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Development of a Frequency-stabilizing Scheme for Integrating Wind Power Generation into a Small Island Grid
Proceedings of the 18th World Congress The International Federation of Automatic Control Milano (Italy) August 28 - September 2, 2011
Development of a Frequency-stabilizing Scheme for Integrating Wind Power Generation into a Small Island Grid K. Yamashita, O. Sakamoto, Y. Kitauchi, T. Nanahara, T. Inoue* H. Fukuda, T. Shiohama**
*Central Research Institute of Electric Power Industry, Tokyo, 201-8511 Japan (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected]). **Okinawa Electric Power Company, Okinawa, 901-2602 Japan (e-mail: [email protected], [email protected])
Abstract: Integrating wind power generation into small islands has been one of the demonstration projects in Okinawa Prefecture, Japan. Since such integration could deteriorate power quality, including frequency, in an island grid, a frequency-stabilizing system using flywheels has been integrated into a small island. In order to establish a proper frequency-stabilizing scheme for a small island, an accurate model of a diesel generator including a governor is vital. Therefore, a model was developed through generator dump tests. A new frequency-stabilizing scheme was also developed through the time-domain simulation of the island grid model, which consists of the above mentioned diesel generator model and negative load change representing wind power variation. The developed stabilizing scheme was applied to the flywheels in the island grid and revealed great performance for mitigating frequency variation. Keywords: power system, wind power generation, small island power system, flywheel energy storage system, diesel generator
1. INTRODUCTION A project to increase wind penetration for small remote islands in Okinawa Prefecture, Japan was started through the local government of Okinawa Prefecture, including Okinawa Electric Power Company Incorporated, in 2009. One of the purposes of the project is to introduce two wind power generators (245 kW in each) and eight flywheels (30 kW×30 s in total) onto a small island with a maximum demand of 613 kW (Refer to Fig. 1). The flywheels (referred to FWs, hereafter) are expected to alleviate the impact of wind penetration.
standard model for hydraulic turbines, and the validation of the scheme was investigated using only simulation analysis. Another scheme for stabilizing system frequency using FWs in an isolated grid including wind generation was proposed (Hamsic et al. [2007]). The actual power of the wind generation and system frequency was used as the input of the proposed scheme. The scheme was applied to real FWs installed in the Flores power system and verified its fundamental performance in the Flores isolated grid. However, no detailed control logic for FWs has been described in the paper.
FWs are known as one type of energy storage system and are suited for alleviating the high frequency fluctuation of output of wind power generation. Although various frequency stabilization schemes using FWs have been proposed, only a few schemes can be applied for an isolated grid. Thus, a scheme for stabilizing system frequency using FWs in a small power system including a wind farm was proposed (Takahashi et al. [2007]). In this paper, system frequency is used as the input of the proposed scheme. However, diesel generator models with a governor action were represented by a general IEEE 978-3-902661-93-7/11/$20.00 © 2011 IFAC
Diesel Generators
6G
7G
8G
9G
Rated Capacity 150 kW
Rated Capacity 245 kW
150 kW
245 kW
300 kW
300 kW
WT1
WT2
Wind Generators
Because a power system on a small island is an isolated power system, the increasing wind penetration causes the increase of frequency variation. In order to mitigate the increasing variation, the following three items are required: 1) development of accurate diesel generator models with a governor action; 2) extraction of wind power variation characteristics; 3) establishment of an effective frequency-stabilizing scheme using FWs.
Load
FW
Rated Capacity: 200 kW (W72 cm×H47.5 cm ×D82 cm×8 sets) Flywheel Energy Storage System
Fig. 1. A small remote islanded power system. In order to establish a proper control scheme, accurate diesel generator models with a governor action were firstly examined based on the measured values of generator dump tests in this study. Then, a new frequency-stabilizing scheme was developed using time-domain simulation, which consists of the developed diesel generator models and an equivalent load change representing wind power variation.
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
The developed stabilizing scheme was applied to the actual frequency-stabilizing system in the small island and verified its performance through connecting to the island power system. 2. DEVELOPMENT OF A DIESEL GENERATOR MODEL INCLUDING A GOVERNOR 2.1 Validation of the Governor Model of the Diesel Generators A governor model is a key generator controller for analyzing wind power impact on system frequency deviation in a small isolated power system. Although various types of governor models of steam turbines and hydro turbines have been used for power system planning and analysis, few governor models of diesel engines have been developed. Therefore, a generator dump test was performed for main diesel generators in the island grid in order to develop the governor model of a diesel engine. The following findings were obtained through the generator dump test.
Static and dynamic response characteristics for frequency change vary depending on the manufacturers of engines and/or governors.
Dynamic response characteristics of the same diesel generator vary depending on the magnitude of frequency deviation.
Based on the above findings, the governor model was developed considering the following two conditions:
The transient increase of generator power output and post-fault steady state generator output obtained from time-domain simulation should be consistent with the same increase obtained from the result of the generator dump test respectively with regards to a few different magnitudes of frequency deviations.
The calculated active power output was compared with the measured active power output. Based on the comparison, the construction of the model and the identification of its parameters were performed through trial and error. For example, one lead-lag element in Fig. 2 was applied for the governor model of 6G and 7G, while two lead-lag elements were applied for the model of 8G and 9G. The feedback control loop, including an integral element in Fig. 2, denotes a first-order lag element with a restricted rate of change and enables emulating a slow trend of the increasing generator output after a generator tripping. Two lead-lag elements in Fig. 2 enable emulating a transient response of the generator output immediately after a generator tripping. Although the washout element in Fig. 2 originally has the function of a high-pass filter, this element here has a role of eliminating high-frequency components from the original signal (output of the signal transducer in Fig. 2) through the accumulator element. That helps preventing excessive control. Post-contingency analysis showed steady-state frequency deviation obtained by the generator dump test was proportion to the output of the tripped generator. However, the largest frequency deviation was not proportion to the output. Therefore, the nonlinear element in Fig. 2 was introduced to match measured values with simulated ones for three different magnitudes of frequency deviations (about 0.3 Hz, 0.4 Hz, and 0.5 Hz). The example simulation results obtained by CRIEPI's Power Analysis Tools (CPAT) are shown with the testing result in Fig. 3. It should be noted that the responses of 6G, 8G, and 9G are the result in case of 7G tripping, and the response of 7G is the result in case of 6G tripping. As shown in Fig. 3, the developed governor model can express the response of the generator dump test precisely. 2.2 Validation of the small island power system model
The time to reach maximal generator output obtained from time-domain simulation immediately after a generator tripping should be consistent with the time obtained from the result of the generator dump test.
