CN107482656B - Power planning method, device and equipment for microgrid and computer readable storage medium - Google Patents
Power planning method, device and equipment for microgrid and computer readable storage medium Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000003860 storage Methods 0.000 title claims abstract description 10
- 238000004146 energy storage Methods 0.000 claims abstract description 69
- 238000004364 calculation method Methods 0.000 claims abstract description 57
- 230000015654 memory Effects 0.000 claims description 24
- 238000004590 computer program Methods 0.000 claims description 9
- 238000010248 power generation Methods 0.000 claims description 7
- 230000010354 integration Effects 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 238000009826 distribution Methods 0.000 description 10
- 230000005611 electricity Effects 0.000 description 7
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Classifications
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- 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
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- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H02J3/382—
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- H02J3/383—
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- H02J3/386—
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- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- 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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides a method, a device, equipment and a computer readable storage medium for planning power of a microgrid, wherein the power planning method comprises the following steps: 1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system; 2) predicting the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy; 3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value; 4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set; 5) predicting according to historical data to obtain a probability corresponding to the peak regulation margin, forming a peak regulation margin probability table according to the peak regulation margin and the probability corresponding to the peak regulation margin, and calculating according to the peak regulation margin probability table to obtain the wind curtailment and the light curtailment electric quantity; 6) and configuring power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
Description
Technical Field
The invention relates to the technical field of energy, in particular to a method, a device and equipment for planning power of a microgrid with stored energy and a computer readable storage medium.
Background
The micro-grid is a small-sized low-voltage system which is composed of a distributed power supply, an energy storage and a load, the balance of electric power and electric quantity in the network can be realized by a proper control means, and the micro-grid can be operated in a grid-connected mode or an isolated network mode. Due to its flexible configuration and convenient operation, the microgrid has gained much attention in recent years. The method can improve the safety and reliability of the power system and improve the power supply quality of users and the service level of a power grid. The distributed new energy is accessed to the system through the micro-grid, so that the line loss can be reduced, the electric energy quality at the tail end of the power grid is improved, the power utilization pressure is relieved, the disaster resistance of the power grid is improved, and the reliable power supply for important users is ensured; the independent micro-grid can also solve the power utilization problem in remote inland or island areas. Therefore, the rapid development of the microgrid technology is an important means for promoting the development and consumption of new energy.
In the micro-grid, through the combined application of the distributed new energy and the stored energy, the fluctuation and randomness of the output of the distributed new energy can be inhibited, the capacity value of the distributed new energy is improved, the conventional energy installation is reduced, and the reliability of a regional power system is enhanced. The larger the energy storage capacity is, the more obvious the benefit is, but the price factor often restricts the configuration of energy storage. In the prior art, the capacity of the stored energy is often configured empirically or by simple calculation, and often the best results are not achieved. Therefore, how to combine the output characteristics of the distributed new energy and configure reasonable energy storage capacity is a key problem to be solved urgently in the development of the micro-grid and the distributed new energy.
Disclosure of Invention
In view of the above, the present invention is to provide a method, an apparatus, and a device for planning power of a microgrid, which are capable of performing power electric quantity and peak shaving balance calculation on the microgrid, and determining the requirements of a power type energy storage device and an energy type energy storage device configured by the microgrid under the background of considering new energy, so as to reduce the occurrence of wind and light electric quantity abandonment, and improve the new energy electric quantity consumption ratio.
To solve the above technical problem, according to an aspect of the present invention, a method for planning power of a microgrid is provided.
The power planning method of the microgrid provided by the embodiment of the invention comprises the following steps:
1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
2) predicting according to historical data to obtain the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy;
3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value;
4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set;
5) predicting according to historical data to obtain a probability corresponding to the peak shaver margin, forming a peak shaver margin probability table according to the peak shaver margin and the probability of the peak shaver margin, and calculating according to the peak shaver margin probability table to obtain wind curtailment and light curtailment electric quantities;
6) and configuring power type and energy type energy storage according to the abandoned wind and abandoned light electric quantity.
According to some embodiments of the invention, the step 2) may comprise:
2-1) for the grid-connected point, calculating a adequacy probability table of the grid-connected point according to the off-grid capacity, wherein the occurrence probability of the maximum off-grid capacity is 100%;
2-2) the generating set comprises a thermal power generating set and a new energy generating set,
calculating a adequacy probability table of the thermal power generating unit according to the adjustable capacity of the thermal power generating unit, wherein the occurrence probability of the adjustable capacity when the adjustable capacity is full output is 100 percent,
the thermal power generating unit comprises an existing thermal power generating unit, a planning thermal power generating unit and an ideal thermal power generating unit, wherein the adjustable capacity of the existing thermal power generating unit is used for measuring an actual measurement numerical value or a typical numerical value of the same type of unit, the adjustable capacity of the planning thermal power generating unit is used for measuring a typical numerical value of the same type of unit, the adjustable capacity of the ideal thermal power generating unit is used for measuring a calculation step length,
for the new energy machine set, according to the historical output data, calculating the adequacy probability table,
the new energy unit comprises an existing new energy unit and a planning new energy unit, wherein the output data of the existing new energy unit is measured, and the output data of the planning new energy unit is the typical value of the existing similar units in the local or nearby areas;
2-3) for the power load, predicting a future load prediction value according to historical data, and calculating a adequacy probability table of the power load according to the load prediction value.
Further, according to some embodiments of the invention, the step 3) may include:
3-1) assigning the priority order of the grid-connected point and the generator set with load;
3-2) calculating the adequacy probability table of the microgrid system and the adequacy probability table of the power load by the grid-connected points and the generator sets in a superposition manner according to the priority order at the preset time to obtain the adequacy probability table of the microgrid system at the preset time,
calculating an expected loss load value according to the microgrid system adequacy probability table every time one grid-connected point or generator set is superposed;
3-3) adding the load loss expected values in a specific period, taking the comprehensive sum of the load loss expected values less than or equal to a preset value as a convergence condition, and after the calculation of the step 3-2) is convergence, taking the input grid-connected points and the generator sets as the actual load carrying sequence, and actually inputting the planning new energy source set and the planning thermal power unit, namely the installed capacity which needs to be newly added to meet the power load, wherein if the planning thermal power unit and/or the planning new energy source set do not need to be input, the installed capacity can meet the power requirement.
Furthermore, according to some embodiments of the present invention, the power planning method of the microgrid may further include the steps of:
3-4) when one power generating unit is put into the step 3-3) and then is converged for the first time, removing the power generating unit, replacing the power generating unit with 1 or more ideal thermal power generating units, recalculating until the convergence is reached, and taking the sum of the capacities of the ideal thermal power generating units put into the calculation as the capacity of the power generating unit.
According to further embodiments of the present invention, the power planning method of the microgrid may further include the steps of:
3-5) removing the new energy generator set, and keeping the loaded priority of other generator sets unchanged;
3-6) carrying out the calculation of the steps 3-2) to 3-3) again until the convergence is carried out again, wherein the difference of the installed capacities needing to be added in the two calculations is the capacity value of the new energy unit.
According to some embodiments of the invention, the step 4) may comprise:
in the step 3-2), electric quantity shortage expectations are respectively calculated according to the current microgrid system adequacy probability table before and after one generator set is put into the power generating system each time, and the difference between the electric quantity shortage expectations before and after is the power generating amount of the generator set in a preset time.
According to some embodiments of the invention, the step 5) may comprise:
5-1) calculating peak shaver margin probability tables of the grid-connected point, the generator set and the power load respectively;
5-2) performing convolution integration on the peak shaving margin probability table of the generator set and the peak shaving margin probability table of the grid-connected point and the peak shaving margin probability table of the power load in an accumulated mode one by one according to the actual priority sequence of the loads of the grid-connected point and the generator set determined in the step 3-3) to obtain a peak shaving margin probability table of the microgrid system, calculating the electric quantity surplus expectation,
wherein if the electric quantity surplus expectation is larger than zero, the values of the electric quantity surplus expectation and the electric quantity surplus expectation are the wind abandoning and light abandoning electric quantities in the preset time,
if the electric quantity surplus expectation is smaller than zero, indicating that wind and light abandoning electric quantity does not occur in the preset time;
5-3) accumulating the wind abandoning amount and the light abandoning amount of the step 5-2) in a specific period to obtain the wind abandoning amount and the light abandoning amount in a preset period.
According to some embodiments of the invention, the step 6) may comprise:
6-1) carrying out peak shifting and valley filling calculation on a load curve according to the abandoned wind and abandoned light electric quantity in a specific period, wherein the energy type energy storage absorbs electric quantity at the time of the abandoned wind and abandoned light, and the absorbed abandoned wind and abandoned light electric quantity is equal to the capacity of the energy type energy storage; at the peak moment of the net load obtained by subtracting the new energy output from the original load in a preset time, the energy type energy storage releases electric quantity, the released electric quantity is equal to the sum of the electric quantities absorbed by the energy type energy storage in the specific period, and the reduced peak load is equal to the power of the energy type energy storage;
6-2) arranging the power type energy storage to reduce the randomness of the output according to the adequacy probability table of the new energy machine set,
the energy of the power type energy storage is released at the position where the abundance probability table of the new energy source unit is less than the mathematical expectation of the probability table, the energy is absorbed at the position where the abundance probability table is more than the mathematical expectation of the probability table, the sum of the absorbed and released energy is zero, and the absorbed and released energy in unit time is not more than the capacity of the power type energy storage;
6-3) repeating the steps 1) -5) until the wind and light abandoning amount is reduced within a preset range, thereby solving the power and the capacity of the required power type and energy type energy storage devices, and configuring the power type and energy type energy storage devices correspondingly.
According to another aspect of the present invention, a power planning apparatus for a microgrid is provided.
The power planning device of the microgrid according to the embodiment of the invention comprises:
the determining module is used for determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
the adequacy probability table generating module is used for predicting according to historical data to obtain the probability corresponding to the adequacy and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy;
the power balance calculation module is used for performing power balance calculation according to the adequacy probability table to obtain the required new additional installed capacity and the new energy unit capacity value;
the electric quantity balance calculation module is used for carrying out electric quantity balance calculation according to the adequacy probability table to obtain the electric quantity to be generated by the generator set;
the wind curtailment and light curtailment electric quantity calculation module is used for predicting according to historical data to obtain the probability corresponding to the peak regulation margin, forming a peak regulation margin probability table according to the peak regulation margin and the probability corresponding to the peak regulation margin, and calculating according to the peak regulation margin probability table to obtain the wind curtailment and light curtailment electric quantity;
and the energy storage configuration module is used for configuring the power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
According to still another aspect of the present invention, there is provided a power planning apparatus of a microgrid, comprising:
a processor; and
a memory having computer program instructions stored therein,
wherein the computer program instructions, when executed by the processor, cause the processor to perform the steps of:
1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
2) predicting according to historical data to obtain the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy;
3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value;
4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set;
5) predicting according to historical data to obtain a probability corresponding to the peak shaver margin, forming a peak shaver margin probability table according to the peak shaver margin and the probability of the peak shaver margin, and calculating according to the peak shaver margin probability table to obtain wind curtailment and light curtailment electric quantities;
6) and configuring power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
According to yet another aspect of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the steps in the power planning method for a microgrid according to any one of the embodiments described above.
According to the invention, at least one of the following advantages is achieved:
1) the capacity of the newly-added energy storage device is estimated not according to experience, but the electric power and electric quantity balance calculation is carried out on the micro-grid, so that the capacity of the newly-added energy storage device can be calculated more accurately;
2) the electric power and electric quantity balance calculation is carried out in different time periods, and the non-simultaneity of the maximum value of the output of the new energy and the maximum value of the load can be correctly reflected;
3) the wind and light abandoning electric quantity of the new energy is obtained through real-time calculation and analysis, and the energy storage device is pertinently configured according to the actual conditions of wind and light abandoning, so that the capacity configured by the energy storage device is reasonably balanced on the premise of meeting the new energy consumption and the economy.
Drawings
Fig. 1 is a flowchart of a power planning method of a microgrid according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a power planning apparatus of a microgrid according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention.
First, the adequacy probability table, the peak shaver margin, and the peak shaver margin probability table related to the present invention are defined as follows.
Adequacy and adequacy probability tables for the grid-connected point, the generator set, and the electrical load are defined as follows:
(1) the adequacy of the grid-connected point refers to the maximum power which can be provided by the grid-connected point to the microgrid system at a certain moment;
(2) the adequacy probability table of the grid-connected point refers to a probability distribution table formed by various possible adequacy of the grid-connected point at a certain moment and the probability of the grid-connected point appearing correspondingly;
(3) the adequacy of the thermal power generating unit refers to the maximum output of the thermal power generating unit which can be called at a certain moment;
(4) the adequacy probability table of the thermal power generating unit refers to a probability distribution table formed by various possible adequacy of the thermal power generating unit at a certain moment and the probability of the thermal power generating unit correspondingly appearing;
(5) the adequacy of the new energy unit refers to the output of the new energy unit at a certain moment;
(6) the adequacy probability table of the new energy source unit refers to a probability distribution table formed by various possible adequacy of the new energy source unit at a certain moment and the probability of the new energy source unit correspondingly appearing;
(7) the adequacy of the power load refers to the value of the power generation load of the power system at a certain moment;
(8) the adequacy probability table of the electric load refers to a probability distribution table formed by various possible adequacy of the load at a certain moment and the probability of the load corresponding to the adequacy;
(9) the adequacy of the micro-grid system refers to the adequacy of the system obtained by subtracting the power load from the sum of the adequacy of all grid-connected points and the adequacy of all generator sets at a certain moment;
(10) the adequacy probability table of the microgrid system refers to a probability distribution table formed by various possible adequacy and corresponding probability of the microgrid system at a certain moment.
The peak shaver margin and the probability table of the peak shaver margin about the grid-connected point, the generating set and the electric load are defined as follows:
(11) the peak regulation margin of the grid-connected point refers to the maximum power which can be absorbed by the grid-connected point from the microgrid system at a certain moment;
(12) the peak shaving margin probability table of the grid-connected point refers to a probability distribution table formed by various possible peak shaving margins and the corresponding probabilities of the peak shaving margins at a certain moment of the grid-connected point as defined above;
(13) the peak regulation margin of the thermal power generating unit refers to the minimum technical output of the thermal power generating unit at a certain moment;
(14) the peak shaving margin probability table of the thermal power generating unit refers to a probability distribution table formed by various possible peak shaving margins of the thermal power generating unit at a certain moment and the corresponding probability of the peak shaving margins as defined above;
(15) the peak regulation margin of the new energy unit refers to the output of the new energy unit at a certain moment;
(16) the probability table of the peak shaver margin of the new energy source unit is a probability distribution table formed by various possible peak shaver margins of the new energy source unit at a certain moment and the corresponding probability of the new energy source unit;
(17) the peak regulation margin of the load refers to the value of the power generation load of the power system at a certain moment;
(18) the load peak shaving margin probability table is a probability distribution table formed by various possible peak shaving margins and corresponding probabilities of the load at a certain moment, which are defined as above;
(19) the peak regulation margin of the micro-grid system is the peak regulation margin of the system minus the load subtracted from the sum of the peak regulation margins of all grid-connected points, the thermal power generating unit and the new energy source unit at a certain moment;
(20) the peak shaving margin probability table of the microgrid system refers to a probability distribution table formed by various possible peak shaving margins and corresponding occurrence probabilities of the peak shaving margins at a certain moment of the microgrid system defined above.
First, a power planning method for a microgrid according to an embodiment of the present invention will be described with reference to the accompanying drawings.
As shown in fig. 1, the power planning method for the microgrid according to the embodiment of the present invention is particularly suitable for power planning of a microgrid with stored energy under a high new energy occupancy, and specifically includes the following steps:
step S1 determines adequacy and peak shaver margin of grid-connected point, generator set and power load of micro-grid system
The generating set can comprise a thermal power generating set and a new energy generating set.
Specifically, adequacy and peak shaver margins for the grid-connected point, the generator set, and the electrical load may be calculated and determined according to the above definitions.
Step S2, according to the historical data, the probability corresponding to the adequacy is obtained through prediction, and according to the adequacy and the probability corresponding to the adequacy, a adequacy probability table is formed
Specifically, the following substeps may be included:
2-1) for the grid-connected point, calculating a adequacy probability table according to the off-line capacity, wherein the occurrence probability of the maximum off-line capacity is 100%.
2-2) the generating set comprises a thermal power generating set and a new energy generating set.
Calculating a adequacy probability table of the thermal power generating unit according to the adjustable capacity of the thermal power generating unit, wherein the occurrence probability of the adjustable capacity when the adjustable capacity is full output is 100 percent, the thermal power generating unit comprises an existing thermal power generating unit, a planning thermal power generating unit and an ideal thermal power generating unit, wherein, the adjustable capacity of the existing thermal power generating unit can measure the measured value or the typical value of the similar unit, the adjustable capacity of the planning thermal power generating unit is a typical numerical value of the same type of unit, the adjustable capacity of the ideal thermal power generating unit is a calculation step length, calculating a adequacy probability table of the new energy set according to historical output data of the new energy set, wherein the new energy set comprises the existing new energy set and a planned new energy set, the output data of the existing new energy unit is measured, and the output data of the planned new energy unit is the typical value of the existing similar units in the local or nearby area.
2-3) for the power load, predicting a future load prediction value according to historical data, and calculating a adequacy probability table of the power load according to the load prediction value.
Step S3, according to the adequacy probability table, the power balance calculation is carried out to obtain the required new installed capacity and the capacity value of the new energy source unit
The method specifically comprises the following steps:
3-1) assigning the grid-connected point, the generator set, with a load priority.
Among them, for example:
when the point of connection is only standby, according to: the existing new energy unit, the planning new energy unit, the existing thermal power generating unit, the planning thermal power generating unit and the grid-connected point are arranged in sequence;
when the point-of-connection usually has power exchange, according to: the method comprises the steps of arranging an existing new energy source unit, a planning new energy source unit, a grid-connected point, an existing thermal power generating unit and a planning thermal power generating unit in sequence.
Of course, the above priority order is merely an example, and may be appropriately adjusted according to a specific use case or the like.
And 3-2) calculating the adequate probability table of the power Load and the adequate probability table of the power Load one by one at preset time according to the priority sequence, and calculating the adequate probability table of the microgrid system at the preset time, wherein each superposed grid-connected point or generator set calculates the Load Loss Expectation (Load of Load expansion) according to the adequate probability table of the microgrid system.
The LOLE is the sum of probabilities corresponding to all values with the adequacy smaller than 0 in the preset time microgrid system adequacy probability table.
The predetermined time may be, for example, "typical day" for each month. Specifically, for the grid-connected point, the generated output and the load data of the "typical day" per month, the convolution integral calculation may be performed by using the adequacy probability table and the adequacy probability table of the power load for each grid-connected point and each power generation unit in an overlapping manner for each data point per hour according to the load priority order of the grid-connected point and the power generation unit, so as to obtain the adequacy probability table of the microgrid system per hour of the "typical day".
3-3) adding the load loss expected values in a specific period, taking the comprehensive sum of the load loss expected values less than or equal to a preset value as a convergence condition, and after the calculation of the step 3-2) is convergence, taking the input grid-connected points and the generator sets as the actual load carrying sequence, and actually inputting the planning new energy source set and the planning thermal power unit, namely the installed capacity which needs to be newly added to meet the power load, wherein if the planning thermal power unit and/or the planning new energy source set do not need to be input, the installed capacity can meet the power requirement.
In which the load loss expectation values for a specific period are added, for example, LOLE for 12 months throughout the year, and "typical days" per month may be added.
In addition, in order to obtain more accurate results, the following sub-steps can be further included:
3-4) when one power generating unit is put into the step 3-3) and then is converged for the first time, removing the power generating unit, replacing the power generating unit with 1 or more ideal thermal power generating units, recalculating until the convergence is reached, and taking the sum of the capacities of the ideal thermal power generating units put into the calculation as the capacity of the power generating unit.
Thus, the accuracy can be up to one calculation step (e.g., 1 MW).
In addition, according to other embodiments of the present invention, the following sub-steps may be further included:
3-5) removing the new energy generator set, and keeping the loaded priority of other generator sets unchanged;
3-6) carrying out the calculation of the steps 3-2) to 3-3) again until the convergence is carried out again, wherein the difference of the installed capacities needing to be added in the two calculations is the capacity value of the new energy unit.
And dividing the capacity value by the installed capacity of the new energy unit to obtain a credible capacity coefficient of the new energy unit in the power planning stage.
Step S4, according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set
According to some embodiments of the present invention, the power balance calculation specifically includes:
in the step 3-2), before and after each time of putting in a generator set, an expected electric quantity shortage EENS (excess Energy Not supplied) is respectively calculated according to a current microgrid system adequacy probability table, and the difference between the expected electric quantity shortage before and after is the electric quantity to be generated by the generator set in a preset time.
And the EENS is numerically equal to the weighted sum of all values with the adequacy smaller than 0 in the adequacy probability distribution function of the microgrid system at the moment and the corresponding probability.
For example, the steps are repeated every hour for each month of the whole year, so that the power generation amount of each hour of each month of the whole year, namely the typical day, of each month of the whole year, of a certain generator set is obtained, and the power generation amount of the generator set in the whole year can be obtained after accumulation.
Particularly, for the new energy source unit, the annual energy production of the new energy source unit can be obtained by calculating according to the steps.
Step S5, according to historical data, predicting to obtain the probability corresponding to the peak regulation margin, forming a peak regulation margin probability table according to the peak regulation margin and the probability corresponding to the peak regulation margin, and according to the peak regulation margin probability table, calculating to obtain the amount of abandoned wind and abandoned light
5-1) calculating peak shaver margin probability tables of the grid-connected point, the generator set and the power load respectively;
for example, for a point of connection, a sufficient probability table is calculated according to the above definition according to the maximum power capacity of the point of connection. Wherein the probability of the occurrence of the maximum uplink power is 100%.
And for the thermal power generating unit, calculating a peak regulation margin probability table according to the definition according to the minimum technical output. Wherein the probability of occurrence of the minimum technical contribution is 100%.
For a heating unit, the minimum technical output in the steps is different in value according to different daytime and night of a heating period and a non-heating period.
For the new energy source set, the probability table of the peak shaver margin is directly calculated according to the definition.
For the electric load, the probability table of the peak shaving margin is directly calculated according to the definition.
5-2) performing convolution integration on the peak regulation margin probability table of the generator set and the peak regulation margin probability table of the grid-connected point and the peak regulation margin probability table of the power load in an accumulated manner one by one according to the actual priority of the load of the grid-connected point and the generator set in the step 3-3) to obtain a peak regulation margin probability table of the microgrid system, and calculating an electric quantity surplus expectation EEOS (excess Energy Over supplied), wherein if the electric quantity surplus expectation is greater than zero, the values of the electric quantity surplus expectation are the abandoned wind and abandoned light electric quantities in the preset time, and if the electric quantity surplus expectation is less than zero, the preset time is represented that the abandoned wind and abandoned light electric quantities do not occur.
The EEOS value is equal to the weighted sum of all values with the adequacy larger than 0 and the corresponding probability in the peak shaving margin probability table of the microgrid system at the moment.
Specifically, for example, for each hour of "typical day" of each month, convolution integration is performed on the peak shaving margin probability tables of the new Energy plant, the thermal power plant, and the grid-connected point, which are accumulated one by one, and the peak shaving margin probability table of the power load is used to calculate the expected eeos (excess Energy Over supplied) for the electric quantity surplus of the finally obtained peak shaving margin probability table of the microgrid system.
5-3) accumulating the wind abandoning amount and the light abandoning amount of the step 5-2) in a specific period to obtain the wind abandoning amount and the light abandoning amount in a preset period.
The wind and light electricity abandoning amount accumulation in each hour of the 'typical day' of each month can be calculated through the steps, and the wind and light electricity abandoning amount in the whole year can be obtained.
Step S6, according to the wind and light electricity, configuring power type and energy type energy storage device
According to some embodiments of the invention, the method may specifically comprise the following sub-steps:
6-1) carrying out peak shifting and valley filling calculation on a load curve according to the abandoned wind and abandoned light electric quantity in a specific period, wherein the energy type energy storage absorbs electric quantity at the time of the abandoned wind and abandoned light, and the absorbed abandoned wind and abandoned light electric quantity is equal to the capacity of the energy type energy storage; the energy type energy storage releases electric quantity at the peak moment of net load obtained by subtracting new energy output from original load in a preset time, the released electric quantity is equal to the sum of electric quantities absorbed by the energy type energy storage in the specific period, and the reduced peak load is equal to the power of the energy type energy storage.
That is, the energy type energy storage is arranged according to the wind and light electricity abandoning amount per hour of the 'typical day' of each month of the whole year obtained in the step (5) to carry out 'peak shifting and valley filling' on the load curve. The specific measures can be that when wind abandoning and light abandoning occur, the energy type energy storage absorbs electric quantity, and the absorbed wind abandoning and light abandoning electric quantity is equal to the capacity of the energy type energy storage; at the peak time of the "typical day" net load (original load minus new energy output), the energy storage releases an amount of electricity, and the amount of electricity released is equal to the sum of the amounts of electricity absorbed by the energy storage on the "typical day", and the peak load subtracted is equal to the power of the energy storage.
6-2) arranging the power type energy storage to reduce the randomness of the output of the power type energy storage according to the adequacy probability table of the new energy machine set.
The energy is released at the position where the allowance of the power type energy storage in the allowance probability table of the new energy machine set is smaller than the mathematical expectation of the probability table, the energy is absorbed at the position where the allowance is larger than the mathematical expectation of the probability table, the sum of the absorbed and released energy is zero, and the absorbed and released energy in unit time is not larger than the capacity of the power type energy storage.
For example, the power storage is arranged to reduce the randomness of the output according to the new energy unit adequacy probability table. The overall goal is to make the mathematical expectation of the new energy bank adequacy probability table constant and the variance as small as possible. The specific measures can be that the power type energy storage absorbs energy at the position where the abundance probability table of the new energy source unit abundance is larger than the mathematical expectation of the probability table, and releases energy at the position as close to the mathematical expectation of the probability table as possible; the power type energy storage releases energy at the place where the probability table of the new energy source unit is adequate and is less than the mathematical expectation of the probability table, absorbs energy at the place as close to the mathematical expectation of the probability table as possible, the sum of the absorbed and released energy is zero, and the absorbed and released energy in unit time is not more than the capacity of the power type energy storage.
6-3) repeating the steps S1-S5 until the wind and light abandon amount is reduced in a preset range, thereby obtaining the power and the capacity of the required power type and energy type energy storage devices, and configuring the power type and energy type energy storage devices correspondingly.
By the means, the power and the capacity of the energy storage device are continuously improved, the steps 1) to 5) are repeated until the economic and social benefits brought by wind abandoning and light abandoning are avoided or the reduction of the wind abandoning and light abandoning power and the cost brought by the increase of the energy storage capacity are balanced, the power and the capacity of the required energy type and power type energy storage devices can be obtained, and the power type and energy type energy storage devices are correspondingly configured, so that the reasonable consumption of high-proportion new energy is realized.
Next, a power planning apparatus of a microgrid according to an embodiment of the present invention is described.
As shown in fig. 2, a power planning apparatus 10 of a microgrid according to an embodiment of the present invention includes:
a determining module 100, which determines adequacy and peak shaving margin of a grid-connected point, a generator set and a power load of the microgrid system;
a adequacy probability table generating module 200, which predicts the historical data to obtain the probability corresponding to the adequacy, and forms an adequacy probability table according to the adequacy and the probability corresponding to the adequacy;
the power balance calculation module 300 is used for performing power balance calculation according to the adequacy probability table to obtain the required new additional installed capacity and the new energy source unit capacity value;
the electric quantity balance calculation module 400 is used for carrying out electric quantity balance calculation according to the adequacy probability table to obtain the electric quantity to be generated by the generator set;
the wind curtailment and light curtailment electric quantity calculating module 500 is used for predicting according to historical data to obtain the probability corresponding to the peak regulation margin, forming a peak regulation margin probability table according to the peak regulation margin and the probability corresponding to the peak regulation margin, and calculating according to the peak regulation margin probability table to obtain the wind curtailment and light curtailment electric quantity;
and an energy storage configuration module 600 which configures power type and energy type energy storage devices according to the wind abandoning and light abandoning electric quantity.
Finally, according to an embodiment of the present invention, there is also provided a power planning apparatus for a microgrid, the power planning apparatus including: a processor and a memory, in which computer program instructions are stored,
wherein the computer program instructions, when executed by the processor, cause the processor to perform the steps of:
1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
2) predicting according to historical data to obtain the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy;
3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value;
4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set;
5) predicting according to historical data to obtain a probability corresponding to the peak shaver margin, forming a peak shaver margin probability table according to the peak shaver margin and the probability of the peak shaver margin, and calculating according to the peak shaver margin probability table to obtain wind curtailment and light curtailment electric quantities;
6) and configuring power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
Further, the power planning device of the microgrid may further include a network interface, an input device, a hard disk, and a display device.
The various interfaces and devices described above may be interconnected by a bus architecture. A bus architecture may be any architecture that may include any number of interconnected buses and bridges. One or more Central Processing Units (CPUs), represented in particular by a processor, and one or more memories, represented by a memory, are connected together by various circuits. The bus architecture may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like. It will be appreciated that a bus architecture is used to enable communications among the components. The bus architecture includes a power bus, a control bus, and a status signal bus, in addition to a data bus, all of which are well known in the art and therefore will not be described in detail herein.
The memory is used for storing programs and data necessary for operating the operating system, intermediate results in the calculation process of the processor and the like.
It will be appreciated that the memory in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. The memory 34 of the apparatus and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, the memory stores elements, executable modules or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system and an application program.
The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs include various application programs such as a Browser (Browser) and the like for implementing various application services. The program for implementing the method of the embodiment of the present invention may be included in the application program.
The method disclosed by the above embodiment of the invention can be applied to a processor or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, configured to implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
Of course, the present invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, performs the steps in the power planning method of a microgrid according to any one of the embodiments of the present invention.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A power planning method for a microgrid is characterized by comprising the following steps:
1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
2) predicting according to historical data to obtain the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy, wherein the method comprises the following steps:
2-1) for the grid-connected point, calculating a adequacy probability table of the grid-connected point according to the off-grid capacity, wherein the occurrence probability of the maximum off-grid capacity is 100%;
2-2) the generating set comprises a thermal power generating set and a new energy generating set,
calculating a adequacy probability table of the thermal power generating unit according to the adjustable capacity of the thermal power generating unit, wherein the occurrence probability of the adjustable capacity when the adjustable capacity is full output is 100 percent,
the thermal power generating unit comprises an existing thermal power generating unit, a planning thermal power generating unit and an ideal thermal power generating unit, wherein the adjustable capacity of the existing thermal power generating unit is used for measuring an actual measurement numerical value or a typical numerical value of the same type of unit, the adjustable capacity of the planning thermal power generating unit is used for measuring a typical numerical value of the same type of unit, the adjustable capacity of the ideal thermal power generating unit is used for measuring a calculation step length,
for the new energy machine set, according to the historical output data, calculating the adequacy probability table,
the new energy unit comprises an existing new energy unit and a planning new energy unit, wherein the output data of the existing new energy unit is measured, and the output data of the planning new energy unit is the typical value of the existing similar units in the local or nearby areas;
2-3) for the power load, predicting a future load predicted value according to historical data, and calculating a adequacy probability table of the power load according to the load predicted value;
3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value;
4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set;
5) predicting according to historical data to obtain a probability corresponding to the peak shaver margin, forming a peak shaver margin probability table according to the peak shaver margin and the probability of the peak shaver margin, and calculating according to the peak shaver margin probability table to obtain wind curtailment and light curtailment electric quantities;
6) and configuring power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
2. The power planning method for the microgrid according to claim 1, wherein the step 3) specifically comprises:
3-1) assigning the priority order of the grid-connected point and the generator set with load;
3-2) calculating the adequacy probability table of the microgrid system and the adequacy probability table of the power load by the grid-connected points and the generator sets in a superposition manner according to the priority order at the preset time to obtain the adequacy probability table of the microgrid system at the preset time,
calculating an expected loss load value according to the microgrid system adequacy probability table every time one grid-connected point or generator set is superposed;
3-3) adding the load loss expected values in a specific period, taking the sum of the load loss expected values less than or equal to a preset value as a convergence condition, and after the calculation of the step 3-2) is convergence, taking the input grid-connected points and the generator sets as an actual loaded sequence, and actually inputting the planning new energy source set and the planning thermal power unit, namely the installed capacity which needs to be newly added to meet the power load, wherein if the planning thermal power unit and/or the planning new energy source set does not need to be input, the installed capacity meets the power requirement.
3. The power planning method for a microgrid according to claim 2, characterized by further comprising the steps of:
3-4) when one power generating unit is put into the step 3-3) and then is converged for the first time, removing the power generating unit, replacing the power generating unit with 1 or more ideal thermal power generating units, recalculating until the convergence is reached, and taking the sum of the capacities of the ideal thermal power generating units put into the calculation as the capacity of the power generating unit.
4. The power planning method for a microgrid according to claim 2, characterized by further comprising the steps of:
3-5) removing the new energy machine set, and keeping the loaded priority of other grid-connected points and the generator set unchanged;
3-6) carrying out the calculation of the steps 3-2) to 3-3) again until the convergence is carried out again, wherein the difference of the installed capacities needing to be added in the two calculations is the capacity value of the new energy unit.
5. The power planning method for the microgrid according to claim 2, characterized in that the step 4) specifically comprises:
4-1) before and after one generator set is put into the step 3-2) each time, respectively calculating electric quantity shortage expectation according to the current microgrid system adequacy probability table, wherein the difference between the electric quantity shortage expectation before and after is the power generation amount of the generator set in a preset time.
6. The power planning method for the microgrid according to claim 2, characterized in that the step 5) specifically comprises:
5-1) calculating peak shaver margin probability tables of the grid-connected point, the generator set and the power load respectively;
5-2) performing convolution integration on the peak shaving margin probability table of the generator set and the peak shaving margin probability table of the grid-connected point and the peak shaving margin probability table of the power load in an accumulated mode one by one according to the actual priority sequence of the load of the grid-connected point and the generator set obtained in the step 3-3) to obtain a peak shaving margin probability table of the microgrid system, calculating the electric quantity surplus expectation,
wherein if the electric quantity surplus expectation is larger than zero, the values of the electric quantity surplus expectation and the electric quantity surplus expectation are the wind abandoning and light abandoning electric quantities in the preset time,
if the electric quantity surplus expectation is smaller than zero, indicating that wind and light abandoning electric quantity does not occur in the preset time;
and 5-3) accumulating the wind abandoning amount and the light abandoning amount of the step 5-2) in a preset period to obtain the wind abandoning amount and the light abandoning amount in the preset period.
7. The power planning method for the microgrid according to claim 1, characterized in that the step 6) specifically comprises:
6-1) carrying out peak shifting and valley filling calculation on a load curve according to the abandoned wind and abandoned light electric quantity in a specific period, wherein the energy type energy storage absorbs electric quantity at the time of the abandoned wind and abandoned light, and the absorbed abandoned wind and abandoned light electric quantity is equal to the capacity of the energy type energy storage; at the peak moment of a net load obtained by subtracting the new energy output from the original load in a preset time, the energy type energy storage releases electric quantity, the released electric quantity is equal to the sum of the electric quantities absorbed by the energy type energy storage in the preset time, and the reduced peak load is equal to the power of the energy type energy storage;
6-2) arranging the power type energy storage to reduce the randomness of the output of the power type energy storage according to a sufficient probability table of the new energy machine set, wherein the sufficient amount of the power type energy storage in the sufficient probability table of the new energy machine set is smaller than the mathematical expectation of the probability table to release energy, the sufficient amount of the power type energy storage is larger than the mathematical expectation of the probability table to absorb energy, the sum of the absorbed and released energy is zero, and the absorbed and released energy in unit time is not larger than the capacity of the power type energy storage;
6-3) repeating the steps 1) -5) until the wind and light abandoning amount is reduced within a preset range, thereby solving the power and the capacity of the required power type and energy type energy storage devices, and configuring the power type and energy type energy storage devices correspondingly.
8. An apparatus for power planning of a microgrid, comprising:
the determining module is used for determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
the adequacy probability table generating module is used for predicting according to historical data to obtain the probability corresponding to the adequacy and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy, and comprises the following steps:
for the grid-connected point, the adequacy probability table generating module is used for calculating an adequacy probability table of the grid-connected point according to the off-line capability, wherein the occurrence probability of the maximum off-line capability is 100%;
the generating set comprises a thermal power generating set and a new energy generating set,
for the thermal power generating unit, the adequacy probability table generating module is used for calculating the adequacy probability table according to the adjustable capacity of the thermal power generating unit, wherein the adjustable capacity is 100% of the occurrence probability when the adjustable capacity is full output,
the thermal power generating unit comprises an existing thermal power generating unit, a planning thermal power generating unit and an ideal thermal power generating unit, wherein the adjustable capacity of the existing thermal power generating unit is used for measuring an actual measurement numerical value or a typical numerical value of the same type of unit, the adjustable capacity of the planning thermal power generating unit is used for measuring a typical numerical value of the same type of unit, the adjustable capacity of the ideal thermal power generating unit is used for measuring a calculation step length,
for the new energy source unit, the adequacy probability table generating module is used for calculating the adequacy probability table according to the historical output data,
the new energy unit comprises an existing new energy unit and a planning new energy unit, wherein the output data of the existing new energy unit is measured, and the output data of the planning new energy unit is the typical value of the existing similar units in the local or nearby areas;
for the power load, the adequacy probability table generating module is used for predicting a future load predicted value according to historical data and calculating an adequacy probability table of the power load according to the load predicted value;
