An improved internal structure of a liquid-cooled heat sink has been proposed numerically and experimentally. The initial motivation is based on the results of thermal and fluid-flow topology optimization, which tends...
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An improved internal structure of a liquid-cooled heat sink has been proposed numerically and experimentally. The initial motivation is based on the results of thermal and fluid-flow topology optimization, which tends to produce a porous region despite suppression through the numerical scheme. The topology optimization was conducted using a Finite-Volume (FV) based procedure with a simplified sensitivity analysis as well as the globally convergent method of moving asymptotes (GCMMA) algorithm. The Spalart-Allmaras turbulence model was modified to handle the varying solid geometry in the topology optimization. As the result of multi-objective topology optimization showed a tendency towards the porous geometry inside the heat transfer domain, new models for the internal structure were proposed: a multi-layered porous medium with metal foam and varying-pitch cylindrical pin-fin structures. An experimental rig was developed for experimental validation of the proposed idea. The results shows that the varying-pitch cylindrical pin-fin structure inside the heat sink has advantages in heat transfer, pressure drop, and the manufacturability. Details of the numerical procedure and the experimental results are summarized in both quantitative and qualitative aspects. (C) 2021 Elsevier Ltd. All rights reserved.
A combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on ...
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A combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on increasing the network's resilience during critical periods is investigated, as well as improvements in the network's technical and economic characteristics. The three objectivefunctions in this regard are the network losses, voltage profile, and running costs, which include the costs of purchasing electrical energy from the upstream network and the devices used, as well as the cost of load shedding. In addition, the impacts of the presence of DG on power flow and the modeling of the problem's objective function are examined. To solve the problem of reconfiguration and placement of a multi-objective distribution feeder, a genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) hybrid algorithm is used. The proposed GA-SFLA algorithm is used to solve the problem with changes in its structure and its combination in three stages. Finally, the proposed method is implemented on the 33-bus distribution network. The simulation results show that the proposed method has an effective performance in improving the considered objectivefunctions and by establishing a suitable fit between the different objectivefunctions based on the three-dimensional Pareto front. Moreover, it introduced a more optimized architecture with lower loss, lower operating costs, and greater reliability compared to other optimization algorithms.
The energy price uncertainty in energy markets is the main challenge for achieving economic modeling of energy consumption and generation. This paper proposes optimal energy scheduling in a smart energy hub (SEH) unde...
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The energy price uncertainty in energy markets is the main challenge for achieving economic modeling of energy consumption and generation. This paper proposes optimal energy scheduling in a smart energy hub (SEH) under the uncertainty of electricity prices in the day-ahead. The proposed optimization approach is implemented by a two-layer interval approach for minimizing energy generation cost. In first layer optimization, demand side management (DSM) for electrical demand subject to the optimal level of electrical consumption is implemented. In second-layer optimization, the interval approach is used for modeling uncertainty. The energy generation cost is converted to bi-objectivefunctions including average and deviation costs with conflicting nature than each other. Also, the multi-performance of the hydrogen storage system based on electrical and natural gas generation is considered for managing uncertainties in second layer optimization. Since the interval optimization approach is proposed in the second layer, minimizing the average cost and deviation cost are formulated as bi-objectivefunctions by the augmented epsilon-constraint method. In the following, the LINMAP procedure is utilized to achieve maximum compatibility and the best trade-off consequence in the Pareto frontier of the multi-objective functions. Finally, the proposed optimization approach is modeled as a numerical simulation in the case studies to verify obtained results. The participation of the DSM and the hydrogen storage systems leads to minimizing the average and deviation costs by 3.03 % and 3.16 % in comparison with non-participation.
To enhance the safety and stability of lane change maneuvers for autonomous vehicles in adverse weather conditions, this paper proposes a quadratic programming-based trajectory planning algorithm for lane changing in ...
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To enhance the safety and stability of lane change maneuvers for autonomous vehicles in adverse weather conditions, this paper proposes a quadratic programming-based trajectory planning algorithm for lane changing in rainy weather. Initially, in order to mitigate the risk of potential collisions on wet and slippery road surfaces, we incorporate the concept of road adhesion coefficients and delayed reaction time to refine the establishment of the minimum safety distance. This augmentation establishes constraints on lane change safety distances and delineates the boundaries of viable lane change domains within inclement weather contexts. Subsequently, adopting a hierarchical trajectory planning framework, we incorporate visibility cost functions and safety distance constraints during dynamic programming sampling to ensure the safety of vehicle operation. Furthermore, the vehicle lane change sideslip phenomenon is considered, and the optimal lane change trajectory is obtained based on the quadratic programming algorithm by introducing the maneuverability objective function. In conclusion, to verify the effectiveness of the algorithm, lateral linear quadratic regulator (LQR) and longitudinal double proportional-integral-derivative (DPID) controllers are designed for trajectory tracking. The results demonstrate the algorithm's capability to produce continuous, stable, and collision-free trajectories. Moreover, the lateral acceleration varies within the range of +/- 1.5 m/s2, the center of mass lateral deflection angle varies within the range of +/- 0.15 degrees, and the yaw rate remains within the +/- 0.1 degrees/s range.
According to the characteristics of distribution systems, this paper proposes a real-time algorithm for solving the optimal control strategies of reactive power and voltage in distribution systems. Under the condition...
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According to the characteristics of distribution systems, this paper proposes a real-time algorithm for solving the optimal control strategies of reactive power and voltage in distribution systems. Under the conditions of bus voltage, branch reactive power used as controlled variables and the setting of the Tap Changing Under Load Transformers, reactive power compensation used as control variables, the strategies are gotten by using Linear Programming in accordance with the requirements of real-time control. There are several different objectivefunctions in the paper. That is: (1).minimum real power losses; (2) minimum reactive power compensation; (3).maximum control gain. The objectivefunctions mentioned above can be choosed in the light of specific circumstance. The paper can follow the sample date in the real-time control, simultaneously, identify the reactive power-voltage static characteristic on load bus, and consider its influence upon the optimal control strategies. The proposed technique has been tested on the IEEE 5-bus, 6-bus, modified 30-bus and Jiaxing distribution system(41-bus) in China, on the personal conputer. The optimal control strategies for different objective function mentioned above are obtained rapidly.
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