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Frankfurt (Germany), 6-9 June 2011
Motivation
Visual overlay
Data mining
Example event analysis
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Systematic Power Quality Monitoring in Municipal Power Grid
Frankfurt (Germany), 6-9 June 2011
Power quality is a key factor for solid energy delivery
Capable and affordable PQ recorders available
Continuous monitoring provides
- transparency of system conditions
- increased customer satisfaction
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Motivation
But: systematic data treatment required
Frankfurt (Germany), 6-9 June 2011
60 PQ recorders firmly installed in municipal grid: - 7 on 110 kV - 8 on 25 kV - 45 on 10 kV
Parameterized according to common standards (mainly EN 50 160)
Warning if 75% of admissible levels are exceeded
Linked to central server in utility headquarters
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Installation
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Original recorder survey (WinPQ)
(a-eberle)
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Geographic visual overlay
No violation
Warnig limit(s) exceeded
EN 50160 limit(s) violated
110 kV 25 kV 10 kV
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Central database
But: multiple SQL queries for survey of complete grid
Queries: commands
(a-eberle)
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Solution for integral database access
MySQL Workbench
Free and multi-functional database tool
Generation, treatment and administration of
complex SQL queries
Stored query procedures of any complexity
Various export formats: HTML, XML, CSV
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Example MySQL Workbench query DELIMITER $$
DROP PROCEDURE IF EXISTS Example procedure;
CREATE PROCEDURE Example procedure( IN name_part VARCHAR(2056), params_what VARCHAR(2056), params_where VARCHAR(2056))
Begin
Declare t_n VARCHAR(1024);
Declare done int default 0;
Declare looper int default 0;
Declare TableCursor Cursor for SELECT table_name FROM information_schema.tables WHERE table_schema = ‘Example database' and table_name LIKE CONCAT('%',name_part,'%');
DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = 1;
SET @s := "";
Open TableCursor;
read_loop: LOOP
FETCH TableCursor INTO t_n;
IF done THEN
LEAVE read_loop;
END IF;
IF looper THEN
SET @s := CONCAT(@s," UNION SELECT '",t_n,"' as table_n , ",params_what," FROM ", t_n , " ",params_where);
ELSE
SET @s := CONCAT(@s,"SELECT '",t_n,"' as table_n , ",params_what," FROM ", t_n , " ",params_where);
SET looper=1;
END IF;
END LOOP;
PREPARE stmt FROM @s;
EXECUTE stmt;
Close TableCursor;
END $$
DELIMITER ;
Only red variables individually adapted
Blue query text firmly stored
CALL Example procedure(„Data class“, „Measure values“, „WHERE criterion x > y“)
Frankfurt (Germany), 6-9 June 2011
Messort AVG(H3_MAX) AVG(H5_MAX) AVG(H7_MAX) AVG(H9_MAX) AVG(H11_MAX) AVG(H13_MAX)qb1uw02ka04 0.40 2.04 0.66 0.06 0.44 0.22qb2uw02kb02 0.41 1.72 0.62 0.04 0.25 0.11qc1uw03kb03 0.61 1.99 0.88 0.12 0.33 0.19qc2uw03ka04 0.44 1.90 1.15 0.10 0.59 0.58qe1uw07ka07 0.36 1.99 0.71 0.07 0.41 0.16qe2uw07ja07 0.33 1.82 0.98 0.03 0.12 0.16qe3uw07ka20 0.34 1.84 0.81 0.09 0.65 0.48
qe4uw07ja01 0.41 1.83 0.85 0.06 0.40 0.31qe5uw07ec04 0.25 0.60 0.74 0.04 0.51 0.27qe6uw07ea04 0.33 1.83 0.85 0.15 0.18 0.26qf1uw08ka06 2.20 1.81 0.97 0.03 0.17 0.17qf2uw08ka10 0.52 1.76 0.68 0.11 0.45 0.44qg1uw09kb02 0.41 2.33 0.64 0.07 0.44 0.17qg2uw09ka07 0.36 1.41 0.51 0.08 0.36 0.25qj1uw63ka07 0.51 1.61 0.58 0.08 0.31 0.24qj2uw63ka03 0.59 1.97 0.60 0.11 0.38 0.13qj3uw63ja15 0.35 1.86 0.71 0.04 0.20 0.07qj4uw63ja12 0.38 1.10 0.49 0.05 0.18 0.11qk1uw64ka13 0.46 2.80 0.44 0.06 0.26 0.10qk2uw64ka06 0.44 1.67 0.95 0.08 0.19 0.06qk3uw64ea04 0.29 0.81 0.67 0.05 0.18 0.17qk4uw64ec01 0.34 1.85 1.02 0.06 0.21 0.07ql1uw30ec01 0.36 1.88 1.04 0.06 0.21 0.06ql2uw32ec02 0.28 1.50 0.89 0.05 0.17 0.05qo1uw33ea03 0.33 1.80 1.01 0.06 0.20 0.06qp1uw34ka12 0.40 1.81 0.48 0.06 0.26 0.22qp2uw34kb06 0.37 1.81 0.59 0.05 0.27 0.22qr1uw36ka18 0.36 1.94 0.86 0.04 0.29 0.28qr2uw36kb06 0.37 2.16 0.96 0.04 0.35 0.13qs1uw37ka05 0.39 1.85 0.47 0.08 0.32 0.28qs2uw37ka11 0.35 1.86 0.87 0.05 0.24 0.21qu1uw52kb12 0.09 0.19 0.12 0.01 0.02 0.01qu2uw52kb08 0.44 1.78 0.39 0.08 0.29 0.18qv1uw53ka01 0.40 2.11 0.62 0.05 0.42 0.24qv2uw53kb01 0.40 2.11 0.62 0.05 0.42 0.24qv3uw53ka11 0.40 1.92 0.71 0.04 0.44 0.19qv4uw53kb11 0.40 1.92 0.71 0.04 0.44 0.19
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Example MySQL result in Exceldaily maxima of voltage harmonics orders 3, 5, 7, 11, 13
Table: not useful
Histogram: gradually betterKiviat diagram: best survey
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Example PQ evaluation Feb 2011
LocationTemporary overvoltages
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Excerpt of 10 ms-recorders
Intermittent single phase earth fault ...
19:49:05 h 19:49:25 h
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Excerpt of 10 min data
19:00 h 22:00 h
... subsequent continuous single phase earth fault
phase –ground
between conductors
Voltages
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Conclusions
High transparency of system status
Easy detection and analysis of faults
Flexible mining system for numerous data
Visual survey
Frankfurt (Germany), 6-9 June 2011
Gerhard Krost – Germany – Session 2 Block 3 – Paper ID 417
Thank you !