JP5013372B2 - Manufacturing method of storage battery equipment for wind power generator - Google Patents

Description

  The present invention relates to a method and a storage battery facility for providing a storage battery having an optimum capacity that minimizes the facility cost in a storage battery facility for leveling generated power in parallel with a wind power generator introduced into a power system.

In recent years, there has been concern about the depletion of fossil fuels such as oil and coal, which are energy resources. In addition, CO ₂ concentration in the atmosphere has increased and global warming has progressed due to an increase in CO ₂ emissions due to an increase in power demand and a decrease in CO ₂ absorption sources due to forest destruction. Against this background, wind power generation systems using wind energy are attracting attention around the world, especially in Europe and the United States. Wind power generation system is intended to take advantage of the inexhaustible natural energy, because it is a clean power generation facilities that do not emit CO _2, also in Japan, the total installed capacity of wind power generation is thought to increase in the future.

Since the output power of the wind power generator is proportional to the cube of the wind speed, it fluctuates violently as the wind speed changes. For this reason, as the capacity of the wind power generation system introduced into the power system increases, system voltage fluctuations and system frequency fluctuations occur due to power generation fluctuations of the wind power generator, and power quality is likely to deteriorate.
For this reason, when a wind power generator is introduced into an electric power system, it is necessary to level the generated power fluctuation to an allowable range. In particular, some measures are required to introduce a large-scale wind power generation system into a power system. Conventionally, it has been common practice to level a wind power generation by adding a storage battery to a wind power generator. By attaching a storage battery to the wind power generation system, it is possible to level the fluctuation in the generated power of the wind power generation and suppress the influence on the power system. By using the storage battery, it is possible to compensate for fluctuations in the generated power from the short cycle to the long cycle of the wind power generation system.

However, when a storage battery is attached, the equipment cost increases, and the storage battery characteristics deteriorate with time, so a maintenance cost is also required.
The storage battery equipment cost and maintenance cost depend on the charge / discharge characteristics of the storage battery, and the charge / discharge characteristics are determined by the characteristics of the controller of the storage battery.
The storage battery attached to the wind power generator is intended to level the fluctuation of the generated power and is more effective as the capacity is larger. However, it is preferable to introduce a storage battery with as small a capacity as possible from the viewpoint of equipment cost.
Conventionally, a method for evaluating the leveling effect due to charging / discharging of the storage battery is known, but there is no literature that discloses a controller characteristic of the storage battery or an evaluation method for the storage battery cost.

For example, Patent Document 1 discloses a wind power generation output stabilization method using a storage battery, but the storage battery is connected to a power line via a converter and an inverter, and the moving average value of the generated power of the wind power generator in a minute unit time is calculated. The excess is stored in the storage battery when the generated power is larger than the moving average value, and when there is a shortage, the shortage is supplied from the storage battery to the power line, and the idea of optimizing the capacity of the storage battery is included. Absent.
Patent Document 2 discloses a method for determining a storage battery capacity of a system in which a storage battery is combined with a solar battery. This disclosure method uses the capacity and price of the solar cell and the capacity and price of the storage battery as parameters, and creates an economic evaluation chart that expresses the merit obtained by performing a simulation using the measurement data of the total solar radiation, The most economical combination of solar cell and storage battery will be determined.
Since the method disclosed in Patent Document 2 is intended for a solar cell system, it cannot be applied to wind power generation in which instantaneous generated power fluctuates drastically.
JP-A-11-299106 JP 2004-032989 A

  Therefore, the problem to be solved by the present invention is to provide a storage battery that has an optimum capacity that minimizes the equipment cost in a storage battery that is provided in a wind power generator and leveles fluctuations in generated power by charging and discharging.

  In order to solve the above problems, a storage battery facility used in the wind power generator of the present invention includes a storage battery, an inverter, and a storage battery controller, and supplies power to the system in parallel with the wind power generator. The storage battery controller includes an average calculator that calculates the moving average value of the generated power of the wind power generator, a subtractor that subtracts the generated power value of the wind power generator from the moving average value to obtain a deviation, and the remaining battery capacity value An adaptive gain controller that can be said to be a function generator, and a multiplier that multiplies the correction coefficient input from the adaptive gain controller by the capacity value of the inverter to output a corrected power value; An adder for adding the deviation and the corrected power value, and an output limiter for limiting the output of the adder with upper and lower limit values and outputting the output command value of the storage battery are provided.

The storage battery output command value instructs the storage battery to store an excess amount compared to the moving average value of the power generated by the wind power generator, and to replenish the shortage amount from the storage battery. It is leveled to the average value and does not show severe power fluctuations.
Further, if the remaining capacity of the storage battery is far from the target 50%, a large correction amount acts on the output command value of the storage battery, so that the remaining capacity of the storage battery is always managed to be in the vicinity of the target value.

