A. Izadian and Dan Shen are with Purdue School of Engineering and Technology, Indianapolis, IN. 46202. E-mail: aizadian@iupui.edu.

Ping Liao is with the Mechanical Engineering Department at Nantong University, Nantong, Jiangsu, China, 226019. liao.p@ntu.edu.cn.

A Hybrid Wind-Solar-Storage Energy Generation System Configuration and Control

Dan Shen1,2, Afshin Izadian1, Senior Member, IEEE, Ping Liao2 1 Energy Systems and Power Electronics Laboratory

Purdue School of Engineering and Technology, Indianapolis 46202, USA 2 Mechanical Engineering, Nantong University, Nantong, Jiangsu 226019, China

Abstract—This paper proposes a standalone distributed

hybrid power system which consists of solar power, wind power, battery storage and the load. A control strategy is introduced to maximize the simultaneous energy harvesting from both renewable sources. The controller results in five contingencies considering the level of power generation available at each renewable energy source and the state of charge in the battery. Power converters interface the source with a common DC bus. The interfacing converter is controlled either as a current or a voltage source. A supervisory controller is proposed to accomplish the source type allocations and balance of energy in the operating contingencies. Simulation results demonstrate accurate operation of the supervisory controller and functionality of the maximum power point tracking algorithm in each operating condition both for solar and for wind power.

I. INTRODUCTION Compared with other renewables, wind and solar have

been established as proven future sources of energy, because of their environment-friendly, safe and cost-effective characteristics. However, there are some difficulties associated with combined utilization of solar and wind, e.g. intermittency of wind and instability of the grid[1]. For this purpose, advanced network of multiple renewable energy systems with storage units have been proposed [2],[3]. Small-scale standalone combination of solar, wind and battery has been found effective in remote areas[4]. Simultaneous intermittency of wind and solar can be compensated by use of energy storage devices[5]. Several designs have used a power converter interface in the battery connection to control the charge-discharge process of the battery. However, a battery can be directly connected to the DC bus and be controlled by limited variation of DC bus voltage. The power converters interfacing the wind and solar can inject the power as a current source or voltage source. Supervisory controller determines the source type according to the availability and rating of the power. As the DC bus voltage floats, the battery can be charged or discharged. A designated voltage source (either wind or solar) will be controlled to charge the battery as the desired rate. When both sources are controlled to inject current, the bus voltage is determined by the battery terminals. Thus, the strategy of the supervisory controller is to satisfy the power required by the load and manage the state of battery. This new hybrid system improves the stability and reliability of power supply [6],[7],[8]. Maximum power point tracking is continuously operated to maximize the power from wind and

solar. In this paper, the perturb and observe P&O method is used on both the solar and wind power sources [9],[10].

This paper is organized as follows: Proposed hybrid energy generation unit are given in section II. The MPPT for Solar system and wind energy system are introduced in Section Ⅲ . Section IV describes supervisory control strategy .Section Ⅵ represents some simulation results.

II. HYBRID ENERGY GENERATION UNIT Fig.1 depicts the proposed topology of combined power

sources consisting of solar, wind and battery with two stage DC-DC converters to interface the load. There are two main branches in the system, thus two new energy sources can compensate each other to some extent under different climates. The first stage converters are controlled by MPPT controller and capture the maximum power from wind and solar respectively. The second stage converters are controlled by local controller as a constant voltage sources (CV). The control action as voltage source is determined by the supervisory controller. Each power system branch runs a maximum-power-point tracking (MPPT) algorithm and receives the voltage and current references from the supervisory controller.

Both energy sources are connected in parallel to a common dc bus through their individual dc-dc converters. The load and battery are directly connected to dc bus. CV controller creates a controlled voltage source [11],[12],[13] to inject current to the system and maintain the voltage.

Fig. 1. Proposed hybrid energy generation system

III. MPPT FOR SOLAR AND WIND POWER SYSTEM To make the high cost of solar power, constant search for maximum power point generation is necessary. Maximum power point tracking is a mechanism to set the voltage output

978-1-4799-5776-7/14/$31.00 ©2014 IEEE 436

of the solar-connected converter to maxigeneration. However, as the system under Mas a voltage source, the set voltage referencmay become different that of the source set The supervisory controller may override theto guarantee the stability of voltage at the DCthe energy generation from the solar panelmaximum power point rendering achievemensolution. A PV module has been modeled inThe simulation parameters setting of PV pTable I.

