This paper addresses modeling and control of traffic flow networks aiming at reduced congestion. We first develop a state-space model of expressing city-level traffic flow controlled by tolling, which is in a class of...
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This paper addresses modeling and control of traffic flow networks aiming at reduced congestion. We first develop a state-space model of expressing city-level traffic flow controlled by tolling, which is in a class of positive systems depending on some designable parameters. Based on the positivity of the model, we next present a design method of optimal tolling in terms of nonlinear programming. The nonlinear programming is transformed into a linear one, which is numerically tractable, by applying the change of variable technique. Finally, the effectiveness of the presented tolling design is shown through a numerical experiment.
The use of variable-speed electric drives has gained increasing importance due to their enhanced technical performance. To address issues like current ripple, additional motor and cables losses, electromagnetic interf...
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ISBN:
(数字)9798331533946
ISBN:
(纸本)9798331533953
The use of variable-speed electric drives has gained increasing importance due to their enhanced technical performance. To address issues like current ripple, additional motor and cables losses, electromagnetic interference, overvoltage on the stator windings, and acoustic noise of PWM controlled variable-speed electric drives and achieve suitable voltage quality at the motor terminals, the use of a sine wave output filter has become a practical industrial solution. This paper presents the optimal design of a sine wave filter for a medium voltage (MV) induction motor powered by a low switching frequency multilevel inverter. The design process considers resonance and stability issues, and determines the optimal filter structure and components by minimizing the weighted sum of the objective function components. The proposed method utilizes genetic algorithms and component modeling, incorporating objective functions such as voltage total harmonic distortion (THD), current THD, and filter components cost. Constraints, including the voltage drop across the inductor and losses due to damping resistance, are also considered in the optimal filter configuration. The sine wave filter is designed with a reduced ratio of switching frequency to filter resonance frequency $\left(r_{f}\right)$, resulting in a higher resonant frequency of filter and therefore smaller inductance and capacitance, and ultimately better voltage quality for the motor across all operating frequencies. Analysis and simulations have been conducted to validate the proposed design.
Suppose we are given two metric spaces and a family of continuous transformations from one to the other. Given a probability distribution on each of these two spaces—namely the source and the target measures—the Was...
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This paper presents an efficient preference elicitation framework for uncertain matroid optimization, where precise weight information is unavailable, but insights into possible weight values are accessible. The core ...
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The small parsimony problem is a fundamental discrete optimization problem in computational biology, aiming to find the most parsimonious ancestral labeling over a fixed phylogenetic tree. Classically, the small parsi...
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This paper deals with the design of a PSO optimization procedure to tune the LQR and $H_{\infty}$ controller parameters, for the control of the active suspension represented by the quarter car model. The objective is ...
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ISBN:
(数字)9798331541811
ISBN:
(纸本)9798331541828
This paper deals with the design of a PSO optimization procedure to tune the LQR and $H_{\infty}$ controller parameters, for the control of the active suspension represented by the quarter car model. The objective is to create a “skyhook” control and therefore suppress the vertical acceleration of the sprung mass of the vehicle. To validate proposed controller simulation utilizing ISO 8608 road profile is used. The work demonstrates a significant improvement of ride comfort compared to the passive system and gives the comparison of performance of the different control approaches.
Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data discretization and classifi...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data discretization and classification are optimized separately, leading to sub-optimal performance. To tackle the issue, we propose a novel multi-objective optimization framework that incorporates the optimization of the naive Bayes classifier into the objective function of optimizing data discretization. To solve this problem, we employ an alternative optimization method to jointly optimize both data discretization and classification. Additionally, to further enhance the optimization process, we leverage a genetic algorithm to explore and exploit a larger solution space. Experimental results on 20 datasets demonstrate that our method outperforms state-of-the-art methods.
DC Optimal Power Flow (DCOPF) is a key operational tool for power system operators, and it is embedded as a subproblem in many challenging optimization problems (e.g., line switching). However, traditional CPU-based s...
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This study focuses on the synergistic use of electricity and cooling energy within data centers, integrating photovoltaic, wind power, air conditioning, electricity and cold storage. Firstly, a model for renewable ene...
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ISBN:
(数字)9798331542139
ISBN:
(纸本)9798331542146
This study focuses on the synergistic use of electricity and cooling energy within data centers, integrating photovoltaic, wind power, air conditioning, electricity and cold storage. Firstly, a model for renewable energy based electricity and cold energy supply has been established, using the economic index as the objective function, with energy and power balances serving as constraints, and incorporating actual data from Qingyang of China as boundary conditions. Secondly, the model is solved by the mixed-integer linear programming (MILP) in Gurobi to determine the minimum net present value of cost and the optimal scales of its components. Finally, a comparative analysis reveals that compared to configuring electricity or cold storage alone, the coordinated configuration of both of them can significantly improve economic performance. This proposed scheme outperforms the current schemes in Qingyang, with a cost per kilowatt-hour of electricity of 0.3529 yuan $/ \mathrm{k W h}$.
The paper proposes a high-dimensional aggregation algorithm for analyzing the objective function in multi-objective location, which is applied to solve the problem of locating new energy facilities. The algorithm cons...
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ISBN:
(数字)9798331520298
ISBN:
(纸本)9798331520304
The paper proposes a high-dimensional aggregation algorithm for analyzing the objective function in multi-objective location, which is applied to solve the problem of locating new energy facilities. The algorithm consists of three steps: Firstly, all facilities within the area are defined as decision variables and their corresponding sub-objective functions are calculated. These decision variables and sub-objective functions are then projected onto facility points in a high-dimensional space, where each dimension corresponds to a sub-objective function value. The Euclidean distance between these high-dimensional facility points reflects the differences among different facilities in the multi-objective optimization environment. Secondly, an n-DFPS (n-dimensional facility point seasonal algorithm) is designed to find the Pareto point in this high-dimensional space by minimizing the sum of Euclidean distances between that point and all other high-dimensional facility points. The facilities are weighted based on their Euclidean distances from both the high-dimensional facility point and the high-dimensional Pareto median point. Finally, all facility points are projected onto weighted facility points on a two-dimensional plane according to their latitude, longitude, and weight information; 2-PGSA (2-dimensional facility point seasonal algorithm) is used to identify Steiner points on this plane as reasonable locations for new energy facilities. To validate its effectiveness, an industrial and commercial energy storage station location case study is conducted using simulation experiments comparing it with classical location algorithms; results demonstrate superiority of our proposed algorithm.
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