KR20220088067A - Method for managing aggrigation resource based on small distributed resource and apparuatus thereof - Google Patents

Abstract

The present invention relates to a method for managing aggregate resources based on small distributed resources, comprising the steps of: acquiring ESS contract information on customer-owned small distributed energy storage devices installed in a distribution network or a small power grid; Based on the obtained ESS contract information, the small distributed energy storage devices are configured as a collective resource corresponding to one virtual energy storage device, and information on at least one of representative efficiency, representative capacity, and representative rating of the configured collective resource detecting; and providing collective resource information including the detected information to an upper-level energy management system.

Description

Method and apparatus for managing aggregate resources based on small distributed resources

The present invention relates to a method of utilizing small distributed resources owned by a customer, and more particularly, to a method of collectively converting small distributed resources owned by a customer installed in a distribution network or a small power grid from the perspective of a power system operator.

Due to the increase of various distributed energy resources (DERs) such as small-scale renewable energy, energy storage facilities, and demand resources, the structure of the power industry is changing significantly. According to these structural changes in the electric power industry and the development of information and communication technology, the energy aggregator market, which can create value without physical infrastructure, is emerging. Energy aggregator refers to an intermediary or intermediary platform that creates common profits by gathering consumers, prosumers, and producers.

The energy aggregation 　 business is most active in the DR (Demand Response) field, in which electricity users change their usage to meet the current demand for electricity. In addition, multiple distributed generators (DGs) can be bundled and used as one virtual power plant (VPP), or distributed power (DG) and energy storage system (ESS) within a specific area can be used. Sharing brokerage business is also becoming more and more commercialized.

Economies of scale are necessary for small power entities such as distributed power generation (DG) and energy storage system (ESS) to have influence. An energy aggregator can perform this role. Energy aggregator's business model is based on aggregating, sharing, and optimizing the power resources owned by multiple customers and sharing the resulting benefits.

On the other hand, the use of energy storage system (ESS) to alleviate the variability of the power system is increasing with the increase of new and renewable energy such as solar and wind power and electric vehicles (EV). By the way, although many application technologies of general energy storage system (ESS) have been developed, from the power system operator's point of view, the development of technology to utilize energy storage systems (ESSs) installed in a power distribution network or a small-scale power grid (ie, microgrid) is difficult. It is insignificant. Therefore, a method for utilizing customer-owned small distributed ESSs installed in a power distribution network or a small power grid is being studied.

In general, when making aggregate resources of small distributed ESSs installed in the power grid, representative capacity and representative rating are given to configure aggregate resources, and the power system operator considers only the representative capacity and representative rating of the aggregate resource to optimize the operation schedule for distributed resources of the power system. will derive However, the premise of such a power system energy management model is that the charge/discharge rates (or charge/discharge rates, C-rate) of the small distributed ESSs constituting the aggregate resource must all be the same. However, battery-based energy storage system (ESS) is mainly used for various purposes by grafting various battery technologies such as lead-acid, lithium ion battery (LiB), and redox flow battery. , the charge/discharge rate (C-rate) varies according to the characteristics of the battery. Therefore, from the perspective of the power system operator, it is difficult to directly utilize the customer's small distributed ESS as a collective resource for the power system energy management model.

[Prior literature number]

[Patent Literature]

KR 10-2015-0092994 A

KR 10-1776168 B

SUMMARY OF THE INVENTION The present invention aims to solve the above and other problems. Another object of the present invention is to provide a method and an apparatus for configuring the small distributed resources as aggregate resources in consideration of the charge/discharge rate (C-rate) of the small distributed resources installed in a distribution network or a small power grid.

Another object is to provide a method and apparatus for calculating the optimal operation command value for controlling the charging/discharging operation of small distributed resources based on the collective resource command value received from the energy management system (EMS) of the upper system. is in

According to an aspect of the present invention in order to achieve the above or other objects, the method comprising: acquiring ESS contract information about customer-owned small distributed energy storage devices installed in a distribution network or a small-scale power grid; Based on the obtained ESS contract information, the small distributed energy storage devices are configured as a collective resource corresponding to one virtual energy storage device, and information on at least one of representative efficiency, representative capacity, and representative rating of the configured collective resource detecting; and providing aggregate resource information including the detected information to an energy management system of an upper system.

