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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Huang, Jieming Huang, Xiaorong Zhang, Qingbo Zhong, Rongfu Lai, Rijing Luo, Junjie Dongguan Power Supply Bureau of Guangdong Power Grid Corporation Guangdong Dongguan China

ISBN: (纸本)9798350339673

Energy storage technology can provide a variety of services for grid operation, such as peak regulation, frequency regulation, standby, startup, demand response, etc. However, considering that energy storage plants operate under multiple operating conditions, the peak regulation and valley filling of the power grid are unstable, and it is impossible to take into account the charging and discharging depth of energy storage plants and the decay of energy storage battery life and its capacity, so the original single charging and discharging control method can hardly meet the demand. The paper proposes an improved strategy of cuckoo algorithm for multiple operating conditions, and proves through experimental results that after considering the multi-operating conditions control strategy, the optimal configuration can be made by integrating all the operating conditions of the energy storage plant and the characteristics of the grid tide, which is superior to the actual operation of the original energy storage plant. © 2023 IEEE.

关键词： cuckoo algorithm Energy storage Grid peaking Multiple operating conditions Power Grid

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An Adaptive cuckoo algorithm-Based Optimization Method for Tourist Traffic Routes

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2024年第2期33卷 2450033-2450033页

作者： Hong, Qian Sun, Yanbin Chongqing Inst Engn Sch Innovat & Entreprenurship Chongqing 400056 Peoples R China Chongqing Inst Engn Sch Elect Informat Chongqing 400056 Peoples R China

This paper presents in-depth research and analysis of the optimization method of tourist traffic routes using the adaptive cuckoo algorithm. The traditional cuckoo algorithm has the disadvantages of slow convergence speed and easy falling into local extremes. This paper proposes the iterative adaptive CHSACS algorithm based on iteration. Based on the original CS algorithm, a dynamic adaptive step control amount and a segmented weighted position update formula are introduced to give a class of improved CS algorithms to coordinate the problem of local search and global search of the CS algorithm and speed up the convergence speed at the later stage. To address the problem that the out-of-bounds nests interfere with the convergence of the algorithm, a memory strategy is introduced to relocate the out-of-bounds nests in the search space to improve the stability of the algorithm. Experiments are conducted on the iterative adaptive-based conductive CHSACS algorithm with test function sets. Compared with the original CS algorithm, and ACO algorithm, the CHSACS algorithm has faster convergence, higher search accuracy and a better ability to avoid local optima when dealing with continuous function optimization problems. For the dynamic travel path problem of travel time optimization, the road travel time and sightseeing time of different periods are predicted based on historical data, and the most traveled distance of travel time between two sights is dynamically searched by using the search mechanism based on time windows. The iterative adaptive CHSACS algorithm is used to continuously find the tourist traffic route with the shortest travel time travel path from all combinations of tour sequences. This paper combines the characteristics of bus vehicle scheduling itself, takes into account the interests of both bus companies and tourists, establishes a bus vehicle scheduling model with the departure interval as the independent variable, introduces this hybrid cuckoo algorith

关键词： Adaptive cuckoo algorithm tourist traffic route optimization

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Trajectory tracking of a quadrotor using a robust adaptive type-2 fuzzy neural controller optimized by cuckoo algorithm

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ISA TRANSACTIONS 2021年 114卷 171-190页

作者： Shirzadeh, Masoud Amirkhani, Abdollah Tork, Nastaran Taghavifar, Hamid Amirkabir Univ Technol Dept Elect Engn Tehran Polytech Tehran 158754413 Iran Iran Univ Sci & Technol Sch Automot Engn Tehran *** Iran Iran Univ Sci & Technol Sch Elect Engn Tehran *** Iran Coventry Univ Sch Mech Aerosp & Automot Engn Coventry CV1 2JH W Midlands England

