Energy management device and energy management method

The present invention pertains to an energy management device 50 of a microgrid S1 which is associated with a power system 1 and is provided with a power storage device 15, the energy management device calculating a target value of received power of the microgrid, the target value optimizing the utilization efficiency of the energy of the microgrid S1, on the basis of power demand prediction in the microgrid S1 by taking, as constraint conditions, the upper and lower limits of the received power of the microgrid S1 and the upper and lower limits of output power of the power storage device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a national stage application, filed under 35 U.S.C. § 371, of International Application No. PCT/JP2020/037140, filed Sep. 30, 2020, which claims priority to Japan Application No. 2019-185021, filed Oct. 8, 2019, the contents of both of which as are hereby incorporated by reference in their entirety.

BACKGROUND

Technical Field

The present invention relates to energy management of a microgrid.

Description of Related Art

Introduction of a distributed power supply typified by a photovoltaic (PV) power generation system has been advanced from the viewpoint of reduction of dependence on a fossil fuel and an environmental problem. A PV system converts power generated by a solar power generation panel from a direct current (DC) to an alternating current (AC) using an inverter circuit of a power control device, and outputs the AC.

Japanese Patent No. 4765162 discloses a technique for controlling second power conversion means such that received power detected by received power detection means does not fall below predetermined power during output of both the generated power of the distributed power supply and the power from power storage means in the power storage type solar power generation system. Thus, the power from the power storage means is prevented from flowing back to a power system.

BRIEF SUMMARY

An object of the present invention is to propose a method for efficiently operating energy in a microgrid connected to a power system.

One aspect of the present invention is an energy management device for a microgrid that is interconnected to a power system and includes an energy storage apparatus, the energy management device calculates a target value of received power of the microgrid, the target value of the received power optimizing energy use efficiency of the microgrid, based on a supply and demand prediction of power in the microgrid with upper and lower limits of received power of the microgrid and upper and lower limits of output power of the energy storage apparatus as constraint conditions. The energy use efficiency means whether the energy can be efficiently used, and an energy saving effect increases as the energy use efficiency increases.

The one aspect of the present invention can be applied to a microgrid energy management method.

The energy can be efficiently operated in the microgrid.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

An energy management device for a microgrid that is interconnected to a power system and includes an energy storage apparatus, wherein the energy management device calculates a target value of received power of the microgrid, the target value of the received power optimizing energy use efficiency of the microgrid, based on a supply and demand prediction of power in the microgrid with upper and lower limits of received power of the microgrid and upper and lower limits of output power of the energy storage apparatus as constraint conditions.

In this configuration, the energy management device can calculate the target value of the received power optimizing the energy use efficiency of the microgrid. The energy management device can optimize the energy use efficiency of the microgrid by causing the received power of the microgrid to follow the calculated target value.

The energy management device may evaluate the energy use efficiency of the microgrid using an objective function. Using the objective function, the energy management device can quantify and objectively evaluate the energy use efficiency.

The objective function may be a function evaluating a use-restricted period of the energy storage apparatus. In this configuration, from the viewpoint of the use efficiency of the energy storage apparatus, the energy management device can optimize the energy use efficiency of the microgrid.

The objective function may be a function evaluating an electricity rate of the microgrid. In this configuration, the energy management device can optimize the energy use efficiency of the microgrid from the viewpoint of the electricity rate of the microgrid.

The objective function may be a function in which a term evaluating the use-restricted period of the energy storage apparatus and a term evaluating the electricity rate of the microgrid are added with weight. In this configuration, the energy management device can optimize the energy use efficiency of the microgrid from two viewpoints of the use efficiency of the energy storage apparatus and the electricity rate of the microgrid. Superiority and inferiority can be decided to the two viewpoints by the way of weighting.

The energy management device may add a condition of a change width of the received power of the microgrid to the constraint condition. In this configuration, the candidate of the target value is narrowed down to the change width of the received power. Thus, the number of arithmetic calculations required to obtain the optimum solution is reduced, and the arithmetic calculation speed can be increased. Because the energy management device can suppress the change in the received power to the change width, the influence on the power system is small and the energy management device is effective for maintaining the quality of electricity.

