CN114881351A - Fine-grained calculation method for distribution network admission distributed power generation capacity in virtual power plant - Google Patents
Fine-grained calculation method for distribution network admission distributed power generation capacity in virtual power plant Download PDFInfo
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Abstract
The invention discloses a fine-grained calculation method for the distribution network admission distributed power generation capacity in a virtual power plant, which comprises the following steps: collecting virtual power plant information; inputting the virtual power plant information into a pre-constructed distribution network power flow model and a pre-constructed distributed power generation output model for calculation to respectively obtain distribution network balance data and photovoltaic and fan power generation output data; and inputting the distribution network balance data and the photovoltaic and fan power generation output data into a pre-constructed optimal coordination scheduling model of the distributed power generation accepting capability, and performing optimization solution based on a preset fine-grained safe operation constraint condition to obtain fine-grained data of the distribution network accepting distributed power generation capability. The fine-grained calculation method for the distributed power generation accepting capacity of the distribution network in the virtual power plant can consider key factors of the virtual power plant, provide technical support for actual installed capacity model selection of distributed power generation, and further promote rapid development, popularization and application of the virtual power plant.
Description
Technical Field
The invention relates to a fine-grained calculation method for the distribution network admission distributed power generation capacity in a virtual power plant, and belongs to the technical field of virtual power plants.
Background
The virtual power plant is formed by aggregating a controllable unit and an uncontrollable unit such as distributed energy sources of wind, light and the like, energy storage, controllable load, an electric vehicle, communication equipment and the like, further considers elements such as demand response, uncertainty and the like, and realizes energy exchange with a large power grid by carrying out information communication with a control center, a cloud center, an electric power trading center and the like. In a broader concept, virtual power plants are a high degree of aggregation of energy based on the internet, and diverse derivative services that can be developed on this basis, with the core being "aggregation" and "communication". The resources are aggregated, the accessed resources participate in power grid interaction, the interaction content comprises demand response, auxiliary service, electric power spot transaction and the like, the running state of the power grid is optimized, the participation of the power market is wide, and the virtual power plant is a main service which can be provided by a virtual power plant in the near term and the long term.
Compared with the regulation mode of demand response, the virtual power plant has more diversified users such as energy storage, distributed power generation, controllable load and the like, when the users participate in regulation, the users on the load side can regulate the increase and decrease of the power consumption of the users, and the users on the energy storage side and the power supply side can be gathered to regulate the electric energy output, so that the virtual power plant has rich regulation modes and means. From the viewpoint of the operation scheme of the virtual power plant, the virtual power plant is divided into a commercial virtual power plant and a technical virtual power plant. Commercial virtual power plants generally cooperate with conventional power generation units to participate in power market competition and jointly implement an optimal power generation plan, whereas technical virtual power plants provide aggregated resources to system operators to achieve system balance at the lowest cost.
The virtual power plant can play the role of a 'positive power plant' or a 'negative power plant' in the power grid due to the aggregation of various energy resources including adjustable load, energy storage, micro-grid, electric automobile, distributed energy and the like. The system can be used as a positive power plant to supply power to the system for peak shaving, can be used as a negative power plant to increase load absorption, is matched with the system for valley filling, can quickly respond to instructions, is matched with the guarantee system to be stable and obtain economic subsidies, and can even be further equivalent to the power plant to participate in various power markets such as capacity, electric quantity, auxiliary service and the like to obtain economic benefits. In the prior art, a fine-grained calculation method capable of considering key factors of a virtual power plant and realizing distributed power generation accepting capability of a distribution network in the virtual power plant is urgently needed, technical support is provided for model selection of actual installed capacity of distributed power generation, and rapid development, popularization and application of the virtual power plant are further promoted.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a fine-grained calculation method for the distributed power generation accepting capacity of a distribution network in a virtual power plant, can consider key factors of the virtual power plant, provides technical support for the actual installed capacity model selection of distributed power generation, and further promotes the rapid development, popularization and application of the virtual power plant.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the fine-grained calculation method for the distributed power generation accepting capacity of the distribution network in the virtual power plant comprises the following steps:
collecting virtual power plant information;
inputting the virtual power plant information into a pre-constructed distribution network power flow model and a pre-constructed distributed power generation output model for calculation to respectively obtain distribution network balance data and photovoltaic and fan power generation output data;
and inputting the distribution network balance data and the photovoltaic and fan power generation output data into a pre-constructed optimal coordination scheduling model of the distributed power generation accepting capability, and performing optimization solution based on a preset fine-grained safe operation constraint condition to obtain fine-grained data of the distribution network accepting distributed power generation capability.
