KR20180103516A - Operating system for energy storage device based on korean type power charges and method thereof - Google Patents

Abstract

A method for operating an energy storage device to reduce power charges in a Korean type power charge system environment according to an embodiment of the present invention includes the steps of: estimating a peak value of demand power for a current month based on past power usage data for predetermined weeks; comparing a predicted peak value of the demand power of the current month with a cumulative peak value of the past months; calculating a charging and discharging ratio for controlling the operation of the energy storage device according to a comparison between the predicted peak value of the demand power of the current month and the cumulative peak value of the past months; and operating the energy storage device to reduce a peak load of the next day according to the calculated charging and discharging ratio.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an energy storage device,

The present invention relates to a method and system for operating an energy storage device based on a Korean electric power charge plan, and more particularly, to a method and system for operating an energy storage device based on a Korean electric power charge plan, And more particularly, to a method and system for operating an energy storage device based on a Korean power bill, which can reduce a peak value of an actual power load pattern and a total electric power charge rate by controlling a charging / discharging operation of the energy storage device.

Energy storage devices are being used to supplement power to electronic equipment to reduce the maximum power consumption of a consumer.

In other countries, it is expected that the actual electricity rate will have the effect of reducing the overall charge rate because it includes the time to reduce the peak load.

However, in case of the domestic power plan, since the power charge is determined according to the maximum peak load in the immediately preceding 12 months, the method of operating the energy storage device considering only the predicted data of the conventional power, Is difficult.

In the same way, existing researches that form a single customer or a large number of customers into a single group and reduce the electricity charge through the energy storage device do not reflect the actual power pattern, It is a situation.

Korean Registered Patent No. 10-1281309 (March 16, 2012, entitled " Power Storage Device Scheduling Apparatus and Method ")

A problem to be solved by the present invention is to provide a technical means for operating an energy storage device in a Korean power plan environment in which the peak value of the actual power load pattern and the total power charge can be reduced through appropriate operation of the energy storage device .

 A method of operating an energy storage device for reducing power charges in a Korean power plan environment according to an embodiment of the present invention includes estimating a peak value of demand power of the current month based on past power usage data for a predetermined week Comparing the predicted peak value of the current demand power with the accumulated peak value of the past several months and comparing the estimated peak value of the current demand power with the cumulative peak value of the past several months, Calculating a charge / discharge ratio for controlling the charge / discharge ratio, and operating an energy storage device for reducing the peak load of the child according to the calculated charge / discharge ratio.

According to the embodiment of the present invention, when the predicted peak value of the current month's demand power is close to the cumulative peak value within the threshold water level, the prediction cost for the current day's charge calculated at the same time as the peak price of the same day is minimized And calculating a charge / discharge ratio for driving the energy storage device of the child from the calculation of the objective function.

In addition, according to an embodiment of the present invention, the charge / discharge ratio, which means the variation of the energy state of the energy storage device, can be calculated from the experimentally calculated range .

According to an embodiment of the present invention, there is provided a method for controlling an energy storage device, the method comprising: updating a battery charge, a charge for each charge and a daily peak value through operation of the energy storage device; Charging and discharging drive of the battery, and calculating the monthly charge based on the daily battery consumption cost, calculating the base charge based on the accumulated peak value for one month by the update, .

According to an embodiment of the present invention, when the predicted peak value of the current month's demand power is not close to the cumulative peak value within the critical water level, the charge / discharge operation of the energy storage device The charge / discharge ratio of the energy storage device is calculated by taking into consideration only the predicted cost of the charge of the child by charge, except for consideration of the electric power load.

According to an embodiment of the present invention, when the predicted peak value of the current month's demand power is not close to the cumulative peak value within the threshold water level, Value.

Further, according to the embodiment of the present invention, the predicted cost for the charge of the child by the time of day is calculated according to the predicted load every hour and the standardized charge / discharge ratio of the energy storage device.

According to an embodiment of the present invention, the step of comparing the predicted peak value of the current month's demand power with the cumulative peak value of the past several months includes a step of comparing the demanded electric power of the current month And the cumulative peak value of the winter and summer in the immediately preceding 12 month.

A system for operating an energy storage device for reducing electric power charges in a Korean type electric power plan environment according to another embodiment of the present invention estimates a peak value of demand electric power for the current month based on past electric power usage data for a predetermined week A comparison and analysis unit for comparing the predicted peak value of the demand power of the current month with the accumulated peak value of the past months, and a charge / discharge ratio of the energy storage device for reducing the peak load of the child according to the result of the comparison. And a control processor for controlling the operation of the energy storage device according to the calculated charge / discharge ratio.

The charging / discharging ratio calculating unit according to the embodiment of the present invention may further include a charging / discharging ratio calculating unit for calculating the charging / discharging ratio of the energy storage device for operating the energy storage device to reduce the peak load when the predicted peak value of the current month's demand power is close to the cumulative peak value, And the charge / discharge ratio is calculated.

