CN111106615A - Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device - Google Patents
Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device Download PDFInfo
- Publication number
- CN111106615A CN111106615A CN202010004628.4A CN202010004628A CN111106615A CN 111106615 A CN111106615 A CN 111106615A CN 202010004628 A CN202010004628 A CN 202010004628A CN 111106615 A CN111106615 A CN 111106615A
- Authority
- CN
- China
- Prior art keywords
- storage device
- battery energy
- energy storage
- electric heat
- heat storage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
Abstract
The invention relates to the technical field of power grid peak-valley difference adjustment, and provides a method for reducing power grid peak-valley difference based on a battery energy storage device and an electric heat storage device. Firstly, collecting data; then, calculating the peak shaving coefficients of the battery energy storage device and the electric heat storage device; secondly, judging the charging and discharging state of the battery energy storage device and the heat generation and release state of the electric heat storage device according to the difference value between the total output of the generator set at each time interval and the average load of the power grid at the time interval, and the total capacity and the residual capacity of the battery energy storage device and the electric heat storage device; finally, when peak clipping is needed, the discharging of the battery energy storage device and the heat release of the electric heat storage device are coordinated and planned according to the peak clipping power requirement of the power grid on the next day and the residual energy of the two devices; when the valley filling is needed, the charging of the battery energy storage device and the heating of the electric heat storage device are coordinated and planned according to the valley filling power requirement of the power grid on the next day and the residual capacities of the two devices. The method can effectively adjust the peak-valley difference of the power grid, consumes new energy as much as possible, and is flexible and economical.
Description
Technical Field
The invention relates to the technical field of power grid peak-valley difference adjustment, in particular to a method for reducing power grid peak-valley difference based on a battery energy storage device and an electric heat storage device.
Background
In order to ensure the power supply quality of the power grid, corresponding measures are required to be taken, and the peak-valley difference of the power grid is reduced. The existing method for reducing the peak-valley difference of the power grid mainly comprises the following steps: (1) and the peak-valley difference of the power grid is reduced by using the time-of-use electricity price and guiding consumption by using the peak-valley difference electricity price. The method has the defects that the consumption of new energy cannot be effectively promoted, and great energy waste is caused. (2) The peak-valley difference of the power grid is reduced by the application of energy storage technologies, such as battery energy storage technology, electric heat storage technology and ice (water) cold storage technology. The method has the disadvantages that in the existing method for reducing the peak-valley difference of the power grid by using the energy storage technology, only a single energy storage mode is usually adopted, and the energy storage is not flexible enough and the operation cost is high.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method for reducing the peak-valley difference of a power grid based on a battery energy storage device and an electric heat storage device, which can effectively adjust the peak-valley difference of the power grid, can consume new energy as much as possible, and is flexible and economical.
