KR101357394B1 - Method and system for power management - Google Patents

Abstract

Provided are a method and system for managing power. The method for managing the power according to the embodiment of the present invention includes the steps of: predicting the power consumption of a load; predicting the generation power of a renewable energy generation system; and operating the power according to an energy use policy prepared for a plan outage made by referring to the predicted generation power and the predicted power consumption if the plan outage is scheduled. Thereby, the plan outage is flexibly dealt with. [Reference numerals] (AA) Start; (BB) End; (S210) Collect basic information; (S220) Predict power consumption in power load; (S230) Predict the generation power of a renewable energy generation system; (S240) Blackout is scheduled?; (S250) Manage the power according to an emergency energy use policy; (S260) Manage the power according to economic energy use policy; (S270) Power consumption/production power predicting error is generated?; (S280) Error feedback

Description

METHOD AND SYSTEM FOR POWER MANAGEMENT

The present invention relates to a power management method and system, and more particularly, to a method and system for managing and operating power supplied through a power grid and renewable energy generation system.

Power generated by self-generation using renewable energy is stored in the battery and discharged to the load if necessary in the future, thereby reducing energy production costs and improving the efficiency of power operation.

However, power operation using the battery as an energy storage source is performed based on the remaining battery capacity, and thus, it is impossible to flexibly operate the power due to changes in the surrounding environment or policy.

In particular, after the Great East Japan Earthquake in 2011, due to the suspicion of nuclear operation, Japan has been carrying out planned blackouts due to the suspension of nuclear power generation, and countries with poor power supply (eg Southeast Asia, China, etc.) The planned power outage is also being implemented for industrial power.

Accordingly, in the case of a planned power outage, it is required to find a way to integrate the power management with the economic power as well as the power supply during the power outage through the power operation plan.

If the planned outage starts without the necessary power without a thorough power operation plan, economic losses are caused, especially for industrial equipment, since the losses are very large.

The present invention has been made to solve the above problems, the object of the present invention is to predict the power consumption in the load and the production power in the renewable energy generation system power in accordance with the energy utilization measures prepared for planned outages In order to provide a power management method and system for operating.

In addition, another object of the present invention is to predict the power consumption at the load and the production power in the renewable energy generation system even when the planned outage is not scheduled to establish a more economical energy utilization measures to operate the power The present invention provides a management method and system.

According to an embodiment of the present invention for achieving the above object, a power management method, comprising: estimating power consumption at a load; Predicting the production power in the renewable energy generation system; And operating the power according to the energy utilization measures prepared for the planned outage by referring to the predicted power consumption and the predicted power consumption when the planned outage is scheduled.

The power consumption predicting step may include obtaining past power consumption and recent power consumption; Calculating the comparison error with respect to the power consumption by comparing the obtained power consumption with the recent power consumption; And predicting future power consumption from past power consumption when the comparison error is within a threshold range.

The power consumption predicting step may include: compensating the past power consumption by adding or subtracting a compensation value to the past power consumption when the comparison error is outside the threshold range; And predicting future power consumption from the compensated past power consumption.

The production power prediction step may include: obtaining a past weather, a recent weather, and a weather forecast; Comparing past weather with recent weather to calculate a comparison error for the weather; And if the comparison error is within a critical range, predicting future power generation by reflecting a weather forecast in the past weather.

In addition, the power management method according to an embodiment of the present invention, if the comparison error is out of the threshold range, the past weather compensation by adding or subtracting a compensation value to the past weather; And predicting future power generation by reflecting the weather forecast on the compensated past weather.

And, the power operation step, if the planned outage, the step of identifying the remaining battery capacity; Calculating the required power during the planned outage with reference to the predicted power consumption; And supplying renewable energy to the load if the required power is smaller than the remaining battery level.

In addition, the power management method according to an embodiment of the present invention, if the required power is more than the remaining battery capacity, calculating the required amount of charge of the battery; Calculating a predicted production power before the planned outage by referring to the predicted production power; And charging the battery with renewable energy if the required charge amount is smaller than the predicted production power before the planned outage, wherein the required charge amount includes: supplying power through the battery to consume power at the load during the planned outage. It may be the amount of charge to be charged more.

In addition, the power management method according to an embodiment of the present invention may further include supplying renewable energy to a load when a required charge amount is completed in the battery.

