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Research on electrical load distribution using an improved bacterial foraging algorithm

FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Zhang, Yi Lv, Yang Jilin Jianzhu Univ Changchun Peoples R China

This paper proposes an improved bacterial foraging algorithm for electrical load distribution to impro-ve power plants' efficiency and reduce energy consumption costs. In the chemotaxis stage, the adaptive step size is introduced to accelerate the random search speed compared with the traditional algorithm. In the replication stage, a hybrid crisscross operator is proposed to replace the traditional binary replication method in the algorithm to ensure the diversity of the population and improve the efficiency of the algorithm. The adaptive dynamic probability is used instead of the initial fixed probability to improve the global search performance of the algorithm. The mathematical model of electrical load distribution in a natural power plant is established, and the improved bacterial foraging algorithm is used to solve the model. Through comparative analysis of two power plant unit experiments, it is proved that the results of the improved algorithm can reduce 3.671% and 1.06% respectively compared with the particle swarm optimization algorithm, and 7.26% and 1.37% respectively compared with the traditional bacterial foraging algorithm, which can significantly reduce the coal consumption of the power plant.

关键词： bacterial foraging algorithm crisscross operator electrical load distribution economic benefits of power plant self-adaption

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Forecasting China's Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a bacterial foraging algorithm

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ENERGIES 2019年第7期12卷 1331页

作者： Jiang, Peng Dong, Jun Huang, Hui North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China

The energy consumption pattern dominated by traditional fossil energy has led to global energy resource constraints and the deterioration of the ecological environment. These challenges have become a major issue all over the world. At present, the Chinese government aims to significantly reduce the fossil energy consumption contribution in the terminal energy consumption. The development of renewable energy in the terminal energy and energy conversion links has significantly increased the proportion of clean low-carbon energy. In order to accurately get the proportion of renewable energy terminal power consumption, firstly, this paper selects a primary influencing-factors set including the gross GDP, fixed investment in renewable energy industry, total length of cross-provincial and cross-regional high-voltage transmission lines, etc. as influencing factors of China's electricity consumption fraction produced by renewable energy based on a multitude of papers. Secondly, from the perspective of signal decomposition, the data inevitably has a lot of interference and noise. This paper uses the empirical mode decomposition (EMD) algorithm to reduce the degree of signal distortion and decomposes the signal into natural modes including several intrinsic mode functions (IMFs) and a residual term (Res);afterwards, a new extreme learning machine (ELM) forecasting model optimized by an Inverse Square Root Linear Units (ISRLU) activation function is proposed, and the ISRLU function is used to replace the implicit layer activation function in the original ELM algorithm. Then, a new bacterial foraging algorithm (BFOA) is applied to optimize the parameters of the optimized ELM forecasting model. After multiple learning and training operations, the optimal parameters are obtained. Finally, we superimpose the output of each IMF and Res training task to get the amount of China's power consumption produced by renewable energy. Some statistical indicators including root mean squard er

关键词： renewable energy terminal power consumption energy forecasting grey theory empirical mode decomposition bacterial foraging algorithm extreme learning machine algorithm

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Utilization of bacterial foraging algorithm for Optimization of Boost Inverter Parameters

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Circuits and Systems 2016年第8期7卷 1430-1440页

作者： G. Arunkumar Dr. I. Gnanambal School of Electrical Engineering VIT University Vellore India Department of Electrical and Electronics Engineering GCE Salem Anna University Chennai India

This paper proposes a boost inverter model capable of coping with changes in load as well as line parameters. In order to achieve an output AC voltage higher than the input DC voltage, we can use this model consisting of a pair of DC-DC converters with a load connected differentially across them. This paper aims at developing a boost inverter that is capable of achieving a very high gain, to obtain an AC voltage of 110 Vrms from a DC input of 36 V. This is exceptionally beneficial in renewable energy applications, where the input voltage garnered is quite small, and in need of stepping up for commercial use or transmission. However, aside from the voltage level itself, lowering the rise time, settling time, peak overshoot and steady state error of the system is of cardinal importance in order to maintain a reliable output voltage. Closed loop control of the differentially connected DC-DC converters is necessary to determine the optimal stable operating point. This paper addresses the above concerns through optimization of the proportional and integral constants using the novel bacterial foraging algorithm, ensuring operation at the required optimal stable operating point. Moreover, load/line disturbances may occur due to which the stability of output voltage may be compromised and THD value may increase to undesirable extents. In these cases, utilization of the output voltage is no longer viable for several applications sensitive to such voltage fluctuations. We have demonstrated that our proposed model is capable of restoring/reverting to the satisfactory sinusoidal waveform fashion within a single voltage cycle. The waveform results that demonstrate the resilience of our model to such disturbances are represented appropriately.