TABLE I. THE SIMULATION PARAMETERS SETTING OF

Voc Isc Vm Im Pm Rs 129V 19.2A 105.6V 17.1A 1800W 0.2Ω

In the table, Voc is the open circuit voltacircuit current, Vm and Im are the nominal voPm in the nominal power, Rs is the series resTref is the reference temperature and Rref is tpanel. Figures 2 shows the (P-V) curves ofdifferent solar illumination intensity levels.

As Figure 2 shows, there is a strong nonin the P-V curve. The output power has onpower point (MPP) under every specific solaFigure 3, the MPP can be captured by tuningregulating the converter. Thus, the solarachieved through adjusting load resistance ato internal resistance of power source.

Fig. 2. P-V characteristics of PV model.

DC/DC Converter

PPV

IPV

VPV VLoa

Fig. 3. Basic diagram of solar MPPT controller.

Figure 4 demonstrates the algorithm ofmethod[14], [15] .

imize the energy MPPT is controlled

ce of solar source as voltage source.

e MPPT algorithm C bus. In this case, l is deviated from nt of a sub-optimal

n Matlab/Simulink. panel are listed in

F PV PANEL

Tref Rref25 1000W/m2

age, Isc is the short ltage and currents. istance of the cell,

the radiation at the f the PV model at

nlinear relationship nly one maximum ar radiation. In the

g the controller and r MPPT will be s close as possible

RLoad

ILoad

ad

PLoad

f the solar P&O

P(k)

Sear

CalcP(k)

ΔD>0

P(k)

V(k)-V(k-1)<0?

ΔD<0

YES

NO

YES NO

Fig. 4. Flow chart of solar MPPT algori

Simulations of PV MPPT ptemperature is 25 has been depicts the variation of peirradiance changing from 600come back to 600W/m2, whicbest duty ratio when the radiFigure 5.b shows, the maximumapproximately 1010W, 1400Wradiances are 600W/m2, 800W/

a. Perturbation signal.

b. MPPT tracking effect.

Fig. 5. PV MPPT Profile to step cha1000w/m2 to 600W/m2.

Start

)-P(k-1)=0?

rch V(k),I(k)

culate Power)=V(k)*I(k)

Return

)-P(k-1)>0?

V(k)-V(k-1)>0?

ΔD<00 ΔD>0

YES

YESNO

ithm.

profile for a 30Ω load when the shown in Figure 5. Figure 5.a

erturbation signal during the 0W/m2 to 1000W/m2 and then ch oscillates slightly around the iation changes quickly. As the m power points of PV model are W and 1800W when the solar /m2 and 1000W/m2 respectively.

ange in the irradiance from 600w/m2 to

437

At the wind energy system, a typicalsystem consists of wind turbine and dc geturbine converts wind energy into mechanicathe generator converts the mechanical enenergy. The fundamental equation of the relwind turbine output power and wind speed is P ,

where, ρ=1.025kg/m3 is air density (kg/mswept by rotor blads, V is the velocity of airpower coefficient of wind turbine. The tip spcan be expressed as follows: λ , ,

. . .

In the above formula, ω is the rotor spee(rad/s), n is the rotational speed of wind turbradius of wind turbine (R=2.5m in this papinformation in Matlab [14-15], C1=0.5176，，C4=5，C5=21，C6=0.0068.

The proposed wind power system in thisa fixed pitch angle 0°and variable speedpermanent magnet synchronous generatordiode brige rectifier was used to convert the wind turbine and PMSG connect directly wthe wind turbine torque and rotor speed generator torque and rotor speed. Figucharacteristics of the wind turbine power vs. Figure 6 the maximum power under differproduced at different rotor speeds. Thus, tracking the MPP for wind turbine is to carotor speed for every wind speed.

Fig. 6. Wind turbine power vs. rotor speed.

In wind power, the P&O method is basedturbine shaft speed with small steps and obseturbine output power changes. The concediagram of P&O method of wind are illustThe details of P&O method are presenteinterested readers. To enforce the P&O me

l wind generation enerator, the wind al energy and then

nergy into electric lationship between given by:

(1)

m3), A is the area r (m/sec), Cp is the peed ratio λ and Cp

(2)

, (3)

(4)

ed of wind turbine bine (r/s), R is the er), from the help C2=116，C3=0.4

s paper consists of d wind turbine, a r (PMSG) and a power to DC. The

without gearbox so are equal to the

ure 6 shows the rotor speed. From ent wind speed is the key point of

apture the optimal

d on perturbing the erving the resulting ept and schematic trated in Figure 7. ed in [16,17] for ethod, the signs of

ΔWT and ΔPT.ΔWT are ovoltage change command and o

Fig.7. P&O method of wind system. (aprinciple of P&O method. (b) Block

According to the principleP&O method for wind MPPT the duty cycle of the SEPIC conand keep the maximum Cp. Figof rotor speed when tuning the

Fig. 8. Configuration of proposed hybri

As can be seen in Figure constant, the MPPT control categorized into four circumstan

(1)

(3) Fig.9. MPPT strategy for wind pow

bserved [18]-[19] similar to a observance of power variation.

a) Turbine power versus shaft speed and k diagram of the P&O control in wind.

e of conservation of energy the can be accomplished by tuning

nverter to change the rotor speed gure 8 demonstrates the variation duty cycle.

id new energy system.

