The Experts below are selected from a list of 2886 Experts worldwide ranked by ideXlab platform
Ilan Aharon - One of the best experts on this subject based on the ideXlab platform.
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sizing procedure for system hybridization based on experimental source modeling for electric vehicles
Energies, 2021Co-Authors: Aaron Shmaryahu, Nissim Amar, Alexander Ivanov, Ilan AharonAbstract:Hybrid vehicles are now more common in response to increasing global warming. The hybridization of energy sources and energy storage units enables improving the sustainability, reliability, and robustness of power systems. To reach the objective of zero emissions, a proton exchange membrane hydrogen fuel-cell was utilized as an energy source. The aim of this research was to create an accurate optimal sizing procedure for determining the nominal rating of the necessary sources. We modeled the fuel cell and the battery pack using data from real experimental results to create the generic database. Then, we added data on the mission profile, system constraints, and the minimization target function. The mission profile was then analyzed by the sizing algorithm to determine optional minimum and maximum fuel cell ratings. Analyzing the optional solutions using the vehicle real time energy management system controller resulted in a set of solutions for each available rated fuel cell, and the optimal compatible battery in the revealed band successfully accomplished the route of the driving cycle within the system limitations. Finally, the Pareto Curve represented the optimal finding of the sizing procedure. Ultimately, in contrast to previous works that utilize gross manufacturer data in the sizing procedure, the main research contribution and novelty of this research is the very accurate sizing results, which draw on real experimental-based fuel-cell and battery sizing models. Moreover, the actual vehicle real time energy management system controllers were used in the sizing procedure.
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sizing procedure for system hybridization based on experimental source modeling in grid application
Energies, 2021Co-Authors: Nissim Amar, Aaron Shmaryahu, Michael Coletti, Ilan AharonAbstract:Hybridization of sources is spreading worldwide by utilizing renewable sources and storage units as standard parts of every grid. The conjunction of energy source and storage type open the door to reshaping the sustainability and robustness of the mains while improving system parameters such as efficiency and fuel consumption. The solution fits existing networks as well as new ones. The study proposes the creation of an accurate optimal sizing procedure for setting the required rating of each type of source. The first step is to model the storage and energy sources by using real experimental results for creating the generic database. Then, data on the mission profile, system constraints, and the minimization target function are inserted. The mission profile is then analyzed to determine the minimum and maximum energy source rating. Next, the real time energy management system controller is used to find the set of solutions for each available energy source and the optimal compatible storage in the revealed band to fulfil the mission task. A Pareto-Curve is then plotted to present the optimal findings of the sizing procedure. Ultimately, the main research contribution is the far more accurate sizing results. A case study shows that relying on the standard method leads to noncompliance of sizing constraints, while the proposed procedure leads to fulfilling the mission successfully. First, by utilizing experimentally based energy and a storage unit. Second, by using the same real time energy management system controller in the sizing procedure.
Miguel A Marino - One of the best experts on this subject based on the ideXlab platform.
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extraction of flexible multi objective real time reservoir operation rules
Water Resources Management, 2014Co-Authors: Mohsen Ahmadi, Omid Bozorg Haddad, Miguel A MarinoAbstract:To extract optimal reservoir operation policies, it is important to consider different objectives simultaneously. In this study, by applying a meta-heuristic, multi-objective optimization approach, real-time optimal operation rules of Karoon4 dam are extracted as two-objectives by considering performance criteria of the reservoir as objective functions. The rules are extracted by relating water release to storage volume and inflow with simple linear equations for two states of real-time operation, which are called dependent on forecast state and independent of forecast state. In the dependent on forecast state, inflow volume is considered during the current period and in the independent of forecast state, inflow volume is considered during the period before the operation. In fact, by associating water release in each period to inflow during a past period, inflow forecasting is employed. Multi-objective optimization results of conflicting objectives of reliability and vulnerability in hydropower generation of Karoon4 are exhibited as a Pareto Curve by employing the non-dominated sorting genetic algorithm II (NSGA-II). Each point on the Pareto Curve represents an optimal operation policy. Actually, based on the priority and desired criterion of the reservoir operator, for the value of any criterion, the optimal value of another criterion and its optimal operation policy can be extracted by using a Pareto Curve. Maximum reliabilities of Pareto Curves in first and second states of real-time operation are 60.83 and 60.00 %, respectively, with corresponding minimum vulnerabilities of 8.52 and 9.08 %. Although the dependence of reservoir release in each period to inflow during the previous period (i.e., independent of forecast state) improves the values of objective functions compared with the dependent on forecast state, the difference is insignificant. Since the independent of forecast state of real-time operation does not depend on inflow forecasting, the small difference is negligible and so this state seems more efficient. Also, a comparison of results of long-term operation with real-time operation shows that bcomputed real-time operation rules are flexible and accurate. Copyright Springer Science+Business Media Dordrecht 2014
