JP2011114956A - Stable-operation control device for micro grid - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an effective and appropriate control method that stably and efficiently executes frequency control of distributed power supplies. <P>SOLUTION: A control method for distributed power supplies is configured as follows. When executing power fluctuation compensation by cooperatively controlling distributed power supplies respectively having following performance to changes in power demand, time-series data of load variations to be compensated and frequency variations are statistically analyzed. Consequently, the load variations are separated into controllable components and unpredictable load variations in frequency bands so as to maximally reduce an amount of compensation by making any one of the respective distributed power supplies share the load variations. The magnitude of the load variations to be shared and compensated by each distributed power supply is set so as to control the output of each distributed power supply, thereby compensating unpredictable random load variations in the frequency bands. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a microgrid composed of a diesel generator, a gas turbine generator, a distributed power source using natural energy, and the like, and is stable by controlling the distributed power source in an integrated and autonomous manner during load fluctuations and accidents. The present invention relates to a stable operation control device for a microgrid that realizes operation.

  According to Non-Patent Document 1, a microgrid is a small-scale system with a distributed power source and a load. Multiple power sources and heat sources are collectively controlled and managed using IT-related technology, and are independent from the commercial system of an existing power company. This is an on-site power supply system that can be operated as a remote control.

  In other countries except Japan, the quality of the power network is not necessarily high. For example, in some parts of the Asian region, power outages are a daily occurrence, and in Europe and the United States, power outages in New York and Europe are new to memory, although there are debates about the relationship with electricity liberalization. Under such circumstances, there is inevitably a demand for ensuring the reliability of electrical energy supply (no power failure) and quality stability (appropriate frequency and voltage) without relying only on commercial power networks. . One of the simplest and quickest answers to this is to install a distributed power source in close proximity to the customer to create a mini-network (microgrid).

  On the other hand, in the case of a remote island, in Japan, the above request is not necessarily inevitable. Rather, there are greater demands for energy cost reduction and energy conservation including electricity against the backdrop of expanding the use of renewable energy related to global warming prevention, strengthening international competitiveness in the industrial field, and private life. Against this backdrop, inevitably renewable energy, especially natural energy such as solar and wind power, is left untouched and unstable, so it is more local than connecting directly to the power network. There is a demand to improve the independence (by making it a microgrid) by controlling to some extent collectively and to improve the compatibility with commercial power networks.

  By adopting such a distributed power source as an in-house power generation facility in buildings, it is possible to reduce global warming gas emissions, reduce contract power consumption of commercial grids (purchasing power from power companies), and reduce distribution facilities. Costs can be reduced by simplification, and there are various advantages such as being able to ensure independence stability in the event of an earthquake or fire. For example, Patent Document 1 proposes an operation method in which a distributed power source is interchanged among a plurality of consumers. Further, Patent Document 2 proposes a control method for performing load fluctuation compensation by integrally controlling a plurality of types of distributed power sources having different tracking performance with respect to load fluctuation.

JP 2002-238168 A JP 2006-246484 A

Tadahiro Goda et al. Microgrid Japan Newspaper Department 2004

  When a microgrid is configured by linking private power generation facilities composed of a large number of distributed power sources, how to ensure frequency control capability against random load fluctuations becomes a problem. Although interconnection with a commercial system is also considered as a countermeasure, it is generally based on that the base load is borne by the distributed power source and that the load exceeding the base load is handled by the commercial system. In other words, by continuously operating a distributed power source at a constant load, the amount of power generation commensurate with the base load is secured, and the load exceeding the base load is adjusted by adjusting the amount of power received from the commercial system according to the fluctuations. Overall, it meets the demand of the entire microgrid.

  In this way, it is possible to operate the distributed power source efficiently and economically by securing the base load with the distributed power source and making the received power amount of the commercial system follow the load fluctuation. Therefore, there is a high demand for an adjustment function for compensating for fluctuations in voltage and frequency due to load fluctuations, and there is a concern that the burden on commercial systems will increase if distributed power sources become widespread in the future.

  Therefore, in the future, it will be necessary to stabilize the voltage and frequency with the distributed power supply itself without relying on the commercial system to compensate for load fluctuations, and it is also necessary to operate such a distributed power supply independently. It is also important to increase the independence of distributed power sources for the grid.