The energy management device may divide the prediction target period of the target value into a plurality of sections, and calculate the target value of the received power optimizing the energy use efficiency of the microgrid for each of the divided sections. When the prediction target period is divided into the plurality of sections, because the energy management device reduces the number of arithmetic calculations required to obtain the optimal solution as compared with the case where the arithmetic calculation is performed on all the sections, the arithmetic calculation can be accelerated.

The section may be longer than a cycle of the supply and demand prediction. In this configuration, the energy management device can determine the target value of the received power in consideration of the demand prediction of a plurality of cycles.

First Embodiment

A microgrid S is a small-scale power system linked to a power system1, and includes at least a distributed power supply, an energy storage apparatus, and a load. The power system1may be a power system of a power provider or an independent power system constituted by a self-sustained operation output of a large power conditioner.

FIG.1is a block diagram of the microgrid S1. The microgrid S1 includes a solar power generation panel10that is the distributed power supply, a storage battery15that is the energy storage apparatus, a power conditioner20that is the power control device, and a load L.

The power conditioner20includes a first converter circuit21that is a first power converter, a second converter circuit23that is a second power converter, a DC link unit25, a bidirectional inverter circuit31, a relay37, a control device50, a DC voltage detection unit27, an output current detection unit33, and an output voltage detection unit35.

The solar power generation panel10is connected to the first converter circuit21. The first converter circuit21is a DC/DC converter, and boosts and outputs an output voltage (DC) of the solar power generation panel10. The first converter circuit21may be a chopper.

The storage battery15is connected to the second converter circuit23. For example, the storage battery15is a secondary battery. The second converter circuit23is a bidirectional DC/DC converter that discharges and charges the storage battery15. The second converter circuit23may be a bidirectional chopper.

The solar power generation panel10and the storage battery15are connected in parallel to the DC link unit25through the first converter circuit21and the second converter circuit23.

The DC link unit25is located between a connection point24of the converter circuits and the bidirectional inverter circuit31. An electrolytic capacitor C1 is provided in the DC link unit25. The electrolytic capacitor C1 is provided so as to stabilize voltage Vdc of the DC link unit25.

The DC voltage detection unit27detects the voltage Vdc of the DC link unit25. The voltage Vdc of the DC link unit25detected by the DC voltage detection unit27is input to the control device50.

The bidirectional inverter circuit31is a bidirectional conversion circuit that selectively performs an inverse conversion (inverter) converting the DC into the AC and a forward conversion (converter) converting the AC into the DC. The bidirectional inverter circuit31is connected to the DC link unit25, and converts DC power input from the DC link unit25into AC power and outputs the AC power during reverse conversion operation. Particularly, power corresponding to voltage increased from a reference value in the DC link unit25by power generation of the solar power generation panel10is input to the bidirectional inverter circuit31. Consequently, the power corresponding to the voltage increased from the reference value is converted from the DC to the AC and output from the bidirectional inverter circuit31.

The storage battery15can store surplus power of the solar power generation panel10through the second converter circuit23. When the generated power of the solar power generation panel10is insufficient, the storage battery15can compensate for the shortage of the generated power by the discharge through the second converter circuit23.

The bidirectional inverter circuit31is connected to the power system1using the system power supply2as an AC power supply through a relay37.

The relay37is installed for interconnection with the power system1. The microgrid S1 can be interconnected to the power system1by closing the relay37.

The output current detection unit33detects output current Iinv of the bidirectional inverter circuit31. The output voltage detection unit35is located on an output side of the bidirectional inverter circuit31, and detects output voltage Vinv of the bidirectional inverter circuit31.

The output current Iinv of the bidirectional inverter circuit31detected by the output current detection unit33and the output voltage Vinv of the bidirectional inverter circuit31detected by the output voltage detection unit35are input to the control device50. The control device50calculates output power (active power) Pinv of the bidirectional inverter circuit31based on the output current Iinv and the output voltage Vinv of the bidirectional inverter circuit31. The output power Pinv is “positive” during the reverse conversion and “negative” during the forward conversion.

The load L that is a demand facility is connected to a power line (trunk line)5connecting the bidirectional inverter circuit31and the power system1through a branch line4. The power can be supplied to the load L from both the power conditioner20and the power system1.