The small island power system model including not only diesel generators but transformers and loads should also be validated. Therefore, the small island power system model was developed and was validated through the dump test. The outline of the system model shows the following:
Fig. 2 shows the block diagram of the developed governor model of the diesel engine. The model parameters for each diesel engine are provided in Table 1. It should be noted that the model was not developed using a component-based approach, but it was developed using a measurement-based approach. The measured frequency is inserted into the input of the governor model as the rotor speed deviation in Fig. 2.
(1) Composition of the island power system model: The island power system model consists of diesel generator models for G6, G7, G8, and G9, a step-up transformer, transmission lines, and loads as shown in Fig. 1. Because the generator is almost directly connected to the loads, the reactance of the transmission lines was set to extremely low values.
Signal Transducer 1 Sg 1+T1S Rotor Speed Deviation
-
K
Governor Gain
Load Reference + +
Nonlinear Element
1 T4S
T3S 1+T2S Washout Element
Fig. 2. Governor model of a diesel engine. 12874
U L
First Lead-Lag Element 1+T6S 1+T5S
Second Lead-Lag Element 1+T8S 1+T7S
TQT Mechanical Output
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
Frequency [Hz]
Table 2. Generator constants
6G Tripping
60.0
Specification Rated capacity [kVA] Rated power [kW] Inertia constant [s]* D axis reactance [p.u.] D axis transient reactance [p.u.] D axis sub-transient reactance [p.u.] Q axis reactance [p.u.] Q axis sub-transient reactance [p.u.] D axis open circuit time constant [s] D axis transient time constant [s] D axis sub-transient time constant[s] Armature leakage reactance [p.u.] Armature time constant [s] Zero phase reactance [p.u.] Negative phase reactance [p.u.] *The inertia constant of the generator and its larger than that of only one generator.
59.8 59.6 7G Tripping
60.0 59.8
G9 [kW]
G8 [kW]
G7 [kW]
G6 [kW]
59.6
120 100 80 60 120 100 80 60
7G Tripping
6G Tripping
180 160 140 120 250
Table 3. Initial conditions for the generator dump test Case
7G Tripping 1 2
Measured Value Simulated Value
150 7G Tripping 10
20
30
40
50
9G 0.02 2.0 0.01 95 0.02 1.053 -0.1 0.01 0.20 0.50 0.01
(2) Load model: As the component of the loads in the island power system is obscure, a static exponential model with typical load voltage parameters was applied. The load voltage characteristics were given as constant current characteristics for active power and constant impedance characteristics for reactive power. Load frequency characteristics were not considered for this study because conservative simulation results were preferable. (3) Diesel generator model: The generator model with d-axis and q-axis rotor circuits was used because the transient response of generators is closely related to the dynamic behavior of system voltage and, eventually, loads and system frequency. Each rotor circuit includes one damper winding respectively. The generator constants are shown in Table 2. Although an inertia constant of generators and its engine is critical for this study, only the generator inertia was able to be derived from the design data. Therefore, the inertia con-
Frequency [Hz]
8G 0.02 0.05 0.01 16 0.1 1.053 -0.1 20.0 30.0 0.02 0.13
60.0 59.9 59.8 59.7 59.6 59.5
Active Power Output[kW]
Table 1. Parameters of the developed governor models 7G 0.02 0.25 0.015 40 0.1 1.053 -0.1 0.01 0.15
[kW] 150 150
Total Generation
Active 6G 7G 8G 9G Power 150 73 130 136 490 75 152 141 137 500
Reactive Power 130 120
Item Testing Result Simulation Result Bottom frequency 59.53 [Hz] 59.52 [Hz] 1 Time to reach the bottom frequency 1.15 [s] 1.20 [s] Post-disturbance steady-state frequency 59.76 [Hz] 59.79 [Hz] Bottom frequency 59.46 [Hz] 59.42 [Hz] 2 Time to reach the bottom frequency 1.27 [s] 1.22 [s] Post-disturbance steady-state frequency 59.77 [Hz] 59.77 [Hz]
Fig. 3. Example of the active power outputs of diesel generators No. 6 through No. 9 with frequency data.
6G 0.1 0.4 0.2 70 4.0 1.053 -0.1 0.7 4.5
6G 7G
Generator Trip- Active Power Outping Amount put [kW]
Case
Time [s]
Variable T1 T2 T3 K T4 U L T5 T6 T7 T8
Tripping Generator
Table 4. Frequency response obtained from simulation results and testing results
200
0
6G 7G 8G 9G 187.5 187.5 375.0 375.0 150.0 150.0 300.0 300.0 1.36 1.36 0.868 2.41 0.83 0.83 2.84 1.62 0.19 0.19 0.31 0.15 0.15 0.15 0.22 0.10 0.50 0.50 1.15 0.72 0.14 0.14 0.26 0.16 0.73 0.73 2.29 2.26 0.165 0.165 0.25 0.208 0.020 0.020 0.020 0.022 0.134 0.134 0.198 0.083 0.014 0.014 0.025 0.03 0.07 0.07 0.20 0.078 0.13 0.13 0.24 0.15 engine was assumed to be 1.5 times
240
Measured Value Simulated Value
9G
200
8G
160 120
7G
80 0
5
10
15
20
Time [s]
Fig. 4. Example comparison between measured and simulated value of frequency response and active power output response (Case 1). stant of the engine was assumed to be half of the generator inertia, the ratio of which is the smaller value selected from its appropriate range. (4) Generator control model: The standard AC exciter model, with its standard parameters, was applied. The developed governor model was also used. Example initial conditions for the generator dump test are shown in Table 3. The characteristic frequency response is shown in Table 4. The bottom frequency, the time it takes to reach the bottom frequency, and the post-disturbance steady state frequency obtained from time-domain simulation are
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
WP Output [kW]
Rated Rotating Speed 46 rpm
The installed wind turbines, produced by Vergnet in France, adopt a fixed-speed two-bladed wind turbine with active stall control. The characteristics of the fixed-speed two-bladed wind turbine are the appearance of remarkable power variations the frequency of which is proportion to the rated rotating speed of the wind turbine (0.769 Hz). Fig. 5 shows an example power spectrum of the system frequency and the wind power generation under its power output limitation (100 kW). The variation characteristics of wind power generation are summarized as follows:
120 Gain
10s 1+10s Washout Element
DP Active Power of Wind Generation [PU]
0.002[PU]
0.8 Gain
5s 1+5s Washout -0.002[PU] Element
180
2 -3
4
6N
2
10 6 4
4N
2
10
-4
4
10
Wind Generation Output System Frequency
2
6 4
1 0.8 0.6 0.4 0.2
Coherence between Wind Generation Output and Frequency 2
3
4 5 67
2
3
4 5 67
1 Time Period [1/Hz]
2
10
3
4 5
FWs are known as one of the effective ways to alleviate the frequency variation caused by wind power generation. The developed frequency-stabilizing scheme using FWs employs both wind power variation and the deviation of the system frequency as an input. Fig. 6 shows a block diagram of the FW model equipped with the developed scheme. The proper parameters of this scheme were derived considering rolesharing between diesel generators and FWs. The considera200
10000
-
0
100 -2[PU]
150
1N
2N
100
90 120 Time [s]
3.2 Development of a frequency-stabilizing scheme
+
PU→rpm
6000[rpm]
Scale Conversion
kW→PU
Inverter
1 240
-1 1+0.02s
+
+
1 1+0.02s Signal Transducer
2
PU→kW
+
DP Input Part
60
effective way to alleviate the frequency variation caused by wind power generation.
