KR102396712B1 - Energy management system and method for minimizing the power purchase cost of microgrid using the same - Google Patents

Abstract

As a method for the energy management system to calculate the power purchase cost of the microgrid, a first amount of power to be generated by an energy generating device constituting the microgrid is predicted, and a second amount of power to be used by a load constituting the microgrid is predicted. And when the power shortage in the microgrid is predicted based on the predicted first and second power amounts, the minimum power purchase cost to purchase from the main grid that provides power to the microgrid or the adjacent microgrid adjacent to the microgrid is calculated.

Description

Energy management system and method for minimizing the power purchase cost of microgrid using the same}

The present invention relates to an energy management system for minimizing power purchase cost of a microgrid and a method for determining power purchase cost using the same.

Recently, with the supply and spread of new and renewable energy in industrial complexes and residential complexes, small-scale electric power communities that can be self-sufficient in electric power such as micro grids are being built. At this time, the power generated by the renewable energy generating device constituting the microgrid is not produced in a certain amount depending on the situation.

Therefore, it is necessary to be able to monitor and control renewable energy generators and energy storage devices so that power can be stably supplied within the microgrid. Nevertheless, if it is difficult to meet the electricity demand by the microgrid itself by predicting the amount of power generation and demand within the microgrid, electricity must be purchased through a utility (eg, Korea Electric Power Corporation) or an adjacent microgrid.

Economic dispatch or generator operation plan through minimizing power generation cost using traditional fossil energy has been established academically. And, based on this, an actual system is implemented and operated.

An ideal microgrid has renewable energy facilities and energy storage devices, so that electricity can be generated and consumed within the microgrid. However, there are many cases in which the production of renewable energy is affected by the environment such as the weather, and the energy storage device does not have sufficient capacity, so it is often not possible to store energy sufficiently.

Therefore, insufficient power must be supplied either from the main grid (eg, the utility's power grid) or from an adjacent microgrid. However, there are disadvantages in that it is difficult to predict how much insufficient power should be supplied from the main grid or an adjacent microgrid, and what the minimum power purchase cost to stably supply the supplied power is.

Accordingly, the present invention provides an energy management system capable of minimizing the cost of power purchase and a method of determining the cost of power purchase using the same, in order to prepare for a case where a microgrid needs to purchase power from the outside, such as a main grid or an adjacent microgrid. do.

The present invention relates to an energy management system for minimizing power purchase cost of a microgrid and a method for determining power purchase cost using the same.

The energy management system for managing the energy of the microgrid is a reference information generation module for generating reference information for calculating the electricity purchase cost of the microgrid, and based on the reference information An optimization module for optimizing the affected demand response cost, and a calculation module for calculating the minimum power purchase cost for the microgrid to purchase from the outside based on the optimized power purchase amount and demand response cost, and the reference information, , the energy management system interworks with the main grid that supplies electric power from the outside to the microgrid and adjacent microgrids.

According to an embodiment, the microgrid includes an energy generating device generating power inside the microgrid, a load consuming the power generated inside the microgrid and the power supplied from the outside, and the power generated inside the microgrid. It may include an energy storage device for storing the remaining power consumed by the load.

According to an embodiment, the reference information generation module may include an energy output prediction module that predicts an amount of power output to be generated during a preset period by the energy generation device.

According to an embodiment of the present disclosure, the reference information generating module may further include a load usage prediction module for estimating an expected amount of power to be used in the future based on the amount of power currently used by the load.

According to an embodiment, the reference information generating module further comprises a microgrid measurement module for measuring a power usage pattern in the microgrid, wherein the power usage pattern includes a power usage used in the microgrid, a current time, In addition, the power operation information corresponding to the current time may be included among the previously set and stored power operation information in the microgrid.

According to an embodiment, the reference information generating module may further include a demand response planning module for confirming load reduction plan information scheduled in the microgrid.

