Abstract—Compounding the various kinds of power sources

would impact the quality of power supply within the MicroGrid and cause many control problems to be dealt with. This paper focuses on the stability of MicroGrid operation and discusses the control techniques of combining micro turbine and Fuel cell, Hydrogen tank, and Electrolyzer system hybrid System (FHES) to expand the MicroGrid system s ability for solving power quality issue of frequency fluctuation. The paper examines the feasibility of FHES control, especially dynamic control of electrolyzer system, to secure real power balance and enhance the operation capability of handling frequency fluctuation. It is presented that the Proposed PC control and monitoring system can be considered as a means of power quality control to improve the frequency fluctuation caused by a random power fluctuation on generation and load sides and to relax a tie line power flow fluctuation by the frequency one on the interconnected MicroGrid local power system.

Index Terms—power quality control, MicroGrid, renewable energy, electrolyzer system, frequency fluctuation, distributed generation

NOMENCLATURE PCMS PC Control and Monitoring System PQC Power Quality Control CMD Command UG Utility Grid WP Wind Power PV PhotoVoltaic MT Micro Turbine FC Fuel Cell PEMFC Proton Exchange Membrane Fuel Cell HOGEN Hydrogen generator CAN Control Area Network ES Electrolyzer System H2T Hydrogen Tank FHES FC, H2T, and ES hybrid system SoC State of Charge PG Generated real power PL System load PWP Wind power output PPV PV power output

Xiangjun Li, Yu-Jin Song, Soo-Bin Han ware with the National Research

Lib. of Electric Energy and Lighting Center, Korea Institute of Energy Research (KIER), Daejeon, Korea (e-mail: xjli79@hotmail.com).

PFC FC power output PMT MT power output PES Load power of ES PHousing Load power of Housing Pini

WP Initial WP output Pini

PV Initial PV output Pini

MT Initial MT output Pini

FC Initial FC output Pini

ES Initial ES load power Pini

Housing Initial housing load Ptie Tie line power Ptie_ref Scheduled Ptie Xtie Tie line reactance Relative phase angle between UG and MG

f0 System frequency P Real power unbalance P_ref Expected P in MicroGrid f Frequency deviation PPV Change in PV output PFC Change in FC output PMT Change in MT output Ptie Difference between Ptie and Ptie_ref

dPWP Standard deviation for WP output dPPV Standard deviation for PV output dPHousing Standard deviation for housing real power KMT Droop property of MT output M Inertia constant D Damping coefficient KFC Gain for FC KES Gain for ES TFC Time constant of FC TES Time constant of ES Base Base capacity of MicroGrid system Sw. On/Off switch (1 or 0)

I. INTRODUCTION LTHOUGH an effective use of renewable energy attracts a great deal of attention globally to cope with the

environmental and resource problems, especially, to reduce CO2 emission, an inappropriate application of distributed generators can be a cause of insecure power supply for example,. MicroGrid is one of the expected local power supply system that consists of distributed generators, loads, power storage devices and heat recovery equipments etc[1] [2]. Main features of MicroGrid system are:

Study on Power Quality Control in Multiple Renewable Energy Hybrid MicroGrid System

Xiangjun Li, Member, IEEE, Yu-Jin Song, Member, IEEE, Soo-Bin Han, Member, IEEE

A

IDENTIFICATION NUMBER: 351

2000978-1-4244-2190-9/07/$25.00 ©2007 IEEE PowerTech 2007

PCMS

ES

H2

H2T

FCVCB

TR

Utility Gird

PV

Housing

WP

MT

μ

Fig. 1 MicroGrid Network

(1) it can be operated independently from conventional UG, (2) it can make use of power and heat sources collectively, (3) it can be interconnected to the utility grid at one point.

In this paper, a MicroGrid system comprising of PC control and monitoring system, micro turbine aimed to supply base load, electrolyzer system to manufacture hydrogen, hydrogen tank and renewable energy used generators such as wind power, photovoltaic, proton exchange membrane fuel cell etc. is considered. That is, we use a generation system of 25kW photovoltaic, 100kW wind power, 5kW proton exchange membrane fuel cell and load controllable electrolyzer system and housing load etc. as a model MicroGrid system (see Fig.1).

We assume that energy obtained from the wind power and photovoltaic is mainly used to produce hydrogen, which is stored in the hydrogen tank to be converted back to electricity in the proton exchange membrane fuel cell. On the other hand, when MicroGrid is isolated from utility gird and wind power and photovoltaic etc. are unable to supply base load containing the electrolyzer system and the housing load, micro turbine will be committed to supply them.