The charging / discharging ratio calculating unit may calculate an objective function for minimizing a predicted cost for a charge of each day of the day considered simultaneously with a peak charge of the same day for operating the energy storage device according to an embodiment of the present invention, From the calculation of the objective function, a charging / discharging ratio for driving the energy storage device of the child.

The charging / discharging ratio calculating unit according to the embodiment of the present invention calculates the charging / discharging ratio of the energy storage device by applying an experimentally calculated range to reduce the total power charge with respect to the error of the predicted load according to the time of the day do.

In addition, the control processor according to an embodiment of the present invention updates the battery charge, the charge for each charge and the daily peak value through the operation of the energy storage device, and updates the energy peak value of the energy storage device Charge / discharge drive of the battery.

Further, the control processor according to an embodiment of the present invention calculates the base rate based on the peak value accumulated for one month by the update, adds the base rate to the charge for each time, calculates the monthly electric power charge considering the daily battery consumption cost, do.

The charging / discharging ratio calculating unit according to the embodiment of the present invention controls the charging / discharging operation of the energy storage device of the awning when the predicted peak value of the current month's demand power is not close to the cumulative peak value within the threshold water level The charging / discharging ratio of the energy storage device is calculated by taking into account only the predicted cost of charge for each child's time, except for the consideration of the peak power load of the day.

The charging / discharging ratio calculating unit may calculate a predicted cost for the charge for each hour of the child in real time if the predicted peak value of the current month's demand power is not close to the cumulative peak value within the critical water level, Is set to be smaller than the updated cumulative peak value.

Further, the comparison and analysis unit according to the embodiment of the present invention compares the predicted peak value for the demand power of the current month calculated based on the past power use data for the past two weeks and the estimated peak value for the demand power of the current month Compare the values.

Also, the control processor according to an embodiment of the present invention updates the battery consumption charge, the charge for each charge and the daily peak value through the operation of the energy storage device on the same day, and, based on the cumulative peak value updated in real time, Discharge drive of the energy storage device.

Also, the control processor according to the embodiment of the present invention calculates the base rate based on the peak value accumulated for one month by the update, adds up the base rate with the charge for each time, and considers the daily battery consumption cost, .

According to an embodiment of the present invention, the charge / discharge ratio of the optimized energy storage device is calculated according to the result of comparing and analyzing the peak value and the actual cumulative peak value with respect to the predicted demand power, By controlling the operation, it is possible to reduce the peak value of the actual power load pattern and the total power charge.

1 is a schematic diagram illustrating a connection of an energy storage device and a load according to an embodiment of the present invention.
2 is a block diagram schematically illustrating a configuration of a system for operating an energy storage device based on a Korean power plan according to an embodiment of the present invention.
FIG. 3 is a flowchart for schematically explaining a method of operating an energy storage device based on a Korean power plan according to an embodiment of the present invention.
FIG. 4 illustrates a method of operating an energy storage device for a year according to an embodiment of the present invention. Referring to FIG.
FIG. 5 is a graph illustrating a comparison of power peak values derived by a conventional power plan based energy storage system and other algorithms according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following description and the accompanying drawings, detailed description of well-known functions or constructions that may obscure the subject matter of the present invention will be omitted. It is to be noted that the same constituent elements are denoted by the same reference numerals as possible throughout the drawings.

, 에너지 저장장치의 출력 전력을

라고 정의하면, 수요/공급의 원리에 따라, 전력망에서 인가되는 전력량은

로 나타나게 된다. FIG. 1 schematically shows a connection of a power network, an energy storage device, and a load. Arrows indicated by dashed lines denote flow directions of energy, which is power, and can be defined as functions of time. The relationship between the supply of power to the load side via the grid and the energy storage is defined as a function with time t as a parameter and the required power at the load side

, The output power of the energy storage device

According to the principle of demand / supply, the amount of power applied in the grid is defined as

Respectively.

The present invention discloses an energy storage device operating system and method in a Korean power plan environment that can reduce a peak value of an actual power load pattern and a total power charge through proper operation of the energy storage device do.

2 is a block diagram schematically illustrating a configuration of a system for operating an energy storage device based on a Korean power plan according to an embodiment of the present invention.

2, the operation system 100 for a Korean type power plan based energy storage device according to an embodiment of the present invention includes a demand power detection unit 110, a demand power prediction unit 130, a comparison and analysis unit 150, A charge / discharge ratio calculation unit 170, and a control processing unit 190. [

The demanded power detection unit 110 calculates the current demanded power using the external power metering device and calculates the accumulated peak value of the demanded power over the past several months. The last few months correspond to the winter and summer months of the 12 months before the month.

The demand power detection unit 110 uses data on power consumption stored every 15 minutes through AMI (Advanced Metering Infrastructure) or Smart meter employed as the external power metering device to calculate demand power of a customer.