关键词： Boost Inverter bacterial foraging algorithm PI Controller

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Binarization based Image Edge Detection using bacterial foraging algorithm

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Procedia Technology 2012年 6卷 315-323页

作者： Om Prakash Verma Rishabh Sharma Deepak Kumar Department of Information Technology Delhi Technological University Delhi India Ericsson India Global Services Pvt. Ltd Software Engineer Noida UP India National Informatics Center Delhi State Ministry Of Communication And IT Govt. Of India Delhi India

bacterial foraging algorithm (BFA) is one of the powerful bio-inspired optimization algorithms which attempt to imitate the single and groups of E. Coli bacteria. In BFA algorithm, a set of bacteria try to forage towards a nutrient rich medium to get more nutrients. In this scheme, an objective function is posed as the effort or a cost incurred by the bacteria in search of food. In the present, an approach is presented for edge detection in a binarized image using bacterial foraging algorithm. .First binarization is applied to the input image to get an image matrix consisting of only the intensity values 0 and 255 of 8-bit image and then a swarm of bacteria are enthrusted on the binary image for extraction of edge information. Edges are detected by calculating the difference between intensity values of the present pixel with each of the neighboring eight pixels. Whenever the bacteria finds this intensity difference of 255 it will treat that pixel as its food and mark it as an edge pixel.

关键词： bacterial foraging algorithm Edge Optimization Binarization and heuristic

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A New Bidirectional Research Chord Method Based on bacterial foraging algorithm

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电脑学刊 2018年第3期29卷 210-219页

作者： Hang Li Lin Teng Shoulin Yin

In order to improve mismatching problem between physical topology and the logical topology in traditional Chord, and improve low search efficiency produced by space complexity, we propose a new bidirectional research Chord method based on bacterial foraging algorithm, which combines the advantage of bidirectional research method and bacterial foraging algorithm. This new algorithm regards topology matching problem as one traveling salesman problem, because bacterial foraging algorithm can get optimal solution for TSP, then we use the optimal solution to construct Chord ring, which can solve the mismatching problem. On this basis, we use the bidirectional search method to further accelerate the search speed. The experimental results show that the new algorithm has better performance than the traditional Chord algorithm on the aspect of query path length and finding the hop number. We also make comparison to other latest algorithms with the new method.

关键词： bacterial foraging algorithm bidirectional research chord method physical topology traveling salesman problem

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Proportional and Integral Constants Optimization Using bacterial foraging algorithm for Boost Inverter

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Energy Procedia 2016年 90卷 535-539页

作者： G. Arunkumar I. Gnanambal P.C. Karthik S. Naresh Vellore Institute of Technology Vellore India Govt. College of Engineering Affiliated to Anna University Salem India

A boost dc-ac inverter is one which is capable of generating in a single stage ac voltage whose peak value can be higher or lower than the given input dc voltage. The major problem with this system is that the closed loop gain parameters kp and ki have to be optimized because these parameters help us to get desired result with better system response by lowering the rise time, settling time, peak overshoot and steady state error. Moreover when they are not optimized load line disturbances arise because of which the stability of output voltage decreases and THD value increases. So to overcome these difficulties bacterial foraging algorithm is being used.

关键词： Boost Inverter bacterial foraging algorithm PI Controller.

