Customized normalization clustering meth-odology for consumers with heterogeneous characteristics

• RIBEIRO, Catarina ^[1] ; PINTO, Tiago ^[2] ; VALE, Zita ^[3] ; BAPTISTA, Jose ^[4]
  1. [1] GECAD - Polytechnic of Porto / UTAD – University of Trás-os-Montes e Alto-Douro
  2. [2] GECAD - Polytechnic of Porto
  3. [3] Polytechnic of Porto
  4. [4] University of Trás-os-Montes e Alto-Douro / CPES - INESCTEC

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• Localización: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, ISSN-e 2255-2863, Vol. 7, Nº. 2, 2018, págs. 53-69
• Idioma: inglés
• DOI: 10.14201/ADCAIJ2018725369
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• Resumen

  • The increasing use and development of renewable energy sources and distributed generation, brought several changes to the power system operation. Electricity markets worldwide are complex and dynamic environments with very particular characteristics, resulting from their restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. With the eminent implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. This paper proposes a clustering methodology regarding the remuneration and tariff of VPP. It proposes a model to implement fair and strategic remuneration and tariff methodologies, using a clustering algorithm, applied to load values, submitted to different types of normalization process, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to the players characteristics. The proposed clustering methodology has been tested in a real distribution network with 30 bus, including residential and commercial consumers, photovoltaic generation and storage units

• Referencias bibliográficas
  • Anil K. Jain, 2010. “Data Clustering: 50 years beyond K-Means”. Pattern Recognition Letters, Elsevier, Vol. 31, Issue 8, pp.651-666.
  • Anil K. Jain, M.N Murty, P.J. Flynn, 1999. “Data Clustering: A Review.” ACM Computing Surveys, 31 (3). pp. 264-323.
  • Anthony C. Chrysopoulos, Andreas L. Symeonidis, Pericles A. Mitkas, 2009. “Improving agent bidding in power stock markets through a data mining...
  • Blumsack S and Fernandez A., 2012. “Ready or not, here comes the smart grid!” Energy. 2012; 37(1): 61-8
  • CAISO – California Independent System Operator. Available: http://www.caiso.com [accessed on July 2017]
  • Canizes B., Silva M., Faria P., Ramos S., Vale Z., 2015. “Resource Scheduling in Residential Microgrids Considering Energy Selling to External...
  • C. Ribeiro, T. Pinto, Z. Vale, 2016. “Customized Normalization Method to enhance the Clustering process of Consumption Profiles”, 7th International...
  • C. Ribeiro, T. Pinto, M. Silva, S. Ramos, Z. Vale, 2015. “Data Mining approach for Decision Support in real data based Smart Grid scenario”...
  • C. Ribeiro, T. pinto, H. Morais, Z. Vale, G. Santos, 2013. “Intelligent Remuneration and Tariffs in for Virtual Power Players”, IEEE PowerTech...
  • C. KienY, B. Berseneff, N. Hadjsaid, Y. Besanger, J. Maire, 2009. “On the concept and the interest of Virtual Power plant: some results from...
  • Dore A. and Regazzoni C., 2010, “Interaction Analysis with a Bayesian Trajectory Model”, IEEE Intelligent Systems, vol. 25, no. 3, pp. 32–40
  • EPEXSPOT – European Power Exchange Products Day-Ahead Auction, 2015. Available: https://www.epexspot.com/en/product-info/auction, [accessed...
  • Erev, I. and Roth, A.,1998. “Predicting how people play games with unique, mixed-strategy equilibria”, American Economic Review, vol. 88,...
  • G. Chicco and I. Ilie, 2009. “Support Vector Clustering of Electrical Load Pattern Data”. IEEE Transactions on Power Systems, vol.24, no.3,...
  • G. Chicco, R. Napoli, P. Postolache, M. Scutariu, C. Toader, 2003. “Customer Characterization Options for Improving the Tariff Offer”, IEEE...
  • G. Gan, C. Ma, J. Wu, 2007. “Data Clustering Theory, Algorithms and Applications”, ASA-SIAM Series on Statistics and Applied Probability,...
  • I. Praça, C. Ramos, Z. Vale, M. Cordeiro, 2003. “MASCEM: A Multi-Agent System that Simulates Competitive Electricity Markets”, IEEE Intelligent...
  • MIBEL - Mercado Ibérico de Electricidade, 2017. Available: http://www.mibel.com/, [accessed on July 2017]
  • Mohammad Shahidehpour, Hatim Yamin, Zuyi Li., 2002. “Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management”,...
  • Nord Pool Spot - Trading, Day-ahead market Elspot, 2016. Available: http://www.nordpoolspot.com/TAS/Day-ahead-market-Elspot/, [accessed on...
  • Oliveira P., Pinto T., Morais H., Vale Z., 2012. “MASGriP - A Multi-Agent Smart Grid Simulation Plataform,” IEEE Power and Energy Society...
  • S. Ramos, J. Duarte, J. Soares, Z. vale, F. Duarte, 2012. “Typical Load Profiles in the Smart Grid Context – A Clustering Methods Comparison”,...
  • Sharma K.C., Bhakar R., Tiwari, H.P., 2014. “Strategic bidding for wind power producers in electricity markets.” Energy Conversion and Management...
  • Sioshansi, F.P., 2013. “Evolution of Global Electricity Markets – New paradigms, new challenges, new approaches”, Academic Press.
  • Sousa T., Morais H., Vale Z., Faria P., Soares J., 2012. “Intelligent Energy Resource Management Considering Vehicle-to-Grid: A Simulated...
  • T. Pinto, Z. Vale, F. Rodrigues, H. Norais, I. Praça, 2011. “Strategic Bidding Methodology for Electricity Markets using Adaptive Learning”,...
  • T. Pinto, Z. Vale, H. Morais, I.Praça, C. Ramos, 2009. “Multi-Agent Based Electricity Market Simulator With VPP: Conceptual and Implementation...
  • Z. Vale, T. Pinto, I. Praça, H. Morais, 2011. “MASCEM - Electricity markets simulation with strategically acting players”, IEEE Intelligent...
  • Z. Vale, H. Morais, P. Faria, H. Khodr, J. Ferreira, P. Kadar, 2010. “Distributed Energy Resources Management with Cyber-Physical SCADA in...