A power receiving point3is a power supply point by the power system1, and is a boundary portion between the power system1and a premises (microgrid S1) as illustrated inFIG.1.

An external measuring instrument40such as an external transducer is provided in the power system1as an instrument detecting the power at the power receiving point3.

The external measuring instrument40includes a received current detection unit41and a system voltage detection unit43. The external measuring instrument40is installed corresponding to the power receiving point3, and the received current detection unit41detects a received current at the power receiving point3. The system voltage detection unit43detects the system voltage of the power system1.

The external measuring instrument40calculates the received power (effective power) PRCVbased on the received current and the system voltage. The received power PRCVdetected by the external measuring instrument40is input to the control device50. The received power PRCVcan be used to determine the state of a power flow (hereinafter, simply referred to as a flow). The external measuring instrument40is a measuring instrument that measures the received power PRCVof the power receiving point3.

In the received power PRCV, a forward flow (FIG.1: the flow of electricity from the power system1to the microgrid S1) is set to “positive”, and a reverse flow (FIG.2: the flow of electricity from the microgrid S1 to the power system1) is set to “negative”.

The control device50includes a CPU51that is an arithmetic unit and a memory53that is a storage. The memory53stores a program predicting supply and demand of the power of the microgrid S1 and a program calculating a target value of the received power PRCVoptimizing energy use efficiency of the microgrid S1. Data necessary for performing the supply and demand prediction and data necessary for calculating the target value of the received power PRCVoptimizing the energy use efficiency are stored. The CPU51calculates the target value of the received power PRCVoptimizing the energy use efficiency of the microgrid S1 based on the supply and demand prediction of the power of the microgrid S1. Power control of the microgrid S1 is performed such that the received power PRCVof the microgrid S1 follows the target value. The control device50is an example of the energy management device.

The control device50can give a command to the bidirectional inverter circuit31to control switching between the forward conversion operation and the reverse conversion operation. The output of the bidirectional inverter circuit31, namely, the output power Pinv can be controlled. The output power Pinv can be controlled by adjusting the output current Iinv.

The control device50can turning on and off the first converter circuit21to control connection and non-connection of the solar power generation panel10to and from the DC link unit25. The connection and disconnection of the storage battery15with respect to the DC link unit25can be controlled by turning on and off the second converter circuit23. The control device50can control switching between charge and discharge of the storage battery15through the second converter circuit23. The output power of the storage battery15can be controlled through the second converter circuit23. For example, the output power can be controlled by adjusting a current amount.

2. Supply and Demand Prediction of Power of Microgrid

The control device50predicts supply and demand of the power of the microgrid S1. Specifically, an electricity supply amount in the microgrid S1 (generated power of the distributed power supply) [kW] and an electricity demand amount in the microgrid S1 [kW] are predicted.

Because the microgrid S1 includes the solar power generation panel10as the distributed power supply, the generated power of the solar power generation panel10is the electricity supply amount of the microgrid S1. Because the microgrid S1 has the load L, power consumption PLOADof the load L is the electricity demand amount.

Generated power PPVof the solar power generation panel10has a correlation with a solar radiation amount X as illustrated inFIG.3. The prediction value of the generated power PPVcan be obtained from a prediction data providing spot70through a network NW. The prediction data providing spot70may be a provider by a providing spot of the power conditioner20or a providing spot of a power generation company. The generated power PPVof the solar power generation panel10is converted into the AC by the bidirectional inverter circuit31. Conversion efficiency η is conversion efficiency of the inverter circuit31when the DC is converted into the AC.

The power consumption PLOADof the load L can be predicted from past data. For example, the power consumption of the next day can be predicted by statistically processing the data of the power consumption PLOADfor several days.

The power consumption PLOADof the load L can be obtained from the received power PRCVof the power receiving point3and the output power Pinv of the bidirectional inverter circuit31. In the case of the forward current (PRCV>0), the power consumption PLOADof the load L is a sum of the output power Pinv and the received power PRCV. In the case of the reverse power flow (PRCV<0), the power consumption PLOADof the load L is a difference between the output power Pinv and the received power PRCV.
PLOAD=Pinv+PRCV(A)
PLOAD=Pinv−PRCV(B)

FIG.4is a graph illustrating a supply and demand prediction result of the power of the microgrid S1. A broken line is the prediction value of the generated power of the microgrid S1, and a solid line is the prediction value of the power consumption of the microgrid S1. In this example, the power supply and demand prediction is performed every hour with a prediction target period T as one day, and the prediction value is a stepwise waveform in which the value changes every hour. The supply and demand prediction of the power of the microgrid S1 may be performed by the control device50, or the data predicted by another device may be obtained.

