JP4864803B2 - Electric power supply and demand control apparatus and method - Google Patents

Electric power supply and demand control apparatus and method Download PDF

Info

Publication number
JP4864803B2
JP4864803B2 JP2007113031A JP2007113031A JP4864803B2 JP 4864803 B2 JP4864803 B2 JP 4864803B2 JP 2007113031 A JP2007113031 A JP 2007113031A JP 2007113031 A JP2007113031 A JP 2007113031A JP 4864803 B2 JP4864803 B2 JP 4864803B2
Authority
JP
Japan
Prior art keywords
power
power generation
generation output
value
load distribution
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
JP2007113031A
Other languages
Japanese (ja)
Other versions
JP2008271723A (en
Inventor
崎 保 幸 宮
中 真 理 田
羽 廣 次 鳥
Original Assignee
株式会社東芝
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社東芝 filed Critical 株式会社東芝
Priority to JP2007113031A priority Critical patent/JP4864803B2/en
Publication of JP2008271723A publication Critical patent/JP2008271723A/en
Application granted granted Critical
Publication of JP4864803B2 publication Critical patent/JP4864803B2/en
Application status is Active legal-status Critical
Anticipated expiration legal-status Critical

Links

Images

Description

  The present invention relates to an apparatus and method for performing power supply and demand control of a small-scale power system, and more particularly to an apparatus and method for performing power supply and demand control of a small-scale power system including a plurality of types of distributed power sources.

  Multiple types of distributed power sources such as engine generators, turbine generators, power storage devices, fuel cells, solar power generation and wind power generation, etc. There is a small-scale electric power system called a microgrid or the like that supplies electric power to consumers in a specific area.

  When connecting a small-scale power system to a commercial power system of an electric power company, it may be a forward flow that receives power from the commercial power system or a reverse flow that supplies power to the commercial power system. Even in this case, it is necessary to control power supply and demand of distributed power sources in a small-scale system that keeps the deviation between the power flow at a certain point on the power system or the load power and power generation output in the small-scale power system constant. is there.

  To realize power supply and demand control with multiple distributed power sources, predict the load power, calculate the total power output of the distributed power source with a constant deviation between the predicted load power and the power generation output, and calculate the total power output. Allocate power generation output targets for each distributed power source.

  For example, in Patent Document 1, in power supply from a power generation facility group composed of a plurality of power generation facilities to a customer group including one or more consumers, the total predicted power reception amount of the entire consumer group matches the power generation facility group. The planned power generation amount of each power generation facility is optimized so that the predetermined evaluation value is optimized while satisfying the constraint condition, with the total adjustment margin for the total planned power generation amount being equal to or greater than the predetermined set total adjustment margin. A power generation planning method for planning is disclosed.

  If a small-scale system includes a natural energy generator whose power generation output is affected by the natural environment such as solar radiation and wind conditions, the predicted value of the output of the natural energy generator and the predicted value of the load power are considered. Then, the total power output of the distributed power source other than the natural energy power generation device is calculated.

  For example, Patent Document 2 discloses a method for realizing power generation amount prediction from meteorological information that collects weather information about sunshine and wind power and predicts power generation amount for each region by solar power generation and wind power generation on the previous day and in real time. Has been.

  There are a plurality of distributions of power generation output as individual power generation outputs of the distributed power source that realize the total power generation output of the distributed power source. In distributed power sources such as engine generators and turbine generators, the higher the power generation output, the higher the energy efficiency and the higher the economic efficiency. Evaluate the economics of fuel costs, etc. by allocation, determine each power generation output of each distributed power source that is more economical, and give each power generation output to each distributed power source as a power generation output command value for power supply and demand control Realized.

  The part that generates the power generation output command value in consideration of the economic efficiency is called economic load distribution, ELD (Economical Loading Dispatching, hereinafter referred to as ELD) or the like. There has been disclosed an ELD device that distributes economic load while eliminating poor tracking of generator output due to speed constraints.

In this way, power supply and demand control of the distributed power source is performed in order to keep constant the power flow at an arbitrary place on the power system or the deviation between the load power in the small-scale power system and the power generation output. The power generation output command value of the distributed power source calculates the total power generation output of the distributed power source in the target system based on the prediction of the load and the power generation output of the natural energy power generation device, and realizes the total power generation output with high economic efficiency. Each power generation output command value of each distributed power source is determined by a flow of calculating by ELD.
JP 2004-48852 A JP 2004-289918 A JP-A-6-14464

  In order to improve the control performance of small-scale power supply and demand control in a specific area, the accuracy of each predicted value of load power and the output of natural energy power generation equipment is improved, and the response characteristics and power reserve of each distributed power source are taken into account. ELD is required.

  However, improvement of the prediction accuracy of the load amount and the power generation output of the natural energy power generation device requires a large amount of cost, such as increasing the measurement points and measurement amount of information used for the prediction processing, and each region and each natural energy power generation device. However, it is difficult to realize such as having to adopt a different prediction method.

