On the potential contribution of rooftop PV to a sustainable electricity mix: the case of Spain

This work evaluates the potential contribution of rooftop PV to the future electricity mix. Several sustainable scenarios are considered, each comprising different shares of centralized renewables, rooftop PV and storage. For each generation scenario, the storage capacity that balances the net hourly demand is determined, and the portfolio combination that minimizes the cost of supplying electricity is obtained. The analysis is applied to mainland Spain, using public information and detailed granular models, both in time (hourly resolution) and space (municipal level). For the Spanish case, when the flexibility of hydro and biomass generation is taken into account, the least-cost portfolio involves rather modest storage capacities, in the order of daily rather than seasonal values. This shows that a sustainable, almost emissions-free electricity system for Spain is possible, at a cost that can be even lower than current wholesale market prices.Comment: 7 tables & 11 figures in the main body (24 pages), and 13 pages for the supplementary material, wit

Robustness of electricity systems with nearly 100% share of renewables: a worst-case study

Several research studies have shown that future sustainable electricity systems, mostly based on renewable generation and storage, are feasible with current technologies and costs. However, recent episodes of extreme weather conditions, probably associated with climate change, cast shades of doubt on whether the resulting generation portfolios are sufficiently robust to assure, at all times, a suitable balance between generation and demand, when adverse conditions are faced. To address this issue, this work elaborates a methodology intended to determine a sustainable electricity system that can endure extreme weather conditions, which are likely to occur. First, using hourly production and demand data from the last decade, along with estimates of new uses of electricity, a worst-case scenario is constructed, including the storage capacity and additional photovoltaic power which are needed to serve the demand on an hourly basis. Next, several key parameters which may have a significant influence on the LCOE are considered, and a sensitivity analysis is carried out to determine their real impact, significance and potential trends. The proposed methodology is then applied to the Spanish system. The results show that, under the hypotheses and conditions considered in this paper, it is possible to design a decarbonized electricity system that, taking advantage of existing sustainable assets, satisfies the long-term needs by providing a reliable supply at an average cost significantly lower than current market prices.Comment: 33 pages, 13 figures, 10 table

Solving Optimal Power Flow for Distribution Networks with State Estimation Feedback

Conventional optimal power flow (OPF) solvers assume full observability of the involved system states. However, in practice, there is a lack of reliable system monitoring devices in the distribution networks. To close the gap between the theoretic algorithm design and practical implementation, this work proposes to solve the OPF problems based on the state estimation (SE) feedback for the distribution networks where only a part of the involved system states are physically measured. The SE feedback increases the observability of the under-measured system and provides more accurate system states monitoring when the measurements are noisy. We analytically investigate the convergence of the proposed algorithm. The numerical results demonstrate that the proposed approach is more robust to large pseudo measurement variability and inherent sensor noise in comparison to the other frameworks without SE feedback

Cyber-physical framework for emulating distributed control systems in smart grids

This paper proposes a cyber-physical framework for investigating distributed control systems operating in the context of smart-grid applications. At the moment, the literature focuses almost exclusively on the theoretical aspects of distributed intelligence in the smart-grid, meanwhile, approaches for testing and validating such systems are either missing or are very limited in their scope. Three aspects need to be taken into account while considering these applications: (1) the physical system, (2) the distributed computation platform, and (3) the communication system. In most of the previous works either the communication system is neglected or oversimplified, either the distributed computation aspect is disregarded, either both elements are missing. In order to cover all these aspects, we propose a framework which is built around a fleet of low-cost single board computers coupled with a real-time simulator. Additionally, using traffic control and network emulation, the flow of data between different controllers is shaped so that it replicates various quality of service (QoS) conditions. The versatility of the proposed framework is shown on a study case in which 27 controllers self-coordinate in order to solve the distributed optimal power flow (OPF) algorithm in a dc network

Effect of a Low-Methane Diet on Performance and Microbiome in Lactating Dairy Cows Accounting for Individual Pre-Trial Methane Emissions

Simple Summary Low methane-emitting dietary ingredients have been identified in extensive research conducted during the past decade. This study investigated the effects of replacing grass silage with maize silage, with or without rapeseed oil supplementation, on the methane emissions and performance of dairy cows. Pre-trial measurements of methane-emissions were used in the evaluation. Partial replacement of grass silage with maize silage did not affect methane emissions but reduced dairy cow performance. Adding rapeseed oil to the diet substantially reduced methane emissions due to modified rumen microbiota, resulting in impaired nutrient intake, digestibility, and yield of energy-corrected milk. Correcting for individual cow characteristics of methane emissions did not affect the magnitude of suppression of methane emissions by dietary treatments. This study examined the effects of partly replacing grass silage (GS) with maize silage (MS), with or without rapeseed oil (RSO) supplementation, on methane (CH4) emissions, production performance, and rumen microbiome in the diets of lactating dairy cows. The effect of individual pre-trial CH4-emitting characteristics on dietary emissions mitigation was also examined. Twenty Nordic Red cows at 71 +/- 37.2 (mean +/- SD) days in milk were assigned to a replicated 4 x 4 Latin square design with four dietary treatments (GS, GS supplemented with RSO, GS plus MS, GS plus MS supplemented with RSO) applied in a 2 x 2 factorial arrangement. Partial replacement of GS with MS decreased the intake of dry matter (DM) and nutrients, milk production, yield of milk components, and general nutrient digestibility. Supplementation with RSO decreased the intake of DM and nutrients, energy-corrected milk yield, composition and yield of milk fat and protein, and general digestibility of nutrients, except for crude protein. Individual cow pre-trial measurements of CH4-emitting characteristics had a significant influence on gas emissions but did not alter the magnitude of CH4 emissions. Dietary RSO decreased daily CH4, yield, and intensity. It also increased the relative abundance of rumen Methanosphaera and Succinivibrionaceae and decreased that of Bifidobacteriaceae. There were no effects of dietary MS on CH4 emissions in this study, but supplementation with 41 g RSO/kg of DM reduced daily CH4 emissions from lactating dairy cows by 22.5%

