scholarly journals An Experimental and Simulation Study on Optimisation of the Operation of a Distributed Power Generation System with Energy Storage—Meeting Dynamic Household Electricity Demand

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1091 ◽  
Author(s):  
Jie Ji ◽  
Xin Xia ◽  
Wei Ni ◽  
Kailiang Teng ◽  
Chunqiong Miao ◽  
...  

There are few experimental reports combining hybrid energy storage and diesel engine generators as the power source of distributed power generation systems. In this article, a distributed power generation with energy storage system (DG-ES) which contains a diesel engine generator and an energy storage unit is set up and tested in the laboratory to satisfy the dynamic changing load. The hybrid energy storage system is composed of a lead-acid battery and a supercapacitor. The DG-ES supplied power to meet the domestic load demand successfully under different seasons. A simulation model of this system was also set up in MATLAB software used to guide to the experimental operation of this system. The simulation results has 2.69% and 2.35% error. The results of the experimental tests show the DG-ES can provide enough power to meet the dynamic loads of the selected house, especially at peak time in both winter and summer time. Computational simulation results show that the performance of DG-ES is improved by 3.61% in summer and 1.86% in winter when the system’s operations are optimised.

2019 ◽  
Vol 11 (19) ◽  
pp. 5441 ◽  
Author(s):  
Chao Ma ◽  
Sen Dong ◽  
Jijian Lian ◽  
Xiulan Pang

Hybrid energy storage systems (HESS) are an effective way to improve the output stability for a large-scale photovoltaic (PV) power generation systems. This paper presents a sizing method for HESS-equipped large-scale centralized PV power stations. The method consists of two parts: determining the power capacity by a statistical method considering the effects of multiple weather conditions and calculating the optimal energy capacity by employing a mathematical model. The method fully considers the characteristics of PV output and multiple kinds of energy storage combinations. Additionally, a pre-storage strategy that can further improve stability of output is proposed. All of the above methods were verified through a case study application to an 850 MW centralized PV power station in the upstream of the Yellow river. The optimal hybrid energy storage combination and its optimization results were obtained by this method. The results show that the optimal capacity configuration can significantly improve the stability of PV output and the pre-storage strategy can further improve the target output satisfaction rate by 8.28%.


The paper represents the design of a 100 kW three-phase network inverter for a hybrid energy storage system based on batteries and supercapacitors. The presented design is based on fast IGBT switches, provides their effective cooling and can be performed in a modular design. The inverter is designed for parallel operation with the network in bidirectional mode and island mode. The control algorithm allows for direct control of active and reactive power. The obtained simulation model and simulation results are used to calculate the inverter parameters and debug the control system. Simulation results show good performance and effectiveness of the invertor and the algorithm


Author(s):  
Shangzhou Zhang

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.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1721
Author(s):  
Ratnam Kamala Sarojini ◽  
Palanisamy Kaliannan ◽  
Yuvaraja Teekaraman ◽  
Srete Nikolovski ◽  
Hamid Reza Baghaee

The role of renewable energy sources in the power grid is increasing tremendously. However, power electronic converters are used to incorporate RES into the grid without inertia. This article recommends an improved emulated inertia control approach focused on the frequency deviation and rate of change of frequency to enhance the inertia of a power system. The required inertial power calculated from emulated inertia control is delivered through hybrid energy storage systems equipped with a proper hybrid energy storage system control. The fast-varying power calculated from emulated inertia control is linked to super-capacitor. Simultaneously, the battery handles the slow varying power by regulating the DC bus voltage proportionate to the frequency variations. Further, the stability of the emulated inertia control and hybrid energy storage system controller is validated by Bode plots. The simulation results verified the correctness of the proposed emulated inertia control and hybrid energy storage system control. The real-time simulation results with the help of OPAL-RT are presented to validate the proposed method’s feasibility.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Rui Zhu ◽  
An-lei Zhao ◽  
Guang-chao Wang ◽  
Xin Xia ◽  
Yaopan Yang

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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