The upper and lower limit values of the output limiter are determined in relation to the inverter capacity.
The remaining capacity of the storage battery may be calculated by integrating the storage battery output command value with an integrator.
Further, a dead zone element may be provided between the subtracter and the adder so that the output to the adder becomes zero when the absolute value of the deviation does not reach a predetermined value.

Using the battery controller model of the present invention, the number n of data used for moving average calculation, the slope α in the correction coefficient of the adaptive gain controller, and the dead band width Dzone are set, and a charge / discharge simulation is performed to determine the maximum generated power fluctuation ΔPmax. Assuming that the standard deviation σx of the combined output power fluctuation ΔPsys satisfies the determined condition, the storage battery capacity C _B and the inverter capacity C _{I at} which the equipment cost Ccap = C _B C _P + C _I C _W is minimized are obtained. Here, C _P is the cost per capacity of the storage battery, and C _W is the cost per capacity of the inverter.
Controller parameters n, alpha, by varying within a range set to Dzone, battery capacity C _B comprising equipment cost Ccap is minimized within the range, the inverter capacity C _I when determining the controller parameters at that time, These values are the optimal solutions.

  In the present invention, in the above system in which the wind power generator is provided with a storage battery that equalizes wind power generation fluctuations by charging and discharging, the optimum capacity that minimizes the storage battery facility cost by simulation based on wind speed observation data obtained in the field is obtained. Can be calculated. The optimal capacity of the storage battery is simulated using field observation data under conditions where the parameters of the storage battery controller are exhaustively changed at large intervals, and the storage battery capacity and inverter capacity that minimize equipment costs are locally determined. Search by simple simulation.

The power generated by the wind power generator fluctuates violently with changes in wind speed. Although the generated power fluctuation can be leveled by providing a storage battery, the leveling effect varies depending on the storage battery capacity and the inverter capacity. Further, the charge / discharge operation of the storage battery is greatly influenced by the controller parameters of the storage battery.
The storage battery equipment used in the wind power generator according to the present invention has an optimal storage battery capacity and inverter that minimizes the equipment cost while the composite output power fluctuation satisfies the restriction condition, with the condition that the power generation fluctuation is leveled to the allowable value Capacity and storage battery controller parameters may be provided.

Hereinafter, the present invention will be described in detail based on embodiments with reference to the drawings.
FIG. 1 is a block diagram of a storage battery controller of a storage battery facility used in a wind power generator according to this embodiment, FIG. 2 is a connection diagram of a storage battery facility used in a wind power generator, and FIG. 3 is an adaptive gain controller used in the storage battery controller. FIG. 4 is a graph showing the measured wind speed data over one year, FIG. 5 is a table showing the correspondence between the surface condition and the correction coefficient, FIG. 6 is a graph showing the operating characteristics of the wind power generator, and FIG. 7 is the measured wind speed. FIG. 8 is a flow chart showing the procedure for confirming the relationship between the capacity of the storage battery and the inverter and the leveling effect, and FIG. 9 is the combined output power obtained by the charge / discharge simulation. the inverter capacity standard deviation sigma] x C _I and graph depicting on the coordinates of the battery capacity C _B, FIG. 10 is the maximum output variation ΔPmax of the resulting combined output power by charging and discharging simulation Converter capacitance C _I and graph depicting on the coordinates of the battery capacity C _B, FIG. 11 is a graph representing the combined output power variation of the one-year wind turbine was leveled large storage battery calculated on the basis of FIG. 4, Figure 12 is a technique for searching a flow diagram, FIG. 13 is the optimum value of the inverter capacitance C _I and battery capacity C _B in the simulation of Figure 12 illustrating a procedure for determining by simulation the optimum battery control parameters and the optimum capacity of the storage battery and the inverter FIG. 14 is a table showing parameter setting values in a simulation for obtaining an optimal solution, FIG. 15 is a table showing simulation results, and FIGS. 16 to 19 are applied with the optimal solutions of the first case to the fourth case, respectively. It is drawing which shows the variation | change_quantity of synthetic | combination output electric power when it controls by a storage battery system.

Battery equipment used in the wind power generator of the present embodiment, as shown in FIG. 2, the storage battery 12 via the inverter 13 to the wind turbine 11 is connected in parallel, the power generation output P _G and battery of the wind power generator 11 This is a system for supplying a combined output power Psys, which is the sum of 12 input / output powers Pbat, to the power system 14 connected to the power demand section.
Battery 12, when the power generation output P _G exceeds the reference value stored in receiving the battery 12, when the missing the reference value to level the output fluctuations of the wind power generator 11 by supplementing the shortage from the storage battery 12 Is.
Ability to level the power generation output P _G by battery 12 is achieved by the storage battery output power command value Pbat generated by the controller of the storage battery shown in the block diagram of FIG.

