Continuous Simulation Approach Research Articles

Continuous Time Simulation and System-Level Model of a MVDC Distribution Grid Including SST and MMC-Based AFE

Medium-voltage DC (MVDC) technology has gained increasing attention in recent years. Power electronics devices dominate these grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system-level control model of such a modern MVDC distribution grid. The aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/−10 kV MVDC grid case study, including a solid-state transformer (SST)- and modular multilevel converter (MMC)-based active front end (AFE). An additional aim of this paper is to supply educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

Design and hydrologic performance estimation of highway filter drains using a novel analytical probabilistic model

Sustainable drainage systems (SuDS) are nature-based methods of managing urban stormwater runoff. Although they are widely used, some SuDS, such as highway filter drains (HFDs), are understudied with respect to sizing and performance. For the first time, we developed an analytical probabilistic model (APM) that can be used to design and estimate the hydrologic performance of HFDs. Unlike the conventionally used design-storm based or continuous simulation approaches, our APM can directly calculate the runoff capture ratios of HFDs using closed-form analytical equations. Validation of the APM presented here shows that it is robust and reliable. The relative differences between the APM-estimated and continuous simulation-determined runoff capture ratios for all the simulated design cases are less than 8.5%.

Can continuous simulation be used as an alternative for flood regionalisation? A large sample example from Chile

Flood frequency analysis lies at the core of hydrology and water engineering as one of the most required estimates for water planning and design of hydraulic structures. For ungauged basins, where no information is available, various flood regionalisation techniques have varying degrees of complexity and resulting performance, depending on the study's goal, the region analysed, and the information available. This study evaluates the use of hydrological models for flood regionalisation in Chile, using 1) A large sample dataset of 101 catchments; 2) the continuous simulation approach with the GR4J model; 3) the leave-one-out strategy for performance testing; and, 4) two regionalisation methods: Nearest Neighbour (NN) and Physical Similarity (PS), together with several alternative objective functions for calibration purposes and regionalisation strategy (in all cases adopting a single criterion, single variable and determinist approach for the parameter’s selection). Our results showed that performance (both in calibration–validation and regionalisation) is highly variable (in terms of reproducing the runoff hydrograph and flood statistics), depending on the catchment’s aridity (e.g., around 66–82% of catchments with NSE above 0 in humid regions but it severely drops to 12–44% of catchments with NSE above 0 when evaluating arid catchments). We also found that flood-specific calibration strategies produce better results for floods but poorer performance in runoff hydrograph reproduction. Finally, we highlight that our regionalisation results were in close agreement with those from one of the currently recommended methods by Chilean engineering for flood regionalisation. This is particularly promising, considering that the continuous simulation approach gives access to the complete time series and not only flood statistics. We end this manuscript by discussing several sources of uncertainty, hoping that these can be accounted for in future studies.

Relationship of Rainfall and Flood Return Periods through Hydrologic and Hydraulic Modeling

In order to examine the relationship between rainfall return periods and flood return periods, the design storm approach is compared to the rainfall–runoff continuous simulation and flood frequency analysis approach. The former was based on rainfall frequency analysis and event-based hydrological simulations, while the latter was based on continuous hydrological simulations and flood frequency analysis. All hydrological simulations were undertaken employing the HEC-HMS software. For the rainfall frequency analysis, the Generalized Extreme Value (GEV) probability distribution was used. For the flood frequency analysis, both the Extreme Value Type I (Gumbel) and GEV theoretical distributions were used and compared to each other. Flood hazard (inundation depth, flow velocities and flood extent) was estimated based on hydrodynamic simulations employing the HEC-RAS software. The study area was the Pineios catchment, upstream of Larissa city, Greece. The results revealed that the assumption of equivalent return periods of rainfall and discharge is not valid for the study area. For instance, a 50-year return period flood corresponds to a rainfall return period of about 110 years. Even if flow measurements are not available, continuous simulation based on re-analysis datasets and flood frequency analysis may be alternatively used.