Based on the above findings, it can be observed that the two frequency components of the wind power variation have substantial impact on frequency fluctuation. Therefore, mitigation of the two frequency components with FWs is the most
1 DF Frequency 1+0.01s Deviation Signal [PU] Transducer
30
Fig. 5. Example of the power spectrum of wind power generation output and coherence between wind power generation output and system frequency.
(2) The coherence between wind power generation and the system frequency at the above two frequency components was high.
2[PU]
0
0.1
(1) Two frequencies, 0.769 Hz and 1.54 Hz, were obvious for both the wind power variation and frequency variation. Note that 1.54 Hz is double the rated rotating speed of the wind turbine.
pukW/puHz
Output of Wind Power Generation
2
3.1 Variation characteristics of wind power generation
Frequency of "2N" 1.54 Hz
Frequency fS [Hz ]
The dynamic behavior of wind power generation is important for the frequency-stabilizing system. Wind power generation output was represented as an equivalent time-varying negative load for time-domain simulation.
DF Input Part
180 120 60 0
Frequency of "1N" 0.769 Hz
2
3. DEVELOPMENT OF A FREQUENCY-STABILIZING SCHEME FOR THE FREQUENCY-STABILIZING SYSTEM
Table 5. Frequency change of wind power generation output
Coherence Wind Generation Output fS [kW ]
consistent with those three indices obtained from the testing result, respectively. As shown as Fig. 4, the transient response and the steady state response of each generator output obtained from time-domain simulation are also consistent with the same responses obtained from the testing result. Therefore, it can be concluded that the small island power system model expresses the frequency response properly.
+
w0 w
1 Ms 1500[rpm]
PU→kW 100×103
10000
+
0
-
-200
Scale Conversion
4373[rpm] 0.1
15 -15
1 1+5s Center Frequency Control
Fig. 6. Block diagram of the FW model equipped with the developed frequency-stabilizing scheme. 12876
+
-
wREF + -
w [PU] PU→rpm
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
The time constant of the washout in the DP input part was set to 5 s in order to suppress the obvious high-frequency components of wind power vibration directly, while the time constant of the washout in the DF input part was set to 10 s. Not only the center frequency control but these two short time constants of the washouts also help the FWs to avoid the depletion of charge or discharge energy. As shown in Fig. 3, the rate of output change and the output change amount of 9G after the sudden frequency change were much larger than those of other diesel generators. It is considered that this difference is related to: the rated rotor speed of 9G, which is much higher than others, and the response time of its fuel supply control, which is much faster than others. Therefore, it might be difficult to adjust the power output of 9G within its proper operating range in case of large sudden frequency changes caused by wind power generation. Those two short-duration constants of washouts were selected considering the prevention of the abnormal operation of 9G. 3.3 Validation of the developed frequency-stabilizing scheme A start-up field test was assigned to one of the wind turbines in Jan. 2010. The data measured at the test was used for the verification of the performance of the developed frequencystabilizing scheme. In order to evaluate the high penetration of wind power generation (the interim goal was 5 min average penetration up to 50%) through time-domain simulation, the measured values were extended 2.75 times larger than the original measured values. Operating diesel generators were assumed to be 6G, 7G, and 9G. Their initial outputs were set to 100 kW, 100 kW, 284 kW, respectively.
Active Power Output [kW]
300
G6 G7 G9
200 100 0
WP Output [kW]
WP Output
400 300 200 100 0 0
30
60
90 120 Time [s]
150
180
(a) Simulation result without FW
Frequency [Hz]
(3) Center frequency control was originally equipped in the frequency-stabilizing system. This control helps FWs to avoid the depletion of charge or discharge energy. If the rotating speed of the FWs reaches the lowest or the highest speed, its charge energy or discharge energy will be depleted and that depletion leads to the undesirable sudden change of the frequency. Therefore, the rotating speed of the FWs should be controlled near the center of the rotating speed (4,373 rpm) using the center frequency control, unless a large sudden frequency change occurs. The parameters of the center frequency control were selected in order to position the rotating speed of FWs back to the center quickly, after a large sudden frequency change.
Frequency 60.36Hz
500
Rotating Speed [RPM]WP FW Output [kW] Active Power Output [kW]
(2) Deviation of the system frequency was used as the DF input of the developed scheme. The parameters of the DF input part in Fig. 6 were selected in order to extract a specified frequency component range (0.1 Hz or higher) of the load variations, which is difficult for diesel generators to suppress.
61.0 60.8 60.6 60.4 60.2 60.0 59.8
0.39Hz 0.39Hz
(1) Wind power variation was used as the DP input of the developed scheme. The parameters of the DP input part in Fig. 6 were selected in order to extract a specified frequency component range (0.2 Hz or higher) of wind variations, including 0.769 Hz and 1.54 Hz.
Frequency [Hz]
tion for deriving the parameters is described below.
61.0 60.8 60.6 60.4 60.2 60.0 59.8
Frequency
300
G6 G7 G9
200 100 0
WP Output,
FW Output
400 200 0 -200 6000 5000 4000 3000 2000
FW Rotating Speed 0
30
60
90 120 Time [s]
150
180
(b) Simulation result with FW
Fig. 7. Time series data of wind power generation output (2.75 times larger than the actual measured data). Figure 7(a) shows an example simulation result without FWs. The average system frequency was 60.36 Hz (see Table 6) during the operation of the wind turbine because the Load Frequency Controller (LFC) was not equipped. If the average frequency was shifted to 0 Hz with the AFC, the frequency deviation was plus or minus 0.39 Hz, which exceeded the
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
desired frequency deviation (normally between 0.2 Hz and 0.3 Hz). Moreover, the generator output of 9G was sometimes below zero, which might cause tripping of 9G due to its reverse power relay. In other words, this simulation result revealed that the small island power system cannot maintain power quality and power system stability without a frequency-stabilizing system if high wind penetration such as 50% is pursued. Figure 7(b) shows the same example simulation result with FWs. As shown in this figure, FW output increased its output while wind power generation decreased its output and vice versa, if a specified frequency component range (0.1 Hz or higher) of the wind generation and system frequency was focused on. If the average frequency was shifted to 0 Hz with the LFC, the frequency deviation was plus or minus 0.12 Hz, which is much smaller than the desired frequency deviation (see Table 6). Figure 8 shows the power spectrum of the frequency with and without FW along with the power spectrum of the FW output. FWs mitigated a frequency component range of the system frequency between 0.033 Hz and 3.33 Hz effectively.
