KR102290038B1 - Apparatus for managing of energy and method thereof - Google Patents

Abstract

To an energy management apparatus and method, wherein the energy management apparatus connects individual energies, and outputs at least one random value for the output of renewable energy using the maximum and minimum generation amount, and the random value. and a post-processing unit configured to obtain at least one result data corresponding to the random value based on the random value.

Description

APPARATUS FOR MANAGING OF ENERGY AND METHOD THEREOF

The present invention relates to an energy management device and method.

Renewable energy (renewable energy, which may be referred to as renewable energy) refers to energy (eg, electrical energy) produced by using renewable resources (hereinafter, renewable resources) instead of non-renewable resources such as fossil fuels. Renewable energy is produced using, for example, solar power, wind power, hydro power, tidal power, wave power or geothermal power. Recently, renewable energy has been in the spotlight for various reasons such as the occurrence of environmental pollution caused by fossil fuel-based energy production or the depletion of fossil fuels.

However, in producing energy based on renewable resources, it is impossible to accurately predict energy production due to difficulties in controlling renewable resources, and thus unexpected cases or situations may occur. In particular, in recent years, as the grid connection of renewable energy sources (for example, places or facilities that generate energy based on renewable energy such as solar power plants or wind power plants) has increased rapidly, blackouts occur all over the world due to the lack of flexibility in the power system. are doing For example, the UK power outage in August 2019 was caused by unstable power supply and demand due to an increase in the proportion of renewable energy.

To prepare for this, various step prediction methods are used. However, it is impossible to accurately predict the change in energy production using only such a short-term forecasting method. This is because the amount of power generation may be lower or higher than expected due to unforeseen abnormal weather conditions. Therefore, it is necessary for the system operator to review the system stability for all cases or situations as much as possible in order to prevent accidents and take prompt action. However, in order to take into account both the constantly fluctuating load (for example, devices that use electrical energy in a home or factory) and the amount of generation of renewable energy, it is physically constrained because it is necessary to consider all of the numerous possible cases and situations. there has to be

Japanese Patent Laid-Open No. 2019-030065 (published on February 21, 2019) Japanese Patent Laid-Open No. 2016-194849 (published on November 17, 2016) Republic of Korea Patent Publication No. 2014-0043987 (published on April 14, 2014)

An object of the present invention is to provide an energy management device and method capable of detecting a case (case or situation, etc.) having weak stability in a system having at least one energy source and outputting a detection result.

An energy management device and an energy management method are provided in order to solve the above problems.

The energy management device relates to individual energies, and a first mode processing unit for outputting at least one random value for the output of renewable energy by using the maximum and minimum power generation and corresponding to the random value based on the random value It may include a post-processing unit that acquires at least one result data.

The energy management method includes the steps of selecting at least one of a first mode, a second mode, and a third mode, and when the first mode is selected, linking individual energies, and using the maximum and minimum generation amounts of renewable energy It may include outputting at least one random value for the output of , and obtaining at least one result data corresponding to the random value based on the random value.

According to the above-described energy management apparatus and method, it is possible to appropriately detect and acquire a case in which stability is weak in a system having at least one energy source, and also to output the detection result obtained in this way.

In addition, it is possible to check and review a number of cases that may occur in the management of the energy system, and accordingly, the safety of the management of the energy system can be promoted and improved.

In addition, since it is possible to separately acquire information on cases vulnerable to system stability among numerous possible cases (cases or situations), the system operator does not need to review all cases directly, so work efficiency can be improved.

In addition, according to the above-described energy management apparatus and method, it is possible to establish in advance countermeasures for various situations (eg, lack of power generation, etc.) related to renewable energy generation in advance based on the obtained information, so that when a situation occurs It is possible to respond quickly and to stabilize power supply and demand.

In order to more fully understand the drawings recited in the Detailed Description of the Invention, a detailed description of each drawing is provided.
1 is a block diagram of an embodiment of an energy management device.
2 is a diagram of one embodiment of input data.
3 is a diagram of an embodiment of a first mode processing unit.
4 is a diagram illustrating an example of an input screen for the first mode.
5 is a diagram of an embodiment of a second mode processing unit.
6 is a diagram illustrating an example of an input screen for the second mode.
7A is a diagram of an embodiment of a post-processing unit.
7B illustrates a first example of synthesizing result data output from the post-processing unit in the form of a spreadsheet file.
7C illustrates a second example of synthesizing result data output from the post-processing unit in the form of a spreadsheet file.
8 is a first diagram of an embodiment of a third mode processing unit.
9 is a second diagram of an embodiment of a third mode processing unit.
10 is a first flowchart of an embodiment of an energy management method.
11 is a second flowchart of an embodiment of an energy management method.

In the following specification, the same reference numerals refer to the same elements unless otherwise specified. The term added with 'unit' used below may be implemented in software or hardware, and depending on the embodiment, one 'unit' may be implemented as one physical or logical part, or a plurality of 'units' may be implemented as one It may be implemented as a physical or logical part, or one 'unit' may be implemented with a plurality of physical or logical parts.

Throughout the specification, when it is said that a part is 'connected' to another part, it may mean a physical connection or an electrically connected part depending on the part and the other part. In addition, when it is said that a certain part 'includes' another part, it does not exclude another part other than the other part unless otherwise stated, and may further include another part according to the designer's choice. means there is

Terms such as 'first' or 'second' are used to distinguish one part from another, and unless otherwise specified, they do not mean sequential expressions. Also, singular expressions may include plural expressions unless the context clearly dictates otherwise.

Hereinafter, various embodiments of the energy management device will be described with reference to FIGS. 1 to 9 .

1 is a block diagram of an embodiment of an energy management device.