Battery controller, an average calculator 1 for calculating a past successive predetermined number of n of the moving average value Pcom for generated power P _G of the wind power generator 11, the generator power value of the wind power generator 11 from the moving average value Pcom a subtracter 2 of a deviation R subtracts the P _G, an adaptive gain controller 7 for outputting a factor proportional with a slope α to the battery remaining capacity value Wbat as the correction factor M, modifying the input from the adaptive gain controller 7 coefficients Multiplier 8 that multiplies M by the capacitance value C _I of inverter 13 and outputs a corrected power value Pc, adder 4 that adds deviation R and corrected power value Pc, and the output of adder 4 is constrained by upper and lower limits. And an output limiter 5 that outputs the output command value Pbat of the storage battery.

The storage battery output command value Pbat supplied from the output limiter 5 instructs the power output from the storage battery 12 when positive, and instructs the power input to the storage battery 12 when negative, and the upper and lower limits of the output limiter 5 A value equal to or _smaller than the capacitance value CI of the inverter 13 is used.
The storage battery output command value Pbat instructs the system 14 to store an excess amount in the storage battery 12 and replenish the shortage amount from the storage battery 12 as compared with the moving average value Pcom of the generated power of the wind power generator 11. The supplied power is leveled to the moving average value Pcom and does not show severe power fluctuations.

The adaptive gain controller 7 is intended to designate a suitable gain to maintain the battery charging rate ξ = Wbat / C _B to a predetermined value, the function of outputting the correction factor M to input xi] battery charging rate Generator. FIG. 3 is a diagram illustrating the function of the adaptive gain controller 7. The illustrated function is to maintain the storage battery charging rate ξ around 50%, and when the storage battery is discharged, the correction value M is output when the storage battery charging rate ξ exceeds 55%, and the correction value when ξ is greater than 55%. M is increased with an inclination α with respect to the increase amount of ξ. Similarly, when the battery is charged, the correction value M is output when ξ drops below 45%, and when ξ further decreases, the correction value M is decreased with a slope α with respect to the decrease amount of ξ.

Therefore, if the remaining battery capacity Wbat is far from a target value, for example, 50% of the storage battery capacity, a large correction amount Pc acts on the output command value Pbat of the storage battery.
In this way, when the remaining battery capacity Wbat increases, the discharge amount Pbat increases, and when the remaining battery capacity Wbat decreases, the charge amount Pbat tends to increase, and the remaining battery capacity Wbat is always managed to be close to the target value. .
However, when the setting of the inclination α is increased, the output power fluctuation of the storage battery 12 increases, which adversely affects the leveling of the generated power fluctuation.
Therefore, ΔM needs to be set appropriately in system design.

Further, the upper and lower limit values of the output limiter 5 are determined in relation to the capacity of the inverter 13.
The remaining capacity Wbat of the storage battery 12 can be an actual measurement value obtained from an appropriate measuring device, but may be calculated by integrating the storage battery output command value Pbat using the integrator 9. The integrator 9 is preferably associated with an upper / lower limiter corresponding to the upper / lower limit value of the storage battery capacity.

Further, a dead zone element 3 may be provided between the subtracter 2 and the adder 4 so that the output to the adder 4 becomes zero when the absolute value of the deviation R is smaller than a predetermined dead zone width Dzone.
Deadband element 3, the absolute value of the generated power P _G and the deviation R of the moving average value Pcom wind generator 11 outputs a deviation R when the dead zone width Dzone larger. Therefore, since charging / discharging of the storage battery 12 is performed only when a large power generation output fluctuation occurs, the number of times of charging / discharging can be suppressed and the life of the storage battery 12 can be extended by introducing the dead zone element 3.
However, the combined output power Psys supplied to the power system 14 are the sum of the input and output power Pbat the generator output P _G and battery 12 of the wind power generator 11, the power system variation absolute value is smaller than the dead zone width Dzone is 14 is a disturbance. This disturbance can be suppressed by reducing the dead zone width Dzone. Therefore, it is necessary to appropriately set the size of the dead zone width Dzone.

In the storage battery facility used for the wind power generator of the present embodiment, the optimal storage battery capacity C that has an appropriate leveling effect and minimizes the facility cost is obtained by simulation using wind speed data acquired in advance at the wind power generator installation site. _B , inverter capacity C _I , controller parameters n, α, Dzone can be selected.
In the simulation for determining the optimum value, the storage battery controller model of this embodiment is used to set the number n of data used for moving average calculation, the slope α in the correction coefficient M of the adaptive gain controller, and the dead zone width Dzone. Charge / discharge simulation is performed using actual wind speed data.

Based on the result of the charge / discharge simulation, assuming that the maximum power fluctuation ΔPmax and the standard deviation σx of the combined output power Psys satisfy the predetermined conditions, the storage battery in which the equipment cost Ccap = C _B C _P + C _I C _W is minimized KWh capacity C _B and inverter kW capacity C _I are obtained. Incidentally, C _P is the cost, C _W per volume kWh battery is cost capacity kW per inverter, different in the form of a storage battery and an inverter.
The charge / discharge simulation is performed by changing the controller parameters n, α, and Dzone within a set range, and the storage battery capacity C _B and the inverter capacity C _I at which the equipment cost Ccap is minimized within the set range, and at that time When the controller parameters n, α, and Dzone are obtained, these values are the optimal solutions. Therefore, if a system using the obtained values is constructed, a storage battery facility that equalizes wind power fluctuations with minimum equipment costs can be obtained. Obtainable.

