scholarly journals Efficient integration of IoT-based micro storages to improve urban drainage performance through advanced control strategies

2021 ◽  
Author(s):  
Martin Oberascher ◽  
Wolfgang Rauch ◽  
Robert Sitzenfrei
Keyword(s):  
Large Scale ◽  
Control Strategies ◽  
First Flush ◽  
Weather Forecasts ◽  
Advanced Control ◽  
Combined Sewer ◽  
Discharge Valve ◽  
Efficient Integration ◽  
Precipitation Events

Abstract The smart rain barrel (SRB) consists of a conventional rain barrel with storage volumes between 200 and 500 L, which is extended by a remotely (and centrally) controllable discharge valve. The SRB is capable to release stormwater prior precipitation events by using high-resolution weather forecasts to increase detention capacity. However, as shown in the previous work, a large-scale implementation combined with a simultaneously opening of discharge valves clearly reduce effectiveness. The aim of this work is to systematically investigate different control strategies for wet weather by evaluating their impact on sewer performance. For case study, an Alpine municipality is hypothetically retrofitted with SRBs (total additional storage volume of 181 m3). The results show that combined sewer overflow (CSO) volume and subsequently pollution mass can be reduced between 7 and 67% depending on rain characteristics (e.g., rain pattern, amount of precipitation) and applied control strategy. Effectiveness of the SRBs increases with lower CSO volume, whereas more advanced control strategies based on sewer conditions can clearly improve system's performance compared to simpler control strategies. For higher CSO volume, the SRBs can postpone start of an CSO event which is important for first-flush phenomenon.

scholarly journals Artificial Intelligence for Advanced Building Control: Energy and GHG Savings from a Case Study

Proceedings ◽  
2019 ◽  
Vol 23 (1) ◽  
pp. 7 ◽  
Author(s):  
Nunzio Cotrufo ◽  
Etienne Saloux
Keyword(s):  
Artificial Intelligence ◽  
Natural Gas ◽  
Predictive Control ◽  
Control Strategies ◽  
Weather Forecasts ◽  
Early Results ◽  
Advanced Control ◽  
Gas Consumption ◽  
Building Operation

Model-based Predictive Control (MPC) is a promising advanced control strategy for the improvement of building operation. MPC uses a model of the building along with weather forecasts to optimize control strategies, such as indoor air temperature set-points, thermal storage charging and discharging cycles, etc. An obstacle to the adoption of MPC is the modelling step: developing a dedicated control-oriented model is a time-consuming process, requiring technical expertise and a large amount of information about the building and its operation. To overcome these issues, this paper proposes a new approach for the development of MPC strategies based on Artificial Intelligence (AI) techniques, aiming to map correlations among commonly available operation variables and to develop models suitable for predictive control. The proposed approach was applied in an institutional building in Varennes, QC, with the aim of reducing the natural gas consumption during the heating season. Early results show a remarkable effectiveness of the proposed approach, with a reduction of natural gas and building heating consumption of 23.9% and 6.3%, respectively.

scholarly journals Rabies control in wildlife: the golden jackal (Canis aureus) requests for attention – a case study

2020 ◽  
Vol 24 (2) ◽  
Author(s):  
Péter Kemenszky ◽  
Ferenc Jánoska ◽  
Gábor Nagy ◽  
Ágnes Csivincsik
Keyword(s):  
Paradigm Shift ◽  
Large Scale ◽  
Control Strategies ◽  
Control Programme ◽  
Wild Boar Population ◽  
Research Groups ◽  
Multidisciplinary Research ◽  
Natural Reservoir ◽  
Rabies Control

In Hungary, the rabies control programme with oral bait immunisation of wild carnivores dates back to 1992. Since than, the rules of vaccine placement on bait density has not changed, in spite of drastic expansion of both the carnivore community and the wild boar population in Europe. Though, all these elements of the concerned ecosystem compete for the baits. This case study was based on the accidental finding of vaccine blisters in jackal stomachs during a large-scale investigation on jackals’ feeding ecology. The results showed 3.17% (0.57-10.87%) frequency of bait occurrence in jackal specimens harvested during the vaccination term. This finding contradicted previous reports on high bait uptake rate and rabies seroconversion in golden jackals. These results called the attention the need for paradigm shift in management of diseases maintained in a natural reservoir. In the authors’ opinion, for reassuring result, multidisciplinary research groups should re-evaluate disease control strategies time and again.