4.1 Performance of the frequency-stabilizing scheme with regard to various frequency components of wind power generation Figure 10 shows the filtered total output of wind power generation and the filtered FW output. The filter was designed for extracting a specified frequency range (0.20 Hz or higher). The filtered FW output increased its output, while the filtered total wind power generation decreased its output and vice versa. That means that the frequency-stabilizing scheme, especially the DP input part in Fig. 6, effectively mitigated the obvious frequency components of the system frequency variation caused by wind power generation. Figure 11 shows another filtered total output of wind power generation and another filtered FW output. The filter was designed for extracting a specified frequency range (0.025 Hz or higher). The filtered FW output increased its output, while the filtered total wind power generation decreased its output and vice versa. That means that the frequency-stabilizing scheme, especially the DF input part in Fig. 6, effectively mitigated the obvious frequency components of the system frequency variation caused by wind power generation. 4.2 Performance of the frequency-stabilizing system using flywheels
The developed stabilizing scheme was applied to the frequency-stabilizing system using FWs in the isolated small island grid. The performance of the frequency-stabilizing system was verified under a 5 min average penetration of 48%. As shown in Fig. 9, the system frequency deviation was within plus or minus 0.1 Hz. That value was almost the same as the simulation result (0.12 Hz) described in Section 3. That means the developed frequency-stabilizing system successfully mitigated the frequency variation caused by wind power generation.
Figure 12 shows the example response of FWs and diesel generators when one wind turbine (150 [kW]) was tripped due to its power output limitation control. The FWs promptly controlled its output, which led to the mitigation of not only frequency fluctuation but the power output variation of the diesel generators within their proper operating range. The frequency fluctuation after the tripping was also effectively mitigated with the introduction of FWs even without excessive compensation. Figure 13 shows another sample response of FWs and diesel generators when G7 (150 [kW]) was intentionally tripped. Although only the DF input part in Fig. 6 is active, the FWs
-5
10
Power Spectrum of Frequency without FW Power Spectrum of Frequency with FW
-7
10
-7
10 10
-10
10
-13
Power Spectrum of FW Output 0.1
1 10 Time Period [1/Hz]
100
Fig. 8. Power spectrum of frequency with/without FW and the power spectrum of the FW output. Table 6. Simulation result of frequency change Stabilizing System
Fmax[Hz]
Fmin[Hz]
DF[Hz]
F
Median F
Without FWs With FWs
0.75 0.48
-0.02 0.24
±0.39 ±0.12
0.117 0.044
0.36 0.37
Frequency [Hz]
-3
10
60.2 60.1 60.0 59.9 59.8
Active Power [kW]
-1
10
320
Total Output of Diesel Power Station Total Output of Wind Power Generation
280 240 200
FW Output [kW]
2
FW Output fS [kW ]
2
Frequency fS [Hz ]
4. VERIFICATION OF THE PERFORMANCE OF THE DEVELOPED FREQUENCY-STABILIZING SYSTEM IN THE SMALL ISLAND GRID
40 20 0 -20 -40 0
50
100 Time [s]
150
200
Fig. 9. Example of measured data under high wind penetration (5 min average penetration: 48 %). 12878
Frequency [Hz]
250 200 150
Nonfiltered Total Output of Wind Power Generation
20 0 -20 -40 30
Active Power [kW]
Filtered Total Output of Wind Generation (over 0.2 Hz) Filtered FW Output (over 0.2 Hz)
20 10 0 -10
5
10 Time [s]
15
20
Fig. 10. Filtered FW output and wind power generation output (cut-off frequency: 0.2 Hz).
FW Output [kW]
Nonfiltered FW Output
0
250 200 150 100 80 40 0 -40 0
50
100 Time [s]
150
200
WP [kW]
200 150
Total Output of Wind Power Generation
20 0 -20 -40
FW Output Filtered Total Output of Wind Generation (over 0.025 Hz) Filtered FW Output (over 0.025 Hz)
40 20 0 -20 0
20
40
60
80
100
Time [s]
Fig. 11. Filtered FW output and wind power generation output (ut-off frequency: 0.025 Hz). promptly controlled its output from -10 kW to 50 kW, which contributed to the mitigation of not only frequency deviation but also the power output variation of the diesel generators. It should be noted that generator tripping could cause larger frequency deviation than the cut-out of a wind turbine.
Load [kW] Frequency [Hz]
Fig. 12. Example of measured data when one wind turbine stopped due to its power output limitation control.
250
FW [kW]
Total Output of Wind Power Generation 6G, 8G, 9G
300
-20
FW, WP [kW]
60.1 60.0 59.9 59.8 59.7
60.00 59.90 59.80 59.70
FW Output [kW] Active Power [kW]
FW, WP [kW]
FW [kW]
WP [kW]
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
300
540 520 500
200 100
6G,
0
7G,
8G,
9G
60 40 20 0 -20 -40 0
10
20 Time [s]
30
40
Fig. 13. Example of measured data in case of a 7G tripping. tion Funds for Promotion of Okinawa.
5. CONCLUSION The developed stabilizing system using FWs is currently operating in the small island power system and has shown great performance for alleviating frequency variation caused by wind power generation. The FWs have contributed to increase in wind power generation and decrease in diesel fuel usage. Future work would be concerned with the development of a voltage-stabilizing scheme and with the integration of the voltage stabilizing-scheme into the developed frequencystabilizing scheme. ACKNOWLEDGEMENTS This work was supported in part by the Ministry of Economy, Trade and Industry in Japan under Grant Special Coordina
REFERENCES CRIEPI (1991). Integrated Analysis Software for Bulk Power System Stability, CRIEPI report, ET90002, July 1991. Hamsic, N, Schmelter. A, Mohd, A, Ortjohann. E, Schultze, E, Tuckey, A, and Zimmermann, J (2007). Increasing renewable energy penetration in isolated grids using a flywheel energy storage system, IEEE International Conference on Energy and Electrical Drives, 2007 pp. 195–200. Kundur, P (1994). Power System Stability and Control, McGraw-Hill, New York. Takahashi, R, and Tamura, J (2007). Frequency stabilization of small power systems with wind farm by using flywheel energy storage systems, IEEE International Symposium on Electronics and Drives, 2007 pp. 393–398.
