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1st IEEE Tencon Spring Conference for Region 10

作者： Sulaiman, Shahril Irwan Muhammad, Khairul Safuan Musirin, Ismail Shaari, Sulaiman Univ Teknol MARA Fac Elect Engn Shah Alam 40450 Selangor Malaysia Univ Teknol MARA Fac Sci Appl Shah Alam 40450 Selangor Malaysia

ISBN: (纸本)9781467363495

The unpredictable weather conditions has motivated the need of predicting the output of photovoltaic (PV) system. This paper presents a Grid-Connected Photovoltaic (GCPV) system output prediction scheme using hybridization of evolutionary programming (EP) and Artificial Neural Network (ANN). In this study, the AC kWh output of a GCPV system was predicted using ANN based on solar irradiance (SI) and PV module temperature (MT) as the inputs. In addition, a Meta-EP was hybridized with a Multi-Layer Feedforward Neural network (MLFNN) to search for the optimal number of neurons in hidden layer, the learning rate, the momentum rate, the type of activation function and the learning algorithm during ANN training such that the root mean square (RMSE) of the prediction could be minimized. Besides Meta-EP, other variations of EP were also tested for the hybridization with MLFNN such that the proposed Meta- EP could be justified. The results showed that Meta- EP based hybrid MLFNN (HMLFNN) had produced the lowest average RMSE, the lowest standard deviation (STD) and the lowest computation time during training when compared to other EP-based HMLFNNs. Similarly, during testing, the Meta- EP based HMLFNN had also outperformed the others in producing the lowest RMSE. In the comparisons, the coefficient of determination was found to be relatively very close to unity such that a high prediction performance could be ensured.

关键词： grid-connected photovoltaic prediction artificial neural network evolutionary programming root mean square error

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On Rotor Aeroacoustic Optimization for Urban Air Mobility 28

On Rotor Aeroacoustic Optimization for Urban Air Mobility

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28th AIAA/CEAS Aeroacoustics Conference

作者： Pinto, Olivia L. Bossotto, Gabriele Afonso, Frederico Lau, Fernando P. Univ Lisbon Inst Super Tecn P-1049001 Lisbon Portugal Politecn Torino I-10129 Turin Italy Univ Lisbon Inst Super Tecn IDMEC P-1049001 Lisbon Portugal Deloitte New York NY USA Brembo SpA Curno Italy

ISBN: (数字)9781624106644

ISBN: (纸本)9781624106644

This article presents an optimization study of the noise produced by rotors in the context of Urban Air Mobility (UAM). The importance of this study is based on the expected growth of UAM in larger cities across the globe and on the consequent effort to decrease the noise emitted by this type of aircraft. Provided that rotors constitute a major part of the noise produced by this aviation segment, given the fact that the aircraft are intended to be fully electric, the design of these components is of paramount importance for noise minimization. Herein, the focus is on small rotors given the availability of experimental data to compare the numerical results. For the simulation accomplished within the optimization process, an open-source aerodynamic and aeroacoustic code (FLOWUnsteady, or FLight, Optimization, and Wind Unsteady) was integrated within an optimization module created specifically for the current work. These tools are based on the Formulation 1A of Farassat (PSU-WOPWOP) and the Brooks-Pope-Marcolini airfoil noise model (FLOWNoise), being utilized for the prediction of the tonal and atonal noise, respectively. The simulation code is applied to predict rotor noise which is posteriorly reduced by the means of a gradient-free optimization algorithm, leading to the proposed optimal rotor design, with a reduction of 16,21% of the Energy Averaged Overall Sound Pressure Level (EAOSPL) having been achieved.

