Multi agent system for cooperative energy management in microgrids

Mangiatordi, Federica; Pallotti, Emiliano; Panzieri, Diego; Capodiferro, Licia

doi:10.1109/eeeic.2016.7555822

Cited by 17 publications

(15 citation statements)

References 8 publications

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“…This leads to increased computational burden compared to a fully decentralised scheme such as SwarmGrid‐X and introduces a single point of failures, at least for subparts of the system. Similar considerations apply for concepts in which community cells [6] or microgrids [25] are used as smallest control units and a hierarchical control scheme is formed by clustering of these units.…”

Section: Related Researchmentioning

confidence: 98%

Swarm‐based automation of electrical power distribution and transmission system support

Dähling

Kolen

Monti

2018

IET cyber-phys. syst.

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Section: Related Researchmentioning

confidence: 98%

Swarm‐based automation of electrical power distribution and transmission system support

Dähling

Kolen

Monti

2018

IET cyber-phys. syst.

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“…The electrical grid is the physical environment of the agents and is coupled with the MAP. Popular MAPs for the multi-agent system (MAS) implementation are JADE [8][9][10]12] and NetLOGO [11]. While JADE works well for small system sizes, it is known to have scalability issues [15].…”

Section: Related Workmentioning

confidence: 99%

“…The interface must induce only a minimal latency and computational load. Either, custom interfaces for specific combinations of simulators and MAPs can be developed as in [8][9][10][11][12], or a generic abstract interface can be used such as the opensource VILLASnode library [16]. It is designed for fast forwarding of data vectors that are optionally translated from one communication protocol to another.…”

Section: Related Workmentioning

confidence: 99%

Scalable assessment method for agent‐based control in cyber‐physical distribution grids

Happ

Dähling

Monti

2020

IET cyber-phys. syst.

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This study proposes a scalable method to assess agent-based control concepts and deployment systems for cyberphysical electrical distribution grids. The deployment system of an agent-based control concept is the system that executes the agents and their interactions in a real implementation. Due to the increasing number of controllable loads, generators, and storage systems installed in distribution grids, scalability of control concepts and deployment systems plays a key role. Hence, the assessment method for both has to be scalable itself. For this reason, the proposed method bases on DistAIX, an opensource scalable simulation tool for cyber-physical distribution grids designed for execution on distributed computing clusters. DistAIX is extended with an interface for coupling with the deployment system of the agent-based control approach. The performance of the proposed method is evaluated for an agent-based control concept called SwarmGrid-X and the deployment system cloneMAP. The results demonstrate the feasibility of the proposed method and exemplify the functionality and scalability of SwarmGrid-X and cloneMAP.

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“…Related works in the literature include [3][4][5][6], where greedy RE management strategies are proposed at an individual level. Cooperative RE management strategies have been proposed in [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. However, most of these strategies do not take into consideration electricity price variations across time and location, as well as the energy loss incurred by power lines connecting RE generators and loads.…”

Section: Introductionmentioning

confidence: 99%

“…This result motivates the clustering of households to avoid the deployment of some of the connecting wires in the network. Transmission line power losses have been accounted for in works such as [11] and [23]. However, these works either disregard the time-varying nature of the electricity prices, or do not account for the losses incurred in the operation of ESDs charged with RE.…”

Section: Introductionmentioning

confidence: 99%

Price-aware Renewable Energy Management with Transmission Losses

Leithon

Werner

Koivunen

et al. 2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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In this paper we propose a genie-aided strategy to optimize the use of renewable energy (RE) in a community of households with shared access to storage and RE generation facilities. The households are spread over a limited geographical area, and are subject to different time-varying power consumption profiles, and energy prices. We consider a finite number of RE generators and energy storage devices (ESDs), which are deployed in specific locations. The proposed strategy seeks to minimize the energy cost incurred by the participating households by optimizing the rate at which RE is consumed over time. Our model takes into account the power loss incurred in the transmission of energy from the generators to the loads. The optimization problem is cast as a non-convex quadratically constrained quadratic program, which is simplified in order to derive an approximate solution. Numerical results show that transmission losses and differences across price and load can significantly affect the optimal RE allocation among the households. The proposed strategy offers valuable insights for energy planning purposes and can be used to devise real-time RE management algorithms by incorporating the necessary forecasting techniques.

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Multi agent system for cooperative energy management in microgrids

Cited by 17 publications

References 8 publications

Swarm‐based automation of electrical power distribution and transmission system support

Swarm‐based automation of electrical power distribution and transmission system support

Scalable assessment method for agent‐based control in cyber‐physical distribution grids

Price-aware Renewable Energy Management with Transmission Losses

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