  Also, if the prediction accuracy of the power generation output of the load or the natural energy power generation device is not sufficient, the power generation output command of each distributed power source by ELD and the actual power generation output of each distributed power source that has received the power generation output command will be different. If the power generation output does not become highly economical, or if the power generation output of each distributed power source is not enough to compensate for fluctuations in the power generation output of the load or the natural energy power generation device, the power generation reserve that is necessary to compensate the power generation output. When ELD is performed while securing the power generation reserve, there may be a case where the economy is lowered, and there is a problem that the control performance of the power supply / demand control is lowered.

  The present invention has been made in view of the above points, and an object of the present invention is to provide a control device and method for smoothly and efficiently controlling power supply and demand in a small-scale power system including a distributed power source.

In order to achieve the above object, in the present invention,
In the power supply and demand control device that adjusts the power generation output of a plurality of distributed power sources connected in the power system to make the deviation between the total power output of the power generation device connected in the power system and the load power constant,
Prediction means for outputting the power generation output of the power generator connected in the power system or the predicted value of the load power and the reliability of the predicted value;
Total generation output calculation means for obtaining a total generation output of the plurality of distributed power sources using the predicted value and a power flow target value at an arbitrary location of the power system;
Load distribution switching means for selecting a load distribution calculation method for calculating the load distribution of the plurality of distributed power sources according to the reliability of the predicted value;
Load distribution means for generating each power generation output target value of the plurality of distributed power sources from the total power generation output of the distributed power source by the load distribution calculation method selected by the load distribution switching means;
A power supply and demand control device, comprising:
And a power supply and demand control method for adjusting the power generation output of a plurality of distributed power sources connected in the power system to make the deviation between the total power generation output of the power generation device connected in the power system and the load power constant,
Output the power generation output of the power generator connected in the power system or the predicted value of the load power and the reliability of the predicted value,
Using the predicted value and the power flow target value at any location of the power system, find the total power output of the plurality of distributed power sources,
Select a load distribution calculation method for calculating the load distribution of the plurality of distributed power sources according to the reliability of the predicted value,
A power supply and demand control method for generating each power generation output target value of the plurality of distributed power sources from the total power generation output of the distributed power source by the selected load distribution calculation method;
I will provide a.

  As described above, the present invention obtains the predicted value of the power generation output and load power of the power generator connected to the power system including the distributed power source and the reliability of the predicted value, and uses the predicted value and the power flow target value. Obtain the power transmission output, select the load distribution calculation method according to the reliability of the predicted value, determine the total power output of the distributed power source by the selected load distribution calculation method, and distribute the load according to the reliability of the predicted value Since the calculation method is selected and the power distribution output target value of the distributed power source is determined by this load distribution calculation method, the power supply and demand control of the small-scale power system including the distributed power source can be performed smoothly and efficiently. .

  Embodiments of the present invention will be described below with reference to the accompanying drawings.

  FIG. 1 is a block diagram showing the configuration of the first embodiment of the present invention. Here, in a target power system that performs power supply and demand control by the power supply and demand control device or power supply and demand control method according to the present invention, a device that cannot variably control the power generation output, for example, a natural energy power generation device such as a solar power generation device or a wind power generation device Are installed as a natural energy power generation device A and a natural energy power generation device B.

  Further, the target system and the external power system are connected at one connection point, and the power generation output in the target system is set so that the active power amount within the set time passing through the connection point becomes the target power amount. The first embodiment will be described on the assumption that power supply and demand control is performed by n distributed power sources that can be variably controlled. The sign of the active power at the interconnection point is positive when the target system receives active power from an external power system.

(Constitution)
In the first embodiment shown in FIG. 1, the power supply / demand control apparatus 1 performs power supply / demand control of the distributed power sources 2 a and 2 n that can variably control the n power generation outputs installed in the target power system. Examples of the distributed power sources 2a and 2n include an engine generator, a turbine generator, a power storage device, and a fuel cell.

  One power supply / demand control apparatus 1 is installed for one target power system that performs power supply / demand control, and the power supply / demand control apparatus 1 may be installed outside the target power system. It may be a location where each input / output signal can be transmitted.

  The signal names inside the power supply / demand control apparatus 1 will be described using the suffix k and the suffix t. It is assumed that the subscript k signal always has a longer sampling time than the subscript t signal. In the case of the same subscript k or the same subscript t, the sampling times are the same. There are roughly two sampling times, the sampling time of the subscript k signal is assumed to be in the range of several seconds to several minutes, and the sampling time of the signal of subscript t is assumed to be in the range of several milliseconds to several seconds.

  The generation output prediction means 11A of the natural energy power generation apparatus A inputs the past α generation output GA_Pk-1, GA_Pk-2,... GA_Pk-α at the sampling time of the subscript k-1 of the natural energy power generation apparatus A, The expected value GA_Pk and variance GA_σk of the power generation output of the natural energy power generation apparatus A at the point in time k are output.

  The power generation output prediction means 11B of the natural energy power generation apparatus B inputs the past β power generation outputs GB_Pk-1, GB_Pk-2,... GB_Pk-β at the sampling time of the subscript k-1 of the natural energy power generation apparatus B, and 1 The expected value GB_Pk and variance GB_σk of the power generation output of the natural energy power generation apparatus B at the point in time k are output.

