Frankfurt (Germany), 6-9 June 2011 Manuel Avendaño J. V. Milanović Manuel Avendaño – UK – Session 2 – Paper 0529 METHODOLOGY FOR FLEXIBLE, COST-EFFECTIVE MONITORING OF VOLTAGE SAGS School of Electrical & Electronic Engineering Manchester, UK

Frankfurt (Germany), 6-9 June 2011 What did we do?  Proposed methodology for determining a range of best monitoring programmes for estimating the performance of sags with different characteristics.  Incorporated user-defined voltage sag characteristics and a measure of the overall accuracy of sag estimation. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Presentation Outline  Why did we do it? (Importance and motivation)  How did we do it? (Methodology)  What did we get? (Results)  What did we learn? (Conclusions) Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Why did we do it?  Knowledge of voltage sag incidence in the network can help in tailoring solutions to mitigate the consequences of sags.  Estimation of sag characteristics is required when measurements are not available.  Fault location method utilized directly influences the number of monitors. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Why did we do it?  Sag monitoring programs (SMPs) should be focused on quantifying most critical sags − (E.g. SARFI-90%, SARFI-70%, SEMI F47, etc)  To provide a measure for assessing the sag estimation derived from a SMP − (Diff. between real and estimated events) Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 How did we do it?  Selection of monitor locations based on minimization of overall sag estimation error.  Utilization of existing fault location method.  Application in a generic distribution system (GDS) and comparison with an optimal placement method. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Sag estimation error (SEE) = total number of buses = real number of sags below i.c. SEMI F47 at bus i = estimated number of sags below i.c. SEMI F47 at bus i N SEMI F47 can be substituted by any other voltage- tolerance curve (CBEMA), performance index (SARFI), etc. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June Set target value for SEE or number of monitors (stop criteria). 2. Simulate faults to obtain sag performance. 3. Perform fault location using voltage measurements of all buses. 4. Calculate SEE incurred by all buses. 5. Monitor location = min(SEE) 6. Repeat steps 3-5 until a stop criterion is fulfilled. Monitor placement Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 What did we get? An iterative search algorithm that is: Flexible. One or multiple monitoring programmes can be determined for any kind of user-defined voltage sag characteristics. Cost-effective. If technical and/or economic constraints limit the number of monitors to be deployed, a series of SMPs can be provided accordingly. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Application  295-bus GDS, 278 lines, 37 transformers. GDS equipment shut-down region below SEMI F47 Voltage level (kV) Fault clearing time (cycles) Bus faults3.6 Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Sag Monitoring Programmes Number of monitors SEE (number of sags) SARFI-90SARFI-80SARFI-70SEMI F Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Reduction of sag estimation error Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Location of monitors SMP – SARFI-90Optimal monitoring Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Effects of robustness in fault location method on sag magnitude estimation Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Comparison with optimal monitoring 12 monitors optimally placed vs. 5 monitors placed with proposed approach. Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Comparison with optimal monitoring Distribution of SEE for Monte Carlo simulations representing 100 years of system performance Manuel Avendaño – UK – Session 2 – Paper 0529

Frankfurt (Germany), 6-9 June 2011 Conclusions  A methodology for determining a range of best voltage sag monitoring programmes is proposed.  DNOs can choose a sag monitoring programme specifically designed to estimate the performance of the sags more relevant to its customers.  Due to the fault location technique employed it is more robust than previous approaches. Manuel Avendaño – UK – Session 2 – Paper 0529