The demand power predicting unit 130 predicts the peak value of the demand power of the current month based on the data on the past power consumption amount detected from the demand power detection unit 110. [ Specifically, the demand power predicting unit 130 can predict the peak value of the demand power of the current month based on the demand power data of the last two weeks.

The comparison and analysis unit 150 compares the estimated peak value of the current monthly demand power predicted by the demanded power prediction unit 130 with the accumulated peak value of the demanded power over the past several months calculated from the demanded power detection unit 110. [ Specifically, the comparison and analysis unit 150 compares the predicted peak value for the demand power of the current month calculated based on the past power use data for the past two weeks with the cumulative peak value of the winter and summer seasons in the immediately preceding 12 months Can be analyzed.

In addition, the comparison and analysis unit 150 determines whether the estimated peak value of the demand power of the current month is close to the cumulative peak value of the demanded power within a preset threshold water level.

The charging / discharging ratio calculating unit 170 calculates the charge / discharge ratio of the energy storage device for reducing the peak load of the awning according to the comparison result performed by the comparison / analysis unit 150. That is, the charge / discharge ratio of the energy storage device is calculated from the objective function set differently depending on whether the comparison / analysis unit 150 is close to the cumulative peak value of the demanded electric power within the predetermined threshold water level of the predicted peak electric power of the current month's demand electric power.

Specifically, when the predicted peak value of the demand power of the current month is close to the accumulated peak value within the critical water level, the charge / discharge ratio for operating the energy storage device for the child to reduce the peak load is calculated.

To this end, the charging / discharging ratio calculating unit 170 calculates an objective function (Equation 1) for minimizing the predicted cost for the charge of each day of the day considered simultaneously with the peak charge of the day to operate the energy storage device , And calculates the charge / discharge ratio for driving the energy storage device of the child from the calculation of the objective function. At this time, the charge / discharge ratio of the energy storage device is calculated by applying an experimentally calculated range to reduce the total electric power charge to the error of the predicted load according to the time of the day.

Here, the objective function is derived by Equation (1).

In this case, equation (1) represents the objective function for minimizing the base rate and the time of use price, and (2) represents the state of charge of the battery. (SoC) value must be within a certain range, and (3) is a constraint condition for the portion where power can not be recovered according to domestic power regulation. Equation (4) And the final state is always set to be the same, and is a value set in advance to solve the unstable side that may occur due to the change of the initial state of the battery through the constraint condition.

Table 1 below shows parameters used in the objective function of the present invention.

Real time load profile in time slot

Predicted load profile in time slot

Normalized charging / discharging schedule value in ESS

Minimum / Maximum SoC value in ESS

Initial battery SoC

Maximum charging / discharging rate of ESS

Represents the use of each time slot

Base electricity cost from historical peak value

Auxiliary variable to reduce peak value in load profile

Weight factor to reflect the importance of base cost vs ToU cost

by

matrix from predicted load profile and maximum charging rate in ESS

Uncertainty boundary of

Absolute value in optimal charging / discharging value

Daily peak load which use ESS to minimize peak value

ESS to minimize peak value

Historical peak load from past 12months excluding spring and fall

ToU cost of day

of month

Electricity bill which is sum of base cost and ToU cost

Battery cycle life at the level of discharging (DoD)

Battery wear-out cost in each time slot

를 보조변수 η(eta)로 설정하고, 추가적인 제약조건인 식 (6)을 설정함으로써, 상기 목적함수를 아래 수학식 2의 식 (5)와 같이 단순하게 나타내는 것이 가능하다.Equation (2) is a formula for solving the min-max problem for the peak rate reduction in the above Equation (1). To solve the min-max problem of Equation (1), Equation (2) uses linear programming to calculate the basic rate item

It is possible to simply express the objective function as the following equation (5) by setting it as the auxiliary variable eta (eta) and setting the equation (6) as an additional constraint condition.

)에서 불확정한 오차가 발생하는 것을 감안하기 위한 일종의 boundary(

)를 감안하여 최적화 문제를 해결 한다. 이 때,

값으로,

를 통해 발생할 수 있는 오차를 사전에 고려하도록 하였다. In addition, the present invention discloses an energy optimization method under a power use environment in which an indeterminate element that can not be actually measured occurs. For this, as shown in Equation 3 below, a given data (

) Is a kind of boundary to take into account that an uncertain error occurs in

) To solve the optimization problem. At this time,

By value,

And the errors that may occur through the system are considered in advance.

On the other hand, in the case where the predicted peak value of the demand power of the current month is not close to the cumulative peak value within a preset threshold water level, the charge / discharge operation of the energy storage device of the child is controlled, The charge / discharge ratio of the energy storage device is calculated taking into consideration only the predicted cost of the charge of each time.

If the charge / discharge ratio calculation unit 170 does not approach the cumulative peak value within a preset threshold value of the demand power of the current month, the predicted cost for the charge for each day of the day is updated to the cumulative peak value . In this case, the charge / discharge ratio of the energy storage device can be calculated from the objective function expressed by Equation (4) below.

