2017
DOI: 10.1049/oap-cired.2017.0994
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Aggregation model for curtailable generation and sheddable loads

Abstract: This study shows modelling developed during the first year of the SmartNet project. In particular, it presents a mathematical model for aggregation of curtailable generation and sheddable loads. The model determines the quantity and the cost of the flexibility provided by the flexible resources based on their physical and dynamic behaviours. The model also proposes a bidding strategy in order to translate the aggregated behaviour into market bids. 2 Flexibility intervals 2.1 Flexibility of a single device 2.1.… Show more

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Cited by 2 publications
(2 citation statements)
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“…dimmable lights) can be curtailed without rebound effects. In this case, a conventional bidding strategy can be adopted, without the necessity of specifying logical constraints and rebound information [19]. particular, having considered the free-of-cost reactive power flexibility, its optimal management allows the solution of a significant portion of distribution network problems (especially voltage issues) even in CSs with marginal DSO market involvement.…”
Section: Curtailable Generators and Loadsmentioning
confidence: 99%
“…dimmable lights) can be curtailed without rebound effects. In this case, a conventional bidding strategy can be adopted, without the necessity of specifying logical constraints and rebound information [19]. particular, having considered the free-of-cost reactive power flexibility, its optimal management allows the solution of a significant portion of distribution network problems (especially voltage issues) even in CSs with marginal DSO market involvement.…”
Section: Curtailable Generators and Loadsmentioning
confidence: 99%
“…The solution provided by the simulator yields electricity nodal prices and dispatch volumes for participating DERs over thousands of nodes. The focus of this paper is on the design and implementation of one of the aggregation models, the Curtailable Generator / Curtailable Load (CGCL) aggregator (Marthinsen et al, 2017). This paper outlines the design of such a software aggregator agent, and discusses the lessons learned from simulating a more realistic large power grid system.…”
Section: Introductionmentioning
confidence: 99%