Measuring Energy Security

Continuity of energy supplies is a central aspect of concerns about energy security. Although the continuity of supplies can be influenced by a large number of risks, most models only analyse a small subset of risk sources and often neglect interdependencies between them. In this paper we introduce a probabilistic time-series model that quantifies the impact of inter-dependent natural, technical and human risk sources on energy supply continuity. Based on a case study of Italian gas and electricity markets we conclude that typical simplifications in time-series models and alternative approaches lead to a bias, which justifies the usage of detailed time-series models of interdependent risks such as the framework suggested in this paper, even though more detailed versions of this and other frameworks may quickly become very resource intensive

Robustness of Various Capacity Mechanisms to Regulatory Errors

In the EU, several governments have introduced or are contemplating a capacity mechanism to ensure adequate investment in generation capacity. Previous research has focused on the impacts of capacity mechanisms on installed capacity and cost to consumers in case of efficient regulation. By contrast we find that the choice between capacity mechanisms may be influenced by the extent of regulatory errors as well as whether the mechanisms evaluated from the perspective of consumer cost or from a welfare perspective

Tariff menus to avoid rebound peaks : results from a discrete choice experiment with Swiss customers

While automation helps to increase load-shifting, the combination of automation with time-of-use (TOU) or critical-peak prices (CPP) may lead to rebound peaks at the beginning of low-tariff periods which may exceed the original peak. Using a discrete choice experiment with a representative sample of 696 Swiss consumers, we find that a tariff menu including (i) a flat price with direct load control (DLC) and (ii) a time-of-use tariff without direct load control could avoid this problem. The majority (57%) of mostly younger customers, which could be interested in automation would likely sign up for a DLC with flat prices, while the remaining customers would either chose a TOU tariff with manual load control (28%) or avoid any form of load-shifting incentives (15%)

Impacts of traffic data on short-term residential load forecasting before and during the COVID-19 pandemic

Accurate load forecasting is essential for power-sector planning and management. This applies during normal situations as well as phase changes such as the Coronavirus (COVID-19) pandemic due to variations in electricity consumption that made it difficult for system operators to forecast load accurately. So far, few studies have used traffic data to improve load prediction accuracy. This paper aims to investigate the influence of traffic data in combination with other commonly used features (historical load, weather, and time) – to better predict short-term residential electricity consumption. Based on data from two selected distribution grid areas in Switzerland and random forest as a forecasting technique, the findings suggest that the impact of traffic data on load forecasts is much smaller than the impact of time variables. However, traffic data could improve load forecasting where information on historical load is not available. Another benefit of using traffic data is that it might explain the phenomenon of interest better than historical electricity demand. Some of our findings vary greatly between the two datasets, indicating the importance of studies based on larger numbers of datasets, features, and forecasting approaches

Remote Ischemic Preconditioning Neither Improves Survival nor Reduces Myocardial or Kidney Injury in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI)

BACKGROUND: Peri-interventional myocardial injury occurs frequently during transcatheter aortic valve implantation (TAVI). We assessed the effect of remote ischemic preconditioning (RIPC) on myocardial injury, acute kidney injury (AKIN) and 6-month mortality in patients undergoing TAVI. METHODS: We performed a prospective single-center controlled trial. Sixty-six patients treated with RIPC prior to TAVI were enrolled in the study and were matched to a control group by propensity-score. RIPC was applied to the upper extremity using a conventional tourniquet. Myocardial injury was assessed using high-sensitive troponin-T (hsTnT), and kidney injury was assessed using serum creatinine levels. Data were compared with the Wilcoxon-Rank and McNemar tests. Mortality was analysed with the log-rank test. RESULTS: TAVI led to a significant rise of hsTnT across all patients (p < 0.001). No significant inter-group difference in maximum troponin release or areas-under-the-curve was detected. Medtronic CoreValve and Edwards Sapien valves showed similar peri-interventional troponin kinetics and patients receiving neither valve did benefit from RIPC. AKIN occurred in one RIPC patient and four non-RIPC patients (p = 0.250). No significant difference in 6-month mortality was observed. No adverse events related to RIPC were recorded. CONCLUSION: Our data do not show a beneficial role of RIPC in TAVI patients for cardio- or renoprotection, or improved survival