3. Optimization of Receiving Power Target Value Based on Supply and Demand Prediction of Power

FIG.5is a simple block diagram of the microgrid S1. The CPU51of the control device50calculates a target value (hereinafter, referred to as a received power target value PRCVreft) of the received power PRCVoptimizing the energy use efficiency of the microgrid S1 based on the power supply and demand prediction (FIG.4) of the microgrid S1.

An equation 1 is an objective function evaluating the energy use efficiency of the microgrid S1.

A first term and a second term of the objective function F are terms evaluating the use-restricted period of the storage battery15. A third term and a fourth term are terms evaluating the electricity rate of the microgrid S1.

The use-restricted period includes two periods including a charge-restricted period TMAXand a discharge-restricted period TMIN. The charge-restricted period TMAXis a period during which the charge is restricted, and for example, is the case where a state of charge SOC of the storage battery15is located at the upper limit of the use range (in the case of full charge). The discharge-restricted period TMINis a period during which the discharge is restricted, and for example, is the case where the state of charge SOC of the storage battery15is located at a lower limit of the use range.

In this example, k1>k2>k3>k4is satisfied, and the evaluation of the use-restricted period of the storage battery15is prioritized in the evaluation of the energy use efficiency of the microgrid S1. k1=k2and k3=k4may be satisfied.

When the arithmetic calculation optimizing a received power target value PRCVreftis performed, there are two conditions of an upper limit and a lower limit (an equation 2) of the received power target value PRCVreftand an upper limit and a lower limit (an equation 3) of the output power [kW] of the storage battery15as constraint conditions.
−PCSCAP≤PRCVref t≤PPCSCAP(t∈T)  [Mathematical formula 2]
−PBATCAP≤(PLOAD t−PRCVref t−PPV t·η)≤PBATCAP(t∈T)  [Mathematical formula 3]

TABLE 1TSet of total time section t (prediction target period)TMAX(PRCVref t,Charge-restricted period in time section tPPV t, PLOAD t)TMIN(PRCVref t,Discharge-restricted period in time section tPPV t, PLOAD t)PRCV(PRCVref t,Received power estimated value in time section t [kW]PPV t, PLOAD t)PPEAKReceived power peak value of prediction target periodT [kW]k1~k4Weighting factorPRCVref tReceived power target value in time section t [kW]PPV tGeneration power prediction value of PV panel in timesection t [kW]PLOAD tPower consumption prediction value of load in timesection t [kW]PPCSCAPPower conditioner rated capacity [kW]ηConversion efficiency [%]PBATCAPStorage battery rated charge-discharge power [kW]

The state-of-charge SOC is a ratio of a charge amount to a rated capacity of the storage battery15. In order to calculate the objective function F, the state of charge SOC of the storage battery15is required to be estimated. A method of simulating the state of charge SOC of the storage battery15and the estimated value of received power PRCVtwill be described below.

A method for calculating the charge-restricted period TMAXand discharge-restricted period TMINin a time section t will be described.

A provisional output power prediction value PBATtmp tof the storage battery15at the time section t is calculated from an equation 4 and an equation 5.

From an equation 6 to an equation 9, a provisional state-of-charge prediction value SOCtmp tof the storage battery15in the time section t is calculated.

The presence or absence of deviation from the upper and lower limits in the time section t is determined, and the state-of-charge prediction value SOCtof the storage battery15, the output power PBAT tof the storage battery15, the charge-restricted period TMAX, and the discharge-restricted period TMINare determined.

Subsequently, an initial value (in the case of t=0) of the charge amount prediction value WhBATtof the storage battery15can be obtained from equations 16, 17.
WhBAT 0=SOCIN1×BATCAP  [Mathematical formula 16]
WhBAT t=WhBAT 0−PBAT t×hour  [Mathematical formula 17]

Subsequently, the charge amount prediction value WhBAT tof the storage battery15can be obtained for each time section (when t≠0) by an equation 18. The prediction value SOCtof the state of charge SOC of the storage battery15can be obtained from an equation 19.