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Development of a Frequency-stabilizing Scheme for Integrating Wind Power Generation into a Small Island Grid K. Yamashita, O. Sakamoto, Y. Kitauchi, T. Nanahara, T. Inoue* H. Fukuda, T. Shiohama**
*Central Research Institute of Electric Power Industry, Tokyo, 201-8511 Japan (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected]). **Okinawa Electric Power Company, Okinawa, 901-2602 Japan (e-mail: [email protected], [email protected])
Abstract: Integrating wind power generation into small islands has been one of the demonstration projects in Okinawa Prefecture, Japan. Since such integration could deteriorate power quality, including frequency, in an island grid, a frequency-stabilizing system using flywheels has been integrated into a small island. In order to establish a proper frequency-stabilizing scheme for a small island, an accurate model of a diesel generator including a governor is vital. Therefore, a model was developed through generator dump tests. A new frequency-stabilizing scheme was also developed through the time-domain simulation of the island grid model, which consists of the above mentioned diesel generator model and negative load change representing wind power variation. The developed stabilizing scheme was applied to the flywheels in the island grid and revealed great performance for mitigating frequency variation. Keywords: power system, wind power generation, small island power system, flywheel energy storage system, diesel generator
1. INTRODUCTION A project to increase wind penetration for small remote islands in Okinawa Prefecture, Japan was started through the local government of Okinawa Prefecture, including Okinawa Electric Power Company Incorporated, in 2009. One of the purposes of the project is to introduce two wind power generators (245 kW in each) and eight flywheels (30 kW×30 s in total) onto a small island with a maximum demand of 613 kW (Refer to Fig. 1). The flywheels (referred to FWs, hereafter) are expected to alleviate the impact of wind penetration.
standard model for hydraulic turbines, and the validation of the scheme was investigated using only simulation analysis. Another scheme for stabilizing system frequency using FWs in an isolated grid including wind generation was proposed (Hamsic et al. [2007]). The actual power of the wind generation and system frequency was used as the input of the proposed scheme. The scheme was applied to real FWs installed in the Flores power system and verified its fundamental performance in the Flores isolated grid. However, no detailed control logic for FWs has been described in the paper.
FWs are known as one type of energy storage system and are suited for alleviating the high frequency fluctuation of output of wind power generation. Although various frequency stabilization schemes using FWs have been proposed, only a few schemes can be applied for an isolated grid. Thus, a scheme for stabilizing system frequency using FWs in a small power system including a wind farm was proposed (Takahashi et al. [2007]). In this paper, system frequency is used as the input of the proposed scheme. However, diesel generator models with a governor action were represented by a general IEEE 978-3-902661-93-7/11/$20.00 © 2011 IFAC
Diesel Generators
6G
7G
8G
9G
Rated Capacity 150 kW
Rated Capacity 245 kW
150 kW
245 kW
300 kW
300 kW
WT1
WT2
Wind Generators
Because a power system on a small island is an isolated power system, the increasing wind penetration causes the increase of frequency variation. In order to mitigate the increasing variation, the following three items are required: 1) development of accurate diesel generator models with a governor action; 2) extraction of wind power variation characteristics; 3) establishment of an effective frequency-stabilizing scheme using FWs.
Load
FW
Rated Capacity: 200 kW (W72 cm×H47.5 cm ×D82 cm×8 sets) Flywheel Energy Storage System
Fig. 1. A small remote islanded power system. In order to establish a proper control scheme, accurate diesel generator models with a governor action were firstly examined based on the measured values of generator dump tests in this study. Then, a new frequency-stabilizing scheme was developed using time-domain simulation, which consists of the developed diesel generator models and an equivalent load change representing wind power variation.
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
The developed stabilizing scheme was applied to the actual frequency-stabilizing system in the small island and verified its performance through connecting to the island power system. 2. DEVELOPMENT OF A DIESEL GENERATOR MODEL INCLUDING A GOVERNOR 2.1 Validation of the Governor Model of the Diesel Generators A governor model is a key generator controller for analyzing wind power impact on system frequency deviation in a small isolated power system. Although various types of governor models of steam turbines and hydro turbines have been used for power system planning and analysis, few governor models of diesel engines have been developed. Therefore, a generator dump test was performed for main diesel generators in the island grid in order to develop the governor model of a diesel engine. The following findings were obtained through the generator dump test.
Static and dynamic response characteristics for frequency change vary depending on the manufacturers of engines and/or governors.
Dynamic response characteristics of the same diesel generator vary depending on the magnitude of frequency deviation.
Based on the above findings, the governor model was developed considering the following two conditions:
The transient increase of generator power output and post-fault steady state generator output obtained from time-domain simulation should be consistent with the same increase obtained from the result of the generator dump test respectively with regards to a few different magnitudes of frequency deviations.
The calculated active power output was compared with the measured active power output. Based on the comparison, the construction of the model and the identification of its parameters were performed through trial and error. For example, one lead-lag element in Fig. 2 was applied for the governor model of 6G and 7G, while two lead-lag elements were applied for the model of 8G and 9G. The feedback control loop, including an integral element in Fig. 2, denotes a first-order lag element with a restricted rate of change and enables emulating a slow trend of the increasing generator output after a generator tripping. Two lead-lag elements in Fig. 2 enable emulating a transient response of the generator output immediately after a generator tripping. Although the washout element in Fig. 2 originally has the function of a high-pass filter, this element here has a role of eliminating high-frequency components from the original signal (output of the signal transducer in Fig. 2) through the accumulator element. That helps preventing excessive control. Post-contingency analysis showed steady-state frequency deviation obtained by the generator dump test was proportion to the output of the tripped generator. However, the largest frequency deviation was not proportion to the output. Therefore, the nonlinear element in Fig. 2 was introduced to match measured values with simulated ones for three different magnitudes of frequency deviations (about 0.3 Hz, 0.4 Hz, and 0.5 Hz). The example simulation results obtained by CRIEPI's Power Analysis Tools (CPAT) are shown with the testing result in Fig. 3. It should be noted that the responses of 6G, 8G, and 9G are the result in case of 7G tripping, and the response of 7G is the result in case of 6G tripping. As shown in Fig. 3, the developed governor model can express the response of the generator dump test precisely. 2.2 Validation of the small island power system model
The time to reach maximal generator output obtained from time-domain simulation immediately after a generator tripping should be consistent with the time obtained from the result of the generator dump test.
The small island power system model including not only diesel generators but transformers and loads should also be validated. Therefore, the small island power system model was developed and was validated through the dump test. The outline of the system model shows the following:
Fig. 2 shows the block diagram of the developed governor model of the diesel engine. The model parameters for each diesel engine are provided in Table 1. It should be noted that the model was not developed using a component-based approach, but it was developed using a measurement-based approach. The measured frequency is inserted into the input of the governor model as the rotor speed deviation in Fig. 2.