Wind and photovoltaic generators have the characteristic of instable power output. Therefore, a sudden real power unbalance and a large frequency fluctuation are easy to occur in such renewable energy hybrid small-scale local power system. And it is sometimes not sufficient to reduce the fast frequency fluctuation by means of only applying dynamic control of micro turbine.

Moreover, because the main power line interconnected to the utility grid is designed to use 380V three-phase AC line, handling a DC or AC source to the AC grid would lead to harmonic distortion on voltages and currents. Thus compounding the various kinds of power sources would impact the quality of power supply within the MicroGrid and cause many control problems to be dealt with.

This paper focuses on the stability of MicroGrid operation and proposes a control means of combining micro turbine and a fuel cell, hydrogen tank, and electrolyzer system hybrid one to deal with the fast frequency fluctuation and the sudden real power unbalance and accordingly maintain the power quality of frequency.

An electrolyzer system of HOGEN is considered in this paper[3]. The power consumption (kW) of HOGEN can be controlled in millisecond level by adjusting the pressure in the customer piping system. The pressure control can be realized

by PC control and monitoring system through CAN composed communication network. Therefore, the electrolyzer system has controllability condition to compensate system real power unbalance.

This paper is organized as follows. Section II presents the formulation of power change by frequency fluctuation and that of random power fluctuation at generation and load sides. Section III presents the considered MicroGrid power system model. Simulation results are discussed in Section IV. Section V is the conclusion.

II. FORMULATION FOR POWER QUALITY CONTROL Since frequency fluctuation, f, is mainly effected by the

undulation of real power, the power quality issue for frequency stability can be realized by satisfying the real power supply-demand balance constraint in the MicroGrid power system. Therefore, an objective function for frequency control in MicroGrid system is formulized as follows.

0LG PPP where

)( MTFCini

MTini

FCPVWP

MTFCPVWPG

PPPPPP

PPPPP

ESini

ESgHouESgHouL PPPPPP sinsin

subject to maxmin

FCFCFC PPP

maxminMTMTMT PPP

maxminESESES PPP

As shown in Eqs.(2) and (3), by controlling PFC, PMT, PES to meet the real-time power fluctuations at generation

(WP, PV) and load (Housing) sides, the Eq.(1) can be guaranteed.

The PFC and PES are approximated in this paper by a first order transfer function, referred to the operation of a battery energy storage facility as shown in ref.[4].

fsT

KP

FC

FCFC 1

fsT

KP

ES

ESES 1

When consider the linear P versus f droop characteristic, PMT is derived as

fK

PMT

MT1

Since the is obtained by

fdtf02

(1)

(2)

(3)

(7)

(8)

(10)

(9)

(4)

(6)

(5)

2001

the Ptie is derived from

tietie X

sffsin

P

02

The standard deviations for wind power, photovoltaic, and housing load etc. are mathematically estimated as[5].

WPWP PdP 8.0

PVPV PdP 7.0

gHougHou PdP sinsin 6.0

and these standard deviations are multiplied by a random output fluctuation derived from the white noise block in MATLAB/SIMULINK to simulate the real-time random power fluctuation on the generation and load sides.

III. SPECIFICATION OF MICROGRID MODEL A schematic diagram of the MicroGrid system constructed

by the MATLAB/SIMULINK is shown in Fig.2. The tie line power and the dynamic behaviors of electrolyzer system, fuel cell, and micro turbine are assessed by PCMS depending on the feedback parameter of P.

The schematic diagrams of PCMS and PI controller are shown in Figs.3 and 4 respectively. The other PI controller related to Ptie compensation has the regulators of PI2 and PI4

and has a reference value of Ptie_ref. PI1 and PI3 are proposed to reduce the P and PI2 and PI4 are introduced to alleviate the

Ptie. The parameters of MicroGrid model and each PI regulators

are shown in Tables I and II. The P and Ptie are measured at every 5 and 4 seconds respectively by setting input signal delay time of PI regulators as shown in Fig. 4. Moreover, in this paper, it is considered that the PEMFC power not attended

TABLE I MICROGRID MODEL PARAMETERS

PiniES 50kW Pini

FC 5kW Pmax

ES 70kW PmaxFC 5kW

PminES 30kW Pmin

FC 2kW KES 100 KFC

ES

TES 60

FC

TFC Pini

MT 70kW PiniWP 15kW

PmaxMT 100kW

WP Pmax

WP 100kW Pmin

MT 10kW PiniPV 10kW

KMT 0.04 PV

PmaxPV 25kW

M 10 Tie line Xtie 0.072

MT

D 1 f0 50Hz Housing Pini

Housing 50kW System Base 100kW

TABLE II

PI REGULATOR PARAMETERS MT output control ES load control PI regulator PI1 PI2 PI3 PI4 Proportional gain KP 0.1 0.1 0.1 0.1 Integral gain KI 0.5 0.1 0.5 0.1

to the real-time control of P and the PFC is set to a constant value of 5kW through a 500 seconds test time period.

