Age-dependent & multi-load reliability analysis in transmission systems

Transcription

1 CIGRE US National Committee 2013 Grid of the Future Symposium October 20-22, 2013 Boston, USA Age-dependent & multi-load reliability analysis in transmission systems Marco Fleckenstein, Prof. Dr. -Ing. Claus Neumann, Prof. Dr. -Ing. Gerd Balzer Technical University of Darmstadt, Institute of Electrical Power Systems Landgraf-Georg-Str. 4, Darmstadt, Germany phone:

2 Content Motivation Transmission system model Vertical load situations Reliability values Results Conclusions 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 2

3 Motivation Technical aspects Higher network utilization Availability of the transmission system Financial interests Liberalization of the energy market Achieve profit Limited billable fees Reduce network risk by constant maintenance costs with risk based maintenance Exact determination of individual asset risk Multi-load reliability analysis Age-dependent outage values 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 3

4 Structure of the transmission system model Overview Large part of the transmission system from a TSO in Germany The model includes this voltage levels: 380 kv transmission system 220 kv transmission system 110 kv network groups 380 kv overhead line network 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 4

5 Structure of the transmission system model 380 kv transmission system Detail level: Substations & busbar configurations Switch positions Power plant units & transformers Length of overhead lines Connection points to other TSOs More detailed modeling is difficult. Element Number of Elements Bus bar 145 Center break disconnector 263 Circuit breaker 337 Generator 30 Overhead line Pantograph disconnector Power transformer 4453 km 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein /110kV: /220kV: 25

6 Structure of the transmission system model 220kV transmission system Detail Level: Length of overhead lines Power plant units No substation layout No reliability data for assets Only modeled structurally. Modeling necessary for load flow in 380 kv system 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 6

7 Structure of the transmission system model 110kV sub-transmission network groups Detail Level: Coupling transformers from 380 kv & 220 kv Load aggregated as loading of coupling transformers X X X X X X X X Infeed of power plant units disregarded 34 Utility network groups 8 industrial network groups 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 7

8 Power in GW Load & power plant scenarios water uranium hard coal natural gas lignite vertical load number of load scenario k All common network states within one year adopted. Surplus power is transferred into neighboring transmission systems. Power plant power gradients are considered in the model Reliability & Availability analysis for all ten load scenarios T ND (n,k) non-delivered outage duration in h P ND (n,k) non-delivered power in MW T NS (n,k) non-supplied outage duration in h P NS (n,k) non-supplied power in MW 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 8

9 Values for power plants Type of power plant Load gradients in % per minute Share of auxiliary power in % Number of power plant units Installed gross power in MW Hard coal Lignite Gas turbine Combined cycle Nuclear Pump storage October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 9

10 Outage Rate of PTR in 1/a Outage Rate of CB, BB, DIS and OHL in 1/a Reliability values Element Outage rate H in [1/a] Outage duration T in [h] Bus bar Center break disconnector Circuit breaker Overhead lines a Selector switch disconnector b 0 0 Power transformer years DIS CB BB OHL PTR years years years years 5-10 years years 35 years and October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 10

11 outage rates in 1/a Results: outage rates (1) (2) H n W C,n W P,n n outage rate of the individual asset in 1/a. non delivered energy caused by the individual asset n in MWh. non feed in energy of power plants caused by the individual asset n in MWh. identification number of the individual asset Consumption Production number of load scenario k 10 load scenarios peak load scenario October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 11

12 Energy in MWh Number of assets Results outage rates Non-delivered & non-supplied energy of the ten load scenarios Consumption Production number of load scenario k Number of assets responsible for outages Consumption Production number of load scenario k 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 12

13 K(n) in percent Results outage rates W C,Peak,n W C,TL,n non delivered energy caused by the individual asset n during the Peak load with averaged outage rate in MWh. averaged non delivered energy caused by the individual asset n with age-dependent outage rate within the ten load scenarios in MWh. 100% 0% -100% -200% -300% -400% -500% -600% -700% -800% -900% asset n of the 380 kv level 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 13

14 Conclusions & further work Different load & power plant scenarios are important for asset risk determination Age-dependent outage rates are necessary for exact analysis More reliability and availability data must integrated in the database Source: abb.com Risk-based maintenance is a good possibility to improve the reliability and availability of the transmission system and reduce operative costs. 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 14

15 End Thank you for your attention. 24 October 2013 Electrical Engineering and Information Technology Institute of Electrical Power Systems Marco Fleckenstein 15