(1) Composition of the island power system model: The island power system model consists of diesel generator models for G6, G7, G8, and G9, a step-up transformer, transmission lines, and loads as shown in Fig. 1. Because the generator is almost directly connected to the loads, the reactance of the transmission lines was set to extremely low values.
Signal Transducer 1 Sg 1+T1S Rotor Speed Deviation
-
K
Governor Gain
Load Reference + +
Nonlinear Element
1 T4S
T3S 1+T2S Washout Element
Fig. 2. Governor model of a diesel engine. 12874
U L
First Lead-Lag Element 1+T6S 1+T5S
Second Lead-Lag Element 1+T8S 1+T7S
TQT Mechanical Output
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
Frequency [Hz]
Table 2. Generator constants
6G Tripping
60.0
Specification Rated capacity [kVA] Rated power [kW] Inertia constant [s]* D axis reactance [p.u.] D axis transient reactance [p.u.] D axis sub-transient reactance [p.u.] Q axis reactance [p.u.] Q axis sub-transient reactance [p.u.] D axis open circuit time constant [s] D axis transient time constant [s] D axis sub-transient time constant[s] Armature leakage reactance [p.u.] Armature time constant [s] Zero phase reactance [p.u.] Negative phase reactance [p.u.] *The inertia constant of the generator and its larger than that of only one generator.
59.8 59.6 7G Tripping
60.0 59.8
G9 [kW]
G8 [kW]
G7 [kW]
G6 [kW]
59.6
120 100 80 60 120 100 80 60
7G Tripping
6G Tripping
180 160 140 120 250
Table 3. Initial conditions for the generator dump test Case
7G Tripping 1 2
Measured Value Simulated Value
150 7G Tripping 10
20
30
40
50
9G 0.02 2.0 0.01 95 0.02 1.053 -0.1 0.01 0.20 0.50 0.01
(2) Load model: As the component of the loads in the island power system is obscure, a static exponential model with typical load voltage parameters was applied. The load voltage characteristics were given as constant current characteristics for active power and constant impedance characteristics for reactive power. Load frequency characteristics were not considered for this study because conservative simulation results were preferable. (3) Diesel generator model: The generator model with d-axis and q-axis rotor circuits was used because the transient response of generators is closely related to the dynamic behavior of system voltage and, eventually, loads and system frequency. Each rotor circuit includes one damper winding respectively. The generator constants are shown in Table 2. Although an inertia constant of generators and its engine is critical for this study, only the generator inertia was able to be derived from the design data. Therefore, the inertia con-
Frequency [Hz]
8G 0.02 0.05 0.01 16 0.1 1.053 -0.1 20.0 30.0 0.02 0.13
60.0 59.9 59.8 59.7 59.6 59.5
Active Power Output[kW]
Table 1. Parameters of the developed governor models 7G 0.02 0.25 0.015 40 0.1 1.053 -0.1 0.01 0.15
[kW] 150 150
Total Generation
Active 6G 7G 8G 9G Power 150 73 130 136 490 75 152 141 137 500
Reactive Power 130 120
Item Testing Result Simulation Result Bottom frequency 59.53 [Hz] 59.52 [Hz] 1 Time to reach the bottom frequency 1.15 [s] 1.20 [s] Post-disturbance steady-state frequency 59.76 [Hz] 59.79 [Hz] Bottom frequency 59.46 [Hz] 59.42 [Hz] 2 Time to reach the bottom frequency 1.27 [s] 1.22 [s] Post-disturbance steady-state frequency 59.77 [Hz] 59.77 [Hz]
Fig. 3. Example of the active power outputs of diesel generators No. 6 through No. 9 with frequency data.
6G 0.1 0.4 0.2 70 4.0 1.053 -0.1 0.7 4.5
6G 7G
Generator Trip- Active Power Outping Amount put [kW]
Case
Time [s]
Variable T1 T2 T3 K T4 U L T5 T6 T7 T8
Tripping Generator
Table 4. Frequency response obtained from simulation results and testing results
200
0
6G 7G 8G 9G 187.5 187.5 375.0 375.0 150.0 150.0 300.0 300.0 1.36 1.36 0.868 2.41 0.83 0.83 2.84 1.62 0.19 0.19 0.31 0.15 0.15 0.15 0.22 0.10 0.50 0.50 1.15 0.72 0.14 0.14 0.26 0.16 0.73 0.73 2.29 2.26 0.165 0.165 0.25 0.208 0.020 0.020 0.020 0.022 0.134 0.134 0.198 0.083 0.014 0.014 0.025 0.03 0.07 0.07 0.20 0.078 0.13 0.13 0.24 0.15 engine was assumed to be 1.5 times
240
Measured Value Simulated Value
9G
200
8G
160 120
7G
80 0
5
10
15
20
Time [s]
Fig. 4. Example comparison between measured and simulated value of frequency response and active power output response (Case 1). stant of the engine was assumed to be half of the generator inertia, the ratio of which is the smaller value selected from its appropriate range. (4) Generator control model: The standard AC exciter model, with its standard parameters, was applied. The developed governor model was also used. Example initial conditions for the generator dump test are shown in Table 3. The characteristic frequency response is shown in Table 4. The bottom frequency, the time it takes to reach the bottom frequency, and the post-disturbance steady state frequency obtained from time-domain simulation are
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
WP Output [kW]
Rated Rotating Speed 46 rpm
The installed wind turbines, produced by Vergnet in France, adopt a fixed-speed two-bladed wind turbine with active stall control. The characteristics of the fixed-speed two-bladed wind turbine are the appearance of remarkable power variations the frequency of which is proportion to the rated rotating speed of the wind turbine (0.769 Hz). Fig. 5 shows an example power spectrum of the system frequency and the wind power generation under its power output limitation (100 kW). The variation characteristics of wind power generation are summarized as follows:
120 Gain
10s 1+10s Washout Element
DP Active Power of Wind Generation [PU]
0.002[PU]
0.8 Gain
5s 1+5s Washout -0.002[PU] Element
180
2 -3
4
6N
2
10 6 4
4N
2
10
-4
4
10
Wind Generation Output System Frequency
2
6 4
1 0.8 0.6 0.4 0.2
Coherence between Wind Generation Output and Frequency 2
3
4 5 67
2
3
4 5 67
1 Time Period [1/Hz]
2
10
3
4 5
FWs are known as one of the effective ways to alleviate the frequency variation caused by wind power generation. The developed frequency-stabilizing scheme using FWs employs both wind power variation and the deviation of the system frequency as an input. Fig. 6 shows a block diagram of the FW model equipped with the developed scheme. The proper parameters of this scheme were derived considering rolesharing between diesel generators and FWs. The considera200
10000
-
0
100 -2[PU]
150
1N
2N
100
90 120 Time [s]
3.2 Development of a frequency-stabilizing scheme
+
PU→rpm
6000[rpm]
Scale Conversion
kW→PU
Inverter
1 240
-1 1+0.02s
+
+
1 1+0.02s Signal Transducer
2
PU→kW
+
DP Input Part
60
effective way to alleviate the frequency variation caused by wind power generation.