This paper proposes an adaptive and robust adaptive control strategy based on type-2 fuzzy neural network (T2FNN) for tracking the desired trajectories of a quadrotor. The designed methods can control both the position and the orientation of a quadrotor. Contrary to common sliding mode controllers (SMCs), the robust adaptive trajectory tracking scheme presented here is based on SMC with exponential reaching law;which helps reduce the phenomenon of chattering. Moreover, parameters including the gains of sliding surfaces, are optimized by cuckoo optimization algorithm (COA), and the results are compared with those obtained by genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO). The designed methods in this study are called adaptive T2FNN controller and the exponential SMC (ESMC)-T2FNN. The law for updating the T2FNN is obtained online by using the Lyapunov stability theory. Considering undesired factors such as uncertainties, external disturbances and control signal saturation, the results of our controllers are compared with those of the adaptive type-1 fuzzy neural network controller (T1FNN) and ESMC-T1FNN. The extensive simulations demonstrate the effectiveness of the proposed COA-based ESMC-AT2FNN approach compared to the other tested techniques (i.e. GA, PSO and ACO) in terms of the improved transient and steady-state trajectory-tracking performance. The mean and standard deviation values concerning the COA are obtained through statistical analyses at 0.00006173 and 0.000092, respectively. This paper also examines the complexity of COA in optimizing the trajectory tracking control of quadrotor and investigates the effects of COA parameters on optimization results. The stable performance of the cuckoo algorithm is demonstrated by varying its parameters and analyzing the obtained results. These results also show the convergence of COA for the considered problem. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Type-2 fuzzy controller Fuzzy neural network Quadrotor Trajectory tracking cuckoo algorithm

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Addressing the Cold-Start Problem Using Data Mining Techniques and Improving Recommender Systems by cuckoo algorithm: A Case Study of Facebook

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COMPUTING IN SCIENCE & ENGINEERING 2020年第4期22卷 62-73页

作者： Forouzandeh, Saman Aghdam, Atae Rezaei Forouzandeh, Soran Xu, Shuxiang Univ Appl Sci & Technol Dept Comp Engn Tehran Iran Ctr Tehran Municipal ICT Org Tehran Iran Univ Appl Sci & Technol Informat Technol Dept Tehran Iran Univ Appl Sci & Technol Tehran Iran Univ Tasmania Sch Technol Environm & Design Hobart Tas Australia

One of the most common problems in recommender systems is a "cold-start" problem, which is related to users who do not indicate any behavior on social media. This paper proposes a solution for tackling this ... 详细信息

关键词： Facebook Recommender systems Data mining Clustering algorithms Optimization Software Recommender Systems Data Mining Social Networks Cold-start cuckoo algorithm

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Multi-objective optimization of integrated gas-electricity energy system based on improved multi-object cuckoo algorithm

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ENERGY SCIENCE & ENGINEERING 2021年第10期9卷 1839-1857页

作者： Yang, Bowen North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China

With the depletion of sources of primary energy across the world, the prospect of a global energy crisis in the near future has raised considerable concern. Among the many sources of clean energy, wind energy is considered to be the most effective means of sustainable and environmentally friendly energy. Traditional systems of energy based on oil and natural gas still operate in a discrete manner, and the promise offered by the mutual coordination between energy systems to draw complementary benefits has not yet been fully exploited. This has prompted all energy sectors to examine the optimal integration of interconnected gas-electricity energy systems. In this context, this study proposes a multi-objective collaborative operational optimization model of P2G for an interconnected, integrated gas-electricity energy system in case of uncertain wind power. Based on the effect of carbon capture by using P2G, the effect of coupling gas and electricity, and the cost of low-capacity reserves, the authors use conditional risk values to design four targets of optimization-the operating cost of the system, rate of consumption of the natural gas system, total carbon emissions and capacity stand-by cost-according to the power system, natural gas system, thermal energy system, and their elements of coupling from multiple perspectives to clarify the constraints on the model. Moreover, to reduce the likelihood of the optimal solution falling into the local optimum, the improved cuckoo algorithm is used to optimize the multi-objective scheduling model. The authors used a 10-node power system and a six-node natural gas system as examples for simulation to verify the proposed model. The results of empirical analysis show the following: (a) Once the P2G equipment had been connected, it reduced the total operating cost and improved the consumption of wind power of the natural gas system regardless of whether backup services were provided. (b) The P2G equipment could be combined with ga

关键词： conditional risk value cuckoo algorithm integrated gas-electricity energy system multi-objective optimal scheduling model

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Short-term Wind power Prediction Model Based on cuckoo algorithm and BP neural Network

Short-term Wind power Prediction Model Based on Cuckoo Algor...

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2020 Asia Energy and Electrical Engineering Symposium

作者： Zhu, Chengming Wei, Yunbing Zhu, Jianan Jiang, Chengcheng Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781728167824

Aiming at the shortcomings of existing accurate prediction methods of wind power generation, a prediction model combining cuckoo algorithm and BP neural network is proposed. The optimal solution obtained by the cuckoo algorithm is used to assign the initial weight and threshold value of the BP neural network, and the historical power generation data is trained, and then the wind power is predicted by the BP neural network. In this paper, the actual wind power generation in Belgium is taken as an example to compare and analyze the error between BP neural network based on cuckoo algorithm and common BP neural network, BP neural network based on particle swarm optimization algorithm and BP neural network based on Genetic algorithm in wind power generation prediction. The experimental results show that the improved BP neural network model based on the cuckoo algorithm has better nonlinear fitting ability and higher accuracy than the other three network models for wind power prediction.