According to another aspect of the present invention, the small distributed energy storage devices are aggregated resources corresponding to one virtual energy storage device based on the ESS contract information on the customer-owned small distributed energy storage devices installed in the power distribution network or the small-scale power grid. and, detecting information on at least one of representative efficiency, representative capacity, and representative rating of the configured collective resource, and providing collective resource information including the detected information to an energy management system of a higher system. wealth; and calculating an individual CES command value for controlling the charging/discharging operation of the small distributed energy storage devices based on the collective resource command value received from the energy management system, and calculating the calculated individual CES command value for the small distributed energy storage devices It provides a small distributed resource-based aggregate resource management device including a setpoint operation unit provided by

According to another aspect of the present invention, the process of obtaining ESS contract information about customer-owned small distributed energy storage devices installed in a distribution network or a small-scale power grid; Based on the obtained ESS contract information, the small distributed energy storage devices are configured as a collective resource corresponding to one virtual energy storage device, and information on at least one of representative efficiency, representative capacity, and representative rating of the configured collective resource the process of detecting And it provides a computer program stored in a computer-readable recording medium so that the process of providing the collective resource information including the detected information to the higher-level energy management system can be executed on the computer.

A method for managing an aggregate resource based on a small distributed resource according to embodiments of the present invention and an effect of the apparatus will be described as follows.

According to at least one of the embodiments of the present invention, an aggregator for configuring the small distributed resources as one virtual aggregate resource in consideration of the charge/discharge rate (C-rate) of the small distributed resources installed in the distribution network or the small power grid By providing the power system operator, it is possible to reduce the investment cost for ESS by utilizing small distributed resources composed of collective resources, and for the ESS owner, additional revenue is created by lending the ESS during unused time to the power system operator. There are advantages to being able to

However, the effects achievable by the method and the apparatus for managing aggregated resources based on small distributed resources according to the embodiments of the present invention are not limited to those mentioned above, and other effects not mentioned above can be seen from the description below. It will be clearly understood by those of ordinary skill in the art to which the invention pertains.

1 is a diagram illustrating a microgrid system utilizing aggregate resources based on small distributed resources related to the present invention;
FIG. 2 is a diagram referenced to explain a method for managing distributed resource energy of a microgrid system in the energy management system of FIG. 1;
3 is a flowchart illustrating an operation of an apparatus for managing aggregate resources according to an embodiment of the present invention;
4 is a diagram referenced to explain a method of calculating a representative rating of an aggregate resource using a linear model of an interval;
5 is a diagram referenced to explain a process of controlling the charging/discharging operation of small distributed energy storage devices according to a command of the energy management system;
6 is a diagram showing the configuration of an aggregate resource management apparatus according to an embodiment of the present invention;
7 is a block diagram of a computing device according to an embodiment of the present invention;

Hereinafter, the embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are assigned the same reference numbers regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "part" for components used in the following description are given or mixed in consideration of only the ease of writing the specification, and do not have distinct meanings or roles by themselves. That is, the term 'unit' used in the present invention means a hardware component such as software, FPGA, or ASIC, and 'unit' performs certain roles. However, 'part' is not limited to software or hardware. The 'unit' may be configured to reside on an addressable storage medium or it may be configured to refresh one or more processors. Thus, as an example, 'part' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. Functions provided within components and 'units' may be combined into a smaller number of components and 'units' or further divided into additional components and 'units'.

In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical idea disclosed herein is not limited by the accompanying drawings, and all changes included in the spirit and scope of the present invention , should be understood to include equivalents or substitutes.

The present invention proposes a method and apparatus for configuring the small distributed resources as aggregate resources in consideration of the charge/discharge rate (C-rate) of the small distributed resources installed in a distribution network or a small power grid. In addition, the present invention proposes a method and apparatus for calculating an optimal operation command value for controlling the charging/discharging operation of small distributed resources based on the collective resource command value received from the upper-level energy management system (EMS). Hereinafter, the small distributed resource described in this specification refers to all types of energy storage devices including EV batteries.

Hereinafter, various embodiments of the present invention will be described in detail with reference to the drawings.

1 is a diagram illustrating a microgrid system utilizing aggregate resources based on small distributed resources related to the present invention.

