1. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 1 RISK CRITERIA TO APPLY AND MANAGE DISTRIBUTION TRANSFORMERS M. A. Hernandez; M. R. Gouvea ENERQ – University of São Paulo

2. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 2 Solutions to minimize energy interruptions caused by failures in distribution transformers Reintroducing (from maintenance) distribution transformers in the system Evaluating the risk of failures of distribution transformers in operation Objectives

3. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 3 Sources of Transformer Failures Failures due to problems arising from: –severe system requirements (grounding, lightning protection, etc.) –network installation procedures –project design –maintenance procedures

4. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 4 Basic Methodology Evaluation of: Transformer Supportability (TS) System Requirements (SR) Compromise solution

5. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 5 Transformer Supportability (TS) design characteristics operating characteristics The above characteristics lead to the evaluation of the TS indices

6. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 6 System Requirements (SR) Physical characteristics: location : –average expected rate of failures caused by trees, pollution, shielding from the buildings, grounding, etc. - supplied load with predictable behavior network design: –insulated cables to avoid short circuits –underground network, –etc.

7. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 7 SR indices obtained by direct measuring of: –loading, voltage levels and statistical records of transformer failures, etc. obtained by network simulations: –loading from typical customer daily curves –lightning performance

8. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 8 Clustering network locations - classifying the network locations where transformers may be installed, according to their physical, design and operational characteristics, - grouping these locations according to similar characteristics - representing each group through an element whose features equal the average characteristics of the group

9. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 9 Transformer Clustering - classify the transformers, according to their statistical indices: - supportability under specific requirement levels, - expected economic life (calculated with Arrenius equation) - expected supportability in overvoltage situations according to technical standards - group these transformers according to similar characteristics - represent each group through an element whose features equal the average characteristics of the group

10. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 10 Two-dimensional Example TS SR Loading Over- voltage TS  SRf  C Minimise Associated Cost

11. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 11 Optimization Model Propose a set of possible solutions for the allocation of transformers in the system; Represent TS and SR, for each possible solution, in a n-dimensional space; Determine the overall associated cost for each solution; The Risk of each solution is represented by the convolution between the SR and TS statistical distributions The optimum solution is the best compromise solution comprising cost and risk associated to the set of distances between SR and TS

12. M. R. Gouvea BR Session 1 – Block 1 – Transformers – Paper #36 Barcelona 12-15 May 2003 12 Conclusions The suggested methodology is an efficient tool to manage distribution transformers, in that it: considers the technical characteristics of the transformers and the network locations in which they are applied; optimizes associated costs; avoids failures as it identifies risk areas; Improves the presently used transformer management methodology by introducing new control parameters.