scholarly journals Comparing methods to place adaptive local RTC actuators for spill volume reduction from multiple CSOs

2021 ◽  
Author(s):  
M. Eulogi ◽  
S. Ostojin ◽  
P. Skipworth ◽  
S. Kroll ◽  
J. D. Shucksmith ◽  
...  
Keyword(s):  
Time Series ◽  
Control Device ◽  
Volume Reduction ◽  
Rainfall Time Series ◽  
Storm Events ◽  
Real Time Control ◽  
Location Selection ◽  
Time Control ◽  
Computational Resources

Abstract The selection of flow control device (FCD) location is an essential step for designing real-time control (RTC) systems in sewer networks. In this paper, existing storage volume-based approaches for location selection are compared with hydraulic optimisation-based methods using genetic algorithm (GA). A new site pre-screening methodology is introduced, enabling the deployment of optimisation-based techniques in large systems using standard computational resources. Methods are evaluated for combined sewer overflow (CSO) volume reduction using the CENTAUR autonomous local RTC system in a case study catchment, considering overflows under both design and selected historic rainfall events as well as a continuous 3-year rainfall time series. The performance of the RTC system was sensitive to the placement methodology, with CSO volume reductions ranging between −6 and 100% for design and lower intensity storm events, and between 15 and 36% under continuous time series. The new methodology provides considerable improvement relative to storage-based design methods, with hydraulic optimisation proving essential in relatively flat systems. In the case study, deploying additional FCDs did not change the optimum locations of earlier FCDs, suggesting that FCDs can be added in stages. Thus, this new method may be useful for the design of adaptive solutions to mitigate consequences of climate change and/or urbanisation.

Pollution based real time control strategies for combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 331-336 ◽  
Author(s):  
Gabriela Weinreich ◽  
Wolfgang Schilling ◽  
Ane Birkely ◽  
Tallak Moland
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Ammonia Nitrogen ◽  
Simple Extension ◽  
Real Time Control ◽  
Time Control ◽  
Sewer Systems ◽  
Receiving Waters ◽  
Tunnel System

This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

Integrative Modeling Platform for Design and Control of an Adaptive Wind Turbine Blade

2018 ◽  
Author(s):  
Hamid Khakpour Nejadkhaki ◽  
John F. Hall ◽  
Minghui Zheng ◽  
Teng Wu
Keyword(s):  
Simulation Model ◽  
Wind Turbine ◽  
Real Time ◽  
Turbine Blade ◽  
Design Tool ◽  
Real Time Control ◽  
Time Control ◽  
Partial Load ◽  
And Control

A platform for the engineering design, performance, and control of an adaptive wind turbine blade is presented. This environment includes a simulation model, integrative design tool, and control framework. The authors are currently developing a novel blade with an adaptive twist angle distribution (TAD). The TAD influences the aerodynamic loads and thus, system dynamics. The modeling platform facilitates the use of an integrative design tool that establishes the TAD in relation to wind speed. The outcome of this design enables the transformation of the TAD during operation. Still, a robust control method is required to realize the benefits of the adaptive TAD. Moreover, simulation of the TAD is computationally expensive. It also requires a unique approach for both partial and full-load operation. A framework is currently being developed to relate the TAD to the wind turbine and its components. Understanding the relationship between the TAD and the dynamic system is crucial in the establishment of real-time control. This capability is necessary to improve wind capture and reduce system loads. In the current state of development, the platform is capable of maximizing wind capture during partial-load operation. However, the control tasks related to Region 3 and load mitigation are more complex. Our framework will require high-fidelity modeling and reduced-order models that support real-time control. The paper outlines the components of this framework that is being developed. The proposed platform will facilitate expansion and the use of these required modeling techniques. A case study of a 20 kW system is presented based upon the partial-load operation. The study demonstrates how the platform is used to design and control the blade. A low-dimensional aerodynamic model characterizes the blade performance. This interacts with the simulation model to predict the power production. The design tool establishes actuator locations and stiffness properties required for the blade shape to achieve a range of TAD configurations. A supervisory control model is implemented and used to demonstrate how the simulation model blade performs in the case study.

scholarly journals Quick and accurate Cellular Automata sewer simulator

2014 ◽  
Vol 16 (6) ◽  
pp. 1359-1374 ◽  
Author(s):  
Rebecca J. Austin ◽  
Albert S. Chen ◽  
Dragan A. Savić ◽  
Slobodan Djordjević
Keyword(s):  
Cellular Automata ◽  
Real Time ◽  
Flow Conditions ◽  
Computationally Efficient ◽  
Real Time Control ◽  
Time Control ◽  
Ca Model ◽  
Control Of Networks ◽  
Expensive Model

As urbanisation and climate change progress, the frequency of flooding will increase. Each flood event causes damage to infrastructure and the environment. It is thus important to minimise the damage caused, which can be done through planning for events, real-time control of networks and risk management. To perform these actions, many different simulations of network behaviour are required involving complex and computationally expensive model runs. This makes fast (i.e. real-time or repetitive) simulations very difficult to carry out using traditional methods, thus there is a requirement to develop computationally efficient and accurate conceptual sewer simulators. A new Cellular Automata (CA) based sewer model is presented which is both fast and accurate. The CA model is Lagrangian in nature in that it represents the flow as blocks, and movement of the blocks through the system is simulated. To determine the number of blocks which should be moved it uses either the Manning's or Hazen–Williams equation depending on the flow conditions to calculate the permitted discharge. A case study of the sewer network in Keighley, Yorkshire, is carried out showing its performance in comparison to traditional sewer simulators. The benchmarks used to verify the results are SIPSON and SWMM5.