Referring to FIG. 1 , the community-based microgrid system 100 includes photovoltaic power generation (photovoltaics, PV, 110), fuel cell (Fuel Cell, FC, 120), and energy storage system (Energy Storage System, ESS, 130). , an energy management system (EMS, 140) and an aggregator (AGG, 150). Here, the aggregator 150 is a kind of intermediary system (or intermediary platform), and includes one or more Aggregated Resource Management System (ARMS) 151 and customer owned ESS, CES, 153).

The fuel cell 120 and the energy storage device 130 of the microgrid system 100 are distributed resources owned by the power system operator, and the energy storage devices 153 of the aggregator 150 are owned by intermediaries or customers. It is a distributed resource that The microgrid system 100 may be operated in connection with the power system 50 , which is an upper system, or may be operated independently from the power system 50 .

The microgrid system 100 requires a large-capacity energy storage system (ESS) for energy independence, variability mitigation, and system contribution according to the increase of new and renewable energy sources. However, from the point of view of the power system operator, large-capacity energy storage device installation costs a lot of money, so it is necessary to reduce the initial investment and operation cost by sharing and renting the energy storage devices of customers dispersed in the consumers. Accordingly, the power system operator can use the microgrid system 100 by sharing and renting the energy storage devices 153 owned by customers.

A power system operator can utilize the aggregate resource by signing a fixed-cost contract with an intermediary operator for a small distributed ESS-based aggregate resource (ACES). An intermediary business operator may enter into a fixed cost contract with each owner for each energy storage device 153 and lend the energy storage device 153 to a power system operator. Accordingly, the power system operator can reduce the investment cost for the ESS by using the small distributed ESS, and the ESS owner can create additional revenue by lending the ESS during the unused time to the power system operator. On the other hand, when the bilateral contract between the power system operator and the intermediary service provider and the bilateral contract between the intermediary service provider and the ESS owners are completed, the power system operator uses the aggregator 150 to manage small distributed ESS-based aggregate resources in the microgrid system ( 100) can be built.

The energy management system 140 may perform overall energy management of the microgrid system 100 by utilizing a small distributed ESS-based aggregate resource (ACES) owned by customers. That is, the energy management system 140 may determine the operation mode of the microgrid system 100 , and may establish an optimal operation plan of the corresponding system 100 according to the determined operation mode. In this case, the energy management system 140 may derive the optimal operation plan of the microgrid system 100 in consideration of the aggregate resource information received from the aggregator 150 .

The energy management system 140 may derive the optimal operation schedule information of the distributed resource based on the optimal operation plan of the microgrid system 100 . In this case, the optimal operation schedule information of the distributed resource may include optimal operation schedule information on the small distributed ESS-based aggregate resource (ACES). In addition, the energy management system 140 may transmit the optimal operation schedule information (ie, the collective resource command value) on the aggregate resource to the aggregator 150 . A more detailed description of the energy management system 140 will be described later with reference to FIG. 2 .

The aggregator 150 configures the customer-owned energy storage devices (CES, 153) installed in the microgrid into one or more collective resource groups, and manages the energy of the configured collective resource group information (ie, collective resource information). A function of transmitting to the system 140 may be performed. In addition, the aggregator 150 may perform a function of individually controlling the charging/discharging operation of the small distributed energy storage devices 153 according to the operation command of the energy management system 140 . In this case, the operation of the aggregator 150 may be performed by one or more aggregate resource management devices 151 . Meanwhile, in this embodiment, the aggregator 150 exemplifies including the customer-owned small distributed energy storage devices (CES, 153), but is not necessarily limited thereto, and the aggregator 150 is an aggregate resource. It may be configured with only the management device 151 .

The collective resource management device 151 may transmit/receive CES-related data to/from the small distributed energy storage devices 153 owned by the customer. That is, the collective resource management device 151 may receive individual CES information from the small distributed energy storage devices 153 , and may transmit an individual CES command value to the small distributed energy storage devices 153 . Here, the individual CES command value means an operation command value for controlling the charge/discharge operation of the small distributed energy storage device 153 .