Referring to FIG. 1 , the energy management device 100 is connected to at least one of an input/output device (I/O device) 90 and a storage unit 160 to transmit/receive data, and the input/output device 90 ) operates according to the signal transmitted from the input unit 91 or transmits a signal to the output unit 92 of the input/output device 90 so that the output unit 92 outputs an image (still image or moving image, etc.) or sound or data from the storage unit 160, for example, input data 161 or result data (162-1 to 152-n, where n is a natural number equal to or greater than 1) is read and obtained and/or data stored in the storage unit 160 , for example, by transmitting the result data 162-1 to 152-n, the storage unit 160 may store these data. In this case, the energy management device 100 , the input/output device 90 , and/or the storage unit 160 may perform mutual data transmission/reception based on a wired communication network, a wireless communication network, or a combination thereof. Here, the wired communication network may be constructed using a cable, and the cable may include, for example, a pair cable, a coaxial cable, an optical fiber cable, or an Ethernet cable. The wireless communication network may be implemented using at least one of a short-range communication network and a telecommunication network. According to an embodiment, the energy management device 100, the input/output device 90, and/or the storage unit 160 may be installed together in one physical device (eg, a server computer, etc.), or spaced apart from each other. It may be installed on each physical device (eg, a computer for a server and an external storage device).

According to an embodiment, the energy management apparatus 100 may include a mode processing unit 101 , a pre-processing unit 141 , and a post-processing unit 142 .

The mode processing unit 101 performs at least one of an operation (which can be expressed as a processing or an algorithm, etc.) corresponding to at least one pre-stored mode according to a user's instruction/command or a predefined setting input through the input unit 91 . can do. For example, the mode processing unit 101 may perform at least one process to obtain an evaluation result of system stability and/or a result according to regional renewable energy output characteristics. More specifically, for example, the mode processing unit 101 outputs at least one random value for the output of renewable energy, for example, outputs a random value corresponding to the connection of large-scale renewable energy, or simulates the amount of power generation in the selected area It is also possible to output a random value corresponding to . Also, for another example, the mode processing unit 101 may detect an optimal operating point of at least one converter introduced into the system. To perform the above-described operation, the mode processing unit 101 may include at least one of the first mode processing unit 110 , the second mode processing unit 120 , and the third mode processing unit 130 . Each of the processing units 110 to 130 will be described later.

The preprocessor 141 obtains at least one of the first to n-th result data 151-1 to 151-n from the storage 160 , and at least one of the obtained result data 151-1 to 151-n. ) calculates the power flow and transmits it to the mode processing unit 101 . In this case, the preprocessing unit 141 searches the storage unit 160 based on a path and/or file name input by the user or predefined, and the first to nth result data 151-1 to 151-n). At least one of them may be obtained.

The post-processing unit 142 may generate at least one new result data based on the random values output by the first mode processing unit 110 and the second mode processing unit 120, for example, the second result data to the n-th result data 151- 2 to 151-n), the obtained result data 151-2 to 151-n may be transmitted to the storage unit 160 . For example, when the pre-processing unit 141 obtains the i-th result data 151-i, the post-processing unit 142 may perform an (i+1)-th result data 151-(i+1) in response thereto. ) may be obtained and transmitted to the storage unit 160 . The storage unit 160 stores the result data 151-1 to 151-n obtained by the post-processing unit 142 . A detailed operation of the post-processing unit 142 will be described later.

The above-described energy management device 100 may be implemented using at least one processor, where the processor is, for example, a central processing unit (CPU, Central Processing Unit), a micro controller unit (MCU, Micro Controller Unit). ), an application processor (AP), an application processor (AP), a microprocessor (Micom), an electronic control unit (ECU), and/or other electronic devices capable of processing various calculations and generating control signals, etc. there is. These devices may be implemented using, for example, one or more semiconductor chips and related components. According to an embodiment, the processor drives at least one application (which can be expressed as software, a program, or an app) stored in the storage unit 160 to perform a predefined operation, determination, processing and/or control operation, etc. can also be done Here, the application stored in the storage unit 160 may be directly written by a designer and input and stored in the storage unit 160, or acquired or updated through an electronic software distribution network accessible through a wired or wireless communication network. it might be

In addition, the energy management device 100 may be implemented using at least one information processing device in which one or more such processors are installed, and the electronic information processing device is, for example, a desktop computer, a laptop computer, a server computer, and a smart device. Phones, tablet PCs, smart watches, navigation devices, portable game machines, head mounted display (HMD) devices, artificial intelligence sound reproduction devices, digital televisions, home appliances, mechanical devices, and/or electronic computing/processing of information and at least one device capable of controlling related thereto and specially manufactured for energy management.

The storage unit 160 stores data (161, 162-1 to 162-n) or applications necessary for the operation of the energy management device 100 , and at least one data ( 161, 162-1 to 162-n) may be transmitted to the energy management device 100 . In addition, according to an embodiment, the storage unit 160 is electrically connected to the input/output device 90 to receive and store data or applications from the input/output device 90 , or to store data 161 , stored in the input/output device 90 , 162-1 to 162-n).

According to an embodiment, the storage unit 160 may store at least one of the input data 161 and the at least one result data 162-1 to 162-n, and if necessary, the first comprehensive data 163, 7B ), the second comprehensive data 164 (refer to FIG. 7C ), and the third comprehensive data 165 may be further stored.

2 is a diagram of one embodiment of input data.

The input data is data input by a user by manipulating the input unit 91 or input in advance by a designer, etc. Referring to FIG. (161-2), it may include at least one of the renewable energy installation location bus data (161-3) and the line data (161-4).