The technical scheme of the invention is as follows:
a method for reducing peak-to-valley difference of a power grid based on a battery energy storage device and an electric heat storage device is characterized by comprising the following steps:
step 1: collecting data: collecting power grid next-day prediction data, wherein the power grid next-day prediction data comprise the next-day average temperature T and the next-day average temperature reference value T of the place where the power grid is located1The relative humidity H of the air in the next day and the reference value H of the relative humidity of the air in the next day1The next day atmospheric pressure P and the next day atmospheric pressure reference value P1And the temperature T of the battery energy storage devicecTemperature reference value T of battery energy storage devicec1Voltage U of battery energy storage devicecVoltage reference value U of battery energy storage devicec1η conversion efficiency of charging and discharging of battery energy storage devicecAnd temperature T of the electric heat storage deviceceTemperature reference value T of electric heat storage devicece1Voltage U of electric heat storage deviceceVoltage reference value U of electric heat storage devicece1Heat generation and release conversion efficiency η of electric heat storage deviceceAnd the system also comprises the capacity Q of the wind driven generator assembling machinefInstalled capacity Q of thermal generator sethTotal capacity S of battery energy storage deviceecResidual capacity S of battery energy storage deviceec_sTotal capacity S of electric heat storage devicercResidual capacity S of electric heat storage devicerc_s(ii) a Dividing the next day into n time intervals, and collecting the predicted power grid average load data of each time interval of the next day as { S }1,S2,...,Si,...,SnAnd the generated power data of the wind generating set at each time interval is (Q)f1,Qf2,...,Qfi,...,QfnPredicted value data of electric heating load of each time interval is { Q }r_1,Qr_2,...,Qr_i,...,Qr_n}；
Wherein S isiIs the average load of the i-th period, QfiFor the power generation of the wind generating set in the ith period, Qr_iThe predicted value of the electric heating load of the ith time interval;
step 2: calculating the peak regulation coefficient of the battery energy storage device and the electric heat storage device:
step 2.1: calculating the peak regulation coefficient A of the battery energy storage device1Is composed of
Wherein k isrThe influence coefficient, k, of the external operating environment of the power grid on the battery energy storage device next daycThe influence coefficient of the inside of the battery energy storage device in the next day of the power grid is obtained;
T*、H*、P*predicting the average temperature, the relative humidity and the unit value of the atmospheric pressure for the next day,
T*＝T/T1；H*＝H/H1；P*＝P/P1； (4)
Tc *、Uc *are the temperature of the battery energy storage device and the voltage per unit value of the battery energy storage device respectively,
Tc *＝Tc/Tc1；Uc *＝Uc/Uc1(5)
step 2.2: calculating the peak regulation coefficient A of the electric heat storage device2Is composed of
Wherein k isreInfluence coefficient, k, of the external environment on the electric heat storage device for the next day of operation of the power gridceInfluence coefficients inside the electric heat storage device for the next day of power grid operation;
Tce *、Uce *are the per unit values of the temperature of the electric heat storage device and the voltage of the electric heat storage device respectively,
Tce *＝Tce/Tce1；Uce *＝Uce/Uce1(9)
and step 3: judging the charging and discharging state of the battery energy storage device and the heat generation and release state of the electric heat storage device:
calculating the difference value of the predicted total output of the generator set in each time period of the next day and the average load of the power grid in the time period as
Sdi＝Qfi+Qh-Si(10)
When S isdi<When 0, the peak clipping is needed, and the step 4 is carried out: at this time, if Sec-Sec_sIf the voltage is more than 0, the battery energy storage device can discharge to participate in peak clipping, otherwise, the battery energy storage device does not discharge; if Src-Src_sIf the temperature is higher than 0, the electric heat storage device can release heat to participate in peak clipping, otherwise, the electric heat storage device does not release heat;
when S isdi>When 0, the valley is required to be filled, and the step 5 is carried out: at this time, if Sec_sIf the charging rate is more than 0, the battery energy storage device can be charged to participate in valley filling, otherwise, the battery energy storage device is not charged; if Src_sIf the temperature is more than 0, the electric heat storage device can heat to participate in valley filling, otherwise, the electric heat storage device does not heat;
and 4, step 4: calculating the total load power required to be peak-clipped at the next day, and coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device:
step 4.1: the total load power of the peak clipping required by the next day is calculated as
Wherein ε (x) is a unit step function, and x is Si-Qfi-Qh；
Calculating the total power of the electric heating load in the peak clipping period as