The collective resource management device 151 may transmit/receive aggregate resource related data to and from the energy management system 140 . That is, the collective resource management device 151 may transmit collective resource information representing the small distributed energy storage devices 153 as one virtual energy storage device to the energy management system 140 , and set the collective resource command value to the energy management system. It can be received from (140). Here, the collective resource command value means an operation command value for controlling the charge/discharge operation of the aggregate resource (ACES) representing the small distributed energy storage devices (153).

The microgrid system 100 having such a configuration may utilize the customer-owned small distributed energy storage devices for various purposes (eg, energy independence, volatility mitigation, system contribution, etc.) through the aggregator 150 . At this time, in order to operate the microgrid system using small distributed energy storage devices (CESs) from the perspective of the power system operator, the small distributed energy storage devices are configured as an aggregate resource (ACES) corresponding to one virtual energy storage device. The method is very important. In general, the aggregator 150 configures aggregate resources by giving representative capacity and representative rating when converting small distributed ESSs into aggregate resources, and the energy management system 140 considers only the representative capacity and representative rating of the aggregated resource into a microgrid. An optimal operating schedule for distributed resources of the system 100 is derived. However, the premise of such an energy management model is that the charge/discharge rates (C-rates) of all small distributed ESSs constituting the collective resource must be the same. However, most energy storage systems (ESS) have various charge/discharge rates (C-rate) according to battery characteristics. For this reason, it is difficult for the power system operator to directly utilize the small distributed ESS-based collective resources in the energy management model. Therefore, it is necessary to configure the aggregate resource in consideration of the fact that the charge/discharge rates (C-rates) of small distributed ESSs installed in the microgrid are different from each other.

FIG. 2 is a diagram referenced to explain a method for managing distributed resource energy of a microgrid system in the energy management system of FIG. 1 .

Referring to FIG. 2 , the energy management system (EMS, 140) related to the present invention predicts renewable output information and load information of the microgrid system 100, respectively, and based on the predicted information, the system 100 can determine the driving mode of In this case, the energy management system 140 may determine the operation mode of the corresponding system 100 in units of one day before one day.

The energy management system 140 may establish an optimal operation plan of the microgrid system 100 according to a predetermined operation mode using a distributed resource optimal operation model (algorithm). Here, the objective function (f) of the distributed resource optimal operation model aims to minimize energy cost, and can be defined as in Equation 1 below.

Here, w is the weight, and ESS charge/discharge loss cost is the sum of C.ESS charge/discharge loss cost and ACES charge/discharge loss cost.

Constraints of the optimal distributed resource operation model include FC output restrictions, C.ESS operation restrictions, ACES operation restrictions, power reception restrictions, supply and demand restrictions, and flexible power variability restrictions by time period.

The energy management system 140 satisfies the above-described objective function (f) based on renewable output prediction information, load prediction information, SMP (System Marginal Price) information, system parameter information, aggregate resource group information, and constraint condition information, etc. An optimal operation plan of the microgrid system 100 can be derived. Here, the aggregate resource group information refers to information about the small distributed ESS-based aggregate resources collected from the aggregator 150 .

The energy management system 140 may derive the optimal operation schedule information of the distributed resource in a predetermined time unit (eg, every 15 minutes) based on the optimal operation plan of the microgrid system 100 derived through the above-described process. have. In this case, the optimal operation schedule information of the distributed resource may include C.ESS optimal operation schedule information, C.FC optimal operation schedule information, and ACES optimal operation schedule information.

The energy management system 140 may transmit, to the aggregator 150 , ACES optimal operation schedule information (ie, aggregate resource command value) on the small distributed ESS-based aggregate resource upon completion of optimization and scheduling. The aggregator 150 may individually control the charging/discharging operations of the small distributed energy storage devices 153 constituting the aggregate resource based on the ACES optimal operation schedule information received from the energy management system 140 . .

Thereafter, the energy management system 140 may control the distributed resources of the microgrid system 100 in real time based on the distributed resource optimal operation schedule information, the system measurement information, and the distributed resource state information. As an example, the energy management system 140 may perform point of common coupling (PCC) reception power control, new and renewable detection, load blocking, and the like in real time.

As such, the energy management system 140 can stably operate the microgrid system 100 by utilizing the small distributed energy storage devices owned by the customer. Hereinafter, the aggregator 150 for collectively converting small distributed energy storage devices owned by the customer will be described in detail.

