scholarly journals Application of an improved PSO algorithm mixed BFO algorithm in optimal scheduling of hydropower station

2018 ◽  
Vol 246 ◽  
pp. 01044
Author(s):  
Yibo Zou ◽  
Mo Li ◽  
Xiaogang Xiao
Keyword(s):  
Strong Dependence ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Local Extremum ◽  
Optimal Scheduling ◽  
Hydropower Station ◽  
Scheduling Model ◽  
Multi Stage ◽  
Improved Pso

The optimal scheduling of hydropower station is a constrained strong, nonlinear and multi-stage combinatorial optimization. Aiming at this issue, this paper analyses the shortcomings of previous PSO algorithm in hydropower station optimal scheduling model, and presents an improved PSO algorithm for hybrid BFO algorithm, which overcomes the problem that the PSO algorithm is easy to fall into local extremum and has strong dependence on parameters. A case study of a short-term scheduling period of a hydropower station is used to compare the improved PSO algorithm mixed BFO algorithm with previous PSO algorithm. The results show that the improved PSO algorithm can converge to the global optimal solution more accurately. Therefore, it provides a new method for solving the optimal scheduling model of hydropower station.

scholarly journals A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets

Processes ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 107 ◽  
Author(s):  
Li ◽  
Tan ◽  
Ren ◽  
Yang ◽  
Yu ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Spot Market ◽  
Optimal Scheduling ◽  
Spot Markets ◽  
Chance Constrained Programming ◽  
Two Stage ◽  
Market Prices ◽  
Scheduling Model ◽  
Proposed Model ◽  
Constrained Programming

Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market.

scholarly journals Application of Improved Particle Swarm Optimization in Vehicle Crashworthiness

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Dawei Gao ◽  
Xiangyang Li ◽  
Haifeng Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Design ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Local Extremum ◽  
Local Optimum ◽  
Global Optimality ◽  
Critical Position ◽  
Swarm Optimization ◽  
Improved Pso

In the optimization design process, particle swarm optimization (PSO) is limited by its slow convergence, low precision, and tendency to easily fall into the local extremum. These limitations make degradation inevitable in the evolution process and cause failure of finding the global optimum results. In this paper, based on chaos idea, the PSO algorithm is improved by adaptively adjusting parameters r1 and r2. The improved PSO is verified by four standard mathematical test functions. The results prove that the improved algorithm exhibits excellent convergence speed, global search ability, and stability in the optimization process, which jumps out of the local optimum and achieves global optimality due to the randomness, regularity, and ergodicity of chaotic thought. At last, the improved PSO algorithm is applied to vehicle crash research and is used to carry out the multiobjective optimization based on an approximate model. Compared with the results before the improvement, the improved PSO algorithm is remarkable in the collision index, which includes vehicle acceleration, critical position intrusion, and vehicle mass. In summary, the improved PSO algorithm has excellent optimization effects on vehicle collision.

scholarly journals Optimal operating scenario for Polerood hydropower station to maximize peak shaving and produced profit

2018 ◽  
Vol 7 (3) ◽  
pp. 233-239
Author(s):  
Behzad Forouzi Feshalami
Keyword(s):  
Optimal Solution ◽  
Hydropower Station ◽  
Dynamic Programming Method ◽  
Optimal Operating ◽  
Peak Shaving ◽  
The North ◽  
Renewable Energy Development ◽  
North Of Iran ◽  
Performance Strategies

This paper deals with the optimization of the daily operation of Polerood hydropower station being constructed in the north of Iran. Dynamic Programming method (DP) is applied as the preferred optimization tool owing to the fact that it guarantees the optimal solution and is applicable to the present problem. Produced profit and peak-shaving are the two objectives considered separately in this study. The results show that the optimal water management of the case study through charging and discharging the reservoir at the appropriate times led to 4% increase in the produced profit. In another part of this study, the optimal performance strategies regarding to the two objectives (produced profit and peak-shaving) are compared. The observed similarity between the two performance strategies implies the substantial dependence of the electricity price and the network demand level. The paper ends with the profitability study of the project and the sensitivity analysis of the results to various economic parameters. Article History: Received December 15th 2017; Received in revised form April 18th 2018; Accepted September 16th 2018; Available onlineHow to Cite This Article: Feshalami, B.F. (2018) Optimal Operating Scenario for Polerood Hydropower Station to Maximize Peak Shaving and Produced Profit. International Journal of Renewable Energy Development, 7(3), 233-239.https://doi.org/10.14710/ijred.7.3.233-239

scholarly journals Improved PSO Algorithm Based on Exponential Center Symmetric Inertia Weight Function and Its Application in Infrared Image Enhancement

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 248 ◽  
Author(s):  
Chaoxuan Qin ◽  
Xiaohui Gu
Keyword(s):  
Weight Function ◽  
Image Enhancement ◽  
Fitness Function ◽  
Infrared Image ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Histogram Equalization ◽  
Inertia Weight ◽  
Enhancement Method ◽  
Improved Pso

In this paper, an improved PSO (Particle Swarm Optimization) algorithm is proposed and applied to the infrared image enhancement. The contrast of infrared image is enhanced while the image details are preserved. A new exponential center symmetry inertia weight function is constructed and the local optimal solution jumping mechanism is introduced to make the algorithm consider both global search and local search. A new image enhancement method is proposed based on the advantages of bi-histogram equalization algorithm and dual-domain image decomposition algorithm. The fitness function is constructed by using five kinds of image quality evaluation factors, and the parameters are optimized by the proposed PSO algorithm, so that the parameters are determined to enhance the image. Experiments showed that the proposed PSO algorithm has good performance, and the proposed image enhancement method can not only improve the contrast of the image, but also preserve the details of the image, which has a good visual effect.