In addition, the power management method according to an embodiment of the present invention, if the required charging amount is greater than the predicted production power before the planned outage, further comprising the step of charging the battery with renewable energy and energy supplied through the power grid; The battery charge amount by the energy supplied from the electric power grid can be determined by subtracting the charge amount by the predicted production power before the planned outage from the required charge amount.

And, when the energy is supplied through the power grid, when the power supply price for each time zone is different may be determined to the time zone when the power price of the power supplier is the lowest.

In addition, the power management method according to an embodiment of the present invention, if the planned outage, the step of operating the power in accordance with the energy utilization measures established by creating a charge and discharge schedule of the battery; Can be.

In addition, the power management method according to an embodiment of the present invention, if the discharge time according to the schedule does not arrive, the step of charging by supplying renewable energy to the load or to the battery; And when the discharge time according to the schedule arrives, supplying the stored energy and the renewable energy and the renewable energy to the load to the load.

In addition, the power management method according to an embodiment of the present invention, by supplying the energy remaining in the supply phase to the power grid, selling the surplus power; may further include a.

In addition, the power management method according to an embodiment of the present invention, after the power operation, determining whether an error occurred for at least one of the predicted power consumption and the expected production power; And if it is determined that an error has occurred, feeding back the error such that the influence of the error is reflected in performing at least one of the next power consumption prediction and the production power prediction.

Meanwhile, the power management system according to another embodiment of the present invention predicts power consumption at a load, predicts production power at a renewable energy generation system, and predicts power consumption when a planned power failure is scheduled. EMS (Energy Management System) that establishes energy utilization measures against planned outages with reference to predicted power generation; And an ESS (Energy Storage System) for operating power in accordance with the energy utilization measures established by the EMS.

As described above, according to the present invention, since the electric power is operated in accordance with the energy utilization measures in preparation for the planned outage by predicting the power consumption at the load and the produced power in the renewable energy generation system, it is possible to flexibly cope with the implementation of the planned outage. Becomes possible.

In addition, even when the planned outage is not scheduled, the energy utilization measures are established by predicting the power consumption at the load and the production power at the renewable energy generation system, thereby pursuing more economical power operation.

In addition, since the production of renewable energy is predicted using meteorological information, which plays an important role in the production of renewable energy, it is possible to accurately predict power generation.

In addition, since the prediction method by the error compensation that compares the historical data and the recent data is applied, it also reflects the weather forecast, so that it is possible to accurately predict the power consumption and the production power even in an environment in which power consumption and meteorological changes fluctuate.

1 is a view showing a power system to which the present invention is applicable;
2 is a flowchart provided to explain a power management method according to a preferred embodiment of the present invention;
3 is a flowchart provided in a detailed description of a process of collecting basic information necessary for power management in an EMS server;
4 is a flowchart provided in a detailed description of a power consumption prediction process at a power load;
5 is a flowchart provided in a detailed description of a production power prediction process in a renewable energy generation system;
6 is a flow chart provided in the detailed description of the power operation process according to the emergency energy utilization measures in preparation for the planned outage in the EMS server,
7 is a flowchart provided in a detailed description of a power operation process according to economic energy utilization measures in an EMS server when a planned outage is not scheduled, and
FIG. 8 is a detailed block diagram of the EMS server shown in FIG. 1.

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

1. Power system

1 is a diagram showing a power system to which the present invention is applicable. As shown in FIG. 1, the power system to which the present invention is applicable includes a renewable energy generation system 110, a power load 120, an energy storage system (ESS) 130, a power grid 150, and an EMS (Energy). Management System) 160, power plant 170, power server 180 and weather server 190 are included. Meanwhile, in FIG. 1, a solid line represents a power line to which power moves, and a dotted line represents a wired / wireless communication network.

Renewable energy generation system 110 is a power generation facility using renewable energy, such as solar, wind, tidal, biomass, and the like, power load 120 is a facility, such as homes, buildings, factories that consume power.

The ESS 130 charges the battery 140 to store energy and discharges the battery 140 to supply the stored energy to the power load 120 or the power grid 150, as shown in FIG. 1. A power conditioning system (PCS) 131, a battery management system (BMS) 132, and a battery 140.

PCS 131, 1) to supply the power load 120 or charge the battery 140, the energy supplied from the power plant 170 via the power grid 150, 2) from the renewable energy generation system 110 The supplied energy is supplied to the power load 120 or charged to the battery 140, and 3) the battery 140 is discharged to supply the stored energy to the power load 120 or the power grid 150 to perform power management.