According to an embodiment, the calculation module determines the power purchase period, purchase amount, and purchase timing so that a purchase cost to purchase power from the main grid, a purchase cost to purchase power from the adjacent microgrids, or a demand response cost are minimized. can

The method for the energy management system to calculate the power purchase cost of the microgrid includes predicting a first amount of power to be generated by an energy generating device constituting the microgrid, and predicting a second amount of power to be used in a load constituting the microgrid step, and when the power shortage in the microgrid is predicted based on the predicted first and second power amounts, the minimum power purchase cost to be purchased from the main grid providing power to the microgrid or a microgrid adjacent to the microgrid including calculating

According to an embodiment, the calculating of the minimum power purchase cost may include a power purchase cost to be purchased from the main grid at any time, a power purchase cost to be purchased from the adjacent microgrid at the arbitrary time, and the arbitrary time. A value obtained by adding a cost for demand response in the microgrid to the minimum value may be determined as the minimum power purchase cost.

According to an embodiment, the estimating of the second amount of power further includes measuring the power usage pattern of the microgrid, wherein the power usage pattern includes the power usage being used in the microgrid, the current time, In addition, the power operation information corresponding to the current time may be included among the previously set and stored power operation information in the microgrid.

According to an embodiment, predicting the second amount of power may further include checking information on a load reduction plan scheduled in the microgrid.

According to the present invention, energy in the microgrid can be stably operated, and insufficient energy can be economically purchased through a utility or an adjacent microgrid.

In addition, load reduction according to demand response can also be achieved.

In addition, it is possible to minimize the microgrid operating cost by minimizing the electricity purchase cost and the demand response cost based on the optimization method.

1 is an exemplary diagram of a microgrid system according to an embodiment of the present invention.
2 is a structural diagram of an energy management system according to an embodiment of the present invention.
3 is a flowchart of a method for determining a power purchase cost according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art to which the present invention pertains can easily implement them. However, the present invention may be embodied in several different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part "includes" a certain element, it means that other elements may be further included, rather than excluding other elements, unless otherwise stated.

Hereinafter, an energy management system and method for minimizing the power purchase cost of a microgrid according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is an exemplary diagram of a microgrid system according to an embodiment of the present invention.

As shown in FIG. 1 , the microgrid 100 is a new and renewable energy generating device 10 that generates power through renewable energy such as sunlight and wind power, and the power generated by the new and renewable energy generating device 10 . It is composed of an energy storage device 20 for storing, and a load 30 for consuming power.

Power generated by the renewable energy generating device 10 is provided to the load 30 to be consumed by the load 30 , and the remaining power is stored in the energy storage device 20 . The power stored in the energy storage device 20 may supply power to the load 30 when the renewable energy generating device 10 fails to produce power.

At this time, the microgrid 100 is a main grid (or, also referred to as a 'utility') 200 that supplies power to the load 30 due to the uncertainty of the renewable energy output, or an adjacent microgrid (hereinafter, 'adjacent') Insufficient power may be supplied from the 'microgrid') 300 .

For the stable power supply/consumption operation of the microgrid and the purchase of power from the outside, the amount of power generation and demand for renewable energy must be predicted in advance. This is predicted by the energy management system 400 linked with the microgrid 100 .

The energy management system 400 can manage to stably supply power to the load 30 using the energy storage device 20 while minimizing the power purchase cost for a certain period based on the predicted power generation and demand information. there is.

The energy management system 400 calculates the sum of the real-time electricity rates of the main grid 200 and the adjacent microgrid 300, which are direct power purchases, and the cost for DR: Demand Response (DR) in the load 30 . It is possible to minimize the cost of electricity purchase through an optimization technique that minimizes it.

The power demand response is when the demand for power from the load 30 increases, the consumer responds to reduce power use. The number of consumers, that is, the number of loads 30 is large, and it is very difficult to individually adjust a large number of loads 30 . Therefore, it is not an exaggeration to say that there is no method other than a planned power outage that the power grid operator can adjust to the current power system.