  The load amount predicting means 12 collects the total load power in the target power system at the sampling time represented by subscript k−1, and the past γ load powers L_Pk−1, L_Pk−2,... L_Pk−γ. Is input, and the expected value L_Pk and variance L_σk of the total load power at the time point k one period ahead are output.

  The expected values GA_Pk, GB_Pk, and L_Pk at the time point k one period ahead output by the power generation output prediction means 11A and 11B and the load amount prediction means 12 are input to the total power generation calculator 13. In the total power generation calculator 13, the expected values GA_Pk, GB_Pk, and L_Pk, and the power flow target value at the time point k passing through the interconnection point between the target system and the external system set and stored in the power supply and demand control apparatus 1 Pf k is input, and G_all k obtained by subtracting GA_Pk, GB_Pk, and Pf k from L_Pk is output.

  G_all k is a target value of the total generated power at the time point k of the n distributed power sources 2a, ..., 2n in the target system. The output G_all k of the total power generation calculator 13 is input to the load distribution means 14.

  The variances GA_σk, GB_σk, and L_σk at the time point k one period ahead output from the power generation output prediction means 11A, 11B and the load amount prediction means 12 are input to the load distribution method switching means 15. The output of the load distribution method switching unit 15 is input to the load distribution unit 14.

  The load distribution unit 14 receives the output G_all k of the total power generation calculator 13 and the output of the load distribution method switching unit 15. The load distribution means 14 selects one load distribution method corresponding to the output of the load distribution method switching means 15, and in accordance with the selected load distribution method, G_all k is changed to k of n distributed power sources 2a,. The power generation output targets G1_ref k,..., Gn_ref k at the time are distributed and output.

  In the subtracter 16, the passing power flow Pf t− at the connection point between the target system and the external system measured from the power flow target value Pf k at the time k to the time t−1 and input to the power supply / demand control apparatus 1. Pf k−Pf t−1 obtained by subtracting 1 is sent to the power generation output correcting means 17.

  In the power generation output correcting means 17, the target correction amounts G1_cmpt,..., Gn_cmpt for the power generation output targets G1_ref k,..., Gn_ref k at the k time points of the distributed power sources 2a to 2n from the input Pf k-Pf t-1. Is calculated.

  In the adders 18a to 18n, the respective power generation output targets G1_ref k,..., Gn_ref k of the distributed power sources 2a to 2n and the target correction amounts G1_cmpt, ..., Gn_cmpt are added, and the distributed power sources 2a at the time t are added. , Gn_ref t is calculated as G1_ref t = G1_ref k + G1_cmpt,. , G1_ref t,..., Gn_ref t are continuously output at a constant value.

(Function)
The power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 will be described. The power generation output prediction means 11A and 11B and the load amount prediction means 12 are different in input signal and output signal, but the structure of the prediction model which is the internal structure is the same.

  The variables that are predicted by the power generation output prediction means 11A, 11B and the load amount prediction means 12 are the power generation output of the natural energy power generation apparatus A in the power generation output prediction means 11A, and the power generation output of the natural energy power generation apparatus B in the power generation output prediction means 11B. It is an output, and is the total load power in the target power system in the load amount prediction means 12.

  Both the power generation output prediction means 11A and 11B and the load amount prediction means 12 are provided with a prediction model that estimates the expected value and variance at the time point k, which is one period ahead of the variable, by linear combination of past variables. An AR-GAARCH model is known as such a prediction model, and the power generation output prediction means 11A and 11B and the load amount prediction means 12 both adopt the AR-GAARCH model.

  Note that other prediction models can be applied in the same manner as described above as long as the prediction model quantitatively outputs the reliability of the expected value such as the expected value of the variable and the variance of the variable. The AR-GAARCH model is a combination of the AR model and the GARCH model.

In the autoregressive (AR) model, the variable X k at the time point k is expressed by the following equation (1).
X k = a 0 + a 1 · X k-1 + a 2 · X k-2 + ... + a m · X k-m + ε k (1)
Here, m is the AR order, a k is the AR coefficient, and ε k is the residual.

In the GARCH (1,1) model, if the AR model residual is ε k = σ k · dZ k (dZ k : for example, an increment of the standard Brownian motion), the variance σ k 2 at the time point k is expressed by the following equation (2 ).
σ k 2 = r · σ 2 + p · ε k −1 2 + q · σ k −1 2 (2)
Here, p, q, and r are non-negative constants, p + q + r = 1, and σ 2 is the average variance.

As described above, in the AR-GAARCH model, when the past m variables X k−1 , X k−2 ,..., X k−m are input, the above equation (1) and (2) Expected value X k and variance σ k 2 are output.

The constants m and a 0 , a 1, ..., A m, p, q, r, σ 2 in the above formulas (1) and (2) are used for, for example, the power generation output prediction unit 11A of the natural energy power generation apparatus A as long as, by using time-series data of power output of the previous day or the like to the sampling time k by 1 day measured natural energy power generation device a, the constants a known method m and a 0, a 1, ..., a m, p, q, r, and σ 2 can be determined. The same applies to the power generation output prediction means 11B and the load amount prediction means 12 of the natural energy power generation apparatus B.

