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9th International Conference on Advanced Computing (ICoAC)

作者： Das, Sujoy Bhattacharya, Aniruddha Chakraborty, Ajoy Kumar Pandey, Vibhav Natl Inst Technol Agartala Dept Elect Engn Agartala 799046 Tripura India

ISBN: (纸本)9781538643495

In this article the authors have proposed the whale optimization algorithm to solve fixed-head short-term hydrothermal scheduling problem in the presence of solar powerconsidering multi-reservoir cascaded hydro plants. The generation of solar power mainly depends on the amount of solar irradiance, which is uncertain in nature. So, to deal with the uncertainty associated with solar energy, an efficient 2m point estimate method is used. To tackle the optimization part whale optimization algorithm is used. The hunting strategy of whales is very interesting and known as bubble-net feeding method. This strategy is very unique and mathematically modeled to perform an optimization process. To analyze the performance of the whale optimization algorithm, it has been tested on two test systems. The comparison of result shows that the proposed algorithm obtained better solution compare to other methods.

关键词： Hydrothermal scheduling Point estimate method Solar power whale optimization algorithm

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Feature Selection with The whale optimization algorithm and Artificial Neural Network

Feature Selection with The Whale Optimization Algorithm and ...

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2017 International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Canayaz, Murat Demir, Murat Van Yuzuncu Yil Univ Bilgisayar Muhendisligi Bolumu Van Turkey Mus Alparslan Univ Bilgisayar Muhendisligi Bolumu Mus Turkey

ISBN: (纸本)9781538618806

Feature selection is addressed an important problem in data mining. To be high dimension of the data obtained from the sources is encountered as an issue in many issues such as computation cost. For this reason, eliminating the unnecessary ones among these data and choosing the appropriate ones makes it possible to evaluate the information correctly. In this study, it is tried to suggest a method that can be used in feature selection on data sets. In this method, The whale optimization algorithm, which is one of the new meta-heuristic algorithms, is used to select appropriate features. Training with artificial neural networks takes place during the evaluation process of selected features. At the end of the training, the features that provide the minimum error value are selected. In the performance evaluation of the method, known data sets will be used and the results will be given in comparison with the Particle Swarm optimization method.

关键词： whale optimization algorithm feature selection artificial neural network

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Aero-engine Performance optimization Based on whale optimization algorithm 36

Aero-engine Performance Optimization Based on Whale Optimiza...

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第36届中国控制会议

作者： Xinge Huang Rui Wang Xudong Zhao Kaijian Hu School of Aeronautics and Astronautics Dalian University of Technology School of Control Science and Engineering Dalian University of Technology

ISBN: (纸本)9781538629185

Under the goal of pursuing safety,aero-engine is optimized by using an optimization algorithm to improve its performance and the comprehensive performance of the airplane.A nonlinear programming model is established to optimize the acceleration progress of a certain turbofan engine,where the rotor speed is involved in the objective ***,a novel nature-inspired optimization algorithm,called whale optimization algorithm（WOA）,which is used to solve the optimization problem of the *** results show that the WOA has a strong border search capacity and the engine’s acceleration capability has been improved.

关键词： Aero-engine optimization whale optimization algorithm

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A Multi-Objective Optimal Vehicle Fuel Consumption Based on whale optimization algorithm 12th

A Multi-Objective Optimal Vehicle Fuel Consumption Based on ...

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12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)

作者： Horng, Mong-Fong Thi-Kien Dao Shieh, Chin-Shiuh Trong-The Nguyen Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung Taiwan Haiphong Private Univ Dept Informat Technol Haiphong City Vietnam

ISBN: (纸本)9783319502120;9783319502113

Due to the complex environmental constraints in the field of transport and logistics, optimization for the vehicle fuel consumption problem satisfies not only one criterion but also several criteria. In this paper, a novel multi-objective method for an optimal vehicle traveling based on whale optimization algorithm (WOA) is proposed. In the proposed method, two criteria of distance and path-travel gasoline of the vehicle traveling issue are transformed into a minimization one. The vehicle routing and traffic status in the environmental transportation are considered to model the fitness function for the solution in WOA. The path of the globally best whale in each iteration is selected, and reached by the vehicles in sequence. In addition, the information of traffic status updates to vehicle periodically times from traffic navigation system during the traveling. Series scenarios of simulations are implemented in different traffic environments for the optimal paths when the vehicles reached the destination. The results show that the proposed method provides the confirm the practicality of the model of transport and logistics, and this proposed method may be the alternative method of optimization for the vehicle traveling in the logistics.

