Integrated Load-Split Scheme for Hybrid Ship Propulsion Considering Transient Propeller Load and Environmental Disturbance

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Nikolaos Planakis ◽  
George Papalambrou ◽  
Nikolaos Kyrtatos
Keyword(s):  
Diesel Engine ◽  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Engine Performance ◽  
Hybrid Plant ◽  
Environmental Disturbance ◽  
Time Operation ◽  
Marine Propulsion ◽  
Real Time Operation

Abstract This work addresses the design and experimental implementation in real-time of an integrated predictive load-split management system for the transient and fluctuating propeller load sharing. Control-oriented modeling of the power system was performed based on experimental data gathered from the hybrid plant and on first principles for the diesel engine behavior and battery charging. Propulsion plant and environmental disturbance models are developed to simulate realistic marine load application. A nonlinear model predictive control (NMPC) scheme is proposed for the optimal transient power-split problem of a hybrid diesel-electric marine propulsion plant. The NMPC scheme directly controls the torque output of the diesel engine and the electric motor/generator ensuring that certain constraints concerning the system overloading are met, avoiding fast accelerations and load fluctuations of the diesel engine that affect engine performance. To achieve offset-free model predictive control (MPC) control, an observer is developed to provide the propeller law parameter to the NMPC for load estimation. The control system was experimentally tested in real-time operation. Results showed that controller rejected load disturbances and maintained the desired rotational speed of the powertrain as well as the desirable state of charge (SOC) in battery within the power plant limits, achieving smooth power transitions and mitigation of power fluctuations of the diesel engine.

Transient and disturbed propeller load compensation in hybrid propulsion using propeller estimator and predictive control

2021 ◽  
pp. 147509022110298
Author(s):  
George Papalambrou ◽  
Nikolaos Planakis ◽  
Nikolaos Kyrtatos
Keyword(s):  
Diesel Engine ◽  
Engine Performance ◽  
Hybrid Plant ◽  
Hybrid Propulsion ◽  
Load Compensation ◽  
Time Operation ◽  
Marine Propulsion ◽  
Power Split ◽  
Real Time Operation ◽  
Predictive Controller

We address the design of a predictive power-split management system for the transient and fluctuating propeller load sharing. Modeling of the power system was carried out based on experimental data gathered from the hybrid plant and on first principles for the diesel engine behavior and battery charging. Propulsion plant and wave disturbance models are employed to simulate realistic marine load application that affects the powerplant operation. A propeller observer is developed to provide the propeller law parameter to the controller, in order to perform load estimation and prediction based on shaft speed elevation. A Nonlinear Model Predictive Controller (NMPC) is designed for the optimal transient power-split problem of a hybrid diesel-electric marine propulsion plant. The NMPC scheme directly controls the torque output of the diesel engine and the electric motor generator ensuring that certain constraints concerning the system overloading are met, avoiding fast accelerations, and load fluctuations of the diesel engine that affect engine performance. The control system was experimentally tested in real-time operation in a physical testbed. Results showed that controller rejected successfully load disturbances and maintained the desired rotational speed of the powertrain as well as the desirable state of charge in battery within the power plant limits, achieving smooth power transitions and compensation of power fluctuations of the diesel engine.

scholarly journals Multi-Objective Model Predictive Control for Real-Time Operation of a Multi-Reservoir System

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1898 ◽  
Author(s):  
Nay Myo Lin ◽  
Xin Tian ◽  
Martine Rutten ◽  
Edo Abraham ◽  
José M. Maestre ◽  
...  
Keyword(s):  
Decision Making ◽  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Nsga Ii ◽  
Multi Objective ◽  
Reservoir System ◽  
Time Operation ◽  
Real Time Operation ◽  
Objective Model

This paper presents an extended Model Predictive Control scheme called Multi-objective Model Predictive Control (MOMPC) for real-time operation of a multi-reservoir system. The MOMPC approach incorporates the non-dominated sorting genetic algorithm II (NSGA-II), multi-criteria decision making (MCDM) and the receding horizon principle to solve a multi-objective reservoir operation problem in real time. In this study, a water system is simulated using the De Saint Venant equations and the structure flow equations. For solving multi-objective optimization, NSGA-II is used to find the Pareto-optimal solutions for the conflicting objectives and a control decision is made based on multiple criteria. Application is made to an existing reservoir system in the Sittaung river basin in Myanmar, where the optimal operation is required to compromise the three operational objectives. The control objectives are to minimize the storage deviations in the reservoirs, to minimize flood risks at a downstream vulnerable place and to maximize hydropower generation. After finding a set of candidate solutions, a couple of decision rules are used to access the overall performance of the system. In addition, the effect of the different decision-making methods is discussed. The results show that the MOMPC approach is applicable to support the decision-makers in real-time operation of a multi-reservoir system.

scholarly journals Robust Model Predictive Control for Energy Management of Isolated Microgrids Based on Interval Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Huihui He ◽  
Shengjun Huang ◽  
Yajie Liu ◽  
Tao Zhang
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Prediction Error ◽  
Optimal Operation ◽  
Robust Model Predictive Control ◽  
Interval Prediction ◽  
Robust Model ◽  
Time Operation ◽  
Prediction Approach

With the integration of Renewable Energy Resources (RERs), the Day-Ahead (DA) scheduling for the optimal operation of the integrated Isolated Microgrids (IMGs) may not be economically optimal in real time due to the prediction errors of multiple uncertainty sources. To compensate for prediction error, this paper proposes a Robust Model Predictive Control (RMPC) based on an interval prediction approach to optimize the real-time operation of the IMGs, which diminishes the influence from prediction error. The rolling optimization model in RMPC is formulated into the robust model to schedule operation with the consideration of the price of robustness. In addition, an Online Learning (OL) method for interval prediction is utilized in RMPC to predict the future information of the uncertainties of RERs and load, thereby limiting the uncertainty. A case study demonstrates the effectiveness of the proposed with the better matching between demand and supply compared with the traditional Model Predictive Control (MPC) method and Hard Charging (HC) method.

scholarly journals Optimal control of marine propulsion diesel engine during transient loading operation

2008 ◽  
Author(s):  
Γιώργος Παπαλάμπρου
Keyword(s):  
Optimal Control ◽  
Diesel Engine ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Transient Loading ◽  
Marine Propulsion

Η μείωση των εκπομπών καπνού και η βελτίωση απόκρισης φορτίου σε ένα ναυτικό υπερτροφοδοτούμενο κινητήρα Diesel, σε μεταβατική λειτουργία που περιλαμβάνει απότομες αυξήσεις στο φορτίο, αποτέλεσαν το αντικείμενο αυτής της εργασίας. Χρησιμοποιήθηκε σύστημα ελέγχου με μοντέλο πρόβλεψης (Model Predictive Control-MPC), σε ένα σύστημα εξωτερικής παροχής παροχής πεπιεσμένου αέρα απευθείας στο δοχείο αέρα. Ταυτόχρονα, στόχος ήταν η αποφυγή πάλμωσης του συμπιεστή του υπερπληρωτή, ανάντι του δοχείου αέρα.

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