These constants m and a 0 , a 1, ..., A m, p, q, r, σ 2 are converted into the above formulas (1) and (2) in the power generation output prediction means 11A of the natural energy power generation apparatus A, For example, it may be updated and set every day. In the present invention, the update period of each constant is not limited. The points of the past variable time series data respectively input to the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 are the constant m determined above. In general, the power generation output prediction means 11A and 11B and the load amount prediction means 12 have different values for the constant m.

  Thus, in the power generation output prediction means 11A of the natural energy power generation apparatus A, the expected value of the power generation output of the natural energy power generation apparatus A at the time point k using the time series data of the past power generation output of the natural energy power generation apparatus A. And output the variance.

  The power generation output prediction unit 11B of the natural energy power generation apparatus B outputs the expected value and variance of the power generation output of the natural energy power generation apparatus B at the time point k using the time series data of the past power generation output of the natural energy power generation apparatus B. To do.

  The load amount predicting means 12 outputs the expected value and variance of the total load power in the target system at the time point k using time series data of the total load power value at each past time point in the target system.

  Each expected value is a predicted value at time point k, and each variance can be regarded as a reliability of the predicted value at time point k. When the variance value is large, the expectation value varies widely, so the reliability of the expectation value is low. When the variance value is small, the reliability of the expectation value is high.

  Next, the load distribution method switching means 15 will be described. The load distribution method switching means 15 includes the variances GA_σk, GB_σk at the time points k output by the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12, respectively. L_σk is input. In the load distribution method switching means 15, the same number of values as the number of input signals are set.

  In the description of the first embodiment, since the number of input signals is three, GA_σk, GB_σk, and L_σk, three values are set. This value will be described as A, B, and C. The values A, B, and C act as thresholds for GA_σk, GB_σk, and L_σk, and when even one threshold is exceeded, the load distribution method switching means 15 outputs 1.

  That is, when GA_σk is larger than A, when GB_σk is larger than B, or when L_σk is larger than C, the output of the load distribution method switching means 15 becomes 1. On the other hand, when GA_σk, GB_σk and L_σk do not exceed the thresholds A, B and C, 0 is output.

  Therefore, the load distribution method switching unit 15 is configured such that each variance at the time point k output by the power generation output prediction unit 11A of the natural energy power generation apparatus A, the power generation output prediction unit 11B of the natural energy power generation apparatus B, and the load amount prediction unit 12 is When the value exceeds a threshold value A, B or C, or when the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 output. When the reliability of the expected value of k is low, the load distribution method switching means 15 outputs 1. On the contrary, when the reliability of the expected value at the time point k is high, the load distribution method switching means 15 outputs 0.

  Next, the load distribution unit 14 will be described. The load distribution means 14 generates power at the time point k of the n distributed power sources 2a,..., 2n in the target system output from the 1 or 0 signal output from the load distribution method switching means 15 and the total power generation calculator 13. Given the target value G_all k of the total power, the respective power generation output targets G1_ref k,..., Gn_ref k at the time k of the distributed power sources 2a to 2n are output. The load distribution means 14 has two load distribution methods. The first is the economic load allocation method, and the second is the reserve allocation method.

First, the “economic load distribution method” will be described. In the economic load distribution method, when the target value G_all k of the total generated power at the time point k is distributed to the power generation output of the n distributed power sources, each distributed type that makes the fuel cost of the n distributed power sources the lowest The power generation output targets G1_ref k,..., Gn_ref k of the power source are obtained. When the fuel cost function fi (Gp) (i is 1 to n) is set for the power generation output Gp of each distributed power source, the following equations (3) and (4), that is, G1_ref k + ... + Gn_ref k = G_all k ( 3)
G1pmin ≤ G1_ref ≤ G1pmax
...
Gnpmin ≦ Gn_ref ≦ Gnpmax (4)
However, Gipmin is the minimum power output of the i-th (i is 1 to n) distributed power source,
Gipmax is the maximum power generation output of the i-th (i is 1 to n) distributed power source.
It can be expressed as

Under the constraints of the above formulas (3) and (4), the total fuel cost, that is, the relational expression F1 shown by the following formula (5),
F1 = f 1 (G1_ref k) +... + F n (Gn_ref k) (5)
G1_ref k,..., Gn_ref k that minimizes.

  This optimal solution can be obtained by a known Lagrange's undetermined multiplier method, and the obtained power generation output targets of the n distributed power sources are G1_ref k,..., Gn_ref k.

  Next, the “reserve capacity allocation method” will be described. In the reserve capacity allocation method, when the target value G_allk of the total generated power at the time point k is realized by the power generation outputs of n distributed power sources, as shown in FIG. Target G1_ref k,..., Gn_ref k is set to a value close to the intermediate value between the output minimum value Gipmin (i is 1 to n) and the output maximum value Gipmax (i is 1 to n) of each distributed power source. In the range between the minimum output value Gipmin (i is 1 to n) and the maximum output value Gipmax (i is 1 to n) of the type power supply, a large generation reserve capacity that can increase or decrease each power generation output is secured.

Expressed by a mathematical formula, the constraint condition is a function F2 represented by the following formula (6) under the above formulas (3) and (4), that is,
G1_ref k,..., Gn_ref k that minimizes.

