Hierarchical control of DC micro-grid for photovoltaic EV charging station based on flywheel and battery energy storage system

Shen, Lei; Cheng, Qi; Cheng, Yinman; Lin, Wei; Wang, Yujiao

doi:10.1016/j.epsr.2019.106079

Cited by 66 publications

(68 citation statements)

References 13 publications

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“…Then, the match between electricity generation power of clean energy and electricity consumption power of centralized charging stations may not be realized. More seriously, low on‐site consumption rate of new energy and mass waste of energy storage may be caused 13,14 …”

Section: Multiobjective Operation Optimization Strategy Of Bssmentioning

confidence: 99%

Capacity coordination planning of isolated microgrid and battery swapping station based on the quantum behavior particle swarm optimization algorithm

Guo

Lei²,

Wang

2021

Int Trans Electr Energ Syst

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Summary In battery swapping station (BSS), the battery swapping of electric vehicle (EV) is not synchronous with the centralized charging of BSS. Based on new energy electricity generation and battery swapping demand information of EVs, how to formulate charging–discharging strategies of centralized charging stations is essential in BSS energy management system. Different from traditional BSS scheduling issues, considering that the supply–demand balance of power in isolated microgrid (IMG) could be regulated by the discharging of backup batteries, a service model of EV BSS is proposed with strong constraints, coupling relationships and randomness. Because the microgrid‐BSS capacity configuration optimization issue is nonlinear and multivariable, if traditional optimization algorithms are utilized, it would take a long time and the optimal solution may not be obtained. Moreover, there is no guarantee of complete convergence even with the standard particle swarm optimization (PSO) algorithm. In this paper, the quantum behavior particle swarm optimization (QPSO) algorithm is used to handle operation control issues of BSS. As shown in case results, with the QPSO algorithm proposed, both the reliability of battery swapping service and the maximum profit of BSSs could be implemented.

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Section: Multiobjective Operation Optimization Strategy Of Bssmentioning

confidence: 99%

Capacity coordination planning of isolated microgrid and battery swapping station based on the quantum behavior particle swarm optimization algorithm

Guo

Lei²,

Wang

2021

Int Trans Electr Energ Syst

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“…Energy storage: Since the DCNG does not contain controllable power sources, the charging and discharging processes of energy storage units are the main way to achieve power balance. The power exchange between the ESS and the system has two components: high frequency (HF) and low frequency (LF) components (Tudu et al, 2019;Shen et al, 2020;Chang et al, 2018). Short-term power fluctuations caused by sudden changes in load or fluctuations of renewable energy sources are regarded as HF components.…”

Section: Structure and Components Of Dcngmentioning

confidence: 99%

Review of Control Strategies for DC Nano-Grid

2021

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As an emerging energy management technology, the DC nano-grid coordinates renewable energy sources output through demand-side management which would provide more options and flexibility for the dispatch of smart buildings and communities with high reliability and efficiency. In this context, this article has analyzed the structure and components of the DC nano-grid. The role and components in DC nano-grid are reviewed in this article. Then the crucial control technologies for the DC nano-grid in recent years are investigated from two aspects: local control and coordinated control, which contains control schemes such as voltage/current control technology, power-sharing technology and cooperative control technology. Different control strategies at various levels are compared and their application scenarios, advantages and disadvantages are also analyzed. The current research progress and challenges are summarized at the end of this article.

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“…120 Shen et al also suggested a hybrid ESS for a DC micro-grid system for electric vehicle charging station. 121 The hybrid ESS comprised of a flywheel and a lithium iron phosphate battery. However, real-time extensive research is further required on the integration of ESS in SG and optimization of their key performance parameters.…”

Section: Integration Of Renewable Energy Sources and Storage Systemmentioning

confidence: 99%

“…Aktas et al proposed a hybrid ESS consisting of battery bank and ultra‐capacitor unit to ensure high power density ability during sudden fluctuation of energy demand 120 . Shen et al also suggested a hybrid ESS for a DC micro‐grid system for electric vehicle charging station 121 . The hybrid ESS comprised of a flywheel and a lithium iron phosphate battery.…”

Section: Integration Of Renewable Energy Sources and Storage System Imentioning

confidence: 99%

Progress on the demand side management in smart grid and optimization approaches

et al. 2020

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The integration of demand side management (DSM) with smart grid (SG) can facilitate residents' transfer into smart homes and sustainable cities by reducing the carbon emission. This manuscript reviews the recent works related to the application of DSM in SG through discussing the techniques and algorithms and their associated challenges for effective implementation. This paper also critically discusses the operation mode of DSM, the profile of energy production, storage and consumption, and finally the benefit obtained by the DSM implementation. Previous literature suggested that DSM practice reduced peak-to-average ratio, energy cost and carbon emission by approximately 10% to 65%, 5% to 50%, and 14%, respectively. The implementation of DSM in SG deals with a number of challenges such as security and privacy, tariff regulation, energy transmission, distribution, and effective utilization of energy resources. A number of international organizations have taken various measures and solutions to guarantee the security and privacy of the DSM in SG discussed. So far, a number of algorithms have been used as optimization approach to solve the DSM optimization problems; however hybrid algorithms have showed better performance than single algorithms due to their faster convergence speed. At the end, the paper presents the research gaps and future research directions.

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Hierarchical control of DC micro-grid for photovoltaic EV charging station based on flywheel and battery energy storage system

Cited by 66 publications

References 13 publications

Capacity coordination planning of isolated microgrid and battery swapping station based on the quantum behavior particle swarm optimization algorithm

Capacity coordination planning of isolated microgrid and battery swapping station based on the quantum behavior particle swarm optimization algorithm

Review of Control Strategies for DC Nano-Grid

Progress on the demand side management in smart grid and optimization approaches

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