The power generation unit price data 161-1 may include data on the power generation unit price of at least one generator(s). The power generation unit price data 161-1 may be implemented in the form of a table (or list, etc.) of generators and corresponding power generation unit prices, and in this case, they may be arranged in descending order or ascending order of power generation unit prices according to embodiments. The power generation unit price data 161-1 may be used by the post-processing unit 142 .

The region of interest bus data 161 - 2 may include data on a bus of at least one region of interest for which a stability result is to be observed. A bus bar is a facility or facility provided between at least one energy source, such as a power plant, and at least one load, in which the power generated from the at least one energy source is temporarily collected to be distributed to at least one load. The current concentrated in the bus bar is distributed and delivered to each load. The region of interest bus data 161 - 2 may be transmitted to the post-processing unit 142 and used by the post-processing unit 142 .

The installation location busbar data 161-3 means data on at least one busbar to which at least one renewable energy source is connected or installed. The installation location bus data 161-3 may be transmitted to and used by the second mode processing unit 120 .

The line data 161-4 may include information on a line between at least one energy source, at least one busbar, and/or at least one load (such as From-To busbar information). The line data 161-4 may be transmitted to the third mode processing unit 150 and used for N-level detection.

The first result data to the n-th result data 162-1 to 162-n may include data previously prepared and input separately, and/or may include data generated by the energy management device 100 . can Separately, the pre-written and input data may be provided in the form of a database. For example, the result data 162-1 to 162-n may include the value of the flexible current corresponding to the random value of the amount of renewable energy generation, and the value of the flexible current is the sum of the flexible currents, but each region It may include the value of the flexible current for each line connecting them (163, see FIG. 7b ). Also, as another example, the result data 162-1 to 162-n may include values for the generation amount and/or voltage of the ROI corresponding to the random value (164, see FIG. 7C ).

The first comprehensive data 163 (refer to FIG. 7B ) includes first to n-th result data 162-1 to 162-n obtained according to the processing operations of the first mode processing unit 110 and the post-processing unit 142 . It may include data obtained by combining at least one of them, for example, it may be generated in the form of a table. In this case, the first comprehensive data 163 (refer to FIG. 7B ) may be stored in a spreadsheet file format.

The second comprehensive data 164 (refer to FIG. 7C ) includes first to n-th result data 162-1 to 162-n obtained according to the processing operations of the second mode processing unit 120 and the post-processing unit 142 . It may be data constructed by combining at least one of them, and may include, for example, data on the amount of power generation or voltage of at least one region of interest. The second comprehensive data 164 (refer to FIG. 7C ) may also be generated in the form of a table, and more specifically, may be stored in the form of a spreadsheet file.

The third comprehensive data 165 may include information on an optimal operating point obtained according to a processing operation of the third mode processing unit 130 . The third aggregate data 165 may have a table format, and may be stored, for example, in a spreadsheet file format.

At least one of the first comprehensive data 163 (refer to FIG. 7b), the second comprehensive data (164, see FIG. 7c) and the third comprehensive data 165 may be output to the outside through the output unit 92, etc., It can be viewed by a user or the like.

The storage unit 160 may include, for example, at least one of a main memory device and an auxiliary memory device. The main memory may be implemented using a semiconductor storage medium such as a ROM and/or a RAM. The ROM may include, for example, a conventional ROM, an EPROM, an EEPROM, and/or a MASK-ROM. The RAM may include, for example, DRAM and/or SRAM. Auxiliary storage devices include flash memory devices, Secure Digital (SD) cards, solid state drives (SSDs), hard disk drives (HDDs), magnetic drums, compact discs (CDs), and DVDs. ) or an optical recording medium such as a laser disk, a magnetic tape, a magneto-optical disk, and/or a floppy disk, etc. may be implemented using at least one storage medium capable of permanently or semi-permanently storing data.

The input/output unit 90 includes an input unit 91 that receives a command/instruction or data from a user, etc., and data 161, 162-1 to 162 stored in the operation result of the energy management device 100 or the storage unit 160 . -n) may include an output unit 92 for outputting to the outside.

The input unit 91 may include, for example, at least one of the power generation unit price data 161-1, the region of interest bus data 161-2, the renewable energy installation location bus data 161-3, and the line data 161-4. You can input one. The information 161-1 to 161-4 may be input before the operation of the first mode processing unit 110 and the second mode processing unit 120 . These information 161-1 to 161-4 may be input in the form of a table, or may be input in the form of a predetermined spreadsheet file. If necessary, the input unit 91 may receive at least one of the first result data to the n-th result data 162-1 to 162-n, and among them, the first mode processing unit 110 and the second mode processing unit The result data 162-1 to 162-n initially used by any one of 120 may include a pre-fabricated database in relation to the lineage. In addition, the input unit 91 is the maximum output value of the renewable energy, the minimum output value, information on the bus corresponding to the region of interest, information on the essential operation generator and / or mode processing unit 101 and post-processing unit 142, etc. An iteration time, etc. may be input, or the file names or stored locations (paths) of the first to n-th result data 162-1 to 162-n may be input according to an embodiment. The input unit 91 is, for example, a data input/output terminal capable of receiving data (eg, a universal serial bus terminal, etc.), a keyboard device, a mouse device, a scanner device, a trackball, a trackpad, a touch screen, and/or a touch screen. It may include a pad and the like, but is not limited thereto.

The output unit 92 may visually and/or audibly output an operation result of the energy management device 100 , for example, first to n-th result data 162-1 to 162-n. and/or data generated based on the first result data to the n-th result data 162-1 to 162-n, for example, the first result data to the n-th result data 162-1 to 162-n ), the spreadsheet files 163 (refer to FIG. 7b) and 164 (refer to FIG. 7c)) constructed by combining at least one of them may be output. The output unit 92 may include, for example, a display, a monitor device, a digital television, a printer device, a speaker device, and/or a lighting device, but is not limited thereto.