The method comprises the steps that virtual power plant information is collected, wherein the virtual power plant information comprises photovoltaic power generation characteristic data, fan power generation characteristic data, electric energy storage characteristic data, controllable electric load data, conventional electric load data, new energy grid-connected interface physical characteristic data, new energy grid-connected point data, a distribution network physical topological structure and a virtual power plant coordination scheduling mode; the fine-grained data of the distributed power generation accepting capacity of the distribution network comprise maximum photovoltaic power generation access distribution network power, maximum fan power generation access distribution network power, electric energy storage charging and discharging power, actual electric power consumption of controllable electric loads, new energy grid-connected interface power transmission values, distribution network node voltage amplitude values, distribution network node voltage phase angles and optimal values of distributed power generation accepting capacity of the distribution network in a virtual power plant.
The power balance equation expression of the distribution network power flow model is as follows:
wherein:
in the formula: p p 、Q p Respectively injecting active power and reactive power at a distribution network node p; u shape p 、U q Voltage amplitudes at the nodes p and q of the distribution network are respectively; g pq 、B pq Respectively the conductance and susceptance of the branch pq; theta pq The voltage phase angle difference of the nodes p and q of the distribution network is obtained; q belongs to p and represents all branches connected with the distribution network node p, and the branch end points are the node p and the node q respectively;
respectively providing photovoltaic power generation output, fan power generation output, conventional generator set output, electric energy power transmitted by a tie line, electric energy storage discharge power, electric load demand and electric energy storage charging power at the p-th node in the distribution network;
respectively providing photovoltaic power generation reactive power output, fan power generation reactive power output, conventional generator set reactive power output, reactive power transmitted by a tie line, electric energy storage discharge reactive power, electric load reactive power demand and electric energy storage charging reactive power at a p-th node in a distribution network;
and adjusting the factor for the controllable load at the distribution network node p.
The expression of the distributed generation output model is as follows:
in the formula: beta is a pv Is a photovoltaic power generation output factor; chi shape pv Receiving photovoltaic power generation factors for a distribution network; l is pv 、L st Respectively testing the real-time illumination intensity of the photovoltaic power generation working environment and the illumination intensity of the photovoltaic power generation working environment in a standard test environment; delta pv Adjusting factors for the output temperature change of the photovoltaic power generation; t is ope 、T amb Respectively representing the real-time temperature of the photovoltaic power generation working environment and the temperature of the photovoltaic power generation working environment in a standard test environment;
the photovoltaic power generation output under the standard test environment is provided;
the photovoltaic power generation output at the ith node in the distribution network;
(4b) the expression of the fan power generation model is as follows:
in the formula:
is prepared forGenerating output of a fan at the jth node in the network;
rated capacity for fan power generation; v, v in 、v rat 、v out The real-time wind speed, the starting wind speed, the rated wind speed and the cut-off wind speed of the working environment of the fan are respectively.