关键词： whale optimization algorithm Vehicle fuel consumption Multi-objective optimization

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ENERGIES 2017年第7期10卷 874-874页

作者： Zhao, Haoran Guo, Sen Zhao, Huiru North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China

Accurate and reliable forecasting on energy-related carbon dioxide (CO2) emissions is of great significance for climate policy decision making and energy planning. Due to the complicated nonlinear relationships of CO2 emissions with its driving forces, the accurate forecasting for CO2 emissions is a tedious work, which is an important issue worth studying. In this study, a novel CO2 emissions prediction method is proposed which employs the latest nature-enlightened optimization method, named the whale optimization algorithm (WOA), to search the optimized values of two parameters of LSSVM (least squares support vector machine), namely the WOA-LSSVM model. Meanwhile, the driving forces of CO2 emissions including GDP (gross domestic product), energy consumption and population are chosen to be the import variables of the proposed WOA-LSSVM method. Taking China's CO2 emissions as an instance, the effectiveness of WOA-LSSVM-based CO2 emissions forecasting is verified. The comparative analysis results indicate that the WOA-LSSVM model is significantly superior to other selected models, namely FOA (fruit fly optimization algorithm)-LSSVM, LSSVM, and OLS (ordinary least square) models in terms of CO2 emissions forecasting. The proposed WOA-LSSVM model has the potential to effectively improve the accuracy of CO2 emissions forecasting. Meanwhile, as a new nature-enlightened heuristic optimization algorithm, the WOA has the prospect for wide application.

关键词： CO2 emissions prediction whale optimization algorithm LSSVM parameters optimization driving forces

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Stabilization of a reduced order inverted pendulum by using whale optimization algorithm

Stabilization of a reduced order inverted pendulum by using ...

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International Conference on Computing Communication Control and Automation

作者： Dipayan Guha Ravi Kant Ranjan Shivam Kumar Singh Swati Priya Shubham Kumar Sharma Arnab Ghosh Electrical Engineering Department Motilal Nehru National Institute of Technology Allahabad India Electrical Engineering Department Dr B C Roy Engineering College Durgapur West Bengal India Electrical Engineering Department National Institute of Technology Rourkella Odisha India

ISBN: (纸本)9781538652589;9781538652572

In this paper, an attempt has been made to develop an efficient control algorithm for the stabilization of an inverted pendulum. A novel stochastic optimization technique namely whale optimization algorithm (WOA) is employed to search the optimum settings of proportional-integral-derivative controller with derivative filter (PIDF). The proposed WOA mimics bubble net hunting mechanism of humpback whales in nature. The main advantage of this algorithm is that only population size and maximum iteration count are required for its operation. Logarithmic approximation and time-moments have been adopted to formulate the reduced order model (ROM) of inverted pendulum. The results presented in this paper clearly show that proposed control algorithm with ROM exhibit satisfactory outputs and effectively increases the stability margin of inverted pendulum.

关键词： Inverted pendulum whale optimization algorithm Logarithmic approximation Time-moments Transient analysis

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Price Penalty Factors based Approach for Emission Constrained Economic Dispatch Problem Solution using whale optimization algorithm 1

Price Penalty Factors based Approach for Emission Constraine...

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1st IEEE International Conference on Power Electronics, Intelligent Control, and Energy Systems (ICPEICES)

作者： Trivedi, Indrajit N. Jangir, Narottam Jangir, Pradeep Pandya, Mahesh H. Bhesdadiya, R. H. Kumar, Arvind Govt Engn Coll Dept Elect Engn Gandhinagar Gujarat India Lukhdhirji Engn Coll Dept Elect Engn Morbi Gujarat India SS Engn Coll Dept Elect Engn Bhavnagar Gujarat India

ISBN: (纸本)9781467385879

In The main ambition of utility is to provide continuous reliable supply to customers, satisfying power balance, transmission loss while generators are allowed to be operated within rated limits. Meanwhile, achieve this purpose emission value and fuel cost should be as less as possible. An allowable deviation in fuel cost and feasible tolerance in fuel cost has been called emission constrained economic dispatch (ECED) problem. A new nature-inspired whale optimization algorithm (WOA) is based on concept of bubble-net hunting strategy is applied to solve ECED problem. ECED is a multi-criteria problem can transformed to single criteria using price penalty factor method. In this paper quadratic function together with emission value and fuel cost are considered as individual objective makes it multi-criteria problem. The effect of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average", "Common" price penalty factors and emission value of various pollutants gases exhalation are included. The emission constrained economic dispatch (ECED) problem is analysed for an IEEE-30 Bus system with six operational generator units. Results prove capability of WOA in solving ECED problem with different penalty factors.

