Impact of wind power to the power system

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Topics

1. Introduction

2. Characteristics of variation of wind and windpower

3. Impacts of wind power to the power systemstability (PS)

4. Impacts of wind power to power quality (PQ)

5. Probabilistic methods for PS and PQ analysis

6. Objectives and scopes of thesis7. Research methodology

8. Expected results


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n Thailand has possibility for wind power development (small ormedium scale), as reported by ASTAE World Bank, that almost 750sq.km. of areas have good potential with totally about 3,000 MW.

n The 15 Years Renewable Energy Development Plan (15Years REDP)has targeted for wind power to achieve 800 MW within 2022.

n Power system stability and power quality are the first important to be

studied for grid interconnection standardization, for grid performanceimprovement and as the basic knowledge for long-term planning of REdevelopment.

n Wind power affects both PS and PQ since it generates random andfluctuating signal to the power system. This cause system responsevaries drastically and result in power system instability and/or poor

power quality.n

The stochastic characteristics of winds, varied by space and time, cancause large and random variation of power output.n Accordingly, the probabilistic methods are the most relevant tools to

overcome the realistic and dynamic conditions.

Jay Apt, The Spectrum of Power from Wind Turbines, Carnegie Mellon University,12 March 2007.

1. Introduction


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n Over a large frequency range (0.007 to 900 cycles/hr) of wind speedspectrum (WSS) at Brookhaven, N.Y., Van der Hoven found that the 2main phenomena influencing WSS are synoptic scale, and micro-scaledynamics. Meso-scale dynamics has less influence in this area.

2. Characteristics of variation of windand wind power

H. J. HWANG, POWER DENSITY SPECTRUM OF SURFACE WIND SPEED ON PALMYRA ISLAN, St. Louis University, August1969.

synoptic scale

(Slow variation)

Meso-scale

Micro-scale(Fast variation)

(land sea breeze)

(Turbulence)(monsoon)


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H. J. HWANG, POWER DENSITY SPECTRUM OF SURFACE WIND SPEED ON PALMYRA ISLAN, St. Louis University, August1969.

n At Palmyra island,Hwang found that WSSat 3 sites are notablydifferent.

n Synoptic scale

dynamics is, clearly,the most influence forBarren Island, andCauseway.

n For Army site, synopticscale dynamics has less

influence to wind speed


Barren Island site,Causeway site, andArmy siteof Palmyra Island in

tropical Pacific(5.8N., 162.2 W.)

Studies by Hwang on characteristic of wind


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2. Characteristics of variation of wind andwind power

n Figure below presents that, log-scale PSD has linear relationshipwith log-scale frequency during about 0.002 1 Hz

Joaqun Mur-Amada, ngel A. Bayod-Rjula, Characteri zation of Spectral Density of Wi nd Farm Power Output, Zaragoza University,October 2007.

n At about 1 - 2 Hz,fluctuated PSD occurs

due to 3p (3 bladespassing frequencies ofthe rotor) or towershadow effect.

n The low wind speedcauses PSD trend tokeep constant and thenfall at frequency higherthan 2Hz

PSD

(W2.Hz -1)

Grey = original PSDBlack = estimated PSDRed = modelGreen = Avg. error ofmodel from original


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Subsection conclusions

n Synoptic scale dynamics is most influencing to wind speedfollow by micro-scale dynamics.

n

WSS at various sites are significantly different.n During about 0.002 - 1 Hz , log-scale PSD of wind power

has linear relationship with log-scale frequency.

n About 1 - 2 Hz, wind power is influenced by tower shadoweffect.

n Higher than 2Hz, the low wind speed cause PSD trend tokeep constant and then fall.



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3. Impacts of wind power to the powersystem stability (PS)

.


n Wind power can impact to power system stability depends onlevel of penetration, system characteristic, fluctuation of windpower (P and Q), mismatch between load and generation.


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For wind power

n Voltage varied with reactive power. Reactive powercompensation can improve voltage quality. [E.Muljadiet.al.,2006]

n Frequency varied with derivative of active power. Reactivepower compensation can slightly improve frequency.[E.Muljadi et.al.,2006]

n Aggregation of wind farm (separate into many groups) cancause power smoother due to wind power fluctuation is

compensated among each group of wind turbines [PedroRosas, 2003]

4. Impacts of wind power to powerquality (PQ)

E. Muljadi and C.P. Butterfield1, J. Chacon2, H. Romanowitz3,POWER QUALITY ASPECTS IN A WIND POWER PLANT, 1. NationalRenewable Energy Laboratory, 2. Southern California Edison, 3. Oak Creek Energy Systems, Inc., 2006.

Pedro Rosas, Dynamic Influences of Wind Power on The Power System, Technical University of Denmark, 2003.


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n 3p effect (~2.1Hz) is from the rotational turbulence when the 3 bladespassing tower. 1p effect (~0.7Hz) is from the rotor speed variation.12p effect (~8.4Hz) is from the flexible aeroelastic part of the wind turbine.


12p

3p

1p

n These major 3 flickerproblems are normally

found, especially for 3peffect in the areas close towind farm (turbine).

Power spectral density(kW2.Hz-1) of power from225kW wind turbine



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.


n For wind power impact to PQ, three major problems are voltage variation,frequency variation and flicker during continuous operation.

n Severity depends on fluctuation and penetration of wind power, point ofcommon coupling (PCC), reactive power compensation, aggregation of windfarm, distance from wind farm, and wind turbine design.