3 is a flowchart illustrating an operation of an apparatus for managing aggregate resources according to an embodiment of the present invention.

Referring to FIG. 3 , the collective resource management device (ARMS, 151) according to the present invention is a customer-owned small distributed energy storage device (153) installed in a power distribution network or a small power grid when a bilateral contract between an intermediary operator and an ESS owner is completed. ) on ACES contract information (or ESS contract information) may be obtained (S310). In this case, the ACES contract information may include information on contract battery capacity, battery efficiency, PCS (Power Conditioning System) capacity and rental cost (ie, fixed cost) of each energy storage device 153, and is not necessarily limited thereto. does not

The collective resource management device 151 may configure the small distributed energy storage devices (CES, 153) owned by the customer as an aggregate resource corresponding to one virtual energy storage device based on the ACES contract information (S330). That is, the collective resource management device 151 calculates information on at least one of representative efficiency, representative capacity, and representative rating of the virtual energy storage device based on the ACES contract information, and configures the collective resource based on the calculated information. can do.

First, the aggregate resource management device 151 may calculate the representative efficiency of the aggregate resource (ACES) based on the contract battery capacity and the information on the battery efficiency of the small distributed energy storage devices (153). As an example, the aggregate resource management apparatus 151 may calculate the representative efficiency of the aggregate resource using Equation 2 below. Here, the representative efficiency of the aggregate resource has a fixed value.

The aggregate resource management device 151 may calculate the representative capacity of the aggregate resource (ACES) based on the information on the contract battery capacity of the small distributed energy storage devices 153 . As an example, the aggregate resource management apparatus 151 may calculate the representative capacity of the aggregate resource using Equation 3 below. Similarly, the representative capacity of the aggregate resource has a fixed value.

The aggregate resource management device 151 may calculate the representative rating of the aggregate resource (ACES) based on the information on the contract battery capacity and the PCS capacity of the small distributed energy storage devices 153 . Here, the representative rating of the aggregate resource means a PCS capacity that varies according to the SOC of the aggregate resource, unlike the representative efficiency and representative capacity having fixed values. This is to take into account that, when the charge/discharge rates (C-rates) of the small distributed energy storage devices 153 constituting the aggregate resource are different from each other, the available PCS capacity may vary according to the SOC of the aggregate resource.

The collective resource management apparatus 151 may calculate the representative rating of the collective resource using a piecewise linear model. For example, FIG. 4 is a diagram referenced to explain a method of calculating a representative rating of an aggregate resource using a linear model of an interval. As shown in (a) of FIG. 4 , since the charge/discharge rates (C-rate) of general small distributed energy storage devices (CES) are different from each other, it is necessary to charge/discharge each small distributed energy storage device (CES). It can be seen that the time required is different. In the figure, CES _k _PCS means the maximum PCS output value of the k-th CES, and t _k means the maximum time during which the k-th CES can be charged or discharged with its own PCS capacity (CES _k _PCS).

On the other hand, in consideration of the fact that the charge/discharge rates (C-rate) of the small distributed energy storage devices (CES) are different from the perspective of the power system operator, a virtual collective resource representing the small distributed energy storage devices (CES) ( ACES) needs to be configured. Therefore, as shown in (b) of FIG. 4, it is necessary to define the PCS capacity according to the SOC point of the aggregate resource as the representative rating of the aggregate resource. In the drawing, ACES_PCS _k means the maximum PCS output value when the SOC of the aggregate resource is between BP _k-1 and BP _k , and BP (Break Point) _k is the maximum PCS output value of the aggregate resource (ACES_PCS _k ) changes. means the SOC point.

The aggregate resource management apparatus 151 may calculate the SOC point (BP _k ) of the aggregate resource using Equation 4 below, and may calculate the representative rating (ACES_PCS _k ) of the aggregate resource using Equation 5 below.

는 i번째 소형 분산 에너지저장장치(CES)의 PCS 용량이고,

는 i번째 소형 분산 에너지저장장치(CES)의 충/방전 최대 시간임.here,

is the PCS capacity of the i-th small distributed energy storage system (CES),

is the maximum charge/discharge time of the i-th small distributed energy storage system (CES).

