scholarly journals Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems

2021 ◽  
Author(s):  
Khalid El Ghazouli ◽  
Jamal El Khatabi ◽  
Aziz Soulhi ◽  
Isam Shahrour
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategies ◽  
Dynamic Control ◽  
Combined Sewer Overflows ◽  
Sewer System ◽  
Sewer Systems ◽  
Proposed Model ◽  
The Impact ◽  
The City

Abstract Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally and spatially varied dynamic control strategies of sewer system actuators. This paper presents a novel MPC based on neural networks for predicting flows, a stormwater management model (SWMM) for flow conveyance, and a genetic algorithm for optimizing the operation of sewer systems and defining the best control strategies. The proposed model was tested on the sewer system of the city of Casablanca in Morocco. The results have shown the efficiency of the developed MPC to reduce CSOs while considering short optimization time thanks to parallel computing.

scholarly journals Controlling Switchable Electrochromic Glazing for Energy Savings, Visual Comfort and Thermal Comfort: A Model Predictive Control

CivilEng ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 1019-1053
Author(s):  
Abolfazl Ganji Kheybari ◽  
Tim Steiner ◽  
Steven Liu ◽  
Sabine Hoffmann
Keyword(s):  
Model Predictive Control ◽  
Thermal Comfort ◽  
Predictive Control ◽  
Energy Savings ◽  
Control Strategies ◽  
Temperate Climate ◽  
Base Case ◽  
North East ◽  
Simulation Based ◽  
The Impact

Dynamic façades play an important role in enhancing the overall performance of buildings: they respond to the environmental conditions and adjust the amount of transmitted solar radiation. This paper proposes a simulation-based framework to evaluate the energy and comfort performance of different control strategies for switchable electrochromic glazing (EC). The presented method shows the impact of a model predictive control (MPC) on energy savings and on visual and thermal comfort for different orientations compared to other strategies. Besides manual operation and conventional rule-based controls, the benchmark in this study was a simulation-based control (multi-objective penalty-based control) with optimal performance. The hourly results of various control cases were analyzed based on the established performance indicators and criteria. The cumulative annual results show the capabilities and limitations of each control strategy for an EC glazing. For a temperate climate (Mannheim, Germany), results showed that an MPC for EC glazing provides visual and thermal comfort while saving energy of up to 14%, 37%, 37%, and 34% respectively for facing north, east, south, and west relative to the base-case.

scholarly journals Nitrogen Mass Balance and Pressure Impact Model Applied to an Urban Aquifer

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1171 ◽  
Author(s):  
Mitja Janža ◽  
Joerg Prestor ◽  
Simona Pestotnik ◽  
Brigita Jamnik
Keyword(s):  
Groundwater Quality ◽  
Urban Areas ◽  
Transport Model ◽  
Nitrate Concentration ◽  
Impact Model ◽  
Sewer System ◽  
Management Measures ◽  
Pressure Impact ◽  
The Impact ◽  
The City

The assurance of drinking water supply is one of the biggest emerging global challenges, especially in urban areas. In this respect, groundwater and its management in the urban environment are gaining importance. This paper presents the modeling of nitrogen load from the leaky sewer system and from agriculture and the impact of this pressure on the groundwater quality (nitrate concentration) in the urban aquifer located beneath the City of Ljubljana. The estimated total nitrogen load in the model area of 58 km2 is 334 ton/year, 38% arising from the leaky sewer system and 62% from agriculture. This load was used as input into the groundwater solute transport model to simulate the distribution of nitrate concentration in the aquifer. The modeled nitrate concentrations at the observation locations were found to be on average slightly lower (2.7 mg/L) than observed, and in general reflected the observed contamination pattern. The ability of the presented model to relate and quantify the impact of pressures from different contamination sources on groundwater quality can be beneficially used for the planning and optimization of groundwater management measures for the improvement of groundwater quality.