Comprehensive space–time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin

Abstract. Estimates for rare to very rare floods are limited by the relatively short streamflow records available. Often, pragmatic conversion factors are used to quantify such events based on extrapolated observations, or simplifying assumptions are made about extreme precipitation and resulting flood peaks. Continuous simulation (CS) is an alternative approach that better links flood estimation with physical processes and avoids assumptions about antecedent conditions. However, long-term CS has hardly been implemented to estimate rare floods (i.e. return periods considerably larger than 100 years) at multiple sites in a large river basin to date. Here we explore the feasibility and reliability of the CS approach for 19 sites in the Aare River basin in Switzerland (area: 17 700 km2) with exceedingly long simulations in a hydrometeorological model chain. The chain starts with a multi-site stochastic weather generator used to generate 30 realizations of hourly precipitation and temperature scenarios of 10 000 years each. These realizations were then run through a bucket-type hydrological model for 80 sub-catchments and finally routed downstream with a simplified representation of main river channels, major lakes and relevant floodplains in a hydrologic routing system. Comprehensive evaluation over different temporal and spatial scales showed that the main features of the meteorological and hydrological observations are well represented and that meaningful information on low-probability floods can be inferred. Although uncertainties are still considerable, the explicit consideration of important processes of flood generation and routing (snow accumulation, snowmelt, soil moisture storage, bank overflow, lake and floodplain retention) is a substantial advantage. The approach allows for comprehensively exploring possible but unobserved spatial and temporal patterns of hydrometeorological behaviour. This is of particular value in a large river basin where the complex interaction of flows from individual tributaries and lake regulations are typically not well represented in the streamflow observations. The framework is also suitable for estimating more frequent floods, as often required in engineering and hazard mapping.

Analyzing the impact of hydrological storage and connected impervious area on the performance of distributed kerbside infiltration systems in an urban catchment

The popularity of subsurface distributed storage-based kerbside stormwater infiltration systems is increasing because they can be integrated within the strict spatial constraints of existing infrastructure. Distributed systems operate based on the concept of spreading a limited amount of storage throughout the catchment area to achieve runoff management objectives. Storage can also limit the performance of urban stormwater systems. This study investigated the role of storage capacity, especially the volumetric capacity and the emptying time, in the performance of kerbside leaky well systems in a residential catchment area with a native clay soil environment. A detailed, process-based deterministic hydrological model was used to analyze hydrologic storage via a continuous simulation approach. The model was calibrated against catchment outflows measured with stormwater infiltration devices. Individual kerbside infiltration systems were also calibrated to monitor the behavior of on-site kerbside infiltration systems. By using approach of continuous simulations during designed scenarios, this study considered the prestorm storage availability in the hydrological analysis. The results demonstrated that hydrologic storage greatly influences the performance of kerbside leaky well systems during higher-intensity storms. In addition, the results show that distributing a stormwater storage volume equal to thirty-five 1-kL rainwater tanks across the catchment area as a kerbside infiltration system could notably reduce the runoff flow rates and volumes. The results further highlight that the addition of more homes within the connected area could diminish the stormwater reduction benefits achieved through the installation of a distributed kerbside infiltration system.

Continuous Simulation of Highly Urbanized Watershed to Quantify Nutrients’ Loadings

The United States has witnessed various extreme land use changes over the years. These changes led to alterations in watersheds’ characteristics, impacting their water quality and quantity. To quantify this impact in highly urbanized watersheds such as the Chicago Metropolitan Area, it is crucial to examine the characteristics and imperviousness distribution of urban land uses and available point and non-point sources. In this paper, the effect of urban runoff and nutrient loadings to water bodies in the Chicago River Watershed resulting from level (III) detailed urban land uses is investigated. A watershed scale hydrologic and water quality simulation using BASINS/HSPF model was developed for the highly urbanized watershed. Appropriate considerations were given to the effective impervious area (EIA). The results from the five-year calibrated water quality simulation were reasonably reflected with observed data in the study area and nutrient loadings of both point and non-point sources for 44 different land uses were found. The export coefficients (EC) values obtained are site-specific depending on conditions and variables at the watershed level such as physical characteristics, land use management practices, hydro-meteorological and topographical data, while using a continuous simulation approach and watershed perspective analysis. This is the first attempt to measure and model nutrients’ loadings using detailed land use types in the Chicago River Watershed. The proposed continuous calibrated and validated model can be used in the investigation and analysis of different scenarios and possible future conditions and land utilization.

Assessing the Effects of Climate Change on Compound Flooding in Coastal River Areas

AbstractFlood assessment in coastal river areas is subject to complex dependencies and interactions between flood drivers. In addition, coastal areas are especially vulnerable to climate change, and thus its effects should be considered in the evaluation of future flood hazard. In the present study, we propose a methodology for a robust evaluation of historical and future flooding in coastal river areas. It follows a continuous simulation approach in which a hydrologic‐hydraulic modeling cascade is run for several years, driven by a simultaneous series of flood drivers. The method differs from other existing methodologies in: (a) jointly considering the relevant flood drivers, both coastal and inland, together with their dependencies and interactions, to represent the simultaneous occurrence of extreme water levels correctly, and (b) obtaining local‐scale physically consistent projections of flood drivers to account for future climate change effects on compound flood hazard. The methodology is tested for a coastal river reach in NW Spain. The results show that, although mean sea level rise is usually expected to be the main driver of increased flood hazard, climate change effects on river discharge can play a very significant role in regions with compound flooding potential.