The collective resource management apparatus 151 may transmit collective resource information including at least one of representative efficiency, representative capacity, and representative rating of the aggregate resource to the energy management system 140 of the upper system (S330). Then, the energy management system 140 may store the collective resource information received from the collective resource management device 151 in a memory or a database.

The collective resource management apparatus 151 may receive CES state information (or ESS state information) from the small distributed energy storage devices 153 owned by the customer (S340). In this case, the CES state information may include information on whether the batteries of the small distributed energy storage devices 153 are charging/discharging, the battery state of charge (SOC), the battery charging/discharging current, etc., but is not necessarily limited thereto. .

The aggregate resource management device 151 generates current state information of the aggregate resource (ACES) based on the CES state information received from the small distributed energy storage devices 153, and uses the generated current state information of the aggregate resource as energy. It can be transmitted to the management system 140 (S350). In this case, the current state information of the aggregate resource may include SOC information of the aggregate resource. The SOC value of the collective resource may be calculated by summing the SOC values of all energy storage devices 153 .

The energy management system 140, through the above-described optimization and scheduling process of the microgrid system 100, information about the aggregate resource received from the aggregate resource management device 151 (ie, aggregate resource information and aggregate resource status information) ), it is possible to calculate the optimal operation schedule information of the corresponding collective resource (S360). That is, from the perspective of the power system operator, it is possible to calculate the optimal operation schedule information of the distributed resource based only on the information on the aggregate resource without considering the state of the small distributed energy storage devices.

The energy management system 140 may transmit the optimal operation schedule information of the aggregate resource to the aggregate resource management apparatus 151 (S370). Here, the optimal operation schedule information of the aggregate resource may include an operation command value of the aggregate resource.

The collective resource management device 151 may calculate an individual CES command value for controlling the charge/discharge operation of the small distributed energy storage devices 153 based on the collective resource command value received from the energy management system 140 ( S380).

For example, as shown in FIG. 5 , the collective resource management device 151 may calculate individual CES command values for the small distributed energy storage devices 153 using a predetermined optimal command value distribution model (algorithm). . The objective function f of the optimal setpoint distribution model aims to minimize the difference between the sum of all CES setpoints and the collective resource setpoint, and can be defined as in Equation 6 below.

Here, Ref(t) is the collective resource command value of the energy management system at time t, and P _CES (i,t) is the charge/discharge amount of the i-th CES at time t.

), CES의 동시 충/방전 방지, SOC 상/하한 제약(

), SOC 갱신, 전체 스케줄링 기간 동안 각 CES의 충/방전량이 균등하도록 충/방전량 제약 등과 같은 ESS 운전 제약을 포함할 수 있다.On the other hand, the constraint of the optimal setpoint distribution model is the CES maximum charge/discharge (

), CES simultaneous charge/discharge prevention, SOC upper/lower limit restrictions (

), SOC update, and ESS operation constraints such as charge/discharge amount constraints so that the charge/discharge amount of each CES is equal during the entire scheduling period.

The collective resource management device 151 may calculate the individual CES command values of the small distributed energy storage devices 153 that satisfy the objective function and constraint condition of the above-described optimal distribution model of the command value.

The collective resource management device 151 may transmit the calculated CES command value to the small distributed energy storage devices 153 (S390). Each small distributed energy storage device 153 may perform a charge/discharge operation based on the CES command value received from the collective resource management device 151 .

As described above, the aggregate resource management apparatus 151 according to an embodiment of the present invention considers the charge/discharge rate (C-rate) of the small distributed ESSs installed in the power distribution network or the small power grid. can be configured as one virtual aggregate resource, and information about the configured aggregate resource can be provided to an energy management system (EMS) of an upper system. Accordingly, from the perspective of the power system operator, it is possible to reduce the investment cost of the ESS by using a small distributed ESS composed of collective resources, and from the point of the ESS owner, it is possible to create additional revenue by lending the ESS during the unused time to the power system operator. can

6 is a diagram showing the configuration of an aggregate resource management apparatus according to an embodiment of the present invention.

Referring to FIG. 6 , an apparatus for managing aggregate resources 600 according to an embodiment of the present invention may include an aggregate resource configuration unit 610 and a command value operation unit 620 . The components shown in FIG. 6 are not essential in implementing the apparatus 600 for collective resource management, so the apparatus for managing aggregate resources described herein may have more or fewer components than those listed above. have.

