CN116436100B - Power grid capacity margin optimization configuration method and system considering source load storage interaction characteristics - Google Patents
Power grid capacity margin optimization configuration method and system considering source load storage interaction characteristics Download PDFInfo
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Abstract
The application belongs to the technical field of power grid optimization, and particularly relates to a power grid capacity margin optimization configuration method and system considering source load storage interaction characteristics, wherein the method comprises the following steps: taking the load shedding rate and the wind power wind abandoning rate into consideration, and acquiring a flexible margin index at the power supply side and a capacity margin index at the power grid side; the total cost of the operation of the power grid is taken as a target, and the acquired flexible margin index of the power supply side and the margin index of the capacity of the power grid are combined to construct a capacity margin model of the power grid; and solving an optimal solution of the constructed grid capacity margin model to finish the optimal configuration of the grid capacity margin considering the source load storage interaction characteristic. According to the application, the calculation of the grid capacity margin optimization configuration is realized by constructing the grid equipment capacity margin measuring and calculating model considering the source load storage interaction characteristic, and the analysis index is provided for evaluating and analyzing the source load bearing capacity and the new energy consumption capacity of the regional grid.
Description
Technical Field
The application belongs to the technical field of power grid optimization, and particularly relates to a power grid capacity margin optimization configuration method and system considering source load storage interaction characteristics.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the gradual increase of the duty ratio of renewable energy generated energy such as wind power, photovoltaic power generation and the like, the increase of the new energy permeability provides a serious challenge for the flexibility of the power system. The flexibility of the power grid is insufficient, the power generation is difficult to follow the change of the net load, and the operations of wind abandoning, light abandoning and load shedding are needed to be carried out, so that huge waste is caused. The flexibility of the power system is ensured to be abundant, and the method has important significance for new energy consumption and new energy power system construction.
The analysis of the interaction characteristics of the source network and the charge storage needs to consider uncertainty factors influencing the interaction of a power source side, a power grid side and a load side, wherein the uncertainty factors comprise the load characteristics of a planned level year, the new energy access scale and the output characteristics, the resource access scale of a demand side such as energy storage and controllable load and the like. Margin is an indication of capacity, and the larger the margin is, the stronger the indication is, but at the same time, the cost is increased. The capacity margin of the power grid equipment mainly comprises the capacity margin of various power supply installation capacity margins, the power grid adjustment capacity margin and the power grid transmission capacity margin. Taking the power grid regulation capacity margin as an example, a system with larger regulation margin has higher new energy consumption capacity, however, pursuing the maximum regulation margin in the system dispatching can lead to lower power level of a regulating unit, so that the system reserves larger standby resources, thereby improving the investment cost of the system. How to find a proper balance point among new energy consumption capability, power-saving capability and operation economy of the system is important.
According to the knowledge of the inventor, related researches adopt a prediction method to process the output of new energy units such as wind power and the like, and calculate the net load value of the new energy units to participate in scheduling; although the new energy output is completely consumed, more severe requirements are put forward on the running economy and reliability of the power system; the consideration of flexible resources is incomplete, and the potential of flexible interaction of the power system is not explored; the method has the advantages that the limited flexible resources are optimally allocated to cope with adverse effects caused by large-scale wind power access, but the effects of various flexible resource characteristics on power grid operation scheduling are not considered at the same time.
Disclosure of Invention
In order to solve the problems, the application provides a power grid capacity margin optimal configuration method and system for considering source load storage interaction characteristics, and the power grid capacity margin optimal configuration calculation is realized by constructing a power grid equipment capacity margin calculation model for considering the source load storage interaction characteristics by combining factors such as load characteristics, new energy output characteristics and energy storage configuration of a regional power grid, so that analysis indexes are provided for evaluating and analyzing the source load bearing capacity and the new energy consumption capacity of the regional power grid.
According to some embodiments, the first scheme of the application provides a power grid capacity margin optimization configuration method considering source-load storage interaction characteristics, which adopts the following technical scheme:
a power grid capacity margin optimization configuration method considering source load storage interaction characteristics comprises the following steps:
taking the load shedding rate and the wind power wind abandoning rate into consideration, and acquiring a flexible margin index at the power supply side and a capacity margin index at the power grid side;
the total cost of the operation of the power grid is taken as a target, and the acquired flexible margin index of the power supply side and the margin index of the capacity of the power grid are combined to construct a capacity margin model of the power grid;
and solving an optimal solution of the constructed grid capacity margin model to finish the optimal configuration of the grid capacity margin considering the source load storage interaction characteristic.
As a further technical definition, the power side flexible margin index considers the operating characteristics of the generator set and the regulation characteristics of the energy storage power station, including the generator set flexible capacity and the energy storage power station flexible capacity.
Further, the generator set has flexible capacityIs->； wherein ,/>Is 0-1 variable, ">Indicating the up-regulation flexibility of the generator set, +.>Indicating power generation down-regulation flexibility; />Providing capacity for up-regulation flexibility; />Supply capacity for turndown flexibility; and is also provided with
and />Respectively represent the firstiClass unit ofm i The upper limit and the lower limit of the output of the bench unit;Nindicating the total number of unit types,M i represent the firstiThe total number of class units; /> and />Respectively represent the firstiClass unit ofm i Climbing and descending capabilities of the platform unit.
Further, the energy storage power station has flexible capacityIs that
wherein ,is an energy storage power stationtCapacity at time; /> and />Respectively representtTime of day energy storage power stationActual charge and discharge power; /> and />Respectively representing the charging efficiency and the discharging efficiency of the energy storage system; />Is 0-1 variable, ">Indicating the state of charge of the energy storage station +.>Representing a discharge state of the energy storage power station; />To calculate the time interval.
As a further technical definition, the grid-side capacity margin index includes a cut load rate and a wind power rejection rate.
As a further technical definition, the constructed grid capacity margin model includes a power supply capacity benefit margin index and a grid capacity benefit margin index of the multi-region interconnection.
As a further technical definition, the total operation cost of the power grid includes a wind turbine generator set power-losing penalty cost, a load-losing penalty cost, an operation cost of charging and discharging of the energy storage power station, a decision area real-time scheduling cost and a protocol cost of capacity benefit margin.
As further technical definition, constraint conditions of the grid capacity margin model comprise wind power rejection rate upper and lower limit constraint, cut load rate upper and lower limit constraint, energy storage power station power constraint and state of charge constraint, power receiving area reliability constraint and power transmission area self reliability constraint.
According to some embodiments, the second scheme of the application provides a grid capacity margin optimization configuration system considering source load storage interaction characteristics, which adopts the following technical scheme:
a power grid capacity margin optimization configuration system considering source load storage interaction characteristics comprises:
the acquisition module is configured to acquire a power supply side flexible margin index and a power grid side capacity margin index in consideration of a cut load rate and a wind power wind rejection rate;
the modeling module is configured to construct a grid capacity margin model by taking the minimum total running cost of the grid as a target and combining the acquired power supply side flexible margin index and the grid side capacity margin index;
and the optimization module is configured to solve the optimal solution of the constructed grid capacity margin model and complete the optimal configuration of the grid capacity margin considering the interaction characteristics of the source load and the storage.
As a further technical definition, in the obtaining module, the power supply side flexible margin index considers an operation characteristic of the generator set and an adjustment characteristic of the energy storage power station, including a generator set flexible capacity and an energy storage power station flexible capacity.
Further, the generator set has flexible capacityIs->； wherein ,/>Is 0-1 variable, ">Indicating the up-regulation flexibility of the generator set, +.>Indicating power generation down-regulation flexibility; />Providing capacity for up-regulation flexibility; />Supply capacity for turndown flexibility; and is also provided with
and />Respectively represent the firstiClass unit ofm i The upper limit and the lower limit of the output of the bench unit;Nindicating the total number of unit types,M i represent the firstiThe total number of class units; /> and />Respectively represent the firstiClass unit ofm i Climbing and descending capabilities of the platform unit.
Further, the energy storage power station has flexible capacityIs that
wherein ,is an energy storage power stationtCapacity at time; /> and />Respectively representtActual charging and discharging power of the energy storage power station at any moment; /> and />Respectively representing the charging efficiency and the discharging efficiency of the energy storage system; />Is 0-1 variable, ">Indicating the state of charge of the energy storage station +.>Representing a discharge state of the energy storage power station; />To calculate the time interval.
As a further technical definition, in the obtaining module, the grid-side capacity margin index includes a cut load rate and a wind power rejection rate.
As a further technical definition, in the modeling module, the constructed grid capacity margin model includes a power supply capacity benefit margin index and a multi-region interconnected grid capacity benefit margin index.
As a further technical definition, in the modeling module, the total power grid operation cost includes a wind turbine generator power-rejection penalty cost, a load loss penalty cost, an operation cost of charging and discharging the energy storage power station, a decision area real-time scheduling cost and a protocol cost of capacity benefit margin.
As further technical definition, in the modeling module, constraint conditions of the power grid capacity margin model comprise wind power rejection rate upper and lower limit constraint, load shedding rate upper and lower limit constraint, energy storage power station power constraint and state of charge constraint, power receiving area reliability constraint and power transmission area self reliability constraint.
Compared with the prior art, the application has the beneficial effects that:
according to the application, the uncertain factors to be considered in system planning are analyzed, the power supply side flexibility margin is considered, and the power grid side capacity margin index is redefined, so that the comprehensive influence of the economic index of large-scale new energy access and the reliability index of power supply can be reflected, and the quantitative expression and the optimization solution of the power grid capacity margin model are realized; and (3) integrating capacity margin indexes of a power supply side, a load side and a power grid side, establishing a two-stage optimization model of capacity margin of power grid equipment under the condition of considering the operation cost of a generator set, the operation cost of an energy storage power station, the electricity discarding penalty cost of the new energy, the electricity discarding penalty cost of the load side and the inter-region power transmission cost, calculating to obtain an optimal solution of power grid capacity margin configuration considering the interaction characteristic of source and load, and providing analysis indexes for evaluating and analyzing the source load bearing capacity and the new energy absorbing capacity of the regional power grid.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification, illustrate and explain the embodiments and together with the description serve to explain the embodiments.
FIG. 1 is a flowchart of a power grid capacity margin optimization configuration method considering source load storage interaction characteristics according to a first embodiment of the present application;
FIG. 2 shows a first embodiment of the present applicationtA moment system payload probability distribution diagram;
FIG. 3 shows a first embodiment of the present applicationtTime CBM、/>Is a schematic diagram of the relationship of (1);
FIG. 4 is a general frame diagram of a grid capacity margin optimization configuration method considering source load storage interaction characteristics according to a first embodiment of the present application;
fig. 5 is a structural block diagram of a grid capacity margin optimization configuration system taking account of source load storage interaction characteristics in a second embodiment of the application.
Detailed Description
The application will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Embodiments of the application and features of the embodiments may be combined with each other without conflict.
Example 1
The embodiment of the application introduces a power grid capacity margin optimization configuration method considering source load storage interaction characteristics.
The power grid capacity margin optimization configuration method considering the source load storage interaction characteristics shown in fig. 1 comprises the following steps:
taking the load shedding rate and the wind power wind abandoning rate into consideration, and acquiring a flexible margin index at the power supply side and a capacity margin index at the power grid side;
the total cost of the operation of the power grid is taken as a target, and the acquired flexible margin index of the power supply side and the margin index of the capacity of the power grid are combined to construct a capacity margin model of the power grid;
and solving an optimal solution of the constructed grid capacity margin model to finish the optimal configuration of the grid capacity margin considering the source load storage interaction characteristic.
The flexibility margin of the power system in the embodiment considers the influence of the operation characteristics of conventional power supplies such as thermal power, gas power and the like and the adjustment characteristics of the energy storage power station, and provides an engineering quantization method of the power supply side flexibility margin.
The installed proportion of various power supplies of the power grid in different areas has different characteristics, and by taking a Shandong power grid as an example, the installed proportion of the hydropower station in the power grid is small, the nuclear power unit basically operates with fixed output, and the supply side mainly depends on flexible power supplies such as pumping and storing, energy storage and the like and the capacities of conventional power supplies such as gas power, thermal power and the like to form a flexibility margin. The capacity of the power system for coping with large-scale wind power grid connection is measured from the power supply side, and a power supply flexibility margin index and a calculation method thereof are provided.
The sum of the adjustable capacities of all conventional units in each period is equal to the flexible adjustment capacity which can be provided by the system in the period, and the adjustable capacities are respectively called up-regulation flexibility and down-regulation flexibility supply for the condition of load rising and falling, and are specifically shown as a formula (1) and a formula (2):
wherein , and />Respectively represent the firstiClass unit ofm i The upper limit and the lower limit of the output of the bench unit;Nindicating the total number of unit types,M i represent the firstiThe total number of class units; /> and />Respectively represent the firstiClass unit ofm i Climbing and descending capabilities of the platform unit.
The conventional unit thus provides flexibility in capacity of
wherein ,is 0-1 variable, ">Indicating the up-regulation flexibility of the conventional units, +.>Indicating the flexibility of the down-regulation.
The energy storage power station plays a main role in balancing power supply and demand, and is used for improving new energy consumption rate, peak clipping and valley filling and improving power supply reliability. During the use process of the energy storage power station, the energy storage state is always in dynamic change. The linear model of the energy storage system is utilized to quantitatively describe and calculate the energy change condition of the energy storage power station, and the energy calculation formula of the energy storage power station after charge and discharge is as follows
Thus, the energy storage power station provides a flexible capacity of
wherein ,is an energy storage power stationtCapacity at time; /> and />Respectively representtActual charging and discharging power of the energy storage power station at any moment; /> and />Respectively representing the charging efficiency and the discharging efficiency of the energy storage system; />Is 0-1 variable, ">Indicating the state of charge of the energy storage station +.>Representing a discharge state of the energy storage power station; />To calculate the time interval.
The capacity benefit margin CBM (Capacity Benefit Margin) refers to a part of transmission power of a line reserved by the power transmission system of the node where each concentrated load is located for a power supply service company, so as to ensure the supply and demand balance and operation reliability of each node of the power system. The rationality and accuracy of the capacity benefit margin calculation configuration will directly impact the reliability and economy of the power system.
Load shedding rateThe index is an important index for measuring the running reliability and safety of the regional power grid; in a new energy grid-connected system with larger capacity scale, the wind power rejection rate should be considered>Photovoltaic power rejection rate->And factors that the payload fluctuates greatly. Aiming at the situation that new energy power generation becomes the main power supply (analysis is performed by taking wind power as an example) in the future, the load shedding rate based on the reliability index is proposed>And economic index wind power rejection rate ∈>A regional power grid CBM calculation model.
Wind power generation) Output and load demand of equal new energy unit (+)>) The difference of (2) is defined as the net load of the system, i.e
Due to and />Are all attThe random variables of the moment are mutually independent, probability distribution results of wind power output and load prediction are obtained according to a probability prediction method, and a convolution formula is utilized to calculate +.>Probability density function of (2), namely:
wherein ,、/> and />Probability density functions of net load, wind power output and load fluctuation of the system are respectively represented.
And (3) for a certain regional power grid, according to the model, a probability model of wind power plant output, load and net load can be obtained. From the following componentsThe model can be obtainedProbability mass function +.>And draw +.>As shown by curve 2 in figure 2.
The output model of the conventional unit is that
（1）And load shedding rate->Corresponding relation of (3)
When (when)<At 0, the +>Representing the expected value of the load shedding electric quantity, the load shedding rate is expected to be
wherein 、/>Respectively represent the load shedding rate and the pair->The result of the calculation of the cumulative distribution of the probability distribution of the negative regions,/->Representation oftExpected value of moment load probability distribution.
When the regulation effect of the output of the conventional unit is considered, the control methodThe probability of the corresponding region of (2) is integrated to determine the +.>And->Corresponding relation of (3). When the system pair->When the index requirements are different, the CBM value reserved on the transmission section is adjusted, < >>The probability distribution of (c) also changes accordingly. The calculation formula is as follows:
wherein ,indicating that the conventional machine is intThe maximum value of the output at the moment, namely the condition that the up-regulating capacity is fully input. From the above calculation, it can be obtainedtTime CBM value and +.>Is the relation of: let us assume when->Is thatαWhen CBM is 0, as shown in curve 2 of FIG. 2.
If the power system has an improved requirement on the power supply reliability, the requirement on the load loss is expected to be reduced, namelyIs thatβ（α>β) In this case, by increasing the value of the transmission section CBM +.>As shown by the dashed curve 3 in fig. 2, and the transmission section (which is considered as the receiving end region at this time) is calculated to require input from the interconnected transmission regionsφMW power supply, i.e. leaving the transmission sectionφThe capacity benefit margin of MW makes up the shortage of the generating capacity of the system and meets the requirement of the load side.
（2）And->Corresponding relation of (3)
For a system with larger wind power installed capacity scale, the new energy power generation rate is more than 60%, the main power part of power supply in the system is a wind power part with larger fluctuation, and the power output of a conventional unit plays a role in up-regulating and down-regulating more at the moment.
When (when)At > 0>The expected value of the wind power output power electricity rejection amount under the condition of no participation of a conventional unit is shown, and the electricity rejection rate of wind power is expected to be
wherein 、/>Respectively represent wind power rejection rate and pair->The result of the calculation of the cumulative distribution of the probability distribution of the positive-valued areas +.>Representation oftExpected value of wind power output probability distribution at moment.
Taking the regulation function of a conventional unit into account, forThe probability of the corresponding region of (2) is subjected to cumulative distribution processing to determine +.>And->Corresponding relation of (3). When the system pair->When the index requirements are different, the power transmission section (which is regarded as a transmitting end area at this time) is adjusted to leave the CBM size>The probability distribution of (c) varies. The calculation formula is as follows
in the formula Indicating that the conventional machine is intThe minimum value of the moment output force, namely the condition that the down-regulating capacity is completely out of operation. From the above calculation, it can be obtainedtTime CBM value and +.>Is the relation of: let us assume when->Is thatαThe CBM is 0. If the system absorbs wind powerThe requirement is further increased, i.e.)>Is thatβ（α>β) When (I)>The probability distribution of (2) is changed as shown by a dotted curve 1 in figure 2, and the capacity benefit margin left by the transmission section is obtained by calculation–φMW, when the system is a power transmission area, the power receiving area which can be interconnected with the system can be output without exceedingφMW electric energy, and realizes the off-site absorption of wind power.
Separately considering different power system pairsOr->When different indexes are required, the method can correspondingly calculatetCapacity benefit margin required to be reserved for transmission section in time period>Is of a size of (a) and (b). According to->Or->The correspondence with the CBM may be plotted as generally shown in FIG. 3. To take into account only +.>The case of the index is exemplified by the CBM values on the abscissa,/->The size is on the ordinate, if the system requires a reliability index +.>Is->The point marked in the curve can be found, in which case CBM is +.>MW. Namely, in order to meet the requirement of wind power consumption of the system, the CBM size required to be reserved for the power transmission section of the system in the period is +.>MW. In order to simplify the practical application process, the curve can be applied to obtain the corresponding CBM size directly according to different requirements of the power system on wind power consumption indexes during calculation.
Because wind power output and load uncertainty and fluctuation cause the wind power output and load uncertainty and fluctuation to be difficult to predict accurately, and the peak clipping and valley filling regulation effect of the energy storage power station is not considered, and further a capacity benefit margin calculation model established according to a wind power output and load probability distribution model has a certain limitation, in order to solve the problem and improve the consumption proportion of new energy power generation such as wind power, the embodiment provides a two-stage power grid capacity margin configuration method which takes the interaction characteristics of source and load into account in a staged manner as shown in fig. 4.
First stage
Under the condition of taking into account the regulation action of the energy storage power station, the formula (10) and the formula (12) are corrected to respectively obtain a CBM calculation formula taking into account the source charge storage characteristic, wherein the CBM calculation formula is shown as follows
wherein ,、/>respectively representtAnd the charging and discharging states of the energy storage unit are all the time. For->Integrating the probability of the corresponding region to obtain a system wind power electricity rejection expectation (standby redundancy expectation) of +.>And system cut load desire->. When the system has different requirements for two indexes at the same time, decision +.>Is of a size such that->Is changed and at the same time decision +.> and />The system can meet the requirements of two indexes and has economical efficiency.
Under the condition that large-scale wind power grid connection participates in power supply, the calculation model of the capacity margin of the power grid equipment takes the economical efficiency optimization formed by the capacity margin as an objective function, wherein the economic efficiency optimization comprises the electricity discarding punishment cost, the load losing punishment cost, the charging and discharging operation cost of the energy storage power station and the like of the wind turbine. The objective function of the margin model is
wherein , and />Penalty cost coefficients respectively representing the amount of discarded electricity and the amount of cut load; /> and />Respectively representing the cost coefficients of charging and discharging of the energy storage power station; />The subscript 0 of (2) denotes a decision region.
Solving an objective function asThe optimal solution of the grid capacity benefit margin can be obtained by the optimization problem of (1)>Charging and discharging power of energy storage power station>And its operating state parameters->. Constraint conditions comprise wind power electricity rejection rate, upper limit constraint, lower limit constraint of load shedding rate, power constraint of energy storage power station, state of charge constraint and the like, and the constraint conditions are as follows
wherein ,representing the charge or discharge power of the energy storage power station; />Representing the charge state of the energy storage power station after charging and discharging; />Representing the rated capacity of the energy storage power station.
Second stage
According totAnd (3) according to the actual running condition of the system at the moment, solving the grid capacity benefit margin index of the multi-region interconnection by taking the minimum protocol cost of the real-time scheduling cost and the capacity benefit margin of the decision region as an objective function. The objective function of the second stage is
wherein ,indicating that the interconnection area g is intThe protocol cost function of CBM reserved for decision area through transmission section at moment is as follows
wherein ,representation oftTime of daygThe area is a blockA CBM for taking the area; />Indicating machine setjThe power provided for the CBM is reserved; />Representing a regiongProtocol cost coefficients that leave capacity benefit margins for decision regions. The part mainly comprises the reliability constraint of a power receiving area and the reliability constraint of a power transmission area per se, and is specifically as follows
Solving the second stage objective function asOptimal solution of the optimization problem->Finally, the optimal solution of the grid capacity margin index considering the source load storage interaction characteristic is obtained>And its optimal solution for each regional interconnect>。
According to the embodiment, the uncertain factors to be considered in system planning are analyzed, the power supply side flexibility margin is considered, and the power grid side capacity margin index is redefined, so that the comprehensive influence of the economic index of large-scale new energy access and the reliability index of power supply can be reflected, and the quantitative expression and the optimal solution of a power grid capacity margin model are realized; and (3) integrating capacity margin indexes of a power supply side, a load side and a power grid side, establishing a two-stage optimization model of capacity margin of power grid equipment under the condition of considering the operation cost of a generator set, the operation cost of an energy storage power station, the electricity discarding penalty cost of the new energy, the electricity discarding penalty cost of the load side and the inter-region power transmission cost, calculating to obtain an optimal solution of power grid capacity margin configuration considering the interaction characteristic of source and load, and providing analysis indexes for evaluating and analyzing the source load bearing capacity and the new energy absorbing capacity of the regional power grid.
Example two
The second embodiment of the application introduces a power grid capacity margin optimizing configuration system considering source-load storage interaction characteristics.
The grid capacity margin optimizing configuration system considering the source load storage interaction characteristic as shown in fig. 5 comprises:
the acquisition module is configured to acquire a power supply side flexible margin index and a power grid side capacity margin index in consideration of a cut load rate and a wind power wind rejection rate;
the modeling module is configured to construct a grid capacity margin model by taking the minimum total running cost of the grid as a target and combining the acquired power supply side flexible margin index and the grid side capacity margin index;
and the optimization module is configured to solve the optimal solution of the constructed grid capacity margin model and complete the optimal configuration of the grid capacity margin considering the interaction characteristics of the source load and the storage.
The detailed steps are the same as those of the grid capacity margin optimization configuration method considering the source load storage interaction characteristic provided in the first embodiment, and are not described herein again.
The above description is only a preferred embodiment of the present embodiment, and is not intended to limit the present embodiment, and various modifications and variations can be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.
Claims (8)
1. The power grid capacity margin optimization configuration method considering the source load storage interaction characteristic is characterized by comprising the following steps of:
taking the operation characteristics of the generator set and the adjustment characteristics of the energy storage power station into consideration, wherein the operation characteristics comprise the flexibility capacity of the generator set and the flexibility capacity of the energy storage power station, and acquiring a flexible margin index of a power supply side; taking the load shedding rate and the wind power wind discarding rate into consideration to obtain a capacity margin index of a power grid side;
the method comprises the steps of taking the minimum total running cost of a power grid as a target, combining the acquired flexible margin index of a power supply side and the margin index of a capacity of the power grid, constructing a capacity margin model of the power grid, wherein the total running cost of the power grid comprises the power discarding punishment cost, the load losing punishment cost, the running cost of charging and discharging of an energy storage power station, the real-time scheduling cost of a decision area and the protocol cost of capacity benefit margin, and the constructed capacity margin model of the power grid comprises the margin index of the power supply capacity benefit and the margin index of the capacity benefit of the power grid of multi-area interconnection;
and solving the constructed grid capacity margin model to obtain an optimal solution, and completing the optimal configuration of the grid capacity margin considering the source load storage interaction characteristic.
2. The power grid capacity margin optimization configuration method considering source load storage interaction characteristics as set forth in claim 1, wherein the power generating set flexible capacityIs->； wherein ,/>Is 0-1 variable, ">Indicating the up-regulation flexibility of the generator set, +.>Indicating power generation down-regulation flexibility；/>Providing capacity for up-regulation flexibility; />Supply capacity for turndown flexibility; and is also provided with
and />Respectively represent the firstiClass unit ofm i The upper limit and the lower limit of the output of the bench unit;Nindicating the total number of unit types,M i represent the firstiThe total number of class units; /> and />Respectively represent the firstiClass unit ofm i Climbing and descending capabilities of the platform unit.
3. The power grid capacity margin optimization configuration method considering source load storage interaction characteristics as set forth in claim 1, wherein the energy storage power station is flexible in capacityIs that
wherein , and />Respectively representtActual charging and discharging power of the energy storage power station at any moment; />Is a variable which is 0 to 1,indicating the state of charge of the energy storage station +.>Indicating the discharge state of the energy storage power station.
4. The power grid capacity margin optimization configuration method considering source load storage interaction characteristics according to claim 1, wherein constraint conditions of the power grid capacity margin model comprise wind power rejection rate upper and lower limit constraint, load shedding rate upper and lower limit constraint, energy storage power station power constraint and state of charge constraint, power receiving area reliability constraint and power transmission area self reliability constraint.
5. The utility model provides a power grid capacity margin optimal configuration system that takes into account source lotus stores interactive characteristic which characterized in that includes:
the power supply side flexible margin index is acquired by taking the operation characteristics of the generator set and the adjustment characteristics of the energy storage power station into consideration, wherein the operation characteristics comprise the flexibility capacity of the generator set and the flexibility capacity of the energy storage power station; taking the load shedding rate and the wind power wind discarding rate into consideration to obtain a capacity margin index of a power grid side;
the modeling module is configured to construct a grid capacity margin model by taking the minimum total running cost of the power grid as a target and combining the acquired flexible margin index of the power source side and the margin index of the capacity of the power grid, wherein the total running cost of the power grid comprises the power discarding punishment cost, the load losing punishment cost, the charging and discharging running cost of the energy storage power station, the real-time scheduling cost of a decision area and the protocol cost of the capacity margin, and the constructed grid capacity margin model comprises the margin index of the power source capacity margin and the margin index of the capacity margin of the power grid of multi-area interconnection;
and the optimization module is configured to solve the constructed grid capacity margin model to obtain an optimal solution, and complete the optimal configuration of the grid capacity margin considering the source load storage interaction characteristic.
6. The grid capacity margin optimization configuration system considering source load storage interaction characteristics as recited in claim 5, wherein said generating set is flexible in capacityIs->； wherein ,/>Is 0-1 variable, ">Indicating the up-regulation flexibility of the generator set, +.>Indicating power generation down-regulation flexibility; />Providing capacity for up-regulation flexibility; />Supply capacity for turndown flexibility; and is also provided with
and />Respectively represent the firstiClass unit ofm i The upper limit and the lower limit of the output of the bench unit;Nindicating the total number of unit types,M i represent the firstiThe total number of class units; /> and />Respectively represent the firstiClass unit ofm i Climbing and descending capabilities of the platform unit.
7. The grid capacity margin optimization configuration system considering source-load storage interaction characteristics as set forth in claim 5, wherein said energy storage power station has a flexible capacityIs that
wherein , and />Respectively representtActual charging and discharging power of the energy storage power station at any moment; />Is a variable which is 0 to 1,indicating the state of charge of the energy storage station +.>Indicating the discharge state of the energy storage power station.
8. The grid capacity margin optimization configuration system considering source-charge storage interaction characteristics according to claim 5, wherein in the modeling module, constraint conditions of a grid capacity margin model comprise wind power rejection rate upper and lower limit constraint, load shedding rate upper and lower limit constraint, energy storage power station power constraint and state of charge constraint, power receiving area reliability constraint and power transmission area self reliability constraint.
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