Simultaneous Regeneration of Two 160 Gbit/s WDM Channels in a Single Highly Nonlinear Fiber

We experimentally demonstrate simultaneous all-optical regeneration of two 160-Gbit/s wavelength-division multiplexed (WDM) channels in a single highly nonlinear fiber (HNLF). The multi-channel regeneration performance is confirmed by bit-error rate (BER) measurements. The receiver powers at a BER of 10-9 are improved by about 4.9 dB and 2.1 dB for the two channels, respectively. The BER performance is not degraded by the presence of a second channel. Mitigation of the inter-channel nonlinearities is achieved through bidirectional propagation.</p

A complete genome sequence of Cupriavidus necator H16 (DSM 428)

The hydrogen-utilizing strain Cupriavidus necator H16 (DSM 428) was sequenced using a combination of PacBio and Illumina sequencing. Annotation of this strain reveals 6,543 protein-coding genes, 263 pseudogenes, 64 tRNA genes, and 15 rRNA genes

Metabolic engineering of Cupriavidus necator H16 for heterotrophic and autotrophic production of 3-hydroxypropionic acid

3-Hydroxypropionate (3-HP) is a versatile compound for chemical synthesis and a potential building block for biodegradable polymers. Cupriavidus necator H16, a facultative chemolithoautotroph, is an attractive production chassis and has been extensively studied as a model organism for biopolymer production. Here, we engineered C. necator H16 for 3-HP biosynthesis from its central metabolism. Wild type C. necator H16 can use 3-HP as a carbon source, a highly undesirable trait for a 3-HP production chassis. However, deletion of its three (methyl-)malonate semialdehyde dehydrogenases (mmsA1, mmsA2 and mmsA3) resulted in a strain that cannot grow on 3-HP as the sole carbon source, and this strain was selected as our production host. A stepwise approach was used to construct pathways for 3-HP production via β-alanine. Two additional gene deletion targets were identified during the pathway construction process. Deletion of the 3-hydroxypropionate dehydrogenase, encoded by hpdH, prevented the re-consumption of the 3-HP produced by our engineered strains, while deletion of gdhA1, annotated as a glutamate dehydrogenase, prevented the utilization of aspartate as a carbon source, one of the key pathway intermediates. The final strain carrying these deletions was able to produce up to 8 mM 3-HP heterotrophically. Furthermore, an engineered strain was able to produce 0.5 mM 3-HP under autotrophic conditions, using CO2 as sole carbon source. These results form the basis for establishing C. necator H16 as an efficient platform for the production of 3-HP and 3-HP-containing polymers

Social innovation supports inclusive and accelerated energy transitions with appropriate governance

Accelerating energy transitions that are both sustainable and just remains an important challenge, and social innovation can have a key role in this transition. Here, we examine the diversity and potential of social innovation in energy systems transformation, synthesizing original mixed methods data from expert interviews, document analysis, social innovation experiments, a representative survey, and an expert survey. Based on a thematic analysis of these data, we advance four key findings: (1) the diversity of social innovation in energy is best understood when recognizing core social practices (thinking, doing, and organizing) and accounting for changes in social relations (cooperation, exchange, competition, and conflict); (2) governance, policy networks, and national context strongly shape social innovation dynamics; (3) processes of social innovation are implicated by multidimensional power relations that can result in transformative changes; and (4) social innovation in energy generally has strong social acceptance among citizens, benefits local communities and is legitimized in key community and city organizations. We discuss an agenda for 9 future research directions on social innovation in energy, and conclude with insights related to national context, governance, and acceleration