Hereinafter, the first mode processing unit 110 will be described in more detail.

3 is a diagram of an embodiment of the first mode processing unit, and FIG. 4 is a diagram illustrating an example of an input screen for the first mode.

As shown in FIG. 3 , the first mode processing unit 110 is provided to evaluate stability when a large-capacity renewable energy source(s) is introduced into the system. The first mode processing unit 101, for example, sequentially performs the individual energy linkage process 111 and the random value output process 112 based on the maximum/minimum power generation amount, and at least one A random value may be output and transmitted to the post-processing unit 142 . The post-processing unit 142 may acquire at least one instance for stability evaluation by performing predetermined processing based on the output random value.

Specifically, for example, as shown in FIG. 4 , the output unit 92, when the first mode processing unit 110 starts an operation according to a user's manipulation or a predefined setting, the user's desired setting and data A predetermined menu screen 93 for receiving . On the menu screen 93, a path 93a in which any one of the result data 162-1 to 162-n (eg, the first result data 162-1) is stored, and the result data 162-1 to 162-n ) of any one (for example, the first result data 162-1), the file name 93b, information about the busbar (93c, for example, the bus identification number), the maximum generation amount 93d, the minimum generation amount 93e, essential It may include an input field for inputting at least one of information about the operation generator (eg, a list, etc., 93f) and the number of repetitions 93g. The user may manipulate the input unit 91 to input a desired value into at least one of the respective menus 93a to 93g of the output unit. Accordingly, based on the desired result data 162-1 to 162-n, the user obtains a random value for the case belonging to the desired range (the range between the maximum and minimum power generation) with respect to the grid connected to the desired bus. be able to do In addition, the user can also set the essential operation generator to solve the power transmission constraint. In addition, the user may output the result data 162-1 to 162-n corresponding to the number of repetitions by inputting the number of repetitions.

When the user inputs information about the busbar, the maximum power generation amount, and the minimum power generation amount using the menu screen 93 described above, the first mode processing unit 110 selects a linkage point based on the input busbar information 93c. It is determined ( 111 ), and a random value corresponding to the input bus is returned using the maximum and minimum power input by the user ( 112 ). Here, the random value includes a value between the maximum power generation amount and the minimum power generation amount. Accordingly, based on the result data 162-1 to 162-n selected by the user, a random value for an instance belonging to a desired range (a range between the maximum and minimum power generation) in a desired area may be obtained. The returned random value is transmitted to the post-processing unit 142 (112).

Hereinafter, the second mode processing unit 120 will be described in more detail.

5 is a diagram of an embodiment of the second mode processing unit, and FIG. 6 is a diagram illustrating an example of an input screen for the second mode.

Referring to FIG. 5 , the second mode processing unit 120 outputs a random value by performing a power generation amount acquisition process 121 and a random example output process 122 for each region of interest in order to simulate the generation amount by region, and the post-processing unit 142 ) can be passed to In this case, the installation position busbar data 161-3 input by the user or the like can be used.

Specifically, for example, referring to the bar shown in FIG. 6 , when an operation is started according to a user's manipulation or a predefined setting, the second mode processing unit 120 provides the user's desired setting and data to the output unit 92 . A predetermined menu screen 94 for receiving may be output. In this case, the menu screen 94 output to the output unit 92 is a path 94a in which any one of the result data 162-1 to 162-n (eg, the first result data 162-1) is stored. ), the file name 94b of any one of the result data 162-1 to 162-n (for example, the first result data 162-1), the number of repetitions 94c, and information 94d about the required operation generator It may include an input box for at least one of them. Also, the menu screen 94 may include at least one input field through which predetermined data 94e for at least one ROI may be input. At least one region of interest displayed on the menu screen 94 may be determined based on a correlation of climate change, for example, a region having the same output characteristic due to a high correlation of climate change as one region of interest. can be decided. Also, the data 94e for the region of interest may include input fields for each of the maximum power generation amounts 94f1 and 94g1 and the minimum power generation amounts 94f2 and 94g2 for at least one area. In other words, the user may input the maximum power generation amount and/or the minimum power generation amount for each of the desired regions (eg, at least one region of interest that uses a lot of power and/or at least one region of interest that is weak in voltage). According to an embodiment, the menu screen 94 may not receive separate information about the mother ship.

When the user inputs the maximum and minimum power generation of at least one region of interest using the above-described menu screen 93, the second mode processing unit 120 obtains the maximum and minimum power generation of at least one region of interest and ( 121 ), a random value is output for each ROI by using the maximum and minimum power generation for each ROI ( 122 ). Here, the random value output for each ROI may include an arbitrary value between the maximum amount of power input for each ROI and the minimum amount of power input for the same region. According to an embodiment, the second mode processing unit 110 may distribute a random value to each bus in each ROI by using the pre-inputted installation location bus data 161-3. That is, at least one bus located in each ROI or related to each ROI is obtained from the installation location bus data 161-3, and a random value corresponding to each ROI is obtained from at least one bus in each ROI. can be distributed to In this case, the random value may be equally distributed for each bus or may be distributed according to a predefined weight. For example, a value obtained by dividing a random value output for the region of interest by the number of busbars in the region of interest may be determined as a random value corresponding to each busbar. More specifically, for example, if, as a result of reading the installation location busbar data 161-3, there are 5 busbars corresponding to any one ROI, the minimum value for the same ROI is set to 0, and the maximum The value is set to 10, and if 5 is output as a random value for the region of interest, 1 (=5/5) is distributed to each of the 5 busbars in the region of interest. A random value for each bus in at least one ROI may be transmitted to the post-processing unit 142 .

