improved power quality at pcc of standalone wind …standalone wind energy generating system (wegs)...

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Improved Power Quality at PCC of Standalone Wind-Battery Microgrid Using Improved

Normalized Sign Regressor Adaptive Control

Bhim Singh, Fellow, IEEE Department of Electrical Engineering Indian Institute of Technology, Delhi

New Delhi-110016, India [email protected]

Farheen Chishti, Member, IEEE Department of Electrical Engineering Indian Institute of Technology, Delhi


Shadab Murshid, Member, IEEE Department of Electrical Engineering Indian Institute of Technology, Delhi


Abstract—This paper proposes a new improved normalized

sign regressor least mean square (INSR-LMS) adaptive control for filtering the load current component in order to improve the power quality (PQ) of the voltage profile at the point of common coupling (PCC). The enhanced PQ allows the effective functioning of the sensitive loads connected along with the nonlinear loads at the PCC. The INSR-LMS offers fast convergence to attain the steady state. The wind turbine driven synchronous generator (SG) reference speed is acquired by implementing perturb and observe (P&O) maximum power extraction scheme. A sensor-less vector control scheme is used for speed control of the generator. A prototype of proposed microgrid is developed in the laboratory and tested successfully under steady state and dynamic conditions.

Keywords—INSR-LMS, Wind Turbine Driven SG, BES, Microgrid and Power Quality.

I. INTRODUCTION

The renewable energy sources are the key driver for a clean, pollution free sustainable energy future. They are safe, widely available energy sources when compared with the fossil fuels. Solar photovoltaic (PV), wind, hydro, tidal and geothermal are non-depleting sources and the harnessed energy feeds the escalating demand of power [1]. The economic constraints of the remote areas and islands, vulnerability to oil price and supply disruptions, are the basic factors that lead to divergence towards the renewables. The standalone wind energy generating system (WEGS) provides cost effective energy future for islands and rural areas [2-3]. The intermittency of variable wind speed, hampers the sound provision of the power flow on networks and imposes the necessity of energy storage. The energy balance between load and the wind generation, is fulfilled at all times by using battery energy storage (BES). It provides power reliability as well as power quality improvement. BES enables energy time shifting at times of excess generation and releases energy at times of peak load demand [4]. The wind generation does not always coincide with the peak demand. So, BES integration with the standalone wind energy generating system, becomes a must especially in the case, when diesel engine is not present as the backup [5].

The variability of wind leads to harmonic pollution and power fluctuations that need to be mitigated. The variable speed WEGS entirely eliminates the high frequency fluctuation in active power when operated in the variable speed operation with the help of two back to back voltage source converters (VSCs) namely machine side VSC (MVSC) and load side VSC (LVSC) [6]. The customers polluting nonlinear loads often interact with the system components and distort the voltage at the point of common coupling (PCC). With the distorted supply voltage, the

devices connected at the PCC draw non sinusoidal currents that are different than the sinusoidal voltage condition. The after effects include, extra heating due to extra losses and early aging of the components. The malfunctioning of the sensitive loads or medical diagnostics machines such as, X-rays, computed tomography (CT) scans, finely calibrated magnetic resonance imaging (MRI) machines can lead to a matter of life and death of the patients when connected at the PCC with distorted voltage. These equipment are made to run with complete reliability at all times and with improved quality [7]. With the advancement of technology, the sensitive devices with sophisticated process control render the need of an active PCC voltage power quality restoring strategy. The issue of improving the power quality at PCC of standalone microgrid has not been addressed yet.

This paper proposes a novel technique for improving the voltage profile at PCC by filtering the load current. However, the filtering can be implemented by using a number of control schemes, which are existing in the literature. The conventional control schemes can be enumerated as synchronous reference frame theory (SRFT) [8], improved linear sinusoidal tracer (ILST) [9], enhanced phase locked loop (EPLL) [10], observer based filters [11] and adaptive linear neural network based filters [12]. Adaptive filtering techniques such as, least mean square (LMS) and least mean fourth (LMF) [13], have paved their way in tracking the characteristics and filter parameters in the changing environment. The LMS technique has the drawback that the steady state performance is not attained with the environment having low signal to noise ratios (SNR). It acts like a lower order adaptive filter. LMF technique acts as a higher order filter with the mean square error (MSE) considerably less as compared to the LMS. The MSE is the parameter that defines the performance of the algorithm.

