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In this contribution, we discuss the implementation of a novel microelectromechanical-systems (MEMS)-based energy harvester (EH) concept within the technology platform available at the ISAS Institute (TU Vienna, Austria). The device, already presented by the authors, exploits the piezoelectric effect to convert environmental vibrations energy into electricity, and presents multiple resonant modes in the frequency range of interest (i.e. below 10 kHz). The experimental characterisation of a sputter deposited aluminium nitride piezoelectric thin-film layer is reported, leading to the extraction of material properties parameters. Such values are then incorporated in the finite element method model of the EH, implemented in Ansys Workbench (TM), in order to get reasonable estimates of the converted power levels achievable by the proposed device solution. Multiphysics simulations indicate that extracted power values in the range of several mu W can be addressed by the EH-MEMS concept when subjected to mechanical vibrations up to 10 kHz, operating in closed-loop conditions (i.e. piezoelectric generator connected to a 100 k Omega resistive load). This represents an encouraging result, opening up the floor to exploitations of the proposed EH-MEMS device in the field of wireless sensor networks and zero-power sensing nodes.

Computers can reduce their power consumption by decreasing their speed using Dynamic Voltage and Frequency Scaling (DVFS). A form of DVFS for multicore processors is global DVFS, where the voltage and clock frequency is shared among all processor cores. Because global DVFS is efficient and cheap to implement, it is used in modern multicore processors like the IBM Power 7, ARM Cortex A9 and NVIDIA Tegra 2. This theory oriented paper discusses energy optimal DVFS algorithms for such processors. There are no known provably optimal algorithms that minimize the energy consumption of nontrivial real-time applications on a global DVFS system. Such algorithms only exist for single core systems, or for simpler application models. While many DVFS algorithms focus on tasks, this theoretical study is conceptually different and focuses on the amount of parallelism. We provide a transformation from a multicore problem to a single core problem, by using the amount of parallelism of an application. Then existing single core algorithms can be used to find the optimal solution. Furthermore, we extend an existing single core algorithm such that it takes static power into account.

Heating and cooling using aquifer thermal energy storage (ATES) has hardly been applied outside the Netherlands, even though it could make a valuable contribution to the energy transition. The Climate-KIC project "Europe-wide Use of Energy from aquifers" - E-USE(aq) - aimed to pave the way for Europe-wide application of ATES, through the realization and monitoring of six ATES pilot plants across five different EU countries. In a preceding paper, based on preliminary results of E-USE(aq), conclusions were already drawn, demonstrating how the barriers for this form of shallow geothermal energy can be overcome, and sometimes even leveraged as opportunities. Based on final pilot project results, key economic and environmental outcomes are now presented. This paper starts with the analysis of specific technological barriers: unfamiliarity with the subsurface, presumed limited compatibility with existing energy provision systems (especially district heating), energy imbalances and groundwater contamination. The paper then shows how these barriers have been tackled, using improved site investigation and monitoring technologies to map heterogeneous subsoils. In this way ATES can cost-efficiently be included in smart grids and combined with other sources of renewable (especially solar) energy, while at the same time achieving groundwater remediation. A comparative assessment of economic and environmental impacts of the pilots is included, to demonstrate the sustainability of ATES system with different renewables and renewable-based technologies. The paper concludes with an assessment of the market application potential of ATES, including in areas with water scarcity, and a review of climate beneficial impact.

The introduction of local, often uncontrollable, generation units as well as larger loads such as electric vehicles (EVs) causes an increasing amount of stress on our energy supply chain, specifically on the distribution grids. Demand-side management (DSM) is often seen as a potential technology to counter-act this increasing stress on the (distribution) grid. An important and expensive asset within these grids are the power transformers. Thus, economic incentives for DSM can be obtained by decreasing transformer ageing. To study the potential of using DSM to decrease transformer ageing, we consider an ageing model of distribution transformers based on the load profile being supplied by the transformer. We combine this with an optimization problem to find optimal charging profiles of EVs w.r.t. transformer ageing. Furthermore, we compare the results of the optimization problem to three other charging strategies. We conclude that smart charging strategies can give improvements of up to two orders of magnitude in reducing the ageing incurred by EV charging over the base load. Furthermore, we show that for the considered scenarios, a DSM strategy that steers towards the flattening of a neighbourhood's load profile gives similar results to our approach, which directly optimizes transformer lifetime.

Electricity grids are in a transition phase. With the rise of renewable energy, energy "prosumers," and electric vehicles, traditional models of matching supply and demand are no longer adequate. Grid pilot projects can help identify ways to improve cybersecurity in future grids.