2016
DOI: 10.1016/j.engappai.2016.02.010
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Self-organising energy demand allocation through canons of distributive justice in a microgrid

Abstract: The energy sector is being driven into a new era where considerable portions of electrical demand will be met through distributed energy resources (DERs). Microgrids have been suggested as a tool for integrating and managing DERs. In this context, we formulate the energy demand allocation problem in order to provide service to a given load. We then propose a dynamic method for agreeing and setting the rules to perform the allocation. The methodology is based on self-organisation and the concept of distributive… Show more

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Cited by 5 publications
(4 citation statements)
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References 17 publications
(25 reference statements)
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“…Such macro-effects are often connected with the ability of the system to be resilient to environmental perturbations (ranging from human in-the-loop effects to faults in physical devices or communications-which are the norm in large-scale distributed systems), or to deal with changing functional/non-functional requirements that have to be satisfied in a wide variety of conditions. Relevant application of self-organization include: study of human social behavior [28], crowd tracking and steering [15], energy demand allocation [29], terrain exploration [30], smart camera coverage [31], task allocation of autonomous vehicles [32], and ICT resources coordination [33].…”
Section: Self-organizationmentioning
confidence: 99%
“…Such macro-effects are often connected with the ability of the system to be resilient to environmental perturbations (ranging from human in-the-loop effects to faults in physical devices or communications-which are the norm in large-scale distributed systems), or to deal with changing functional/non-functional requirements that have to be satisfied in a wide variety of conditions. Relevant application of self-organization include: study of human social behavior [28], crowd tracking and steering [15], energy demand allocation [29], terrain exploration [30], smart camera coverage [31], task allocation of autonomous vehicles [32], and ICT resources coordination [33].…”
Section: Self-organizationmentioning
confidence: 99%
“…Substituting (9) in (21), the coefficient of the proposed SPC -D loop can directly be represented as…”
Section: Selection Of Control Parametersmentioning
confidence: 99%
“…Furthermore, a proportional–integral (PI) controller with optimally computed PI‐parameters according to the state of complex demand has been introduced for maintaining the power density high in a flywheel‐based storage unit [20]. The concept of self‐organising energy demand allocation has been proposed in [21]. In the study, the steady‐state active power demand has been bifurcated among the available distributed energy resources.…”
Section: Introductionmentioning
confidence: 99%
“…Monitoring can carry both physical costs, e.g., energy or CPU cycles, or opportunity costs where the time spent on monitoring is time lost carrying out other productive activities. This is true both in natural systems, such as irrigation systems (Weissing & Ostrom, 2000) and fisheries, and artificial systems such as community clouds (Khan, Freitag & Rodrigues, 2015) or community co-production energy systems (Torrent-Fontbona, López, Busquets & Pitt, 2016). Therefore, if self-interested agents are to be incentivised to monitor rule compliance then they need to be reimbursed for this cost somehow.…”
Section: Illustrating the Role And Benefits Of Value-based Modelsmentioning
confidence: 99%