An improved normalized signed regressor-LMS (INSR-LMS) based control algorithm, which is a variant of adaptive filtering technique is proposed in this work for filtering the load current component. The INSR-LMS reduces the complexity of the LMS algorithm. This reduction is done by clipping the input data. The clipped sample is used to update the coefficients only when the absolute value of the input samples is higher than the average values of the absolute value of the input samples. It provides better convergence than the conventional signed regressor (SR) algorithm. The filtering of load current improves the total harmonic distortion (THD) of the PCC voltage. The filtered load current along with the reference current is used for generating the switching pulses for the LVSC. Owing to the simple organization and easy implementation, conventional

Proceedings of the National Power Systems Conference (NPSC) - 2018, December 14-16, NIT Tiruchirappalli, India

2

Fig. 1 System configuration

field oriented control (FOC) technique utilizing proportional and integral (PI) controller is used for controlling the speed of the generator by acquiring the switching pulses for MVSC [14]. Due to the non-linear speed-torque characteristics of the wind turbine generator, the reference SG speed is determined by the wind maximum power point (MPP) extraction techniques. The simplicity of implementation and freedom from dependence on system parameters, have led to the use of perturb and observe (P&O) MPP technique [15]. In order to determine the optimal power, the generator speed is perturbed in the direction of the MPP. For the estimation of the actual speed of the SG, back electromotive force (BEMF) sensorless speed and rotor position estimation techniques, are adopted from the optimized cost and performance view point. It has simple structure and does not rely on intense complex observers for computation [16].

II. SYSTEM CONFIGURATION

Fig. 1 shows the system configuration of a standalone wind-BES based microgrid system. The wind turbine driven SG is used for feeding the single phase nonlinear load. The torque ripples due to variability of wind speed is absorbed by using the back to back connected VSCs. The BES provides the deficit power to the load when wind generation is low and absorbs the excess power at times of superfluous generation. The ripple filter removes the switching harmonics as well as the smoothening of the load current is apparently done by using interfacing inductors connected in series with the single phase nonlinear load.

III. CONTROL METHODOLOGY

The proposed wind-BES based microgrid system implements control for the LVSC and MVSC for effective functioning under variable wind speeds and load removal and insertion.

A. Voltage Control for Switching of LVSC

Fig. 2 shows the control structure of the LVSC.

s ss s 2

s

e (n) sign [u (n)]w (n+1)=w (n)+μ

ξ+||u (n)||

sL s s i =w *u

Fig. 2 Control structure for LVSC

Here, the load voltage is sensed and compared with the reference voltage (vL

*) and an error is generated (verror). The reference voltage is generated by the given condition as,

vL* =vmsinωt (1)

*error L Lv = v -v (2)

verror is fed to the PI controller to generate reference load current (iLref). The governing equation of the PI controller is given as,

Lref Lref i error error p errori (n) = i (n-1)+k v (n)-v (n-1) +k v (n) (3)

1. Improved Normalized Sign Regressor Least Mean Square Algorithm

The adaptive controls have been used in numerous applications for noise cancellation, signal detection and harmonic compensation. The INSR-LMS adaptive algorithm is used for filtering the load current component so that the PCC voltage profile is improved. The unit template is estimated as,

' L

t

vu =

Vs (4)

where, vL is the sensed load voltage and Vt is the terminal voltage maintained at 220V root mean square (RMS). The fundamental weight component ‘ws’ is evaluated as,

's

s s 2s

e (n) sign [u (n)]w (n+1)=w (n)+μ

ξ+||u (n)||s (5)

2 ' T||u (n)|| =u (n) u (n)s s s (6)

where, ‘ξ’ is a small positive number that avoids the division by zero at times when the signal attains a small value or is zero and ‘es’ is the error adaptation component, which is calculated as,

s L s se =i (n)-(u (n)*w (n)) (7)

The active filtered component of load current (isL) is calculated as,

sL s si =w *u (8)

The updation of the coefficients takes place as, L-11'u (n-1)=sign[u (n-1),|u (n-1)|³ |u (n-j)|s s s sLj=0 (9)

L-11'u (n-1)=0,|u (n-1)|< |u (n-j)|s s sLj=0 (10)

' ' ' ' Tu (n)=u (n),u (n-1),...u (n-L+1)s s s s (11)


3

2 2r r d q q

d refd

λ - λ -4L L iI =

2L

Fig. 3 Control structure for MVSC.

where, ‘L’ is the number of filter weights. The computational complexity of the proposed INSR-LMS is same as the conventional SR-LMS but the convergence performance in attaining the steady state is faster. The reference load current (iLref) along with the filtered load current (isL) is fed to the hysteresis current controller for generating the switching signals (S1 to S4) for the LVSC.

