Nguyen Dang Manh, Anton Evgrafov, Jens Gravesen and Domenico Lahaye
The waste recycling industry increasingly relies on magnetic density separators. These devices generate an upward magnetic force in ferro-fluids allowing to separate the immersed…
Abstract
Purpose
The waste recycling industry increasingly relies on magnetic density separators. These devices generate an upward magnetic force in ferro-fluids allowing to separate the immersed particles according to their mass density. Recently, a new separator design has been proposed that significantly reduces the required amount of permanent magnet material. The purpose of this paper is to alleviate the undesired end-effects in this design by altering the shape of the ferromagnetic covers of the individual poles.
Design/methodology/approach
The paper represents the shape of the ferromagnetic pole covers with B-splines and defines a cost functional that measures the non-uniformity of the magnetic field in an area above the poles. The authors apply an iso-geometric shape optimization procedure, which allows us to accurately represent, analyze and optimize the geometry using only a few design variables. The design problem is regularized by imposing constraints that enforce the convexity of the pole cover shapes and is solved by a non-linear optimization procedure. The paper validates the implementation of the algorithm using a simplified variant of the design problem with a known analytical solution. The algorithm is subsequently applied to the problem posed.
Findings
The shape optimization attains its target and yields pole cover shapes that give rise to a magnetic field that is uniform over a larger domain.
Research limitations/implications
This increased magnetic field uniformity is obtained at the cost of a pole cover shape that differs per pole. This limitation has negligible impact on the manufacturing of the separator. The new pole cover shapes therefore lead to improved performance of the density separation.
Practical implications
Due to the larger uniformity the generated field, these shapes should enable larger amounts of waste to be processed than the previous design.
Originality/value
This paper treats the shapes optimization of magnetic density separators systematically and presents new shapes for the ferromagnetic poles covers.
Details
Keywords
Arnaud Baraston, Laurent Gerbaud, Vincent Reinbold, Thomas Boussey and Frédéric Wurtz
Multiphysical models are often useful for the design of electrical devices such as electrical machines. In this way, the modeling of thermal, magnetic and electrical phenomena by…
Abstract
Purpose
Multiphysical models are often useful for the design of electrical devices such as electrical machines. In this way, the modeling of thermal, magnetic and electrical phenomena by using an equivalent circuit approach is often used in sizing problems. The coupling of such models with other models is difficult to take into account, partly because it adds complexity to the process. The paper proposes an automatic modelling of thermal and magnetic aspects from an equivalent circuit approach, with its computation of gradients, using selectivity on the variables. Then, it discusses the coupling of various physical models, for the sizing by optimization algorithms. Sensibility analyses are discussed and the multiphysical approach is applied on a permanent magnet synchronous machine.
Design/methodology/approach
The paper allows one to describe thermal and magnetic models by equivalent circuits. Magnetic aspects are represented by reluctance networks and thermal aspects by thermal equivalent circuits. From circuit modelling and analytical equations, models are generated, coupled and translated into computational codes (Java, C), including the computation of their jacobians. To do so, model generators are used: CADES, Reluctool, Thermotool. The paper illustrates the modelling and automatic programming aspects with Thermotool. The generated codes are directly available for optimization algorithms. Then, the formulation of the coupling with other models is studied in the case of a multiphysical sizing by optimization of the Toyota PRIUS electrical motor.
Findings
A main specificity of the approach is the ability to easily deal with the selectivity of the inputs and outputs of the generated model according to the problem specifications, thus reducing drastically the size of the jacobian matrix and the computational complexity. Another specificity is the coupling of the models using analytical equations, possibly implicit equations.
Research limitations/implications
At the present time, the multiphysical modeling is considered only for static phenomena. However, this limit is not important for numerous sizing applications.
Originality/value
The analytical approach with the selectivity gives fast models, well-adapted for optimization. The use of model generators allows robust programming of the models and their jacobians. The automatic calculation of the gradients allows the use of determinist algorithms, such as SQP, well adapted to deal with numerous constraints.