Hereinafter, the post-processing unit 142 will be described in more detail.

7A is a diagram of an embodiment of a post-processing unit. 7B shows a first example in which the result data output from the post-processing unit is synthesized in the form of a spreadsheet file, and FIG. 7C shows a second example in which the result data output from the post-processing unit is synthesized in the form of a spreadsheet file. will be.

The post-processing unit 142 may acquire new result data based on a random value transmitted from at least one of the first mode processing unit 110 and the second mode processing unit 120 .

According to an embodiment, the post-processing unit 142 may obtain result data by processing the results of the first mode processing unit 110 and the second mode processing unit 120 differently from each other, or processing the same results to obtain the result data. You can also obtain data.

For example, when a random value is transmitted from the first mode processing unit 110 , the post-processing unit 142 may adjust the amount of power generation using the power generation unit price data 161-1 input in advance (142- One). In the power system, supply and demand must be matched with each other, so when additional electrical energy is supplied by the generation of renewable energy, the amount of power generated by the existing generator must be reduced. In the case of economic dispatch, the generators are sequentially terminated or removed according to the economic order in order to reduce the amount of power generation. The post-processing unit 142 may reflect that the actual generator is terminated by sequentially removing the amount of power generated corresponding to at least one generator based on the power generation unit price data 161-1 to reflect the economic power supply. Accordingly, the amount of power generation is adjusted.

According to an embodiment, the post-processing unit 142 may sequentially remove only the other generators except for the essential operation generator among the at least one generator. That is, when the user inputs information 93f on the essential operation generator as shown in FIG. 4 , the post-processing unit 142 removes the generation amount corresponding to the generator excluding the essential operation generator based on this and adjusts the generation amount. may be

The post-processing unit 142 may sequentially calculate algae ( 142 - 2 ).

When the tidal current calculation is finished, new result data is generated based on the calculated tidal current, and the generated result data is transferred to and stored in the storage unit 160 ( 142 - 3 ). In this case, the resulting data may be saved in a spreadsheet file format.

Meanwhile, the pre-processing unit 141, the first mode processing unit 110, and the post-processing unit 142 repeat the above-described processing based on the acquired new result data (eg, (i+1)th result data) to You can also do it again. Accordingly, another new result data corresponding to the (i+1)th result data (eg, (i+2)th result data) may be generated again. The pre-processing unit 141, the first mode processing unit 110, and the post-processing unit 142 may repeatedly perform the above-described processing according to the number of repetitions input by the user or according to a predefined setting. For example, when the i-th result data is the initial data and the number of iterations is set to k, the (i+1)-th according to the iterative processing of the pre-processing unit 141, the first mode processing unit 110, and the post-processing unit 142 ) result data to (i+k)th result data are generated and stored in the storage unit 160 . As the number of iterations increases, the first mode processing unit 110 returns more various random values. Therefore, it becomes possible to observe more various types of renewable energy generation. At least one result data 162-1 to 162-n obtained according to this method may be combined, and accordingly, first comprehensive data may be generated as shown in FIG. 7B .

According to an embodiment, the first comprehensive data 163 (see FIG. 7b ) may include a flexible tidal current output result (eg, a total tidal flow and a tidal current of each flexible line) according to the random generation amount for renewable energy. Also, according to an embodiment, data on each bird at the time of N-1 accident of the flexible bird as well as the flexible bird may also be included. In addition, it is also possible to include the contents of the second comprehensive data 164 (refer to FIG. 7C ) to be described later.

As another example, when the random value is transmitted from the 21st mode processing unit 120 , the post-processing unit 142 calculates the amount of power generation by using the power generation unit price data 161-1 input in advance in the same manner as described above. Adjust (142-1), and sequentially count algae (142-2). When adjusting the amount of power generation, as described above, the amount of power generated for the essential operation generator may be maintained as needed.

According to an embodiment, the post-processing unit 142 may perform a process of acquiring a vulnerable case when the algae calculation is finished ( 142 - 4 ). Specifically, the post-processing unit 142 may detect and acquire a case with the weakest stability among all regions of interest or for each region of interest.

For example, the post-processing unit 142 may include at least one data obtained according to the iterative processing results of the pre-processing unit 141, the mode processing unit 101 (eg, the second mode processing unit 120) and the post-processing unit 142, That is, one or more result data (at least one of 162-1 to 162-n) representing the most vulnerable case (case or situation) in terms of stability is selected and obtained from among at least one result data (162-1 to 162-n). can do. In other words, the post-processing unit 142 may acquire a case that has the greatest influence on system stability among a plurality of acquired and output cases.

According to an exemplary embodiment, the post-processing unit 142 may be designed to select a case that can have the greatest influence on system stability using at least one objective function.

For example, the objective function detects a case in which the sum of flexible currents in at least one area of interest (eg, the metropolitan area) with a large amount of power is the maximum among at least one case that may occur due to various renewable energy generation conditions. It may be designed to do so, and the post-processing unit 142 may use such an objective function to select a case that has the greatest influence on system stability. The situation in which the sum of flexible currents in at least one area is the maximum may occur when the amount of power generation in areas other than at least one area is very large and, conversely, the load in at least one area is very large. In such a situation, since it can greatly affect the transient stability in the event of a flexible line accident, the post-processing unit 142 detects such a case, and stores the detection result in the storage unit 160 and/or the input/output unit 90 It may be provided to output to the outside through the.

For another example, the objective function may be designed to select a case in which the average voltage value of at least one ROI with weak voltage is the lowest among at least one possible case, and the post-processing unit 142 may Functions can also be used to select the cases that have the greatest influence on the system stability. In a situation where the average voltage value is the lowest, there is a possibility that a wide-area blackout due to a voltage collapse is induced. The post-processing unit 142 may be provided to detect and store it or output it to the outside.