关键词： whale optimization algorithm Bubble-net Hunting Strategy Emission Constrained Economic Dispatch Fuel Cost Emission Value

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An Emission Constraint Environment Dispatch Problem Solution with Microgrid using whale optimization algorithm

An Emission Constraint Environment Dispatch Problem Solution...

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National Power Systems Conference (NPSC)

作者： Trivedi, Indrajit N. Jangir, Pradeep Bhoye, Motilal Jangir, Narottam Bhesdadiya, R. H. Kumar, Arvind GEC Dept Elect Engn Gandhinagar Gujarat India LE Coll Dept Elect Engn Morbi Gujarat India SSEC Bhavnagar Dept Elect Engn Gujrat India

ISBN: (纸本)9781467399685

In this work, microgrid is modern small scale power system of the centralized electricity for a small community such as villages and commercial area. Microgrid consists of microsources like distribution generator, solar and wind units, etc., and different loads. In the microgrid, the energy management system (EMS) having a problem of Combined Economic Emission Dispatch (CEED) and it is optimized by metaheuristic techniques. The CEED is the procedure to scheduling the generating units within their bounds together with minimizing the fuel cost and emission values. The whale optimization algorithm (WOA) is applied for the solution of CEED problem in the MATLAB environment. The minimization of total cost and total emission are obtained for all sources included. The result shows the comparison of WOA with the Gradient Method (GM), Ant Colony optimization (ACO) and Particle Swarm Optimizer (PSO) technique for the two different cases which are Economic Load Dispatch (ELD) without emission and with emission. The results are calculated for different power demand of 24 hours. The results obtained with WOA gives better cost reduction in less iterations as compared to GM, ACO and PSO which shows the effectiveness of the given algorithm. The key objective of this work is to solve the CEED problem to obtained optimal system cost.

关键词： Microgrid Combined Economic Emission Dispatch Solar Generation Forecast Wind Generation Forecast whale optimization algorithm

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A Novel Global MPP Tracking of Photovoltaic System based on whale optimization algorithm

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY DEVELOPMENT-IJRED 2016年第3期5卷 225-232页

作者： Kumar, C. H. Santhan Rao, R. Srinivasa JNT Univ Kakinada Dept Elect & Elect Engn Kakinada 533003 Andhra Pradesh India

To harvest maximum amount of solar energy and to attain higher efficiency, photovoltaic generation (PVG) systems are to be operated at their maximum power point (MPP) under both variable climatic and partial shaded condition (PSC). From literature most of conventional MPP tracking (MPPT) methods are able to guarantee MPP successfully under uniform shading condition but fails to get global MPP as they may trap at local MPP under PSC, which adversely deteriorates the efficiency of Photovoltaic Generation (PVG) system. In this paper a novel MPPT based on whale optimization algorithm (WOA) is proposed to analyze analytic modeling of PV system considering both series and shunt resistances for MPP tracking under PSC. The proposed algorithm is tested on 6S, 3S2P and 2S3P Photovoltaic array configurations for different shading patterns and results are presented. To compare the performance, GWO and PSO MPPT algorithms are also simulated and results are also presented. From the results it is noticed that proposed MPPT method is superior to other MPPT methods with reference to accuracy and tracking speed.

关键词： Maximum power point tracking Partial shaded condition Photovoltaic generation system Single diode model whale optimization algorithm

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A Multi-Objective Optimal Mobile Robot Path Planning Based on whale optimization algorithm

A Multi-Objective Optimal Mobile Robot Path Planning Based o...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Thi-Kien Dao Tien-Szu Pan Jeng-Shyang Pan Department of Electronics Engineering Kaohsiung University of Applied Sciences Harbin Institute of Technology Shenzhen Graduate School Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology

Due to the complex physical constraints in working space of robot, optimization for mobile robot operations satisfies not only one criterion but also several criteria. In this paper, a novel multi-objective method for optimal mobile robot path planning based on whale optimization algorithm(WOA) is proposed. In the proposed method, two criteria of distance and smooth path of the robot path planning issue are transformed into a minimization one. The positions of the target and the obstacles in the environment are considered the fitness for the solution in WOA. The position of the globally best whale in each iteration is selected, and reached by the robot in sequence. In addition, the robot processor updates its information during the motion, and the environment is partially unknown for the robot due to the limit of the detection range of its sensors. Series of simulations are implemented in different static environments for the optimal path when the robot reaches its target. The results show that the proposed method provides the robot reaches its target with colliding free obstacles, and the proposed method may be the alternative method of optimization for robot planning.

关键词： whale optimization algorithm Path planning

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