Finite-Set Model-Predictive Control Strategies for a 3L-NPC Inverter Operating With Fixed Switching Frequency

2018 ◽  
Vol 65 (5) ◽  
pp. 3954-3965 ◽  
Author(s):  
Felipe Donoso ◽  
Andres Mora ◽  
Roberto Cardenas ◽  
Alejandro Angulo ◽  
Doris Saez ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategies ◽  
Switching Frequency ◽  
Finite Set

scholarly journals A Novel Fuzzy Model Predictive Control of a Gas Turbine in the Combined Cycle Unit

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Guolian Hou ◽  
Linjuan Gong ◽  
Xiaoyan Dai ◽  
Mengyi Wang ◽  
Congzhi Huang
Keyword(s):  
Model Predictive Control ◽  
Gas Turbine ◽  
Predictive Control ◽  
Control Strategies ◽  
Control Process ◽  
Fuzzy Model ◽  
Weight Coefficient ◽  
Combined Cycle ◽  
Generation Process ◽  
Selection Mechanism

The complex characteristics of the gas turbine in a combined cycle unit have brought great difficulties in its control process. Meanwhile, the increasing emphasis on the efficiency, safety, and cleanliness of the power generation process also makes it significantly important to put forward advanced control strategies to satisfy the desired control demands of the gas turbine system. Therefore, aiming at higher control performance of the gas turbine in the gas-steam combined cycle process, a novel fuzzy model predictive control (FMPC) strategy based on the fuzzy selection mechanism and simultaneous heat transfer search (SHTS) algorithm is presented in this paper. The objective function of rolling optimization in this novel FMPC consists of two parts which represent the state optimization and output optimization. In the weight coefficient selection of those two parts, the fuzzy selection mechanism is introduced to overcome the uncertainties existing in the system. Furthermore, on account of the rapidity of the control process, the SHTS algorithm is used to solve the optimization problem rather than the traditional quadratic programming method. The validity of the proposed method is confirmed through simulation experiments of the gas turbine in a combined power plant. The simulation results demonstrate the remarkable superiorities of the adopted algorithm with higher control precision and stronger disturbance rejection ability as well as less optimization time.

ON MODEL PREDICTIVE CONTROL OF QUASI-RESONANT CONVERTERS

2009 ◽  
Vol 18 (07) ◽  
pp. 1167-1183 ◽  
Author(s):  
FARZAD TAHAMI ◽  
MEHDI EBAD
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Models ◽  
Control Strategies ◽  
Sampling Interval ◽  
Control Synthesis ◽  
Resonant Converters ◽  
Control Input ◽  
Model Approximation ◽  
Dynamic Matrix

In this paper, different model predictive control synthesis frameworks are examined for DC–DC quasi-resonant converters in order to achieve stability and desired performance. The performances of model predictive control strategies which make use of different forms of linearized models are compared. These linear models are ranging from a simple fixed model, linearized about a reference steady state to a weighted sum of different local models called multi model predictive control. A more complicated choice is represented by the extended dynamic matrix control in which the control input is determined based on the local linear model approximation of the system that is updated during each sampling interval, by making use of a nonlinear model. In this paper, by using and comparing these methods, a new control scheme for quasi-resonant converters is described. The proposed control strategy is applied to a typical half-wave zero-current switching QRC. Simulation results show an excellent transient response and a good tracking for a wide operating range and uncertainties in modeling.

scholarly journals Plant and Controller Optimization for Power and Energy Systems With Model Predictive Control

2021 ◽  
Vol 143 (8) ◽  
Author(s):  
Donald J. Docimo ◽  
Ziliang Kang ◽  
Kai A. James ◽  
Andrew G. Alleyne
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Performance Metrics ◽  
Control Strategies ◽  
Transportation Systems ◽  
Thermal Dynamics ◽  
Plant Optimization ◽  
Power And Energy Systems ◽  
And Control

Abstract This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal dynamics within new components creates integration challenges, increasing component degradation, and reducing performance. Diminishing these issues requires novel plant designs and control strategies. The electrified mobility literature provides prior studies on plant and controller optimization, known as control co-design (CCD). A void within these studies is the lack of model predictive control (MPC), recognized to manage multi-domain dynamics for electrified systems, within CCD frameworks. This article addresses this through three contributions. First, a thermo-electromechanical hybrid electric vehicle (HEV) powertrain model is developed that is suitable for both plant optimization and MPC. Second, simultaneous plant and controller optimization is performed for this multi-domain system. Third, MPC is integrated within a CCD framework using the candidate HEV powertrain model. Results indicate that optimizing both the plant and MPC parameters simultaneously can reduce physical component sizes by over 60% and key performance metric errors by over 50%.

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