IV. SIMULATION RESULTS The initial real power balance in MicroGrid is set to zero at

the simulation starting point as shown in Table I and the feasibility of the ES dynamic control is examined during 500

(11)

(12)

(13)

(14)

Fig.2. Schematic diagram of MicroGrid model system Fig.3. Proposed PCMS structure

Fig.4. PI controller related to P compensation

2002

Fig.5. Power profile without ES and PI1 control

PES

PMT

PHousing

0.4

0.5

0.6

0.7

0.8

0 100 200 300 400 500time (s)

kW (p

.u.)

Simulation Results for islanding operation (Case A)

-0.2

-0.1

0

0.1

0 100 200 300 400 500

time (s)

f (H

z)

with ES without ES

Fig.7. f with or without ES control

Simulation Results for utility grid connected operation (Case B)

-0.4

-0.2

0.0

0.2

0.4

0 100 200 300 400 500

time (s)

P (k

W)

Fig.13. P by utility grid connected operation

Fig.11. Ptie fluctuation with or without PI2

-0.1

-0.05

0

0.05

0 100 200 300 400 500

time (s)

Ptie

(kW

)

with PI without PI2 2

Fig.10. Power profile with PI2

-0.1

0.1

0.3

0.5

0.7

0.9

0 100 200 300 400 500time (s)

kW (p

.u.)

PES

PMT

Ptie

PHousing

Fig.9. Power profile without PI2

-0.1

0.1

0.3

0.5

0.7

0.9

0 100 200 300 400 500

time (s)

kW (p

.u.)

PES

PMT

Ptie

PHousing

WP, PV, and FC output in both operation models

Fig.14. WP, PV, and FC output

0.040.060.08

0.10.120.140.16

0 100 200 300 400 500time (s)

kW (p

.u.)

PPV

PWP

PFC

Fig.12. f with or without PI2

-0.001

-0.0005

0

0.0005

0.001

0 100 200 300 400 500

time (s)

f (H

z)

with PI without PI22

Fig.8. f with or without PI1

-0.1

-0.05

0

0.05

0.1

0 100 200 300 400 500

time (s)

f (H

z)

with PI without PI1 1

Fig.6. Power profile with ES and PI1 control

0.4

0.5

0.6

0.7

0.8

0 100 200 300 400 500time (s)

kW (p

.u.)

PMT

PHousing

PES

2003

seconds. The reference parameters of Ptie_ref and P_ref are set to zero. Simulation results by two operation modes, islanding operation mode and utility grid connected one, are presented as follows. A. Islanding operation

Figs.5 and 6 show the change of real power profile by using ES and PI1 controls. Figs. 7 and 8 show the frequency fluctuation for using ES dynamic operation or PI1 regulator respectively. Comparing Figs. 5 and 6, shows that the PCMS controls the power consumption of electrolyzer system to relax load fluctuation and changes the output power of micro turbine to match the real power balance. As a result, the frequency fluctuation is improved as shown in Figs 7 and 8. B. Utility grid connected operation

Figs. 9 and 10 show the change of real power profile by applying PI2. Comparing Figs. 9 and 10, shows that using PI2

to adjust the power output of micro turbine, the power supply from utility grid is decreased. The Ptie fluctuation is magnified in Fig.11.

Fig.12 shows the frequency fluctuation by PI2. It is seen that the frequency fluctuation is changed slightly by utilizing PI2

and compared with Figs. 7 and 8, in which MicroGrid is running for islanding mode, the power quality for frequency is improved by interconnecting the utility grid. The real power unbalance by utility grid connected operation is shown in Fig. 13 and the WP, PV, and FC outputs under the above-mentioned two operation modes are shown in Fig. 14.

C. Discussion for setting TES For the above-mentioned two cases A and B, the TES was set to 60 to adjust the power consumption of ES by a slow response time. At whiles, a fast frequency fluctuation cannot be repressed adequately by means of governors of generators and slow response power sources. Since load power of the ES considered in this paper can be controlled in millisecond level, the PCMS can adjust the load power rapidly by changing the TES to a smaller value. Therefore, a case C in which the TES is set to 1 is discussed below. In this case, assuming that a 20kW overload are occurred suddenly at third second to simulate a fast and a large frequency fluctuation in the MicroGrid system. Figs.15, 16, and 17 show the power profile and f respectively before and after the ES dynamic controls are considered. It appears that the maximum frequency fluctuation of 0.35Hz is improved effectively by utilizing ES’s high response capability for kW load control.