보다만 작도록 설정한다.In this case, when the predicted peak value of the demanded power of the current month is not close to the accumulated peak value within the threshold water level, the power used must not exceed the existing accumulated peak value in the optimization considering only the billing- this

.

The control processing unit 190 controls the operation of the energy storage device according to the charge / discharge ratio of the energy storage device calculated by the charge / discharge ratio calculation unit 170.

In addition, the control processor 190 updates the battery charge, the charge for each charge and the daily peak value through the operation of the energy storage device, and controls the charge / discharge drive of the energy storage device of the child according to the cumulative peak value updated in real- do.

In addition, the control processor 190 calculates the base rate based on the accumulated peak value for one month by the update, adds the base rate to the billing fee per calendar, and calculates the monthly power bill considering the daily battery consumption cost.

In addition, the control processor 190 is a component for controlling various components of the Korean Power Plans based energy saving system and handling various data, and is provided with a central processing unit such as a CPU processor And the operation of the control processing unit as described above can be performed by executing the program stored in the control processing unit or the memory.

Meanwhile, a method of considering an uncertain load factor in an embodiment of the present invention will be described below in detail.

The present invention allows for a charge / discharge ratio and a desired SoC (State of Charge) at each time slot in a daily operation, taking into account uncertain load factors. This result is also applied to the annual operation method shown in FIG.

d is a T-dimensional vector and is set to have an empirical load profile of a typical day, i.e., T timeslots per day.

d = [d1, d2, ..., dT] (1)

I represents the predicted load profile of d.

 l = [l1, l2, ..., lT] (2)

X represents a normalized charge / discharge schedule vector, whose elements are placed at [-1, 1] and obtained by the optimization process. The optimization process is implemented by the objective function described below.

X = [x1, x2, ..., xT] (3)

이다.Let T = {1, 2, ..., T}. In battery operation, xi> 0 means battery charge, xi <0 means battery discharge,

to be.

For actual operation, the SoC of the battery should be set to be within the following range.

(4)

(4)

Where b0 is the initial battery state and r is the maximum charge / discharge ratio of the ESS. Since the energy storage device is prohibited to recapture the surplus power according to the actual Korea Electric Power Regulations, the restricting conditions that occur according to the actual operation are reflected as the restriction requirements, the optimization technique is applied, and the following additional restriction requirements are set .

(5)

(5)

And, the present invention assumes that the daily SoC level is the same. Therefore, the sum of the charge and discharge rates during one day should be zero.

(6)

(6)

를 (4), (5) 및 (6)을 만족하는 x의 가능한 집합으로 정의한다.To simplify the notation

Is defined as a possible set of x that satisfies (4), (5) and (6).

Electricity rates in Korea are divided into two parts: the basic cost, which is determined as the monthly maximum load, and the time of use (ToU) cost.

Thus, the present invention takes both peak decrement and time-of-turn (ToU) pricing in the objective function and formulates linear programming.

(7)

(7)

는 시간 슬롯

에서의 계시별 요금이다.

는 기본 비용 대 계시별 요금의 중요도를 반영하는 가중치이다. 선형 프로그래밍을 사용하여 최소/최대 문제를 해결하기 어렵기 때문에 본 발명에서는 다음과 같이 보조변수를 사용함으로써 수학식 1을 수학식 2와 같이 변형시킨다.

Time slots

It is the charge for the revelation in.

Is a weight that reflects the importance of the basic cost versus the expense. Since it is difficult to solve the minimum / maximum problem using linear programming, the present invention transforms Equation 1 as Equation 2 by using auxiliary variables as follows.

Equation 2 is linear programming that reflects how to reduce the peak load. As a result, the energy storage device operates to minimize the total cost, taking into account the peak load and expense-specific costs.

은 예측되어야 하므로 불확실성이 있다. Formulas (2) through (9) are valid only if all parameters are known in advance. However,

There is uncertainty.

In order to implement a robust operation algorithm for an energy storage device considering this, the following nominal linear programming is derived.

Robust optimization:

는 비용벡터

의 전치 행렬이고, A는 불확실성 요소를 갖는 행렬이며, s는 제약 조건 벡터이며 나중에 정의되고, 1은 모두 하나의 벡터이다. 로버스트 최적화를 적용하기 위해 수학식 2를 (10)-(12)와 같은 위 공식으로 변환한다. (5)와 (9)의

는 불확실하므로, 본 발ㅁ명은 (5)와 (9)를 식 (13)에서와 같은 행렬 형태로 놓는다.here,

Is a cost vector

Where A is a matrix with an uncertainty factor, s is a constraint vector and is defined later, and 1 is a single vector. To apply the robust optimization, we convert equation (2) to the upper equation (10) - (12). (5) and (9)

(5) and (9) are arranged in matrix form as in (13).