Step 4.2: and coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough power for peak clipping:
if it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough power for peak clipping:
if Sec-Sec_s≥QcdAnd Src-Src_s＜QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s≥QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s＜QcrOr Src-Src_s＜QcrAnd Sec-Sec_s＜Qcd *Or Sec-Sec_s＜QcdAnd Src-Src_s＜Qcr *The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
And 5: calculating the total load power amount of the next daily valley filling, coordinating and planning the charging of the battery energy storage device and the heating of the electric heat storage device:
step 5.1: calculating the total load power of the next daily valley filling
Wherein epsilon (t) is a unit step function, and t is Qfi+Qh-Si；
Step 5.2: coordinating and planning charging of the battery energy storage device and heating of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough capacity for filling the valley: the capacities of the battery energy storage device and the electric heat storage device which need to be provided during the next valley filling are planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough capacity for valley filling:
if Sec_s≥Qc_dAnd Src_s＜Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s≥Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s＜Qc_rOr Src_s＜Qc_rAnd Sec_s＜Qc_d *Or Sec_s＜Qc_dAnd Src_s＜Qc_r *The capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
The invention has the beneficial effects that:
the invention stores the redundant electric energy in the low ebb of the electric load by using the battery energy storage technology, releases the stored electric energy in a reasonable mode in the high ebb of the electric load of the power grid, and can cut peaks and fill valleys to reduce the peak-valley difference of the power grid; the rigid constraint of a cogeneration unit for determining electricity by heat is broken by utilizing the electric heat storage device, and the active balance of a power grid and heat supply can be effectively ensured; based on the coordinated operation of the battery energy storage device and the electric heat storage device in the power grid, the peak-valley difference of the power grid can be effectively adjusted, new energy is consumed as much as possible, the operation cost is reduced, the energy storage mode is flexible, the reliability of power supply of the power grid is guaranteed, and the quality of electric energy is guaranteed.
Drawings
Fig. 1 is a flow chart of a method for reducing grid peak-to-valley difference based on a battery energy storage device and an electric heat storage device according to the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and specific embodiments.
In this embodiment, the method of the present invention is used to perform peak shaving in an area having a battery energy storage peak shaving device and an electric heat storage peak shaving device.
As shown in fig. 1, the method for reducing the peak-to-valley difference of the power grid based on the battery energy storage device and the electric heat storage device of the present invention comprises the following steps:
step 1: collecting data: collecting power grid next-day prediction data, wherein the power grid next-day prediction data comprise the next-day average temperature T of the place where the power grid is located being 25 ℃ and the next-day average temperature reference value T122 deg.C, relative humidity H of air of next day 0.6, and relative humidity reference value H of air of next day10.5, 96.0KPa, and reference value P1100.0KPa, and the temperature T of the battery energy storage devicecThe temperature of the battery energy storage device is 28.5 ℃ and the temperature reference value Tc1Voltage U of battery energy storage device at 25 DEG Cc385V, voltage reference value U of battery energy storage devicec1380V, charge-discharge conversion efficiency η of battery energy storage devicec0.95 and temperature T of the electric heat storage devicece38 ℃ reference value T of the electric heat storage devicece1Voltage U of 35 deg.C electric heat storage devicece383V, voltage reference value U of the electric heat storage devicece1380V heat generation and release conversion efficiency η of electric heat storage devicece0.86, and the capacity Q of the wind driven generator assembling machinef30MW capacity Q of assembling machine of thermal power generatorh60MW total capacity S of battery energy storage deviceec180MW, residual capacity S of battery energy storage deviceec_sTotal capacity S of electric heat storage device of 120MWrcResidual capacity S of 200MW electric heat storage devicerc_s80 MW; dividing the next day into n-24 time periods, and collecting predicted power grid average load data { S) of each time period of the next day1,S2,...,Si,...,S24The generated power data (Q) of the wind generating set at each time interval is shown in the table 1f1,Qf2,...,Qfi,...,Qf24As shown in table 2, the predicted value data of the electric heating load at each time interval is { Q }r_1,Qr_2,...,Qr_i,...,Qr_24As shown in table 3; wherein S isiIs the average load of the i-th period, QfiFor the power generation of the wind generating set in the ith period, Qr_iIs the ithAnd predicting the electric heating load of each time interval.