关键词： Urban Air Mobility Overall Sound Pressure Level Cambered Airfoil Gradient Free Optimization Aviation Strouhal Number Aerodynamic Coefficients Turbulent Boundary Layer Blade Element Momentum Theory evolutionary programming

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Optimal construction of montages from mathematical functions on a spectrum of order-disorder preference

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JOURNAL OF MATHEMATICS AND THE ARTS 2022年第4期16卷 347-373页

作者： Smith-Miles, Kate Munoz, Mario Andres Univ Melbourne Sch Math & Stat Parkville Vic 3010 Australia

We previously generated diverse mathematical functions that are difficult for optimization algorithms. Represented as 2D contour plots, each image depicts a 'blue river' running through an intricate landscape. This paper describes the challenge of constructing an aesthetic montage of these images. A survey revealed a spectrum of tastes, divergent in preference from order to disorder, considering the structure created by connecting these 'blue rivers'. A new artwork, Negentropy Triptych, was created to depict this spectrum by manually swapping images from a random arrangement, guided by human eye to enhance or destroy the structure. An optimization algorithm automates the process, with the results of its efforts to emulate the artistic vision presented and discussed. The challenges faced by the algorithm, despite exploring several objective functions, highlight the difficulties of capturing the goals that a human decision-maker can easily achieve. Therefore, machine learning of these goals is a promising future direction. [GRAPHICS]

关键词： evolutionary programming optimization problems exploratory landscape analysis genetic algorithms evolved mathematical functions aesthetics mosaic arrangement global structure

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Image denoising and enhancement with evolutionary programming in wavelet domain

Image denoising and enhancement with evolutionary programmin...

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6th International Symposium on Computational Intelligence and Design (ISCID)

作者： Fang, Liu Deng, ZhiRen Beijing Univ Technol Sch Elect Informat & Control Engn Beijing Peoples R China

ISBN: (纸本)9780769550794

Unmanned Aerial Vehicles (UAV) digital images are often badly degraded by noise during dynamic acquisition and transmission process. Denoising is very important and difficult for UAV-vision Guided, because natural scene image is complicated and having lots of the edges and texture details. The image denoising and enhancement algorithm based on adaptive dual-tree discrete wavelet packets(ADDWP) which combine the dual-tree discrete wavelet packets and evolutionary programming is proposed in this paper. In order to reduce the noise and enhance detail for a UAV image by the EP(evolutionary programming) in wavelet domain(.) Firstly, The de-noising threshold is estimated by EP in the wavelet domain. Secondly, Noise is reduced in the fine high-frequency sub-bands of each decomposition level, respectively, so that the maximum signal-noise ratio can be obtained in the high-frequency subbands, respectively. Thirdly, The enhancement parameters is estimated by EP in the wavelet domain, and the detail is adaptive enhanced by an improved non-linear gain operator in the coarse high-frequency subbands of each decomposition level, respectively. The experiment result improves our algorithm is efficient.

关键词： dual-tree discrete wavelet packets image denoising image enhancing evolutionary programming

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Self-Adaptive Mutation Strategy for evolutionary programming Based on Fitness Tracking Scheme

Self-Adaptive Mutation Strategy for Evolutionary Programming...

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IEEE Congress on evolutionary Computation

作者： Anik, Md. Tanvir Alam Ahmed, Saif Islam, K. M. Rakibul Bangladesh Univ Engn & Technol Dept Comp Sci & Engn CSE Dhaka 1000 Bangladesh

ISBN: (纸本)9781479904549;9781479904532

In order to achieve a satisfactory optimization performance by evolutionary programming (EP), it is necessary to ensure proper balance between global exploration and local exploitation. It is obvious that one single mutation operator is not the answer. Moreover, early loss of genetic diversity causes premature trapping around locally optimal points of the fitness landscape. This paper presents a fitness tracking based evolutionary programming (FTEP) algorithm incorporating a fitness tracking scheme to find the locally trapped individuals and treat them in a different way so that they are able to improve their performance. In comparison with other EP based algorithms, FTEP incorporates several mutation operators in one algorithm and employs a self-adaptive strategy to gradually self-adapt the mutation operators in order to apply an appropriate mutation operator on the individual based on its need. A test-suite of 25 benchmark functions has been used to evaluate the performance and results have been compared with some recent evolutionary systems. The experimental results show that FTEP often performs better than most other algorithms on most of the problems.

关键词： evolutionary programming mutation stagnant population fitness tracking

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Solving Economic and Emission Dispatch Problem Using Search And Rescue Optimization Technique 13

Solving Economic and Emission Dispatch Problem Using Search ...