Fine-grained safe operation constraints include:
the power supply side safe operation constraint conditions are as follows:
the installed capacity constraint expression of a single photovoltaic power generation is as follows:
in the formula:
outputting power for photovoltaic power generation at the ith node in the distribution network;
respectively representing the lower limit and the upper limit of installed capacity of the photovoltaic power generation;
the photovoltaic power generation total installed capacity constraint expression is as follows:
in the formula:
the photovoltaic power generation output power at the ith node and the electric load demand at the kth node in the distribution network are respectively obtained; n is pv 、n load The total number of the grid nodes which are incorporated into the photovoltaic in the distribution network and the total number of the grid nodes with loads are respectively; epsilon pv 、
Are respectively photovoltaicPermeability factor, photovoltaic permeability factor upper limit value accepted by the distribution network; i. k is different power grid nodes in the distribution network;
the single fan power generation installed capacity constraint expression is as follows:
in the formula:
generating output power for a fan at the jth node in the distribution network;
respectively setting the lower limit and the upper limit of the installed capacity of the fan;
the constraint expression of the total installed capacity of the fan power generation is as follows:
in the formula:
respectively outputting power generated by a fan at the jth node in the distribution network and requiring the electrical load at the kth node; n is wp 、n load Respectively counting the total number of the grid nodes which incorporate wind power in the distribution network and the total number of the grid nodes with loads; epsilon wp 、
Wind power permeability factors and wind power permeability factor upper limit values acceptable to a distribution network are respectively set; j. k is different power grid nodes in the distribution network;
the conventional generator set safe operation constraint expression is as follows:
in the formula:
generating power for a conventional generator set at the mth node in the distribution network;
respectively is the lower limit and the upper limit of the power output generated by the conventional generator set; x is a radical of a fluorine atom gen The value of the starting and stopping state variable of the conventional generator set is 0 during operation and 1 during shutdown;
the physical transmission constraint expression of the distribution network tie line is as follows:
in the formula:
electric energy power transmitted for the nth tie line in the distribution network, wherein in the virtual power plant
When in use
When the value is negative, the distribution network sells electricity to a large power grid,
when the value is positive, the distribution network purchases electricity to the large power grid;
respectively transmitting a lower limit and an upper limit of power for the distribution network tie line;
the constraint conditions for safe operation at the power grid side are as follows:
the node voltage constraint expression is as follows:
in the formula: u shape p 、
Respectively representing the voltage amplitude at the distribution network node p, the lower limit of the voltage amplitude and the upper limit of the voltage amplitude;
the branch power flow constraint expression is as follows:
in the formula: s pq 、
Respectively indicating the apparent power of the distribution network branch pq, the lower limit of the apparent power and the upper limit of the apparent power;
the controllable load adjustment factor constraint expression is as follows:
in the formula:
respectively setting a controllable load adjustment factor, a lower limit of the controllable load adjustment factor and an upper limit of the controllable load adjustment factor at a distribution network node p;
the electric energy storage charging and discharging power constraint expression is as follows:
in the formula:
respectively providing electric energy storage discharge power and electric energy storage charging power at the p-th node in the distribution network;
the upper limit of the electrical energy storage discharge power and the upper limit of the electrical energy storage charging power at the p-th node in the distribution network are respectively set.
The specific expression of the optimal coordination scheduling model of the distributed generation admission capacity is as follows:
in the formula: ABI is an index of the distributed generation receiving capacity of a distribution network in a virtual power plant; alpha is alpha re The importance factor of the new energy distributed power generation is defined;
respectively providing photovoltaic power generation output at the ith node and fan power generation output at the jth node in the distribution network; n is pv 、n wp The total number of grid nodes which are merged into photovoltaic and the total number of grid nodes which are merged into wind power in the distribution network are respectively; i. j is different grid nodes in the distribution network.
New energy distributed power generation importance factor alpha re Determining a distributed generation admission capacity optimal coordination scheduling mode with a series of specific settings through artificial setting or directly distributing new energy sources through non-artificial setting to generate an importance factor alpha re And performing coordinated scheduling as an optimization variable.
The invention has the beneficial effects that: (1) from the perspective of a technical virtual power plant, key factors of new energy, electric energy storage, controllable load, conventional load, a distribution network topological structure and the like of a distribution network in the virtual power plant are comprehensively considered, a distributed generation receptivity model is established, then a distributed generation receptivity optimal coordination scheduling model is further provided, the virtual power plant is favorably expanded to the ground in a complex and changeable distribution network service direction, technical support is provided for the selection of the actual installed capacity of distributed generation, and the rapid development, popularization and application of the virtual power plant are further promoted; (2) the invention provides a mode of artificially setting and non-artificially setting the importance factor of the distributed power generation of new energy, which is more in line with the application requirement of the distributed power generation capability multi-scene calculation engineering of the distribution network in a real virtual power plant; (3) the invention establishes a fine-grained safe operation constraint condition, and can conveniently provide theoretical guidance and reference for fine modeling of the distributed power generation accepting capacity of the distribution network in the virtual power plant, fine-grained calculation application, actual installed capacity model selection of distributed power generation, multi-mode coordinated scheduling and the like.
Drawings
FIG. 1 is a flow chart of a fine-grained calculation method for the distribution network admission distributed power generation capacity in a virtual power plant according to the present invention;
fig. 2 is a structural diagram of an example of a fine-grained calculation method for distribution network admission distributed power generation capacity in a virtual power plant according to the present invention.