  The function F2 is an intermediate value between the output maximum value Gipmax (i is 1 to n) and the output minimum value Gipmin (i is 1 to n) of each of the n distributed power sources, and each power generation output target Gi_ref (i = 1). To n). This optimum solution can be obtained by the known Lagrange's undetermined multiplier method, and the obtained power generation output targets of the respective distributed power sources are G1_ref k,..., Gn_ref k.

  From the above description, it can be seen that the power generation output targets G1_ref k,..., Gn_ref k of each distributed power source can be obtained as the output of the load distribution means 14 even in the economic load distribution method or the reserve capacity securing distribution method.

  When the output of the load distribution method switching means 15 is 0, the load distribution means 14 calculates and outputs the power generation output targets G1_ref k,..., Gn_ref k of each of the n distributed power sources by the economic load distribution method. .

  On the other hand, when the output of the load distribution method switching means 15 is 1, the power generation output targets G1_ref k,..., Gn_ref k of n distributed power sources are calculated and output by the reserve capacity allocation method. That is, when the reliability of the expected value at the time point k output by the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 is low, the load distribution The method switching means 15 outputs 1. At this time, the load distribution means 14 calculates and outputs the power generation output targets G1_ref k,..., Gn_refk for each of the n distributed power sources by the reserve capacity allocation method.

  When the reliability of the expected value at the time point k output by the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 is high, the load distribution method is switched. The means 15 outputs 0. At this time, the load distribution means 14 calculates and outputs the power generation output targets G1_ref k,..., Gn_refk of each of the n distributed power sources by the economic load distribution method.

  Next, the power generation output correction means 17 will be described. From the power flow target value Pf k at the time point k, the passing power flow Pf t-1 at the connection point between the target system and the external system measured at the time point t-1 and input to the power supply / demand control apparatus 1 is subtracted. Pf k−Pf t−1 is input, and target correction amounts G1_cmpt,..., Gn_cmpt for the power generation output targets G1_ref k,..., Gn_refk of n distributed power sources are output. The inside of the power generation output correction means 17 performs simultaneous and same amount control.

In other words, if the same amount of power [Wh] for 30 minutes coincides with the target amount of power for 30 minutes, the following equation (7)
, Gn_cmpt are output so that the value becomes zero.

  In the case of the same amount at the same time for 30 minutes, the state quantity of the integration in the above equation (7) is reset to zero every 30 minutes. The target correction amount G1_cmp t is obtained by allocating a value obtained by multiplying the value set in the equation (7) at the current time t by the gain to be set so that the equation (7) becomes zero and further dividing by the capacity ratio of the n distributed power sources. , ..., Gn_cmpt is generated.

  Further, the internal processing of the power generation output correcting means 17 may be simultaneous and same amount control, and it is sufficient that the input signal and the output signal can be applied even by a method other than the above.

  The calculated target correction amounts G1_cmpt,..., Gn_cmpt are added to the respective power generation output targets G1_ref k,..., Gn_ref k by the adders 18a to 18n, and are output to the distributed power sources 2a, 2n.

  In each of the distributed power sources 2a and 2n, a power generation output control circuit provided in each of the distributed power sources 2a and 2n so that the power generation output of each power generation output command Gi_ref k + Gi_cmpt (i is 1 to n) is obtained. Thus, each power generation output is controlled.

  In the description of the first embodiment, two natural energy power generation apparatuses have been described. However, it is obvious that the number of natural energy power generation apparatuses can be easily expanded from the case of two or two.

  In addition, when the generation output prediction and the load power prediction of a part of the natural energy power generation apparatus are not performed, for example, the values obtained by performing the moving average process on each measurement data for a specific time are used as the generation output prediction units 11A and 11B of the first embodiment. This can be handled by substituting the expected value output of the load amount prediction means 12 and omitting the distributed output.

  In addition, when there is a distributed power source that operates at a constant power generation output in the target power system, the power supply / demand control by the output of the power supply / demand control device 1 may not be performed. It can be easily analogized that the total output calculator 13 needs to consider the power generation output value of the distributed power source with constant power generation output operation.

(effect)
As described above, in the present invention, based on the expected value that is the predicted value of the load power in the target power system to be controlled for power supply and demand and the power generation output of the natural energy power generation device, and the variance that represents the reliability of the expected value, When the reliability of the predicted value is high, each power generation output target of each distributed power source with high economic efficiency that minimizes the fuel cost by economic load distribution is calculated. On the other hand, when the reliability of the predicted value is low, it is distributed Each power generation output target of each distributed power source that secures the power generation reserve capacity of the distributed power source and increases the range in which the power generation output of each distributed power source can be increased or decreased is calculated.

  Therefore, when the system scale is small or the amount of introduction of natural energy power generation equipment is large, the power fluctuation is large and the power supply and demand balance control is difficult. However, it is possible to operate a distributed power source with high economic efficiency and high power supply / demand control performance without degrading the power supply / demand control performance and with high prediction accuracy.

(Constitution)
The configuration of the second embodiment is the same as the configuration of the power supply and demand control apparatus 1 shown in FIG. 1, and the internal processing of the load distribution method switching function 15 is different.