In particular, with a simple electricity rate system, there is no incentive for consumers to voluntarily respond. Accordingly, in the United States and Europe, more active demand response services are being applied through a method in which a power grid operator provides a strong compensation for a demand response while generating a basic demand response based on various rate plans, and furthermore, through sales in the market.

In an embodiment of the present invention, the energy management system 400 may model the demand response within the microgrid 100 like a virtual power plant. Therefore, an optimization technique that minimizes the cost of the virtual generator can be applied.

The structure of the energy management system 400 in such an environment will be described with reference to FIG. 2 .

2 is a structural diagram of an energy management system according to an embodiment of the present invention.

As shown in FIG. 2 , the energy management system 400 calculates the purchase cost based on the reference information generation module 410 that generates reference information provided when calculating the electricity purchase cost, and the reference information, for a certain period of time. and an optimization module 420 for optimizing the power purchase amount and the demand response cost affected therewith, and a calculation module 430 for calculating the power purchase cost of the microgrid based on the optimized information.

The reference information generation module 410 includes a renewable energy output prediction module 411 , a load usage prediction module 412 , a microgrid measurement module 413 , and a demand response planning module 414 .

The renewable energy output prediction module 411 predicts the amount of the renewable energy output output from the renewable energy generating device 10 . In an embodiment of the present invention, prediction of the output of power using sunlight among various renewable energies will be described as an example.

Renewable energy output prediction module 411 interlocks with the new and renewable energy generating device 10, which is a solar power generation facility, and provides facility information such as the installation location, capacity, azimuth, and elevation angle of the new and renewable energy generating device 10 collect In addition, the renewable energy output prediction module 411 is a specific server (eg, weather information providing server, etc.) (drawing, not shown) of environmental information such as the position of the sun, amount of sunlight, sunrise time, and sunset time by time period. receive from

The renewable energy output prediction module 411 predicts the amount of power output of the renewable energy to be output from the renewable energy generating device 10 based on the facility information and the environment information. There are various methods for the renewable energy output prediction module 411 to predict the amount of power output with facility information and environmental information, and since the information used for prediction is also various, the embodiment of the present invention is not limited to any one method and information. does not

The load usage prediction module 412 interworks with the load 30 to predict an expected power usage amount of the load to be used in the load 30 in the future based on the amount of power being used by the load 30 . Alternatively, based on the power usage information used by the load 30 in the past, the expected power usage amount may be predicted.

Power consumption can be predicted by a power load prediction method using an artificial neural network. Specifically, a pattern for each day of the week is derived by using the history information of the power consumption. A correlation analysis is performed between the daily pattern of power consumption and the surrounding environment information (temperature, wind speed, humidity, dew point, season information). In this case, the Pearson correlation coefficient may be used. It is possible to derive a learning model (learning model for each day of the week) using the Inkyung New Network as input data with the influence of each environmental information and history information, and make predictions based on the learning model.

Since the method of the load usage prediction module 412 estimating the strategic usage amount of the load may be executed in various ways, the embodiment of the present invention is not limited to any one method.

The microgrid measurement module 413 measures the power usage pattern in the current microgrid. Here, the power usage pattern includes power usage used in the microgrid, the current time, and power operation information corresponding to the current time among power operation information preset and stored in the microgrid.

Also, the microgrid measurement module 413 checks the power usage patterns of other adjacent microgrids located in the periphery of the microgrid. In the embodiment of the present invention, although the description is given by taking as an example that the power operation information set in the microgrid is stored in the microgrid measurement module 413, it may be received from an external information storage means.

