A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids

Martínez, Doris Adriana Villota; Mojica‐Nava, Eduardo; Al-Sumaiti, Ameena Saad; Rivera, Sergio

doi:10.1109/access.2020.3002713

Cited by 8 publications

(2 citation statements)

References 30 publications

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“…Mutual information has gained special attention in recent years in areas such as multi-agent systems [ 17 ], coverage control [ 18 , 19 ], distributed control in micro-grids [ 20 ], and neuroscience [ 15 , 21 ] due to its capability to analyze relationships between data from different contexts (e.g., voltage values, stimulus light position, animal position), the ability to detect linear and nonlinear interactions, and its usage in multivariate systems.…”

Section: Methodsmentioning

confidence: 99%

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions

Martínez Vásquez,

Posada-Quintero,

Rivera Pinzón

2023

Behavioral Sciences

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Sleep deprivation, a widespread phenomenon that affects one-third of normal American adults, induces adverse changes in physical and cognitive performance, which in turn increases the occurrence of accidents. Sleep deprivation is known to increase resting blood pressure and decrease muscle sympathetic nerve activity. Monitoring changes in the interplay between the central and autonomic sympathetic nervous system can be a potential indicator of human’s readiness to perform tasks that involve a certain level of cognitive load (e.g., driving). The electroencephalogram (EEG) is the standard to assess the brain’s activity. The electrodermal activity (EDA) is a reflection of the general state of arousal regulated by the activation of the sympathetic nervous system through sweat gland stimulation. In this work, we calculated the mutual information between EDA and EEG recordings in order to consider linear and non-linear interactions and provide an insight of the relationship between brain activity and peripheral autonomic sympathetic activity. We analyzed EEG and EDA data from ten participants performing four cognitive tasks every two hours during 24 h (12 trials). We decomposed EEG data into delta, theta, alpha, beta, and gamma spectral components, and EDA into tonic and phasic components. The results demonstrate high values of mutual information between the EDA and delta component of EEG, mainly in working memory tasks. Additionally, we found an increase in the theta component of EEG in the presence of fatigue caused by sleep deprivation, the alpha component in tasks demanding inhibition and attention, and the delta component in working memory tasks. In terms of the location of brain activity, most of the tasks report high mutual information in frontal regions in the initial trials, with a trend to decrease and become uniform for all the nine analyzed EEG channels as a consequence of the sleep deprivation effect. Our results evidence the interplay between central and sympathetic nervous activity and can be used to mitigate the consequences of sleep deprivation.

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Section: Methodsmentioning

confidence: 99%

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions

Martínez Vásquez,

Posada-Quintero,

Rivera Pinzón

2023

Behavioral Sciences

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“…Ma and Zhang [17] applied an adaptive hierarchical control strategy considering grid stability as a constraint while minimizing the power generation costs in a microgrid with multiple prosumers. Martinez et al [18] proposed a learning-based management approach for a microgrid with competitive agents (i.e., each representing a distributed flexible asset), which improves voltage quality via reactive power-sharing between distributed generators. These studies showed that various control approaches exist to improve power quality in systems similar to LECs.…”

Section: Related Workmentioning

confidence: 99%

Impacts of Local Energy Exchange in Low Voltage Communities: A German Case Study

Wege,

Gümrükcü,

Wortberg

et al. 2023

IEEE Access

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Local Energy Communities (LECs) provide a framework for community-oriented use of prosumer-owned renewable generation and storage units. For LECs to gain acceptance and eventually become widespread actors in future energy systems, their impacts on the grid and its participants must be investigated. However, the scientific landscape lacks sufficient quantitative analyses that specifically investigate the effects of LECs on the underlying grid infrastructure. This work conducts a case study to understand the system effects that may arise from the local cooperation of prosumers in future low voltage systems in Germany. To analyze these effects, performance metrics are defined, which help to compare the energy neutrality and grid reliability of low voltage (LV) grids with and without local energy exchanges. Furthermore, representative test grids are synthesized by considering the existing (2020) and predicted future (2030) distribution of energy assets, such as photovoltaics, battery storage, electrical heat pumps, and electric vehicles in Germany. For these grids, simulations considering different scenarios, including both the reference and community behavior of their participants, are conducted, and the defined performance metrics are applied. The simulations show that the LEC provides significant benefits in terms of energy neutrality and grid reliability. In this way, this study complements ongoing efforts in the design of LECs and incentives for customers, for example, in the form of favorable tariffs for locally generated energy.

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A novel approach for optimal power scheduling of distributed energy resources in microgrids

Askarzadeh

Gharibi

2021

Soft Comput

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A Distortion-Based Potential Game for Secondary Voltage Control in Micro-Grids

Cited by 8 publications

References 30 publications

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions

Impacts of Local Energy Exchange in Low Voltage Communities: A German Case Study

A novel approach for optimal power scheduling of distributed energy resources in microgrids

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