Maintenance Project Scheduling Model Considered Flexible Resource with Capability Difference

2013 ◽  
Vol 791-793 ◽  
pp. 1566-1569
Author(s):  
Chang Zheng Qu ◽  
Hong Qiang Gu ◽  
Hui Song ◽  
Guang Yu Liu
Keyword(s):  
Task Scheduling ◽  
Project Scheduling ◽  
Pso Algorithm ◽  
Resource Constraint ◽  
Swarm Optimization ◽  
Scheduling Model ◽  
Flexible Resource ◽  
Project Scheduling Problem ◽  
Capability Level

Maintenance task scheduling during mission break is described as flexible resource constraint project scheduling problem, and flexible resource constraint maintenance task scheduling model is established. Since capability level of flexible resource is different, the thesis establishes maintenance task scheduling model considering capability difference. To resolve the model, a particle swarm optimization (PSO) algorithm based on activity list is presented. At last, a case study is present.

scholarly journals Research on steering control performance of electric forklift with steer by wire

2021 ◽  
Vol 12 ◽  
pp. 1
Author(s):  
Chuan Feng
Keyword(s):  
High Speed ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Steering Control ◽  
Sideslip Angle ◽  
Cargo Handling ◽  
Locally Optimal Solution ◽  
The Stability ◽  
Improved Pso

Forklift plays an important role in cargo handling in the warehouse; therefore, it is necessary to ensure the stability of the forklift when turning to guarantee the safety of transportation. In this study, the particle swarm optimization (PSO) algorithm was improved by a genetic algorithm (GA), and the parameters of the proportion, integration, and differentiation (PID) controller were calculated using the improved algorithm for forklift steering control. Then simulation experiments were carried out using MATLAB. The results showed that the convergence speed of the improved PSO algorithm was faster than that of GA, and its adaptive value after convergence stability was significantly lower than that of the PSO algorithm; whether it was low-speed or high-speed steering, the three algorithms responded to the steering signal quickly; the yaw velocity and sideslip angle of the forklift steering under the improved PSO algorithm were more suitable for stable steering, and the increase of the steering speed would increase the yaw velocity. The novelty of this paper is that the traditional PSO algorithm is improved by GA and the particle swarm jumps out of the locally optimal solution through the crossover and mutation operations.

Aplikasi Metode Hungarian Dalam Optimalisasi Waktu Penugasan Karyawan dan Keuntungan Produksi Home Industry

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Empya Charlie ◽  
Siti Rusdiana ◽  
Rini Oktavia
Keyword(s):  
Sensitivity Analysis ◽  
Optimal Solution ◽  
Optimal Scheduling ◽  
Total Work ◽  
Work Time ◽  
Hungarian Method ◽  
Total Work Time

Penelitian ini bertujuan untuk mengoptimalkan penjadwalan karyawan di CV. Karya Indah Bordir dalam melakukan tugas-tugas tertentu menggunakan metode Hungaria, serta menganalisis sensitivitas solusi optimal jika ada pengurangan waktu karyawan untuk menyelesaikan tugas-tugas. Metode Hongaria diterapkan pada proses bordir yang melibatkan 11 karyawan dan 10 tugas. Hasil penjadwalan yang optimal meminimalkan waktu produksi bordir perusahaan. Hasil penjadwalan optimal yang ditemukan adalah: karyawan 1 mengerjakan tas Mambo, karyawan 2 mengerjakan tas Elli, karyawan 3 mengerjakan tas Lonjong, karyawan 4 mengerjakan tas Tampang bunga, karyawan 6 mengerjakan tas Ransel, karyawan 7 mengerjakan tas Tima, karyawan 8 mengerjakan tas Keong, karyawan 9 mengerjakan tas Alexa, karyawan 10 mengerjakan tas Luna, dan karyawan 11 mengerjakan tas Mikha, dengan total waktu kerja adalah 13,7 jam. Setelah metode Hongaria diterapkan, CV. Karya Indah Bordir mendapat peningkatan pendapatan sebanyak 9,09%. Analisis sensitivitas dilakukan dengan mengurangi waktu karyawan dalam menyulam tas. Hasil analisis sensitivitas adalah beberapa batasan untuk variabel basis dan non basis untuk mempertahankan solusi optimal.   This research has a purpose to optimize the scheduling of employees in CV. Karya Indah Bordir in doing certain tasks using Hungarian method, as well as analyzing the sensitivity of the optimal solution if there is a reduction on the employees time to finish the tasks. The Hungarian method was applied on the embroidery process involving 11 employees and 10 tasks. The optimal scheduling result minimize the time of the embroidery production of the company. The optimal scheduling result found is: employee 1 does the Mambo bag, employee 2 does the Elli bag, employee 3 does the Lonjong bag, employee 4 does the Tampang bunga bag, employee 6 does the Ransel, employee 7 does the Tima bag, employee 8 does the Keong bag, employee 9 does the Alexa bag, employees 10 does the Luna bag, and employee 11 does the Mikha bag, with the total work time is 13,7 hours. After the Hungarian method was applied, CV. Karya Indah Bordir got the increasing revenue as much as 9,09 %. The sensitivity analysis was conducted by reducing the time of the employees take in embroidery the bags. The results of the sensitivity analysis are some boundaries for basis and non basis variables to maintain the optimal solution. 

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