Equation (13) is identical to that of (11) except that x is increased by 1 to be associated with an uncertain load profile. Thus, the uncertainty exists only in the (T + 1) th column of A. The present invention employs equation (19) for robust optimization, which is terminated by the method of Soyster as follows.

는 식(11) 및 (13)로부터 T+1 행렬에 의한 2T이고,

,

는

행에서 불확실한

를 갖는

의 집합이다. 이는 식 (20)에서 가정되고,

,

는

에 놓여있다.

는 불확실성에 대한 경계 역할을 한다. 불확실성은 식 (5)와 식(9)에서 예측된 부하 데이터

로부터 생기기 때문에 A의 (T+1)번째 열에서만 불확실성이 발생하는 것을 알 수 있다.

는 수학식 3의 최적 해법이고, 식 (20)에서

이고, 그러므로 식 (15)는 다음과 같다.here,

Is 2T by the T + 1 matrix from the equations (11) and (13)

,

The

Uncertain in line

Having

. This is assumed in equation (20)

,

The

Lt; / RTI &gt;

Serve as a boundary for uncertainty. Uncertainty is the load data predicted in Eqs. (5) and (9)

(T + 1) -th column of A, the uncertainty is generated.

Is the optimal solution of Equation (3), and in Equation (20)

(15) is as follows.

는

및

에서 과거 부하 프로파일과 예측 오차를 분석함으로써 결정된다.

The

And

By analyzing past load profiles and prediction errors.

As described above, according to the embodiment of the present invention, the charge / discharge ratio of the optimized energy storage device is calculated according to the result of comparing and analyzing the peak value with respect to the predicted demand power and the actual accumulated peak value, By controlling the charging / discharging operation of the storage device, the peak value of the actual power load pattern and the total power charge can be reduced.

Hereinafter, a method of operating an energy storage device based on a Korean type power plan according to an embodiment of the present invention will be described with reference to FIG.

FIG. 3 is a flowchart for schematically explaining a method of operating an energy storage device based on a Korean power plan according to an embodiment of the present invention.

First, in order to operate an energy storage device in order to reduce electric power charges in a Korean power plan environment, the demand power estimating unit 130 calculates a peak value of the demand power of the current month based on past power use data for a predetermined week (S310). Specifically, the demand power predicting unit 130 can predict the peak value of the demand power of the current month based on the demand power data of the last two weeks.

Meanwhile, the step S310 may further include a step in which the demanded power detection unit 110 calculates the current demanded power using the external power metering apparatus and calculates the accumulated peak value of the demanded power over the past several months. The last few months correspond to the winter and summer months of the 12 months before the month. In order to calculate the demanded power of the customer, data on power consumption stored every 15 minutes through the AMI (Advanced Metering Infrastructure) or Smart meter employed as the external power meter can be used.

Next, the comparison and analysis unit 150 compares the predicted peak value of the demand power with the cumulative peak value of the past months (S320).

That is, the estimated peak value of the current month's demand power predicted by the demanded power prediction unit 130 is compared with the accumulated peak value of the demanded power of the last several months calculated from the demanded power detection unit 110.

Specifically, the comparison and analysis unit 150 can compare and analyze the predicted peak value of the current month power demand calculated based on past power use data for the past two weeks and the cumulative peak value of winter and summer during the immediately preceding 12 months have.

In addition, the comparison and analysis unit 150 determines whether the estimated peak value of the demand power of the current month is close to the cumulative peak value of the demanded power within a preset threshold water level.

Next, the charging / discharging ratio calculating unit 170 calculates a charging / discharging ratio for controlling the operation of the energy storage device based on a comparison between the predicted peak value of the demanded power of the current month and the accumulated peak value of the past several months (S330).

That is, the charging / discharging ratio calculating unit 170 calculates the charge / discharge ratio of the energy storage device for reducing the peak load of the awning according to the comparison result performed by the comparison / analysis unit 150.

Specifically, the charge / discharge ratio of the energy storage device is calculated from the objective function set differently depending on whether the comparison / analysis unit 150 is close to the cumulative peak value of the demanded electric power within the predetermined threshold water level of the predicted peak electric power of the current month's demand electric power.

In the case where the predicted peak value of the demand power of the current month approaches the cumulative peak value of the demanded power within the predetermined threshold water level, the charge / discharge ratio calculation section 170 calculates the charge / Calculates an objective function (Equation 1) for minimizing a predicted cost for a star fare, and calculates a charge / discharge ratio for driving the energy storage device of a child from the calculation of the objective function. At this time, the charge / discharge ratio of the energy storage device is calculated by applying an experimentally calculated range to reduce the total electric power charge to the error of the predicted load according to the time of the day. Here, the objective function is derived from Equation 1 described above.