The demand response planning module 414 checks the load reduction plan information scheduled in the microgrid. Here, the load reduction plan information includes a load reduction time point and reduction amount information at the corresponding time point. To this end, in the embodiment of the present invention, storing and managing the load reduction plan information of all microgrids in the demand response planning module 414 is described as an example, but the load reduction planning module installed in the microgrid (not shown in the drawing) ) can also be received from

The energy management system 400 manages the total power consumption of the microgrid 100, and in the upper EMS (Ex. KPX in Korea, the Korea Power Exchange, not indicated in this patent), the power generation amount of the entire grid (a domestic example, a nationwide system) If the demand for electricity is high, plan to reduce the demand. In the case of summer when peak power use occurs, power is provided to contracted demand response customers (demand response customers, i.e. customers performing power reduction, in this patent, a microgrid operated as an energy management system) to reduce power consumption during peak hours. A reduction target is indicated. The transfer is the total amount of electricity that the customer needs to reduce, and the customer decides what kind of load to reduce in detail at the time (peak time), whether it is possible to save, and the reduction schedule for each detailed load. The demand response planning module selects a load for demand reduction in the microgrid, determines the amount of reduction by load, and the schedule (reduction time and reduction by load) to achieve the target of power reduction required by the upper energy management system. carry out

Demand response has a problem in that it is difficult to limit only the economics of MG. If demand response is performed, it is beneficial for the entire grid to reduce the operation of the corresponding generator. In other words, the minimization of the demand response cost is the same as the minimization of the grid power generation cost. It can be seen as a minimization of MG's externally purchased power and minimization of power generation costs from the grid's point of view.

The optimization module 420 receives the reference information generated by the reference information generation module 410 as an input. And, in order to minimize the operating cost of the microgrid for a predetermined operating period not at a specific point in time, and to minimize the cost of power purchase from the outside and the cost according to the demand response of the load, it is received from the reference information generating module 410 Among the reference information, the amount of power purchased from the outside (eg, the main grid or adjacent microgrid) for a certain period of time and the demand response cost affected by the purchased power are optimized.

The optimization module 420 determines the optimization time for demand response and the amount of power reduction, and determines the amount of electricity purchased outside the corresponding time period (total purchase amount, whether to purchase from a utility or to be purchased from an adjacent microgrid). Demand response cost is the cost of loss for the act of forcibly reducing power consumption in response to a demand measurement request while the load is being used in the microgrid. A cost optimization technique using a linear program (LP) and/or an optimization technique based on a linear condition of a linear function (objective function) may be applied.

When the planned (current) future demand response (power reduction) of time t is performed on the microgrid (#1), the economic cost of performing the demand response, the cost of power purchase from an external utility, and the external microgrid (#2) ), it is necessary to predict the amount of renewable power generation and load in time t (future) to calculate the cost of purchasing electricity. Because these two are unknown numbers that are not planned, predictions are necessary. Load and regeneration prediction methods are diverse, and artificial neural networks, regression analysis, and learning prediction using ARIMA statistical models can be used.

The optimization module 420 uses an optimization technique to optimize the purchased power purchase amount and the demand response cost. Here, as the optimization technique, any one of various techniques used in the power system may be used, and the embodiment of the present invention is not limited to a specific technique.

The calculation module 430 derives the power purchase amount and power supply period from the external/microgrid for each time point of a certain period based on the result optimized by the optimization module 420 . Here, the calculation module 430 minimizes the purchase cost by using a purchase cost minimization algorithm.

The calculation module 430 optimizes the external power purchase amount for each time period determined by the optimization module. Optimize whether to purchase electricity from the utility and the adjacent microgrid by time period (the cost of purchasing electricity for the utility and the adjacent microgrid is different for each time period). The forecast of renewable generation and load by time in the future may not be 100% consistent. The error is checked using the predicted values of renewable energy and load derived from the prediction unit and the values measured in real time using the microgrid measurement module unit, and the planned optimal demand response is maintained. The recalculation of the purchase amount and the determination of the external purchase of the calculator are performed in real time, and calculation and correction of the external power purchase place and purchase amount for each time period are performed.