(Function)
The load distribution method switching means 15 includes the variances GA_σk, GB_σk at the time points k output by the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12, respectively. L_σk is given. In the load distribution method switching means 15, the same number of values as the number of signals input inside and one operation time limit value are set.

In the description of the second embodiment, since the number of input signals is three, GA_σk, GB_σk, and L_σk, it is assumed that three values are set. In the following description, the value is A, B, or C, and the operation time limit value is X. The values A, B, and C act as threshold values for GA_σk, GB_σk, and L_σk, and values S1, S2, and S3 that exceed the threshold values are calculated as in the following equation (8).
When GA_σk> A, S1 = GA_σk−A
When GA_σk ≦ A, S1 = 0
In the case of GB_σk> B, S2 = GB_σk−B (8)
When GA_σk ≦ B, S2 = 0
When L_σk> C, S3 = L_σk−C
When L_σk ≦ C, S3 = 0

Next, S1s, S2s, and S3s obtained by multiplying each value of S1, S2, and S3 by the sampling time of the subscript k are calculated by the following equation (9).
S1s = S1 × sampling time of subscript k + S1s
S2s = S2 × sampling time of subscript k + S2s (9)
S3s = S3 × sampling time of subscript k + S3s
The initial values of S1s, S2s, and S3s are zero.

  When any one of S1s, S2s or S3s in the above equation (9) becomes larger than X, the load distribution method switching means 15 outputs 1. At the same time, S1s, S2s and S3s are reset to zero. When all of S1s, S2s and S3s are smaller than X, the load distribution method switching means 15 outputs 0.

  Accordingly, the load distribution method switching means 15 is configured such that the variance of the time point k output by the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 is the threshold A, When B or C is exceeded and the time integral value exceeds the operation time limit value, the power generation output prediction means 11A of the natural energy power generation apparatus A, the power generation output prediction means 11B of the natural energy power generation apparatus B, and the load amount prediction means 12 are output. When the reliability of the expected value at the time point k continues for a certain period of time, the load distribution method switching means 15 outputs 1, and conversely, when the reliability of the expected value at the time point k is high, the load distribution method The switching means 15 outputs 0.

(effect)
When the expected value variance to be predicted exceeds the operation time limit for a certain period of time, the load distribution method switching means is switched to 0 or 1 output, so the switching frequency is reduced, and the economic load distribution method used by the load distribution means 14 or Switching frequency of the reserve capacity allocation method is reduced. For this reason, changes in the power generation output targets G1_refk and Gn_refk of the respective distributed power sources 2a and 2n are reduced, and there is an effect that the power generation output of each distributed power source is stabilized.

(Constitution)
The third embodiment is the same as the configuration of the power supply and demand control apparatus 1 shown in FIG. 1, and the processing inside the load distribution means 14 is different.

(Function)
In the third embodiment, among the processes inside the load distribution means 14, only the portion in which the processing of the reserve capacity securing distribution method described in the first embodiment is different and the processing is different will be described.

In the third embodiment, the function F2 described in the expression (6) in the description of the first embodiment is different. In the third embodiment, the function F2 will be described as F3 represented by Expression (10). The above equations (3) and (4) of the constraint conditions and the solution of the optimal solution are the same as those in the first embodiment.

  The function F3 is obtained by multiplying the distance between the intermediate value of the maximum output Gnpmax and the minimum output Gnpmin of each of the n distributed power sources and the power generation output target value Gn_ref by a positive weight constant Wi (i is 1 to n). is there. The positive weight constant Wi is stored and stored in the load distribution unit 14 in advance.

  Example 3 will be described with reference to FIG. For example, assume that n = 3 and load distribution of three distributed power sources is a specific example. It is assumed that the maximum output Gipmax (i is 1 to 3) and the minimum output Gipmin (i is 1 to 3) of the three distributed power sources have the same value.

  Under this condition, when the function F2 of the first embodiment is used, the power generation in which the target value G_all k of the total power generation is equally distributed among the three units so as to satisfy the constraint condition (3) as shown in FIG. It becomes an output and does not necessarily increase the power reserve capacity.

  In such a case, when the function F3 is used, the power generation output target value can be made closer to the intermediate value between the maximum output Gipmax and the minimum output Gipmin as the distributed power source having a larger weight constant is used. The reserve power generation can be made larger than the case.

(effect)
Thus, in the reserve capacity securing method according to the embodiment, the power generation output target value of a specific distributed power source that is weighted can be brought close to an intermediate value between the maximum output value and the minimum output value of the distributed power source, It is possible to secure a large power reserve for the distributed power source.

The block diagram of an electric power supply-and-demand control apparatus. Explanatory drawing of the reserve capacity securing distribution method in the load distribution means in Example 1 of this invention. Explanatory drawing of the reserve capacity securing distribution method in the load distribution means in Example 3 of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Electric power supply / demand control apparatus, 2a, 2n ... Distributed power supply,
11A ... Power generation output predicting means of the natural energy power generation apparatus A,
11B ... Generation output prediction means of the natural energy power generation device B, 12 ... Load amount prediction means,
13 ... Power generation total output calculator, 14 ... Load distribution means, 15 ... Load distribution method switching means,
16 ... subtractor, 17 ... power generation output correcting means, 18a to 18n ... adder.