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Generation-based automatic generation control with multisources power system using bacterial foraging algorithm

ENGINEERING REPORTS

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ENGINEERING REPORTS 2020年第8期2卷

作者： Hakimuddin, Nizamuddin Nasiruddin, Ibraheem Bhatti, Terlochan Singh New Okhla Ind Dev Author Noida 201301 Uttar Pardesh India Jamia Millia Islamia Fac Engn & Technol New Delhi India Indian Inst Technol Delhi Ctr Energy Studies Hauz Khas Delhi India

This article presents an application of bacterial foraging algorithm (BFA) for design and implementation of generation-based PID structured automatic generation control (AGC) in a 2-area multisources power system with hydro, thermal, and gas power plants incorporated in each area. Most of AGC studies carried out so far have considered the initial system loading to be equal to 50% of the area generation capacity. But, AGC controller parameters are uncertain due to stochastic nature of power demand of the end users. Hence, in this article, the design of AGC controller is proposed on the basis of generation schedule by incorporating changes in power system gain constant, power system time constant, frequency bias constant, and so on. The dynamic responses of power system with BFA tuned AGC controller are compared with the genetic algorithm tuned AGC controller. The parameters of the controllers are evaluated by using these techniques and investigations are carried out to find the best performance of the system. Therefore, it is desirable to find the parameters of the generation-based controller depending upon the contribution of its constituent hydro, thermal, and gas energy sources in the total power generation.

关键词： automatic generation control multisources power system generation-based controller bacterial foraging algorithm

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Task allocation-based modified bacterial foraging algorithm for maximising reliability of a heterogeneous distributed system

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INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND DISTRIBUTED SYSTEMS 2019年第2期23卷 252-273页

作者： Abbache, Farid Kalla, Hamoudi Univ Batna 2 LaSTIC Lab Comp Sci Dept Batna 05000 Algeria

modified bacterial foraging algorithm for allocation and scheduling tasks on processors and links with high reliability is proposed (MBFA). MBFA ensure high reliability without redundancy of processors or links by using an efficient and simple structure. MBFA is improved by adding an efficient model to deal with the weak solution (i.e., allocation with low reliability). Also a simulated annealing technique is integrated into MBFA in order to strengthen the search of best solution. The efficiency and effectiveness of MBFA are tested using random generated problems. MBFA is tested over the published approaches HPSO and GAA using density parameter (DS), number of nodes (N) and the communication to computation ratio parameter (CCR). The results show the superiority of MBFA over the published approaches in all test cases.

关键词： task allocation heterogeneous distributed system reliability bacterial foraging algorithm simulated annealing algorithm

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Crowd evacuation model based on bacterial foraging algorithm

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INTERNATIONAL JOURNAL OF MODERN PHYSICS C 2018年第3期29卷 1850027-1850027页

作者： Mu Shibiao Chen Zhijun Yiwu Ind & Commercial Coll Yiwu 322000 Peoples R China

To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model can effectively describe a real evacuation.

关键词： Crowd evacuation queue bacterial foraging algorithm

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bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times

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KNOWLEDGE-BASED SYSTEMS 2019年第May 15期172卷 104-122页

作者： Majumder, Arindam Laha, Dipak Suganthan, P. N. Jadavpur Univ Dept Mech Engn Kolkata India Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

In this paper, we propose an improved discrete bacterial foraging algorithm to determine the optimal sequence of parts and robot moves in order to minimize the cycle time for the 2-machine robotic cell scheduling problem with sequence-dependent setup times. We present a method to convert the solutions from continuous to discrete form. In addition, two neighborhood search techniques are employed to updating the positions of each bacterium during chemotaxis and elimination-dispersal operations in order to accelerate the search procedure and to improve the solution. Moreover, a multi-objective optimization algorithm based on NSGA-II combined with the response surface methodology and the desirability technique is applied to tune the parameters as well as to enhance the convergence speed of the proposed algorithm. Finally, a design of experiment based on central composite design is used to determine the optimal settings of the operating parameters of the proposed algorithm. The results of the computational experimentation with a large number of randomly generated test problems demonstrate that the proposed method is relatively more effective and efficient than the state-of-the-art algorithms in minimizing the cycle time in the robotic cell scheduling. (C) 2019 Elsevier B.V. All rights reserved.

关键词： 2-machine robotic cell Sequencing of parts Sequencing of robot moves Cycle time Minimal part set sequence bacterial foraging algorithm

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