TABLE 1
TABLE 2
TABLE 3
Step 2: calculating the peak regulation coefficient of the battery energy storage device and the electric heat storage device:
step 2.1: calculating the peak regulation coefficient A of the battery energy storage device1Is composed of
Wherein k isrThe influence coefficient, k, of the external operating environment of the power grid on the battery energy storage device next daycThe influence coefficient of the inside of the battery energy storage device in the next day of the power grid is obtained;
T*、H*、P*predicting the average temperature, the relative humidity and the unit value of the atmospheric pressure for the next day,
T*＝T/T1；H*＝H/H1；P*＝P/P1； (4)
Tc *、Uc *respectively storing energy for temperature and battery of battery energy storage deviceThe per unit value of the voltage of the device,
Tc *＝Tc/Tc1；Uc *＝Uc/Uc1(5)
in the present embodiment, the first and second electrodes are,
T*＝T/T1＝25/22＝1.136；
S*＝S/S1＝0.6/0.5＝1.2；
P*＝P/P1＝96/100＝0.96；
Tc *＝Tc/Tc1＝28.5/25＝1.14；
Uc *＝Uc/Uc1＝385/380＝1.013
step 2.2: calculating the peak regulation coefficient A of the electric heat storage device2Is composed of
Wherein k isreInfluence coefficient, k, of the external environment on the electric heat storage device for the next day of operation of the power gridceInfluence coefficients inside the electric heat storage device for the next day of power grid operation;
Tce *、Uce *are the per unit values of the temperature of the electric heat storage device and the voltage of the electric heat storage device respectively,
Tce *＝Tce/Tce1；Uce *＝Uce/Uce1(9)
in the present embodiment, the first and second electrodes are,
Tce *＝Tce/Tce1＝38/35＝1.086；
Uce *＝Uce/Uce1＝383/380＝1.008
and step 3: judging the charging and discharging state of the battery energy storage device and the heat generation and release state of the electric heat storage device:
calculating the difference value of the predicted total output of the generator set in each time period of the next day and the average load of the power grid in the time period as
Sdi＝Qfi+Qh-Si(10)
When S isdi<When 0, the peak clipping is needed, and the step 4 is carried out: at this time, if Sec-Sec_sIf the voltage is more than 0, the battery energy storage device can discharge to participate in peak clipping, otherwise, the battery energy storage device does not discharge; if Src-Src_sIf the temperature is higher than 0, the electric heat storage device can release heat to participate in peak clipping, otherwise, the electric heat storage device does not release heat;
when S isdi>When 0, the grain needs to be filled,entering a step 5: at this time, if Sec_sIf the charging rate is more than 0, the battery energy storage device can be charged to participate in valley filling, otherwise, the battery energy storage device is not charged; if Src_sIf the temperature is more than 0, the electric heat storage device can heat to participate in valley filling, otherwise, the electric heat storage device does not heat.
In this embodiment, the difference between the predicted total output of the generator set in each time period of the next day and the average load of the power grid in the time period is calculated and obtained as shown in table 4.
TABLE 4
As can be seen from Table 4, S is measured from the 1 st period to the 9 th period, and from the 23 rd period to the 24 th perioddi>0, needing to perform grain filling; in the 10 th to 22 th periods, Sdi<0, peak clipping is required.