scholarly journals Estimation of deterministic component of monthly rainfall time series : A case study for Pantnagar

MAUSAM ◽  
2021 ◽  
Vol 69 (3) ◽  
pp. 449-458
Author(s):  
MANISHA MADHAV NAVALE ◽  
P. S. KASHYAP ◽  
SACHIN KUMAR SINGH ◽  
DANIEL PRAKASH KUSHWAHA ◽  
DEEPAK KUMAR ◽  
...  
Keyword(s):  
Time Series ◽  
Monthly Rainfall ◽  
Rainfall Time Series ◽  
Deterministic Component

scholarly journals A Quadratic–Exponential Model of Variogram Based on Knowing the Maximal Variability: Application to a Rainfall Time Series

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2466
Author(s):  
Francisco Gerardo Benavides-Bravo ◽  
Roberto Soto-Villalobos ◽  
José Roberto Cantú-González ◽  
Mario A. Aguirre-López ◽  
Ángela Gabriela Benavides-Ríos
Keyword(s):  
Time Series ◽  
Exponential Model ◽  
Complete Analysis ◽  
Rainfall Time Series ◽  
Nugget Effect ◽  
Proposed Model ◽  
Experimental Variogram ◽  
Novel Model ◽  
Hurst Exponents

Variogram models are a valuable tool used to analyze the variability of a time series; such variability usually entails a spherical or exponential behavior, and so, models based on such functions are commonly used to fit and explain a time series. Variograms have a quasi-periodic structure for rainfall cases, and some extra steps are required to analyze their entire behavior. In this work, we detailed a procedure for a complete analysis of rainfall time series, from the construction of the experimental variogram to curve fitting with well-known spherical and exponential models, and finally proposed a novel model: quadratic–exponential. Our model was developed based on the analysis of 6 out of 30 rainfall stations from our case study: the Río Bravo–San Juan basin, and was constructed from the exponential model while introducing a quadratic behavior near to the origin and taking into account the fact that the maximal variability of the process is known. Considering a sample with diverse Hurst exponents, the stations were selected. The results obtained show robustness in our proposed model, reaching a good fit with and without the nugget effect for different Hurst exponents. This contrasts to previous models, which show good outcomes only without the nugget effect.

scholarly journals Optimisation of a fuzzy logic-based local real-time control system for mitigation of sewer flooding using genetic algorithms

2019 ◽  
Vol 22 (2) ◽  
pp. 281-295 ◽  
Author(s):  
S. R. Mounce ◽  
W. Shepherd ◽  
S. Ostojin ◽  
M. Abdel-Aal ◽  
A. N. A. Schellart ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Control Algorithm ◽  
Expert Knowledge ◽  
Economic Losses ◽  
Rainfall Time Series ◽  
Real Time Control ◽  
Spare Capacity ◽  
Time Control ◽  
Drainage Networks

Abstract Urban flooding damages properties, causes economic losses and can seriously threaten public health. An innovative, fuzzy logic (FL)-based, local autonomous real-time control (RTC) approach for mitigating this hazard utilising the existing spare capacity in urban drainage networks has been developed. The default parameters for the control algorithm, which uses water level-based data, were derived based on domain expert knowledge and optimised by linking the control algorithm programmatically to a hydrodynamic sewer network model. This paper describes a novel genetic algorithm (GA) optimisation of the FL membership functions (MFs) for the developed control algorithm. In order to provide the GA with strong training and test scenarios, the compiled rainfall time series based on recorded rainfall and incorporating multiple events were used in the optimisation. Both decimal and integer GA optimisations were carried out. The integer optimisation was shown to perform better on unseen events than the decimal version with considerably reduced computational run time. The optimised FL MFs result in an average 25% decrease in the flood volume compared to those selected by experts for unseen rainfall events. This distributed, autonomous control using GA optimisation offers significant benefits over traditional RTC approaches for flood risk management.

Model based real-time control of sewer system using fuzzy-logic

1997 ◽  
Vol 36 (8-9) ◽  
pp. 343-347 ◽  
Author(s):  
L. Fuchs ◽  
T. Beeneken ◽  
P. Spönemann ◽  
C. Scheffer
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Control Device ◽  
Real Time Control ◽  
Sewer System ◽  
Rule Based ◽  
The Real ◽  
Time Control ◽  
Set Up ◽  
Final System

This paper describes the use of the sewer model HYSTEM-EXTRAN in combination with a rule based control device using fuzzy-logic to simulate the real-time control of a sewer system. The rules for the control of the system were set up with the help of optimization procedures. The advantage of the procedure is proved by comparing the uncontrolled versus the controlled state in a simulated mode for an existing sewer system. The final system was installed and tested within the sewer system.

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