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13th Control and System Graduate Research Colloquium

作者： Feng, Lim Yuan Kamari, Nor Azwan Mohamed Ibrahim, Ahmad Asrul Abd Halim, Syahirah Zulkifley, Mohd Asyraf Ahmad, Halimah Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Elect Elect & Syst Engn Bangi Selangor Malaysia Univ Kuala Lumpur Malaysia France Inst UniKL MFI Japanese Collaborat Program Bangi Selangor Malaysia

ISBN: (数字)9781665468060

ISBN: (纸本)9781665468060

Combined economic and emission dispatch (CEED) in power system is aimed to solve the economics scheduling of generators in order to produce both minimum fuel costs and emission levels, at the same time meets the load demands and its operating constraints. In this paper, Search and Rescue (SAR) optimization technique has been proposed to solve the CEED problem, at which the results obtained are compared with Flower Pollination Algorithm and evolutionary programming methods. The comparisons performed can evaluate both the effectiveness and convergence rate among the studied algorithms, with multiple constraints and different cost curve nature. In general, the CEED problem is considered as biobjective problem initially and it has been transformed into single objective function by using the price penalty factor in its solution. All techniques have been implemented on IEEE 3-Generator 9-Bus system, having a valve point effect with transmission loss. Moreover, MATLAB is used to run the simulations for the test system with three different load demands on each system respectively. Results show that SAR records lowest power loss (0.37-1.62% of power demand), as compared with FPA (0.75-2.36%) and EP (1.00-3.28%). SAR method also show better performance in solving CEED problem with minimum total fuel cost, total emissions and overall CEED cost.

关键词： combined economic and emission dispatch search and rescue algorithm flower pollination algorithm evolutionary programming

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A Mixed Mutation Approach for evolutionary programming Based on Guided Selection Strategy

A Mixed Mutation Approach for Evolutionary Programming Based...

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International Conference on Informatics, Electronics and Vision (ICIEV)

作者： Anik, Md. Tanvir Alam Ahmed, Saif Bangladesh Univ Engn & Technol Dept Comp Sci & Engn Dhaka 1000 Bangladesh

ISBN: (纸本)9781479904006;9781479903979

A proper balance between exploration and exploitation is essential to maintain adequate genetic diversity within the evolving population of an evolutionary algorithm (EA). Early loss of genetic diversity causes premature trapping around the locally optimal points of the fitness landscape. evolutionary programming (EP), one of the major branches of EA, obtains exploration and exploitation abilities by mutation operators. As one single mutation operator is not sufficient, mixing several explorative and exploitative mutation operators can improve the performance of EP. This paper presents a mixed mutation scheme for EP based on a guided selection strategy. This strategy guides the participation of mutation operators throughout the evolutionary process. The proposed algorithm has been examined on a test-suite of 20 benchmark functions. Experimental results show that combining different mutation operators along with the guided selection strategy significantly enhance the performance of EP.

关键词： evolutionary programming mutation pool guided selection exploration exploitation

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Operating Generator Selection Applied for Reactive Power Dispatched using evolutionary programming Technique

Operating Generator Selection Applied for Reactive Power Dis...

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IEEE 7th International Power Engineering and Optimization Conference (PEOCO)

作者： Abdullah, Nor Rul Hasma Musirin, Ismail Othman, Muhammad Murtadha Univ Malaysia Pahang Fac Elect & Elect Engn Pahang Malaysia

ISBN: (纸本)9781467350747;9781467350723

Increment of load demands will cause voltage decay in the system which may lead to voltage collapse and increase thermal effect to transmission line in the system. Thus, reactive power support is one of the alternative available schemes that can be performed to the system other than employing installing compensating devices. One of the choices is optimal reactive power dispatched (RPD). Operating all generators for performing reactive power support to a power system may lead to non-economical results which is rather unnecessary. Therefore, effort should be taken in order to avoid all generators from full operational in the attempt to raise the voltage level and improve the voltage stability condition in the system. This paper presents a new approach for selecting the operating generator performed optimally using evolutionary programming (EP) technique in power system. The proposed technique determines the best combination of generator that should be dispatched in the system considering loss minimization or voltage stability improvement. Implementation on the proposed technique was realized on the IEEE 30-bus RTS. Complete implementations on numerous combinations have been conducted and results indicated that the proposed technique revealed the best combination of the operating generators for improving voltage stability in the system.

