Economic evaluation for wind power generation-hybrid energy storage system based on game theory

2016 ◽  
Vol 41 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Xiaojuan Han ◽  
Zekun Zhao ◽  
Jianlin Li ◽  
Tianming Ji
Keyword(s):  
Power Generation ◽  
Game Theory ◽  
Economic Evaluation ◽  
Storage System ◽  
Energy Storage System ◽  
Wind Power Generation ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System ◽  
Generation Hybrid

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 An Energy Storage Performance Improvement Model for Grid-Connected Wind-Solar Hybrid Energy Storage System

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Rui Zhu ◽  
An-lei Zhao ◽  
Guang-chao Wang ◽  
Xin Xia ◽  
Yaopan Yang
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Generation System ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System ◽  
Hybrid Power ◽  
Power Generation System

This study introduces a supercapacitor hybrid energy storage system in a wind-solar hybrid power generation system, which can remarkably increase the energy storage capacity and output power of the system. In the specific solution, this study combines the distributed power generation system and the hybrid energy storage system, while using the static reactive power compensation system and the conductance-fuzzy dual-mode control method to increase output power in stages. At the same time, the optimal configuration model of the wind-solar hybrid power generation system is established using MATLAB/Simulink software. The output power of the microgrid to the wind-photovoltaic hybrid power generation system is calculated by simulation, and the optimization process of each component of the system is simulated. This study mainly uses the static reactive power compensation system and the conductance-fuzzy dual-mode control method to optimize the wind-solar hybrid power generation system. Using MATLAB software simulation verifies the feasibility and rationality of the optimal configuration of the system.

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