Barcelona 12-15 May 2003 Session 5 – Block 2 1 Geographical Information System and Genetic Algorithm based planning tool for MV distribution networks Minea.

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Barcelona May 2003 Session 5 – Block 2 1 Geographical Information System and Genetic Algorithm based planning tool for MV distribution networks Minea Skok, Davor Skrlec, Slavko Krajcar Faculty of Electrical Engineering and Computing Department of Power Systems University of Zagreb Croatia

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Presentation outline introductory remarks on use of evolutionary algorithms (EA) in distribution systems CADDiN - GA application in long-term large- scale urban distribution network planning

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm computer-based problem solving systems which model evolution mechanisms … genetic algorithms evolutionary algorithms evolution strategies genetic programming classifier systems

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Why interest in EA? well suited to deal with problems with … integer variables non-convex functions non-differentiable functions domains not connected multiple local optima multiple objectives fuzzy data, etc.

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Surveys on application of EA in power systems V. Miranda, D. Srinivasan, L.M. Proenca, Evolutionary computation in power systems, Electrical Power & Energy Systems, Vol.20, No.2, 1998, pp D. Srinivasan, F.S. Wen, C.S. Chang, A.C. Liew, A survey of applications of evolutionary computation to power systems, Proceedings of ISAP’96, Orlando, USA, 1996, pp J.T. Alexander, An indexed bibliography of genetic algorithms in power engineering, Report 94-1-Power, Department of Information Technology and Production Economics, University of Vassa, Finland, February M.A. Laughton, Genetic algorithms in power system planning and operation, IEE Coloquium on Artificial Intelligence in Power Systems, IEE Digest No. 075, London, UK, 1995, pp. 5/1 -5/3.

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Application of EA in distribution systems AreaFieldGAESEPGPHybrid Expansion planning distribution XXGA+Fuzzy VAr planning, capacitor placement XX Distribution operation Loss minimization, switching X Fault diagnosis XGA+NN Service restoration XGA+Exp.Sys. PGA Load management X Load forecasting XXGA+NN Analysis Harmonics X

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May CADDiN – Computer Aided Design of Distribution Networks Geographical Information System Extensions Preparing necessary data – collecting, converting, calculating Interpreting and analyzing the expansion planning results. Evaluating different expansion alternatives Analizing the existing DS – distribution of load, transfer capability of existing cable system capacity limitations and supply areas of substations,etc. Load forecasting Optimization modules 1.urban areas (EA): open-loop link (connective, clasp) 2.rural areas

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Link distribution networks planned link distribution network 3 HV/MV substations 1 switching station tick lines – feeders thin lines – possible routing corridors (GIS)

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm – functions optimal feeders routing switching station & HV/MV substations sitting and sizing service areas of HV/MV substations contingency switching (tie-lines)

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm – objectives minimal capital investments  new substations and transformers costs  costs of new feeder sections  costs of adding new feeders to supply & switching stations minimal power and energy losses costs minimal maintenance costs

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm – constraints voltage drop loading limits contingency margin rules network layout number of feeders emanating from HV/MV and switching station the total load with each link the total number of MV/LV substations per link

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm – coding load point supply substation Preprocessing of link’s routes chromosome decoding The result of the first step of the decoding procedure The result of the second step of the decoding procedure

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Evolutionary algorithm – operators Crossover fragment reordering crossover (FRX) cycle crossover (CX) Mutation order based mutation (OBM)

Minea Skok, Davor Skrlec, Slavko Krajcar Croatia Session 5 – Block 2 Barcelona May Tel: Fax: Department of Power systems Faculty of Electrical Engineering and Computing University of Zagreb PP 148 Zagreb HR Croatia Contact information: