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Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Controllability of DG helps managing Distribution Grids J. A. Peças Lopes

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Presentation on theme: "Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Controllability of DG helps managing Distribution Grids J. A. Peças Lopes"— Presentation transcript:

1 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Controllability of DG helps managing Distribution Grids J. A. Peças Lopes (jpl@fe.up.pt)

2 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Exploiting DG to improve system operation DG has been considered as non controllable and non dispatchable, since all the energy production has priority to be absorbed by the network; The increase in DG foreseen for the next years will require a different approach regarding the way how DG units will be operated: –Concepts of controllability should be developed and exploited: Participation in reactive power control; Interruptability; Delivery of ancillary services (primary and secondary reserves, according to the conversion technology and primary energy sources); Participation in system restoration strategies; –Development of concepts related with control of clusters of DG and virtual power stations;

3 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Main characteristics of DG units and controlability concepts Three main types of energy conversion systems can be found among DG units: –Conventional synchronous machines (cogeneration, CHP, mini-hydro); –Asynchronous generators (wind power, mini-hydro); –AC/DC/AC electronic conversion systems used together with synchronous or induction machines (micro-turbines, fuel cells, wind generators). Classification (according to primary energy source and conversion system used): –Non- controllable (Ex: Wind park with asynchronous stall generators); –Partially controllable (Ex: Wind park with synchronous variable speed gen. and AC/DC/AC converters); –Controllable (Ex: Mini-hydro or Cogeneration plant with synchronous units).

4 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation DG units used to optimise the distribution system operation DG can be used to optimise the operation strategy of distribution networks. The Problem can be formulated an optimisation problem: Min (active power losses) Subj. to: Vmax < V i < Vmin S ij max < S ij Qgmax i < Qg i < Qgmin i taking into account the type of generator Qimpor max < Qimpor Transformer tap limits are kept Control variables: Qg, capacitor banks and transformer taps The need to use a motor of optimisation (Evolutionary Particle Swarm Optimisation – EPSO)

5 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Some results of the participation of DG in Voltage VAR control Test System: 60 kV distribution network with a large penetration of DG (mini-hydro and wind generation). Activate control on reactive power generated in the DG Units. Activate control on reactive power generated in the DG Units.

6 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Some results of the participation of DG in Voltage VAR control Changes in active Losses –Peak load scenario –A clear reduction on actives losses was obtained

7 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Some results of the participation of DG in Voltage VAR control Results concerning voltage in network busses

8 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Dynamic Impacts Dynamic behaviour impacts need to be addressed using adequate DG modelling and DG equivalent representation: –Considering disturbances resulting from DG operation; –Considering disturbances in distribution networks; –Considering disturbances in the transmission system

9 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Dynamic behavior analysis Scenario: Week peak with maximum dispersed generation Disturbance: Outage of Power Plant H: 7,346MVA, production of 6,692+j3,03 MVA, injection of 2,678+j1,081 MVA (tg  = 0,404) Voltage profile: 60kV bus at the substation

10 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Dynamic behavior analysis 15 kV bus of the feeder where the power plant was connected 15 kV bus of the feeder where the power plant was not connected

11 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Dynamic behavior analysis (Impact in the other generators)

12 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Relay coordination Under voltage relay coordination is needed; Energy conversion systems need to able to withstand low voltages during short-circuits up-stream. Frequency changesChanges in contractual inter-area power flows

13 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Impacts on Operation Load flows become bi-directional; Voltage profiles have different patterns; Losses change as a function of the production and load levels; Congestion in system branches is a function of the production and load levels; Short-circuit levels increase; Power quality may be affected; Voltage transients will appear as a result of connection disconnection of generators; Risk of islanding operation; Reliability may be reduced; System dynamic behavior may be largely affected; Protections coordination is needed;

14 Barcelona– May 2003 CIRED’2003 Beta session 4a: Distributed Generation Conclusions The future: –DG units should be more actively used to help in the management of the distribution grid; –New DMS tools need to be developed: Topology processor with capabilities of identification of energised areas; Voltage and reactive power control; Load and current forecasting; Load flow including new generator models and load allocation algorithms to allow load flow to run; Optimum network reconfiguration; State estimation (considering that some DG units will not be monitored and new pseudo-measures need to be defined); –Cluster control strategies should be implemented, involving the development of local dispatch centres; –Development of DMS training simulators for distribution grids with large amounts of DG (steady state and dynamic behaviour).


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