The received power prediction value PRCVat the time section t can be calculated from equations 20, 21.

A receiving power peak prediction value PPEAKin the prediction target period T can be calculated from an equation 22.
PPEAK=PRCV(PRCVref t,PPV t,PLOAD t) ifPPEAK_old≤PRCV(PRCVref t,PPV t,PLOAD t) (however, att=0,PPEAK_old=PPEAK IN1)  [Mathematical formula 22]

TABLE 2PBATtmp tProvisional output power prediction value of storage batteryin time section t [kW]WhBAT t−1Storage battery charge amount in previous time section t − 1[kWh]WhBATtmp tProvisional charge amount prediction value of storagebattery in time section t [kWh]SOCINIStorage battery charge state initial value in prediction targetperiod T [%]BATCAPStorage battery rated capacity [kWh]hourPitch width [h]SOCtmp tProvisional charge state prediction value of storage batteryin time section t [%]SOCMAXStorage battery charge state upper limit [%]SOCMINStorage battery charge state lower limit [%]PBAT tStorage battery output power prediction value in timesection t [kw]WhBAT tStorage battery charge amount prediction value in timesection t [kwh]SOCtStorage battery charge state prediction value in time sectiont [%]PPEAK_oldPeak power until previous time section t − 1 in predictiontarget period T [kw]PPEAK INIPeak power initial value in prediction target period T [kw]

From equations 4 to 19, when the received power target value PRCVreftis determined with respect to a generated power prediction value PPVtand a power consumption prediction value PLOADtof the load L, a state of charge SOCtof the storage battery15can be estimated.

In each time section t, the control device50estimates the state of charge SOCtof the storage battery15using the received power target value PRCVreftas a variable, and calculates four terms of the objective function F from the result.

Such an operation is performed (twenty-four cycles are executed when the prediction target period T is one day and when the arithmetic cycle is one hour) in the prediction target period T. Then, when the values of the objective function F are compared to each other with respect to the pattern of the combination of the received power target values PRCVreft, the combination of the received power target values minimizing the objective function F, namely, the received power target value PRCVreftof each time section t can be determined for the prediction target period T.

FIGS.6and7are graphs in which a horizontal axis represents time [h], a left vertical axis represents power [kW], and a right vertical axis represents a state of charge [%]. Y1 (bold line) indicates a transition of the received power [kW], and Y2 indicates a transition of the generated power [kW]. Y3 represents a transition of the power consumption [kW] of the load, Y4 represents a transition of the output power [kW] of the storage battery, and Y5 (broken line) represents a transition of the state of charge [%] of the storage battery15.

FIG.6illustrates the case where the received power target value PRCVreftis determined by an empirical rule, andFIG.7illustrates the case where the received power target value PRCVreftis determined based on the objective function F.

When the received power target value PRCVreftis determined by the empirical rule (FIG.6), the state of charge SOC of the storage battery15is maintained around 100 [%] in the time zone of 16:00 to 18:00. For this reason, the storage battery15is required to restrict acceptance of the charge in the time zone of 16:00 to 18:00.

When the received power target value PRCVreftis determined based on the objective function F (FIG.7), the state of charge SOC of the storage battery15changes with a margin with respect to an SOC upper limit line Lim1 (SOC=100 [%]) and an SOC lower limit line Lim2 (SOC=10 [%]), and both the charge and the discharge are always possible. That is, when the received power target value PRCVreftis compared with the case of the empirical rule, the state of charge SOC is suppressed to be low in the time zone (A portion) of 16:00 to 18:00, and the point that the charge in this time zone is not limited is improved.

4. Power Control of Microgrid

The CPU51of the control device50controls the power of the microgrid S1 such that the received power PRCVof the microgrid S1 follows the received power target value PRCVreftcalculated using the objective function F.

