An Ordering Procedure for Admissible Network Configurations to Regularize DFR Optimization Problems in Smart Grids

A. Rizzi, F. Possemato, S. Caschera, M. Paschero, F. M. Frattale Mascioli

Abstract

The power loss reduction is one of the main targets for any electrical energy distribution company. In this paper the problem of the joint optimization of both topology and network parameters in a real Smart Grid is faced. A portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. located in Rome is considered. It includes about 1200 user loads, 70 km of Medium Voltage (MV) lines, 6 feeders, a Thyristor Voltage Regulator (TVR) and 6 distributed energy sources (5 generator sets and 1 photovoltaic plant). The power factor correction (PFC) is performed tuning the 5 generator sets and setting the state of the breakers in order to perform the distributed feeder reconfiguration (DFR). The joint PFC and DFR problem is faced by considering a suited objective function and by adopting a genetic algorithm. In this paper we present a heuristic method to compare the graphs of two admissible topologies, such that similar graphs are characterized by close active power loss values. This criterion is used to define a suited ordering of the list of admissible configurations, aiming to improve the continuity of the fitness function to the variation of the configurations parameter. Tests are performed by feeding the simulation environment with real data concerning dissipated and generated active and reactive power values. Preliminary results are very interesting, showing that, for the considered real network, the proposed ordering criteria for admissible network configurations can facilitate the optimization process.

References

  1. Carreno, E., Romero, R., and Padilha-Feltrin, A. (2008). An efficient codification to solve distribution network reconfiguration for loss reduction problem. IEEE Transaction on Power Systems, 23(4):15421551.
  2. Chandramohan, S., Atturulu, N., Kumudini, R., and Ventakesh, B. (2010). Operating cost minimization of a radial distribution system in a deregulated electricity market through reconfiguration using nsga method. International Journal of Electric Power Energy Systems, 32(2):126132.
  3. Civanlar, S., Grainger, J., Yin, H., and Lee, S. (1988). Distribution feeder reconfiguration for loss reduction. IEEE Transactions on Power Delivery, 3(3):12171223.
  4. Dahu, L. (2011). Electric power communication system of the future smart grid. Telecommunication for Electric Power System, 32(222).
  5. Merlin, A. and Back, H. (1975). Search for minimumloss operational spanning tree configuration for urban power distribution systems. In Proceeding of Fifth power system conference (PSCC), page 118.
  6. Nara, K., Shiose, A., Kitagawa, M., and Ishibara, T. (1992). Implementation of genetic algorithm for distribution systems loss minimum reconfiguration. IEEE Transaction on Power Systems, 7(3):10441051.
  7. Possemato, F., Storti, G., Paschero, M., Rizzi, A., and Frattale Mascioli, F. (2013). Two evolutionary computation approaches for active power losses minimization in smart grids. In Proceedings of North America Fuzzy Information Processing Society.
  8. Singh, M., Khadkikar, V., Chandra, A., and Varma, R. (2011). Grid interconnection of renewable energy sources at the distribution level with power-quality improvement features. IEEE Transactions on Power Delivery, 26(1):307-315.
  9. Storti, G., Possemato, F., Paschero, M., Alessandroni, S., Rizzi, A., and Mascioli, F. F. (2013a). Neural Nets and Surroundings 22nd Italian Workshop on Neural Nets, WIRN 2012, May 17-19, Vietri sul Mare, Salerno, Italy, volume 19 of Smart Innovation, Systems and Technologies, chapter Active power losses constrained optimization in Smart Grids by gentic algorithms, pages 279-288. Springer Berlin Heidelberg.
  10. Storti, G., Possemato, F., Paschero, M., and nad F.M. Frattale Mascioli, A. R. (2014). A radial configurations search algorithm for joint pfc and dfr optimization in smart grids. In Proceeding of 23th international conference on industrial electrincs (ISIE).
  11. Storti, G., Possemato, F., Paschero, M., Rizzi, A., and Frattale Mascioli, F. M. (2013b). Optimal distribution feeders configuration for active power losses minimization by genetic algorithms. In Proceedings of North America Fuzzy Information Processing Society.
Download


Paper Citation


in Harvard Style

Rizzi A., Possemato F., Caschera S., Paschero M. and Frattale Mascioli F. (2014). An Ordering Procedure for Admissible Network Configurations to Regularize DFR Optimization Problems in Smart Grids . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014) ISBN 978-989-758-052-9, pages 273-280. DOI: 10.5220/0005127302730280


in Bibtex Style

@conference{ecta14,
author={A. Rizzi and F. Possemato and S. Caschera and M. Paschero and F. M. Frattale Mascioli},
title={An Ordering Procedure for Admissible Network Configurations to Regularize DFR Optimization Problems in Smart Grids},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)},
year={2014},
pages={273-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005127302730280},
isbn={978-989-758-052-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)
TI - An Ordering Procedure for Admissible Network Configurations to Regularize DFR Optimization Problems in Smart Grids
SN - 978-989-758-052-9
AU - Rizzi A.
AU - Possemato F.
AU - Caschera S.
AU - Paschero M.
AU - Frattale Mascioli F.
PY - 2014
SP - 273
EP - 280
DO - 10.5220/0005127302730280