And 4, step 4: calculating the total load power amount of the peak clipping required in the next day, coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device, and ensuring the power required by the peak clipping:
step 4.1: the total load power of the peak clipping required by the next day is calculated as
Wherein ε (x) is a unit step function, and x is Si-Qfi-Qh；
Calculating the total power of the electric heating load in the peak clipping period as
Step 4.2: and coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough power for peak clipping:
if it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough power for peak clipping:
if Sec-Sec_s≥QcdAnd Src-Src_s＜QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s≥QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s＜QcrOr Src-Src_s＜QcrAnd Sec-Sec_s＜Qcd *Or Sec-Sec_s＜QcdAnd Src-Src_s＜Qcr *Planning the next day of peak clippingThe power required to be provided by the battery energy storage device and the electric heat storage device is respectively
In this embodiment, the total load power obtained by calculating the peak clipping required next day is Sxz146.53MW, the total power of the electric heating load in the peak clipping period is Qdre＝179.75MW；
When the battery energy storage device and the electric heat storage device can provide enough power for peak clipping, the power required to be provided by the battery energy storage device and the electric heat storage device is respectively the power required to be provided by the battery energy storage device and the electric heat storage device when the peak clipping of the next day is planned
However, in this case, the total stored power is Sec-Sec_s＝60MW＜QcdAnd the total amount of heat storage power Src-Src_s＝120MW≥QcrTherefore, the battery energy storage device can not provide enough power, and the electric heat storage device can provide enough power, so the formula (16) is selected for calculation, and the output of the battery energy storage device and the output of the electric heat storage device which are planned during peak clipping of the next day are obtained
And 5: calculating the total load power amount of the next daily valley filling, coordinating and planning the charging of the battery energy storage device and the heating of the electric heat storage device:
step 5.1: calculating the total load power of the next daily valley filling
Wherein epsilon (t) is a unit step function, and t is Qfi+Qh-Si；
Step 5.2: coordinating and planning charging of the battery energy storage device and heating of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough capacity for filling the valley: the capacities of the battery energy storage device and the electric heat storage device which need to be provided during the next valley filling are planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough capacity for valley filling:
if Sec_s≥Qc_dAnd Src_s＜Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s≥Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s＜Qc_rOr Src_s＜Qc_rAnd Sec_s＜Qc_d *Or Sec_s＜Qc_dAnd Src_s＜Qc_r *The capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
In this embodiment, the total load power calculated to obtain the next daily valley filling is Stz208.27 MW; when the battery energy storage device and the electric heat storage device are bothWhen enough capacity is provided for filling the valley, the capacities required to be provided by the battery energy storage device and the electric heat storage device are respectively Q when the valley is filled in the next dayc_d＝91.22MW，Qc_r＝96.53MW
But at this time, the remaining capacity S of the battery energy storage deviceec_s＝120MW≥Qc_dAnd the residual capacity S of the electric heat storage devicerc_s＝80MW＜Qc_rTherefore, the battery energy storage device can provide enough capacity, but the electric heat storage device can not provide enough capacity, so the formula (20) is selected for calculation, and the capacities required to be provided by the battery energy storage device and the electric heat storage device which are planned during the next valley filling of the day are obtained respectively
It is to be understood that the above-described embodiments are only a few embodiments of the present invention, and not all embodiments. The above examples are only for explaining the present invention and do not constitute a limitation to the scope of protection of the present invention. All other embodiments, which can be derived by those skilled in the art from the above-described embodiments without any creative effort, namely all modifications, equivalents, improvements and the like made within the spirit and principle of the present application, fall within the protection scope of the present invention claimed.