9, assuming the wind speed is for wind system can also be nces:

(2)

(4)

wer system.

438

1. Pk>Pk-1 and ωk>ωk-1, the output power at k moment is larger than that of k-1 moment, so the operating point is at the left side of MPP. ωk>ωk-1 means that the rotor speed increases, so the last duty cycle perturbation is negative. This causes that the next perturbation become negative;

2. Pk<Pk-1 and ωk<ωk-1, the output power at k moment is less than that of k-1 moment, so the operating point is at the left side of MPP. ωk<ωk-1 means that rotor speed decreases, so the last duty cycle perturbation is positive. This causes that the next perturbation to become negative;

3. Pk>Pk-1 and ωk<ωk-1, the output power at k moment is larger than that of k-1 moment, so the operating point is at the right side of MPP. ωk<ωk-1 means that rotor speed decreases, so the last duty cycle perturbation is positive. This causes that the next perturbation become positive;

4. Pk<Pk-1 and ωk>ωk-1, the output power at k moment is less than that of k-1 moment, so the operating point is at the right side of MPP. ωk>ωk-1 means that rotor speed increases, so the last duty cycle perturbation is nagative. This causes that the next perturbation to become positive.

Simulations of wind MPPT profile for a 30Ω load with wind speed variation from 4m/s to 12m/s are illustrated in Figures 10 and 11. Figures 10 and 11 depict the wind maximum power point tracking effects when the wind speed changed from 4m/s to 8m/s to 4m/s, and 8m/s to 12m/s to 8m/s respectively. The figure also shows the output power generated directly from wind turbine and the actual power captured at the load.

Fig. 10. Wind MPPT tracking profile to step change in the wind speed from 4m/s to 8m/s to 4m/s.

Fig. 11. Wind MPPT tracking profile to step change in the wind speed from 8m/s to 12m/s to 8m/s.

IV. SUPERVISORY CONTROL STRATEGY In a DC-system fed by multiple converters on a common

bus, current must be shared among all sources according to their available power while ensuring the stability of the bus voltage. Therefore, a supervisory control is designed to set the voltage of DC bus and manage the power among sources and storage devices. Considering the wind, solar and a storage system feeding a common load, several contingencies may occur which are listed in Table II. Since the battery storage is directly connected to the DC bus, the supervisory controller can charge or discharge it by setting the DC bus voltage slightly higher or lower than the battery terminal voltage. To charge the battery, the converter of another source such as wind or solar must be controlled as a voltage source while the other is controlled as a current source. This decision is based on the amount of power each source is instantaneously generating. When the battery is fully charged and is required to feed the load, the battery maintains the voltage while other converters are controlled as a current source. A smooth transition from voltage to current source by the use of local controllers results in high performance and efficient controls [20, 21]. The net power that battery needs to provide,ΔP ,can be obtained from the renewable energy and load power deficit as follows:

,s w loadP P P PΔ = + − (5) where Ps is the output power of solar, Pw is the output power of wind, Pload is the power demand from load. The supervision mode is shown in Table II which can be stated as follow: If PΔ is greater than zero and SOC is not higher than 90%, then the net power will be used to charge the battery; When PΔ is greater than zero and SOC is higher than 90%, then no MPPT control on both wind and solar system will be required; When PΔ is zero, battery should be disconnected as a backup power and no MPPT control on both wind and solar system will be required; In case PΔ is less than zero and SOC is higher than 40%, battery will be discharged to satisfy the load power demand; In the worst case, i.e. PΔ is less than zero and SOC is lower than 40%, the load can be disconnected and the available energy is used to charge the battery. In extreme weather conditions, a dump load is required to consume the extra power generated form the sources.

Table II. Contingencies in supervisory control of hybrid wind-solar-battery energy generation system.

