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ALGERIA & RENEWABLE ENERGY (IRENA STATISTICS in 2009): Renewables Electrical Supply: 3.6 PJ (0.2 % of the total supply) Renewables generation: 342 GWh.

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Présentation au sujet: "ALGERIA & RENEWABLE ENERGY (IRENA STATISTICS in 2009): Renewables Electrical Supply: 3.6 PJ (0.2 % of the total supply) Renewables generation: 342 GWh."— Transcription de la présentation:

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3 ALGERIA & RENEWABLE ENERGY (IRENA STATISTICS in 2009): Renewables Electrical Supply: 3.6 PJ (0.2 % of the total supply) Renewables generation: 342 GWh (0.8 % of the total Electricity generation) Renewables capacity: 280 MW (3.4 %). POTENTIAL : Wind energy is one of the most rapidly growing sources of electricity all over the world. Thus It is predicted that 12% of the total world electricity demands will be supplied from wind energy by Producing a balanced electrical power facing to the non regularity of the wind is still the main challenge in WECS. Advanced control Techniques is a major player in Wind Power industry development.

4  3 Kw (average power) a Savonuis Vertical Axis Wind Turbine.  Residential application (buildings, Street Lighting…etc) Wind System description: WECSystem Main Parts :

5 Wind Speed & Wind turbine Modeling: V(t)=6+0.2*sin(0.1047*t)+2*sin(0.2665*t)+sin(1.2930*t)+0.2*sin(3.6645*t) The extracted power from the wind by the Savonuis wind turbine is:

6 The DFIM Complex model: Current-Flux equations: Active & Reactive powers expression: Electromagnetic Torque expression:

7 Oriented flux strategy : q-axis  s   Rotor-ref-axis d-axis Stator-ref-axis s  If the virtual grid flux vector is aligned on the d axis it is found that: And after calculation : So,

8 The above equations are coupled between themselves, so the coupling terms are considered as disturbances to be removed by the control, for this purpose, an optimized fuzzy logic controller is proposed in order to control the stator powers flow with desired performance. This type of controllers is chosen due to its competence in control and its implementation simplicity.

9 Due to the very fast-growing information technology, industry has already developed and released a few good design packages which can be successfully applied in different applications for a fuzzy controller design. Among them are: RT/Fuzzy Toolbox for MATRIXx TM by Integrated Systems Inc., Fuzzy Logic Toolbox for MATLAB TM by The MathWorks Inc.,…etc. Fuzzy Logic Toolbox for MATLAB TM is chosen to design our Fuzzy controller.

10 General block diagram of DFIG control scheme.

11 fuzzy Controller Inner structure:

12 Fuzzification Méthode: All of the Fuzzy controller input and output have a Triangular form Membership fonctions (easy in calculation ) Rules Table : e de BNMNSNVSNZEVSPSPMPBP BNNB NMNSPVSZE MNNB NMNSPVSZEPVS SNNB NMNSPVSZEPVSPS VSNNB NMNSPVSZEPVSPSPM ZENBNMNSPVSZEPVSPSPMPB VSPNMNSPVSZEPVSPSPMPB SPNSPVSZEPVSPSPMPB MPPVSZEPVSPSPMPB BPZEPVSPSPMPB (P, N)=(Positive, Negative), (B, M, S,ZE) =(Big, Medium, Small, Zero) V=(Very). Inference Engine: Is a Mamdani-type and based on the following rules table.

13 These rules were wisely chosen according to prescribe specifications, taking into account the system stability and performances, thus are represented by the overshoot, rise time and the settle time of the fuzzy system response. Defuzification Method: Centre-of-area/gravity method is used in the defuzification procedure. even though it is very expensive in terms of calculation time, but it gives good results.. A right conversion of the actual measured value and the fuzzy value of such kinds are acceptable in the fuzzy space (for the error and its derivative) and in real space (for the control -output-). Optimization of the input/output of the fuzzy controller: Optimization Algorithm bloc

14 Extracting the maximum wind power through the Savonuis wind turbine needs: Operating at variable speed + well-known of the Savonuis wind turbine aerofoil. Maximum Power Point Tracking Strategy Several techniques can be used such as the gradient method, the estimate method…etc. In our case:

15 Wind Speed (m/s) Stator Active Power Response

16 Stator Reactive Power ResponseStator Power factor Cp of the Vertical Axis Wind Turbine Rotor Current (A)

17 Point out on the Renewable energy, (Wind) in Algeria (IRENA Statestics). 3 Kw Residential Wind Energy Conversion System based on Vertical Axis Wind Turbine and Grid connected DFIG is proposed and modeled. Oriented Grid Flux Strategy has been investigated to remove the complexity issue of the WECSystem. Fuzzy Logic control algorithm is proposed using to control the stator powers flow of the Grid-connected DFIG following to specifications. Simulation tests have been done where they have shown the stability and robustness of the system. Maximum Power Point Tracking Strategy is included basing on the turbine aerofoil.

18 ParametersValues DFIG Output power P n /kW7.5 Stator resistance R s /Ω0.455 Rotor resistance R r /Ω0.62 Stator inductance L s /H0.084 Rotor inductance L r /H0.081 Mutual inductance M sr /H0.078 Number of pair poles2 Inertia moment J/(N·m·s 2 ) Rubbing factor F6.73e -3 Vertical Axis Wind Turbine Rated power KW7 Density of air (ρ) kg/m Area swept (Diameter×height) m 2 40 Rotor diameter m4 Optimal coefficient Cp max 1.9 Gearbox ratio40 Appendix (System data)


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