Design and implementation of silicon single-photon avalanche photodiode modeling tool for QKD systems

Single-photon detection concept is the most crucial factor that determines the performance of quantum key distribution (QKD) systems. In this paper, a simulator with time domain visualizers and configurable parameters using continuous time simulation approach is presented for modeling and investigating the performance of single-photon detectors operating in Gieger mode at the wavelength of 830 nm. The widely used C30921S silicon avalanche photodiode was modeled in terms of avalanche pulse, the effect of experiment conditions such as excess voltage, temperature and average photon number on the photon detection efficiency, dark count rate and afterpulse probability. This work shows a general repeatable modeling process for significant performance evaluation. The most remarkable result emerged from the simulated data generated and detected by commercial devices is that the modeling process provides guidance for single-photon detectors design and characterization. The validation and testing results of the single-photon avalanche detectors (SPAD) simulator showed acceptable results with the theoretical and experimental results reported in related references and the device's data sheets.

Modeling and Simulation for Performance Evaluation of Optical Quantum Channels in Quantum key Distribution Systems

In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 protocol based on polarizing encoding with consideration of the optical fiber and free-space quantum channel imperfections and losses by estimating the quantum bit error rate and final secure key. This work shows a general repeatable modeling process for significant performance evaluation. The most remarkable result that emerged from the simulated data generated and detected is that the modeling process provides guidance for optical quantum channels design and characterization for other quantum key distribution protocols.

Modeling-framework for model-based software engineering of complex Internet of things systems.

Internet of things (IoT) systems are composed of variety of units from different domains. While developing a complete IoT system, different professionals from different domains may have to work in collaboration. In this paper we provide a framework which allows using discrete and continuous time modeling and simulation approaches in combination for IoT systems. The proposed framework demonstrates on how to model Ad-hoc and general IoT systems for software engineering purpose. We demonstrate that model-based software engineering on one hand can provide a common platform to overcome communication gaps among collaborating stakeholders whereas, on the other hand can model and integrate heterogeneous components of IoT systems. While modeling heterogeneous IoT systems, one of the major challenges is to apply continuous and discrete time modeling on intrinsically varying components of the system. Another difficulty may be how to compose these heterogeneous components into one whole system. The proposed framework provides a road-map to model discrete, continuous, Ad-hoc, general systems along with composition mechanism of heterogeneous subsystems. The framework uses a combination of Agent-based modeling, Aspect-oriented modeling, contract-based modeling and services-oriented modeling concepts. We used this framework to model a scenario example of a service-oriented IoT system as proof of concept. We analyzed our framework with existing systems and discussed it in details. Our framework provides a mechanism to model different viewpoints. The framework also enhances the completeness and consistency of the IoT software models.

Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach

Abstract. Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but as yet unobserved streamflow time series with the same temporal and distributional characteristics as the observed data. However, the representation of non-stationarities and spatial dependence among sites remains a challenge in stochastic modeling. We investigate whether the use of frequency-domain instead of time-domain models allows for the joint simulation of realistic, continuous streamflow time series at daily resolution and spatial extremes at multiple sites. To do so, we propose the stochastic simulation approach called Phase Randomization Simulation using wavelets (PRSim.wave) which combines an empirical spatio-temporal model based on the wavelet transform and phase randomization with the flexible four-parameter kappa distribution. The approach consists of five steps: (1) derivation of random phases, (2) fitting of the kappa distribution, (3) wavelet transform, (4) inverse wavelet transform, and (5) transformation to kappa distribution. We apply and evaluate PRSim.wave on a large set of 671 catchments in the contiguous United States. We show that this approach allows for the generation of realistic time series at multiple sites exhibiting short- and long-range dependence, non-stationarities, and unobserved extreme events. Our evaluation results strongly suggest that the flexible, continuous simulation approach is potentially valuable for a diverse range of water management applications where the reproduction of spatial dependencies is of interest. Examples include the development of regional water management plans, the estimation of regional flood or drought risk, or the estimation of regional hydropower potential. Highlights. Stochastic simulation of continuous streamflow time series using an empirical, wavelet-based, spatio-temporal model in combination with the parametric kappa distribution. Generation of stochastic time series at multiple sites showing temporal short- and long-range dependence, non-stationarities, and spatial dependence in extreme events. Implementation of PRSim.wave in R package PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization.

