Abstract
Reference Network Models (RNMs) are large-scale distribution network planning tools. RNMs can be used by policy makers and regulators to estimate efficient distribution costs. This is a very challenging task, particularly being network planning a combinatorial problem, which is especially difficult to solve due to the vast size of the distribution areas, and the use of several voltage levels. This chapter presents the main features of RNMs developed by the authors, including high performance requirements related to the type and size of the problem. The model can be used to plan distribution networks either from scratch or incrementally from existing grids. Different case studies illustrate the applicability of these models to the assessment of the impact of massive deployment of renewable distributed generation, demand response actions, and plug-in electric vehicle penetration on distribution costs. The results obtained provide valuable information to guide strategic policy-making decisions regarding the implementation of renewable energy programs and smart grid initiatives.
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References
Al-muhaini, M., Arabia, S.: A New Particle-Swarm-Based Algorithm for Distribution System Expansion Planning Including Distributed Generation. Energy & Environment (2007)
Axsen, J., Burke, A., Kurani, K.: Batteries for Plug-in Hybrid Electric Vehicles (PHEVs): Goals and the State of Technology circa, Institute of transportation Studies, University of California (May 2008) http://pubs.its.ucdavis.edu/
Binato, S., Pereira, M.V.F., Granville, S.: A new benders decomposition approach to solve power transmission network design problems. IEEE Transactions On Power Systems 16, 235–240 (2001)
Carrano, E.G., Cardoso, R.T.N., Takahashi, R.H.C., Fonseca, C.M., Neto, O.M.: Power distribution network expansion scheduling using dynamic programming genetic algorithm. IET Generation, Transmission & Distribution 2, 444 (2008)
Chowdhury, A.A., Kumar Agarwal, S., Koval, D.O.: Reliability Modeling of Distributed Generation in Conventional Distribution Systems Planning and Analysis. IEEE Transactions on Industry Applications 39, 1493–1498 (2003)
Cossent, R., Olmos, L., Gómez, T., Mateo, C., Frías, P.: Mitigating the impact of distributed generation on distribution network costs through advanced response options. In: Proceedings of the 7th Conference on the European Energy Market, Madrid, Spain, June 23-25 (2010a)
Cossent, R., Olmos, L., Gómez, T., Mateo, C., Frías, P.: Distribution network costs under different penetration levels of distributed generation. European Transaction on Electrical Power (2010b) (accepted for publication)
Cossent, R., Olmos, L., Gómez, T., Mateo, C., de Joode, J., Scheepers, M., Nieuwenhout, F., Poot, J., Bongaerts, M., Trebolle, D., Doersam, B., Bofinger, S., Cali, U., Gerhardt, N.: Case studies of system costs of distribution areas. D5 IMPROGRES Project (2009), http://www.improgres.org
Diaz-Dorado, E., Pidre, J., Miguez Garcia, E.: Planning of large rural low-voltage networks using evolution strategies. IEEE Transactions on Power Systems 18, 1594–1600 (2003)
El-Khattam, W., Bhattacharya, K., Hegazy, Y., Salama, M.M.A.: Optimal In-vestment Planning for Distributed Generation in a Competitive Electricity Market. IEEE Transactions on Power Systems 19, 1674–1684 (2004)
EPRI & NRDC, Environmental Assessment of Plug-In Hybrid Electric Vehicles. Nation-wide Greenhouse Gas Emissions. 1015325. Final Report, vol. 1, pp. 1–56 (July 2007)
European Smart Grids Technology Platform, Vision and strategy for Europe’s electricity networks of the future (2006), http://www.smartgrids.eu/
Gallego, R.A., Alves, A.B., Monticelli, A., Romero, R.: Parallel simulated annealing applied to long term transmission network expansion planning. IEEE Transactions on Power Systems 12, 181 (1997)
Garver, L.L.: Transmission network estimation using linear programming. IEEE Transactions on Power Apparatus and Systems Pas-89, 1688 (1970)
Goswami, S.: Distribution system planning using branch exchange technique. IEEE Transactions on Power Systems 12, 718–723 (1997)
IEEE, IEEE guide for electric power distribution reliability indices, IEEE. Std 1366, 2001 Edition (2001)