B. Switching Control of MVSC

Fig. 3 shows the switching control logic used for the obtaining the switching pulses for MVSC. The control is segregated into three subsections. First is to determine the quadrature axis reference current (Iq ref), second is to generate direct axis reference current (Id ref) and third is to obtain the switching signals (SSG1 to SSG6) for MVSC. The FOC is used for instantaneous torque control of the wind turbine driven SG. Maximum power from wind, is attained by effectively implementing P&O MPP tracking technique. BEMF is used for the sensorless generator speed and rotor position estimation.

1) Generation of Iq ref

The wind P&O tracking technique is used for obtaining the reference SG speed (ωgen ref). The optimal power point is tracked through perturbation in estimated generator speed (ωgen est) and SG generated power (Pgen). The governing equations for wind P&O algorithm are as,

gen gen est

gen ref gen ref gengen gen est

ΔP >0 and Δω >0ω (n)=ω (n-1)+Δω ; if

ΔP <0 and Δω <0

(12)

gen gen est

gen ref gen ref gengen gen est

ΔP >0 and Δω <0ω (n)=ω (n-1)-Δω ; if

ΔP <0 and Δω >0

(13)

The ωgen ref is compared with ωgen est to obtain the speed error (ωerror) and is given as,

error gen ref gen estω (n)=ω (n)-ω (n) (14)

2) Generation of Id ref

The control of Id ref is carried out in a way that unity power factor (UPF) is maintained at the SG stator terminals. UPF is attained by keeping the stator power factor angle (ϕs) as zero. For calculating Id ref in order to maintain UPF, the given condition should be fulfilled,

s v i=θ -θ =0φ (15)

The value of Id ref is calculated as, 2 2

r r d q q

d refd

λ - λ -4L L iI =

2L (16)

where, λr is the rotor flux linkage, Ld is the d-axis inductance and Lq is the q-axis inductance.

3) Generation Switching Pulses for MVSC

The reference stator currents (ia ref, ib ref, ic ref), are generated using inverse Park’s transform (dq0 to abc) with Id ref and Iq ref as the inputs. The reference currents (ia ref, ib ref, ic ref) and the sensed SG stator currents (igen a, igen b, igen c) are fed to the hysteresis current controller for generating the switching pulses (SSG1-SSG6) for MVSC.

IV. EXPERIMENTAL RESULTS

The experimental validation of the standalone wind-battery microgrid, is performed on a laboratory developed prototype. The prototype contains two back to back connected VSCs (SEMIKRON make), a salient pole SG (BENLEC make) coupled with a DC motor (BENLEC make). The DC motor is emulated as the wind turbine. The currents and voltages of the SG, load, and battery along with the DC link voltage are measured using Hall-Effect based voltage sensors (LV25-P) and Hall-Effect based current sensors (LA55-P). The opto-coupler provides the optical isolation between the converter signals and the digital signal processor (DSP) signals. The DSP (Micro Lab Box) is used for the execution of control algorithms. The detailed specifications of standalone wind-battery microgrid system used for hardware validation, are given in Appendices. The experimental performance of the microgrid system is discussed in the following sections.

A. Steady State Response of the System

The standalone microgrid using wind turbine driven SG and battery directly at the DC link, is tested for two wind speeds that is 7.2m/s (above cut-in) and 12m/s (cut-off). The response of the SG current and the estimated generator speed (ωgen est) for two wind speeds is shown in Figs. 4 (a-b). The SG currents are sinusoidal and balanced whereas the current magnitude changes with respect to the change in power generation (Pgen) according to the wind speeds. Figs. 4 (c-d) depict the performance of the system with ωgen est, SG current (igena) and the estimated rotor position (θest) under variable wind speeds. With higher speeds of wind, the turbine rotates faster while increasing the speed of rotation of the SG and power generation. So, the currents magnitude rise with rise in ωgen est. Figs. 5 (a-d) demonstrate the waveform of voltage and current of load, power consumed by the nonlinear load, harmonic spectrum of load voltage.


4

(a) (b)

(c) (d)

Fig. 4 Steady state performance of the system under vwind of 7.2m/s and 12m/s

(a) (b)

(c) (d)

Fig. 5 Load response under steady state (a-b) load voltage and current waveform; (c-d) harmonic spectrum of load voltage and current

The total harmonic distortion (THD) is found 2.3% which is within 5%i.e. it satisfies the IEEE-519 standard.

B. Dynamic Response of the System

The proposed microgrid system is tested for the dynamic conditions including wind speed variability and load removal and insertion and the results are demonstrated as follows.