scholarly journals Mathematical modeling of the Mojave Solar Plants

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4197 ◽  
Author(s):  
Antonio J. Gallego ◽  
Manuel Macías ◽  
Fernando de de Castilla ◽  
Eduardo F. Camacho
Keyword(s):  
Mathematical Modeling ◽  
Large Scale ◽  
Control Strategies ◽  
Research Topics ◽  
Trade Off ◽  
Computational Burden ◽  
Main Research ◽  
Advanced Control ◽  
Overall Efficiency ◽  
Tuning Process

Competitiveness of solar energy is one of current main research topics. Overall efficiency of solar plants can be improved by using advanced control strategies. To design and tuning properly advanced control strategies, a mathematical model of the plant is needed. The model has to fulfill two important points: (1) It has to reproduce accurately the dynamics of the real system; and (2) since the model is used to test advanced control strategies, its computational burden has to be as low as possible. This trade-off is essential to optimize the tuning process of the controller and minimize the commissioning time. In this paper, the modeling of the large-scale commercial solar trough plants Mojave Beta and Mojave Alpha is presented. These two models were used to test advanced control strategies to operate the plants.

scholarly journals A case study research on interoperability improvement in Smart Grids: state-of-the-art and further opportunities

2021 ◽  
Vol 1 ◽  
pp. 33
Author(s):  
Johann Schütz ◽  
Mathias Uslar ◽  
Jürgen Meister
Keyword(s):  
Case Studies ◽  
Smart Grids ◽  
Large Scale ◽  
Critical Infrastructure ◽  
State Of The Art ◽  
Case Study Research ◽  
Efficient Integration ◽  
Cost Efficient ◽  
Theoretical Foundations

With the topic of Smart Grids taking up momentum, challenges to integrate systems from various vendors’ at large scale in a critical infrastructure have arisen. This issue is usually tackled utilizing standards and, therefore, agreements between the various parties. However, the aspect of the interoperability between systems is not only defined by physical connections, but has a multi-faceted dimension which needs to be dealt with at all layers in order for a semantic and cost-efficient integration. Within this contribution, we motivate the need for a procedural way to deal with interoperability in Smart Grids, show the theoretical foundations and the approach taken and present case studies that cover the problem in scope. Based on these case studies, results are critically reflected and conclusions are drawn.

scholarly journals Spatial and Temporal Variability in Rainfall Erosivity Under Alpine Climate: A Slovenian Case Study Using Optical Disdrometer Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Nejc Bezak ◽  
Sašo Petan ◽  
Matjaž Mikoš
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Annual Rainfall ◽  
Mean Annual Precipitation ◽  
Rainfall Erosivity ◽  
Spatial And Temporal Variability ◽  
Strongly Correlated ◽  
Erosion Rates ◽  
Precipitation Events

Rainfall erosivity is one of the most important parameters that influence soil erosion rates. It is characterized by a large spatial and temporal variability. For example, in Slovenia, which covers around 20,000 km2, the annual rainfall erosivity ranges from less than 1,000 MJ mm ha−1 h−1 to more than 10,000 MJ mm ha−1 h−1. Drop size distribution (DSD) data are needed to investigate rainfall erosivity characteristics. More than 2 years of DSD measurements using optical disdrometers located at six stations in Slovenia were used to investigate the spatial and temporal variability in rainfall erosivity in Slovenia. Experimental results have indicated that elevation is a poor predictor of rainfall erosivity and that erosivity is more strongly correlated to the mean annual precipitation. Approximately 90% of the total kinetic energy (KE) was accounted for in about 35% of 1 min disdrometer data. The highest 1 min intensities (I) and consequently also KE values were measured in summer followed by autumn and spring. The local KE-I equation yielded an acceptable fit to the measured data in case of all six stations. The relatively large percentage of 1 min rainfall intensities above 5 mm/h can at least partially explain some very high annual rainfall erosivity values (i.e., near or above 10,000 MJ mm ha−1 h−1). Convective and large-scale precipitation events also result in various rainfall erosivity characteristics. The station microlocation and wind impacts in case of some stations yielded relatively large differences between the data measured using the optical disdrometer and the pluviograph. Preliminary conclusions have been gathered, but further measurements are needed to get even better insight into spatial and temporal variability in rainfall erosivity under Alpine climate in Slovenia.