Detailed Description
The present invention is further described with reference to the accompanying drawings, and the following examples are only for clearly illustrating the technical solutions of the present invention, and should not be taken as limiting the scope of the present invention.
Detailed description of the preferred embodiment 1
As shown in fig. 1, the invention discloses a fine-grained calculation method for distribution network admission distributed power generation capacity in a virtual power plant, which comprises the following steps:
step one, collecting virtual power plant information. The method comprises the steps of collecting virtual power plant information, wherein the virtual power plant information comprises photovoltaic power generation characteristic data, fan power generation characteristic data, electric energy storage characteristic data, controllable electric load data, conventional electric load data, new energy grid-connected interface physical characteristic data, new energy grid-connected point data, a distribution network physical topological structure, a virtual power plant coordination scheduling mode and the like.
Step two, establishing a distributed generation admitting ability model, wherein the distributed generation admitting ability of the distribution network in the virtual power plant mainly considers the capability of admitting new energy distributed generation, namely photovoltaic power generation and fan power generation, and the expression of the distributed generation admitting ability is as follows:
in the formula: ABI is an index of the distributed generation receiving capacity of a distribution network in a virtual power plant; alpha is alpha re The importance factor of the new energy distributed power generation is defined;
respectively providing photovoltaic power generation output at the ith node and fan power generation output at the jth node in the distribution network; n is pv 、n wp The total number of grid nodes which are merged into photovoltaic and the total number of grid nodes which are merged into wind power in the distribution network are respectively; i. j is different grid nodes in the distribution network.
Step three, establishing a distribution network power flow model, wherein the power balance equation expression of the distribution network is as follows:
wherein:
in the formula: p p 、Q p Respectively injecting active power and reactive power at a distribution network node p; u shape p 、U q Voltage amplitudes at nodes p and q of the distribution network are respectively; g pq 、B pq Respectively the conductance and susceptance of the branch pq; theta pq The voltage phase angle difference of the nodes p and q of the distribution network is obtained; q belongs to p and represents all branches connected with the distribution network node p, and the branch end points are the node p and the node q respectively;
respectively providing photovoltaic power generation output, fan power generation output, conventional generator set output, electric energy power transmitted by a tie line, electric energy storage discharge power, electric load demand and electric energy storage charging power at the p-th node in the distribution network;
respectively providing photovoltaic power generation reactive power output, fan power generation reactive power output, conventional generator set reactive power output, reactive power transmitted by a tie line, electric energy storage discharge reactive power, electric load reactive power demand and electric energy storage charging reactive power at a p-th node in a distribution network;
and adjusting the factor for the controllable load at the distribution network node p.
Step four, establishing a distributed power generation output model, which comprises a photovoltaic power generation model and a fan power generation model:
A. photovoltaic power generation model
The expression of the photovoltaic power generation model is as follows:
in the formula: beta is a pv Is a photovoltaic power generation output factor; chi shape pv Receiving photovoltaic power generation factors for a distribution network; l is pv 、L st Respectively testing the real-time illumination intensity of the photovoltaic power generation working environment and the illumination intensity of the photovoltaic power generation working environment in a standard test environment; delta. for the preparation of a coating pv Adjusting factors for the output temperature change of the photovoltaic power generation; t is a unit of ope 、T amb Respectively representing the real-time temperature of the photovoltaic power generation working environment and the temperature of the photovoltaic power generation working environment in a standard test environment;
the photovoltaic power generation output under the environment is tested according to standard specifications;
and (4) outputting power by photovoltaic power generation at the ith node in the distribution network.
B. Fan power generation model
The expression of the fan power generation model is as follows:
in the formula:
generating output power for a fan at the jth node in the distribution network;
rated capacity for fan power generation; v, v in 、v rat 、v out The real-time wind speed, the starting wind speed, the rated wind speed and the cut-off wind speed of the working environment of the fan are respectively.
And fifthly, setting fine-grained safe operation constraint conditions, wherein the fine-grained safe operation constraint conditions mainly comprise power supply side safe operation constraint conditions and power grid side safe operation constraint conditions.