In addition, the post-processing unit 142 may be designed to detect a situation or case in which the system is unstable using at least one other objective function input or designed by a designer or a user, and to store or output it.

When the algae calculation and detection of the vulnerable case are finished, new result data is generated based on the calculated algae, and the generated new result data may be transferred to and stored in the storage unit 160 ( 142 - 3 ). In this case, the new result data may be saved in the form of a spreadsheet file.

As described above, the pre-processing unit 141, the second mode processing unit 120, and the post-processing unit 142 perform pre-obtained result data (eg, The above-described processing may be repeatedly performed based on (i+1)th result data), and accordingly, result data corresponding to the input number of repetitions, for example, (i+1)th result data to (i+k)th result data ) result data may be generated and stored in the storage unit 160 . At least one result data 162-1 to 162-n obtained according to this method may be combined, and accordingly, second aggregate data may be generated as shown in FIG. 7C .

According to an embodiment, the second comprehensive data 164 (refer to FIG. 7C ) may include the amount of renewable energy generation by region. In this case, the second comprehensive data 164 (refer to FIG. 7C ) may include a bus voltage or a voltage result value for at least one region of interest in which the generation amount is determined to be particularly weak.

As such, the energy management device 100 returns a random value and repeats the process of adjusting the power generation and calculating the current based on it, so that various power generation patterns can be simulated, and as a result, the renewable energy that has the greatest effect on the system development scenarios can be detected.

Hereinafter, the third mode processing unit 130 will be described in more detail.

8 is a first diagram of an embodiment of the third mode processing unit, and FIG. 9 is a second diagram of an embodiment of the third mode processing unit.

According to an embodiment, the third mode processing unit 130 may be provided to detect an optimal operating point of at least one converter introduced into the system. That is, when it is necessary to change the operating point according to the amount of renewable energy generation, the third mode processing unit 130 obtains an optimal operating point for at least one converter, thereby enabling the converter to operate more efficiently. Here, the converter may include a high-voltage, direct current (HVDC) converter.

Specifically, as shown in FIG. 8 , the third mode processing unit 130 may first select whether to use a converter having data or to add a new converter to a new location ( 131 ).

Sequentially, an objective function for at least one desired converter may be selected according to a user's selection or according to a predefined setting ( 132 ). The selected objective function may include, for example, an objective function for equalizing utilization or minimizing line loss, but is not limited thereto.

Once the objective function is selected and determined, an N-level busbar and/or level is selected 133 to establish a valid range of the selected and determined objective function. Selection of the N-level busbar and/or level may be performed by a user or by a predefined setting, for example, based on pre-input and stored line data 161-4.

When the selection of the N-level bus and/or the level is completed, an optimal value of the operating point of the converter is calculated and obtained based on the input data (134). In this case, a particle swarm optimization (PSO) technique may be used to calculate the optimal value. The particle cluster optimization technique is a method of detecting a global optimal point by iteratively moving initial particles randomly dispersed within a given constraint according to a specific mathematical rule.

Referring to FIG. 9 , an effective area in which particles will be dispersed is first calculated ( 143-1 ), and M particles (hereinafter, random particles) corresponding to the output size of the converter are generated, but each random particle is random. It has the generated information (143-3). Algae calculation may be performed for each particle by reflecting the converter output size information of each random particle ( 143 - 4 ). In this case, the current calculation may be performed through a predetermined power system analysis program. An objective function corresponding to each particle may be obtained based on the information obtained according to the result of calculating the tidal current, and the size of the objective function may be calculated (134-4). Here, the information obtained according to the result of the tidal current calculation may include, for example, a voltage magnitude, a phase angle, and a tidal current magnitude. A global minimum point may be sequentially determined (143-5). The determination of the global optimal particle may be performed by comparing the magnitudes of the objective functions corresponding to the respective particles. When the global optimal particle is obtained, the velocity of individual particles toward the global optimal particle is calculated by a predefined equation (143-6), and the individual particles are moved according to the magnitude of the calculated velocity (143-7) . Accordingly, information on the output size of the converter of each particle, for example, the ultra-high voltage direct current transmission converter is changed. Whether or not to be repeated may be additionally checked sequentially ( 143 - 8 ). If iteration is necessary, calculate the tidal current for each particle (143-3), obtain the objective function for each particle (143-4), determine the global optimal particle (143-5), and calculate the velocity of each particle (143-6) and the moving process (143-7) of each particle is sequentially repeated. Iteration of these operations may be performed continuously until a predefined number of iterations is reached. When the above-described processes 143-3 to 143-7 are performed for a predefined number of iterations, a final global optimal particle is determined (143-9). Information of the final global optimal particle, ie, the output operating point of the converter, may be used as the optimal operating point. The optimal operating point obtained according to such a process may be stored in the storage unit 160 (135).

When the optimum operating point is obtained, the third comprehensive data 165 may be generated based on the optimum operating point. The third comprehensive data may also be stored in the storage unit 160 .

Hereinafter, an embodiment of an energy management method will be described with reference to FIGS. 10 and 11 .

10 is a first flowchart of an embodiment of an energy management method.

As shown in FIG. 10 , first, at least one input data and at least one result data, for example, first result data, may be stored in a storage unit ( 300 ). In this case, the input data may include, for example, at least one of power generation unit price data, interest area bus data, renewable energy installation location bus data, and track data, but is not limited thereto. In addition, the resulting data may include data previously created by other users or other organizations, and/or may include data generated by the energy management device.

A tide for at least one result data among the sequentially stored result data may be calculated ( 302 ).