scholarly journals Modular Feedback Control of Networked Systems by Clustering: A Drinking Water Network Case Study

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 389 ◽  
Author(s):  
José María Maestre ◽  
Francisco Lopez-Rodriguez ◽  
Francisco Javier Muros ◽  
Carlos Ocampo-Martinez
Keyword(s):  
Drinking Water ◽  
Feedback Control ◽  
Large Scale ◽  
Control Strategies ◽  
System Stability ◽  
Linear Matrix ◽  
Water Network ◽  
Common Lyapunov Function ◽  
Network Topologies

This article presents a method based on linear matrix inequalities (LMIs) for designing a modular feedback control law, whose synthesis guarantees the system stability, while switching to different network topologies. Such stability is achieved by means of a common Lyapunov function to all network admissible configurations. Several mechanisms to relieve the computational burden of this methodology in large-scale systems are also presented. To assess its applicability, the modular controller is tested on a real case study, namely the Barcelona drinking water network (DWN), and its performance is compared with that of other control strategies, showing the effectiveness of the proposed approach.

scholarly journals Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 353 ◽  
Author(s):  
Unai Saralegui ◽  
Miguel Antón ◽  
Olatz Arbelaitz ◽  
Javier Muguerza
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Control Strategies ◽  
Thermal Inertia ◽  
Energy Usage ◽  
Meeting Room ◽  
Sensing System ◽  
Advanced Control ◽  
Energy Consuming

The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies.

scholarly journals Improving water management efficiency by using optimization-based control strategies: the Barcelona case study

2009 ◽  
Vol 9 (5) ◽  
pp. 565-575 ◽  
Author(s):  
C. Ocampo-Martinez ◽  
V. Puig ◽  
G. Cembrano ◽  
R. Creus ◽  
M. Minoves
Keyword(s):  
Drinking Water ◽  
Flow Control ◽  
Large Scale ◽  
Control Strategies ◽  
Management Strategies ◽  
Economic Cost ◽  
Performance Indexes ◽  
Future Demands ◽  
Control Stability

This paper describes the application of model-based predictive control (MPC) techniques to the flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC technique is used to generate flow control strategies from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, network safety volumes and flow control stability. The designed management strategies are applied to a real case study based on a representative model of the drinking water network of Barcelona (Spain).

Relationships between Large-Scale Regime Transitions and Major Cool-Season Precipitation Events in the Northeastern United States

2010 ◽  
Vol 138 (9) ◽  
pp. 3454-3473 ◽  
Author(s):  
Heather M. Archambault ◽  
Daniel Keyser ◽  
Lance F. Bosart
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
North Atlantic ◽  
Large Scale ◽  
Precipitation Event ◽  
Composite Analysis ◽  
Cool Season ◽  
Regime Transitions ◽  
Precipitation Events

Abstract This observational study investigates statistical and synoptic–dynamic relationships between regime transitions, defined as a North Atlantic Oscillation (NAO) or Pacific–North American pattern (PNA) index change from at least a 1 standard deviation anomaly to at least a 1 standard deviation anomaly of opposite sign within 7 days, and cool-season (November–April) northeastern U.S. (NE) precipitation. A statistical analysis is performed of daily cool-season NE precipitation during all NAO and PNA transitions for 1948–2003, and a composite analysis and case study of a major cool-season NE precipitation event occurring during a positive-to-negative NAO transition are conducted. Datasets used are the 0.25° NCEP Unified Precipitation Dataset, the 2.5° NCEP–NCAR reanalysis, and the 1.125° 40-yr ECMWF Re-Analysis (ERA-40). Results of the statistical analysis suggest that cool-season NE precipitation tends to be enhanced during positive-to-negative NAO and negative-to-positive PNA transitions, and suppressed during negative-to-positive NAO and positive-to-negative PNA transitions. Of the four types of regime transitions, only the positive-to-negative NAO transition is associated with substantially more frequent major cool-season NE precipitation events compared to climatology. Results of the composite analysis and case study indicate that a surface cyclone and cyclonic wave breaking associated with the major NE precipitation event can help produce a high-latitude blocking pattern over the North Atlantic characteristic of a negative NAO pattern via thermal advection, potential vorticity transport, and diabatic processes.

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