Distributed Control Strategy of Single-Phase Battery Systems for Compensation of Unbalanced Active Powers in a Three-Phase Four-Wire Microgrid

Pinthurat, Watcharakorn; Hredzak, Branislav

doi:10.3390/en14248287

Cited by 12 publications

(7 citation statements)

References 31 publications

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“…Yet, concerns exist regarding their capacity when a substantial number of RESs and loads are integrated into power systems [20]. Distributed control of single-phase battery systems aimed at balancing active powers at the point of common connection (PCC) was proposed in some studies [21] [22], allowing battery owners to engage in balancing when needed. However, scalability concerns arise when numerous battery systems are integrated into a single bus [22].…”

Section: B Literature Surveymentioning

confidence: 99%

Deep Reinforcement Learning for Alleviation of Unbalanced Active Powers Using Distributed Batteries in LV Residential Distribution System

Pinthurat,

Hredzak

2023

Preprint

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<p>The high penetration and uneven distribution of single-phase rooftop PVs and load demands in power systems may lead to unbalanced active powers, adversely impacting power quality and system reliability. This paper introduces a strategy based on multi-agent deep reinforcement learning to address these unbalanced active powers. The approach involves deploying single-phase battery systems throughout the LV residential distribution system, subsidized by the utility. Initially, the unbalanced active powers are framed as a Markov game, which is then addressed using a multi-agent deep deterministic policy gradient algorithm. The strategy relies on local measurements, with agents' experiences centrally shared during training for cooperative tasks. Notably, information about the phase connections of the battery systems becomes unnecessary. The strategy learns from historical data, gradually mastering the process. Real data from rooftop PVs and demands in a four-wire LV residential distribution system validate the effectiveness of the proposed approach. Acting as adaptive agents, the battery systems collaboratively operate by adjusting active powers to minimize neutral current at the point of common connection.</p>

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Section: B Literature Surveymentioning

confidence: 99%

Deep Reinforcement Learning for Alleviation of Unbalanced Active Powers Using Distributed Batteries in LV Residential Distribution System

Pinthurat,

Hredzak

2023

Preprint

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“…The transition to renewable energy and EV platform linkage are crucial for addressing climate change and must be facilitated on an ongoing basis using innovative digital technologies. Many countries worldwide are using PV energy generation systems to reduce carbon emissions [50][51][52]. Alongside the rapid transition to renewable energy, governments worldwide are striving to move away from fossil fuel systems to forge sustainable development pathways and reduce emissions [39,53,54].…”

Section: Renewable Energy Transformation and Ev Charging Platform For...mentioning

confidence: 99%

Carbon-Neutral ESG Method Based on PV Energy Generation Prediction Model in Buildings for EV Charging Platform

Yoon,

Kim,

Shin

et al. 2023

Buildings

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Energy prediction models and platforms are being developed to achieve carbon-neutral ESG, transition buildings to renewable energy, and supply sustainable energy to EV charging infrastructure. Despite numerous studies on machine learning (ML)-based prediction models for photovoltaic (PV) energy, integrating models with carbon emission analysis and an electric vehicle (EV) charging platform remains challenging. To overcome this, we propose a building-specific long short-term memory (LSTM) prediction model for PV energy supply. This model simulates the integration of EV charging platforms and offer solutions for carbon reduction. Integrating a PV energy prediction model within buildings and EV charging platforms using ICT is crucial to achieve renewable energy transition and carbon neutrality. The ML model uses data from various perspectives to derive operational strategies for energy supply to the grid. Additionally, simulations explore the integration of PV-EV charging infrastructure, EV charging control based on energy, and mechanisms for sharing energy, promoting eco-friendly charging. By comparing carbon emissions from fossil-fuel-based sources with PV energy sources, we analyze the reduction in carbon emission effects, providing a comprehensive understanding of carbon reduction and energy transition through energy prediction. In the future, we aim to secure economic viability in the building energy infrastructure market and establish a carbon-neutral city by providing a stable energy supply to buildings and EV charging infrastructure. Through ongoing research on specialized models tailored to the unique characteristics of energy domains within buildings, we aim to contribute to the resolution of inter-regional energy supply challenges and the achievement of carbon reduction.

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“…It involves the interests of three parties: energy-using enterprises, energy-saving service companies, and power grid companies. Therefore, how to accurately analyze photovoltaic operating losses has become a focus of attention of the three parties [11][12][13]. Domestic and foreign scholars or enterprises have integrated the local monitoring data of photovoltaic power plants, environmental meteorological data of power plants, power plant fault information data, and other related information data, and built a unified information data monitoring and analysis platform, a comprehensive platform for power station operation management, and a data analysis platform based on big data [14,15].…”

Section: Introductionmentioning

confidence: 99%

Energy Loss Analysis of Distributed Rooftop Photovoltaics in Industrial Parks

Li¹,

Huang²,

Tan³

et al. 2023

Energy Engineering

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The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users, energy-saving service companies, and power grid companies, so it has always been the focus of the industry and society in some manner or another. However, the related analysis for an actual case that considers different cooperative corporations' benefits is lacking in the presently available literature. This paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object, studies the analysis and calculation methods of line loss and transformer loss, analyzes the change of transformer loss under different temperatures and different load rates, and compares the data and trend of electricity consumption and power generation in industrial parks before and after the photovoltaic operation. This paper explores and practices the analysis method of the operating loss of distributed photovoltaic power generation and provides an essential reference for the benefit analysis and investment cost estimation of distributed photovoltaic power generation systems in industrial parks. The analyzed results reveal that the change loss is stable after the photovoltaic is connected, and there is no additional transformer loss. And before and after the photovoltaic system installation, there was no significant change in the total monthly data difference between the total meter and the sub-meter.

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Distributed Control Strategy of Single-Phase Battery Systems for Compensation of Unbalanced Active Powers in a Three-Phase Four-Wire Microgrid

Cited by 12 publications

References 31 publications

Deep Reinforcement Learning for Alleviation of Unbalanced Active Powers Using Distributed Batteries in LV Residential Distribution System

Deep Reinforcement Learning for Alleviation of Unbalanced Active Powers Using Distributed Batteries in LV Residential Distribution System

Carbon-Neutral ESG Method Based on PV Energy Generation Prediction Model in Buildings for EV Charging Platform

Energy Loss Analysis of Distributed Rooftop Photovoltaics in Industrial Parks

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