Claims (1)
1. A method for reducing peak-to-valley difference of a power grid based on a battery energy storage device and an electric heat storage device is characterized by comprising the following steps:
step 1: collecting data: collecting power grid next-day prediction data, wherein the power grid next-day prediction data comprise the next-day average temperature T and the next-day average temperature reference value T of the place where the power grid is located1The relative humidity H of the air in the next day and the reference value H of the relative humidity of the air in the next day1The next day atmospheric pressure P and the next day atmospheric pressure reference value P1And the temperature T of the battery energy storage devicecTemperature reference value T of battery energy storage devicec1Voltage U of battery energy storage devicecVoltage reference value U of battery energy storage devicec1Charging and discharging of battery energy storage deviceElectrical conversion efficiency ηcAnd temperature T of the electric heat storage deviceceTemperature reference value T of electric heat storage devicece1Voltage U of electric heat storage deviceceVoltage reference value U of electric heat storage devicece1Heat generation and release conversion efficiency η of electric heat storage deviceceAnd the system also comprises the capacity Q of the wind driven generator assembling machinefInstalled capacity Q of thermal generator sethTotal capacity S of battery energy storage deviceecResidual capacity S of battery energy storage deviceec_sTotal capacity S of electric heat storage devicercResidual capacity S of electric heat storage devicerc_s(ii) a Dividing the next day into n time intervals, and collecting the predicted power grid average load data of each time interval of the next day as { S }1,S2,...,Si,...,SnAnd the generated power data of the wind generating set at each time interval is (Q)f1,Qf2,...,Qfi,...,QfnPredicted value data of electric heating load of each time interval is { Q }r_1,Qr_2,...,Qr_i,...,Qr_n}；
Wherein S isiIs the average load of the i-th period, QfiFor the power generation of the wind generating set in the ith period, Qr_iThe predicted value of the electric heating load of the ith time interval;
step 2: calculating the peak regulation coefficient of the battery energy storage device and the electric heat storage device:
step 2.1: calculating the peak regulation coefficient A of the battery energy storage device1Is composed of
Wherein k isrThe influence coefficient, k, of the external operating environment of the power grid on the battery energy storage device next daycThe influence coefficient of the inside of the battery energy storage device in the next day of the power grid is obtained;
T*、H*、P*predicting the average temperature, the relative humidity and the unit value of the atmospheric pressure for the next day,
T*＝T/T1；H*＝H/H1；P*＝P/P1； (4)
Tc *、Uc *are the temperature of the battery energy storage device and the voltage per unit value of the battery energy storage device respectively,
Tc *＝Tc/Tc1；Uc *＝Uc/Uc1(5)
step 2.2: calculating the peak regulation coefficient A of the electric heat storage device2Is composed of
Wherein k isreInfluence coefficient, k, of the external environment on the electric heat storage device for the next day of operation of the power gridceInfluence coefficients inside the electric heat storage device for the next day of power grid operation;
Tce *、Uce *are the per unit values of the temperature of the electric heat storage device and the voltage of the electric heat storage device respectively,
Tce *＝Tce/Tce1；Uce *＝Uce/Uce1(9)
and step 3: judging the charging and discharging state of the battery energy storage device and the heat generation and release state of the electric heat storage device:
calculating the difference value of the predicted total output of the generator set in each time period of the next day and the average load of the power grid in the time period as
Sdi＝Qfi+Qh-Si(10)
When S isdi<When 0, the peak clipping is needed, and the step 4 is carried out: at this time, if Sec-Sec_sIf the voltage is more than 0, the battery energy storage device can discharge to participate in peak clipping, otherwise, the battery energy storage device does not discharge; if Src-Src_sIf the temperature is higher than 0, the electric heat storage device can release heat to participate in peak clipping, otherwise, the electric heat storage device does not release heat;
when S isdi>When 0, the valley is required to be filled, and the step 5 is carried out: at this time, if Sec_sIf the charging rate is more than 0, the battery energy storage device can be charged to participate in valley filling, otherwise, the battery energy storage device is not charged; if Src_sIf the temperature is more than 0, the electric heat storage device can heat to participate in valley filling, otherwise, the electric heat storage device does not heat;
