A two-stage management strategy for the optimal operation and billing in an energy community with collective self-consumption

Mustika, Alyssa Diva; Rigo‐Mariani, Rémy; Debusschere, Vincent; Pachurka, Amaury

doi:10.1016/j.apenergy.2021.118484

Cited by 43 publications

(6 citation statements)

References 23 publications

(44 reference statements)

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“…Karimiafshar et al [6] used Lyapunov optimization techniques to dispatch the users' requests among the nearby fog nodes and remote DCs, increasing the on-site solar energy consumption. This type of multiparticipant oriented renewable energy consumption is known as collaborative self-consumption [26].…”

Section: B Energy Aware Optimizationsmentioning

confidence: 99%

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

Gnibga,

Blavette,

Orgerie

2023

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)

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Edge Computing has emerged from the Cloud to tackle the increasingly stringent latency, reliability and scalability imperatives of modern applications, mainly in the Internet of Things arena. To this end, the data centers are pushed to the edge of the network to diversify and bring the services closer to the users. This spatial distribution offer a wide range of opportunities for allowing self-consumption from local renewable energy sources with regard to the local weather conditions. However, scheduling the users' tasks so as to meet the service restrictions while consuming the most renewable energy and reducing the carbon footprint remains a challenge. In this paper, we design a nationwide Edge infrastructure, and study its behavior under three typical electrical configurations including solar power plant, batteries and the grid. Then, we study a set of techniques that collaboratively allocates resources on the edge data centers to harvest renewable energy and reduce the environmental impact. These strategies also includes energy efficiency optimization by means of reasonable quality of service degradation and consolidation techniques at each data center in order to reduce the need for brown energy. The simulation results show that combining these techniques allows to increase the selfconsumption of the platform by 7.83% and to reduce the carbon footprint by 35.7% compared to the baseline algorithm. The optimizations also outperform classical energy-aware resource management algorithms from the literature. Yet, these techniques do not equally contribute to these performances, consolidation being the most efficient.

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Section: B Energy Aware Optimizationsmentioning

confidence: 99%

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

Gnibga,

Blavette,

Orgerie

2023

2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)

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show abstract

“…Rule-based battery control strategy compared with an optimization-based battery control can lead to a lower cost for prosumer both in the case of shared battery storage [18] and in the case of an energy communities involving decentralized storage system [19].…”

Section: Literature Reviewmentioning

confidence: 99%

A New Smart Batteries Management for Renewable Energy Communities

Pasqui¹,

Felice²,

Messagie³

et al. 2022

SSRN Journal

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“…Indeed, a mix of social, economic, technical and environmental motivations are triggered [16]. However, savings are shown on the overall community bill compared to the scenario in which members are not organized as a community [17]. Community planning and capacity, environmental protection, grid access and payment-based are the four main categories of governmental measures created to assist community energy [18].…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses

et al. 2023

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A two-stage management strategy for the optimal operation and billing in an energy community with collective self-consumption

Cited by 43 publications

References 23 publications

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

Latency, Energy and Carbon Aware Collaborative Resource Allocation with Consolidation and QoS Degradation Strategies in Edge Computing

A New Smart Batteries Management for Renewable Energy Communities

Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses

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