Plug-in electric vehicles (PEVs) have recently attracted much attention due to their potential to reduce CO₂ emissions and transportation costs and can be grouped into entities (aggregators) to provide ancillary services such as frequency regulation. In this paper, the application of aggregators to frequency regulation by making fair use of their energy storage capacity is addressed. When the power grid requires frequency regulation service to the aggregator to adjust the grid frequency, the PEVs participating in providing the service can either draw energy (as it is usually done to charge the vehicle) or deliver energy to the grid by means of the vehicle-to-grid (V2G) interface. Under the general framework of optimizing the aggregator profit, different methods, such as state-dependent allocation and the water-filling approach, are proposed to achieve a final state of charge (SOC) of the PEVs that satisfy the desired fairness criteria once the regulation service has been carried out.

Power line communication, that is, using the electricity infrastructure for data transmission, is experiencing a renaissance in the context ofSmart Grid. Smart Grid objectives include the integration of intermittent renewable energy sources into the electricity supply chain, securing reliable electricity delivery, and using the existing electrical infrastructure more efficiently. This paper surveyspower line communications(PLCs) in the context of Smart Grid. The specificationsG3-PLC,PRIME,HomePlug Green PHY, andHomePlug AV2, and the standardsIEEE 1901/1901.2andITU-T G.hn/G.hnemare discussed.

In this paper, we describe a framework for the selection of the best charging station when plug-in electric vehicles (PEV) need to recharge their batteries, while at the same time the power utilities, which own the charging stations (CS), optimize their revenue. We use two-way communication to transmit positioning information, which is a key factor so that the plug-in electric vehicles evaluate its required energy. Within this framework, we also describe a procedure that is implemented in a distributed manner and is based on a non-cooperative oligopoly game that makes use of differentiated products theory and conjectural variations to provide a Nash equilibrium in prices and quantities.

El escenario actual de crisis y cambios ha llevado a pensar en el emprendimiento como una nueva v The current scenario of crisis and change has prompted the idea of entrepreneurship as a way to develop new media business models that can be promoted by university training. In this study, we aim to assess the effects of such training. A qualitative study was conducted using in-depth interviews of Spanish journalism and communication entrepreneurs who have undergone university training in business creation and management. Our results show the positive effects of this training on entrepreneurship both in general and on specific aspects of entrepreneurial projects such as organization, business plan/model, marketing, innovation, social aspects and quality of life. Different patterns between the effects of university training on new initiatives and advanced projects were also observed. In this respect, the training supported the creation of new businesses and the development of existing ones. Finally, the suggestions for improving training and the limitations to entrepreneurship have revealed the importance of providing this type of education with a more practical, up-to-date approach that is interconnected with the business and university world. Therefore, examples of this work can be of vital importance in opening up new opportunities for sector development to enable future generations of journalists to fulfill their important social function.

Forecasting of stock market returns is a challenging research activity that is now expanding with the availability of new data sources, markets, financial instruments, and algorithms. At its core, the predictability of prices still raises important questions. Here we discuss the economic significance of the prediction accuracy. To develop this question, we collect the daily series prices of almost half of the publicly traded companies around the world over a period of ten years and formulate some trading strategies based on their prediction. Proper visualization of these data together with the use of the No Free Lunch theoretical framework give some unexpected results that show how the a priori less accurate algorithms and inefficient strategies can offer better results than the a priori best alternatives in some particular subsets of data that have a clear interpretation in terms of economic sectors and regions.

We consider the problem of minimizing transmission energy in wireless sensor networks by taking into account that every sensor may require a different bit rate and reliability according to its particular application. We propose a cross-layer approach to tackle such a minimization in centralized networks for the total transmission energy consumption of the network: in the physical layer, for each sensor the sink estimates the channel gain and adaptively selects a modulation scheme; in the MAC layer, each sensor is correspondingly assigned a number of time slots. The modulation level and the number of allocated time slots for every sensor are constrained to attain their applications bit rates in a global energy-efficient manner. The signal-to-noise ratio gap approximation is used in our exposition in order to jointly handle required bit rates, transmission energies, and symbol error rates.