Grid-forming VSC control in four-wire systems with unbalanced nonlinear loads

A grid-forming voltage source converter (VSC) is responsible to hold voltage and frequency in autonomous operation of isolated systems. In the presence of unbalanced loads, a fourth leg is added to provide current path for neutral currents. In this paper, a novel control scheme for a four-leg VSC feeding unbalanced linear and nonlinear loads is proposed. The control is based on two control blocks. A main control commands the switching sequence to the three-phase VSC ensuring balanced three-phase voltage at the output; and an independent control to the fourth leg drives neutral currents that might appear. The proposed control is noninvasive in the sense that both control blocks are independently implemented, avoiding the use of complex modulation techniques such as 3D-SVPWM. Moreover, the main control is deployed in dqo reference frame, which guarantees zero steady-state error, fast transient response during system disturbances and mitigation of harmonics when nonlinear loads are present. Simulations and experimental results are presented to verify the performance of the proposed control strategy.Unión Europea Grant 60777

Comparison of Risk Factors, Safety, and Efficacy Outcomes of Mechanical Thrombectomy in Posterior vs. Anterior Circulation Large Vessel Occlusion

Background and Purpose: It is believed that stroke occurring due to posterior circulation large vessel occlusion (PCLVO) and that occurring due to anterior circulation large vessel occlusion (ACLVO) differ in terms of their pathophysiology and the outcome of their acute management in relation to endovascular mechanical thrombectomy (MT). Limited sample size and few randomized controlled trials (RCTs) with respect to PCLVO make the safety and efficacy of MT, which has been confirmed in ACLVO, difficult to assess in the posterior circulation. We therefore conducted a meta-analysis to study to which extent MT in PCLVO differs from ACLVO.Materials and Methods: We searched the databases PubMed, Cochrane, and EMBASE for studies published between 2010 and January 2021, with information on risk factors, safety, and efficacy outcomes of MT in PCLVO vs. ACLVO and conducted a systematic review and meta-analysis; we compared baseline characteristics, reperfusion treatment profiles [including rates of intravenous thrombolysis (IVT) and onset-to-IVT and onset-to-groin puncture times], recanalization success [Thrombolysis In Cerebral Infarction scale (TICI) 2b/3], symptomatic intracranial hemorrhage (sICH), and favorable functional outcome [modified Rankin Score (mRS) 0–2] and mortality at 90 days.Results: Sixteen studies with MT PCLVO (1,172 patients) and ACLVO (7,726 patients) were obtained from the search. The pooled estimates showed higher baseline National Institutes of Health Stroke Scale (NIHSS) score (SMD 0.32, 95% CI 0.15–0.48) in the PCLVO group. PCLVO patients received less often IVT (OR 0.65, 95% CI 0.53–0.79). Onset-to-IVT time (SMD 0.86, 95% CI 0.45–1.26) and onset-to-groin puncture time (SMD 0.59, 95% CI 0.33–0.85) were longer in the PCLVO group. The likelihood of obtaining successful recanalization and favorable functional outcome at 90 days was comparable between the two groups. PCLVO was, however, associated with less sICH (OR 0.56, 95% CI 0.37–0.85) but higher mortality (OR 1.92, 95% CI 1.46–2.53).Conclusions: This meta-analysis indicates that MT in PCLVO may be comparably efficient in obtaining successful recanalization and 90 day favorable functional outcome just as in ACLVO. Less sICH in MT-treated PCLVO patients might be the result of the lower IVT rate in this group. Higher baseline NIHSS and longer onset-to-IVT and onset-to-groin puncture times may have contributed to a higher 90 day mortality in PCLVO patients

Power system dynamic state estimation: motivations, definitions, methodologies, and future work

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community

Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome

Microorganisms living inside plants can promote plant growth and health, but their genomic and functional diversity remain largely elusive. Here, metagenomics and network inference show that fungal infection of plant roots enriched for Chitinophagaceae and Flavobacteriaceae in the root endosphere and for chitinase genes and various unknown biosynthetic gene clusters encoding the production of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs). After strain-level genome reconstruction, a consortium of Chitinophaga and Flavobacterium was designed that consistently suppressed fungal root disease. Site-directed mutagenesis then revealed that a previously unidentified NRPS-PKS gene cluster from Flavobacterium was essential for disease suppression by the endophytic consortium. Our results highlight that endophytic root microbiomes harbor a wealth of as yet unknown functional traits that, in concert, can protect the plant inside out.</p