  However, it is not always easy to cause each small-scale distributed power source to follow load fluctuations to a high degree. In particular, load fluctuations in the microgrid system are based on a pattern that changes slowly in units of one day, and rapid load fluctuations due to random turning on / off of equipment such as factory induction motors are superimposed. In addition, the load fluctuation range is as wide as several kW to several hundred kW, and depending on the load, as in an electric furnace, a large load fluctuation may occur in milliseconds instead of seconds. It is very difficult to make the power supply follow all such various load variation patterns.

  In addition, there is a move to adopt a distributed power source that uses natural energy such as solar power generation and wind power generation in the future, and it is inevitable that the power generation amount of such a distributed power source is influenced by the weather, time zone, etc. For this reason, it is necessary to compensate for fluctuations in the amount of power generated by other distributed power sources, and in this case, it is necessary to perform control similar to the frequency control operation.

  In view of the above circumstances, it is considered indispensable to develop a control method capable of stably and efficiently performing frequency control of a distributed power source, and the present invention aims to provide an effective and appropriate control method that enables this. Yes.

In the present invention, in a microgrid system that constructs a network that controls and operates a plurality of types of distributed power sources in an integrated manner and supplies power to a specific area, the total power generation amount, the total power demand fluctuation, and the frequency of the specific area The required frequency control capability is defined based on the time series data of the fluctuation, and the configuration of the distributed power source is determined using the CO ₂ emission amount, the output fluctuation, and the frequency control capability as evaluation criteria.

  In the present invention, in a microgrid system that constructs a network that controls and operates a plurality of types of distributed power sources in an integrated manner and supplies power to a specific area, time series data of total power fluctuation and frequency fluctuation in the specific area Is measured online, its frequency control capability is estimated, and the required frequency control capability of the distributed power source is determined.

  In the present invention, in a microgrid system that constructs a network that controls and operates a plurality of types of distributed power sources in an integrated manner and supplies power to a specific area, generator dropout, load dropout, and rapid load fluctuation occurred. In this case, the generator output command value is rapidly changed based on the data on the total power generation amount and the total power demand fluctuation amount in the specific area.

  In the present invention, in a stable operation control apparatus for a microgrid that supplies power to a specific area by constructing a network that controls and operates a plurality of types of distributed power sources in an integrated manner, a plurality of types of distributed power sources are connected to a plurality of types. Including a first means for evaluating with the evaluation index and a second means for determining the start / stop order of the distributed power supply in time units according to the total score of the evaluation index, The output fluctuation standard deviation expressing the degree of the output fluctuation with the standard deviation and the governor-free capacity representing the ability to contribute to the power fluctuation in a short cycle are included.

  Further, the evaluation index of the first means includes the output fluctuation standard deviation of the distributed power source using natural energy and the evaluation index of the governor-free capacity, and these indexes are evaluation indexes of the distributed power source not using natural energy. A lower value is better.

  The evaluation index of the first means includes an index of carbon dioxide emission, and the evaluation index of carbon dioxide emission of a distributed power source that uses natural energy is more than the evaluation index of a distributed power source that does not use natural energy. It is good to be a high value.

  In the present invention, in a stable operation control device for a microgrid that supplies power to a specific area by constructing a network that controls and operates multiple types of distributed power sources in an integrated manner, the total power in the microgrid is input. Then, determine the mid- to long-term fluctuation, set the third means to give a power generation output command to the distributed power source in operation, and set the governor-free capacity required according to the frequency fluctuation in the microgrid, And a fourth means for giving a governor-free command to the mold power source.

  In the present invention, in a stable operation control apparatus for a microgrid that supplies power to a specific area by constructing a network that controls and operates a plurality of types of distributed power sources in an integrated manner, a plurality of types of distributed power sources are connected to a plurality of types. The first means for evaluating with the evaluation index, the second means for determining the start / stop order of the distributed power supply in time units according to the total score of the evaluation index, and the total electric energy in the microgrid are input. The third means to determine the mid- to long-term fluctuations and give the power generation output command to the distributed power source in operation, and the necessary governor-free capacity is set according to the frequency fluctuation in the microgrid. And a fourth means for giving a governor-free command to the power supply.

  The plurality of evaluation indexes of the first means include an output fluctuation standard deviation in which the degree of output fluctuation is expressed by a standard deviation, and a governor-free capacity that represents the ability to contribute to power fluctuation in a short cycle. It is good.

  According to the present invention, since only a plurality of distributed power sources can share a specific frequency band only for unpredictable load fluctuations in a band with a short fluctuation cycle, it can compensate effectively and stably. It is not necessary to request the frequency control capability and the power storage function. In addition, it does not require a high level of ancillary function in the commercial system as usual, so it can be connected to a distributed power source without imposing a heavy burden on the commercial system, and uses natural energy such as sunlight and wind power. The variation in the power generation amount of the distributed power source can be compensated in the same manner, and the independence and reliability of the distributed power source can be sufficiently increased.

It is a conceptual diagram of the microgrid stable operation control apparatus applied to 1st-3rd embodiment of this invention. It is a simplified electrical equivalent circuit diagram for demonstrating the fundamental principle of the frequency stabilization applied to the 1st-2nd embodiment of this invention. It is an equivalent transfer function for demonstrating the fundamental principle of the frequency stabilization applied to the 1st-2nd embodiment of this invention. It is a block diagram of the microgrid stable operation control apparatus applied to 1st Embodiment of this invention. It is a flowchart which shows the required governor free capacity | capacitance calculation process applied to 1st Embodiment of this invention. It is a flowchart which shows the generator operation schedule setting process of the day applied to 1st Embodiment of this invention. It is a figure showing the algorithm of the optimal driving | operation generator selection applied to 1st Embodiment of this invention. It is a figure showing the driving | running pattern applied to 1st Embodiment of this invention. It is a figure showing the total power demand applied to the 1st-2nd embodiment of this invention, a total power demand moving average value, and the extracted short cycle load fluctuation | variation. It is a block diagram of the microgrid stable operation control apparatus applied to 2nd Embodiment of this invention. It is a flowchart which shows the setting process of the generator output command value applied to 2nd Embodiment of this invention. It is a flowchart which shows the setting process of the governor free generator applied to 2nd Embodiment of this invention. It is a block diagram of the microgrid stable operation control apparatus applied to 3rd Embodiment of this invention.

  The best mode for carrying out the present invention will be described below with reference to the drawings.

  FIG. 1 shows the overall configuration of a microgrid stable operation control apparatus 1 according to the present invention.

  The stable operation control device 1 shall give a start / stop command and an output change command value for the generator in the microgrid system 2B. Each of the plurality of generators 8 in the microgrid system 2B is connected to the microgrid bus 5 via the circuit breaker 7, the generator bus 15 and the generator transformer 6. The microgrid bus 5 may be a loop configuration, a mesh configuration, a radial configuration, or the like, but in FIG. The microgrid bus 5 may be connected to the electric power system 2 </ b> A via the interconnection transformer 4, the circuit breaker 7, and the interconnection transmission line 3. The load 9 is connected to the generator bus 15 via the circuit breaker 7 and the power line 19.

  In general, the microgrid system 2B includes a plurality of power supplies 8, a generator transformer 6, a load 9, and the like. Furthermore, the power storage device 10, the AC / DC converter 13, the wind power generation facility 11, the solar power generation facility 12, and the like may be installed. In addition, the state about the power supply and load in each generator 8 and load 9 is given to the microgrid stable operation control apparatus 1 via the constant detection terminal high-speed transmission apparatus 14. In a normal large-scale power system, the total generated power and the total load can be taken into a macro and reflected in the control of the power system, but the microgrid stable operation control device 1 may have a small scale, It is characterized in that the state of the power supply and the load in each generator 8 and each load 9 is captured.

  FIG. 2 is a diagram showing a simplified system for explaining the operation principle of the microgrid stable operation control apparatus applied to the best mode for carrying out the present invention. In FIG. 2, if the output of the generator 8 and the size of the load 9 are equal, the power demand and supply are balanced, and the frequency is maintained at the rated value. However, when the load 9 fluctuates and becomes unbalanced with the generator output, the frequency fluctuates.

  The frequency increases when the output of the generator 8 becomes excessive compared to the magnitude of the load. If the generator output is insufficient compared to the load size, the frequency will drop. At this time, it is the function of the governor 18 that detects supply / demand imbalance from the frequency of the generator, controls the gas, steam flow rate, fuel flow rate, etc. from the fuel tank 17 and gives them to the prime mover 16.

  The equation of motion of the power system brought about by the supply and demand of power in FIG. 2 can be expressed by equation (1). When the frequency fluctuation phenomenon is targeted, the term relating to the phase angle fluctuation of the system generator can be ignored and the generator inertia should be taken into consideration.

Where M: generator inertia constant D (f): load frequency characteristic function Δf: frequency deviation μ (f): governor frequency characteristic function ΔP: deviation formula between power generation amount and load amount (2) Where s is a Laplace operator.

  Here, D (s) and μ (s) are expressed by equations (3) and (4), respectively.

Here, K _L: Load Frequency characteristic constant T _L: Load Frequency characteristic time constant K _G: generator frequency characteristic constant T _G: transfer function in equivalent frequency control electric circuit model of the generator frequency characteristic time constant Figure 2 FIG. 3 shows the model. In FIG. 3, reference numeral 70 denotes a frequency characteristic model of the load 9 expressed by equation (3), 71 is an inertia model of the generator 8, and 72 is a frequency characteristic model of the generator 8 expressed by equation (4).

This model is very simple. In the state of the mechanical torque initial value Tmo of the prime mover 16 given to the generator 8 and the load torque initial value T _L o, the electric output difference ΔP is the inertia M of the generator 8. Originally integrated and appears as a generator angular velocity Δω, and this result is given to the frequency characteristic model 72 of the generator 8 and the frequency characteristic model 70 of the load 9 expressed by a first-order lag circuit. It means that feedback is made as an electrical output with respect to 16 mechanical torque initial value Tmo and load torque initial value T _L o. Therefore, in this circuit, if the machine input Tmo and the electrical output coincide with each other, the frequency is stabilized stably.

  By the way, the load has the characteristic that the power consumption increases as the frequency increases, and the power consumption decreases as the frequency decreases. This characteristic is called the frequency characteristic of the load. The way of changing the power consumption varies considerably depending on the load. For example, the synchronous motor load is properly affected by the frequency change, but the induction motor load has a cushion of slipping and is less affected by the frequency change. Electric lights and electric loads are hardly affected by frequency changes. Furthermore, AC / DC converters installed in combination with solar power generation and wind power generation can be handled as loads. Therefore, the total characteristic is determined depending on what ratio the load exists.

  The change in the generated power with respect to the change in frequency includes the inertia of the generator, the synchronization force generated by the phase difference between the generators, and the output change due to the governor operation. Of these, only the output change due to the governor operation should be considered in the steady state.

  By the way, randomly generated load fluctuations are expressed by mathematical expressions, and the statistical frequency fluctuation Δfi (s) in the steady state is approximately as follows. When the random load fluctuation ΔPi (s) is considered as the sum of many stepwise fluctuations of the load, the Laplace transform of the frequency fluctuation corresponding to the step change of the i-th load ΔPi is expressed by equation (5).

  The frequency Δf i in the steady state can be expressed by equation (6) by the final value theorem.

Here, if the standard deviation of the frequency fluctuation is σ _Δf based on sufficiently large N pieces of frequency observation data, Equation (7) is obtained.

Further, when the standard deviation of load fluctuation is σ _ΔP , (8) is obtained from the equation (6).

Therefore, the relationship of the formula (9) is established between the standard deviation σ _{Δf of the} frequency fluctuation and the standard deviation σ _ΔP of the load fluctuation.

  FIG. 4 is a block diagram showing functions of the microgrid stable operation control apparatus 1 according to the first embodiment of the present invention. In FIG. 4, the microgrid stable operation control device 1 is configured by, for example, a digital computer, and functionally includes a governor-free capacity calculation unit 1A and a generator operation schedule setting unit 1B.

  Among these, the governor-free capacity calculating unit 1A performs statistical analysis by inputting time-series data of the total power demand 20 variation per day based on past experience in advance. That is, based on the output of the moving average processing unit 26A, the short cycle variation extraction unit 27 extracts an unpredictable load variation component. Using this load fluctuation component as an input, the standard deviation calculator 28 takes out the load fluctuation component for one minute and calculates the standard deviation. The governor-free capacity calculation unit 29 assumes a load characteristic constant in consideration of the season, day of the week, and day / night time zone, and calculates the required governor-free capacity for each generator based on the load fluctuation standard deviation.

  In the generator operation schedule setting unit 1B, the total power demand 20 per day based on the past experience described above is input, and the generator operation schedule is determined by calculation based on various evaluation indexes. Based on the output of the long-period fluctuation extraction unit 30 with the output of the moving average unit 26B as an input, the total output of the generator is determined by the generator total output determination unit 31, for example, in units of one hour.

In the operating generator calculation unit 32A, the generator rated output 21, the fuel unit price 22, the CO ₂ emission amount 23, the output fluctuation standard deviation 24, and the governor-free capacity 25 are used as evaluation indexes for each generator constituting the microgrid. The optimal combination of operating generators is determined by calculation based on these evaluation indexes. In the operation schedule preparation part 32B, the starting / stopping time of a generator is set, and a command is output to each generator.

  Next, details of the required governor-free capacity calculating unit 1A in the circuit of FIG. 4 will be described with reference to the flowchart of FIG. First, in step S101 in FIG. 5, a one-year microgrid total power demand database is constructed on the digital computer. The data in this database is, for example, a value in a 1 second cycle. FIG. 9 shows only a few minutes of a day in the total power demand database of the microgrid for one year. Here, 20 is the total power demand, and it fluctuates in a fairly short time interval. Recognize.

  In step S102, a moving average of power demand data per second is obtained with about 60 samples, and random fluctuation components are removed. The total power demand moving average value 210 in FIG. 9 is obtained in this way. It can be seen that the total power demand moving average value 210 fluctuates slowly.

  Subsequently, in step S103, the moving average data 210 in units of one minute is subtracted from the demand fluctuation data 20 per second. As a result, only the short-cycle fluctuation component 220 that is difficult to predict is extracted from the demand fluctuation, but it can be seen that the amplitude is significantly smaller than the fluctuation amplitude of the original demand fluctuation data 20.

  FIG. 9 shows an example of temporal change in the total power demand. By subtracting the 1-minute moving average value 210 from the total power demand power 20, only the short-cycle load fluctuation component 220 is extracted, and the fluctuation amplitude is about 1/4 in absolute value compared to the original data. I understand that.

  In step S104, the load fluctuation standard deviation for one minute is calculated using the short period component 220 of the power demand data.

Step S105 In seasonally as described above, the day, taking into account the day or night time zone assumes the load characteristic constant K _L, based on the load fluctuation standard deviation in step S104, necessary governor-free volume with (9) K _G · σ _Δf0 is calculated. Here, KG is a generator frequency characteristic constant, and σ _Δf0 is a target standard deviation of allowable frequency fluctuation.

  Next, regarding the details of the generator operation schedule setting unit 1B in the circuit of FIG. 4, the flowchart of FIG. 6, the diagram representing the optimum operation generator selection algorithm of FIG. 7, and the diagram of the operation pattern of FIG. Will be described with reference to FIG.

  In the generator operation schedule setting unit 1B, as shown in the flowchart of FIG. 6, first, in step S201, the power demand on the current day is assumed based on the one-year power demand database. The annual power demand database used at this time is the same database used in the required governor-free capacity calculation unit 1A.

  Next, in step S202, the power demand data for 1 second is converted into moving average data for about 1 hour with 3600 samples. Further, the power demand data subjected to the moving average in step S203 is converted into stepwise total power generation amount data, for example, in units of one hour. Here, FIG. 8 is a diagram showing the daily power demand in units of one hour, with the horizontal axis representing time and the vertical axis representing total demand. In this figure, 230 is the “moving average data for about 1 hour obtained from the power demand data for 1 second by the number of samples 3600” obtained in step S202, and it can be seen that there is a smooth fluctuation in the time order. . Further, in this figure, stepwise total power generation amount data obtained in step S203, for example, in units of one hour is shown as 240.

In step S204, a combination of operating generators is determined based on the evaluation indices (generator rated output, fuel unit price, CO ₂ emission, output fluctuation standard deviation, governor-free capacity). FIG. 7 shows a specific method for selecting an operating generator using an evaluation index.

In FIG. 7, the horizontal axis represents operating generators G1 to G7 existing in the microgrid, and the vertical axis represents generator rated output, fuel unit price, CO ₂ emission amount, output fluctuation standard deviation, Each governor-free capacity is listed. Among these evaluation indexes, the generator rated output, the fuel unit price, and the CO ₂ emission amount are well known. Therefore, the explanation is omitted, and the output fluctuation standard deviation and the governor free capacity will be explained.

  First, in the case of power generation using nature as a partner, such as wind power or solar power generation, it is inherently not good at finely controlling the power generation output. For this reason, the concept of output fluctuation standard deviation is introduced, and fluctuations in power output that are difficult to control are not stabilized in frequency, but behave like load fluctuations, and the degree of fluctuation is expressed in standard deviation. . Since the change is difficult to control, the evaluation point is expressed by a negative score.

  The governor-free capacity contributes to power fluctuations in a short cycle, and the greater the control width, the more stable the microgrid frequency is. Therefore, the evaluation point is expressed by a positive score.

Incidentally, among the operating generators of FIG. 7, the power generation plants G1, G5, G6, and G7 that use fossil fuels have a high fuel unit price (thus, the index is a negative value) and a large amount of CO ₂ emissions (thus, Although the index is a negative value), there is no difficulty in controlling fluctuations in power output (output fluctuation standard deviation is zero), and the governor-free capacity is large. In addition, power plants G3 and G4 that deal with nature such as wind power and solar power generation have low fuel unit prices (thus, the index is zero) and CO ₂ emissions are small (thus, the index is zero). Fluctuation control is difficult (output fluctuation standard deviation is negative) and governor-free capacity is also small.

  Based on the evaluation results obtained by quantifying the effect on frequency control and the degree of adverse effects of each generator using the evaluation indexes of these items, the overall evaluation score is finally calculated. However, the governor-free capacity has a restriction that is more than the sum of the load fluctuation standard deviation and the generator output fluctuation standard deviation. This score gives priority to generator operation. Incidentally, in the example of FIG. 7, the higher the total evaluation score, the more suitable for long-term operation, and the lower the score, the better to avoid the use as much as possible.

  Finally, in step S205, for example, an hourly generator start / stop schedule is created. For example, FIG. 8 shows an operation schedule from the generator G1 to the generator G7 for 24 hours on the horizontal time axis. According to FIG. 8, in order to ensure the necessary amount of power generation in accordance with the increase in power demand, the generators are sequentially introduced into the microgrid, and the order of introduction is the order with the highest overall evaluation score. It is also effective in terms of suppressing frequency fluctuations economically.

  According to the operation results of FIG. 8, the power supply configuration is mainly composed of the generators G1 and G2 having a large output fluctuation standard deviation (no difficulty in controlling fluctuations in power supply output) and having a governor-free capacity at night when the total power demand is small. However, during the daytime when the total demand is large, the natural power generators G3 and G4 are additionally activated, and the daily power operation is performed.

  As described above, in the first embodiment using FIG. 4 to FIG. 9, the time series data of the total power demand 20 fluctuations per day based on the past experience is input, and finally the power generation in the hour unit. A signal 53 for instructing start and stop of the machine is given to each generator. In other words, it is a control function that can be said to be a microgrid version of ELD (Economic Load Distribution Function) of a central power supply command station in power system control. However, what is essentially different from the ELD (economic load distribution function) of the central power supply command center in power system control is to introduce the concepts of output fluctuation standard deviation and governor-free capacity to track the generators in the microgrid. The point is to stop.

  FIG. 10 is a block diagram showing functions of the microgrid stable operation control apparatus 1 according to the second embodiment of the present invention. In FIG. 10, the microgrid stable operation control device 1 is configured by, for example, a digital computer, and functionally includes a generator output command setting unit 1C and a governor-free generator setting unit 1D.

  The generator output command setting unit 1 </ b> C inputs the current time series data of the total power demand fluctuation and performs statistical analysis. That is, the total power demand actual measurement data 90 is input to the moving average processing unit 26A, and based on the output of the moving average processing unit 26A, a load fluctuation component that can be predicted by the middle cycle fluctuation extracting unit 35 is extracted. The load fluctuation component extracted by the middle cycle fluctuation extraction unit 35 is used as a correction for the generator output command 58 by the generator output command value determination unit 36.

  The governor-free generator setting unit 1D performs the moving average process 26A based on the actual power demand 90 actual measurement data, and the short period variation extraction unit 27 takes the difference between the original data and the moving average data, which is difficult to predict. Extract the load fluctuation.

This output is processed by the standard deviation calculator 37. Further, the measured value 33 of the frequency fluctuation is processed by the standard deviation calculation unit 39. The outputs of the standard deviation calculation units 37 and 39 are input to the system frequency characteristic constant estimation unit 38, and the system frequency characteristic constant (K _L + K _G ) is calculated based on the equation (9). The standard deviation of the frequency fluctuation 33 and the standard deviation of the target frequency fluctuation 34 are confirmed by the frequency confirmation unit 39, and when the standard deviation of the frequency fluctuation 33 is large, the required generator frequency characteristic constant calculation unit 40 formula (9) Based on the above, a system frequency characteristic constant (K _L + K _GO ) is calculated.

The required governor-free capacity calculating unit 41A calculates the required governor-free capacity K _G0 · σ _Δf0 from the changed generator frequency characteristic constant K _G0 , and then the generator governor-free amount determining unit 41B gives a governor-free command 54. Here _{sigma? F0} is the standard deviation, K _L is the load frequency characteristic constant, K _G is the generator frequency characteristic constant before change, K _G0 is the generator frequency characteristic constant after the change of the target frequency variation.

  As in the processing flow shown in FIG. 11, first, in step S301, the total power demand data of the microgrid is stored online on the digital computer. In step S302, moving average of power demand data per second is performed with about 60 samples to remove random fluctuation components. Subsequently, in step S303, the moving average data in units of one minute is subtracted from the demand fluctuation data every second. As a result, only predictable mid-cycle fluctuation components are extracted from fluctuations in power demand. Next, in step S304, the generator output command value correction is calculated. The correction amount of the generator output command is calculated by subtracting the total sum of the current generator output command values from the medium-long cycle fluctuation component extracted in step S303. Finally, in step S305, the generator output command value correction is distributed to each operating generator.

  As shown in FIG. 12, the governor-free generator setting unit 1D first collects online data of frequency fluctuations and total power demand in the microgrid in step S401. Next, in step S402, the frequency and power demand data at intervals of 1 second are set as moving average data of about 1 minute with about 60 samples. Further, in step S403, the short-period fluctuation component is extracted by subtracting the moving average of the power demand data from the frequency and the power demand data at intervals of one second.

In step S404, the frequency deviation and the standard deviation of the short cycle fluctuation component of the load are calculated, and the system frequency characteristic constant (K _L + K _G ) is estimated. In step S405, it is confirmed whether the observed standard deviation of the frequency fluctuation is within the target standard deviation σ _Δf0 . If the frequency exceeds the target value, a necessary system frequency characteristic constant (K _L + K _GO ) for suppressing the frequency to the target frequency is calculated in step S406. In step S407, the necessary governor free capacity σ _Δf0 · K _G0 is calculated based on the necessary system frequency characteristic constant. Finally, in step S408, a change command for the generator governor-free operation command is transmitted to the target generator.
As described above, in the second embodiment using FIGS. 10 to 12, real-time time-series data is input, and finally the governor-free capacity is calculated. In other words, this function is a control function that can be said to be a microgrid version of the AFC (automatic frequency control function) of the central power supply command station in the power system control, and further, the governor-free function. However, the essential difference from the AFC of the central power supply command center in power system control is that the concept of governor-free capacity is introduced to control the generator in the microgrid.

  FIG. 13: is a block diagram which shows the function of the micro grid stable operation control apparatus 1 which concerns on the 3rd Embodiment of this invention. In FIG. 13, the microgrid stable operation control apparatus 1 is configured by, for example, a digital computer, and functionally includes a necessary control amount calculation unit 45 and a control target selection unit 49.

  The necessary control amount calculation unit 45 inputs the generator output and the total power demand online via the detection terminal high-speed transmission device 14, and first determines whether or not the unbalance amount is within an allowable value to the unbalance determination unit 43. Judgment. When the unbalance value exceeds the allowable value, the required control amount calculation unit 44 calculates the control amount.

  In the control target selection unit 50, first, the control amount determination unit 46 switches the control method depending on the magnitude of the control amount. When the power generation amount is excessive but the control amount is small, the generator output change target selection unit 47 selects a control target generator and gives a generator output change command 55. When the control amount is large, the generator emergency start / stop target selection unit 48 selects a control target generator and issues a generator start / stop command 56. When the load is excessive, a load to be controlled is selected by the load limit selection unit 49 and an additional limit command 57 is given.

  The microgrid is expected to increase in the future, but in that case, the function of managing and controlling the entire grid from the viewpoint of power and frequency is essential.

DESCRIPTION OF SYMBOLS 1 Micro grid operation control apparatus 1A Necessary governor free capacity calculation part 1B Generator operation schedule setting part 1C Generator output command setting part 1D Governor free generator setting part 2A Electric power system 2B Micro grid 3 Transmission line 4 for interconnection Transformer 5 Microgrid bus 6 Generator transformer 7 Circuit breaker 8 Generator 9 Load 10 Power storage device 11 Wind power generation facility 12 Solar power generation facility 13 AC / DC converter 14 Detection terminal high-speed transmission device 15 Generator bus 16 Motor 17 Fuel tank 18 Speed governor 19 Power line 20 Total power demand 21 Generator rated output 22 Fuel unit price 23 CO ₂ emissions 24 Output fluctuation standard deviation 25 Governor-free capacity 26A Moving average (1 minute) Processing unit 26B Moving average (60 Min) Processing unit 27 Short cycle variation extraction unit 28 Load variation standard deviation calculation unit 29 Necessary governor-free Capacity calculation unit 30 Long period fluctuation calculation part 31 Generator total output determination part 32A Operation generator selection calculation part 32B Generator operation schedule setting calculation part 33 Frequency fluctuation 34 Target frequency fluctuation 35 Medium to long period fluctuation extraction part 36 Generator Output command value determination unit 37 Standard deviation calculation 38 System frequency characteristic constant estimation unit 39 Frequency fluctuation confirmation unit 40 Necessary system frequency characteristic constant unit 41A Necessary governor free capacity calculation unit 41B Generator governor free amount distribution unit 43 Supply / demand imbalance determination unit 44 Necessary control amount calculation unit 45 Necessary control amount calculation unit 46 Necessary control amount determination unit 47 Generator output command distribution unit 48 Generator emergency start / stop command distribution unit 49 Generator output command distribution unit 54 Governor-free command 55 Generator output change Command 56 Generator start / stop command 57 Load limit command 58 Generator output command 70 Load frequency characteristics mode Total generation of the moving average 240 stepped le 71 generator inertia model 72 generator frequency characteristic model 90 moving average 220 short-period fluctuation component 230 hour total power demand measured data 210 for one minute

Claims (9)

In a microgrid system that supplies power to a specific area by constructing a network that controls and operates multiple types of distributed power sources in an integrated manner,
The required frequency control capability is defined based on the time series data of the total power generation amount, total power demand variation and frequency variation in the specific area, and the configuration of the distributed power source using the CO ₂ emission amount, output variation and frequency control capability as evaluation criteria A microgrid stable operation control device characterized by determining In a microgrid system that supplies power to a specific area by constructing a network that controls and operates multiple types of distributed power sources in an integrated manner,
Microgrid stable operation characterized in that time series data of total power fluctuation and frequency fluctuation in the specific area is measured online, its system frequency control capability is estimated, and the necessary frequency control capability of the distributed power source is determined Control device. In a microgrid system that supplies power to a specific area by constructing a network that controls and operates multiple types of distributed power sources in an integrated manner,
When the generator dropout, load dropout, and rapid load fluctuation occur, the generator output command value is rapidly changed based on the data of the total power generation amount and the total power demand fluctuation amount in the specific area. Grid stable operation control device. In a stable operation control device for a microgrid that constructs a network that controls and operates multiple types of distributed power sources and supplies power to a specific area,
A first means for evaluating the plurality of types of distributed power supplies with a plurality of evaluation indices; a second means for determining a start-stop sequence of the distributed power supplies in time units according to the total score of the evaluation indices; Among the plurality of evaluation indicators, the output fluctuation standard deviation expressing the degree of output fluctuation as a standard deviation and a governor-free capacity representing the ability to contribute to power fluctuation in a short cycle are included. A microgrid stable operation control device. In the stable operation control device for a microgrid according to item 4,
The evaluation index of the first means includes an output fluctuation standard deviation of a distributed power source that uses natural energy and an evaluation index of a governor-free capacity. These indexes are based on an evaluation index of a distributed power source that does not use natural energy. A stable operation control device for a microgrid characterized by a low value. In the stable operation control device for the microgrid according to item 4 or 5,
The evaluation index of the first means includes an index of carbon dioxide emission, and the evaluation index of carbon dioxide emission of a distributed power source that uses natural energy is more than the evaluation index of a distributed power source that does not use natural energy. A stable operation control device for a microgrid characterized by a high value. In a stable operation control device for a microgrid that constructs a network that controls and operates multiple types of distributed power sources and supplies power to a specific area,
Enter the total power in the microgrid, find its mid- to long-term fluctuation, and provide a power generation output command to the distributed power supply in operation, and the governor-free necessary according to the frequency fluctuation in the microgrid And a fourth means for setting a capacity and giving a governor-free command to an operating distributed power source. In a stable operation control device for a microgrid that constructs a network that controls and operates multiple types of distributed power sources and supplies power to a specific area,
A first means for evaluating the plurality of types of distributed power supplies with a plurality of evaluation indices; a second means for determining a start-stop sequence of the distributed power supplies in time units according to the total score of the evaluation indices; The third means for inputting the total electric energy in the microgrid to obtain the mid- and long-term fluctuation, and giving a power generation output command to the distributed power source in operation, and the governor required according to the frequency fluctuation in the microgrid A stable operation control device for a microgrid, comprising: a fourth means for setting a free capacity and giving a governor-free command to an operating distributed power source. In the stable operation control device of the microgrid according to item 8,
The plurality of evaluation indexes of the first means include an output fluctuation standard deviation expressing the degree of output fluctuation as a standard deviation, and a governor-free capacity representing an ability to contribute to a power fluctuation in a short cycle. A stable operation control device for a microgrid.

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