A continuous simulation approach to quantify the climate condition effect on the hydrologic performance of green roofs

ABSTRACT In order to effectively estimate the hydrologic performance of green roofs, continuous simulation approaches are recently used thus allowing to include the precipitation regime features as well as the varying soil moisture conditions. Continuous simulations are implemented in the EPA Storm Water Management Model (SWMM) using as input data the climate data series recorded at three Italian sites (Bergamo, Genoa and Castelbuono) while a simple methodological approach is adopted to estimate the actual evapotranspiration. Results are examined at the event scale by means of the volume and the peak reduction rates. Results confirm the positive impact of green roof retrofitting scenario for all the investigated climate regimes. On the other hand, the specific rainfall characteristics at the event scale (mainly rainfall depth and antecedent dry weather period) affect both the retention and detention performance of green roofs.

A Comparison of Continuous and Event-Based Rainfall–Runoff (RR) Modelling Using EPA-SWMM

This study investigates the comparative performance of event-based and continuous simulation modelling of a stormwater management model (EPA-SWMM) in calculating total runoff hydrographs and direct runoff hydrographs. Myponga upstream and Scott Creek catchments in South Australia were selected as the case study catchments and model performance was assessed using a total of 36 streamflow events from the period of 2001 to 2004. Goodness-of-fit of the EPA-SWMM models developed using automatic calibration were assessed using eight goodness-of-fit measures including Nash–Sutcliff efficiency (NSE), NSE of daily high flows (ANSE), Kling–Gupta efficiency (KGE), etc. The results of this study suggest that event-based modelling of EPA-SWMM outperforms the continuous simulation approach in producing both total runoff hydrograph (TRH) and direct runoff hydrograph (DRH).

The Influence of Flow Projection Errors on Flood Hazard Estimates in Future Climate Conditions

The continuous simulation approach to assessing the impact of climate change on future flood hazards consists of a chain of consecutive actions, starting from the choice of the global climate model (GCM) driven by an assumed CO2 emission scenario, through the downscaling of climatic forcing to a catchment scale, an estimation of flow using a hydrological model, and subsequent derivation of flood hazard maps with the help of a flow routing model. The procedure has been applied to the Biala Tarnowska catchment, Southern Poland. Future climate projections of rainfall and temperature are used as inputs to the precipitation-runoff model simulating flow in part of the catchment upstream of a modeled river reach. An application of a lumped-parameter emulator instead of a distributed flow routing model, MIKE11, substantially lowers the required computation times. A comparison of maximum inundation maps derived using both the flow routing model, MIKE11, and its lump-parameter emulator shows very small differences, which supports the feasibility of the approach. The relationship derived between maximum annual inundation areas and the upstream flow of the study can be used to assess the floodplain extent response to future climate changes. The analysis shows the large influence of the one-grid-storm error in climate projections on the return period of annual maximum inundation areas and their uncertainty bounds.

A continuous simulation approach for the estimation of extreme flood inundation in coastal river reaches affected by meso- and macrotides

Considering the joint probability of occurrence of high sea levels and river discharges, as well as the interactions between these sources of flooding, is of major importance to produce realistic inundation maps in river reaches affected by the sea level. In this paper, we propose a continuous simulation method for the estimation of extreme inundation in coastal river reaches. The methodology combines the generation of synthetic long-term daily time series of river discharge and sea level, the downscaling of daily values to a time resolution of a few minutes, the computation of inundation levels with an unsteady high-resolution two-dimensional model and the use of interpolation techniques to reconstruct long-term time series of water surface from a limited number of characteristic cases. The method is especially suitable for small catchments with times of concentration of a few hours, since it considers the intradiurnal variation of river discharge and sea level. The methodology was applied to the coastal town of Betanzos (NW of Spain), located at a river confluence strongly affected by the sea level. Depending on the return period and on the control point considered, the results obtained with the proposed methodology show differences up to 50 cm when compared with the standard methodology used in this region for the elaboration of flood hazard maps in accordance with the requirements of the European Directives. These results indicate the need for adaption of the standard methodology in order to produce more realistic results and a more efficient evaluation of flood hazard mitigation measures.