关键词： Reactive Power Dispatch Operating Generator Selection evolutionary programming Static Voltage Stability Index

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Optimum management of manual sectionalizers in electric power distribution networks integrating distributed generations using binary exchange market algorithm

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INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT 2021年第2期15卷 328-351页

作者： Farhadi, Payam Tafreshi, Seycd Masoud Moghaddas Univ Guilan Fac Engn Dept Elect Engn Rasht Iran

Purpose The use of power sectionalizers in electric power distribution networks as disconnecting devices for optimum network configuration is indispensable. Major reasons to use sectionalizers, here manual sectionalizers, is their lower installation and operating prices compared to other types of disconnecting devices and that most of conventional realistic electric power distribution systems are still using manual sectionalizers due to their ease of procurement. However, in case of failure for these switches, power supply interruptions are unavoidable unless optimum solutions are used for configuration (and possibly reconfiguration) of sectionalizers. Thus, in this research, binary exchange market algorithm (BEMA) as a novel evolutionary metaheuristic is used to meet the maximized customer satisfaction by optimized configuration of sectionalizers within electric power distribution networks in the presence of distributed generations (DGs). To solve the problem, BEMA is used on sectionalizing switch placement problem, which has only two open and close (0/1) states. A novel multi-objective optimization problem has been formulated as a function of two aspects, namely, improved reliability index (for customer benefit) and minimized sectionalizing switch costs (for utility benefits). Simulations are carried out in three different case studies to validate the effectiveness of the BEMA both in theory and practice: Standard IEEE 33-bus test system, practical feeder-8 of MeshkinShahr Town's electric power distribution network in northwest of Iran;and Roy Billinton test system Bus 4 (RBTS-Bus 4). The obtained results are compared with those of the previously validated ant colony optimization (ACO) technique in RBTS-Bus 4. Design/methodology/approach The optimum configuration of sectionalizers in the presence of DGs has been formulated as a multi-objective function consisting of two conflicting objectives. First objective is to improve the power distribution network reliabilit

关键词： Energy sector Multiobjective optimization Energy conversion evolutionary programming Simulation Reliability Electricity Distribution network Exchange market algorithm Optimized configuration Sectionalizers

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Optimal DG Placement for Power System Reliability based on N-1 Contingency Analysis 19

Optimal DG Placement for Power System Reliability based on N...

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19th IEEE Student Conference on Research and Development (SCOReD)

作者： Azhar, Noor Aliff Nazmi Bin Noor Mohamad, Hasmaini Salim, Nur Ashida Yasin, Zuhaila Mat Univ Teknol MARA Coll Engn Sch Elect Engn Shah Alam 40450 Selangor Malaysia Univ Teknol MARA Coll Engn Sch Elect Engn Power Syst Planning & Operat Grp PoSPO Shah Alam 40450 Selangor Malaysia

ISBN: (纸本)9781665401937

Typically, consumers experience power outages as a result of transmission system issues. Transmission lines are one of the most used technical systems for transporting large amounts of electricity from one part of a country to the farthest point in the opposite direction. The transmission lines traverse many terrain types and geographic regions, which makes them more sensitive to various types of atmospheric disasters and causes frequent line faults and power outages. Therefore, power system reliability and power loss are important, since if these losses are higher than the industry norm, the amount of power accessible to customers will be reduced. Power from a distributed generator (DG) system is incorporated into a power system in this study to improve the power system reliability, average energy not supplied (AENS), and reduce transmission line losses. The results of an optimal DG installation are gained from the penetration of distributed generation in an IEEE 14-bus system by using the evolutionary programming (EP) optimization technique. The results prove that with the use of EP optimization, power system reliability can be improved post optimization.

关键词： optimization evolutionary programming power system reliability average energy not supplied

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