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extraction of flexible multi objective real time reservoir operation rules
Water Resources Management, 2014Co-Authors: Mohsen Ahmadi, Omid Bozorg Haddad, Miguel A MarinoAbstract:To extract optimal reservoir operation policies, it is important to consider different objectives simultaneously. In this study, by applying a meta-heuristic, multi-objective optimization approach, real-time optimal operation rules of Karoon4 dam are extracted as two-objectives by considering performance criteria of the reservoir as objective functions. The rules are extracted by relating water release to storage volume and inflow with simple linear equations for two states of real-time operation, which are called dependent on forecast state and independent of forecast state. In the dependent on forecast state, inflow volume is considered during the current period and in the independent of forecast state, inflow volume is considered during the period before the operation. In fact, by associating water release in each period to inflow during a past period, inflow forecasting is employed. Multi-objective optimization results of conflicting objectives of reliability and vulnerability in hydropower generation of Karoon4 are exhibited as a Pareto Curve by employing the non-dominated sorting genetic algorithm II (NSGA-II). Each point on the Pareto Curve represents an optimal operation policy. Actually, based on the priority and desired criterion of the reservoir operator, for the value of any criterion, the optimal value of another criterion and its optimal operation policy can be extracted by using a Pareto Curve. Maximum reliabilities of Pareto Curves in first and second states of real-time operation are 60.83 and 60.00 %, respectively, with corresponding minimum vulnerabilities of 8.52 and 9.08 %. Although the dependence of reservoir release in each period to inflow during the previous period (i.e., independent of forecast state) improves the values of objective functions compared with the dependent on forecast state, the difference is insignificant. Since the independent of forecast state of real-time operation does not depend on inflow forecasting, the small difference is negligible and so this state seems more efficient. Also, a comparison of results of long-term operation with real-time operation shows that bcomputed real-time operation rules are flexible and accurate.
Weihong Zhang - One of the best experts on this subject based on the ideXlab platform.
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Shape, sizing optimization and material selection based on mixed variables and genetic algorithm
Optimization and Engineering, 2010Co-Authors: Xingang Tang, David Hicham Bassir, Weihong ZhangAbstract:In this work, we explore simultaneous designs of materials selection and structural optimization. As the material selection turns out to be a discrete process that finds the optimal distribution of materials over the design domain, it cannot be performed with common gradient-based optimization methods. In this paper, material selection is considered together with the shape and sizing optimization in a framework of multiobjective optimization of tracking the Pareto Curve. The idea of mixed variables is often introduced in the case of mono-objective optimization. However, in the case of multi-objective optimization, we still face some hard key points related to the convexity and the continuity of the Pareto domain, which underline the originality of this work. In addition to the above aspect, there is a lack in the literature concerning the industrial applications that consider the mixed parameters. Continuous variables refer to structural parameters such as thickness, diameter and spring elastic constants while material ID is defined as binary design variable for each material. Both mechanical and thermal loads are considered in this work with the aim of minimizing the maximum stress and structural weight simultaneously. The efficiency of the design procedure is demonstrated through various numerical examples
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a min max method with adaptive weightings for uniformly spaced Pareto optimum points
Computers & Structures, 2006Co-Authors: Weihong Zhang, Tong GaoAbstract:Abstract This work aims at obtaining uniformly spaced Pareto optimum points in the objective space when multicriteria optimization problems are solved. An original adaptive scheme is proposed to update automatically weighting coefficients involved in the min–max method. By means of a novel bilevel approach, it is shown that with the calculation of the tangent and normal directions of the Pareto Curve, Pareto optimum points can be obtained sequentially with a uniformly spaced distribution. Meanwhile, the distance between two adjacent Pareto optimum points is controllable depending upon the prescribed step length along the tangent direction. To validate the method, numerical bicriteria examples are solved to show its effectiveness.
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on the Pareto optimum sensitivity analysis in multicriteria optimization
International Journal for Numerical Methods in Engineering, 2003Co-Authors: Weihong ZhangAbstract:To analyse the trade-off relations among the set of criteria in multicriteria optimization, Pareto optimum sensitivity analysis is systematically studied in this paper. Original contributions cover two parts: theoretical demonstrations are firstly made to validate the gradient projection method in Pareto optimum sensitivity analysis. It is shown that the projected gradient direction evaluated at a given Pareto optimum in the design variable space rigorously corresponds to the tangent direction of the Pareto Curve/surface at that point in the objective space. This statement holds even for the change of the set of active constraints in the perturbed problem. Secondly, a new active constraint updating strategy is proposed, which permits the identification of the active constraint set change, to determine the influence of this change upon the differentiability of the Pareto Curve and finally to compute directional derivatives in non-differentiable cases. This work will highlight some basic issues in multicriteria optimization. Some numerical problems are solved to illustrate these novelties.
Jose Maria Ponceortega - One of the best experts on this subject based on the ideXlab platform.