In this case, equation (1) represents the objective function for minimizing the base rate and the time of use price, and (2) represents the state of charge of the battery. (SoC) value must be within a certain range, and (3) is a constraint condition for the portion where power can not be recovered according to domestic power regulation. Equation (4) And the final state is always set to be the same, and is a value set in advance to solve the unstable side that may occur due to the change of the initial state of the battery through the constraint condition. The parameters of the objective function are referred to Table 1 mentioned above.

를 보조변수 η(eta)로 설정하고, 추가적인 제약조건인 식 (6)을 설정함으로써, 상기 목적함수를 앞서 설명한 수학식 2의 식 (5)와 같이 단순하게 나타내는 것이 가능하다.Equation (2) is a formula for solving the min-max problem for the peak rate reduction in the above Equation (1). In order to solve the min-max problem of Equation (1), in order to solve this problem through the linear programming in Equation (2), the basic rate item

It is possible to simply express the objective function as the equation (5) of the above-mentioned equation (2) by setting the auxiliary variable η (eta) as the auxiliary variable η (eta) and setting the equation (6) as the additional constraint.

)에서 불확정한 오차가 발생하는 것을 감안하기 위한 일종의 boundary(

)를 감안하여 최적화 문제를 해결 한다. 이 때,

값으로,

를 통해 발생할 수 있는 오차를 사전에 고려하도록 하였다. In addition, the present invention discloses an energy optimization method under a power use environment in which an indeterminate element that can not be actually measured occurs. For this, as shown in Equation 3,

) Is a kind of boundary to take into account that an uncertain error occurs in

) To solve the optimization problem. At this time,

By value,

And the errors that may occur through the system are considered in advance.

On the other hand, in the case where the peak value of the predicted demand power is not close to the cumulative peak value within a predetermined threshold water level, except for the consideration of the peak power load on the day in controlling the charging / discharging operation of the energy storage device, The charge / discharge ratio of the energy storage device is calculated taking into consideration only the predicted cost for the charge of the day on the day.

In this case, the charge / discharge ratio of the energy storage device can be calculated from the objective function as expressed by Equation (4).

보다만 작도록 설정한다.If the peak value of the demanded power demand is not close to the cumulative peak value within the threshold water level, the power used must not exceed the existing cumulative peak value in the optimization considering only the billing-by-billing plan.

.

Next, the control processor 190 controls the charging / discharging operation of the energy storage device to reduce the peak load of the awning according to the charge / discharge ratio calculated in step S330 (S340).

Thereafter, the control processor 190 updates the battery charge, the charge for each charge and the daily peak value through the operation of the energy storage device, and controls the charging / discharging drive of the energy storage device of the child according to the cumulative peak value updated in real time The method comprising the steps of:

In addition, the control processor 190 calculates the base rate based on the accumulated peak value for one month by the update, adds up the base rate with the billing fee for each time, and calculates the monthly power bill considering both the daily battery consumption cost .

FIG. 4 is a flowchart illustrating a method for operating an energy storage device for one year according to an embodiment of the present invention, which is a mathematical representation of the overall flow of driving the energy storage device that continues throughout the year.

Figure 4 illustrates a configuration that extends to year-round operations based on a daily operation of an energy storage device that takes into account an uncertain load profile.

4, the peak value of the demanded power of the current month m is predicted based on the data of the last two weeks for each month (m) (n) (S403), and the predicted peak value of the demanded power is within the critical water level It is judged whether or not it is close to the cumulative peak value of the past several months (S404).

In step S404, when the predicted peak value of the demanded electric power is close to the cumulative peak value of the past several months within the critical water level, the charge / discharge ratio for driving the energy storage device for the child is calculated by calculating the objective function 1 (S405) .

Here, the objective function 1 is a function for minimizing the predicted cost for the charge of the day of the day, considered simultaneously with the peak charge of the day, to operate the energy storage device. At this time, the charge / discharge ratio of the energy storage device is calculated by applying an experimentally calculated range to reduce the total electric power charge to the error of the predicted load according to the time of the day. The items and parameters of the objective function 1 will be described in detail with reference to the above description.

On the other hand, when the peak value of the demanded electric power estimated in step S404 is not close to the cumulative peak value within a predetermined threshold water level, the consideration of the peak electric power load on the day is not taken into consideration in controlling the charge / And calculates the charging / discharging ratio of the energy storage device for minimizing the power charge considering only the predicted cost of the charge for each day of the day (S406). At this time, the predicted cost for the charge for each day of the day is set to be smaller than the updated cumulative peak value in real time.

In step S407, the daily peak load is extracted and updated in step S405 or step S406, and the accumulated peak value is calculated in step S408.

Next, the cumulative peak value of the last 12 months immediately before the current month excluding the spring and the estimated month is obtained, and the fee for each month of the month n is obtained (S409).

Then, the process of estimating the peak value of the demand power of the current month (m), the cumulative peak value of the past several months, and obtaining the charge for each day of the present day (S403 to S409) is repeated until the end of the month At the month, the base rate is calculated based on the accumulated peak value for one month, and the monthly charge rate is calculated by adding the base rate to the charge at the time of the month (S411). Then, from step S409 to step S412 until December, the final electric power charge for one year is calculated at one year (S414).