Queuing systems in a feedback environment: Continuous versus discrete-event simulation

The discrete stochastic nature of typical queuing problems calls for discrete-event simulation, rather than continuous simulation that would ignore the discrete details that may be important in queuing dynamics. However, continuous simulation can perhaps be suitable for certain large queuing systems that involve feedback interactions and time delays. This study examines this question by a series of simulation experiments with queuing systems. We start with an M/M/2 system with state-dependent arrivals. Since continuous simulation represents the system states by continuous variables, when these variables (number of entities) revolve around small integer values, discrete and continuous simulation approaches exhibit significant differences in their output dynamics. However, when the system scale is increased (many servers, many entities), errors caused by continuity assumption drop significantly and the two simulation approaches yield much closer outputs. Finally, when a delay is introduced before the state of the system influences the arrival rates, the system behaviour becomes oscillatory, involving even sustained oscillations when the delay is discrete. We show that in such settings, continuous simulation can be superior to discrete simulation, since the system exhibits far-from-equilibrium dynamics driven by the endogenous system structure, rather than by discrete stochastic events. Our results have various real-life modelling implications.

Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy

Parameter estimation for rainfall-runoff models in ungauged basins is a key aspect for a wide range of applications where streamflow predictions from a hydrological model can be used. The need for more reliable estimation of flow in data scarcity conditions is, in fact, thoroughly related to the necessity of reducing uncertainty associated with parameter estimation. This study extends the application of a Bayesian procedure that, given a generic rainfall-runoff model, allows for the assessment of posterior parameter distribution, using a regional estimate of ‘hydrological signatures’ available in ungauged basins. A set of eight catchments located in southern Italy was analyzed, and regionalized, and the first three L-moments of annual streamflow maxima were considered as signatures. Specifically, the effects of conditioning posterior model parameter distribution under different sets of signatures and the role played by uncertainty in their regional estimates were investigated with specific reference to the application of rainfall-runoff models in design flood estimation. For this purpose, the continuous simulation approach was employed and compared to purely statistical methods. The obtained results confirm the potential of the proposed methodology and that the use of the available regional information enables a reduction of the uncertainty of rainfall-runoff models in applications to ungauged basins.

Have applications of continuous rainfall–runoff simulation realized the vision for process‐based flood frequency analysis?

AbstractKeith Beven was amongst the first to propose and demonstrate a combination of conceptual rainfall–runoff modelling and stochastically generated rainfall data in what is known as the ‘continuous simulation’ approach for flood frequency analysis. The motivations included the potential to establish better links with physical processes and to avoid restrictive assumptions inherent in existing methods applied in design flood studies. Subsequently, attempts have been made to establish continuous simulation as a routine method for flood frequency analysis, particularly in the UK. The approach has not been adopted universally, but numerous studies have benefitted from applications of continuous simulation methods. This paper asks whether industry has yet realized the vision of the pioneering research by Beven and others. It reviews the generic methodology and illustrates applications of the original vision for a more physically realistic approach to flood frequency analysis through a set of practical case studies, highlighting why continuous simulation was useful and appropriate in each case. The case studies illustrate how continuous simulation has helped to offer users of flood frequency analysis more confidence about model results by avoiding (or exposing) bad assumptions relating to catchment heterogeneity, inappropriateness of assumptions made in (UK) industry‐standard design event flood estimation methods, and the representation of engineered or natural dynamic controls on flood flows. By implementing the vision for physically realistic analysis of flood frequency through continuous simulation, each of these examples illustrates how more relevant and improved information was provided for flood risk decision‐making than would have been possible using standard methods. They further demonstrate that integrating engineered infrastructure into flood frequency analysis and assessment of environmental change are also significant motivations for adopting the continuous simulation approach in practice. Copyright © 2016 John Wiley & Sons, Ltd.

Process-based design flood estimation in ungauged basins by conditioning model parameters on regional hydrological signatures

The use of rainfall–runoff models constitutes an alternative to statistical approaches (such as at-site or regional flood frequency analysis) for design flood estimation and represents an answer to the increasing need for synthetic design hydrographs associated with a specific return period. Nevertheless, the lack of streamflow observations and the consequent high uncertainty associated with parameters estimation usually pose serious limitations to the use of process-based approaches in ungauged catchments, which in contrast represent the majority in practical applications. This work presents a Bayesian procedure that, for a predefined rainfall–runoff model, allows for the assessment of posterior parameters distribution, using limited and uncertain information available about the response of ungauged catchments, i.e. the regionalized first three L-moments of annual streamflow maxima. The methodology is tested for a catchment located in southern Italy and used within a Monte Carlo scheme to obtain design flood values and simulation uncertainty bands through both event-based and continuous simulation approaches. The obtained results highlight the relevant reduction in uncertainty bands associated with simulated peak discharges compared to those obtained considering a prior uniform distribution for model parameters. A direct impact of uncertainty in regional estimates of hydrological signatures on posterior parameters distribution is also evident. For the selected case study, continuous simulation, generally, better matches the estimates of the statistical flood frequency analysis.