1) At wind speed change

The wind speeds are unpredictable. The proposed system is tested for wind speed change from 7.2m/s to 12m/s or vice-versa. When wind speed rises from 7.2m/s to 12m/s, the generation rises simultaneously as ωgen est rises. The rise of vwind, SG currents (igena, igenb, igenc) and ωgen est is shown from Figs. 6 (a-b). The direct axis (Id) and quadrature axis (Iq) currents rise w.r.t the rise in vwind and is demonstrated in Fig. 6 (c). The battery current (Ibat) rise in negative direction (showing charging) at the maximum wind speed. Fig. 6 (d) shows that the generation is maximum and the leftover power after fulfilling the load demand is fed to the battery. Fig. 6 (e) demonstrates that, on the fall of wind speed (i.e. 12m/s to

7.2m/s), the battery discharges to meet the load demand. The battery current (Ibat) and power (Pbat) rises in positive direction (showing discharging). The DC link voltage is maintained constant. Fig. 6 (f) shows the performance when the wind speed is below cut-in. The wind speed is too low to produce the useful power. So, the generation from the wind turbine driven SG is stopped and is considered as zero. The insufficiency of power is provided by the discharging of the battery. The power variations of the same can be seen from Figs. 6 (g-h).

2) At Load Removal/Insertion

Due to sudden removal of the load, the wind generating operating at its maximum wind speed, feeds the excess power into the battery. The load current becomes zero. As soon as the load is recovered and inserted again, the battery discharges and the load currents are maintained.

(a) (b)

(c) (d)

(e) (f)

(g) (h)

Fig. 6 Dynamic response of the system under changing vwind

(a) (b)

(c) (d)

Fig. 7 Dynamic response of the system under load removal and insertion


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This can be seen from Figs. 7 (a-b).The power variations of the load (PLoad) and battery (Pbat) can be seen from Figs. 7 (c-d). As the load is removed, the load power becomes zero, the battery power and current rise in negative direction (showing charging) maintaining the DC link constant and vice versa.

3) Battery Response

Figs. 8 (a-b) show the battery voltage, currents and power, when the wind speeds are high (12m/s), providing maximum generation feeding the load and battery. Figs. 8 (c-d) show the performance of the battery in the case when the load is removed suddenly and the generated wind power is fed into the battery for storage. The battery power rises to 2.20 kW (negative sign shows that the power is fed). Figs. 8 (e-f) illustrate that the case, when the wind speeds are too low and are unable to imitate the wind generation. The power from the wind is considered zero and the battery has to fulfill the load demand. The battery discharges by 843W to fulfill the load demand.

4) THD Analysis

Owing to the nonlinear load connected at the PCC, the THD of the PCC voltage (vPCC) can be seen above 5% in the case, when the sensed load current is fed directly to the control of LVSC for the generation of switching signals. But

(a) (b)

(c) (d)

(e) (f)

Fig. 8 Response of the battery under (a-b) wind generator is feeding the load and battery; (c-d) load is removed and wind generator feeds the battery; (e-f) wind generator is off and battery feeds the load.

(a)

(b) Fig. 9 Signal waveform and harmonic spectrum of load current (a) without control; (b) with INSR-LMS adaptive control

the THD is reduced below 5%, when the load current if filtered using INSR-LMS adaptive control. The harmonics that deteriorate the power quality at the PCC, are filtered successfully and can be seen from Figs. 9 (a-b).

V. CONCLUSION

The aim for reducing the harmonic content at the PCC and improving the voltage profile of the PCC is attained successfully by implementing the INSR-LMS adaptive control for filtering the load current. The sensitive loads connected at the PCC draw sinusoidal currents from the system as the distorted voltage due to nonlinear loads is being filtered and made free from harmonics. The power quality is improved and the sensitive equipment connected at the PCC perform under safe conditions. The effectiveness of the control algorithms for the MVSC and LVSC are validated through the extensive tests that are performed on the developed prototype. The proposed system performs satisfactorily under steady state and dynamic conditions.

ACKNOWLEDGMENT

The authors are thankful to Govt. of India for financially supporting this work under FIST scheme (Grant Number: RP03195), under the Grant Number: RP02979 (RESCUES Project) and JC Bose fellowship (Grant Number: RP03128).

APPENDICES

System Parameters: SG: 5hp, 415V, Rs = 3.1Ω, If = 1.4A, Pole pairs= 2; Wind speed range = 7m/s (cut-in) to 12m/s (cut-out); ripple filter: Rf = 5Ω, Cf = 10 µF; Shunt type DC machine parameters: 220V, 19A, 5hp; SG field excitation voltage: 220 V; DC bus voltage: Vdc = 360V; battery parameters=360V, 50 Ah; controller parameters: ξ=0.01 and μ=0.00002, single phase nonlinear load = 743W.

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improved power quality at pcc of standalone wind …standalone wind energy generating system (wegs)...

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