V. CONCLUSION In this paper, a dynamic control method for electrolyzer

system is proposed to secure real power balance and enhance the operation capability of handling frequency fluctuation.

The content of this paper is summarized as follows. (1) The output changes of fuel cell and electrolyzer system

are defined by the first order transfer function. The tie line power and the output change of micro turbine by the frequency fluctuation are presented.

(2) The fluctuations of frequency and tie line power are considered for islanding and interconnected operation modes respectively, to demonstrate the effectiveness of the proposed dynamic control method. It is concretely shown that a power quality improvement for frequency can be expected by actively utilization of the load controllable electrolyzer system.

(3) PI regulators are used to compensate the power changes at MicroGrid power system and tie line. The influence of considering them is also discussed.

(4) It is considered that in shorter special time periods in which a sudden large frequency fluctuation is happened, applying smaller TES to control ES load rapidly is a means to enhance the operation capability of handling frequency fluctuation.

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0 2 4 6 8 10

time (s)

f (H

z)

with ES without ES

Fig.17. f with or without ES control

Simulation Results for setting TES (Case C)

Fig.15. Power profile without ES control

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10time (s)

kW (p

.u.)

PMT

PHousing

PES

Fig.16. Power profile with ES control

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10time (s)

kW (

p.u.

)

PES

PMT

PHousing

2004

The efficient use of the FHES considering the SoC of hydrogen tank and the slow response characteristic of PEM fuel cell will be studied and the fluctuation of voltage in the MicroGird system examined in the near future. Furthermore, it will be discussed that how to determine the unit commitment of the multiple power sources to obtain an optimal daily operation schedule for the multiple renewable energy hybrid MicroGrid power system.

REFERENCES [1] R. H. Lasseter, A. Akhil, C. Marnay, J. Stephens, J. Dagle, R.

Guttromson, A. S. Meliopoilous, R. Yinger, and J. Eto, “Integration of Distributed Energy Resources–The CERTS MicroGrid Concept,” CERTS white paper, Apr. 2002.

[2] R. H. Lasseter, and P. Paigi, “Microgrid: A Conceptual Solution,” in Proc. 35th Annu. Conf. IEEE PESC’04 pp. 4285-4290.

[3] http://www.protonenergy.com [4] D. Kottick, M. Blau, and D. Edelstein, “Battery Energy Storage for

Frequency Regulation in an Island Power System,” IEEE Trans. EnergyConversion, vol. 8, pp. 455-459, Sep. 1993.

[5] M. Matsubara, G. Fujita, T. Shinji, T. Sekine, A. Akisawa, T. Kashiwagi, and R. Yokoyama, “Supply and Demand Control of Dispersed Type Power Sources in Micro Grid,” in Proc. 13th Int..Conf. ISAP’05, pp. 67-72.

Xiangjun Li (M’07) received the B.E. degree in electrical engineering from Shenyang University of Technology, China, in 2001, and the M.E. and Ph. D. degrees in electrical and electronic engineering from Kitami Institute of Technology (KIT), Japan, in 2004 and 2006, respectively. Since 2006, he has worked as a research associate in Electric Energy and Lighting Center, Korea Institute of Energy Research (KIER) and researched on the control system of fuel cell hybrid vehicle, including PEMFC system control. His

research interests include power system economics, power system reliability and renewable energy hybrid vehicle and power systems.

Yu-Jin Song (M’99) received his B.S. and M.S. degree in electrical engineering from Yonsei University, Seoul, Korea in 1988 and 1991. He worked on the development of the digital control system in Daewoo Heavy Industry from 1991 to 1997. He started the Ph.D. program in electrical engineering at Texas A&M University in the Fall of 1999 and received his Ph.D. in August 2004. He worked as a Research Assistant in the Power Electronics and Power Quality Laboratory of the Electrical

Engineering Department, conducting research on design of high frequency link power conversion system for distributed power system and power quality issues. His research interests are primarily in advanced power electronics converters applied to distributed power system with renewable energy sources, power quality issues and soft switching technique.

Soo-Bin Han (M'95) was born in Korea on Jun 9, 1958. He received the B.S. degree in electronic engineering from Hanyang University, Korea, in 1981, and the M.S. and Ph.D. degrees in electrical engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1986 and 1997, respectively. He has been a Principal Researcher at Korea Institute of Energy Research (KIER) since 1986 and now a leader of Electric Energy and Lighting Center of KIER. His research interests

include electric energy saving/storage technology, hydrogen/fuel cell power application and new lighting technology.

2005