Power management by the PCS 131 operates according to emergency energy utilization measures when planned power outages are planned, but otherwise operates according to economic energy utilization measures to seek profit using renewable energy while saving energy. In parallel.

In addition, the PCS 131 monitors and stores the power consumed by the power load 120 as data.

The BMS 132 is a system for managing the battery 140. The BMS 132 senses the voltage, current, temperature, and the like of the battery 140 to control the charge / discharge amount of the battery 140 to an appropriate level, as well as to control the battery 140. Perform cell balancing and determine the remaining amount of the battery 140. In addition, the BMS 132 protects the battery 140 through an emergency operation when a danger is detected.

The battery 140 functions as an energy store for storing energy by charging power supplied through the renewable energy generation system 110 or the power grid 150, and stores the stored energy through the power load 120 or the power grid ( It serves as an energy source to supply 150).

The power server 180 is a server operated by a power control station of a power supply organization that manages power generation, substation, transmission, and distribution, and operates a power supply. The power server 180 controls / controls the power generation status by the power plant 170 and controls the power control station. It is in charge of spreading planned outages.

The meteorological server 190 is a server operated by the Korea Meteorological Agency, and the meteorological server 190 in the present power system functions as a server providing weather data and weather forecast data.

The EMS server 160 controls the PCS 131 of the ESS 130 to manage power management in the power system shown in FIG. To this end, the EMS server 160 predicts the power consumption at the power load 120, predicts the production power in the renewable energy generation system 110, and whether the planned power outage guided from the power server 180 Accordingly, the appropriate energy utilization measures are established and power is controlled by controlling the PCS 131 accordingly.

2. Power Management Method

Hereinafter, a power management method applicable to the power system shown in FIG. 1 will be described in detail with reference to FIG. 2. 2 is a flowchart provided to explain a power management method according to a preferred embodiment of the present invention.

As illustrated in FIG. 2, first, the EMS server 160 collects basic information necessary for power management (S210). The basic information collected in step S210 includes information necessary to predict power consumption and production power, establish energy utilization measures, and economically operate power. For a detailed description of step S210, refer to FIG. 3. It will be described later in detail.

When the basic information is collected, the EMS server 160 estimates the power consumption at the power load 120 by using the same (S220). The power consumption data of the past and the latest are used for the power consumption prediction in step S220, and the detailed description of the step S220 will be described later with reference to FIG. 4.

Next, the EMS server 160 predicts the production power in the renewable energy generation system 110 by using the basic information collected in step S210 (S230). Historical and recent weather data and weather forecast data are used to predict power generation at step S230. A detailed description of step S230 will be described later with reference to FIG. 5.

Thereafter, the EMS server 160 determines whether a planned outage is scheduled (S240). The planned outage may be due to maintenance of the electric power grid 150 or the electric power facility, as well as power supply and demand problems.

If it is determined that the planned outage (S240-Y), the EMS server 160 establishes emergency energy utilization measures to operate the power (S250). Detailed description of the step S250 will be described later in detail with reference to FIG. 6.

On the other hand, if it is determined that the planned outage is not scheduled (S240-N), EMS server 160 establishes economic energy utilization measures to operate the power (S260). A detailed description of the step S260 will be described later in detail with reference to FIG. 7.

After power operation is performed according to the energy utilization measures, the EMS server 160 determines whether a prediction error for power consumption and production power has occurred (S270). The prediction error in step S270 is calculated for each of power consumption and production power.

That is, 1) comparing the 'predicted power consumption in step S220' and 'actual power consumption in step S250 or S260' to determine the occurrence of errors and the amount of generation, and 2) 'predicting power consumption in step S230' and ' The occurrence of errors and the amount of occurrence are determined by comparing the actual power generated at the step S250 or S260.

When it is determined that the prediction error occurs in step S270 (S270-Y), the EMS server 160 feeds back the error generation amount so that the influence of the error is reflected in the next power consumption prediction and the production power prediction (S280). By the steps S270 and S280 it is possible to pursue the accuracy of the next prediction.

3. Collect basic information

Hereinafter, operation S210 of FIG. 2 will be described in detail with reference to FIG. 3. 3 is a flowchart provided in a detailed description of a process of collecting basic information necessary for power management in the EMS server 160.

As shown in FIG. 3, first, the EMS server 160 obtains and stores past power consumption data and recent power consumption data at the power load 120 from the PCS 131 (S211 and S212).