A. Power supply side safety operation constraint condition
A1, photovoltaic power generation safe operation constraint
The installed capacity constraint expression of a single photovoltaic power generation is as follows:
in the formula:
outputting power for photovoltaic power generation at the ith node in the distribution network;
respectively is the lower limit and the upper limit of the installed capacity of the photovoltaic power generation.
The constraint expression of the total installed capacity of photovoltaic power generation is as follows:
in the formula:
the photovoltaic power generation output power at the ith node and the electric load demand at the kth node in the distribution network are respectively obtained; n is pv 、n load The total number of the grid nodes which are incorporated into the photovoltaic in the distribution network and the total number of the grid nodes with loads are respectively; epsilon pv 、
Respectively the photovoltaic permeability factor and the upper limit value of the photovoltaic permeability factor which can be accepted by the distribution network; i. and k is different power grid nodes in the distribution network.
A2, wind turbine power generation safe operation constraint
The single fan power generation installed capacity constraint expression is as follows:
in the formula:
generating output power for a fan at the jth node in the distribution network;
the lower limit and the upper limit of the installed capacity of the fan power generation are respectively.
The constraint expression of the total installed capacity of the fan power generation is as follows:
in the formula:
respectively outputting power generated by a fan at the jth node in the distribution network and requiring the electrical load at the kth node; n is wp 、n load Respectively counting the total number of the grid nodes which incorporate wind power in the distribution network and the total number of the grid nodes with loads; epsilon wp 、
Wind power permeability factors and wind power permeability factor upper limit values acceptable to a distribution network are respectively set; j. and k is different power grid nodes in the distribution network.
A3, safety operation restraint of conventional generator set
The safe operation constraint expression of the conventional generator set is as follows:
in the formula:
generating output power for a conventional generator set at the mth node in the distribution network;
respectively is the lower limit and the upper limit of the power output generated by the conventional generator set; x is the number of gen The value of the starting and stopping state variable of the conventional generator set is 0 during operation and 1 during shutdown.
A4 distribution network tie line physical transmission constraint
The physical transmission constraint expression of the distribution network tie line is as follows:
in the formula:
electric energy power transmitted for the nth tie line in the distribution network, wherein in the virtual power plant
When in use
When the value is negative, the distribution network sells electricity to a large power grid,
when the value is positive, the distribution network purchases electricity from the large power grid;
and respectively transmitting a lower limit and an upper limit of power for the distribution network tie line.
B. Constraint condition for safe operation of power grid side
The node voltage constraint expression is:
in the formula: u shape p 、
The voltage amplitude, the lower limit of the voltage amplitude and the upper limit of the voltage amplitude at the distribution network node p are respectively.
The branch power flow constraint expression is as follows:
in the formula: s pq 、
The power distribution network branch pq is respectively the apparent power, the lower limit of the apparent power and the upper limit of the apparent power.
The controllable load adjustment factor constraint expression is as follows:
in the formula:
respectively a controllable load adjustment factor at the distribution network node p, a lower limit and a controllable load of the controllable load adjustment factorUpper limit of the charge adjustment factor.
The electric energy storage charging and discharging power constraint expression is as follows:
in the formula:
respectively providing electric energy storage discharge power and electric energy storage charging power at the p-th node in the distribution network;
the upper limit of the electrical energy storage discharge power and the upper limit of the electrical energy storage charging power at the p-th node in the distribution network are respectively set.
Step six, providing a distributed generation admission capacity optimal coordination scheduling model, wherein the expression of the distributed generation admission capacity optimal coordination scheduling model is as follows:
in the formula: ABI is an index of the distributed generation receiving capacity of a distribution network in a virtual power plant; alpha is alpha re The importance factor of the new energy distributed power generation is defined;
respectively providing photovoltaic power generation output at the ith node and fan power generation output at the jth node in the distribution network; n is pv 、n wp The total number of grid nodes which are merged into photovoltaic and the total number of grid nodes which are merged into wind power in the distribution network are respectively; i. j is different grid nodes in the distribution network.
By artificially setting the importance factor alpha of new energy distributed generation re The numerical value can determine a series of specially set optimal coordination scheduling modes of the distributed power generation admission capacity, and can also directly set the new energy distributed power generation importance factor alpha without manual setting re And performing coordinated scheduling as an optimization variable.