Remy Rigo-Mariani, Vincenzo Roccuzzo, Bruno Sareni, Repetto Maurizio and Xavier Robaum
The paper presents the optimization of the power flows inside a microgrid with renewable sources and two kinds of storage. The considered microgrid consists in commercial…
Abstract
Purpose
The paper presents the optimization of the power flows inside a microgrid with renewable sources and two kinds of storage. The considered microgrid consists in commercial buildings with maximum daily peak value of 50 kW, photovoltaic arrays with total capacity of 175 kW, a 50 kW/50 kWh high speed flywheel storage and a 50 kW/50 kWh set of Li-ion accumulators.
Design/methodology/approach
The power flows in the microgrid are optimized the day ahead at one hour discretization in order to minimize the electric bill. Several scheduling strategies are proposed for solving the corresponding optimization problem including standard deterministic methods, stochastic algorithms and hybrid heuristics.
Findings
All scheduling strategies investigated in the paper are compared with regard to their accuracy and computational time.
Originality/value
Beyond the comparison of different algorithms devoted to the power flow optimization problem, our approach also addresses the integration of battery ageing in the scheduling strategy.
Ahmad Ahmadi, Yousef Alinejad Beromi and Hassan rezai soleymanpour
The voltage stability is a basic principle in the power system operation. Different short circuits, load growth, generation shortage, and other faults which disturb the voltage…
Abstract
Purpose
The voltage stability is a basic principle in the power system operation. Different short circuits, load growth, generation shortage, and other faults which disturb the voltage stability are serious threats to the system security. The voltage instability causes dispersal of a power system into sub-systems, and leads to blackout as well as heavy damages of the system equipments. Optimum load shedding during contingency situations is one of the most important issues in power system security analysis.
Design/methodology/approach
In this paper, a New Binary Particle Swarm Optimization technique (NB-PSO) is proposed for solving the integer-valued modeling of under-voltage load shedding (UVLS) problem. The updating mechanisms for the position and velocity of binary particles are amended in the proposed NB-PSO by using a new velocity definition, which has an excellent efficiency for solving complex binary optimization problems.
Findings
The effectiveness and capability of the proposed NB-PSO optimization algorithm were illustrated according to the simulation results of applying it to the IEEE 118-bus test system. In addition, the performance of the proposed NB-PSO based method was compared with other optimization algorithms, such as the Binary Particle Swarm Optimization (BPSO) and Hybrid Discrete Particle Swarm Optimization (HDPSO) techniques. It was perceived that the NB-PSO performs superior than the BPSO and HDPSO for determining the best location and the minimum level of load shedding in order to prevent voltage instability.
Originality/value
The proposed NB-PSO has novel modifications and techniques to enhance both exploration and exploitation capabilities to find the optimal feasible solution. The simulation results confirmed the effectiveness of the proposed method in determining the best location and the minimum amount of load shedding for voltage collapse prevention.
Olivier Bossi, julien pouget, Nicolas Retiere and Laurent Gerbaud
Due to the increase of the traffic, issues are appearing on DC electrified railway feeding systems. One candidate solution to solve these issues and to improve their performances…
Abstract
Purpose
Due to the increase of the traffic, issues are appearing on DC electrified railway feeding systems. One candidate solution to solve these issues and to improve their performances is to add storage systems in the railway DC electrical network. The paper presents a method based on an Optimal Power Flow (OPF) for the analysis and design of DC railway feeding systems with storage.
Design/methodology/approach
The paper describes a new methodology based on optimization to study DC electrified railways, including storage systems. A load flow model of a DC 1500V railway electrification system is presented, including the mobility of the train sets. Then, an Optimal Power Flow model of the DC network, including energy storage systems and feeding substation rectifiers has been developed. Finally, the OPF model has been tested on a real application case showing its benefits while searching solutions in order to improve the network performances.
Findings
An OPF model suitable for analysis of DC networks with storage is presented. It shows its ability to solve large scale problems.
Research limitations/implications
The paper focuses on the physical model of the network. The optimization model will have to be extended with application constraints.
Originality/value
The hypothesis presented in this paper allows to remove the discontinuities of the system in order to use a continuous optimization approach.
Le Nhat Hoang Tran, Laurent Gerbaud, Nicolas Retiere and H. Nguyen Huu
Static converters generate current harmonics in grids. Numerous studies on analytical frequency models of converters are often required to carry out their harmonic modeling in the…
Abstract
Purpose
Static converters generate current harmonics in grids. Numerous studies on analytical frequency models of converters are often required to carry out their harmonic modeling in the context of sizing by optimization. Some formulations are proposed to solve such models. Each formulation has its own advantages and drawbacks. The paper mainly focuses on two formulations: the first to be solved by Sequential Quadratic Programming (SQP) and the second to be solved by Newton-Raphson (NR). In this way, the paper presents the performances of each formulation and compares the results of both formulations for the modeling of a single-phase diode rectifier.