Below, in this embodiment, in the above system in which the wind power generator is equipped with a storage battery that equalizes wind power generation fluctuations by charging and discharging, it is optimal that the facility cost of the storage battery is minimized based on the actual wind speed observation data obtained. An example of simulation for calculating the capacity will be described.
Simulation is carried out in the block diagram of a battery controller of Figure 1, it is equivalent to the power generation output value of the wind power generator as calculated from the measured values of wind speed power generation output P _G.

(Measurement and correction of wind speed)
For the verification test of this example, wind speed data measured at the University of the Ryukyus, Faculty of Engineering, Building No. 2 was used. The measurement was carried out for about one year from November 2005 to October 2006, and 10-minute average wind speed data was collected.
FIG. 4 is a graph showing the measured wind speed data over one year.
The observation days for the wind speed data were 357 days, and the average wind speed for one year was 3.58 m / s.

In order to calculate the generated power from the measured data of wind speed, the ground height of the wind power generator and the ground height of the observation point are different, and correction is necessary. Correction was performed using the following equation.
V _z = V _h (z / h) ^{1 / N} (1)
Here, V _z is the wind speed at the hub height of the wind power generator, V _h is the wind speed at the observation point, z is the hub height, h is the observation point height, and N is a correction coefficient.
As shown in the table of FIG. 5, the correction coefficient N is a coefficient determined based on the surface condition of the place where the wind power generator is installed. In this embodiment, N = 2 is adopted.
The ground height where the meteorological observation equipment is installed is 21.2 m, and the assumed height of the wind turbine hub is 60 m.

(Operating characteristics of wind power generator)
The generated power P _W of the wind power generator has a cube characteristic with respect to the wind speed V, and is expressed by the following equation.
P _W = ρAV ³ η / 2 (2)
Here, ρ is the air density, A is the wind receiving area, and η is the power generation efficiency.
The wind power generator used in this example has a rated output of 1 MW, the wind receiving area A is 2,980 m ² , and the power generation efficiency η is 40% in consideration of mechanical loss. The air density ρ was set to 1.225 kg / m ³ , which is an annual average value in Japanese flat land. Wind speed V uses the wind speed at the hub height.
However, the wind power generator does not output in a very low speed area of 2.5 m / s or less, and the output is saturated at a rated value in a high speed area exceeding a predetermined wind speed, for example, 12 m / s, and further, for example, 25 m / s or more. The output is cut off in the wind speed region for safety. The operating characteristics of the wind power generator are as shown in FIG.

(Fluctuation of generated power for one year)
FIG. 7 is a graph showing the fluctuation of generated power for one year calculated based on the wind speed data over the one year. The generated power fluctuation was calculated from the difference in generated power obtained from the average wind speed data for 10 minutes.
The standard deviation of the generated power fluctuation calculated from the wind speed data was 63.4 kW, and the maximum fluctuation width of the generated power was 981.2 kW.
If the generated power fluctuation follows a normal distribution, the fluctuation data of 88.53% is included in the fluctuation range of ± 100 kW.

(Leveling effect of storage battery equipment)
The average calculator 1, a target value of the leveling by calculating the moving average value Pcom generated power P _G. The moving average value Pcom is calculated using the following formula from the past generated power average value of the wind power generator.
_{Pcom = (P t + P t} -1 + P t-2 + ··· + P t- (n-1)) / n (3)
Here, Pi is an average value of generated power at time i, and n is an integer indicating the width of a window that takes a moving average.
If the width n of the moving average window is increased, the fluctuation of the moving average value Pcom is reduced and the leveling effect is increased, but the fluctuation of the storage battery charging rate is large. Conversely, when n is reduced, the fluctuation of the storage battery charging rate is small, but the leveling effect is also small.

(Storage battery capacity and inverter capacity and leveling effect)
The leveling effect can be evaluated by the maximum value of the maximum generated power fluctuation ΔPmax and the standard deviation σx of the combined output power fluctuation ΔPsys. The maximum generated power fluctuation ΔPmax is the maximum value of the difference between the maximum value and the minimum value of the combined output power Psys within the leveling period T. In the simulation, the combined output power Psys supplied to the power grid 14, the adder 6 provided on the output unit, the sum of the input and output power Pbat the generator output P _G and battery 12 of the wind power generator 11 Can be generated.
The standard deviation σx is obtained by applying the following equation to the combined output power fluctuation calculated from the difference between the combined output powers Psys.
σx ² = n / (n−1) * Σ 1 to _n (x _j −μ) ² (4)
Here, μ is an average value.

