Ηράκλειτος ΙΙ Πανεπιστήμιο Θεσσαλίας Τμήμα Μηχανικών Η/Υ και Δικτύων

Παρουσίαση με θέμα: "Ηράκλειτος ΙΙ Πανεπιστήμιο Θεσσαλίας Τμήμα Μηχανικών Η/Υ και Δικτύων"— Μεταγράφημα παρουσίασης:

1 Ηράκλειτος ΙΙ Πανεπιστήμιο Θεσσαλίας Τμήμα Μηχανικών Η/Υ και Δικτύων
Ημερίδα Παρουσίασης της Ερευνητικής Θεματολογίας και της Προόδου των Διδακτορικών Διατριβών των Υποψήφιων Διδακτόρων Υποψήφιος Διδάκτορας Γκατζίκης Λάζαρος Τεχνικές βελτιστοποίησης και θεωρίας παιγνίων σε αυτόνομα συνεργατικά δίκτυα Παρασκευή 9 Νοεμβρίου 2012 Aμφιθέατρο «Σαράτση» Επιβλέποντες Καθηγητές: Λέανδρος Τασιούλας (UTH,GR) Ιορδάνης Κουτσόπουλος (UTH, GR) Slawomir Stanczak (TUB, GER) 11/19/2018

2 Electricity Market Generators: facilities that generate electricity from renewable and non-renewable resources Transmission: transports high voltage electricity around the country Distribution: transfers the electricity through local ‘wires’ to homes and businesses

3 How does wholesale market work?
Day ahead market predict consumption of the following day auction to meet demand: generators make energy/price bids all accepted offers paid at market clearing price Real time spot market whenever actual demand exceeds prediction usually at a higher cost What about retail prices?

4 Flat pricing vs. demand response
Time of use pricing (static) 2 to 3 price levels for different periods of the day Objective: balance demand stability of electricity network reduced generation cost reduced electricity bill (user side) Real time pricing (day by day) enabled by smart meters motivates demand shifting Brings electricity and communication networks closer

5 The proposed DR market model

6 A realistic model for residential DR
Demands arrival/end time (a,e) deadline(d) consumption requirement (w) of different elasticity (θ) User objective: for given day ahead prices Control δ: time shift vector (separable per appliance) Comfort Payment

7 Price setting strategy
Operator objective: find the pricing strategy p that minimizes electricity generation cost c c( ): convex function of the total demand within a timeslot Optimal scheduling: find the most balanced demand distribution vector (NP-Hard) Lack of elasticity information at the operator side Waterfilling inspired approach increase price at peak consumption periods reduce at the off peak periods

8 Total demand

9 Who is going to enable DR?
An intermediate is required, due to: the sheer number of home users (scalability) the utility operator lacks DR knowhow each home generates tiny demand limited negotiation power Role of the aggregator installation of the smart meters at the homes provide incentives to users to shift demands resell DR services to the operator Objectives Operator: minimize cost (including DR payment) Competing Aggregators: maximize net benefit (income–payment) Users: maximize net utility 11/19/2018 Πανεπιστήμιο Θεσσαλίας 2012

10 Low level market: Aggregators provide incentives to home users
Market structure Low level market: Aggregators provide incentives to home users 11/19/2018 Πανεπιστήμιο Θεσσαλίας 2012

11 Upper level game: competing aggregators sell DR services
Market structure Upper level game: competing aggregators sell DR services 11/19/2018 Πανεπιστήμιο Θεσσαλίας 2012

12 Publications L. Gkatzikis and I. Koutsopoulos “Online Task Migration in Mobile Cloud Computing Environments” (under review) L. Gkatzikis, I. Koutsopoulos and T. Salonidis “An Optimization Framework for Hierarchical Smart Grid Markets” (under review) L. Gkatzikis, T. Salonidis, N. Hegde and L. Massoulie “Electricity Markets Meet the Home through Demand Response” IEEE Conference on Decision and Control (CDC) 2012, Maui, Hawai. L. Gkatzikis, T. Tryfonopoulos and I. Koutsopoulos “An Efficient Probing Mechanism for Next Generation Mobile Broadband Systems”, Proceedings of IEEE Wireless Communications and Networking Conference (WCNC) 2012, Paris, France. V. Sourlas, P. Flegkas, L. Gkatzikis and L. Tassiulas, “Autonomic Cache Management in Information- Centric Networks”, Proceedings of 13th IEEE/IFIP Network Operations and Management Symposium (NOMS) 2012, Hawaii, USA. L. Gkatzikis, G.S. Paschos and I. Koutsopoulos, “Medium Access Games: The impact of energy constraints”, Proceedings of NETGCOOP, Paris, France,2011. V. Sourlas, L. Gkatzikis and L. Tassiulas, “On-Line Storage Management with Distributed Decision Making for Content-Centric Networks" Proceedings of 7th Conference on Next Generation Internet (NGI) 2011, Kaiserslautern, Germany. L. Gkatzikis and I. Koutsopoulos “Low Complexity Algorithms for Relay Selection and Power Control in Interference-Limited Environments”, Proceedings of WiOpt, 2010, Avignon, France. I. Koutsopoulos, L. Tassiulas and L. Gkatzikis, “Client and Server Games in Peer-to-Peer Networks”, Proceedings of IEEE International Workshop on QoS (IWQoS), 2009, Charleston, SC, USA.