Initialization strategies for optimization of dynamic systems

Safdarnejad, Seyed Mostafa; Hedengren, John D.; Lewis, Nicholas R.; Haseltine, Eric L.

doi:10.1016/j.compchemeng.2015.04.016

Cited by 47 publications

(29 citation statements)

References 44 publications

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“…The cost function, Equation (6), is minimized by using MATLAB's fmincon function [28], mainly with the SC SOC constraint SOC SC,min as a final point, 25%, where an SC releases 75% of its stored energy [25]. Meanwhile, initialization strategies can be used to speed up the optimization computation as described in [35]. According to the total time of one traction stage, as shown in Figure 3, here the T s is set to be 2 s. Considering that the DC-DC converter loss calculation is always a kind of approximate calculation [28] and that this study is intended to simulate the power flow between the battery and the SC, the DC-DC converters' losses are considered constant.…”

Section: The Proposed Cost Function and Constraintsmentioning

confidence: 99%

An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

et al. 2018

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A single-objective optimization energy management strategy (EMS) for an onboard hybrid energy storage system (HESS) for light rail (LR) vehicles is proposed. The HESS uses batteries and supercapacitors (SCs). The main objective of the proposed optimization is to reduce the battery and SC losses while maintaining the SC state of charge (SOC) within specific limits based on the distance between consecutive LR stations. To do this, a series of optimized SOC limits is used to prevent the SC from becoming exhausted prematurely instead of the standard SC SOC penalty term in the cost function. Meanwhile, a rule-based EMS (RB-EMS) is used to give the SCs charging priority over the batteries when the vehicle is braking. Moreover, a simplified method for the optimization is proposed to reduce the computational burden. Simulation and experimental results for the proposed EMS and a standard SC SOC penalty-based cost function optimization are provided to evaluate losses. As a result, it is shown that the proposed EMS, compared with standard SC SOC penalty-based cost function optimization, decreases losses and prevents the SOC from reach the discharging limits.

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Section: The Proposed Cost Function and Constraintsmentioning

confidence: 99%

An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

et al. 2018

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“…Even though applying this NLP approach in real applications is somewhat limited due to the modeling of the system with explicit differential and/or algebraic equations, it has been applied to industrial systems [15,83]. Safdarnejad et al [148] shows a comparison between various initialization strategies for optimization of dynamic systems using collocation on finite elements. These strategies include a warm start from a prior solution achieved by structural decomposition, a simultaneous, and a sequential approach, which were demonstrated for an industrial CO 2 removing system integrated with grid-scale power generation units including coal, gas, and wind power units, resulting in large system with 768 decision variables.…”

Section: Solution Approachmentioning

confidence: 99%

Numerical Aspects of Data Reconciliation in Industrial Applications

et al. 2017

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Abstract:Data reconciliation is a model-based technique that reduces measurement errors by making use of redundancies in process data. It is largely applied in modern process industries, being commercially available in software tools. Based on industrial applications reported in the literature, we have identified and tested different configuration settings providing a numerical assessment on the performance of several important aspects involved in the solution of nonlinear steady-state data reconciliation that are generally overlooked. The discussed items are comprised of problem formulation, regarding the presence of estimated parameters in the objective function; solution approach when applying nonlinear programming solvers; methods for estimating objective function gradients; initial guess; and optimization algorithm. The study is based on simulations of a rigorous and validated model of a real offshore oil production system. The assessment includes evaluations of solution robustness, constraint violation at convergence, and computational cost. In addition, we propose the use of a global test to detect inconsistencies in the formulation and in the solution of the problem. Results show that different settings have a great impact on the performance of reconciliation procedures, often leading to local solutions. The question of how to satisfactorily solve the data reconciliation problem is discussed so as to obtain improved estimates.

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“…Safdarnejad et. al [55] consider the use of BLT decompositions for the purpose of more efficiently generating initial guesses to (11) by solving square problems (with fixed degrees of freedom), and in particular identifying infeasibilities. They do however not consider BLT decompositions for the actual solution of (11).…”

Section: Related Workmentioning

confidence: 99%

Symbolic elimination in dynamic optimization based on block-triangular ordering

Magnusson

Åkesson

2017

Optimization Methods and Software

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We consider dynamic optimization problems for systems described by differential-algebraic equations (DAEs). Such problems are usually solved by discretizing the full DAE. We propose techniques to symbolically eliminate many of the algebraic variables in a preprocessing step before discretization. These techniques are inspired by the causalization and tearing techniques often used when solving DAE initial value problems. Since sparsity is crucial for some dynamic optimization methods, we also propose a novel approach to preserving sparsity during this procedure.The proposed methods have been implemented in the open-source JModelica.org platform. We evaluate the performance of the methods on a suite of optimal control problems solved using direct collocation. We consider both computational time and probability of solving the problem in a timely manner. We demonstrate that the proposed methods often are an order of magnitude faster than the standard way of discretizing the full DAE, and also significantly increase probability of successful convergence.

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Initialization strategies for optimization of dynamic systems

Cited by 47 publications

References 44 publications

An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

Numerical Aspects of Data Reconciliation in Industrial Applications

Symbolic elimination in dynamic optimization based on block-triangular ordering

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