model are also included.