Investigating the Optimum Operational Strategy of Energy Storage Tank by Using Particle Swarm Algorithm

2015 ◽  
Vol 45 (7) ◽  
pp. 648-660
Author(s):  
Hassan Hajabdollahi ◽  
Najmeh Pourgholamali
Keyword(s):  
Energy Storage ◽  
Storage Tank ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Operational Strategy ◽  
Swarm Algorithm

Optimal Control of Hybrid Energy Storage System of New Energy Power Generation System Based on Improved Particle Swarm Algorithm

2022 ◽  
Author(s):  
Shangzhou Zhang
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Storage System ◽  
Particle Swarm ◽  
Energy Storage System ◽  
Particle Swarm Algorithm ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System ◽  
Swarm Algorithm

In order to ensure the stability and reliability of power supply and realize day and night power generation, wind and solar complementary power generation systems are built in areas with abundant solar and wind energy resources. However, the system investment cost is too high. Because of this, there are wind, light intermittent, and non-intermittent power generation systems. For issues such as stability, an energy storage system needs to be configured to stabilize power fluctuations. This paper aims to study the optimization control of hybrid energy storage system of new energy power generation system based on improved particle swarm algorithm. In this paper, the application of particle swarm algorithm to power system reactive power optimization has been researched in two aspects. Through optimization methods, reasonable adjustment of control variables, full use of equipment resources of the power grid, to improve voltage quality and reduce system operation network to ensure the stability of the voltage system. In addition, this paper selects the IEEE30 node test system and simulation data analysis, takes the hybrid energy storage system as the optimization object, and optimizes the reactive power of the newly improved particle swarm algorithm. The experiments in this paper show that the improved algorithm has a good effect in reactive power optimization, increasing the performance of the hybrid energy storage system by 27.02%. MPSO algorithm is also better than basic PSO algorithm. It can be seen from the figure that in the PSO algorithm, the algorithm basically tends to be stable after more than 40 iterations, and finally the algorithm converges to 0.089.

scholarly journals Capacity Configuration Optimization of Micro-grid System basedon Quantum Particle Swarm Algorithm

2021 ◽  
Vol 252 ◽  
pp. 01021
Author(s):  
Zhang Yuqiong ◽  
Chen Ziwei ◽  
Shao Zhifang ◽  
Zhao Qiang ◽  
Han Chuyin
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Hydrogen Production ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Environmental Benefits ◽  
Particle Swarm Algorithm ◽  
Grid System ◽  
Micro Grid ◽  
Swarm Algorithm

The optimized configuration of wind/photovoltaic/storage micro-grid system capacity can realize multi-energy complementation and improve the stability and economy of grid-connected operation of power generation units. In this paper, the capacity of each core component of the micro-grid system under different combination paths such as Wind-PV power generation, battery energy storage, hydrogen production by electrolysis, and fuel cell power generation are optimized and economically analyzed. Taking the FCFF (Free Cash Flow of Firm) net present value maximization of the system running for 20 years as the objective function, considering the impact of energy shortage rate and dynamic electricity price, an operation research optimization model is established and intelligent algorithms are used to solve the model. The model can flexibly realize capacity optimization under different micro-grid combination paths, and it can prevent the solution result from falling into the local optimum through the design of quantum particle swarm algorithm. We analyzed the optimization results in terms of economic benefits, social benefits, and environmental benefits, and further analyzed the annual power generation status of the system and the operation status of the electrolysis hydrogen production system. The calculation example shows that under the current technical conditions, the micro-grid system composed of wind and solar power generation, electrochemical energy storage, and hydrogen production by electrolysis has better economic, social and environmental benefits than other models.

Planning Method of Cross-Level Distribution Network Based on Immune Particle Swarm Algorithm

2018 ◽  
Author(s):  
Rui Gong ◽  
Jianshou Kong ◽  
Xiaopeng Ji ◽  
Mingji Xu ◽  
Zhao Liu
Keyword(s):  
Distribution Network ◽  
Particle Swarm ◽  
Planning Method ◽  
Particle Swarm Algorithm ◽  
Swarm Algorithm

Orthogonal Immune Clone Particle Swarm Algorithm on Multiobjective Optimization

2011 ◽  
Vol 30 (10) ◽  
pp. 2320-2324 ◽  
Author(s):  
Lin Cong ◽  
Li-cheng Jiao ◽  
Yu-heng Sha
Keyword(s):  
Multiobjective Optimization ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Swarm Algorithm

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

scholarly journals Microgrid Trading Game Model Based on Blockchain Technology and Optimized Particle Swarm Algorithm

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Binyao Liu ◽  
Ming Wang ◽  
Jiakai Men ◽  
Dechang Yang
Keyword(s):  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Game Model ◽  
Model Based ◽  
Blockchain Technology ◽  
Swarm Algorithm
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