FIG. 8 is a flowchart showing a procedure for confirming the relationship between the capacity of the storage battery and the inverter and the leveling effect.
First, storage battery control parameters are set (Step 1). The storage battery control parameters evaluate the window width n when the average calculator 1 calculates the moving average value of the generated power, the slope α of the correction coefficient in the adaptive gain controller 7, the dead band width Dzone in the dead band element 3, and the fluctuation state. Leveling period T.
Then, set the capacitance C _B of the storage battery (Step2). Also, the inverter capacitance C _I is set (Step 3).

A charge / discharge simulation for one year is performed to calculate the combined output Psys, and ΔPmax and σx are calculated from the obtained Psys (Step 4).
The next inverter capacity C _I is selected (Step 5), and the process proceeds to Step 3.
After processing all of the inverter capacity C _I was scheduled for battery capacity C _B of that time, selects the next battery capacity C _B (Step6), processing proceeds to step 2.
When you process for all of the planned storage battery capacity C _B, to determine the optimal storage battery capacity C _B and the inverter capacity C _I (Step7), the process is terminated.

9 and 10 is thus obtained σx and ΔPmax a view obtained by plotting on the surface of the battery capacity C _B and inverter capacity C _I.
At this time, the storage battery control parameters were n = 40 min, α = 0.0002 pu, Dzone = 0 kW, and T = 10 min.
From the figure, it can be seen that the maximum fluctuation amount ΔPmax and the standard deviation σx of the combined output power both decrease as the storage battery capacity and the inverter capacity increase. When the inverter capacity increases, charge / discharge can be performed more faithfully according to the command value, and leveling becomes easy. Further, when the storage battery capacity increases, the power fluctuation can be absorbed even when a large fluctuation occurs, so that leveling becomes easy.
However, when the storage battery capacity exceeds 500 kWh, ΔPmax does not decrease, and further increase in capacity does not contribute to leveling, so it can be seen that there are optimum values for the capacity of the storage battery and the inverter.

(Synthetic output power fluctuation leveled by large capacity storage battery and inverter)
FIG. 11 is a graph showing a change in combined output power when the output of the wind power generator is leveled using a large capacity storage battery and a large capacity inverter without considering the equipment cost.
FIG. 11 shows a system in which a storage battery having a capacity C _B = 500 kWh is connected in parallel to a 1 MW capacity wind power generator via an inverter having a capacity C _I = 600 kW under a one-year measured wind power fluctuation shown in FIG. The situation of the combined output fluctuation ΔPsys obtained by performing the simulation for leveling the generated power is shown.
The storage battery control parameters were n = 40 min, α = 0.0002 pu, Dzone = 0 kW, and T = 10 min.
As a result of the simulation, the maximum generated power fluctuation ΔPmax = 374 kW and the standard deviation σx of the combined output power fluctuation = 21.43 kW. That is, it was confirmed that fluctuations in the generated power of the wind power generator shown in FIG. 7 were highly leveled, and the combined output produced only fluctuations of up to ± 374 kW throughout the year.

(Standard for calculating optimum capacity of storage battery equipment)
In the storage battery system of this embodiment that equalizes fluctuations in the power generated by the wind power generator, the charge / discharge results differ depending on the values of the controller parameters n, α, and Dzone of the storage battery, and the optimum values of the capacity of the storage battery and the like also differ.
Therefore, the capacity of the storage battery equipment and the inverter are optimized so that the generated power fluctuation is leveled to the required level and the equipment cost is minimized. At this time, it is necessary to use an optimum value for the controller parameter of the storage battery.

To evaluate the simulation results and obtain the optimum capacity value, the objective function and the constraint conditions are specified.
Objective function: minCcap = C _B C _P + C _I C _W (5)
Constraint conditions: ΔPd max ≧ ΔPmax, σd ≧ σx (6)
That is, the controller parameter, the storage battery capacity, and the like are such that the maximum power fluctuation ΔPmax of the combined output power Psys is not more than the fluctuation range ΔPdmax that is the management target, and the standard deviation σx of the combined output power Psys is not more than the target value σd. An object is to minimize the facility cost Ccap of the storage battery system on the premise that the condition of being there exists.

(Procedure for determining optimal capacity and controller parameters)
FIG. 12 is a flowchart showing a procedure for determining the optimum capacity and optimum storage battery control parameters of the storage battery and the inverter by simulation.
First, as permissible conditions for the generated power fluctuation, the power fluctuation width ΔPd max [kW], which is the management target of the combined output power Psys, the power fluctuation fluctuation range ± Pdev [kW], and the probability g (Pdev ) [%] And leveling period T [min] are set (Step 1). It is assumed that the combined output power fluctuation ΔPsys is normally distributed. ΔPsys is required to be included in the range of ± Pdev by at least g (Pdev).