Jamasb, J., Pollitt, M.: International benchmarking and regulation: an application to European electricity distribution utilities. Energy Policy 31, 1609–1622 (2003)
Khator, S.K., Leung, L.C.: Power distribution planning: a review of models and issues. IEEE Transactions on Power Systems 12, 1151 (1997)
Kromer, M.A.: Electric Power trains: Opportunities and Challenges in the US Light-Duty Vehicle Fleet. Massachusetts Institute of Technology (MIT), Massachusetts (2007)
Latorre, G., Cruz, R.D., Areiza, J.M., Villegas, A.: Classification of publications and models on transmission expansion planning. IEEE Transactions on Power Systems 18, 938 (2003)
Mateo, C., Gomez, T., Sánchez, A., Peco, J., Candela, A.: A reference network model for large-scale distribution planning with automatic street map generation. IEEE Transactions on Power Systems (2010) (accepted for publication)
Míguez, E., Cidrás, J., Díaz-Dorado, E., García-Dornelas, J.L.: An Improved Branch-Exchange Algorithm for Large-Scale Distribution Network Planning. IEEE Transactions on Power Systems 17, 931–936 (2002)
Ministry of Industry, Tourism and Trade, Royal Decree 222/2008, that establishes the remuneration regime for the electricity distribution activity (February 15, 2008) (in Spanish)
Mori, H., Iimura, Y.: Application of parallel tabu search to distribution network expansion planning with distributed generation. In: Power Tech Conference Proceedings, 2003 IEEE Bologna, June 23-26, vol. 1, p. 6 (2003)
Nara, K., Satoh, T., Aoki, K., Kitagawa, M., Ishihara, T.: Distribution systems expansion planning by multi-stage branch exchange. IEEE Transactions on Power Systems 7, 208–214 (1992)
Navarro, A., Rudnick, H.: Large-Scale Distribution Planning - Part I: Simultaneous Network and Transformer Optimization. IEEE Transactions on Power Systems 24, 744–751 (2009a)
Navarro, A., Rudnick, H.: Large-Scale Distribution Planning - Part II: Macro-Optimization With Voronoi’s Diagram and Tabu Search. IEEE Transactions on Power Systems 24, 752–758 (2009b)
Peco, J.: Model for designing electrical distribution grids with geographical constraints (In Spanish). PhD dissertation. Universidad Pontificia Comillas. Madrid (2001)
Peponis, G., Papadopoulos, M.P.: New dynamic, branch exchange method for optimal distribution system planning. IEE Proceedings on Generation, Transmission and Distribution 144, 333–339 (1997)
Pieltain, L., Gómez, T., Cossent, R., Mateo, C., Frías, P.: Assessment of the impact of plug-in electric vehicles on distribution networks. IEEE Transactions on Power Systems (2010) (accepted for publication)
Ping, R., Li-Qun, G., Nan, L., Yang, L., Zhi-Ling, L.: Transmission network optimal planning using the particle swarm optimization method. In: Proc. 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China (2009)
Ramirez-Rosado, I.J., Bernal-Agustin, J.L.: Genetic algorithms applied to the design of large power distribution systems. IEEE Transactions on Power Systems 13, 696 (1998)
Ramirez-Rosado, I.J., Dominguez-Navarro, J.A.: New multiobjective tabu search algorithm for fuzzy optimal planning of power distribution systems. IEEE Transactions on Power Systems 21, 224 (2006)
Romero, R., Monticelli, A.: A Hierarchical Decomposition Approach For Transmission Network Expansion Planning. IEEE Transactions on Power Systems 9, 373–379 (1994)
Rothwell, G., Gómez, T.: Electricity Economics: Regulation and Deregulation. IEEE/Wiley, Piscataway (2003)
Rudnick, H., Donoso, J.A.: Integration of price cap and yardstick competition schemes in electrical distribution regulation. IEEE Transactions on Power Systems 4, 1428–1433 (2000)
Valentine-Urbschat, M., Bernhart, M.: Powertrain 2020 –The Future Drives Electric. Roland Berger Strategic Consultants Report, pp. 1– 95 (September 2009), http://www.rolandberger.com
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Gómez, T., Mateo, C., Sánchez, Á., Frías, P., Cossent, R. (2013). Reference Network Models: A Computational Tool for Planning and Designing Large-Scale Smart Electricity Distribution Grids. In: Khaitan, S., Gupta, A. (eds) High Performance Computing in Power and Energy Systems. Power Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32683-7_9
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