Claims (9)

  1. In the power supply and demand control device that adjusts the power generation output of a plurality of distributed power sources connected in the power system to make the deviation between the total power output of the power generation device connected in the power system and the load power constant,
    Prediction means for outputting the power generation output of the power generator connected in the power system or the predicted value of the load power and the reliability of the predicted value;
    Total generation output calculation means for obtaining a total generation output of the plurality of distributed power sources using the predicted value and a power flow target value at an arbitrary location of the power system;
    Load distribution switching means for selecting a load distribution calculation method for calculating the load distribution of the plurality of distributed power sources according to the reliability of the predicted value;
    Load distribution means for generating each power generation output target value of the plurality of distributed power sources from the total power generation output of the distributed power source by the load distribution calculation method selected by the load distribution switching means;
    A power supply and demand control device comprising:
  2. In the electric power supply and demand control device according to claim 1,
    The power supply / demand control apparatus according to claim 1, wherein the prediction means uses an AR-GAARCH model as a prediction model and a variance of variables for predicting reliability of the prediction value.
  3. In the electric power supply and demand control device according to claim 1,
    The load distribution switching unit selects a power reserve reserve distribution method when the variance of the predicted variable exceeds a set threshold value, and the economic load when the predicted variable variance is equal to or less than the threshold value. A power supply and demand control device, characterized by selecting a distribution method.
  4. In the electric power supply and demand control device according to claim 3,
    The load distribution switching means calculates a sum of squares of deviations between an intermediate value between each maximum power generation output and each minimum power generation output of the plurality of distributed power sources and each power generation output target value of the plurality of distributed power sources. An electric power supply and demand control device using a load allocation method for ensuring power reserve capacity to be minimized.
  5. In the electric power supply and demand control device according to claim 3,
    The load distribution switching means sets a square value of each deviation between each intermediate value between each maximum power generation output and each minimum power generation output of the plurality of distributed power sources and each power generation output target value of the plurality of distributed power sources. A power supply and demand control apparatus using a power reserve reserve load distribution method that minimizes a value obtained by multiplying and adding weight constants for each of the plurality of distributed power sources.
  6. In the electric power supply and demand control device according to claim 1,
    The load distribution switching means selects a power reserve reserve distribution method when the time integral value when the variance of the predicted variable exceeds a set threshold value exceeds a time threshold value, and the time integral value is the time limit value. An electric power supply and demand control apparatus, wherein an economic load distribution method is selected when a threshold value is not exceeded.
  7. In the electric power supply and demand control device according to claim 6,
    The load distribution switching means calculates a sum of squares of deviations between an intermediate value between each maximum power generation output and each minimum power generation output of the plurality of distributed power sources and each power generation output target value of the plurality of distributed power sources. An electric power supply and demand control device using a load allocation method for ensuring power reserve capacity to be minimized.
  8. In the electric power supply and demand control device according to claim 6,
    The load distribution switching means sets a square value of each deviation between each intermediate value between each maximum power generation output and each minimum power generation output of the plurality of distributed power sources and each power generation output target value of the plurality of distributed power sources. A power supply and demand control apparatus using a power reserve reserve load distribution method that minimizes a value obtained by multiplying and adding weight constants for each of the plurality of distributed power sources.
  9. In the power supply and demand control method of adjusting the power generation output of a plurality of distributed power sources connected in the power system to make the deviation between the total power output of the power generation device connected in the power system and the load power constant,
    Output the power generation output of the power generator connected in the power system or the predicted value of the load power and the reliability of the predicted value,
    Using the predicted value and the power flow target value at any location of the power system, find the total power output of the plurality of distributed power sources,
    Select a load distribution calculation method for calculating the load distribution of the plurality of distributed power sources according to the reliability of the predicted value,
    A power supply and demand control method, comprising: generating each power generation output target value of the plurality of distributed power sources from the total power generation output of the distributed power source by the selected load distribution calculation method.
JP2007113031A 2007-04-23 2007-04-23 Electric power supply and demand control apparatus and method Active JP4864803B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2007113031A JP4864803B2 (en) 2007-04-23 2007-04-23 Electric power supply and demand control apparatus and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2007113031A JP4864803B2 (en) 2007-04-23 2007-04-23 Electric power supply and demand control apparatus and method

Publications (2)

Publication Number Publication Date
JP2008271723A JP2008271723A (en) 2008-11-06
JP4864803B2 true JP4864803B2 (en) 2012-02-01

Family

ID=40050518

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2007113031A Active JP4864803B2 (en) 2007-04-23 2007-04-23 Electric power supply and demand control apparatus and method

Country Status (1)

Country Link
JP (1) JP4864803B2 (en)