Further, the constraint value of the evaluation index is calculated (Step 2). In calculating the capacity of a storage battery or the like, the constraint condition of the combined output power Psys is, as shown in equation (6), a fluctuation range ΔPd max as a management target of the maximum power fluctuation ΔPmax and a management target value σd of the standard deviation σx. is there.
The fluctuation range ΔPd max is given in step 1. The standard deviation management target value σd is calculated and used based on the power fluctuation probability g (Pdev) [%] and the fluctuation tolerance ± Pdev [kW].

  Next, controller parameters n, α and Dzone are set (Step 3). When these controller parameters change, the charge / discharge status of the storage battery changes, and the optimal capacity of the storage battery and the inverter also changes. Therefore, in the optimum value determination procedure of FIG. 12, the controller parameters n, α, and Dzone are sequentially changed to find the true optimum capacitance value.

After making these preparations, a charge / discharge simulation is performed (Step 4). Simulation, the sequentially selects battery capacity C _B and inverter capacity C _I in battery controller system expressed, thereby inputting the wind generated power variation data of 1 year, which is formed from a wind speed parameter for one year Figure 1 Is done.
Assumed data of the combined output power Psys supplied to the power system 14 can be acquired by simulation, and the maximum power fluctuation ΔPmax and the standard deviation σx are calculated from this data to confirm that the constraint condition of the expression (6) is satisfied. .

Furthermore, as shown in the objective function of equation (5), the storage battery capacity C _B and the inverter capacity C _I that minimize the facility cost are searched.
Optimum value search of battery capacity C _B and inverter capacity C _I, as shown in FIG. 13, takes the intersection of the grid to draw a rough grid network in a planar plotting the battery capacity C _B and inverter capacity C _I to the measuring point, Substituting the capacitance values indicated by these measurement points into the elements of the block diagram for simulation, ΔPmax and σx are obtained.

When a grid that seems to have an extreme value of the target function is detected, a finer grid is formed in the grid, and the measurement points C _B and C _I represented by the intersection of the fine grid are examined. Search for a combination of C _B and C _I that will be minPcon. When such a search method is executed in two stages, a peak solution can be efficiently detected with fewer simulations.
Note that the optimal capacity for a given controller parameter is avoided by avoiding overlooking the true optimal solution by avoiding convergence to the local solution by finely searching the top three solutions with the lowest equipment costs. Determine the solution.

  When the scheduled number of end times has not been reached, the optimum capacity of the set controller parameter is evaluated, the process returns to step 3 to set a new controller parameter, and the process of step 4 is repeated (Step 5). When the number of times of termination is reached, the optimum storage battery capacity and inverter capacity and the controller parameters at that time are determined as a result of the simulation so far (Step 6), and the arithmetic processing is terminated.

  By providing storage battery equipment that realizes the storage battery capacity value, inverter capacity value, controller parameter value, etc. obtained in this way, the storage battery system achieves leveling of the target composite output and has the lowest equipment cost. It becomes.

(Example of determining optimal capacity and optimal parameters)
For a storage battery system using a NaS battery as a storage battery attached to a wind power generator with an output of 1 MW, the fluctuation range ΔPd max [kW] of the maximum power fluctuation ΔPmax as a management target, and the allowable fluctuation range of power fluctuation ± Pdev [kW] For the four cases with different probabilities g (Pdev) [%] and leveling period T [min] included in the range, the optimal capacity value and the optimal controller parameter are optimized using simulation according to the procedure of this embodiment. The value was determined.
It is assumed that the cost per kWh of the NaS battery is 700 $ and the cost per kW of the inverter is 1500 $.

FIG. 14 is a table showing the setting values of these simulation parameters for four cases.
In case 1, ΔPd max is set to 400 kW, g (Pdev) is set to 99.95%, Pdev is set to 100 kW, and T is set to 10 minutes. In cases 2 to 4, the set values are changed one by one in comparison with case 1. . Case 2 is a case where ΔPd max is reduced by 100 kW, Case 3 is a case where Pdev is reduced by 30 kW, and Case 4 is a case where T is increased by 10 minutes.

FIG. 15 is a table showing the optimal solution obtained by the simulation. For each case, the optimal controller parameters n, α, Dzone, the standard deviation σx of the combined output power Psys, the maximum generated power fluctuation ΔPmax, and the optimal inverter capacity C _I , optimal storage battery capacity C _B , and equipment cost Ccap.

(Characteristics of Case 1)
In the capacity optimization of Case 1, when the sample period n that takes the moving average value of the power generation output is increased, the equipment cost Ccap increases. Since the fluctuation of the remaining capacity of the storage battery is large and the generated power fluctuation cannot be leveled at full discharge and full charge, ΔPmax increased. When the dead zone width Dzone <10 kW or less, even if n is decreased, the generated power fluctuation within the dead zone width appears in ΔPsys and σx increases and the constraint condition cannot be satisfied, so a solution cannot be obtained.
In the case 1, the optimum storage battery capacity is 274 kWh, the inverter optimum capacity is 580 kW, the controller parameters n, α and Dzone are 3, 0.0004 pu and 10 kW, respectively, and the equipment cost is $ 1,061. , 800.