Based on the above findings, it can be observed that the two frequency components of the wind power variation have substantial impact on frequency fluctuation. Therefore, mitigation of the two frequency components with FWs is the most
1 DF Frequency 1+0.01s Deviation Signal [PU] Transducer
30
Fig. 5. Example of the power spectrum of wind power generation output and coherence between wind power generation output and system frequency.
(2) The coherence between wind power generation and the system frequency at the above two frequency components was high.
2[PU]
0
0.1
(1) Two frequencies, 0.769 Hz and 1.54 Hz, were obvious for both the wind power variation and frequency variation. Note that 1.54 Hz is double the rated rotating speed of the wind turbine.
pukW/puHz
Output of Wind Power Generation
2
3.1 Variation characteristics of wind power generation
Frequency of "2N" 1.54 Hz
Frequency fS [Hz ]
The dynamic behavior of wind power generation is important for the frequency-stabilizing system. Wind power generation output was represented as an equivalent time-varying negative load for time-domain simulation.
DF Input Part
180 120 60 0
Frequency of "1N" 0.769 Hz
2
3. DEVELOPMENT OF A FREQUENCY-STABILIZING SCHEME FOR THE FREQUENCY-STABILIZING SYSTEM
Table 5. Frequency change of wind power generation output
Coherence Wind Generation Output fS [kW ]
consistent with those three indices obtained from the testing result, respectively. As shown as Fig. 4, the transient response and the steady state response of each generator output obtained from time-domain simulation are also consistent with the same responses obtained from the testing result. Therefore, it can be concluded that the small island power system model expresses the frequency response properly.
+
w0 w
1 Ms 1500[rpm]
PU→kW 100×103
10000
+
0
-
-200
Scale Conversion
4373[rpm] 0.1
15 -15
1 1+5s Center Frequency Control
Fig. 6. Block diagram of the FW model equipped with the developed frequency-stabilizing scheme. 12876
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-
wREF + -
w [PU] PU→rpm
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
The time constant of the washout in the DP input part was set to 5 s in order to suppress the obvious high-frequency components of wind power vibration directly, while the time constant of the washout in the DF input part was set to 10 s. Not only the center frequency control but these two short time constants of the washouts also help the FWs to avoid the depletion of charge or discharge energy. As shown in Fig. 3, the rate of output change and the output change amount of 9G after the sudden frequency change were much larger than those of other diesel generators. It is considered that this difference is related to: the rated rotor speed of 9G, which is much higher than others, and the response time of its fuel supply control, which is much faster than others. Therefore, it might be difficult to adjust the power output of 9G within its proper operating range in case of large sudden frequency changes caused by wind power generation. Those two short-duration constants of washouts were selected considering the prevention of the abnormal operation of 9G. 3.3 Validation of the developed frequency-stabilizing scheme A start-up field test was assigned to one of the wind turbines in Jan. 2010. The data measured at the test was used for the verification of the performance of the developed frequencystabilizing scheme. In order to evaluate the high penetration of wind power generation (the interim goal was 5 min average penetration up to 50%) through time-domain simulation, the measured values were extended 2.75 times larger than the original measured values. Operating diesel generators were assumed to be 6G, 7G, and 9G. Their initial outputs were set to 100 kW, 100 kW, 284 kW, respectively.
Active Power Output [kW]
300
G6 G7 G9
200 100 0
WP Output [kW]
WP Output
400 300 200 100 0 0
30
60
90 120 Time [s]
150
180
(a) Simulation result without FW
Frequency [Hz]
(3) Center frequency control was originally equipped in the frequency-stabilizing system. This control helps FWs to avoid the depletion of charge or discharge energy. If the rotating speed of the FWs reaches the lowest or the highest speed, its charge energy or discharge energy will be depleted and that depletion leads to the undesirable sudden change of the frequency. Therefore, the rotating speed of the FWs should be controlled near the center of the rotating speed (4,373 rpm) using the center frequency control, unless a large sudden frequency change occurs. The parameters of the center frequency control were selected in order to position the rotating speed of FWs back to the center quickly, after a large sudden frequency change.
Frequency 60.36Hz
500
Rotating Speed [RPM]WP FW Output [kW] Active Power Output [kW]
(2) Deviation of the system frequency was used as the DF input of the developed scheme. The parameters of the DF input part in Fig. 6 were selected in order to extract a specified frequency component range (0.1 Hz or higher) of the load variations, which is difficult for diesel generators to suppress.
61.0 60.8 60.6 60.4 60.2 60.0 59.8
0.39Hz 0.39Hz
(1) Wind power variation was used as the DP input of the developed scheme. The parameters of the DP input part in Fig. 6 were selected in order to extract a specified frequency component range (0.2 Hz or higher) of wind variations, including 0.769 Hz and 1.54 Hz.
Frequency [Hz]
tion for deriving the parameters is described below.
61.0 60.8 60.6 60.4 60.2 60.0 59.8
Frequency
300
G6 G7 G9
200 100 0
WP Output,
FW Output
400 200 0 -200 6000 5000 4000 3000 2000
FW Rotating Speed 0
30
60
90 120 Time [s]
150
180
(b) Simulation result with FW
Fig. 7. Time series data of wind power generation output (2.75 times larger than the actual measured data). Figure 7(a) shows an example simulation result without FWs. The average system frequency was 60.36 Hz (see Table 6) during the operation of the wind turbine because the Load Frequency Controller (LFC) was not equipped. If the average frequency was shifted to 0 Hz with the AFC, the frequency deviation was plus or minus 0.39 Hz, which exceeded the
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18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
desired frequency deviation (normally between 0.2 Hz and 0.3 Hz). Moreover, the generator output of 9G was sometimes below zero, which might cause tripping of 9G due to its reverse power relay. In other words, this simulation result revealed that the small island power system cannot maintain power quality and power system stability without a frequency-stabilizing system if high wind penetration such as 50% is pursued. Figure 7(b) shows the same example simulation result with FWs. As shown in this figure, FW output increased its output while wind power generation decreased its output and vice versa, if a specified frequency component range (0.1 Hz or higher) of the wind generation and system frequency was focused on. If the average frequency was shifted to 0 Hz with the LFC, the frequency deviation was plus or minus 0.12 Hz, which is much smaller than the desired frequency deviation (see Table 6). Figure 8 shows the power spectrum of the frequency with and without FW along with the power spectrum of the FW output. FWs mitigated a frequency component range of the system frequency between 0.033 Hz and 3.33 Hz effectively.