Mode Condition Control Action

1 ΔP>0,SOC≤90% Charge battery, Feeding Load

2 ΔP>0, SOC>90% Feeding Load, OFF Battery (No MPPT)

3 ΔP=0 Feeding Load, OFF Battery (No MPPT)

4 ΔP<0, SOC>40% Battery discharge to satisfy the load OFF wind and solar

5 ΔP<0, SOC<40% OFF Load, Just charge Battery

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V. SIMULATION RESULTS A. Control for cascaded boost converter in solar system

As can be seen in Figure 1, the configuration of two stage boost converter has been accomplished in solar system. The first stage converter is operated by solar MPPT controller and captures the maximum power delivered from solar panel under different illumination intensities. The second stage converter is regulated through an adaptive voltage controller which is designed for fixed voltage control at the output of solar subsystem. The simulation results that demonstrate the solar MPPT and voltage control for a 30 Ω load are shown in Figure 12. Fig. 12(a) depicts the solar system running at maximum power point tracking mode when the solar irradiance is 1100W/m2. The output voltage tracking was shown in Fig. 12(b), with the step change in reference voltage from 240V to 220V, the output voltage is tracked and fixed at the required voltage level.

(a) MPPT Profile

(b) Output voltage tracking.

Fig. 12. Control for cascaded boost converter

B. Control for cascaded converter in wind system

Similar to solar system, the wind system consists of two stage converters. The first stage SEPIC converter works for the maximum power tracking by using the wind MPPT controller and the second stage boost converter is also regulated by an adaptive voltage controller to realize the output voltage control in the wind subsystem.

With the pitch angle 0 degree and output resistor is 30 Ω, the power coefficient of wind turbine and voltage control of wind system when wind speed is 7m/s are illustrated in Figure 13. In this case, Cp is always fixed at the maximum value 0.48 and the output voltage can also be controlled around 240V as required by battery.

(a) Control of Cp

(b) Output voltage control around 240V

Fig. 13. Control for cascaded converter in wind system.

C. Control for combined system

Some simulation results which reflect the MPPT performance of combined system are also demonstrated in Figure 14.

(a) MPPT Tracking profile for combined power system (OFF battery).

(b) SOC (battery discharge).

(c) Battery discharge to satisfy the load.

0 2 4 6 8 10 12 14

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v=8m/sR=1000W/m2

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(d) Charge battery.

Fig. 14. Power management of combined renewable energy system.

Figure. 14(a) depicts the mode 2 of the hybrid system in the Table II, battery should be turned off because it has been fully charged. Wind power and solar power should also be controlled in MPPT mode or power tracking mode according to the instantaneous power generated from each renewable sources. At first, ΔP is less than zero, so both the wind power and solar power run at MPPT mode and deliver as much energy as they can; then with the step increment of solar irradiance, the solar power operates at power tracking mode and wind power is still under MPPT mode to satisfy the load demand. Figure. 14(b) and (c) demonstrate mode 4 of hybrid system. In this contingency,ΔP is less than zero and SOC of battery is 70% (larger than 40%), therefore the wind power and the solar power should be turned off and just discharge the battery to satisfy the 5 HP load power. In the Figure 14(d), mode 5 of hybrid energy system is illustrated. Due to negative ΔP and the SOC < 40%, the load should be closed and system charge the battery by using the power generated from wind and solar, the setting of DC bus voltage around 240V, higher than the battery terminal voltage.

VI. CONCLUSION This paper was focused on the configuration of wind

turbine and solar panel and MPPT control methods for a combined wind-solar-battery power generation system. Models of a horizontal axis wind turbine and a PV array and their MPPT power tracking controllers and adaptive voltage controllers and supervisory controller were built in Matlab/Simulink. The P&O method was utilized in both wind power and solar power, which demonstrated a stable and effective tracking performance under the variation of wind speed and solar illumination. A supervisory control strategy was proposed to generate the maximum power from these renewable energy sources and battery while connected to a common coupling point. A robust and smooth switching from MPPT to power tracking mode was obtained in both power sources. Simulation results demonstrated an accurate operation and applicability of the proposed method.

REFERENCES [1] R. G. Wandhare and V. Agarwal, "Novel control scheme

to reduce the effect of intermittent solar radiation on the grid connected PV system power output without losing MPPT," in Applied Power Electronics Conference and Exposition (APEC), 2012 Twenty-Seventh Annual IEEE, 2012, pp. 79-85.

[2] A. M. Gee, F. V. Robinson, and R. W. Dunn, "Analysis of battery lifetime extension in a small-scale wind-energy system using supercapacitors," 2013.

[3] A. Barchowsky, J. P. Parvin, G. F. Reed, M. J. Korytowski, and B. M. Grainger, "A comparative study of MPPT methods for distributed photovoltaic generation," in Innovative Smart Grid Technologies (ISGT), 2012 IEEE PES, 2012, pp. 1-7.