and 4, step 4: calculating the total load power required to be peak-clipped at the next day, and coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device:
step 4.1: the total load power of the peak clipping required by the next day is calculated as
Wherein ε (x) is a unit step function, and x is Si-Qfi-Qh；
Calculating the total power of the electric heating load in the peak clipping period as
Step 4.2: and coordinating and planning the discharge of the battery energy storage device and the heat release of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough power for peak clipping:
if it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If it is
The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough power for peak clipping:
if Sec-Sec_s≥QcdAnd Src-Src_s＜QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s≥QcrThe power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
If Sec-Sec_s＜QcdAnd Src-Src_s＜QcrOr Src-Src_s＜QcrAnd Sec-Sec_s＜Qcd *Or Sec-Sec_s＜QcdAnd Src-Src_s＜Qcr *The power needed to be provided by the battery energy storage device and the electric heat storage device during peak clipping of the next day is planned to be respectively
And 5: calculating the total load power amount of the next daily valley filling, coordinating and planning the charging of the battery energy storage device and the heating of the electric heat storage device:
step 5.1: calculating the total load power of the next daily valley filling
Wherein epsilon (t) is a unit step function, and t is Qfi+Qh-Si；
Step 5.2: coordinating and planning charging of the battery energy storage device and heating of the electric heat storage device:
when the battery energy storage device and the electric heat storage device can provide enough capacity for filling the valley: the capacities of the battery energy storage device and the electric heat storage device which need to be provided during the next valley filling are planned to be respectively
When the battery energy storage device and the electric heat storage device can not provide enough capacity for valley filling:
if Sec_s≥Qc_dAnd Src_s＜Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s≥Qc_rThe capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
If Sec_s＜Qc_dAnd Src_s＜Qc_rOr Src_s＜Qc_rAnd Sec_s＜Qc_d *Or Sec_s＜Qc_dAnd Src_s＜Qc_r *The capacities of the battery energy storage device and the electric heat storage device are planned to be provided respectively during the next valley filling
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010004628.4A CN111106615B (en) | 2020-01-03 | 2020-01-03 | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010004628.4A CN111106615B (en) | 2020-01-03 | 2020-01-03 | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111106615A true CN111106615A (en) | 2020-05-05 |
| CN111106615B CN111106615B (en) | 2023-03-31 |
Family
ID=70425833
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010004628.4A Active CN111106615B (en) | 2020-01-03 | 2020-01-03 | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111106615B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012039686A (en) * | 2010-08-04 | 2012-02-23 | Hitachi Ltd | System operation method using storage battery |
| CN107834580A (en) * | 2017-10-20 | 2018-03-23 | 国网辽宁省电力有限公司 | One kind reduces network load peak valley difference method based on battery energy storage |
| CN107846032A (en) * | 2017-10-27 | 2018-03-27 | 国网辽宁省电力有限公司 | Low-valley interval electric heat accumulation and battery energy storage coordinated operation method on a large scale |
| CN108039736A (en) * | 2017-11-14 | 2018-05-15 | 国网辽宁省电力有限公司 | A kind of large capacity heat accumulation storing up electricity coordinated scheduling method for improving wind-powered electricity generation and receiving ability |
| WO2018200854A1 (en) * | 2017-04-27 | 2018-11-01 | Johnson Controls Technology Company | Building energy system with predictive control |
| CN108808659A (en) * | 2018-06-05 | 2018-11-13 | 国网吉林省电力有限公司 | The coordination optimization of wind electricity digestion integrated energy system controls and economic evaluation method |
| CN109378842A (en) * | 2018-11-01 | 2019-02-22 | 国网辽宁省电力有限公司电力科学研究院 | Electric heat accumulation load and battery energy storage, which are coordinated to maximize, reduces peak valley difference method |
| CN208534687U (en) * | 2018-07-10 | 2019-02-22 | 江卫 | A kind of hot energy storage --- the wind power balance and stability system of power generation two stage cycle |
| US20190206000A1 (en) * | 2017-01-12 | 2019-07-04 | Johnson Controls Technology Company | Building energy storage system with multiple demand charge cost optimization |
-
2020