At least one of the at least one mode provided by the energy management device may be selected ( 304 ). Here, the at least one mode may include at least one of the first mode to the third mode, and the first mode is a mode for evaluating the stability of the system when a renewable energy complex with a very large capacity is introduced into the system and the second mode is a mode for confirming results according to regional renewable energy output characteristics. The third mode is a mode provided to detect an optimal operating point of at least one converter introduced into the system. Selection of at least one mode may be performed manually by a user, or may be performed automatically according to a predefined setting. The selection process 304 of at least one mode may be performed before, after, and/or simultaneously with the above-described tidal flow calculation process 302 for the result data.

If the first mode is selected (YES in S306), the energy management apparatus may output a random value by performing a series of processes corresponding to the first mode (S308). For example, the energy management device may determine and obtain at least one random value for the output of renewable energy based on the maximum/minimum power generation input by the user or predefined by linking individual energies. . In order to receive at least one piece of information necessary for processing in the first mode, a predetermined menu screen as shown in FIG. 4 may be further output in advance if necessary.

According to an embodiment, after a random value for the output of renewable energy is obtained, the amount of power generation may be adjusted ( 310 ). In this case, the adjustment of the amount of power generation may be performed for economic power supply, and specifically, may be performed using, for example, input data (eg, power generation unit price data). More specifically, the energy management device may control the amount of power generation by sequentially removing the amount of power corresponding to at least one generator using the power generation unit price data. According to an embodiment, the sequential removal of the generator may be performed except for the essential operation generator among at least one generator. The information on the essential operation generator may be separately input by the user before and after the execution of the first mode.

Thereafter, the current may be calculated based on the processing result of the first mode or the adjustment result of the power generation ( 312 ).

When the tidal current calculation is finished, new result data is obtained based on the calculated tidal current, and the obtained result data may be additionally stored in the storage unit ( 314 ).

When the new result data is additionally stored in the storage unit, the energy management device determines whether the result data is obtained as many times as the number of repetitions input by the user or preset (that is, whether the operation according to the first mode is performed for the number of repetitions) It is checked and determined, and if the result data is not obtained as many times as the number of repetitions and repetition is necessary (YES in 316), the above-described operations 308 to 314 are repeated. For example, the first mode processing and result data storage (308 to 314) operations are performed in the same manner.

According to an embodiment, the first comprehensive data may be generated based on existing result data or new result data. The first aggregate data may be generated by combining the result data(s), for example, may be generated in a spreadsheet file format.

If the second mode other than the first mode is selected (No in 306, Yes in 320), the predefined second mode is processed ( 322 ). The processing of the second mode obtains the maximum and minimum values of the generation amount by region according to a user input or a predefined setting, and outputs a random value for each region of interest based on the obtained maximum and minimum values of the generation amount of the region of interest. It can also be done through a process. The random value output for each ROI may include an arbitrary value between the maximum amount of power input for each ROI and the minimum amount of power input for the same region. In this case, the menu screen as shown in FIG. 6 may be output to the outside before processing, through which the user can input at least one piece of information required for processing in the second mode. In addition, the processing of the second mode may be performed using the previously inputted installation position bus data as described above.

When a random value for the output of the renewable energy is obtained, the amount of power generation may be adjusted as necessary, and the current may be calculated based on the processing result of the second mode or the adjustment result of the power generation power ( 324 ). Results data are obtained according to the algae calculation. Adjustment of the amount of power generation may be performed by sequentially removing the amount of power generated corresponding to at least one generator based on the power generation unit price data.

According to one embodiment, after the tide is calculated, a vulnerable case may be obtained ( 326 ). Specifically, a case having the weakest stability may be determined and obtained from among at least one ROI or for each ROI. The acquisition of the vulnerable case may be performed based on a plurality of result data acquired according to the second mode processing. The process 326 of acquiring the weak case may be omitted according to the designer's arbitrary selection.

When new result data is obtained through the above-described process, the obtained result data may be additionally stored in the storage unit (328). If a vulnerable case is detected, the vulnerable case may also be stored.

Sequentially, the energy management device may determine whether repetition of the above-described processes 322 to 328 is necessary. In more detail, the energy management apparatus may check whether result data input by the user or a preset number of repetitions is obtained (ie, whether the operation according to the second mode is performed for the number of repetitions). If the result data is not obtained by the number of repetitions (YES in 329), the above-described operations 322 to 328 are repeatedly performed.

If necessary, the second comprehensive data may be generated by combining at least one result data obtained by such a process. The second aggregate data may be in the form of a spreadsheet file, for example.

11 is a second flowchart of an embodiment of an energy management method.

If the user does not select both the first mode and the second mode but selects the third mode (No in 306, No in 320, Yes in 330), the energy management device performs an operation according to the third mode . If any one of the first to third modes is not selected (No in 330 ), the energy management device may execute a predefined operation ( 350 ), for example, enter a state waiting for user input or , an error message may be output, an operation may be terminated, and/or an operation defined by a designer or user may be performed.

When the third mode is selected (YES in S330), a converter may be selected and an objective function may be selected in order to detect an optimal operating point of at least one converter introduced on the grid (S332). When selecting a converter, according to an embodiment, it may be selected whether to use an existing converter or to add a new converter at a new location before calculating the effective area. Also, the objective function may include, for example, an objective function for leveling utilization or minimizing line loss.

Sequentially, N-level busbars and/or levels are selected 324 to establish the effective range of the objective function. Selection of the N-level busbar and level may be performed by the user, or may be performed according to a predefined setting by the designer.

Then, an optimal value of the operating point of the converter may be calculated, and for this, a particle swarm optimization technique may be used.