In addition, the EMS server 160 obtains and stores past weather data, recent weather data, and weather forecast data from the weather server 190 (S213 to S215).

In addition, the EMS server 160 obtains and stores information on the planned outage information, the basic charge / discharge schedule, and the hourly power price from the power server 180 (S216 to S218). Planned outage information includes information on planned outages and scheduled dates.

4. Power consumption prediction

Hereinafter, operation S220 of FIG. 2 will be described in detail with reference to FIG. 4. 4 is a flowchart provided to a detailed description of a power consumption prediction process in the power load 120.

In order to estimate power consumption, the EMS server 160 first reads past power consumption data and recent power consumption data acquired / stored in steps S211 and S212 of FIG. 3 (S221 to S222).

For the convenience of understanding and explaining the reference date generation, the "past" power consumption data is the power consumption data of "2001-2011 (10 years)", and the "recent" power consumption data of the "May 2012" It is power consumption data, and it is assumed that "prediction" power consumption is power consumption of "June 2012".

The EMS server 160 calculates a comparison error with respect to power consumption by comparing the past power consumption data read with the latest power consumption data (S223). For example, in step S223, a comparison error may be calculated by comparing the average power consumption in May of 2001 to 2011 with the power consumption of May 2012.

If the comparison error calculated in step S223 is within the threshold range (S224-Y), the EMS server 160 predicts the future power consumption from the past power consumption data (S225). For example, if the comparison error is determined to be within 3% (critical error) in step S224, in step S225 EMS server 160 is the 'consumption of June 2012 from the average power consumption in June of 2001-2011' Power 'can be predicted.

On the other hand, if the comparison error calculated in step S223 is outside the threshold range (S224-N), the EMS server 160 compensates the past power consumption by adding or subtracting a compensation value to the past power consumption data (S226).

If the comparison error is out of the critical range in step S224, the recent power consumption is inconsistent with the past power consumption. Therefore, the previous power consumption is compensated for in step S226 so as to converge to the recent power consumption to some extent.

The past power consumption compensation in step S226 is performed on all past power consumption data. In other words, the compensation for the past power consumption in the step S226 is performed on the '2001-2011 total power consumption data', not '2001-2011 power consumption data'.

Therefore, if it is determined that the comparison error exceeds 3% (critical error) in step S224, in step S226 the EMS server 160 adds or subtracts the compensation value to the '2001-2011 total power consumption data' to consume the past Compensates for power.

Specifically, when the past consumption power is smaller than the latest consumption power, the compensation value is added to the past consumption power. If the past consumption power is larger than the latest consumption power, the compensation value is subtracted from the past consumption power, .

Thereafter, the process is re-executed from step S223. Nevertheless, if the comparison error calculated in step S223 is outside the threshold range (S224-N), the compensation by step S226 is performed once more.

On the other hand, when the comparison error is within the threshold range by the past power consumption compensation (S224-Y), the EMS server 160 predicts the future power consumption from the compensated past power consumption data (S225).

In step S225, EMS server 160 predicts the 'power consumption in June 2012' from the 'average power consumption in June of 2001-2011' compensated by the comparison error is added or subtracted.

In the above embodiment, the power consumption prediction is described as being performed on a “month” basis, but this is only an example for convenience of description. Power consumption prediction can be made in units of "weeks", "days", "hours", and "minutes" as necessary.

5. Production power forecast

Hereinafter, operation S230 of FIG. 2 will be described in detail with reference to FIG. 5. 5 is a flowchart provided in the detailed description of the prediction process for the production power in the renewable energy generation system 110.

In order to predict power generation, the EMS server 160 first reads past weather data, recent weather data, and weather forecast data acquired / stored in steps S213 to S215 of FIG. 2 (S231 to S233).

For the sake of understanding and explanation, "past" weather data is the temperature / wind data for "2001-2011 (10 years)" and "last" weather data is the temperature / wind data for "May 2012". , Weather "forecast" is the weather (sunny, cloudy, rain, snow) of "June 2012", and "forecast" production power is assumed to be the production power of "June 2012".

The EMS server 160 compares the read past weather data with the latest weather data, and calculates a comparison error with respect to the weather data (S234). For example, in step S234, a comparison error may be calculated by comparing the average temperature / wind speed in May of 2001 to 2011 with the temperature / wind speed in May 2012.

