Choosing the right model for unified flexibility modeling

Using aggregated flexibility from distributed small-scale power devices is an extensively discussed approach to meet the challenges in modern and increasingly stochastic energy systems. It is crucial to be able to model and map the flexibility of the respective power devices in a unified form to increase the value of the cumulative flexibility from different small-scale power devices by aggregation. In order to identify the most suitable approach for unified flexibility modeling we present a framework to evaluate and compare the advantages and disadvantages of already existing modeling approaches in different levels of detail. As an introduction to flexibility modeling and as a basis for the evaluation process we initially provide a comprehensive overview of the broad range of flexibility models described in scientific literature. Subsequently, five selected modeling approaches allowing the generation of a unified flexibility representation for different power devices are presented in detail. By using an evaluation metric we assess the suitability of the selected approaches for unified flexibility modeling and their applicability. To allow a more detailed performance analysis, the best evaluated models are implemented and simulations with different small-scale devices are performed. The results shown in this paper highlight the heterogeneity of modeling concepts deriving from the various interpretations of flexibility in scientific literature. Due to the varying complexity of the modeling approaches, different flexibility potentials are identified, necessitating a combination of approaches to capture the entire spectrum of the flexibility of different small-scale power devices. Furthermore, it is demonstrated that a complex model does not necessarily lead to the discovery of higher flexibility potentials, and recommendations are given on how to choose an appropriate model. © 2022, The Author(s)

Accumulation and detoxication responses of the gastropod Lymnaea stagnalis to single and combined exposures to natural (cyanobacteria) and anthropogenic (the herbicide RoundUp® Flash) stressors.

Freshwater gastropods are increasingly exposed to multiple stressors in the field such as the herbicide glyphosate in Roundup formulations and cyanobacterial blooms either producing or not producing microcystins (MCs), potentially leading to interacting effects. Here, the responses of Lymnaea stagnalis to a 21-day exposure to non-MC or MC-producing (33μgL−1) Planktothrix agardhii alone or in combination with the commercial formulation RoundUp®Flash at a concentration of 1μgL−1glyphosate, followed by 14days of depuration, were studied via i) accumulation of free and bound MCs in tissues, and ii) activities of anti-oxidant (catalase CAT) and biotransformation (glutathione-S-transferase GST) enzymes. During the intoxication, the cyanobacterial exposure induced an early increase of CAT activity, independently of the MC content, probably related to the production of secondary cyanobacterial metabolites. The GST activity was induced by RoundUp®Flash alone or in combination with non MC-producing cyanobacteria, but was inhibited by MC-producing cyanobacteria with or without RoundUp®Flash. Moreover, MC accumulation in L. stagnalis was 3.2 times increased when snails were concomitantly exposed to MC-producing cyanobacteria with RoundUp®, suggesting interacting effects of MCs on biotransformation processes. The potent inhibition of detoxication systems by MCs and RoundUp®Flash was reversible during the depuration, during which CAT and GST activities were significantly higher in snails previously exposed to MC-producing cyanobacteria with or without RoundUp®Flash than in other conditions, probably related to the oxidative stress caused by accumulated MCs remaining in tissues

Integration of Intelligent Neighbourhood Grids to the German Distribution Grid: A Perspective

Renewable energy sources generated locally are becoming increasingly popular in order to achieve carbon neutrality in the near future. Some of these sources are being used in neighbourhood (local, or energy communities) grids to achieve high levels of self-sufficiency. However, the objectives of the local grid and the distribution grid to which it is connected are different and can sometimes conflict with each other. Although the distribution grid allows access to all variable resources, in certain circumstances, such as when its infrastructure is overloaded, redispatch measures need to be implemented. The complexity and uncertainties associated with current and future energy systems make this a challenging bi-level multi-criteria optimisation problem, with the distribution grid representing the upper level and the neighbourhood grid representing the lower level. Solving these problems numerically is not an easy task. However, there are new opportunities to solve these problems with less computational costs if we decompose the flexibility in the lower lever. Therefore, this paper presents a mathematical approach to optimise grid management systems by aggregating flexibility from neighbourhood grids. This mathematical approach can be implemented with centralised or decentralised algorithms to solve congestion problems in distribution grids

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Data quality of the monoclonal gammopathy of undetermined significance diagnosis in a hospital registry

OBJECTIVE: To estimate the positive predictive value (PPV) and completeness of the monoclonal gammopathy of undetermined significance (MGUS) diagnosis coding in a hospital registry within a population-based health-care setting. PATIENTS AND METHODS: Through the Danish National Patient Registry (DNPR), we identified 627 patients registered with MGUS in two Danish regions during the period January 2001–February 2011. We reviewed the medical records of all patients registered with MGUS at the Department of Hematology, Aalborg University Hospital, and a sample of patients registered at the other three hematological departments in the two regions. We estimated the PPV of the MGUS diagnosis based on this sample of 327 medical records. We also estimated the completeness of the DNPR by linking data from the DNPR and data from a previously validated MGUS cohort of 791 patients identified through the laboratory system covering North Jutland Region. RESULTS: The diagnosis of MGUS was confirmed in 231 patients and assessed as probable in an additional 38 patients, corresponding to a PPV of 82.3% (95% confidence interval [CI] 78.1%–86.4%). By contrast, 58 (17.7%) of the patients did not definitively meet the diagnostic criteria for MGUS. When we excluded patients registered with malignant monoclonal gammopathy recorded prior to or within the first year after registration of MGUS in the DNPR, the PPV increased to 88.3% (95% CI 84.5%–92.1%). The DNPR only registered a diagnosis of MGUS in 133 of the 791 MGUS patients identified through the laboratory system, corresponding to a completeness of 16.8% (95% CI 14.1%–19.6%). CONCLUSION: The PPV of the diagnosis coding for MGUS in the DNPR is high and can be further improved by simple data restriction. However, the low completeness raises concern that MGUS patients registered in the hospital system may be highly selected

Choosing the right model for unified flexibility modeling

Abstract Using aggregated flexibility from distributed small-scale power devices is an extensively discussed approach to meet the challenges in modern and increasingly stochastic energy systems. It is crucial to be able to model and map the flexibility of the respective power devices in a unified form to increase the value of the cumulative flexibility from different small-scale power devices by aggregation. In order to identify the most suitable approach for unified flexibility modeling we present a framework to evaluate and compare the advantages and disadvantages of already existing modeling approaches in different levels of detail. As an introduction to flexibility modeling and as a basis for the evaluation process we initially provide a comprehensive overview of the broad range of flexibility models described in scientific literature. Subsequently, five selected modeling approaches allowing the generation of a unified flexibility representation for different power devices are presented in detail. By using an evaluation metric we assess the suitability of the selected approaches for unified flexibility modeling and their applicability. To allow a more detailed performance analysis, the best evaluated models are implemented and simulations with different small-scale devices are performed. The results shown in this paper highlight the heterogeneity of modeling concepts deriving from the various interpretations of flexibility in scientific literature. Due to the varying complexity of the modeling approaches, different flexibility potentials are identified, necessitating a combination of approaches to capture the entire spectrum of the flexibility of different small-scale power devices. Furthermore, it is demonstrated that a complex model does not necessarily lead to the discovery of higher flexibility potentials, and recommendations are given on how to choose an appropriate model