Decentralized control of units in smart grids for the support of renewable energy supply

Sonnenschein, Michael; Lünsdorf, Ontje; Bremer, Jörg; Tröschel, Martin

doi:10.1016/j.eiar.2014.08.004

Cited by 32 publications

(13 citation statements)

References 6 publications

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“…As opposed to the traditional static type, dynamic VPPs -also referred to as clusters -cooperate only temporarily referring both to the actual situation at the market and to the prognosis of the expected feed-in from the participating units. The dynamic VPP is reformed each time after the delivery of a product [8].…”

Section: A Definitionmentioning

confidence: 99%

“…A smart grid can be defined as an "electricity network that can cost efficiently integrate the behavior and actions of all users connected to itgenerators, consumers and those that do both -…" [8]. Therefore, it increases the potential for accurately monitoring the demand and production profiles of its connected units.…”

Section: A Technicalmentioning

confidence: 99%

“…On the transmission level, TSOs are challenged to maintain an instantaneous balance between supply and demand, which is a prerequisite for reliable system operation and to avoid black-outs [7]. On the distribution system level, network congestion and voltage control problems may occur [8].…”

Section: Introductionmentioning

confidence: 99%

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Virtual power plants: Definition, applications and barriers to the implementation in the distribution system

Plancke

Vos

Belmans

et al. 2015

2015 12th International Conference on the European Energy Market (EEM)

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A virtual power plant assists in the integration of distributed energy resources in the power system. With a rising share of distributed generation, an active management of distributed energy resources is indispensable in order to ensure operation of the electricity network towards the future. In this paper, the virtual power plant concept is analyzed. Three essential components that characterize a virtual power plant are distinguished, followed by a comprehensive overview of the services they can deliver in today's liberalized markets in Europe. It is found that a combination of technical, economic and regulatory barriers still hamper a widespread implementation of the concept. In addition, specific regulatory barriers are identified that hinder a virtual power plant in providing certain services. Hence, it is advised that primarily product and service definitions, as well as market mechanisms, are reviewed.

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Section: A Definitionmentioning

confidence: 99%

Section: A Technicalmentioning

confidence: 99%

See 1 more Smart Citation

Virtual power plants: Definition, applications and barriers to the implementation in the distribution system

Plancke

Vos

Belmans

et al. 2015

2015 12th International Conference on the European Energy Market (EEM)

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“…RES interaction and load power management is a key issue to address. In order to develop an efficient and reliable power infrastructure, the interaction among RES subsystems, Energy Storage Systems (ESS) and local power loads have been more properly managed [5][6][7][8]. A data exchange should be foreseen to identify and manage alarms, warning and faults on the smart grid.…”

Section: Introductionmentioning

confidence: 99%

Optimal energy management of smart grids with plug-in hybrid electric vehicles

Caruso

Boscaino

Miceli

et al. 2015

2015 International Conference on Renewable Energy Research and Applications (ICRERA)

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In this paper, smart grids based on Renewable Energy Sources are addressed. An Italian case study which has been developed in the frame of the research project i-NEXT (Innovation for green Energy and eXchange in Transportation) is presented. Storage elements are included. Electric and fuel cell powered vehicles' charging stations are here included as local loads. In this paper, power management algorithms and the control logic are described. The control subsystem aims at an efficient management of the involved renewable energy sources avoiding faults in the power system and ensuring a fully functional supply of local loads. A "Service Center" software collecting data from renewable sources, developing the control strategy and applying the strategy to each renewable source is implemented. The Italian case study and the control algorithms are described and discussed. This paper aims at promoting a suitable solution for the power management of RES-based smart grids.

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“…A usual use case commonly emerging within VPP control is the need for scheduling the operation of participating DER. Predictive scheduling [7] describes the optimization problem for day-ahead planning of energy generation in VPPs, where the goal is to select a schedule for each energy unit -from an individual search space of feasible schedules with respect to a future planning horizon -such that a global objective function (e. g. resembling a target power profile for the VPP as close as possible) is optimized.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity in Multi-Ensemble Scheduling

Bremer

Lehnhoff

2018

Proceedings of the 2018 Federated Conference on Computer Science and Information Systems

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Future smart grid control demands delegation of liabilities to distributed, rather small energy resources in contrast to today's traditional large control power units. Distributed energy scheduling constitutes a complex task for optimization algorithms regarding the underlying high-dimensional, multimodal and nonlinear problem structure. For predictive scheduling with high penetration of renewable energy resources, agent-based approaches using classifier-based decoders for modeling individual flexibilities have shown good performance. On the other hand, such decoder-based methods are currently designed for single entities and not able to cope with ensembles of energy resources. Aggregating training sets sampled from individually modeled energy units results in folded distributions with unfavorable properties for training a decoder. Nevertheless, this happens to be a quite frequent use case, e. g. when a hotel, a small business, a school or similar with an ensemble of co-generation, heat pump, solar power, and controllable consumers wants to take part in decentralized predictive scheduling. Recently, an extension to an established agent approach for scheduling individual single energy units has been proposed that is based on second level optimization. The agents' decision routine may be enhanced by a covariance matrix adaption evolution strategy that is hybridized with decoders. In this way, locally managed ensembles of energy units can be included. The applicability has already been demonstrated, but the effects of ensemble composition are so far unknown. Here, we give an widened view on the underlying power level distribution problem and extend the results by conducting a sensitivity analysis on the impact of ensemble size and penetration on communication overhead and residual error.

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Decentralized control of units in smart grids for the support of renewable energy supply

Cited by 32 publications

References 6 publications

Virtual power plants: Definition, applications and barriers to the implementation in the distribution system

Virtual power plants: Definition, applications and barriers to the implementation in the distribution system

Optimal energy management of smart grids with plug-in hybrid electric vehicles

Sensitivity in Multi-Ensemble Scheduling

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