Families Citing this family (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009284723A (en) 2008-05-26 2009-12-03 Toshiba Corp Power supply/demand controller and method of controlling power supply/demand
JP2012517207A (en) * 2009-02-03 2012-07-26 ドン・エナジー・パワー・エ/エス Distributed power production system and control method thereof
JP5380119B2 (en) * 2009-03-16 2014-01-08 株式会社東芝 Power supply capacity estimation apparatus for small-scale power system, power supply capacity estimation method and power capacity estimation program
JP4770954B2 (en) * 2009-03-16 2011-09-14 Tdk株式会社 Multiple power supply integration device, multiple power supply integration system, and multiple power supply integration program
JP5618511B2 (en) 2009-09-08 2014-11-05 株式会社東芝 Integrated monitoring and control system for smart grid and micro grid
US8744638B2 (en) * 2009-09-11 2014-06-03 General Electric Company Method and system for demand response in a distribution network
JP5404556B2 (en) * 2010-08-09 2014-02-05 三菱電機株式会社 Air conditioner control device and refrigeration device control device
JP5101675B2 (en) 2010-09-09 2012-12-19 株式会社東芝 Supply-demand balance control device
JP5699705B2 (en) * 2011-03-14 2015-04-15 オムロン株式会社 Electric device, its control method, and control program
US9742189B2 (en) * 2011-06-17 2017-08-22 Hitachi, Ltd. Microgrid control system
JP5661053B2 (en) * 2012-02-02 2015-01-28 三菱電機株式会社 Electric power supply and demand control device and electric power supply and demand control method
WO2013121750A1 (en) * 2012-02-14 2013-08-22 日本電気株式会社 Load power management system and method for managing load power
JP5833749B2 (en) * 2012-05-17 2015-12-16 パナソニック株式会社 Power control apparatus, power control method, and program
JP6166894B2 (en) * 2012-12-27 2017-07-19 川崎重工業株式会社 Optimal control apparatus and method for complex energy system
CN103532172B (en) * 2013-10-23 2015-06-24 华北电力大学 Multistage reserve coordination method based on set dynamic classification
KR101540956B1 (en) 2013-11-26 2015-08-04 한국전기연구원 Method and apparatus for controlling output of renewable energy generation complex
CN103683284B (en) * 2013-12-26 2016-08-17 国家电网公司 A kind of power distribution network three-phase unbalanced load flow computational methods containing distributed power source
JP6255251B2 (en) * 2014-01-22 2017-12-27 株式会社日立製作所 Output estimation method and apparatus for photovoltaic power generation apparatus and power system monitoring apparatus using the same
KR101741128B1 (en) * 2015-08-19 2017-05-30 주식회사 그랜드 System for controlling peak and supplying emergency power using distributed photovoltaic power

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4187907B2 (en) * 2000-06-15 2008-11-26 東芝エンジニアリングサービス株式会社 Electric power supply and demand control system
JP4296140B2 (en) * 2004-08-31 2009-07-15 株式会社東芝 Plant optimum operation support system and method, program

Also Published As

Publication number Publication date
JP2008271723A (en) 2008-11-06

Similar Documents

Publication Publication Date Title
Jiang et al. Energy management of microgrid in grid-connected and stand-alone modes
JP4852885B2 (en) Load following operation control method with multiple types of distributed power supply
US8332077B2 (en) Controller and control method for a wind farm including a plurality of wind turbine generators
JP4445361B2 (en) Power system control method and power system control apparatus using secondary battery
Galus et al. Investigating PHEV wind balancing capabilities using heuristics and model predictive control
US9489701B2 (en) Adaptive energy management system
US9343926B2 (en) Power controller
JP3980541B2 (en) Distributed energy community control system, central controller, distributed controller, and control method thereof
JP5095495B2 (en) Electric power system and control method thereof
Roozbehani et al. On the stability of wholesale electricity markets under real-time pricing
US9507367B2 (en) Method and system for dynamic stochastic optimal electric power flow control
JP3792428B2 (en) Power system control apparatus and power system control method
Papavasiliou et al. Supplying renewable energy to deferrable loads: Algorithms and economic analysis
US8571720B2 (en) Supply-demand balance controller
JP4245583B2 (en) Control device, control method, program, and recording medium of distributed energy system
EP2293406B1 (en) Energy storage systems
US9026259B2 (en) Power generation optimization in microgrid including renewable power source
Khatamianfar et al. Improving wind farm dispatch in the Australian electricity market with battery energy storage using model predictive control
Khatib et al. A review on sizing methodologies of photovoltaic array and storage battery in a standalone photovoltaic system
Ghosh et al. Distribution voltage regulation through active power curtailment with PV inverters and solar generation forecasts
US8554383B2 (en) Power supply and demand control apparatus and power supply and demand control method
WO2006013600A2 (en) Distributed system for electrically supplying a power bus and method of controlling power supply using such system
KR101119460B1 (en) Power accumulator and hybrid distributed power supply system
CN104969437B (en) System and method for energy distribution
Tuohy et al. Rolling unit commitment for systems with significant installed wind capacity

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20100218

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20110915

TRDD Decision of grant or rejection written
A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20111018

A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20111109

R151 Written notification of patent or utility model registration

Ref document number: 4864803

Country of ref document: JP

Free format text: JAPANESE INTERMEDIATE CODE: R151

FPAY Renewal fee payment (event date is renewal date of database)

Free format text: PAYMENT UNTIL: 20141118

Year of fee payment: 3

FPAY Renewal fee payment (event date is renewal date of database)

Free format text: PAYMENT UNTIL: 20141118

Year of fee payment: 3