And seventhly, outputting the information of the virtual power plant to obtain fine-grained data of the distributed power generation accepting capacity of the distribution network, wherein the fine-grained data comprises information such as maximum photovoltaic power generation access distribution network power, maximum fan power generation access distribution network power, electric energy storage charging and discharging power, actual consumption electric power of controllable electric loads, a new energy grid-connected interface power transmission value, distribution network node voltage amplitude, distribution network node voltage phase angle, optimal distribution network distributed power generation accepting capacity values in the virtual power plant and the like.
Specific example 2
The architecture and topology of the fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant are shown in FIG. 2. As shown in fig. 2, the distribution network architecture and topology are exemplified by IEEE33 system, the voltage class is 12.66kV, wherein the values 1 to 33 are distribution network power node numbers; the photovoltaic power generation is respectively connected into a node 8, a node 29 and a node 31; wherein, the wind power is respectively accessed into the node 4 and the node 14; the nodes 16, 25 and 33 are connected with controllable loads, and other load nodes default to conventional loads; the node 1 is interconnected with a large power grid through a tie line; the conventional unit is respectively connected into the node 3 and the node 26; in the electrical energy storage access node 11; the control mode of the virtual power plant is centralized control of a centralized scheme, namely distributed power generation, power load and energy storage are in two-way communication with the virtual power plant, and the virtual power plant masters all terminal information and is uniformly controlled by a control coordination center of the virtual power plant; the virtual power plant adopts a technical type virtual power plant coordination scheduling mode.
As shown in fig. 1, the invention discloses a fine-grained calculation method for distribution network admission distributed power generation capacity in a virtual power plant, which comprises the following steps: acquiring virtual power plant information including nodes of the existing basic photovoltaic power generation, fan power generation, conventional units, electric energy storage, controllable electric loads, conventional electric loads and tie line planning access; physical characteristic limitations of individual access points; external characteristics of photovoltaic power generation, fan power generation, a conventional unit, electric energy storage and controllable electric load; a virtual plant coordinated scheduling mode is initialized. And determining each parameter value in the distribution network power flow model. And setting a complete fine-grained safe operation constraint condition. And performing optimal coordinated scheduling on distributed generation acceptance capacity, giving an operation result, and outputting virtual power plant information, wherein the virtual power plant information comprises information such as maximum photovoltaic generation access distribution network power, maximum fan generation access distribution network power, electric energy storage charge-discharge power, actual controllable electric load consumption power, new energy grid-connected interface power transmission value, distribution network node voltage amplitude, distribution network node voltage phase angle, optimal distributed generation acceptance capacity value of a distribution network in a virtual power plant and the like. And determining the optimal result of the distributed power generation receiving capacity, reversely determining and selecting the actual appropriate new energy installed capacity according to the result, and verifying. And finishing the calculation process on the basis of the capacity check suitability and no change of the numerical mode setting of the new energy distributed generation importance factor.
According to the description of the embodiment and the introduction and analysis of the specific implementation process, the fine-grained calculation method for the distributed power receiving capacity of the distribution network in the virtual power plant is effective, practical, easy to operate and reasonable, and can provide theoretical guidance and reference for fine modeling of the distributed power receiving capacity of the distribution network in the virtual power plant, fine-grained calculation application, actual installed capacity selection of distributed power generation, multi-mode coordinated scheduling and the like.
The above is only a preferred embodiment of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (7)
1. The fine-grained calculation method for the distributed power generation accepting capacity of the distribution network in the virtual power plant is characterized by comprising the following steps of: the method comprises the following steps:
collecting virtual power plant information;
inputting the virtual power plant information into a pre-constructed distribution network power flow model and a pre-constructed distributed power generation output model for calculation to respectively obtain distribution network balance data and photovoltaic and fan power generation output data;
and inputting the distribution network balance data and the photovoltaic and fan power generation output data into a pre-constructed optimal coordination scheduling model of the distributed power generation accepting capability, and performing optimization solution based on a preset fine-grained safe operation constraint condition to obtain fine-grained data of the distribution network accepting distributed power generation capability.