4.1 Performance of the frequency-stabilizing scheme with regard to various frequency components of wind power generation Figure 10 shows the filtered total output of wind power generation and the filtered FW output. The filter was designed for extracting a specified frequency range (0.20 Hz or higher). The filtered FW output increased its output, while the filtered total wind power generation decreased its output and vice versa. That means that the frequency-stabilizing scheme, especially the DP input part in Fig. 6, effectively mitigated the obvious frequency components of the system frequency variation caused by wind power generation. Figure 11 shows another filtered total output of wind power generation and another filtered FW output. The filter was designed for extracting a specified frequency range (0.025 Hz or higher). The filtered FW output increased its output, while the filtered total wind power generation decreased its output and vice versa. That means that the frequency-stabilizing scheme, especially the DF input part in Fig. 6, effectively mitigated the obvious frequency components of the system frequency variation caused by wind power generation. 4.2 Performance of the frequency-stabilizing system using flywheels
The developed stabilizing scheme was applied to the frequency-stabilizing system using FWs in the isolated small island grid. The performance of the frequency-stabilizing system was verified under a 5 min average penetration of 48%. As shown in Fig. 9, the system frequency deviation was within plus or minus 0.1 Hz. That value was almost the same as the simulation result (0.12 Hz) described in Section 3. That means the developed frequency-stabilizing system successfully mitigated the frequency variation caused by wind power generation.
Figure 12 shows the example response of FWs and diesel generators when one wind turbine (150 [kW]) was tripped due to its power output limitation control. The FWs promptly controlled its output, which led to the mitigation of not only frequency fluctuation but the power output variation of the diesel generators within their proper operating range. The frequency fluctuation after the tripping was also effectively mitigated with the introduction of FWs even without excessive compensation. Figure 13 shows another sample response of FWs and diesel generators when G7 (150 [kW]) was intentionally tripped. Although only the DF input part in Fig. 6 is active, the FWs
-5
10
Power Spectrum of Frequency without FW Power Spectrum of Frequency with FW
-7
10
-7
10 10
-10
10
-13
Power Spectrum of FW Output 0.1
1 10 Time Period [1/Hz]
100
Fig. 8. Power spectrum of frequency with/without FW and the power spectrum of the FW output. Table 6. Simulation result of frequency change Stabilizing System
Fmax[Hz]
Fmin[Hz]
DF[Hz]
F
Median F
Without FWs With FWs
0.75 0.48
-0.02 0.24
±0.39 ±0.12
0.117 0.044
0.36 0.37
Frequency [Hz]
-3
10
60.2 60.1 60.0 59.9 59.8
Active Power [kW]
-1
10
320
Total Output of Diesel Power Station Total Output of Wind Power Generation
280 240 200
FW Output [kW]
2
FW Output fS [kW ]
2
Frequency fS [Hz ]
4. VERIFICATION OF THE PERFORMANCE OF THE DEVELOPED FREQUENCY-STABILIZING SYSTEM IN THE SMALL ISLAND GRID
40 20 0 -20 -40 0
50
100 Time [s]
150
200
Fig. 9. Example of measured data under high wind penetration (5 min average penetration: 48 %). 12878
Frequency [Hz]
250 200 150
Nonfiltered Total Output of Wind Power Generation
20 0 -20 -40 30
Active Power [kW]
Filtered Total Output of Wind Generation (over 0.2 Hz) Filtered FW Output (over 0.2 Hz)
20 10 0 -10
5
10 Time [s]
15
20
Fig. 10. Filtered FW output and wind power generation output (cut-off frequency: 0.2 Hz).
FW Output [kW]
Nonfiltered FW Output
0
250 200 150 100 80 40 0 -40 0
50
100 Time [s]
150
200
WP [kW]
200 150
Total Output of Wind Power Generation
20 0 -20 -40
FW Output Filtered Total Output of Wind Generation (over 0.025 Hz) Filtered FW Output (over 0.025 Hz)
40 20 0 -20 0
20
40
60
80
100
Time [s]
Fig. 11. Filtered FW output and wind power generation output (ut-off frequency: 0.025 Hz). promptly controlled its output from -10 kW to 50 kW, which contributed to the mitigation of not only frequency deviation but also the power output variation of the diesel generators. It should be noted that generator tripping could cause larger frequency deviation than the cut-out of a wind turbine.
Load [kW] Frequency [Hz]
Fig. 12. Example of measured data when one wind turbine stopped due to its power output limitation control.
250
FW [kW]
Total Output of Wind Power Generation 6G, 8G, 9G
300
-20
FW, WP [kW]
60.1 60.0 59.9 59.8 59.7
60.00 59.90 59.80 59.70
FW Output [kW] Active Power [kW]
FW, WP [kW]
FW [kW]
WP [kW]
18th IFAC World Congress (IFAC'11) Milano (Italy) August 28 - September 2, 2011
300
540 520 500
200 100
6G,
0
7G,
8G,
9G
60 40 20 0 -20 -40 0
10
20 Time [s]
30
40
Fig. 13. Example of measured data in case of a 7G tripping. tion Funds for Promotion of Okinawa.
5. CONCLUSION The developed stabilizing system using FWs is currently operating in the small island power system and has shown great performance for alleviating frequency variation caused by wind power generation. The FWs have contributed to increase in wind power generation and decrease in diesel fuel usage. Future work would be concerned with the development of a voltage-stabilizing scheme and with the integration of the voltage stabilizing-scheme into the developed frequencystabilizing scheme. ACKNOWLEDGEMENTS This work was supported in part by the Ministry of Economy, Trade and Industry in Japan under Grant Special Coordina
REFERENCES CRIEPI (1991). Integrated Analysis Software for Bulk Power System Stability, CRIEPI report, ET90002, July 1991. Hamsic, N, Schmelter. A, Mohd, A, Ortjohann. E, Schultze, E, Tuckey, A, and Zimmermann, J (2007). Increasing renewable energy penetration in isolated grids using a flywheel energy storage system, IEEE International Conference on Energy and Electrical Drives, 2007 pp. 195–200. Kundur, P (1994). Power System Stability and Control, McGraw-Hill, New York. Takahashi, R, and Tamura, J (2007). Frequency stabilization of small power systems with wind farm by using flywheel energy storage systems, IEEE International Symposium on Electronics and Drives, 2007 pp. 393–398.
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