If the comparison error calculated in step S234 is within the critical range (S235-Y), the EMS server 160 reflects the weather forecast in the past weather data to predict the future production power (S236).

For example, if the comparison error is determined to be within 3% (critical error) in step S235, in step S236 EMS server 160 calculates the power that can be produced at the average temperature / wind speed in June of 2001-2011 It is possible to predict the 'production power in June 2012' by reflecting the weather by the post-weather forecast.

Reflecting the weather by weather forecast means adjusting the calculated power that can be produced according to the weather. In the case of solar power generation, if the weather is not sunny, the power that can be produced is subtracted, and in the case of wind power, wind speed In this small case, the power that can be produced is subtracted.

On the other hand, if the comparison error calculated in step S234 is outside the threshold range (S235-N), EMS server 160 compensates the past weather data by adding or subtracting a compensation value to the past weather data (S237).

If the comparison error is out of the critical range in step S235, the recent weather is too different from the past weather. Therefore, the past weather data is compensated for in step S237 to converge to the latest weather data to some extent.

The historical weather data compensation in step S237 is performed on all the past weather data. In other words, the historical weather data compensation in step S237 is performed on 'all weather data from 2001 to 2011' rather than 'weather data from May 2001 to 2011'.

Therefore, if it is determined in step S235 that the comparison error exceeds 3% (critical error), in step S237 the EMS server 160 adds or subtracts the compensation value to the '2001-2011 overall weather data' to add historical weather data. To compensate.

Specifically, if the past temperature / wind speed is less than the recent temperature / wind speed, the compensation value is added to the past temperature / wind speed. If the past temperature / wind speed is larger than the recent temperature / wind speed, the compensation value is reduced by the past temperature / wind speed, Converge temperature / wind speed to recent temperature / wind speed.

Thereafter, the process is re-run from step S234. Nevertheless, if the comparison error calculated in step S235 is outside the critical range (S235-N), compensation by step S237 is performed once more.

On the other hand, when the comparison error is within the critical range by the past weather data compensation (S235-Y), the EMS server 160 reflects the weather forecast to the compensated past weather data to predict the future production power (S236).

For example, if the comparison error is determined to be within 3% (critical error) in step S235, EMS server 160 in step S236 is compensated by the comparison error is added and compensated 'June 2001-2011 average temperature / wind speed value' After calculating the power available for production, the forecasted 'June 2012 production power' will be reflected by the weather forecast.

In the above embodiment, the production power prediction has been described as being performed in "month", but this is only an example for convenience of description. Power generation forecasts can also be made in weeks, days, hours or minutes, as needed.

6. Electric power operation according to emergency energy utilization measures

Hereinafter, operation S250 of FIG. 2 will be described in detail with reference to FIG. 6. 6 is a flowchart provided to the detailed description of the power operation process according to the emergency energy utilization measures in preparation for the planned outage in the EMS server 160.

As shown in FIG. 6, when it is determined that a planned power failure is scheduled (S240 -Y), the EMS server 160 determines the remaining amount of the battery 140 (S251). The remaining battery level at step S251 may be determined by the EMS server 160 receiving information on the remaining battery capacity of the battery 140 calculated by the BMS 132 of the ESS 130.

Meanwhile, the EMS server 160 calculates the required power during the planned power outage by referring to the power consumption predicted in step S220 (S252), and calculates the required power calculated in step S252 and the battery 140 identified in step S251. The remaining amount is compared (S253).

If it is determined in step S253 that the required power is smaller than the remaining amount of the battery 140 (S253-Y), the EMS server 160 is the renewable energy generated by the renewable energy generation system 110 to the power load 120 The PCS 131 of the ESS 130 is controlled to be supplied (S254).

When the required power is smaller than the remaining amount of the battery 140, since all the required power during the planned outage is secured in the battery 140, the renewable energy generated by the renewable energy generation system 110 is transferred to the power load 120. ) To consume everything.

On the other hand, if it is determined in step S253 that the required power is more than the remaining amount of the battery 140 (S253-N), the EMS server 160 calculates the required charging amount of the battery 140 (S255).

The required charge amount refers to a charge amount to be further charged to the battery 140 in order to supply the battery 140 with power to be consumed by the power load 120 during the planned power outage. The required charge amount can be calculated by subtracting the remaining amount of the battery 140 from the required power.