Minimization of purchase cost means to minimize the cost of external power purchase for a certain period in order to prepare for the case where power in the microgrid 100 is insufficient and power must be purchased from the main grid 200 and the adjacent microgrid 300 means to do In order to minimize the purchase cost, the calculation module 430 has equality and inequality constraints. A function defining the constraint conditions will be described with reference to the following equation.

Equation 1 is a function defined by the power purchase decision module 430 in order to minimize the cost of the microgrid, and Equations 2 to 11 are the energy consumption of resource elements in the microgrid, SOC (Social Overhead Capital), cost, etc. It is a function that defines the constraint of .

Variables of functions corresponding to each of the above-defined equations can be defined as shown in Table 1 below.

variable meaning

Unit kW electricity purchase cost at time t from utility u [KRW/kW]

Cost of purchasing unit kWh electricity purchased at time t from external microd m [KRW/kW]

Amount of electricity supplied by utility u into the microgrid at time t [kW]

The amount of electricity supplied by the external microgrid m into the microgrid at time t [kW]

Maximum amount of electricity that utility u can supply within the microgrid at time t [kW]

Maximum amount of power that the external microgrid m can supply within the microgrid at time t [kW]

The amount of electricity that the energy storage device charges at time t [kW]

The minimum amount of charge that the energy storage device can charge per unit time [kW]

The maximum amount of charge that the energy storage device can charge per unit time [kW]

The amount of power discharged by the energy storage device at time t [kW]

The minimum amount of charge that the energy storage device can discharge per unit time [kW]

The maximum amount of charge that the energy storage device can discharge per unit time [kW]

The amount of energy at time t of the energy storage device

Minimum charge amount of energy storage device [kW]

Maximum charge amount of energy storage device [kW]

Energy storage device charging efficiency [%]

Discharge efficiency of energy storage device [%]

unit time (t - (t-1))

Electricity generated by renewable energy at time t [kW]

The amount of power consumed by the load at time t [kW] (meaning the amount of load before DR is reflected)

Cost function for DR in microgrid at time t [won]

Load reduction by DR in microgrid at time t [kW]

Pre-specified ratio of nominal load

Constant term of a linear function that determines the amount of power consumed versus price

The slope coefficient of the linear function that determines the amount of power consumed with respect to price

Marginal cost that determines power consumption

A method of managing energy in the microgrid using the energy management system 400 described above to minimize power purchase cost will be described with reference to FIG. 3 .

3 is a flowchart of a method for determining a power purchase cost according to an embodiment of the present invention.

As shown in FIG. 3 , the energy management system 400 predicts the degree of renewable energy output to be output from the renewable energy generating device 10 in the microgrid ( S100 ). If the renewable energy generating device 10 is a photovoltaic facility, the energy management system 400 provides not only facility information such as the location where the renewable energy generating device 10 is installed, output capacity, etc., but also Based on environmental information (eg, the position of the sun for each time period, amount of sunlight, sunrise time, sunset time, etc.), the degree of renewable energy output of the day is predicted.

Here, since there are various methods for the energy management system 400 to predict the level of new and renewable energy output on the day using facility information and environmental information, the embodiment of the present invention is not limited to any one method. In addition, in the embodiment of the present invention, it is described as an example of predicting the level of renewable energy output for the day, but it is also possible to predict the level of renewable energy output for a certain period of time.

After predicting the degree of renewable energy output, the energy management system 400 predicts the expected amount of power use of the load to be used in the load 30 in the future based on the amount of power being used by the load 30 in the microgrid (S110). Alternatively, based on the power usage information used by the load 30 in the past, the expected power usage amount may be predicted.

The energy management system 400 collects power usage patterns of other adjacent microgrids located in the vicinity along with the current power usage patterns in the microgrid (S120). Here, the power usage pattern includes power usage used in the microgrid, the current time, and power operation information corresponding to the current time among power operation information preset and stored in the microgrid.