Specifically, first, random particles corresponding to the output size of the converter but each having randomly generated information are generated ( 336 ), and a tidal current and an objective function for each random particle are calculated ( 338 ). Specifically, the tidal current is calculated for each particle by reflecting the converter output size information of each random particle, and an objective function corresponding to each particle is obtained based on the information according to the tidal calculation result, and the size of the obtained objective function can be calculated.

The size of the objective function corresponding to each particle is compared with each other, and the most optimal particle may be obtained according to the comparison result ( 340 ).

When the global optimal particle is obtained, the velocity of individual particles toward the global optimal particle may be calculated by a predefined equation (342), and the individual particles may be moved according to the magnitude of the calculated velocity ( 344). According to this process, information about the output size of the converter that each particle has can be changed.

The above-described algae and objective function calculation process or individual particle movement processing processes 338 to 344 may be repeatedly performed a predetermined number of times according to user input or predefined settings (346).

When the above-described processes 338 to 344 are performed for a predefined number of iterations, a global optimal particle may be finally determined ( 348 ). The finally obtained information on the global optimal particle (eg, the output operating point of the converter corresponding to the global optimal particle) may be determined as the optimal operating point, and thus the optimal operating point is obtained ( 350 ). At least one of the obtained global optimal particle and the optimal operating point may be stored in the storage unit. According to an embodiment, the above-described third comprehensive data may also be generated using the optimal cloud point.

The energy management method according to the above-described embodiment may be implemented in the form of a program that can be driven by a computer device. Here, the program may include a program command, a data file, a data structure, etc. alone or in combination. The program may be designed and manufactured using machine code or high-level language code. The program may be specially designed to implement the above-described method, or may be implemented using various functions or definitions that are known and available to those skilled in the art of computer software. In addition, here, the computer device may be implemented including a processor or memory that enables the function of the program to be realized, and may further include a communication device if necessary.

A program for implementing the above-described energy management method may be recorded in a computer-readable recording medium. The computer-readable recording medium includes, for example, a magnetic disk storage medium such as a hard disk or a floppy disk, a magnetic tape, an optical recording medium such as a compact disk or DVD, a magneto-optical recording medium such as a floppy disk, and a ROM. , a semiconductor storage device such as a RAM or flash memory, and the like, may include various types of hardware devices capable of storing a specific program executed in response to a computer call.

Although various embodiments of the energy management device and the energy management method have been described above, the energy management device and the energy management method are not limited to the above-described embodiments. Various devices or methods that can be implemented by a person skilled in the art by modifying and modifying based on the above-described embodiments may also be examples of the above-described energy management device and energy management method. For example, the described techniques are performed in an order different from the described method, and/or the described components of a system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components or Even if it is replaced or substituted by an equivalent, it may be an embodiment of the above-described energy management device and energy management method.

100: energy management device 101: mode processing unit
110: first mode processing unit 120: second mode processing unit
130: third mode processing unit 141: pre-processing unit
142: post-processing unit 160: storage unit
161: input data

Claims (17)

a first mode processing unit linking individual energies and outputting at least one random value for the output of renewable energy using the maximum and minimum power generation;
a post-processing unit configured to obtain at least one result data corresponding to the random value based on the random value; and
A third mode processing unit for detecting an optimal operating point of at least one converter,
The third mode processing unit calculates the optimal operating point of the converter by selecting an objective function for the at least one converter and selecting an N-level bus and the number of levels for the objective function,
energy management device.
According to claim 1,
The post-processing unit calculates algae based on the random value,
energy management device.
3. The method of claim 2,
The post-processing unit adjusts the amount of power generation by terminating at least one generator using the power generation unit price data,
energy management device.
According to claim 1,
A second mode processing unit for outputting a random value for each of the at least one ROI by using the maximum and minimum power generation for each of the at least one ROI, further comprising:
energy management device.
5. The method of claim 4,
The post-processing unit obtains at least one result data based on a random value for each of the at least one ROI,
energy management device.
6. The method of claim 5,
A plurality of result data is obtained according to the operations of the second mode processing unit and the post processing unit,
The post-processing unit obtains result data corresponding to a weak case from among the plurality of result data,
energy management device.
delete delete According to claim 1,
The third mode processing unit calculates the operating point of the converter using a particle swarm optimization technique,
energy management device.
selecting at least one of the first mode, the second mode, and the third mode;
when the first mode is selected, outputting at least one random value for the output of renewable energy by linking individual energies and using the maximum and minimum power generation;
obtaining at least one result data corresponding to the random value based on the random value; and
detecting an optimal operating point of at least one converter when the third mode is selected;
The step of detecting the optimum operating point of the at least one converter includes calculating the optimum operating point of the converter by selecting an objective function for the at least one converter and selecting an N-level bus and the number of levels for the objective function. further comprising steps,
How to manage energy.
11. The method of claim 10,
The step of obtaining at least one result data corresponding to the random value based on the random value comprises:
terminating at least one generator using the input power generation unit price data to adjust the amount of power generation; and
calculating an algae based on the random value; comprising at least one of
How to manage energy.
11. The method of claim 10,
When the second mode is selected, the method further comprising: outputting a random value for each of the at least one ROI by using the maximum and minimum power generation for each of the at least one ROI;
How to manage energy.
13. The method of claim 12,
Further comprising the step of obtaining at least one result data based on a random value for each of the at least one region of interest,
How to manage energy.
14. The method of claim 13,
obtaining a plurality of result data; and
Further comprising the step of obtaining result data corresponding to the vulnerable case from among the plurality of result data,
How to manage energy.
delete delete 11. The method of claim 10,
The detecting of the optimal operating point of the at least one converter further comprises calculating the operating point of the converter using a particle swarm optimization technique.
How to manage energy.

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