The collective resource configuration unit 610 may acquire ACES contract information (or ESS contract information) regarding the customer-owned small distributed energy storage devices 153 installed in a power distribution network or a small-scale power grid. In this case, the ACES contract information may include information on contract battery capacity, battery efficiency, PCS capacity, and rental cost (ie, fixed cost) of each energy storage device 153 .

The collective resource configuration unit 610 may configure the small distributed energy storage devices (CES, 153) owned by the customer as an aggregate resource corresponding to one virtual energy storage device based on the ACES contract information. That is, the collective resource configuration unit 610 calculates information about at least one of representative efficiency, representative capacity, and representative rating of the virtual energy storage device based on the ACES contract information, and configures the aggregate resource based on the calculated information. can do. Here, the representative efficiency, the representative capacity, and the representative rating of the aggregate resource may be derived through Equations 2 to 5 described above.

The aggregate resource configuration unit 610 may provide aggregate resource information including at least one of representative efficiency, representative capacity, and representative rating of the aggregate resource to the higher-level energy management system 140 .

The aggregate resource configuration unit 610 generates current state information of an aggregate resource (ACES) based on the CES state information (or ESS state information) received from the small distributed energy storage devices 153 , and the generated aggregate resource of the current state information may be transmitted to the energy management system 140 . Here, the CES state information may include information on whether the batteries of the small distributed energy storage devices 153 are charging/discharging, the battery SOC, and the battery charging/discharging current. In addition, the current state information of the aggregate resource may include SOC information of the aggregate resource.

The command value calculation unit 620 may calculate an individual CES command value for controlling the charging/discharging operation of the small distributed energy storage devices 153 based on the collective resource command value received from the energy management system 140 . In this case, the command value calculating unit 620 may calculate individual CES command values for the small distributed energy storage devices 153 using a predetermined optimal command value distribution model.

The command value calculating unit 620 may provide the calculated CES command value to the small distributed energy storage devices 153 . Accordingly, the command value calculating unit 620 may evenly distribute (allocate) the collective resource command value of the energy management system 140 to all the small distributed energy storage devices 153 .

7 is a block diagram of a computing device according to an embodiment of the present invention.

Referring to FIG. 7 , a computing device 700 according to an embodiment of the present invention includes at least one processor 710 , a computer-readable storage medium 720 , and a communication bus 730 . The computing device 700 may be one or more components included in the aggregate resource management apparatus 600 or the aggregate resource configuration unit 610 and the command value operation unit 620 constituting the aggregate resource management apparatus 600 described above. .

The processor 710 may cause the computing device 700 to operate according to the aforementioned exemplary embodiment. For example, the processor 710 may execute one or more programs 725 stored in the computer-readable storage medium 720 . The one or more programs may include one or more computer-executable instructions, which when executed by the processor 710 configure the computing device 700 to perform operations according to the exemplary embodiment. can be

Computer-readable storage medium 720 is configured to store computer-executable instructions or program code, program data, and/or other suitable form of information. The program 725 stored in the computer-readable storage medium 720 includes a set of instructions executable by the processor 710 . In one embodiment, computer-readable storage medium 720 includes memory (volatile memory, such as random access memory, non-volatile memory, or a suitable combination thereof), one or more magnetic disk storage devices, optical disk storage devices, flash It may be memory devices, other types of storage media accessed by the computing device 700 and capable of storing desired information, or a suitable combination thereof.

Communication bus 730 interconnects various other components of computing device 700 , including processor 710 and computer-readable storage medium 720 .

Computing device 700 may also include one or more input/output interfaces 740 and one or more network communication interfaces 760 that provide interfaces for one or more input/output devices 750 . The input/output interface 740 and the network communication interface 760 are coupled to the communication bus 730 .