Design/methodology/approach
The paper aims to compare SQP formulation and NR formulation, and to propose the ways to improve their convergence. In the modeling, by using an explicit formulation of the state variables combined to a numerical method, equations are defined to reduce, as far as possible, the number of unknowns.
Findings
The difficulty is to find the good operating mode of the static converter. So, outside the equations and the constraints, the paper proposes to use the eigenvalues of the state space matrixes to initialize the duration of every configuration and to consider the operating symmetries of the static converter that allow to reduce the research area and also the variables calculated.
Research limitations/implications
The number of the conducting phase per half period is a priori, as the operating mode.
Originality/value
The modeling is based on the use of linear components, ideal switches and the static converter operates in steady-state. The main difficulties are to formulate the equations representing the non-controlled switching of semiconductors, and to solve them.
Pierre Caillard, Frederic Gillon, Sid-Ali Randi and Noelle Janiaud
The purpose of this paper is to compare two design optimization architectures for the optimal design of a complex device that integrates simultaneously the sizing of system…
Abstract
Purpose
The purpose of this paper is to compare two design optimization architectures for the optimal design of a complex device that integrates simultaneously the sizing of system components and the control strategy for increasing the energetic performances. The considered benchmark is a battery electric passenger car.
Design/methodology/approach
The optimal design of an electric vehicle powertrain is addressed within this paper, with regards to performances and range. The objectives and constraints require simulating several vehicle operating points, each of them has one degree of freedom for the electric machine control. This control is usually determined separately for each point with a sampling or an optimization loop resulting in an architecture called bi-level. In some conditions, the control variables can be transferred to the design optimization loop by suppressing the inner loop to get a mono-level formulation. The paper describes in which conditions this transformation can be done and compares the results for both architectures.
Findings
Results show a calculation time divided by more than 30 for the mono-level architecture compared to the natural bi-level on the study case. Even with the same models and optimization algorithms, the structure of the problem should be studied to improve the results, especially if computational cost is high.
Originality/value
The compared architectures bring new guidelines in the field optimal design for electric powertrains. The way to formulate a design optimization with some inner degrees of freedom can have a significant impact on computing time and on the problem understanding
Domenico Lahaye and Wouter Mulckhuyse
The purpose of this paper is to provide a framework for the implementation of an adjoint sensitivity formulation for least‐squares partial differential equations constrained…
Abstract
Purpose
The purpose of this paper is to provide a framework for the implementation of an adjoint sensitivity formulation for least‐squares partial differential equations constrained optimization problems exploiting a multiphysics finite elements package. The estimation of the diffusion coefficient in a Poisson‐type diffusion equation is used as an example.
Design/methodology/approach
The authors derive the adjoint formulation in a continuous setting allowing to attribute to the direct and adjoint states the role of different fields to be solved for. They are one‐way coupled through the mismatch between measured and direct states acting as a source term in the adjoint equation. Having solved for the direct and adjoint state, the sensitivity of the cost function with respect to the design variables can then be obtained by a suitable post‐processing procedure. This sensitivity can then be used to efficiently solve the least‐squares problem.
Findings
The authors derived the adjoint formulation in a continuous setting allowing the direct and adjoint states to be attributed the role of different fields to be solved. They are one‐way coupled through the mismatch between measured and direct states acting as a source term in the adjoint equation. It is found that, having solved for the direct and adjoint state, the sensitivity of the cost function with respect to the design variables can then be obtained by a suitable post‐processing procedure.
Research limitations/implications
This paper implies that modern multiphysics finite elements packages provide a flexible and extendable software environment for the experimentation with different adjoint formulations. Such tools are therefore expected to become increasingly important in solving notoriously difficult partial differential equation (PDE)‐constrained least‐squares problems. The framework also provides the possibility of experimentation with different regularization techniques (total variation and multiscale techniques for instance) to handle the ill‐posedness of the problem.
Originality/value
In this paper the adjoint sensitivity computation is casted as a multiphysics problem allowing for a flexible and extendable implementation.