the power balance calculation module is used for performing power balance calculation according to the adequacy probability table to obtain the required new additional installed capacity and the new energy unit capacity value;
the electric quantity balance calculation module is used for carrying out electric quantity balance calculation according to the adequacy probability table to obtain the electric quantity to be generated by the generator set;
the wind curtailment and light curtailment electric quantity calculation module is used for predicting according to historical data to obtain the probability corresponding to the peak regulation margin, forming a peak regulation margin probability table according to the peak regulation margin and the probability corresponding to the peak regulation margin, and calculating according to the peak regulation margin probability table to obtain the wind curtailment and light curtailment electric quantity;
and the energy storage configuration module is used for configuring the power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
9. An apparatus for power planning of a microgrid, comprising:
a processor; and
a memory having computer program instructions stored therein,
wherein the computer program instructions, when executed by the processor, cause the processor to perform the steps of:
1) determining adequacy and peak regulation margin of a grid-connected point, a generator set and a power load of the micro-grid system;
2) predicting according to historical data to obtain the probability corresponding to the adequacy, and forming an adequacy probability table according to the adequacy and the probability corresponding to the adequacy, wherein the method comprises the following steps:
2-1) for the grid-connected point, calculating a adequacy probability table of the grid-connected point according to the off-grid capacity, wherein the occurrence probability of the maximum off-grid capacity is 100%;
2-2) the generating set comprises a thermal power generating set and a new energy generating set,
calculating a adequacy probability table of the thermal power generating unit according to the adjustable capacity of the thermal power generating unit, wherein the occurrence probability of the adjustable capacity when the adjustable capacity is full output is 100 percent,
the thermal power generating unit comprises an existing thermal power generating unit, a planning thermal power generating unit and an ideal thermal power generating unit, wherein the adjustable capacity of the existing thermal power generating unit is used for measuring an actual measurement numerical value or a typical numerical value of the same type of unit, the adjustable capacity of the planning thermal power generating unit is used for measuring a typical numerical value of the same type of unit, the adjustable capacity of the ideal thermal power generating unit is used for measuring a calculation step length,
for the new energy machine set, according to the historical output data, calculating the adequacy probability table,
the new energy unit comprises an existing new energy unit and a planning new energy unit, wherein the output data of the existing new energy unit is measured, and the output data of the planning new energy unit is the typical value of the existing similar units in the local or nearby areas;
2-3) for the power load, predicting a future load predicted value according to historical data, and calculating a adequacy probability table of the power load according to the load predicted value;
3) according to the adequacy probability table, carrying out power balance calculation to obtain the required new installed capacity and the new energy unit capacity value;
4) according to the adequacy probability table, carrying out electric quantity balance calculation to obtain the electric quantity to be generated by the generator set;
5) predicting according to historical data to obtain a probability corresponding to the peak shaver margin, forming a peak shaver margin probability table according to the peak shaver margin and the probability of the peak shaver margin, and calculating according to the peak shaver margin probability table to obtain wind curtailment and light curtailment electric quantities;
6) and configuring power type and energy type energy storage devices according to the abandoned wind and abandoned light electric quantity.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps in the method for power planning of a microgrid according to any one of claims 1 to 7.
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| CN109245176B (en) * | 2018-11-24 | 2021-07-02 | 太原理工大学 | Risk-considering interconnected power grid unit combination method containing large-scale wind power |
| CN110648249B (en) * | 2019-09-23 | 2022-03-29 | 广西电网有限责任公司 | Annual power balance measuring and calculating method, device and equipment |
| CN110676846B (en) * | 2019-10-11 | 2021-06-08 | 国网山东省电力公司经济技术研究院 | Power peak regulation method, dispatching center and power peak regulation system |
| CN115800336B (en) * | 2022-11-22 | 2024-04-09 | 中国能源建设集团广东省电力设计研究院有限公司 | Method, device and equipment for determining energy storage capacity based on peak regulation and frequency modulation |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103490449A (en) * | 2013-10-10 | 2014-01-01 | 华北电力大学 | Method for optimizing operation simulation of multi-energy combined power generation system |
| CN105207211A (en) * | 2015-10-20 | 2015-12-30 | 河海大学 | Evaluation method for adequacy of wind generation and energy storage hybrid power system |
| CN105449664A (en) * | 2014-09-01 | 2016-03-30 | 北京华建网源电力设计研究所 | Wind power consumptive capacity calculation method and system |
| CN105576699A (en) * | 2016-01-12 | 2016-05-11 | 四川大学 | Independent micro-grid energy storage margin detection method |
| CN106684928A (en) * | 2016-11-26 | 2017-05-17 | 国网河南省电力公司电力科学研究院 | Calculation method of power grid peak regulation margin based on peak regulation cost |
| CN106712075A (en) * | 2016-04-26 | 2017-05-24 | 武汉大学 | Peaking strategy optimization method considering safety constraints of wind power integration system |
-
2017
- 2017-08-11 CN CN201710685746.4A patent/CN107482656B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103490449A (en) * | 2013-10-10 | 2014-01-01 | 华北电力大学 | Method for optimizing operation simulation of multi-energy combined power generation system |
| CN105449664A (en) * | 2014-09-01 | 2016-03-30 | 北京华建网源电力设计研究所 | Wind power consumptive capacity calculation method and system |
| CN105207211A (en) * | 2015-10-20 | 2015-12-30 | 河海大学 | Evaluation method for adequacy of wind generation and energy storage hybrid power system |
| CN105576699A (en) * | 2016-01-12 | 2016-05-11 | 四川大学 | Independent micro-grid energy storage margin detection method |
| CN106712075A (en) * | 2016-04-26 | 2017-05-24 | 武汉大学 | Peaking strategy optimization method considering safety constraints of wind power integration system |
| CN106684928A (en) * | 2016-11-26 | 2017-05-17 | 国网河南省电力公司电力科学研究院 | Calculation method of power grid peak regulation margin based on peak regulation cost |
Non-Patent Citations (1)
| Title |
|---|
| 基于充裕度指标的含风电场电力系统储能容量配置方法研究;程卓;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20130715(第07期);第C042-537页 * |
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|---|---|
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