In addition, the EMS server 160 calculates the predicted production power before the planned outage by referring to the production power predicted in step S230 (S256), and the required charge amount calculated in step S255 and before the planned outage calculated in step S256. The predicted production power is compared (S257).

If it is determined in step S257 that the required charge amount is smaller than the predicted production power before the planned outage (S257-Y), the EMS server 160 is a renewable energy generated by the renewable energy generation system 110, the battery 140 is The PCS 131 of the ESS 130 is controlled to be charged (S258).

When the required charge amount is completed in the battery 140 by performing step S258, the EMS server 160 may control the PCS 131 so that renewable energy is supplied to the power load 120.

On the other hand, if it is determined in step S257 that the required charge amount is more than the expected production power before the planned outage (S257-N), the EMS server 160 is a renewable energy and power grid 150 generated by the renewable energy generation system 110. The PCS 131 of the ESS 130 is controlled so that the battery 140 is charged with the energy supplied through the battery 140 (S259).

In operation S259, the amount of charge by energy supplied from the power grid 150 is preferably determined by subtracting the amount of charge required by the predicted production power before the planned outage from the required amount of charge.

Further, when the energy is supplied through the power grid 150, it is more preferable to determine and operate the power price at the lowest time period with reference to the hourly power price obtained / stored through step S218 of FIG. 3.

7. Electric power operation according to economic energy utilization measures

Hereinafter, operation S260 of FIG. 2 will be described in detail with reference to FIG. 7. 7 is a flowchart provided to a detailed description of the power operation process according to the economic energy utilization measures in the EMS server 160 when the planned outage is not scheduled.

As shown in FIG. 7, if it is determined that a planned power failure is not scheduled (S240 -N), the EMS server 160 generates a charge / discharge schedule for the battery 140 (S261). The charge / discharge schedule generated in step S261 is transferred from the EMS server 160 to the PCS 131 of the ESS 130.

The charge / discharge schedule in step S261 is based on the basic charge / discharge schedule obtained by the EMS server 160 through step S217 of FIG. 3, and the power consumption predicted in step S220 of FIG. 2 and in step S230 of FIG. 2. It can be generated by referring to the predicted production power.

Subsequently, when the discharge time according to the charge / discharge schedule generated in step S261 does not arrive (S262-N), the PCS 131 loads the renewable energy generated by the renewable energy generation system 110 into the power load 120. Or supply to the battery 140 to charge (S263).

On the contrary, when the discharge time according to the charge / discharge schedule generated in step S261 arrives (S262-Y), the PCS 131 is charged in the battery 140 and stored in the renewable energy generation system 110. The new renewable energy is supplied to the power load 120 (S264).

At this time, the PCS 131 supplies the energy remaining in the step S264 to the power grid 150 to obtain a profit from the surplus power sale (S265).

8. EMS  server

8 is a detailed block diagram of the EMS server 160 shown in FIG. As shown in FIG. 8, the EMS server 160 includes a communication unit 161, a processor 162, and a storage unit 163.

The communication unit 161 establishes and maintains a communication connection with the PCS 131, the power server 180, and the weather server 190, and transmits and receives information.

The processor 162 uses the information obtained through the communication unit 161 to estimate the power consumption at the power load 120 and to predict the production power at the renewable energy generation system 110.

In addition, the processor 162 establishes an appropriate energy utilization measure according to the planned outage guided by the power server 180 and controls the PCS 131 accordingly to operate the power.

The storage unit 163 is a storage medium in which information obtained through the communication unit 161 is stored and information predicted / calculated by the processor 162 is stored.

It goes without saying that the technical idea of the present invention can also be applied to a computer-readable recording medium having a computer program for performing the functions of the apparatus and method according to the present embodiment. In addition, the technical idea according to various embodiments of the present invention may be embodied in computer-readable code form recorded on a computer-readable recording medium. The computer-readable recording medium is any data storage device that can be read by a computer and can store data. For example, the computer-readable recording medium may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical disk, a hard disk drive, or the like. In addition, the computer readable code or program stored in the computer readable recording medium may be transmitted through a network connected between the computers.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention.