(Characteristics of Case 2)
Case 2 is a case where the allowable width of the maximum generated power fluctuation ΔPmax is reduced from 400 kW to 300 kW. When n is 3 or less, the constraint condition that ΔPmax is 300 kW or less cannot be satisfied, and an optimal solution cannot be obtained.
In the case 2, the optimum storage battery capacity is 451 kWh, the inverter optimum capacity is 675 kW, the controller parameters n, α, and Dzone are 4, 0.0002 pu, 0 kW, and the equipment cost is $ 1,328,200. Became.
Since the output fluctuation range is to be suppressed, the inverter capacity and the storage battery capacity are large and the equipment cost is large as compared with case 1. According to the simulation result of Case 1, it is evaluated that there is no merit corresponding to a large facility cost because ΔPmax becomes 300 kW or more only several times a year.

(Characteristics of Case 3)
In Case 3, the 99.95% statistical fluctuation range Pdev of the combined output power is narrowed from 100 kW to 70 kW. In order to reduce the stochastic distribution of generated power fluctuations, sufficient storage battery capacity is required, and the equipment cost has also increased. If n is not set to 5 or more, a solution cannot be obtained. Further, unless α and Dzone are set to sufficiently small values, the equipment cost may increase and an optimal solution may not be obtained.
In case 3, the optimum storage battery capacity is 501 kWh, the inverter optimum capacity is 574 kW, the controller parameters n, α, and Dzone are 5, 0.0001 pu, 0 kW, and the equipment cost is $ 1, 211,700. Became.
Compared to Case 1, the leveling effect is large. However, in order to reduce the equipment cost, it is necessary to devise such as being located in an area where the fluctuation of generated power is small.

(Characteristics of Case 4)
In Case 4, optimization is performed under a constraint condition that equalizes fluctuations for 20 minutes. When the leveling period is set longer, the generated power fluctuation increases, so that the storage battery capacity for suppressing the fluctuation increases and the equipment cost increases.
In case 4, the optimum storage battery capacity is 720 kWh, the inverter optimum capacity is 601 kW, the controller parameters n, α, and Dzone are 3, 0.0008 pu, 0 kW, and the equipment cost is $ 1,384,500. Became.
The equipment cost was the highest among all cases. When the leveling period is lengthened, it is necessary to increase the storage battery capacity. Therefore, it is preferable to reduce the load on the storage battery by controlling the pitch angle of the windmill or cooperative control with the power system.

(Wind generator operating results when the optimum value is applied)
16 to 19 are obtained by applying the optimum capacity calculated for each case and the controller parameter at that time to the storage battery facility according to the present example provided in the wind power generator, and obtained from the annual wind speed measurement data. It is drawing which shows the generated power fluctuation leveling effect calculated | required by inputting the generated power fluctuation data. The figure shows the fluctuation state over one year of the combined output fluctuation ΔPsys calculated from the difference between the combined output Psys of the wind power generator and the storage battery facility.

In any case, a remarkable leveling effect is shown by suppressing fluctuations in the wind power generator output shown in FIG.
Case 1 has a moderate leveling effect and the equipment cost is the lowest among the cases.
In case 2, the fluctuation range of the combined output power Psys is smaller than that in case 1. However, since the equipment cost is large and a large fluctuation occurs only several times a year, it can be determined that the equipment is excessively heavy.
Case 3 has the same leveling effect as Case 2 although the equipment cost is intermediate between Case 1 and Case 2.
Furthermore, in Case 4, the output fluctuation is best suppressed, but the equipment capacity is the largest and the equipment cost is the largest.

Since the storage battery facility of the present invention gives the storage battery control device a deviation from the moving average value for a predetermined period for the generated power of the wind power generator as a set value, so that the combined output power to the power system approaches the moving average value Has the effect of leveling. When calculating the set value, the upper and lower limit values of the storage battery capacity are taken into account, and a correction value that converges the remaining capacity of the storage battery to the target level is calculated and output while correcting the set value.
Furthermore, based on the method of the present invention, using the generated power data converted into the wind power generator output using the actual wind speed data, the optimum storage battery capacity and inverter capacity with the minimum equipment cost under a predetermined condition by simulation. , And the controller parameters at that time can be searched and set in the actual machine.
Therefore, according to the present invention, the combined output to be output to the power system is sufficiently leveled, and a storage battery facility with the minimum facility cost can be obtained.