- 2020-01-03 CN CN202010004628.4A patent/CN111106615B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012039686A (en) * | 2010-08-04 | 2012-02-23 | Hitachi Ltd | System operation method using storage battery |
| US20190206000A1 (en) * | 2017-01-12 | 2019-07-04 | Johnson Controls Technology Company | Building energy storage system with multiple demand charge cost optimization |
| WO2018200854A1 (en) * | 2017-04-27 | 2018-11-01 | Johnson Controls Technology Company | Building energy system with predictive control |
| CN107834580A (en) * | 2017-10-20 | 2018-03-23 | 国网辽宁省电力有限公司 | One kind reduces network load peak valley difference method based on battery energy storage |
| CN107846032A (en) * | 2017-10-27 | 2018-03-27 | 国网辽宁省电力有限公司 | Low-valley interval electric heat accumulation and battery energy storage coordinated operation method on a large scale |
| CN108039736A (en) * | 2017-11-14 | 2018-05-15 | 国网辽宁省电力有限公司 | A kind of large capacity heat accumulation storing up electricity coordinated scheduling method for improving wind-powered electricity generation and receiving ability |
| CN108808659A (en) * | 2018-06-05 | 2018-11-13 | 国网吉林省电力有限公司 | The coordination optimization of wind electricity digestion integrated energy system controls and economic evaluation method |
| CN208534687U (en) * | 2018-07-10 | 2019-02-22 | 江卫 | A kind of hot energy storage --- the wind power balance and stability system of power generation two stage cycle |
| CN109378842A (en) * | 2018-11-01 | 2019-02-22 | 国网辽宁省电力有限公司电力科学研究院 | Electric heat accumulation load and battery energy storage, which are coordinated to maximize, reduces peak valley difference method |
Non-Patent Citations (3)
| Title |
|---|
| 孟娅等: "电池储能参与配电网削峰填谷的变功率控制策略", 《电力建设》 * |
| 王振浩等: "考虑风电消纳的风电-电储能-蓄热式电锅炉联合系统能量优化", 《中国电机工程学报》 * |
| 邵竑湄等: "单相分时电能表常见故障及改进措施", 《供用电》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111106615B (en) | 2023-03-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lee et al. | Determination of optimal contract capacities and optimal sizes of battery energy storage systems for time-of-use rates industrial customers | |
| JP3740099B2 (en) | Power network management system and power network management method | |
| JP2003032890A (en) | Load power controller | |
| Gbadega et al. | Impact of incorporating disturbance prediction on the performance of energy management systems in micro-grid | |
| JP5793572B2 (en) | Peak cut control device | |
| CN112886645A (en) | New energy power system operation simulation method based on hydrogen energy super-high proportion | |
| KR102240556B1 (en) | Methods and apparatuses for operating power generator combined with heterogeneous renewable energy | |
| CN111106615B (en) | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device | |
| CN112101632B (en) | Building load optimal scheduling method based on distributed estimation algorithm | |
| CN113159423A (en) | Multi-energy combined optimization scheduling operation method based on wind, fire and light storage coordination | |
| CN109378842B (en) | Method for reducing peak-valley difference by coordinating and maximizing electric heat storage load and battery energy storage | |
| CN116644994A (en) | Energy storage comprehensive value evaluation method and system considering battery aging | |
| CN116914785A (en) | Optimized operation method of electrothermal hydrogen system | |
| CN112952915B (en) | Optimized scheduling method for stabilizing peak and valley of power grid in comprehensive energy system | |
| CN115189423A (en) | Multi-energy coordination optimization scheduling method and device for wind-fire storage system | |
| CN115081700A (en) | Comprehensive energy storage technology-based data center multi-energy collaborative optimization method and system | |
| CN115169973A (en) | Regional comprehensive energy optimization scheduling method and system based on hydrogen storage device | |
| CN115187018A (en) | Double-layer optimized scheduling method and device for park comprehensive energy system | |
| JP2002048004A (en) | Heat/electric power cogenerating device and environment control room using the same | |
| JP6280736B2 (en) | Energy management system and energy management method | |
| CN111740444A (en) | Wind power acceptance regulation and control method considering power grid short-time operation state | |
| CN116914860B (en) | Power supply capacity configuration optimization method and system for multi-energy complementary power generation system | |
| CN113517691B (en) | Multi-type power supply cooperative scheduling method based on peak-valley time-of-use electricity price | |
| CN113517709B (en) | Control and management method for household electric energy storage system | |
| WO2023238711A1 (en) | Renewable energy electric power generation system and method for charging electric power storage device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |