Power Smoothing and Power Ramp Control for Wind Energy Using Energy Storage

Ali Esmaili and Adel Nasiri Electrical Engineering and Computer Science Department

University of Wisconsin-Milwaukee Milwaukee, WI 53201

Email: nasiri@uwm.edu; URL: www.uwm.edu/~nasiri

Abstract— Due to randomness of wind speed, the wind farm output power varies drastically. These fluctuations make undesirable effects on the voltage, frequency, and transient stability of the utility grid. In this paper, two types of energy storage devices are integrated with a wind farm to support the short-term shortcomings of wind energy. The support specifically improves power ramp rate control and power smoothing. The utilized energy storages devices are zinc bromide flow battery and Lithium-Ion Capacitors (LIC). The actual models of the battery and ultracapacitor, which are derived from testing, are used in this study. The power data for the wind farm and load are actual data from a local power system. The analysis shows that considerable improvements can be made to shape the output power of the farm using the energy storage systems.

I. INTRODUCTION Energy consumption has increased all around the world.

World net electricity generation increases by 87 percent in the IEO2010 reference case, from 18.8 trillion kWh in 2007 to 25.0 trillion kWh in 2020 and 35.2 trillion kWh in 2035[1]. Moreover, due to price volatility, limited supply, and environmental concerns of fossil fuels, wind power generation is rapidly growing as an alternative energy source in many parts of the world [2]. According to American Wind Energy Association (AWEA), wind energy is now the largest new source for electricity production. Installed wind energy capacity in the U.S. was at 40,180MW by the end of 2010. Since the investment in large power plants has been lowering, the need for new electrical power sources could be very high in the near future.

It is clear to everyone that renewable energies, including wind turbines, have many advantages, however, the higher injection of wind energy power, the more technical and non-technical issues have been manifested. These issues include power quality, reliability, safety and protection, load management, grid interconnections and controls, new regulations, and grid operation economics [3-5].

Randomness of wind speed is probably one of the main drawbacks of wind energy. Energy storage elements when integrated with renewable energy systems can alleviate many

of these problems and facilitate higher penetration of renewable energy systems [6-9].

Many studies have been done to smooth wind turbines’ output power fluctuations. One study indicates that short-term wind power fluctuations could be reduced to half by a storage capacity of 25 kWh per MW of wind power [10]. In another work, active output power was conditioned via a shunt inverter connected to ultracapacitor storage system [2]. Authors in [11] used ultracapacitor or battery connected to the DC bus of a doubly fed induction generator via a DC/DC converter in order to adjust the power exported to the grid.

In this paper, two different storage devices are integrated with the wind turbine to adjust the total output power. Ultracapacitor is one type of storage which is directly located in the DC bus of a double-conversion wind turbine. The other storage device is a battery which is connected to the DC bus via a DC/DC converter.

Analyses and modeling are conducted in this paper for power ramp control and power smoothing using practical models of all components and real data. The analyses are provided for a single turbine and a wind farm consisting of 21 turbines. The difference between the desired and actual power can be either injected or drawn from the storage system. Monitoring the output power of the farm instead of each single turbine to adjust the storage charging and discharging results in a need for smaller energy storage devices.

There are other techniques to perform the power smoothing and ramp control of wind turbines e.g. using the power electronics converters instead of energy storage systems. However, those techniques will reduce the total energy produced by the turbines. For instance, [12] reports that to limit the ramp up and ramp down rate of a farm to 0.1 per unit per minute, 18% of the total energy production of the wind farm will be lost.

II. SYSTEM DESCRIPTION The studied system in this paper contains three major

components: wind farm, ultracapacitor energy storage, and utility level zinc-bromide energy storage. Both battery and

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ultracapacitor are integrated at turbine level. The components are discussed in the following.

A. Wind Farm The wind farm consists of 21 wind turbines are

connected to the main substation in the wind farm. It is assumed that the turbines in a row see a similar wind speed profile with time delay. Therefore there is coloration between the wind speed profiles. The whole wind farm is designed for 48.3 MW of rated capacity.

As mentioned before, two different type of storage devices are connected to each wind turbine: a string of ultracapacitor, which includes 378 cells, and one 50kWh battery storage. The string of ultracapacitor has the capacity of 5.82F, rated current at 220Amps, and the voltage range is between 900v-1400v. The configuration of each single turbine is illustrated in Figure 1. The components include:

- A 2.3MW double-conversion wind turbine system.

- Ultracapacitor strings directly placed on the DC bus of the double conversion system.

- Battery storage connected to the DC bus through a bi- directional DC/DC converter.

The AC/DC converter operates the generator on Maximum Power Point Tracking (MPPT). The DC/AC converter exports the power to the grid. The DC/AC inverter will perform power smoothing and power ramp control via the charging and discharging of the ultra capacitors and battery storage. The wind turbines are connected to the grid via the power conversion circuitry and transformer. The generator could be of synchronous (permanent magnet or wound) or induction type.

Figure 1. Configuration of each turbine integrated with energy storage

systems.

B. Ultra capacitor There are currently several types of energy storage

technologies which provide different characteristics, e.g. energy and power density, efficiency, cost, lifetime, and response time [15-16]. Examples of energy storage systems are ultra-capacitors, superconducting magnetic energy storage systems (SMES), flywheels, batteries, compressed air, pumped hydro, fuel cells, and flow batteries [17]. Some of these devices have a quick response time with high power density such as ultra capacitors and SMES, which are proper technologies to deal with transient and short-term issues.

Compressed air and hydro systems are appropriate for high energy long term applications.

The ultracapcitors used in this research are LICs. In order to reduce the output power variations, ultracapacitor energy storage on the DC link is utilized. Such energy storage gives the device an additional degree of freedom in controlling of the output power. They utilize a hybrid technology to provide an energy density which is four times greater than that of conventional electric double layer capacitors (EDLC) (super capacitors or ultra capacitors). LICs combine a cathode constructed from activated carbon with high capacitance, typically found in EDLCs, with an anode constructed from structure-controlled carbon doped with lithium, commonly found in Lithium Ion Batteries (LIB). Li-doping of the anode lowers its potential, resulting in a doubling of the overall cell’s capacitance, without increasing the size or weight of the package. The lower potential allows LIC to operate at 3.8V, which doubles the cell’s energy storage. The minimum cell voltage is 2.2V. It also offers the power and long cycle life typically associated with capacitors. LICs increase in energy and power density results in shift in energy/power density relative to EDLCs. Compared to EDLCs, LICs have a significantly lower self discharge rate of less than 5% after 3 months. Unlike lithium-ion batteries no thermal chain reaction occurs, since the positive electrode does not react with electrolyte [13].

C. Battery

The battery storage used in this paper, is zinc-bromide flow batteries. Zinc bromide battery energy storage devices with pumped electrolyte batteries are generally suitable for large scale power utility, vehicular and industrial applications with energy storage requirements of 50 kWh and above. This type of battery utilizes continuous circulation of electrolytes to feed reactants to the battery stacks. Zinc metal is chemically plated onto the electrodes during charging and is re-dissolved into the electrolytes on discharging. The reaction is reversible and non-destructive. Zinc Bromide Batteries can exceed 2000 full charge and discharge cycles during their operating lifetime compared with 750 cycles for conventional lead acid batteries. They are capable of full discharge (100% of stored energy) without any damage to the battery. Their energy density is in the range of 65–84 Wh/Kg and they can operate at a wide range of temperatures without degradation. The materials of the components can be made entirely with plastic to reduce costs and provide readily for recycling or disposal. In addition, they use a low toxicity electrolyte and recyclable plastic battery stacks compared with more toxic lead and sulphuric acid [18]. The battery model is composed of three elements, Open Circuit Voltage (OCV), self discharge resistance, and internal resistance [18]. All these elements are function of the State of Charge (SOC). The self discharge resistance, however, does not vary significantly, so that it could be considered as a constant value. The measured value of the

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self discharge resistance is 12 Ω . Internal resistance is a function of many variables, but it mainly depends on the cell and ambient temperatures and the SOC. The internal resistance is also a function of the materials and the geometrical construction of the plates.

III. POWER RAMP CONTROL Utility companies impose a ramp up and ramp down rate

on all power generation sources. There are proposals to apply similar limitations on wind farms [19-20]. For the proposed system, the ramp up and down rate is considered to be limited at 5% per minute for the last minute average. It means that the farm power can ramp up or down for more than 2.4 MW per minute (or 40kW per second), if the average power for the last minute is at 48MW. Charging/discharging of batteries and ultracapcitors will be utilized to reach at this ramp rate level for the wind farm. It should be noted that in the systems without storage, the power ramp is controlled by adjusting the incoming electric power from the turbine, consequently decreasing the power capturing efficiency of the turbine.

For power ramp control, there are three possible tasks for the storage device depending on the actual power ramp rate. The storage device may have to charge/discharge to limit the ramp rate. The rate of charging or discharging depends on the power difference between desired and actual value. In some cases of input/output current restrictions of storage system, limits the power transmission and cause partial coverage. It will be explained more in details in next sections.

Figure 2 shows the ideal output after ramp control. Green profile shows the desired output when the ultimate change is less than 5% of the last value. Convergence is an advantage of this method. In other words, all desired value converge to the same profile after a while, regardless of the initial value.

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Time (second)

Pow

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Actual powerDesired ramp controled power

Figure 2. Desired and actual power profile for a 2.3MW wind turbine.

IV. POWER SMOOTHING Since captured power by a wind turbine is proportional to

the cube of the wind speed, any small variation in the wind speed makes an enormous change in the output power. Since all wind turbines are located close to each other, there is coloration between their speed profiles and results in averaging the output. Consequently, the rises and falls in the wind farm output power is much less than the output of a

single turbine, but the averaging is not typically enough to prevent unacceptable variations on the frequency and voltage supplied to a stand alone load or weak utility [21].

In order to resolve the above problem, a simple moving average technique has been used in this paper. In order to smooth the output power, the output is forced to the average of the last 60 seconds for each single second. Figure 3 shows the output before and after smoothing. The difference between smoothed and actual profile either charges the storage devices or discharge them. Storages are large enough to support the difference in many areas; however, the current limitation creates some restrictions. The practical case with constraints is discussed in the next section.

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Actual After Smoothing

Figure 3. The output power before and after power smoothing.

V. COMBINATION OF POWER RAMP AND SMOOTHING CONTROL

As seen in Figure 3, the green profile is much smoother than the actual profile, however, it cannot compensate for the high ramp rates. Therefore, the best result will be achieved, if both techniques are combined. The combination of techniques has been applied and is illustrated in Figure 4. The total energy storage requirement is higher to perform both tasks.

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0

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ActualAfter ramp and smoothing

Figure 4. The output of single wind turbine before and after both

smoothing and ramp control techniques are applied.

As explained before, the fluctuations in the output power of the wind farm is much less than the output of a single turbine. Thus, the power difference between actual and smoothed power are less, compared to a single wind turbine. Figure 5 demonstrates power before and after smoothing on

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a wind farm. The discussed difference is visible on the peaks as shown in figure 6.

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Figure 5. The output power before and after both smoothing and ramp

control techniques are applied.

VI. PRACTICAL CONSTRAINTS AND SYSTEM PERFORMANCE

Table 1 shows the specification of storage devices including a zinc-bromide battery and a string of ultracapacitor. The rated current of the ultracapacitor module is at 220A. The short-term (5 seconds) current rating of the module is three times larger. The battery efficiency is approximately 80%, with the capacity of 50kWh and power rating of 25kW. The efficiency increases when the rate of charge/discharge decreases.

TABLE I. ENERGY STORAGE DEVICE SPECIFICATIONS

Zinc-bromide Battery Rated Power : 25kW Energy Capacity : 50kWH

Lithium-ion capacitor module

Cells per module: 378 Capacitance per cell: 2200F Rated current: 220A Minimum voltage: 900V Maximum voltage: 1400V Capacitance: 5.82F

In order to quantify the performance of the system, we define the following parameters:

- Full Coverage Percentage (FCP) as:

timecycle Total

timeCyclepower desired poweroutput ==FCP (1)

- Area Coverage Percentage (ACP):

power) desired poweroutput (Energy Total

Energy Total1

≠

−=while

outputdesiredtheandoutputactualbetween

outputdesiredtheandoutputbetweenACP (2)

FCP and ACP can provide an indication on how well the output power profile tracks the desired one. While the FCP provides the ratio for the covered time over one cycle, the ACP provides the ratio of difference between the desired and conditioned power profile with the actual profile for the

partially conditioned sections only. The ACP indicates how effective the conditioning has been although it may not be 100%.

Given these values, it is easier to calculate the additional energy storage and/or the increase in the existed energy storage system power ratings to achieve acceptable FCP. The optimal value of FCP is at 100%. This means that the energy storage system capacity and/or its ratings are enough for the output power to track the desired profile.

For a given power profiles of Figure 6, the FCP and the ACP can be calculated as follows:

%7580

)4580()025( =−+−=FCP

In this particular case, the limitation of the used energy storage system is capable of providing the desired power profile for 75% of the total time.

ACP can also be calculated by dividing the area B( green) (6242 kWs) over the area A (yellow) (2134kWs) plus area B (green).

%53.7462422134

624262422134

21341 =+

=+

−=ACP

The higher the ACP, the better the performance.

Figure 6. Sample power profile for FCP and ACP

VII. RESULTS Figure 7 illustrates the output power of the whole wind

farm at the grid point of view after using storage systems. As it can be seen, some part of the actual profile is entirely pushed to the desired value by the storage systems. Conversely, output is exactly same as actual profile due to lack of storage capacity in a few areas. Array A in figure 8 points one of these areas. Output profile has perfectly followed the desired value for a while. Storage systems are fully charged and no room is left to absorb extra energy at 7020 seconds. Therefore the final output power profile suddenly jumps up and starts following the actual power profile till actual power profile crosses zero. Then the storage systems are being discharged to push the actual profile to the desired profile till they are fully discharged. This is shown by array B. At the end of the B area, storage systems are

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empty. Due to losses in the system the B area is just little smaller than the A area.

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A

B

Figure 7. Output at the grid point after using both ultra capacitor and battery

Different cases have been studied in this paper. The 1st case is integrating ultracapacitor to an individual wind turbine. In next step, a battery was added to the system. Table 1 shows FCP and ACP for an individual wind turbine in both cases. Battery improves the result by 16%. However, the final FCP is 11.7%, which is not considerable. In order to increase the FCP, the simplest solution is increasing the storage capacity. However, another solution is sharing the capacity of the storage devices between all wind turbines and control the charging and discharging at the Point of Common Coupling (PCC).

TABLE II. FCP AND ACP FOR SINGLE 2.3 MW WIND TURBINE

Table II shows FCP and ACP for the whole wind farm when each turbine is equipped with one ultracapacitor while the capacity is shared between all wind turbines. As seen in table III, FCP improves almost 300%. The improvement has two main reasons: 1- The capacity is shared among the farm. 2- Wind farm roughly does averaging of all wind turbines output and makes the output power profile smoother than one individual wind turbine.

TABLE III. EFFECT OF USING ULTRACAP ON A WIND FARM TURBINE INCLUDING 21 OF 2.3 MW WIND TURBINES AND AN INDIVIDUAL 2.3 MW

WIND TURBINE

Ultracap module specifications FCP ACP5.82 F. ±220Amp. 900-1400 Volts 10.12% 8.02% 21 of 5.82 F. ±220Amp. 900-1400 Volts 40.33% 10.45% Improvement 298.52% -----

Adding battery helps the ultracapacitor to reach the full coverage in some areas. Moreover, the battery partially covers over the whole operation time. These changes are shown in Figure 8.

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Time(second)

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ActualDesiredAfter Ultracap and battery

Figure 8. The output after using ultracap and battery packages (21 of

5.82Farad-current limitation=220-21 batteries: 25kW-50kWH)

Table IV compares these two cases. FCP increased 4.25% after adding batteries. Therefore adding battery, using ultracapacitor, and most of all sharing the capacities almost covers half of the power profile, while it was 11.76% for the same case when one individual isolated wind turbine was studied ( Having battery and ultracapacitor for an individual wind turbine changes FCP to 11.76%).

TABLE IV. EFFECT OF USING ULTRACAP ON A WIND FARM TURBINE INCLUDING 21 OF 2.3 MW WIND TURBINES WITH AND WITHOUT BATTERY

Storage module specifications FCP ACP21 of 5.82 F. ±220Amp. 900-1400 Volts 40.33% 10.45% Ultracap packages: 21 of 5.82 F. ±220Amp. 900-1400 Volts Batteries:21 of 25kW-50kWH

44.58% 18.72%

Improvement 10.54%% -----

Last modification would be doubling the ultracapacitor capacity. In this case, another string of ultracapacitor will be added to each wind turbine. Therefore, the capacity of the entire wind farm will be doubled. Doubling the capacity gives the controller more flexibility since there is more room for both absorbing and releasing energy.

Figure 9 illustrates output after doubling the ultracapacitor. Brown arrows show significant changes after adding another string of ultracapacitor. As shown with brown arrows, some areas are completely covered while they were either partially covered or not covered at all before in Figure 9.

Storage module specifications FCP ACPUltracap only: 5.82 F. ±220Amp. 900-1400 Volts

10.12% 8.02%

Ultracap only: 5.82 F. ±220Amp. 900-1400 Volts Battery: 25kW-50kWH

11.76% 10.77%

Improvement 16.21% -----

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x 104

Time(second)

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er(k

W)

ActualDesiredAfter doubling ultracap

significant changes

Figure 9. Changes in output after doubling the ultracap packages (21 of

11.64Farad-current limitation=440)

Table V shows FCP and ACP after the last change. Adding another string of ultracapacitor made 19.6% improvement on FCP and increased the FCP up to 53.33%. Using two strings of ultracapacitor along with battery, covers more than half of the operation time perfectly. There are some methods to increase the FCP, they have been under studied. The methods include: increasing the ramp limit, using dynamic ramp control instead of fix ramp, and predicting wind profile. Increasing the number of storage devices, improves the FCP as well, however, it might not be economic.

TABLE V. EFFECT OF DOUBLING ULTRACAPACITOR PACKAGES ON A WIND FARM INCLUDING 21 OF 2.3 MW WIND TURBINES

Storage module specifications (21 battery is included in both cases)

FCP ACP

Ultracap packages: 21 of 5.82 F. ±220Amp. 900-1400 Volts

44.58% 18.27%

Ultracap packages: 42 of 5.82 F. ±220Amp. 900-1400 Volts Or Ultracap packages: 21 of 11.64 F. ±440Amp. 900-1400 Volts

53.33% 10.80%

Improvement 19.63% -----

VIII. CONCLUSION In this paper, ultracapacitor and battery have been used to

smooth the output of a wind farm as well as controlling the output ramp. A technique was introduced to achieve this goal and make a desired output profile. Analysis shows that the storage devices could shape the actual profile to the desired curve perfectly on more than half of the operation time. The rest of the time was partially covered. Therefore a proper control algorithm and storage devise can mitigated wind power variations and fluctuations.

ACKNOWLEDGEMENT This material is based upon work supported by the National Science Foundation under Grant No. 0925709.

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