The energy management system 400 checks the load reduction plan information scheduled in the microgrid (S130). Here, the load reduction plan information includes a load reduction time point and reduction amount information at the corresponding time point.

The energy management system 400 optimizes the power purchase amount and demand response cost among the renewable energy output prediction information, the power usage prediction information in the load, the microgrid measurement information and the demand response information collected through steps S100 to S130. is used to optimize (S140). That is, based on the renewable energy output prediction information predicted in step S100 and the power usage prediction information in the load predicted in step S110, it is predicted whether there is a power shortage in the microgrid.

If it is predicted that the power will be insufficient, the energy management system 400 calculates the power purchase cost of the microgrid using the optimized power purchase amount and demand response cost (S150). When calculating the power purchase cost in step S150, the energy management system 400 calculates using a purchase cost minimization algorithm.

),인접 마이크로그리드로부터 상기 임의의 시각에 구매할 전력 구매 비용(

), 그리고 시간 t에 마이크로그리드 내 수요 반응에 대한 비용 함수(

)의 합이 최소가 되도록(

) 전력 구매 비용을 계산한다.That is, the energy management system 400 is the power purchase cost (

), the cost of purchasing electricity from the adjacent microgrid at any time above (

), and the cost function for the demand response in the microgrid at time t (

) so that the sum of (

) to calculate the cost of purchasing electricity.

In addition, the energy management system 400 may also determine a power purchase strategy for the microgrid based on the calculated power purchase cost. Here, the power purchase strategy refers to how much power purchase amount and for how long time period after which point in time to purchase power.

In this way, when the power purchase cost is determined using the energy management system 400 , energy in the microgrid can be stably operated, and insufficient energy can be economically purchased through the main grid or an adjacent microgrid.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto. is within the scope of the right.

400: energy management system
410: reference information generation module
420: optimization module
430: calculation module

Claims (11)

As an energy management system for managing the energy of the microgrid,
a reference information generation module for generating reference information for calculating the power purchase cost of the microgrid;
an optimization module for optimizing the amount of electricity purchased for a certain period based on the reference information and the demand response cost affected by the amount of electricity purchased; and
A calculation module for calculating the minimum power purchase cost for the microgrid to purchase from the outside based on the optimized power purchase amount and demand response cost, and the reference information
including,
The energy management system interworks with a main grid that supplies power from the outside to the microgrid and adjacent microgrids,
The reference information generation module,
Including a demand response planning module to check the load reduction plan information scheduled in the microgrid,
The load reduction plan information includes selection of a load for demand reduction in the microgrid, a reduction amount for each load, and reduction amount information at the time of reduction of the selected load and the time of reduction,
The demand response planning module is

