The Impact of Smart Grid Prosumer Grouping on Forecasting Accuracy and Its Benefits for Local Electricity Market Trading

IEEE Transactions on Smart Grid

Volumn 5, Issue 1, 2014, Pages 402-410

  Goncalves Da Silva, Per ^a   Ilic, Dejan ^a   Karnouskos, Stamatis ^a  

^a SAP RESEARCH   (Germany)

Author keywords

Autonomous agents; demand forecasting; energy management; renewable energy resources; smart grids

Indexed keywords

DEMAND FORECASTING; DISTRIBUTED GENERATION RESOURCES; ELECTRICITY MARKET; FORECAST ACCURACY; FORECASTING ACCURACY; FORECASTING ERROR; OPPORTUNITY COSTS; SMART GRID;

AUTONOMOUS AGENTS; DISTRIBUTED POWER GENERATION; ELECTRIC INDUSTRY; ENERGY MANAGEMENT; ERRORS; FORECASTING; RENEWABLE ENERGY RESOURCES; SMART POWER GRIDS;

COMMERCE;

EID: 84892604177     PISSN: 19493053     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSG.2013.2278868     Document Type: Article

References (23)

1. X. Yu, C. Cecati, T. Dillon, andM. Simões, "The new frontier of smart grids," IEEE Ind. Electron. Mag., vol. 5, no. 3, pp. 49-63, Sep. 2011.
2. S. Karnouskos, "Demand side management via prosumer interactions in a smart city energy marketplace," in IEEE Int. Conf. Innov. Smart Grid Technol. (ISGT 2011), Manchester, U.K., Dec. 5-7, 2011.
3. J. K. Kok,M. J. J. Scheepers, and I. G. Kamphuis, "Intelligence in electricity networks for embedding renewables and distributed generation," in Intelligent Infrastructures, ser. Intelligent Systems, Control and Automation: Science and Engineering, R. R. Negenborn, Z. Lukszo, and H.Hellendoorn, Eds. Delft, TheNetherlands: Springer, 2010, vol. 42, pp. 179-209.
4. C. Julian and J. Dobson, "Re-energising our communities: Transforming the energy market through local energy production," in ResPublica Green Paper, Feb. 2012 [Online]. Available: http://www.respublica. org.uk
5. F. Hvelplund, "Renewable energy and the need for local energy markets," Energy, vol. 31, no. 13, pp. 2293-2302, 2006.
6. N. Hatziargyriou, A. Dimeas, A. Tsikalakis, J. Lopes, G. Karniotakis, and J. Oyarzabal, "Management of microgrids inmarket environment," in Proc. 2005 Int. Conf. Future Power Syst.
7. D. Menniti, A. Pinnarelli, and N. Sorrentino, "Operation of decentralized electricity markets in microgrids," in Proc. 20th Int. Conf. Exh. Electr. Distrib. Part 1 (CIRED 2009), pp. 1-4.
8. D. Ilic, P. Goncalves Da Silva, S.Karnouskos, andM. Griesemer, "An energy market for trading electricity in smart grid neighbourhoods," in Proc. 6th IEEE Int. Conf. Digit. Ecosyst. Technol.-Complex Environ. Eng. (IEEE DEST-CEE), Campione d'Italia, Italy, Jun. 2012.
9. European Commission, "SmartGrids SRA 2035-Strategic research agenda: Update of the SmartGrids SRA 2007 for the needs by the year 2035," European Technology Platform SmartGrids, European Commission, Mar. 2012 [Online]. Available: http://www.smartgrids. eu/documents/sra2035.pdf, Tech. Rep.
10. Internet of Energy: ICT for Energy Markets of the Future. Berlin, Germany: Federation of German Industries (BDI), Feb. 2010, BDI publ. 439.
11. V. L. Smith, "An experimental study of competitive market behavior," J. Political Econ., vol. 70, no. 2, pp. 111-137, Apr. 1962.
12. P. Vytelingum, S. D. Ramchurn, T. Voice, A. Rogers, and N. R. Jennings, "Trading agents for the smart electricity grid," in Proc. 9th Int. Conf. Auton. Agents Multiagent Syst. (AAMAS 2010), Toronto, ON, Canada, May 10-14, 2010, pp. 897-904.
13. R. K. Dash, P. Vytelingum, A. Rogers, E. David, and N. R. Jennings, "Market-based task allocation mechanisms for limited-capacity suppliers," Trans. Syst., Man, Cybern. A, vol. 37, no. 3, pp. 391-405, May 2007. (Pubitemid 46621523)
14. S. Lamparter, S. Becher, and J.-G. Fischer, "An agent-based market platform for smart grids," in Proc. 9th Int. Conf. Auton. Agents Multiagent Syst.: Ind. Track (AAMAS '10), Richland, SC, USA, 2010, International Foundation for Autonomous Agents and Multiagent Systems, pp. 1689-1696.
15. P. Goncalves Da Silva, S. Karnouskos, and D. Ilic, "Evaluation of the scalability of an energy market for smart grid neighbourhoods," in Proc. IEEE 11th Int. Conf. Ind. Informatics (INDIN), Bochum, Germany, Jul. 29-31, 2013.
16. D. Ilic, S. Karnouskos, P. Goncalves Da Silva, and M. Jacobi, "Impact assessment of smart meter grouping on the accuracy of forecasting algorithms," in Proc. 28th ACM Symp. Appl. Comput. (SAC), Coimbra, Portugal, Mar. 18-22, 2013.
17. J. W. Taylor, L. M. de Menezes, and P. E. McSharry, "A comparison of univariate methods for forecasting electricity demand up to a day ahead," Int. J. Forecasting, vol. 22, no. 1, pp. 1-16, Jan. 2006. (Pubitemid 43174787)
18. R. J. Hyndman and G. Athanasopoulos, Forecasting: Principles and Practice 2012 [Online]. Available: http://otexts.com/fpp/
19. U. Focken, M. Lange, K. Mönnich, H. Waldl, H. G. Beyer, and A. Luig, "Short-term prediction of the aggregated power output of wind farms-A statistical analysis of the reduction of the prediction error by spatial smoothing effects," J. Wind Eng. Ind. Aerodyn., vol. 90, no. 3, pp. 231-246, 2002. (Pubitemid 34315977)
20. EPIA, "Global market outlook for photovoltaics until 2016," European Photovoltaic Industry Association, Tech. Rep., 2012 [Online]. Available: http://www.iea.org/publications/freepublications/publication/kwes.pdf
21. E. Matallanas, M. Castillo-Cagigal, E. Caama no-Martín, D. Masa-Bote, A. Gutiérrez, and F. Monasterio, "Analysis of the self-consumption possibilities in small grid-connected photovoltaic systems in spain," in Proc. 26th Eur. Photovoltaic Solar Energy Conf., Munich, Germany, 2011, pp. 4619-4624, WIP-Renewable Energies.
22. D. Cliff and J. Bruten, "Less than human: Simple adaptive trading agents for CDA markets," in Computation in Economics, Finance and Engineering: Economic Systems, S. Holly, Ed. Oxford, U.K.: Pergamon, 2000, pp. 117-122.
23. D. Ilic, S. Karnouskos, and P. Goncalves Da Silva, "Improving load forecast in prosumer clusters by varying energy storage size," in Proc. IEEE Grenoble PowerTech 2013, Grenoble, France, Jun. 16-20, 2013.