[4] H. Fargli, F. Fahmy, and M. EL-Sayed, "Artificial Intelligence Techniques for Controlling PV-Wind Powered Rural Zone in Egypt," in International Conference on Renewable Energies and Power Quality (ICREPQ’09). Valencia (Spain), 15th-17th April, 2009.

[5] N. A. Ahmed and M. Miyatake, "A stand-alone hybrid generation system combining solar photovoltaic and wind turbine with simple maximum power point tracking control," in Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International, 2006, pp. 1-7.

[6] M. Cirstea and A. Parera-Ruiz, "An FPGA controller for a combined solar/wind power system," in Optimization of Electrical and Electronic Equipment (OPTIM), 2010 12th International Conference on, 2010, pp. 1103-1108.

[7] R. G. Wandhare and V. Agarwal, "A control strategy to reduce the effect of intermittent solar radiation and wind velocity in the hybrid photovoltaic/wind SCIG system without losing MPPT," in Photovoltaic Specialists Conference (PVSC), 2012 38th IEEE, 2012, pp. 001399-001404.

[8] F. Nejabatkhah, S. Danyali, S. H. Hosseini, M. Sabahi, and S. M. Niapour, "Modeling and Control of a New Three-Input DC–DC Boost Converter for Hybrid PV/FC/Battery Power System," Power Electronics, IEEE Transactions on, vol. 27, pp. 2309-2324, 2012.

[9] W. Xiao and W. G. Dunford, "A modified adaptive hill climbing MPPT method for photovoltaic power systems," in Power Electronics Specialists Conference, 2004. PESC 04. 2004 IEEE 35th Annual, 2004, pp. 1957-1963.

[10] B. Subudhi and R. Pradhan, "A comparative study on maximum power point tracking techniques for photovoltaic power systems," 2013.

[11] A. Traca de Almeida, A. Martins, H. Jesus, and J. Climaco, "Source reliability in a combined wind-solar-hydro system," Power Apparatus and Systems, IEEE Transactions on, pp. 1515-1520, 1983.

[12] C. Liu, K. Chau, and X. Zhang, "An efficient wind–photovoltaic hybrid generation system using doubly excited permanent-magnet brushless machine," Industrial Electronics, IEEE Transactions on, vol. 57, pp. 831-839, 2010.

[13] W.-M. Lin, C.-M. Hong, and C.-H. Chen, "Neural-network-based MPPT control of a stand-alone hybrid power generation system," Power Electronics, IEEE Transactions on, vol. 26, pp. 3571-3581, 2011.

[14] F. Liu, S. Duan, F. Liu, B. Liu, and Y. Kang, "A variable step size INC MPPT method for PV systems," Industrial Electronics, IEEE Transactions on, vol. 55, pp. 2622-2628, 2008.

[15] M. Veerachary, "Power tracking for nonlinear PV sources with coupled inductor SEPIC converter," Aerospace and Electronic Systems, IEEE Transactions on, vol. 41, pp. 1019-1029, 2005.

[16] S. Barakati, M. Kazerani, and X. Chen, "A new wind turbine generation system based on matrix converter," in Power Engineering Society General Meeting, 2005. IEEE, 2005, pp. 2083-2089.

0 0.5 1 1.5 2 2.5 3 3.5 4

x 105

100

120

140

160

180

200

220

240

260

Time(1e-6s)

Vol

tage

(V)

Charge battery

dc bus voltage

Battery terminal voltage(SOC=30%)

441

[17] S. M. Barakati, M. Kazerani, and J. D. Aplevich, "Maximum power tracking control for a wind turbine system including a matrix converter," Energy Conversion, IEEE Transactions on, vol. 24, pp. 705-713, 2009.

[18] G. Hua and Y. Geng, "A novel control strategy of MPPT taking dynamics of wind turbine into account," in Power Electronics Specialists Conference, 2006. PESC'06. 37th IEEE, 2006, pp. 1-6.

[19] K.-H. Kim, D.-C. Lee, and J.-M. Kim, "Fast tracking control for maximum output power in wind turbine

systems," in Universities Power Engineering Conference (AUPEC), 2010 20th Australasian, 2010, pp. 1-5.

[20] T. Dragicevic, J. M. Guerrero, J. C. Vasquez, and D. Skrlec, "Supervisory Control of an Adaptive-Droop Regulated DC Microgrid with Battery Management Capability," 2013.

[21] W. Qi, J. Liu, X. Chen, and P. D. Christofides, "Supervisory predictive control of standalone wind/solar energy generation systems," Control Systems Technology, IEEE Transactions on, vol. 19, pp. 199-207, 2011.

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