Hybrid Battery-SC and Battery-Battery Multistage Design and Energy Management for Power Sharing

Jan, Khadim Ullah; Dubois, A.

doi:10.1109/iecon48115.2021.9589603

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Although batteries are an excellent choice to meet the demand of sudden fluctuations, they have challenges, such as fast response. They cannot handle high ramp power because their lower energy density affects their life span [12]. Supercapacitors provide a possible solution.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Supercapacitors in Renewable Energy Systems for Managing Power Fluctuations

Mbendane,

Abe,

Richards

2024

International Journal of Energy Research

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Environmental decarbonization drives the world to find better ways to generate and store energy. Sustainable energy in the form of solar and wind is explored with the use of conventional energy storage systems (batteries) to close the gap. Green energy generation is weather-dependent, leading to power output fluctuations, and the short-term variability in irradiance adversely affects the system’s energy output and reliability. Standalone operation of a generating system necessitates a storage energy unit that manages transient loading and effectively shares power between the load and energy storage. This article presents an approach to managing energy fluctuations when renewable energy sources fluctuate, this occurs when short-term variability in irradiance, and transient loading occurs. The approach uses supercapacitors as a short-term energy storage solution. The proposed configuration has the following key advantages: effective power sharing, rapid charge, and discharge cycles in supercapacitors result in voltage restoration under transient conditions. The performance of the system is confirmed in MATLAB/Simulink. The proposed study confirms that integrating supercapacitors with PV systems does provide significant power oscillation management when sudden variations occur in renewable sources. A practical test was performed using smaller components following the same concept, and the results supported the hypothesis. The results show that the output voltage is managed when oscillation in irradiance occurs. This is seen in the simulation without supercapacitors when the output voltage fluctuates between 100 and 450 V within the first second of the simulation; however, with the introduction of SC, the voltage becomes stable and maintains an output of 620 V within 0.02 seconds. This is further supported by the experimental outcomes where almost 50% of the solar panel is covered and the output voltage is maintained.

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Section: Introductionmentioning

confidence: 99%

Analysis of Supercapacitors in Renewable Energy Systems for Managing Power Fluctuations

Mbendane,

Abe,

Richards

2024

International Journal of Energy Research

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“…The proposed strategy can reduce energy loss and improve battery life. Jan et al [11] designed and simulated a two−stage hybrid structure of a battery supercapacitor (SC). An easy−to−implement control algorithm based on the decision was adopted to share the power delivery capacity of the hybrid battery supercapacitor in proportion, effectively dealing with light load changes and realizing economic advantages in the industry.…”

Section: Introductionmentioning

confidence: 99%

Power Battery Scheduling Optimization Based on Double DQN Algorithm with Constraints

Xiong

Chen

Song³

et al. 2023

Applied Sciences

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Power battery scheduling optimization can improve the service life of the battery, but the existing heuristic algorithm has poor adaptability, and the capacity fluctuates significantly in the cycle aging process, which makes it easy to fall into the local optimal. To overcome these problems, we take the battery cycle life maximization as the goal, propose a reinforcement learning scheduling optimization model with temperature and internal resistance difference constraints, so as to determine whether to charge or discharge during battery cycle aging. We do this using the deep−learning−based battery capacity estimation model as the learning environment for the agent, using the Double DQN algorithm to train the agent, and proposing the principal component analysis method to reduce the dimension of the state space. These experiments, using multiple publicly available battery aging data sets, show that the principal component analysis method and the constraint functions reduce the computational time to find the optimal solution, providing the possibility of obtaining larger reward values. Meanwhile, the trained model effectively extends the cycle life of the battery, and has good adaptivity. It can automatically adjust parameters with the battery aging process to develop optimal charging and discharging protocols for power batteries with different chemical compositions.

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Hybrid battery-supercapacitor energy storage for enhanced voltage stability in DC microgrids using autonomous control strategy

Khan

Atif

Khalid

2023

Emerging Trends in Energy Storage Systems and Industrial Applications

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Hybrid Battery-SC and Battery-Battery Multistage Design and Energy Management for Power Sharing

Cited by 4 publications

References 26 publications

Analysis of Supercapacitors in Renewable Energy Systems for Managing Power Fluctuations

Analysis of Supercapacitors in Renewable Energy Systems for Managing Power Fluctuations

Power Battery Scheduling Optimization Based on Double DQN Algorithm with Constraints

Hybrid battery-supercapacitor energy storage for enhanced voltage stability in DC microgrids using autonomous control strategy

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