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n Wind power variation can significantly impact todynamic stability and voltage stability.

n Wind power fluctuation can cause 3 major PQ problems,that are, 1) voltage variation leads to over/under voltage,2) frequency variation leads to over/under frequency and3) flicker during continuous operation.

n Therefore, this topic concern only these issues above.

5. Probabilistic methods for PS and PQanalysis

.


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Deterministic methods

n Deterministic method analyze PS by solving Differential Algebra Equations(DAE) of the power system both static and dynamic

n All operating conditions and network parameters are explicitly determinedn Therefore, the dynamic response to time-variation of generation input and

dynamic (or static) state variables are computed.

n The deterministic methods are, for example, Numerical simulation,Equal-area criterion, Direct method, Eigenvalue analysis,V-Q sensitivity analysis and Q-V modal analysis .

n However, deterministic methods require enormous exact information tocompute highly accurate results which is far from possibility under therealistic random nature of power system and present computer technology.


Prabha. Kundur, Power System Stability and Control by. 1998.

2 methods for PS and PQ analysis are deterministic and probabilisticmethods


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Probabilistic methods

n The power system concerning many uncertainties from, for example, loadvarying, random occurrence of faults, dispatching of transmission line,operation of control system, and variation of generation such as renewablesources especially wind power.

n Spectrum of these uncertainties varies from very low frequency (~0-0.1 Hz)to high frequency (up to 3kHz) with small or large scale affecting tooperating condition differently.

n To incorporate the real random nature of the complex power system,probabilistic methods were developed and applied for studying the effects ofrandom fluctuated variables.




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5.1) Classical probability method for small signal stability analysis

n Small signal (or dynamic) stability (SSS) is based on eigenvalues analysismethod for the linearized equation of the power system.

n Probabilistic method was applied to compute the probability that alleigenvalues (with uncertainty) have negative real part which remains in the

stable region.n For this topic, state space equation are reformed to be

n Unknown uncertainty of eigenvalues () are computed from knownmultivariate random variables of system parameters (Z) , from

n Since rotor angle influenced by load, increasing of loading factor causeeigenvalues (corresponding to rotor angle) move from negative to close

zero. This will increase probability of instability as a result.n Next slide show the process to analyze SSS using classical probabilistic

method.


R. C. Burchett and G. T. Heydt, Probabilistic Methods For Power System Dynamic Stability Studies, IEEE Transactions on PowerApparatus and Systems, Vol. PAS-97, no. 3, May/June 1978.

X=A X &

i ij jS z =


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5.2) Stochastic differential equation (SDE) for dynamic stability analysis

n For any dynamical system that is continuously perturbed by noise,cumulative effect of random variation can finally cause the system away offan equilibrium region and thus instability.

n When the system is perturbed by stochastic variation,

the perturbed differential equation becomes

n For the exit problem, (x) is mean first exit time (MFPT)when x exit from boundary of the domain of attraction ,while at time 0, x .

n (x) is determined from the solution of boundary value

problem as,


d (t)= ( )d d ( )t w t +X X

S.M. Shahidehpour and J. Qiu,Effect of Random Perturbations on the Dynamic Behavior of Power Systems, Illinois Institute ofTechnology, Chicago, IL (U.S.A.), Electric Power Systems Research, 11, 1986.

X(t) is state variablesmatrix

g(X) is boundedfunction matrix

0 is a small realparameter

is diffusion matrix

w(t) is n-dimensional

Weiner process(Brownian motion)

L( (x)) -1 for x =

(x) 0 for x =

2

,, 1 1

L ( ) ( )n n

i j i

i j ii j i

a x g xx x x

= =

+

( ), ,

1*

2i j i ja =


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Conclusion for Stochastic differential equation (SDE) for PS

n However, wind speed varied with space and time and result in different PSDof wind power over a finite range of frequency.

n Therefore, noise intensity and bandwidth will be different depend onlocation, time, wind turbine technology, and wind farm design.

n Noise intensity and bandwidth including wind power in earlier studies stilllack of the details and need more information for several aspects such as

1) Weather or not that only noise intensity and bandwidth parameters areenough for studying various PSD characteristics of wind power2) If enough, how to determine noise intensity and bandwidth with differentrange of frequency and different factors relating. But if not, what else.

3) How to apply SDE with colored noise to analyze dynamics and voltagestability incorporating wind power4) How to determine energy function of SDE applying to the problem of

power quality especially, voltage variation, frequency variation and flicker.


.


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Objectives

To quantitatively assess the effects of wind energy on power quality andstability of the power system using probabilistic methods to incorporate thestochastic characteristics of wind power.

Scopes of thesis1) The probabilistic methods will be developed for the purpose of assessing the

effect of wind power to power quality and stability of the power system toincorporate the stochastic characteristics of winds.

2) The designed power system is based on standard test system as a main partand with case study of Thailand as addition.

3) The wind power system models are from the selection of suitable publishedresearches. Fixed Speed Induction Generator (FSIG) and Dubbly-FedInduction Generator (DFIG) will be used in this research.

6. Objectives and Scopes of thesis


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Scopes of thesis

4) For power system stability analysis, dynamic stability and voltage stabilityare the major part of interest for this research. Theory of StochasticDifferential Equation will be applied for power system stability analysis.

5) For power quality, over/under magnitude from fluctuation of voltage and

frequency are the major part of interest for this research. Monte Carlosimulation and analytical probabilistic method will be used for powerquality analysis.

6) This research is based on simulation method , therefore, measurement cannotbe applied for probabilistic issues.

7) Wind energy potential data is from the reports by ASTAE World Bank and

Energy Ministry of Thailand.8) Wind speed data is from measurement data.

6. Objectives and Scopes of thesis


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Impact of wind power to the power system