Simulation Study on the Effect of Sponge Transformation in Old Neighborhoods Based on XP Drainage Model Construction

To address the practical application of runoff reduction and control effects of sponge measures at the building plot scale, XP Drainage was applied to construct a hydrological-hydraulic model and systematically analyze the runoff reduction and control effects of three typical sponge measures, such as storage pond, recessed green space and permeable pavement, by setting up and simulating sponge modification scenarios [1]. The results show that the effect of flood peak reduction and control is recessed green area > storage pond > permeable pavement, the effect of runoff reduction and control is storage pond > recessed green area > permeable pavement, and the effect of various sponge measures on rainfall runoff reduction and delay is good for the recurrence period below 1 in 10 years, and when the rainfall recurrence period reaches 1 in 10 years and above, the proportion of runoff and flood peak reduction decreases to different degrees, and the effect of rainfall storage for high recurrence period is not The results of the study can provide important reference values for the transformation of sponge measures in Xi’an urban districts.

Measuring the impact of COVID-19 vaccination and immunity waning: a modelling study for Portugal

Vaccination strategies to control COVID-19 have been ongoing worldwide since the end of 2020. Understanding their possible effect is key to prevent future disease spread. Using a modelling approach, this study intends to measure the impact of the COVID-19 Portuguese vaccination strategy on the effective reproduction number and explore three scenarios for vaccine effectiveness waning. Namely, the no-immunity-loss, 1-year and 3-years of immunity duration scenarios. We adapted an age-structured SEIR deterministic model and used Portuguese hospitalisation data for the model calibration. Results show that, although the Portuguese vaccination plan had a substantial impact in reducing overall transmission, it might not be sufficient to control disease spread. A significant vaccination coverage of those above 5 years old, a vaccine effectiveness against disease of at least 80% and softer non-pharmaceutical interventions (NPIs), such as mask usage and social distancing, would be necessary to control disease spread in the worst scenario considered. The immunity duration scenario of 1-year displays a resurgence of COVID-19 hospitalisations by the end of 2021, the same is observed in 3-year scenario although with a lower magnitude. The no-immunity-loss scenario presents a low increase in hospitalisations. In both the 1-year and 3-year scenarios, a vaccination boost of those above 65 years old would result in a 53% and 38% peak reduction of non-ICU hospitalisations, respectively. These results suggest that NPIs should not be fully phased-out but instead be combined with a fast booster vaccination strategy to reduce healthcare burden.

A single-agent extension of the SIR model describes the impact of mobility restrictions on the COVID-19 epidemic

Mobility restrictions are successfully used to contain the diffusion of epidemics. In this work we explore their effect on the epidemic growth by investigating an extension of the Susceptible-Infected-Removed (SIR) model in which individual mobility is taken into account. In the model individual agents move on a chessboard with a Lévy walk and, within each square, epidemic spreading follows the standard SIR model. These simple rules allow to reproduce the sub-exponential growth of the epidemic evolution observed during the Covid-19 epidemic waves in several countries and which cannot be captured by the standard SIR model. We show that we can tune the slowing-down of the epidemic spreading by changing the dynamics of the agents from Lévy to Brownian and we investigate how the interplay among different containment strategies mitigate the epidemic spreading. Finally we demonstrate that we can reproduce the epidemic evolution of the first and second COVID-19 waves in Italy using only 3 parameters, i.e , the infection rate, the removing rate, and the mobility in the country. We provide an estimate of the peak reduction due to imposed mobility restrictions, i. e., the so-called flattening the curve effect. Although based on few ingredients, the model captures the kinetic of the epidemic waves, returning mobility values that are consistent with a lock-down intervention during the first wave and milder limitations, associated to a weaker peak reduction, during the second wave.

Modeling the Impact of Electric Vehicle Charging Infrastructure on Regional Energy Systems: Fields of Action for an Improved e-Mobility Integration

Since e-Mobility is on the rise worldwide, large charging infrastructure networks are required to satisfy the upcoming charging demand. Planning these networks not only involves different objectives from grid operators, drivers and Charging Station (CS) operators alike but it also underlies spatial and temporal uncertainties of the upcoming charging demand. Here, we aim at showing these uncertainties and assess different levers to enable the integration of e-Mobility. Therefore, we introduce an Agent-based model assessing regional charging demand and infrastructure networks with the interactions between charging infrastructure and electric vehicles. A global sensitivity analysis is applied to derive general guidelines for integrating e-Mobility effectively within a region by considering the grid impact, the economic viability and the Service Quality of the deployed Charging Infrastructure (SQCI). We show that an improved macro-economic framework should enable infrastructure investments across different types of locations such as public, highway and work to utilize cross-locational charging peak reduction effects. Since the height of the residential charging peak depends up to 18% on public charger availability, supporting public charging infrastructure investments especially in highly utilized power grid regions is recommended.

Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction

The goal of this paper is to optimally combine day-ahead solar and demand forecasts for the optimal battery schedule of a hybrid solar and battery farm connected to a distribution station. The objective is to achieve the maximum daily peak load reduction and charge battery with maximum solar photovoltaic energy. The innovative part of the paper lies in the treatment for the errors in solar and demand forecasts to then optimize the battery scheduler. To test the effectiveness of the proposed methodology, it was applied in the data science challenge Presumed Open Data 2021. With the historical Numerical Weather Prediction (NWP) data, solar power plant generation and distribution-level demand data provided, the proposed methodology was tested for four different seasons. The evaluation metric used is the peak reduction score (defined in the paper), and our approach has improved this KPI from 82.84 to 89.83. The solution developed achieved a final place of 5th (out of 55 teams) in the challenge.

Hydrological performance of lined permeable pavements in Norway

Lined permeable pavements (LPPs) are types of sustainable urban stormwater systems (SUDs) that are suitable for locations with low infiltration capacity or shallow groundwater levels. This study evaluated the hydrological performance of an LPP system in Norway using common detention indicators and flow duration curves (FDCs). Two hydrological models, the Storm Water Management Model (SWMM)-LID module and a reservoir model, were applied to simulate continuous outflows from the LPP system to plot the FDCs. The sensitivity of the parameters of the SWMM-LID module was assessed using the generalized likelihood uncertainty estimation methodology. The LPP system was found to detain the flow effectively based on the median values of the detention indicators (peak reduction = 89%, peak delay = 40 min, centroid delay = 45 min, T50-delay = 86 min). However, these indicators are found to be sensitive to the amount of precipitation and initial conditions. The reservoir model developed in this study was found to yield more accurate simulations (higher NSE) than the SWMM-LID module, and it can be considered a suitable design tool for LPP systems. The FDC offers an informative method to demonstrate the hydrological performance of LPP systems for stormwater engineers and decision-makers.

Impact of shared battery energy storage system on total system costs and power peak reduction in commercial buildings

The power system is experiencing an increasing share of renewable and intermittent energy production and increasing electrification. However, these changes are creating high power peaks, are straining the grid and call for expensive investments in expansions and improvements. This paper examines how the operational strategy of shared battery energy storage systems (s-BESS) can address these issues for commercial buildings with relatively high power peaks. Due to the uncertainty in long-term costs when subject to a measured peak (MP) grid tariff, the scheduling of the battery is optimised with a receding horizon control algorithm. The optimisation model is used on a Norwegian real-life case study to find the best possible configuration with an already existing battery. Although current Norwegian regulations challenge the possibility for shared metering and billing for a s-BESS configuration, the results show that the total system cost was reduced by 19.2% compared to no battery. The community peak was reduced by 17.8% compared to no battery and 6.22-17.5% compared to individual storage, which indicates that s-BESS is of value for the DSO as well.

A secular trend in age at menarche in Yunnan Province, China: a multiethnic population study of 1,275,000 women

Background Age at menarche (AAM) has shown different trends in women from different ethnic and economic regions in recent decades. Data on AAM among multiethnic women living in developing areas are scarce. Methods Data on AAM from 1,275,000 women among 26 ethnicities in Yunnan Province, China, who were born from 1965 to 2001 were obtained from the National Free Preconception Health Examination Project from 2010 to 2018. The patterns of AAM trends were analysed according to ethnic group, area of residence, and socioeconomic status. Results The mean AAM was 13.7 ± 1.21 years (95% CI 13.697–13.701), with a decrease from 14.12 (±1.41) among women born before 1970 to 13.3 (±1.04) among those born after 2000. The decline was 0.36 years per 10-year birth cohort, and the plateau has not yet been reached in Yunnan. A secular trend of earlier AAM was observed in all 26 ethnic groups. The fastest rate of decline was observed for the Bai ethnicity (0.36 years per decade). Consistent declining trends in AAM appeared among extreme-, middling-, and nonpoverty economic patterns from 1965 to 2001, with reductions of 1.19, 1.44, and 1.5 years, respectively (P < 0.001). The peak reduction among middling poverty and extreme poverty occurred in the early 2000s (0.4 and 0.32 years). Multivariate analysis showed a significant difference in the declining trends in AAM along rural/urban lines (P < 0.001). Conclusion There was a secular trend towards a younger AAM during the twentieth century and early twenty-first century birth cohorts in the Yunnan population. Considering the difference in AAM trends due to ethnic and socioeconomic status in Yunnan, the health authority should utilize flexible adjusted health care strategies in different regions.

Forecasting for Battery Storage: Choosing the Error Metric

We describe our approach to the Western Power Distribution (WPD) Presumed Open Data (POD) 6 MWh battery storage capacity forecasting competition, in which we finished second. The competition entails two distinct forecasting aims to maximise the daily evening peak reduction and using as much solar photovoltaic energy as possible. For the latter, we combine a Bayesian (MCMC) linear regression model with an average generation distribution. For the former, we introduce a new error metric that allows even a simple weighted average combined with a simple linear regression model to score very well using the competition performance metric.