关键词： wind power generation cuckoo algorithm BP neural network prediction model

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An Optimized Electrifying Strategy for the Permanent-Magnet Spherical Actuator Based on the cuckoo algorithm

ELEKTROTEHNISKI VESTNIK

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ELEKTROTEHNISKI VESTNIK 2021年第1-2期88卷 8-16页

作者： Guo, Xiwen Wu, Siao Wang, Qunjing Li, Guoli Wen, Yan Anhui Univ Sch Elect Engn & Automat Hefei Anhui Peoples R China Anhui Univ Natl Engn Lab Energy Saving Motor & Control Tech Hefei Anhui Peoples R China Anhui Univ Ind Power Saving & Safety Lab Hefei Anhui Peoples R China Anhui Univ Collaborat Innovat Ctr Ind Energy Saving & Power Hefei Anhui Peoples R China

To assure a complex control of the permanent-magnet spherical actuator (PMSA), an optimized electrifying strategy based on the cuckoo algorithm is proposed. An electromagnetic analysis in mode and the PMSA torque values of the rotor and stator coils of different angles are obtained. A position-torque black-box model is set-up using the random forest method. Combined with the spin and tilt trajectory, the cuckoo algorithm optimizes the electrifying strategy resulting in a 5% similar to 18% power-loss reduction. Simulations and experiment show that by using the proposed strategy, the PMSA control system ensure a stable and effective performance of a reduced power-loss rate, thus providing a reference for the PMSM high-precision trajectory tracking control.

关键词： Permanent-Magnet Spherical Actuator (PMSA) Random Forest cuckoo algorithm Electrifying Strategy

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Collision avoidance decision-making by altering course based on Pareto cuckoo algorithm in multi-ship encounter

Collision avoidance decision-making by altering course based...

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作者： Xinlian XIE Aiyuan LIU Yukuan WANG Comprehensive Transportation Research Institute Dalian Maritime University

Aiming at collision avoidance decision-making problem in multi-ship encounter situation,the Pareto optimal theory is applied to the course altering decision making,a multiship encounter course alternation decision making model considering ship maneuverability is established,with collision avoidance effect,range loss,and rudder effect as three objective functions.A multi-objective cuckoo algorithm based on optimal solution set is designed to solve the optimal value of course angle *** the visibility clause and define the feasible area according to the navigation *** with the traditional weight-based multi-objective function solution,an example was verified in a certain area to verify the effectiveness of the model and *** results show that the Pareto cuckoo algorithm has a good effect in multi-ship encounter situations,and can provide the driver with various optimal collision avoidance plan.

关键词： Multi-ship encounter Course alteration Pareto cuckoo algorithm

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The Parameter Identification of PMSM Based on Improved cuckoo algorithm

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NEURAL PROCESSING LETTERS 2019年第3期50卷 2701-2715页

作者： Wu, Zhongqiang Du, Chunqi Yanshan Univ Coll Elect Engn Qinhuangdao 066004 Hebei Peoples R China

In view of the multi-parameter identification problem of permanent magnet synchronous motor, a kind of parameter identification method was proposed based on an improved cuckoo search algorithm. cuckoo search algorithm has the advantages of simple, less parameters, fast convergence etc., but it also has the defects of premature convergence and low computation accuracy. In view of the deficiency of cuckoo search algorithm, the fuzzy reasoning based on the cloud membership was designed to adjust the probability of an alien egg being discovered by host birds and adaptive variable step method was used to adjust the step size of Levy flights. The improved algorithm can accelerate the convergence speed and improve the local and global optimizing ability by increasing the diversity of the population. The multi-parameter identification results of permanent magnet synchronous motor show that the improved cuckoo algorithm can effectively identify the motor parameters, and compared with the traditional cuckoo algorithm, the effectiveness and superior performance are tested.

关键词： Permanent magnet synchronous motor Cloud membership cuckoo algorithm Parameter identification Fuzzy

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Short-term Wind power Prediction Model Based on cuckoo algorithm and BP neural Network

Short-term Wind power Prediction Model Based on Cuckoo Algor...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Chengming Zhu Yunbing Wei Jianan Zhu Chengcheng Jiang School of Electric and Electronic Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9781728167824

ISBN: (纸本)9781728167831

关键词： wind power generation cuckoo algorithm BP neural network prediction model BP neural networks Wind energy generation Cuculidae Wind energy Prediction models

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