Prosumer clustering into virtual microgrids for cost reduction in renewable energy trading markets

[1]  Ujjwal Maulik,et al.  Genetic algorithm-based clustering technique , 2000, Pattern Recognit..

[2]  Frede Hvelplund.  Renewable energy and the need for local energy markets , 2006 .

[3]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[4]  Shi You,et al.  A market-based Virtual Power Plant , 2009, 2009 International Conference on Clean Electrical Power.

[5]  Anna Pinnarelli,et al.  Operation of decentralized electricity markets in microgrids , 2009 .

[6]  Marina Thottan,et al.  A two-stage market model for microgrid power transactions via aggregators , 2011, Bell Labs Technical Journal.

[7]  P. Varaiya,et al.  Bringing Wind Energy to Market , 2012, IEEE Transactions on Power Systems.

[8]  Javier Del Ser,et al.  A new grouping genetic algorithm for clustering problems , 2012, Expert Syst. Appl..

[9]  Stamatis Karnouskos,et al.  An energy market for trading electricity in smart grid neighbourhoods , 2012, 2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST).

[10]  Jarosław Milewski,et al.  Virtual Power Plants - general review : structure, application and optimization , 2012 .

[11]  Lazaros Gkatzikis,et al.  The Role of Aggregators in Smart Grid Demand Response Markets , 2013, IEEE Journal on Selected Areas in Communications.

[12]  Henrik Madsen,et al.  A bilevel model for electricity retailers' participation in a demand response market environment , 2013 .

[13]  Phuong H. Nguyen,et al.  Local electricity market design for the coordination of distributed energy resources at district level , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[14]  Stamatis Karnouskos,et al.  The Impact of Smart Grid Prosumer Grouping on Forecasting Accuracy and Its Benefits for Local Electricity Market Trading , 2014, IEEE Transactions on Smart Grid.

[15]  Alexandra Purkus,et al.  Market integration of renewable energies through direct marketing - lessons learned from the German market premium scheme , 2015 .

[16]  Matti Lehtonen,et al.  A market-oriented hierarchical framework for residential demand response , 2015 .

[17]  Emmanouel A. Varvarigos,et al.  A virtual microgrid platform for the efficient orchestration of multiple energy prosumers , 2015, Panhellenic Conference on Informatics.

[18]  Asgeir Tomasgard,et al.  Prosumer bidding and scheduling in electricity markets , 2016 .

[19]  Suryanarayana Doolla,et al.  Multi-agent based Demand Response management system for combined operation of smart microgrids , 2016 .