For example, when a measurement value of the received power PRCVis lower than the received power target value PRCVreftduring the forward flow in the power receiving point3and the reverse conversion operation in the inverter circuit31, the output power of the storage battery15is narrowed to reduce the difference between the measurement value of the received power PRCVand the received power target value PRCVreft. When the measurement value of the received power PRCVis higher than the received power target value PRCVreft, the difference between the measurement value of the received power PRCVand the received power target value PRCVreftis reduced by increasing the output power of the storage battery15.

As described above, the received power PRCVof the microgrid S1 can follow the received power target value PRCVreftcalculated using the objective function F by adjusting the output of the storage battery15according to the difference between the measurement value of the received power PRCVand the target value.

The storage battery15compensates for the shortage of the power by charging the surplus power of the microgrid S1 and discharging the surplus power during the shortage of the power. When the use of the storage battery15is restricted, the surplus power cannot be stored and the energy is lost, so that the energy use efficiency of the microgrid S1 decreases.

In this configuration, the use-restricted period of the storage battery15can be minimized by obtaining the optimum value of the received power target value PRCVreftbased on the objective function F. Thus, the energy use efficiency of the microgrid S1 can be optimized from the viewpoint of the use efficiency of the storage battery15.

When the use-restricted period of the storage battery15is the minimum, it is possible to flexibly cope with a demand response (DR). That is, because the state of charge SOC of the storage battery15has the margin with respect to the upper and lower limits, both a raising DR and a lowering DR can be coped with.

The raising DR is a request for increasing the demand of electricity. The storage battery15is charged and used as the load, so that the raising DR can be coped with. The lowering DR is a request for increasing the supply of electricity. The storage battery15is discharged and used as a power supply, so that the lowering DR can be coped with.

Second Embodiment

In order to determine the optimum value of the received power target value PRCVreft, the state of charge SOC and the like of the storage battery15are required to be estimated by the number of candidates of the received power target value PRCVreftfor each time section t of the prediction target period T, and each term of the objective function F is required to be calculated. For example, in the case where the prediction target period T is one day and the number of time sections is twenty-four, when the received power target value PRCVreftis changed in the range of 0 to 10 [kW] in increments of 1 [kW], the total number of candidates of the received power target value PRCVreftis 1124=9.85×1024, and the arithmetic load increases in proportion to the total number of candidates.

In a second embodiment, the arithmetic load is reduced using the following two methods.(A) Constraint on change width of received power target value(B) Division of prediction target period T
(A) Will be Described.

Because there is a possibility that the change in the received power PRCVaffects the power quality of the power system1, desirably the change width is as small as possible. For this reason, as illustrated in an equation 23, the constraint is provided on the change width of the received power target value PRCVreftper time section t.
−ΔPRCVref≤(PRCVref t−PRCVref t-1)≤ΔPRCVref(t∈T) ΔPRCVref: Change width maximum value of received power target value[kW]  [Mathematical formula 23]

FIGS.8A and8Bare views illustrating a combination of candidates of the received power target value PRCVreft.FIG.8Aillustrates the case where the constraint is not provided on the change width of the received power target value PRCVreft, andFIG.8Billustrates the case where the maximum value of the change width of the received power target value PRCVreftis set to ±2 [kW].

The number of candidates of the received power target value PRCVreftper time section t is “11” when the constraint is not provided on the change width of the received power target value PRCVreft(in the case ofFIG.8A). On the other hand, the number of candidates of the received power target value PRCVreftper time section t is “4” when the maximum value of the change width of the received power target value PRCVreftis set to ±2 [kW] (in the case ofFIG.8B).

In this way, the constraint is provided on the change width of the received power target value PRCVreft, so that the number of candidates of the received power target value PRCVreftper time section t can be reduced to greatly reduce the arithmetic load. The influence on the power system1can be reduced, and the quality of electricity can be maintained.

(B) Will be Described.

The prediction target period T is divided into a plurality of sections ΔT. Then, each divided section ΔT is set to one prediction target period, and an optimum value of the received power target value PRCVreftof each time section t is determined using the objective function F.

For example, when the prediction target period T is one day, the prediction target period T is divided into four sections ΔT of ΔT1 to ΔT4 as illustrated inFIG.9. Then, the arithmetic calculation optimizing the received power target value PRCVreftis performed using the objective function F with each section ΔT as one prediction target period.

In this case, the received power target value PRCVreftin the entire prediction target period T is obtained by connecting the received power target values PRCVreftof the respective time sections t of the respective sections ΔT determined as the optimum values in time series.