110: Renewable energy generation system
120: power load
130: Energy Storage System (ESS)
131: Power Conditioning System (PCS)
132: Battery Management System (BMS)
140: battery 150: power grid
160: EMS (Energy Management System) server
161: communication unit 162: processor
163: storage unit 170: power plant
180: power server 190: weather server

Claims (15)

Predicting power consumption at a load;
Predicting the production power in the renewable energy generation system; And
If the planned outage is scheduled, operating the power according to the energy utilization measures prepared for the planned outage with reference to the predicted power consumption and the predicted production power;
The power operation phase,
Determining a battery level when a planned power failure is scheduled;
Calculating the required power during the planned outage with reference to the predicted power consumption;
Calculating a required charging amount of the battery if the required power is larger than the remaining battery level;
Calculating a predicted production power before the planned outage by referring to the predicted production power; And
If the required charge amount is greater than the estimated production power before the planned outage, charging the battery with renewable energy and energy supplied through the grid;
Required charge amount
The amount of charge that must be charged to the battery to supply the battery with power for the load during a planned outage,
The charge of the battery by the energy supplied from the power grid,
A power management method characterized by determining the required amount of charge by subtracting the amount of charge by the predicted production power before the planned outage.
The method of claim 1,
Power consumption prediction step,
Obtaining past power consumption and recent power consumption;
Calculating the comparison error with respect to the power consumption by comparing the obtained power consumption with the recent power consumption; And
If the comparison error is within a threshold range, predicting future power consumption from past power consumption; power management method comprising a.
3. The method of claim 2,
Power consumption prediction step,
If the comparison error is outside the threshold range, compensating the past power consumption by adding or subtracting a compensation value to the past power consumption; And
Predicting future power consumption from the compensated past power consumption.
The method of claim 1,
Production power prediction phase,
Obtaining past weather, recent weather, and weather forecasts;
Comparing past weather with recent weather to calculate a comparison error for the weather; And
If the comparison error is within a critical range, reflecting the weather forecast in the past weather to predict future power generation; power management method comprising a.
5. The method of claim 4,
If the comparison error is outside the threshold range, compensating the past weather by adding or subtracting a compensation value to the past weather; And
Predicting future power generation by reflecting weather forecast on the compensated past weather; power management method further comprising.
The method of claim 1,
The power operation phase,
And supplying renewable energy to the load if the required power is less than or equal to the battery level.
The method according to claim 6,
The power operation phase,
If the required charge amount is smaller than the predicted production power before the planned outage, charging the battery with renewable energy.
8. The method of claim 7,
The power operation phase,
And supplying renewable energy to the load when the required amount of charge in the battery is completed.
delete The method of claim 1,
When the energy is supplied through the power grid,
Power management method characterized in that the time of the lowest power price is determined.
The method of claim 1,
The power operation phase,
If the power failure is not scheduled, generating a charge and discharge schedule of the battery and operating the power in accordance with the established energy utilization measures; power management method further comprising.
12. The method of claim 11,
The power operation phase,
If the discharge time according to the schedule has not arrived, supplying renewable energy to a load or charging the battery; And
When the discharge time according to the schedule arrives, the step of supplying the stored energy and renewable energy stored in the battery to the load; power management method characterized in that it further comprises.
13. The method of claim 12,
The power operation phase,
And supplying surplus energy to the electric power grid in the supplying step, and selling surplus power.
Predicting power consumption at a load;
Predicting the production power in the renewable energy generation system;
If the planned outage is scheduled, operating the power according to the energy utilization measures prepared for the planned outage with reference to the predicted power consumption and the predicted power consumption;
Determining whether an error occurs in at least one of the predicted power consumption and the predicted power consumption after the power operation; And
If it is determined that an error has occurred, feeding back the error such that the influence of the error is reflected in performing at least one of the next power consumption prediction and the production power prediction.
Predict the power consumption at the load, predict the production power in the renewable energy generation system, and if the planned outage is scheduled, refer to the estimated power consumption and the predicted production power to take measures for energy utilization in preparation for the planned outage. EMS (Energy Management System) to establish; And
Includes an ESS (Energy Storage System) that operates the power in accordance with the energy utilization measures established by the EMS,
EMS,
If a planned outage is planned, find out the battery level,
Based on the estimated power consumption, the required power during the planned outage is calculated,
If the power required is greater than the battery level, the required charge level must be charged to the battery in order to supply the battery with power to be consumed by the load during planned outages.
Based on the predicted production power, the estimated production power before the planned outage is calculated,
If the required charge is greater than the estimated production power before the planned outage, the battery is charged with renewable energy and energy supplied through the grid, but the battery charge by the energy supplied from the power grid is determined by the estimated production power before the planned outage. A power management system characterized by determining the amount of charge subtracted.

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