It is a block diagram of the storage battery controller of the storage battery equipment used for the wind power generator concerning one example of the present invention. It is a connection diagram of the storage battery equipment used for the wind power generator in a present Example. It is a graph which shows the characteristic of the adaptive gain controller used for the storage battery controller in a present Example. It is a graph which shows the measured wind speed data over one year. It is a table | surface which shows a response | compatibility with the auxiliary coefficient used for a present Example, and a ground surface state. It is a graph showing the operating characteristic of the wind power generator used for a present Example. It is a graph showing the electric power fluctuation for one year of the wind power generator of rated capacity 1MW calculated based on FIG. It is a flowchart showing the procedure which confirms the relationship between the capacity | capacitance of a storage battery and an inverter, and a leveling effect in a present Example. The standard deviation σx of the combined output power obtained by charging and discharging a simulation of the present embodiment is a graph depicting on the coordinates of the inverter capacity C _I and battery capacity C _B. The maximum output variation ΔPmax combined output power obtained by charging and discharging a simulation of the present embodiment is a graph depicting on the coordinates of the inverter capacitance C _I and battery capacity C _B. It is a graph showing the synthetic | combination output electric power fluctuation | variation for one year of the wind power generator equalized by the large capacity storage battery computed based on FIG. It is a flowchart showing the procedure which determines the optimal capacity | capacitance and the optimal storage battery control parameter of the storage battery and inverter of a present Example by simulation. It is a diagram illustrating a method of searching for the optimum value of the inverter capacitance C _I and battery capacity C _B in the simulation of Figure 12. It is a table | surface which shows the parameter setting value of the simulation which calculates | requires an optimal solution in a present Example. It is a table | surface which shows the simulation result of a present Example. It is drawing which shows the variation | change_quantity of synthetic | combination output electric power when it controls by the storage battery system to which the optimal solution of the 1st case in the simulation of a present Example is applied. It is drawing which shows the variation | change_quantity of synthetic | combination output electric power when it controls by the storage battery system to which the optimal solution of the 2nd case in the simulation of a present Example is applied. It is drawing which shows the variation | change_quantity of synthetic | combination output electric power when it controls by the storage battery system to which the optimal solution of the 3rd case in the simulation of a present Example is applied. It is drawing which shows the variation | change_quantity of synthetic | combination output electric power when controlling with the storage battery system to which the optimal solution of the 4th case in the simulation of a present Example is applied.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Average calculator 2 Subtractor 3 Dead zone element 4 Adder 5 Output limiter 6 Adder 7 Adaptive gain controller 8 Multiplier 9 Integrator 11 Wind generator 12 Storage battery 13 Inverter 14 Electric power system

Claims (3)

A method for producing a storage battery facility for a wind power generator including a storage battery, an inverter, and a storage battery controller, which is provided in parallel with the wind power generator in parallel with the wind power generator ,
An average computing unit that calculates a moving average value of the generated power of the wind power generator, a subtractor that subtracts the generated power value of the wind power generator from the moving average value to obtain a deviation, and a remaining capacity value of the storage battery A function generator for outputting a proportional correction coefficient, a multiplier for multiplying the correction coefficient input from the function generator by a capacity value of the inverter and outputting a corrected power value, the corrected power value and the deviation An adder to be added, and an output limiter for restricting the output of the adder with upper and lower limit values and outputting the output command value of the storage battery,
The storage battery output command value is characterized in that an excessive amount is stored in the storage battery compared to a moving average value of the generated power of the wind power generator, and a shortage is instructed to be supplemented from the storage battery.
According to a transfer function model representing the battery controller,
Input the number of data n used for moving average calculation, which is a controller parameter, the slope α and the dead band width Dzone in the correction coefficient of the function generator, and the number n of data used for the moving average calculation, the slope α and the dead band width Dzone. was selected in the set width and the input, is sequentially selects battery capacity C _B and inverter capacity C _I and subjected to a charge-discharge simulation, maximum generated power variation of the combined output power Psys? Pmax and the standard deviation σx is determined Assuming that the above-mentioned constraints are satisfied, the storage battery capacity C _B and the inverter capacity C _{I at} which the equipment cost Ccap = C _B C _P + C _I C _W is minimized are obtained, and the selected controller parameters n, α, that an optimum battery capacity C _B and inverter capacity C _I in Dzone, the controller parameter n, alpha, repetition is varied within a range set to Dzone, the set of Storage battery capacity C _B of the facility cost Ccap becomes minimum within _the optimal accumulator volume seeking inverter capacity C _I within the set range C _B, is employed as the inverter capacity C _I, the controller parameters of the time A method of manufacturing a storage battery facility for wind power generators, which is adopted to construct a storage battery facility for wind power generators.
Here, _CP is the cost per capacity of the storage battery, and C _W is the cost per capacity of the inverter. The storage battery controller further includes a dead band element between the subtracter and the adder so that the output to the adder becomes zero when the absolute value of the deviation does not reach a predetermined value. The manufacturing method of the storage battery equipment for wind power generators of Claim 1 characterized by the above-mentioned. The storage battery controller further includes an integrator for integrating an output command value, and the remaining capacity of the storage battery is calculated by integrating the storage battery output command value by the integrator. The manufacturing method of the storage battery equipment for wind generators of 2.

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