과

은 각각 n일의 시간 슬롯

에서 실제 부하 프로파일과 충방전 비율을 나타낸다. 그런 다음 일일 피크 부하는

로 나타내고, 당월 피크 부하는

로 나타내며, 여기서

는 m월의 작업 일의 집합을 의미한다.

은 m달의 n일까지 춘계와 추계를 제외한 당월 직전의 지난 12개월의 누적 피크 부하를 나타낸다.

은 m월 n일의 예측 피크 부하를 나타낸다. 그러면,

에 기반하여 에너지 저장장치는 피크 부하 제어를 실행할지 결정한다. 4,

and

Lt; RTI ID = 0.0 &gt; n &

And the actual load profile and charge / discharge ratio. Then the daily peak load is

, The peak load for the month

Lt; / RTI &gt;

Means a set of work days in month m.

Represents the cumulative peak load of the last 12 months immediately before the month except the spring and the autumn until the nth day of the mth month.

Represents the predicted peak load of day n of month m. then,

The energy storage device determines whether to perform peak load control.

Minimizing the predicted cost of the current day's peak charge for the same day of the day in order to operate the energy storage device if the expected peak value of the current month's demand power approaches the cumulative peak value of the demanded power within a predetermined threshold water level Step S405 is executed.

On the other hand, when the peak value of the predicted demand power is not close to the cumulative peak value within a predetermined threshold water level, the charge / discharge operation of the energy storage device of the child is controlled in consideration of the peak power load of the day , The charge / discharge ratio of the energy storage device is calculated taking into consideration only the predicted cost for the charge of the day on the same day.

는

(22)로 정의되고,

는 식 (22)와 같이 매일 업데이트 된다.Here, in order to avoid ambiguity,

The

(22), &lt; / RTI &gt;

Is updated daily as shown in equation (22).

는 m월 n일의 계시별 비용이라 하면, 다음과 같이 나타낼 수 있다.

Is the expense for the nth day of the month n, it can be expressed as follows.

(23)

(23)

When n reaches the end of the month, the monthly electricity charge is calculated as the sum of the base charge and the charge per revelation.

(24)

(24)

를 계산한다. Finally, after annual operation, annual cost

.

FIG. 5 is a graph illustrating a comparison of power peak values derived by a conventional power plan based energy storage system and other algorithms according to an embodiment of the present invention.

In FIG. 5 (a), monthly peak values are calculated. Based on this, the cumulative peak load value applied to the actual fare system is calculated as shown in FIG. 5 (b). However, even if an energy storage device is used, the lower peak load in the domestic power plan does not directly affect the charge plan, so only the charge reduction according to the charge plan according to the charge plan will affect the charge plan for one year immediately after installation.

 When the result is analyzed, the case of the case of Offline shows the optimization method when the actual prediction is perfect, and the experimental result is shown only when it is theoretically possible. On the other hand, the simulation for deterministic is based on actual used prediction data and then applied the actual data to the resultant value after applying the optimization technique. If the incorrect optimization technique by uncertainty factors does not reduce the peak load appropriately . Most current research focuses on the implementation of energy storage devices that depend solely on predicted data, and thus is not suitable for the domestic electric utility environment. No ESS refers to the peak load based on the actual usage power of the consumer as a result of not applying energy storage and other algorithms. Robust optimization is a method proposed in the present invention. It can be seen that each peak load gradually decreases. It can be seen that although the energy storage device is used, the initial goal of peak load reduction can be achieved have.

100: Operation system of energy storage device based on Korean power plan system
110: Demand power detector
130: demand power prediction unit
150:
170: charge / discharge ratio calculating unit
190:

Claims (20)

