• Energy Research

Abstract The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets in greenhouse gas reduction set forth in the Paris Agreement of 2015. Reducing uncertainty about demand and, in case of renewable electricity generation, supply is important for the determination of spot electricity prices. In this work we propose and evaluate a context-based technique to anticipate the electricity production and consumption in buildings. We focus on a household with photovoltaics and energy storage system. We analyze the efficiency of Markov chains, stride predictors and also their combination into a hybrid predictor in modelling the evolution of electricity production and consumption. All these methods anticipate electric power based on previous values. The main goal is to determine the best method and its optimal configuration which can be integrated into a (possibly hardware-based) intelligent energy management system. The role of such a system is to adjust and synchronize through prediction the electricity consumption and production in order to increase self-consumption, reducing thus the pressure over the power grid. The experiments performed on datasets collected from a real system show that the best evaluated predictor is the Markov chain configured with an electric power history of 100 values, a context of one electric power value and the interval size of 1.

Abstract Two-stage anaerobic digestion (AD) is a promising method of converting organic waste into clean and sustainable energy. This work aimed to study the efficiency of a two-stage AD system with the production of hydrogen at the first acidogenic stage and methane in an electromethanogenic reactor. Two types of biocathodes based on carbon cloth were used in the electromethanogenic reactor: with and without retention of biomass on the electrode surface. A high applied voltage continuously supplied to the pair of electrodes was automatically maintained at 2.5 V. Hydrogen yield (0.11 NL/g volatile solids (VS)init or 2 mol H2/mol hexose) and hydrogen content in biogas (52%) were relatively high, even despite the extremely low pH (∼4.0). Improved retention of biomass on the surface of the carbon cloth-based biocathode led to greater stability of the AD process (no water electrolysis was observed) and a significant increase in the efficiency of electromethanogenesis, including the methane yield (by 40.5% up to 0.39 NL/g VSinit), volumetric methane production rate (by 38.8% up to 1.16 NL/L/d) and current density (by 233% up to 0.56 A/m2).

In this paper we present EnergySave, a smart energy-saving system that, by leveraging the consolidated WoL (Wake on LAN) technology, allows the remote wake-up of PCs from a centralized management server, providing easy and secure power management capabilities for local or remote IP-based networks of personal computers (PCs). We also present a lightweight web-based platform implementing the remote management interface as less intrusively as possible. Finally, we model the mathematical saving functions to be used in order to evaluate through simulation the amount of potential energy savings, and hence the whole framework effectiveness, both in the general case and in a real case scenario. Results show that significant savings are achievable provided that the hardware supports the Wake-on-LAN specifications and that proper configuration of the Web server is set-up, allowing the WoL magic packet to travel to the destination hosts and wake them up only when they are really needed. Peer Reviewed

Energy consumption is now one of the most important issues for network carriers, since the majority of the energy needed for their operation is consumed in the wireless access and optical transport networks. The continuous growth in the wireless customers and traffic volumes and the consequent energy demand on modern carriers’ broadband infrastructures require reconsidering their energy efficiency, by starting from the formulation of new, more complete and representative network models that should become the foundations for modern energy-aware control plane architectures. Accordingly, this work presents a novel comprehensive energy model for next-generation wireless access-over-optical-transport networks characterized by hybrid power systems (i.e., multiple dynamically available power sources). The objective is to identify the energy-related information that need to be handled at the control plane layer to support energy-aware networking practices. Such information can be made available to suitable energy-aware routing and wavelength assignment algorithms that may exploit them to optimize the overall network energy-consumption and reducing the associated carbon footprint. The proposed model may be taken as a reference for the implementation of new energy-aware control plane protocols (routing and signaling) that make use of power-related considerations to achieve energy-efficiency and energy-awareness in wavelength-routed network infrastructures. Peer Reviewed

In recent years, more and more countries have paid close attention to energy and environmental issues [...]

This work analyzes a new and very subtle kind of security threat that can affect large-scale cloud-based IT service infrastructures, by exploiting the computational resources of their component data center to waste as much energy as possible. The consequence of these threats ranges from increased costs in the energy bill, to penalization for exceeding the agreed quantity of greenhouse gases (GHG) emissions, up to complete denial of service caused by electrical outages due to power budget exhaustion. We analyzed different types of such attacks with their potential impacts on the energy consumption, modeled their behavior and quantified how current energy-proportional technologies may provide attackers with great opportunities for raising the target facility emissions and costs. These efforts resulted in a simple model with some parametric reference values that can be used to estimate the impact of such attacks also in presence of very large infrastructures containing thousands or millions of servers. Peer Reviewed