Select a load for demand reduction under the constraint of do,
Here, P _DER,t is the amount of power of renewable energy generated by the microgrid at time t, P _u,t is the amount of power supplied by the utility u corresponding to the main grid into the microgrid at time t, P _{m , t} is the amount of power supplied to the microgrid by the external adjacent microgrid m at time t, P _t ^d is the amount of power discharged by the energy storage device of the microgrid at time t, and ΔD _t is the amount of power supplied to the microgrid at time t is the amount of load reduction due to a demand response (DR) in the grid, Lt is the amount of power consumed by the load at time t, and P _t ^c is the amount of power that the energy storage device charges at time t energy management system. According to claim 1,
The microgrid is
an energy generating device for generating electric power within the microgrid;
A load that consumes the power generated inside and the power supplied from the outside, and
An energy storage device for storing power remaining after being consumed by the load among the power generated inside
An energy management system comprising a. 3. The method of claim 2,
The reference information generation module,
an energy output prediction module for predicting the amount of power output to be generated during a preset period in the energy generating device;
An energy management system further comprising a. 4. The method of claim 3,
The reference information generation module,
A load usage prediction module for predicting an expected amount of power to be used in the future based on the amount of power currently used by the load;
An energy management system further comprising a. 5. The method of claim 4,
The reference information generation module,
Microgrid measurement module for measuring the power usage pattern in the microgrid
further comprising,
The power usage pattern is an energy management system including power usage used in the microgrid, a current time, and power operation information corresponding to the current time among power operation information preset and stored in the microgrid. 5. The method of claim 4,
The reference information generation module,
A new and renewable energy output prediction module that predicts and derives renewable power generation by time in the future; and
Further comprising a microgrid measurement module for measuring the power usage pattern in the microgrid,
The calculation module is
determining power to be purchased from the utility and adjacent microgrids for each time period determined by the optimization module;
If the predicted value of the load derived from the renewable power generation and the load usage prediction module derived from the renewable energy output prediction module matches the measured value measured in real time by the microgrid measurement module, the power demand response is maintained, and the When an error occurs between the predicted value and the measured value, the energy management system performs calculation and correction of the external power purchase place and purchase amount for each time period. According to claim 1,
The calculation module is
An energy management system for determining a purchase period, purchase amount and purchase timing so that a purchase cost to purchase power from the main grid, a purchase cost to purchase power from the adjacent microgrids, or a demand response cost are minimized. A method for an energy management system to calculate the cost of purchasing electricity for a microgrid, the method comprising:
Predicting the first amount of power to be generated by the energy generating device constituting the microgrid;
Predicting a second amount of power to be used in a load constituting the microgrid, and
When the power shortage in the microgrid is predicted based on the predicted first and second power amounts, calculating the minimum power purchase cost to purchase from the main grid that provides power to the microgrid or an adjacent microgrid adjacent to the microgrid step
including,
The step of predicting the second amount of power,
checking information on a load reduction plan scheduled in the microgrid; and

Select a load for demand reduction in the microgrid included in the load reduction plan information under the constraint of Including the step of achieving the power reduction target required by the management system,
Here, P _DER,t is the amount of power of renewable energy generated by the microgrid at time t, P _u,t is the amount of power supplied by the utility u corresponding to the main grid into the microgrid at time t, P _{m , t} is the amount of power supplied to the microgrid by the external adjacent microgrid m at time t, P _t ^d is the amount of power discharged by the energy storage device of the microgrid at time t, and ΔD _t is the amount of power supplied to the microgrid at time t is the amount of load reduction due to a demand response (DR) in the grid, Lt is the amount of power consumed by the load at time t, and P _t ^c is the amount of power that the energy storage device charges at time t How to calculate the cost of purchasing electricity. 9. The method of claim 8,
Calculating the minimum power purchase cost comprises:
The sum of the cost of purchasing electricity from the main grid at any time, the cost of purchasing electricity from the adjacent microgrid at the arbitrary time, and the cost for demand response in the microgrid at the arbitrary time is the minimum A method of calculating the cost of purchasing power, wherein a value is determined as the minimum cost of purchasing power. 9. The method of claim 8,
The step of predicting the second amount of power,
Measuring the power usage pattern of the microgrid
further comprising,
The power usage pattern is a power purchase cost calculation method including power usage used in the microgrid, the current time, and power operation information corresponding to the current time among the power operation information preset and stored in the microgrid . 9. The method of claim 8,
The step of predicting the first amount of power,
Includes a step of predicting new and renewable energy output by predicting and deriving new and renewable power generation and load by time in the future,
Predicting the second amount of power,
A microgrid measurement step of measuring the power usage pattern in the microgrid,
Calculating the minimum power purchase cost comprises:
determining the power to be purchased from the utility and the adjacent microgrid for each time period determined by the optimization module;
If the predicted value of the renewable power generation and load derived in the renewable energy output prediction step matches the measured value measured in real time in the microgrid measurement step, the power demand response is maintained, and the error between the predicted value and the measured value is When it occurs, a power purchase cost calculation method that performs calculation corrections for external power purchase locations and purchase amounts by time period.

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