Estimating a peak value of the demand power of the current month based on past power usage data for a predetermined week;
Comparing a predicted peak value of the demand power of the current month with an accumulated peak value of several months past;
Calculating a charging / discharging ratio for controlling an operation of the energy storage device according to a comparison between the predicted peak value of the current month's demand power and the cumulative peak value of the past several months; And
And operating the energy storage device for reducing the peak load of the awning according to the calculated charging / discharging ratio. The method according to claim 1,
When the predicted peak value of the demand power of the current month is close to the cumulative peak value within the threshold water level,
Calculating an objective function for minimizing a predicted cost for the charge of the day of the day considered at the same time as the peak charge of the same day; And
And calculating a charge / discharge ratio for driving the energy storage device of the child from the calculation of the objective function. 3. The method of claim 2,
The charge / discharge ratio, which means the variation of the energy state of the energy storage device,
A method of operating an energy storage device based on a Korean electric power plan, which is calculated by applying an experimentally calculated range to reduce the total electric power charge to the error of the predicted load over the time of the day. The method according to claim 1,
Updating a battery charge, a charge for each charge, and a daily peak value through operation of the energy storage device;
Controlling charge / discharge drive of the energy storage device of the child according to the cumulative peak value updated in real time; And
Further comprising the step of calculating a monthly electricity rate by simultaneously calculating a base rate based on the peak value accumulated for one month by the update, Of the energy storage device. The method according to claim 1,
When the predicted peak value of the demand power of the current month is not close to the cumulative peak value within the threshold water level,
The charge / discharge ratio of the energy storage device is calculated by taking into account only the predicted cost of the charge of the child by the charge of the child, except for the consideration of the peak power load of the day in the charge / discharge operation of the energy storage device of the child, Further comprising the steps of: a. 6. The method of claim 5,
When the predicted peak value of the demand power of the current month is not close to the cumulative peak value within the threshold water level,
Wherein the predicted cost for the charge for each of the ailments is set to be smaller than the updated cumulative peak value in real time. 6. The method of claim 5,
The predicted cost of the child's fee for each turn is
The method of operating an energy storage device based on a Korean power plan, which is calculated based on a predicted load every hour and a standardized charge / discharge ratio of the energy storage device. The method according to claim 1,
Comparing the predicted peak value of the demand power of the current month with the accumulated peak value of the past several months,
A method of operating an energy storage device based on a Korean electric power charge plan that compares the predicted peak value of the demand power of the current month calculated based on the past electric power usage data of the last two weeks with the cumulative peak value of the winter and summer of the immediately preceding month . A computer-readable recording medium storing a program for causing a computer to execute the method according to any one of claims 1 to 8. A demand power predictor for predicting a peak value of demand power of the current month on the basis of past power use data for a predetermined week;
A comparison and analysis unit for comparing the predicted peak value of the demand power of the current month with the cumulative peak value of the past several months;
A charge / discharge ratio calculating unit for calculating a charge / discharge ratio of the energy storage device for reducing the peak load of the awning according to a result of the comparison; And
And a control processor for controlling the operation of the energy storage device according to the calculated charge / discharge ratio. 11. The method of claim 10,
The charge / discharge ratio calculator calculates the charge /
And a charge / discharge ratio for operating the energy storage device to reduce the peak load when the predicted peak value of the current demand power of the current month is close to the cumulative peak value within the critical water level, Device operation system. 11. The method of claim 10,
The charge / discharge ratio calculator calculates the charge /
Calculating an objective function for minimizing a predicted cost for a charge for each day of the day considered at the same time as a peak charge for the day to operate the energy storage device and for driving the energy storage device of the child from the calculation of the objective function Based energy storage device operation system that calculates the charge / discharge ratio for the electric power charge system. 11. The method of claim 10,
The charge / discharge ratio calculator calculates the charge /
Wherein the charge / discharge ratio of the energy storage device is calculated by applying an experimentally calculated range to reduce the total power charge with respect to the error of the predicted load according to the time of the day. 11. The method of claim 10,
The control processing unit,
The charge control unit controls the charging and discharging operation of the energy storage device in accordance with the accumulated peak value updated in real time by updating the battery charge, the charge amount adjustment and the daily peak value through the operation of the energy storage device, Energy storage device operating system. 15. The method of claim 14,
The control processing unit,
Based on the peak value accumulated for one month by the above update, the basic charge is calculated and added to the charge for each time of day, and the monthly charge is calculated considering the daily battery consumption cost. . 11. The method of claim 10,
The charge / discharge ratio calculator calculates the charge /
In the case where the predicted peak value of the current month's demand power is not close to the cumulative peak value within the critical water level, except for the consideration of the peak power load on the day in controlling the charging / discharging operation of the energy storage device of the child, And the charge / discharge ratio of the energy storage device is calculated taking into account only the predicted cost for the charge of each charge of the energy storage device. 17. The method of claim 16,
The charge / discharge ratio calculator calculates the charge /
When the predicted peak value of the demand power of the current month is not close to the cumulative peak value within the threshold water level,
Wherein the predicted cost for the charge for each time of the child is set to be smaller than the updated cumulative peak value in real time. 11. The method of claim 10,
The comparison /
Based energy saving device that compares the predicted peak value for the demand power of the current month calculated based on past power use data of the past two weeks with the cumulative peak value of winter and summer during the immediately preceding month Operating system. 11. The method of claim 10,
The control processing unit,
Wherein the charge / discharge drive of the energy storage device is controlled based on a cumulative peak value updated in real time by updating a battery consumption charge, a charge plan adjustment for each charge and a daily peak value through the operation of the energy storage device on the same day, Energy storage system based on Korean power plan system. 20. The method of claim 19,
The control processing unit,
Based on the peak value accumulated for one month by the above update, the energy storage device operation system based on the Korean electric power charge plan, which calculates the monthly electric power charge at the same time by calculating the base charge based on the peak value accumulated in one month, .

Images