When the prediction target section T is divided, the received power target value PRCVreftof the entire prediction target period T is calculated in a plurality of times. Thus, the number of combinations of candidates of the received power target value PRCVreftper one time is reduced, so that the arithmetic load can be greatly reduced.

The number of divisions N of the prediction target period T may be other than four, such as three divisions. The number of time sections of each section ΔT may or may not be the same. Each section ΔT may be longer than the cycle of the supply and demand prediction. In the example ofFIG.9, ΔT=6 hours and the cycle of the supply and demand prediction=1 hour.

OTHER EMBODIMENTS

The present invention is not limited to the embodiments described with reference to the above description and the drawings. For example, the following embodiments are also included in the technical scope of the present invention.

(1) In the first embodiment, the grid having the linear power line (trunk line)5is illustrated as an example of the microgrid S1. However, a grid having a circular power line (trunk line) may be used. A microgrid S2 inFIG.10includes a power line100having a circular shape. A solar power generation panel110and a wind power generator120are connected to the power line100through power converters115,125. A load130and a storage battery140are connected to the power line100. The power line100of the microgrid S2 is connected to the power system1through the interconnection line105.

The microgrid S2 includes a control device150. The control device150calculates the received power target value PRCVreftoptimizing the energy use efficiency of the microgrid S2 based on the supply and demand prediction of the microgrid S2. The control device150performs power control of the microgrid S2 such that the received power of the power receiving point3follows the calculated received power target value PRCVreft. Specifically, the received power PRCVof the power receiving point3is monitored based on the output of the meter160provided at the power receiving point3. When the difference exists with respect to the received power target value PRCVreft, the control device150charges or discharges the storage battery140through the power converter145to reduce the difference. In this way, the received power PRCVcan follow the calculated target value PRCVreft, and the energy use efficiency of the microgrid S2 can be optimized. The control device150is an example of the “energy management device” of the present invention.

The microgrid S2 includes the solar power generation panel10and the wind power generator120as distributed power supply. When the supply and demand prediction of the microgrid S2 is performed, the power supply amount of the microgrid S2 may be set to a total value of the generated power of each distributed power supply. In the case of a plurality of loads, the power demand amount of the microgrid S2 may be a total value of the loads. The distributed power supply is a generic term for all small-scale power generation facilities dispersedly disposed adjacent to a demand site. For example, the distributed power supply may be a biomass power generator or the like in addition to the solar power generation panel10and the wind power generator120. The distributed power supply may be a power source using renewable energy or a power source using fossil fuel.

(2) In the first embodiment, the objective function F includes four terms of the first term to the fourth term, and the four terms are multiplied by the weighting coefficients k1to k4and added. In the first embodiment, the magnitude relationship of the weighting factors is k1>k2>k3>k4. However, the magnitude relationship may be k3>k4>k1>k2. The electricity rate of the microgrid can be preferentially evaluated by reversing the magnitude relationship of the weighting factors, so that the energy use efficiency of the microgrid can be optimized from the viewpoint of the electricity rate. The objective function F may be only the first and second terms evaluating the use-restricted period of the storage battery15, or may be only the third and fourth terms evaluating the electricity rate of the microgrid. The objective function F may be any other function as long as the function optimizes the energy utilization efficiency of the microgrid.

(3) In the first embodiment, the arithmetic calculation obtaining the optimum value of the received power target value PRCVreftis performed by the control device50of the power conditioner20. An arithmetic subject is not limited to the power conditioner20, but may be an arithmetic device provided separately from the power conditioner20. The arithmetic device is an example of the energy management device.

(4) In the first embodiment, the optimum value of the received power target value PRCVreftis calculated using the objective function. However, for example, the optimum value of the received power target value PRCVreftmay be calculated using AI. Any method can be used when the target value of the received power of the microgrid optimizing the energy use efficiency of the microgrid based on the power supply and demand prediction in the microgrid, with the upper and lower limits of the received power of the microgrid and the upper and lower limits of the output power of the energy storage apparatus as constraint conditions. In the first embodiment, the storage battery is exemplified as the energy storage apparatus. However, the energy storage apparatus may be a capacitor or the like.