Real Time Control and Optimized Storage for Affordable Peak Flow Management

2017 ◽  
Vol 2017 (2) ◽  
pp. 142-147
Author(s):  
Michael Milius ◽  
Devin Lake
2021 ◽  
Author(s):  
Ruijie Liang ◽  
Mark Thyer ◽  
Holger Maier ◽  
Michael Di Matteo ◽  
Graeme Dandy

<p>Stormwater infrastructure will require investments in the order of $100s of millions per local government area to maintain current levels of urban flood protection. This investment is likely to increase in the future as a result of the impact of climate change, population growth and increased urban densification. Traditional solutions aimed at increasing the capacity of stormwater systems have been directed towards pipe upgrades. An alternative approach is the use of smart storages, which have the following advantages:</p><ul><li>Extension of the lifespan of existing stormwater systems</li> <li>Provision of water supply</li> <li>Reduction in pollution levels in receiving waters.</li> </ul><p>The development of smart technologies enables the use of real-time control for increasing the effectiveness of storages. If forecasts of the timing and magnitude of impending rainfall events are available, storage outlet controls can be optimised to release stored water prior to and during the rainfall event to enable the peak flows to be reduced. In addition, by jointly controlling the outflows from multiple, distributed storages, rather than using a single storage or controlling multiple storages independently, coincident flood peaks from different sub-catchments can be minimised, further reducing peak flows at critical locations.</p><p>In this study, the potential benefits of real-time time control for distributed storages are compared with a system that uses storages without real-time controls. The impacts were assessed using a two-storage system, which is modelled using the software package SWMM with the real-time control schemes of the storages being optimised using a genetic algorithm. The case study was conducted for two storage sizes (2 and 10 m<sup>3</sup>) under a wide range of design rainfall conditions, with storm durations ranging from short (30mins) to long (24hrs), and annual exceedance probability ranging from frequent (50%AEP), to rare (1%AEP) for three different Australian climates (sub-tropical/Mediterranean). This results in a total of 75 different combinations. Results show there is a generic relationship between percentage peak flow reduction and the ratio of storage size to storm runoff volume irrespective of location and storm characteristics. The benefits of real-time control of smart storage systems identified were:</p><ul><li>Significant peak flow reductions ranging from 85% (for a larger storage size of 80% of storm volume) to 35% (for small storages size of 15% of runoff volume).</li> <li>Importantly, real-time control of storages significantly outperforms storages without real-time control, with additional peak flow reduction of between 35% to 50%.</li> </ul><p>These results highlight the potential for using distributed storages for mitigating urban flooding, even for extreme events. The potential benefits of smart storages in more realistic cases studies (uncertain rainfall forecasts and larger scales) are also discussed.</p>


1995 ◽  
Vol 34 (05) ◽  
pp. 475-488
Author(s):  
B. Seroussi ◽  
J. F. Boisvieux ◽  
V. Morice

Abstract:The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.


2007 ◽  
Vol 73 (12) ◽  
pp. 1369-1374
Author(s):  
Hiromi SATO ◽  
Yuichiro MORIKUNI ◽  
Kiyotaka KATO

Author(s):  
Vladimir V. NEKRASOV

Developing a microcontroller-based system for controlling the flywheel motor of high-dynamics spacecraft using Russian-made parts and components made it possible to make statement of the problem of searching control function for a preset rotation rate of the flywheel rotor. This paper discusses one of the possible options for mathematical study of the stated problem, namely, application of structural analysis based on graph theory. Within the framework of the stated problem a graph was constructed for generating the new required rate, while in order to consider the stochastic case option the incidence and adjacency matrices were constructed. The stated problem was solved using a power matrix which transforms a set of contiguous matrices of the graph of admissible solution edge sequences, the real-time control function was found. Based on the results of this work, operational trials were run for the developed control function of the flywheel motor rotor rotation rate, a math model was constructed for the real-time control function, and conclusions were drawn about the feasibility of implementing the results of this study. Key words: Control function, graph, incidence matrix, adjacency matrix, power matrix, microcontroller control of the flywheel motor, highly dynamic spacecraft.


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