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optimal planning of feedstock for butanol production considering economic and environmental aspects
ACS Sustainable Chemistry & Engineering, 2017Co-Authors: Juan Jose Quirozramirez, Eduardo Sanchezramirez, Salvador Hernandezcastro, Juan Gabriel Segoviahernandez, Jose Maria PonceortegaAbstract:This paper presents a multiobjective optimization to obtain the optimal planning of butanol production, considering the optimal selection of feedstock and the correct ratio of fermentable sugars. This multiobjective methodology was applied during both the fermentation and purification process of butanol. The multiobjective optimization problem considers minimizing the total annual cost and environmental impact as objective function. The economic objective function takes into account the availability of bioresources, the cost of feedstocks, the fermentation conditions, and the separation units. On the other hand, the environmental assessment includes the overall impact measured through the eco-indicator 99 which is based on a life cycle analysis methodology. Both objective functions were applied to a case study for the optimal planning to produce biobutanol in Mexico. After the optimization process, we generated a set of solutions represented by a Pareto Curve that identifies a group of optimal solutions f...
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optimal planning of a biomass conversion system considering economic and environmental aspects
Industrial & Engineering Chemistry Research, 2011Co-Authors: Jose Ezequiel Santibanezaguilar, Betzabe J Gonzalezcampos, Jose Maria Ponceortega, Medardo Sernagonzalez, Mahmoud M ElhalwagiAbstract:This paper presents a multiobjective optimization model based on a mathematical programming formulation for the optimal planning of a biorefinery, considering the optimal selection of feedstock, processing technology, and a set of products. The multiobjective optimization problem simultaneously considers the profit maximization and the environmental impact minimization. The economic objective function takes into account the availability of bioresources, processing limits, and demand of products, as well as the costs of feedstocks, products, and processing routes. On the other hand, the environmental assessment includes the overall environmental impact measured through the eco-indicator-99 based on the life cycle analysis methodology. The proposed methodology generates a Pareto Curve that identifies the set of optimal solutions for both objectives, and it is applied to a case study for planning the production of a biorefinery in Mexico.
Aaron Shmaryahu - One of the best experts on this subject based on the ideXlab platform.
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sizing procedure for system hybridization based on experimental source modeling for electric vehicles
Energies, 2021Co-Authors: Aaron Shmaryahu, Nissim Amar, Alexander Ivanov, Ilan AharonAbstract:Hybrid vehicles are now more common in response to increasing global warming. The hybridization of energy sources and energy storage units enables improving the sustainability, reliability, and robustness of power systems. To reach the objective of zero emissions, a proton exchange membrane hydrogen fuel-cell was utilized as an energy source. The aim of this research was to create an accurate optimal sizing procedure for determining the nominal rating of the necessary sources. We modeled the fuel cell and the battery pack using data from real experimental results to create the generic database. Then, we added data on the mission profile, system constraints, and the minimization target function. The mission profile was then analyzed by the sizing algorithm to determine optional minimum and maximum fuel cell ratings. Analyzing the optional solutions using the vehicle real time energy management system controller resulted in a set of solutions for each available rated fuel cell, and the optimal compatible battery in the revealed band successfully accomplished the route of the driving cycle within the system limitations. Finally, the Pareto Curve represented the optimal finding of the sizing procedure. Ultimately, in contrast to previous works that utilize gross manufacturer data in the sizing procedure, the main research contribution and novelty of this research is the very accurate sizing results, which draw on real experimental-based fuel-cell and battery sizing models. Moreover, the actual vehicle real time energy management system controllers were used in the sizing procedure.
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sizing procedure for system hybridization based on experimental source modeling in grid application
Energies, 2021Co-Authors: Nissim Amar, Aaron Shmaryahu, Michael Coletti, Ilan AharonAbstract:Hybridization of sources is spreading worldwide by utilizing renewable sources and storage units as standard parts of every grid. The conjunction of energy source and storage type open the door to reshaping the sustainability and robustness of the mains while improving system parameters such as efficiency and fuel consumption. The solution fits existing networks as well as new ones. The study proposes the creation of an accurate optimal sizing procedure for setting the required rating of each type of source. The first step is to model the storage and energy sources by using real experimental results for creating the generic database. Then, data on the mission profile, system constraints, and the minimization target function are inserted. The mission profile is then analyzed to determine the minimum and maximum energy source rating. Next, the real time energy management system controller is used to find the set of solutions for each available energy source and the optimal compatible storage in the revealed band to fulfil the mission task. A Pareto-Curve is then plotted to present the optimal findings of the sizing procedure. Ultimately, the main research contribution is the far more accurate sizing results. A case study shows that relying on the standard method leads to noncompliance of sizing constraints, while the proposed procedure leads to fulfilling the mission successfully. First, by utilizing experimentally based energy and a storage unit. Second, by using the same real time energy management system controller in the sizing procedure.