The input/output device 750 may be connected to other components of the computing device 700 through the input/output interface 740 . Exemplary input/output device 750 may include a pointing device (such as a mouse or trackpad), a keyboard, a touch input device (such as a touchpad or touchscreen), a voice or sound input device, various types of sensor devices, and/or imaging devices. input devices and/or output devices such as display devices, printers, speakers and/or network cards. The exemplary input/output device 750 may be included in the computing device 700 as a component constituting the computing device 700 , and may be connected to the computing device 700 as a separate device distinct from the computing device 700 . may be

The present invention described above can be implemented as computer-readable codes on a medium in which a program is recorded. The computer-readable medium may continuously store a computer-executable program, or may be temporarily stored for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or several hardware combined, it is not limited to a medium directly connected to any computer system, and may exist distributedly on a network. Examples of the medium include a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and those configured to store program instructions, including ROM, RAM, flash memory, and the like. In addition, examples of other media may include recording media or storage media managed by an app store for distributing applications, sites supplying or distributing other various software, and servers. Accordingly, the above detailed description should not be construed as restrictive in all respects but as exemplary. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present invention are included in the scope of the present invention.

100: microgrid system 110: solar power
120: community fuel cell 130: community energy storage device
140: energy management system 150: aggregator
151: collective resource management device 153: small distributed energy storage device

Claims (12)

acquiring ESS contract information on customer-owned small distributed energy storage devices installed in a power distribution network or a small power grid;
Based on the obtained ESS contract information, the small distributed energy storage devices are configured as a collective resource corresponding to one virtual energy storage device, and information on at least one of representative efficiency, representative capacity, and representative rating of the configured collective resource detecting; and
and providing the aggregate resource information including the detected information to an energy management system of an upper system. According to claim 1,
The ESS contract information is a small distributed resource-based collective resource management method, characterized in that it includes information on contract battery capacity, battery efficiency, and PCS (Power Conditioning System) capacity of the small distributed energy storage devices. 3. The method of claim 2,
The representative efficiency of the collective resource is a small distributed resource-based collective resource management method, characterized in that it is calculated based on information on contract battery capacity and battery efficiency of the small distributed energy storage devices. 3. The method of claim 2,
The representative capacity of the collective resource is a small distributed resource-based collective resource management method, characterized in that calculated based on information on contract battery capacity of the small distributed energy storage devices. 3. The method of claim 2,
The representative rating of the collective resource is a small distributed resource-based collective resource management method, characterized in that it is calculated based on information about the contract battery capacity and PCS capacity of the small distributed energy storage devices. 3. The method of claim 2,
The representative rating of the aggregate resource is a PCS capacity that varies according to the SOC (State Of Charge) point of the aggregate resource, and is defined as the following equation.
[Equation]

here,

is the PCS capacity of the i-th small distributed energy storage device,

is the maximum charge/discharge time of the i-th small distributed energy storage system (CES). According to claim 1, wherein the detecting step,
A method for managing a collective resource based on a small distributed resource, characterized in that the representative rating of the collective resource is calculated using a piecewise linear model. According to claim 1,
Generating the current SOC information of the aggregate resource based on the ESS state information received from the small distributed energy storage devices, and transmitting the current SOC information of the generated aggregate resource to the energy management system Distributed resource-based collective resource management method. According to claim 1,
calculating individual CES command values for controlling charging/discharging operations of the small distributed energy storage devices based on the collective resource command values received from the energy management system; and
and providing the calculated individual CES command values to the small distributed energy storage devices. 10. The method of claim 9, wherein the calculating step,
A method for managing aggregated resources based on small distributed resources, characterized in that the individual CES command values of the small distributed energy storage devices are calculated using a setpoint optimal distribution model having a predetermined objective function and constraint conditions. A computer program stored in a computer-readable recording medium so that the method according to any one of claims 1 to 10 can be executed on a computer. Based on the ESS contract information on the customer-owned small distributed energy storage devices installed in the power distribution network or small power grid, the small distributed energy storage devices are configured as a collective resource corresponding to one virtual energy storage device, and the configured collective resource an aggregate resource configuration unit that detects information on at least one of representative efficiency, representative capacity, and representative rating of , and provides aggregate resource information including the detected information to an energy management system of an upper system; and
Based on the collective resource command value received from the energy management system, an individual CES command value for controlling the charging/discharging operation of the small distributed energy storage devices is calculated, and the calculated individual CES command values are transmitted to the small distributed energy storage devices. A small distributed resource-based collective resource management device including a setpoint calculating unit to provide.

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