2. The fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant according to claim 1, characterized by comprising the following steps: the virtual power plant information comprises photovoltaic power generation characteristic data, fan power generation characteristic data, electric energy storage characteristic data, controllable electric load data, conventional electric load data, new energy grid-connected interface physical characteristic data, new energy grid-connected point data, a distribution network physical topological structure and a virtual power plant coordination scheduling mode; the fine-grained data of the distributed power generation accepting capacity of the distribution network comprise maximum photovoltaic power generation access distribution network power, maximum fan power generation access distribution network power, electric energy storage charging and discharging power, actual electric power consumption of controllable electric loads, a new energy grid-connected interface power transmission value, a distribution network node voltage amplitude value, a distribution network node voltage phase angle and an optimal value of distributed power generation accepting capacity of the distribution network in a virtual power plant.
3. The fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant according to claim 1, characterized by comprising the following steps: the pre-constructed power balance equation expression of the distribution network power flow model is as follows:
wherein:
in the formula: p p 、Q p Respectively injecting active power and reactive power at a distribution network node p; u shape p 、U q Voltage amplitudes at the nodes p and q of the distribution network are respectively; g pq 、B pq Respectively the conductance and susceptance of the branch pq; theta pq The voltage phase angle difference of the nodes p and q of the distribution network is obtained; q belongs to p and represents all branches connected with the distribution network node p, and the branch end points are the node p and the node q respectively;
respectively providing photovoltaic power generation output, fan power generation output, conventional generator set output, electric energy power transmitted by a tie line, electric energy storage discharge power, electric load demand and electric energy storage charging power at the p-th node in the distribution network;
respectively providing photovoltaic power generation reactive power output, fan power generation reactive power output, conventional generator set reactive power output, reactive power transmitted by a tie line, electric energy storage discharge reactive power, electric load reactive power demand and electric energy storage charging reactive power at a p-th node in a distribution network;
and adjusting the factor for the controllable load at the distribution network node p.
4. The fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant according to claim 1, characterized by comprising the following steps: the pre-constructed distributed power generation output model comprises a fan power generation model and a fan power generation model, and the expression is as follows:
the expression of the fan power generation model is as follows:
in the formula: beta is a pv For photovoltaic power generationA force factor; chi shape pv Receiving photovoltaic power generation factors for a distribution network; l is a radical of an alcohol pv 、L st Respectively testing the real-time illumination intensity of the photovoltaic power generation working environment and the illumination intensity of the photovoltaic power generation working environment in a standard test environment; delta pv Adjusting factors for the output temperature change of the photovoltaic power generation; t is ope 、T amb Respectively representing the real-time temperature of the photovoltaic power generation working environment and the temperature of the photovoltaic power generation working environment in a standard test environment;
the photovoltaic power generation output under the environment is tested according to standard specifications;
the photovoltaic power generation output at the ith node in the distribution network;
the expression of the fan power generation model is as follows:
in the formula:
generating output for a fan at the jth node in the distribution network;
rated capacity for fan power generation; v, v in 、v rat 、v out The real-time wind speed, the starting wind speed, the rated wind speed and the cut-off wind speed of the working environment of the fan are respectively.
5. The fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant according to claim 1, characterized by comprising the following steps: the pre-constructed optimal coordination scheduling model of the distributed power generation receiving capacity is optimized and solved based on pre-constructed fine-grained safe operation constraint conditions;
the fine-grained safe operation constraint condition comprises a power supply side safe operation constraint condition and a power grid side safe operation constraint condition:
the power supply side safe operation constraint conditions are as follows:
the installed capacity constraint expression of a single photovoltaic power generation is as follows:
in the formula:
outputting power for photovoltaic power generation at the ith node in the distribution network;
respectively representing the lower limit and the upper limit of installed capacity of the photovoltaic power generation;
the photovoltaic power generation total installed capacity constraint expression is as follows:
in the formula:
the photovoltaic power generation output power at the ith node and the electric load demand at the kth node in the distribution network are respectively obtained; n is pv 、n load The total number of the grid nodes which are incorporated into the photovoltaic in the distribution network and the total number of the grid nodes with loads are respectively; epsilon pv 、
Respectively the photovoltaic permeability factor and the upper limit value of the photovoltaic permeability factor which can be accepted by the distribution network; i. k is different power grid nodes in the distribution network;
the single fan power generation installed capacity constraint expression is as follows:
in the formula:
generating output power for a fan at the jth node in the distribution network;
respectively setting the lower limit and the upper limit of the installed capacity of the fan;
the constraint expression of the total installed capacity of the fan power generation is as follows:
in the formula:
respectively outputting power generated by a fan at the jth node in the distribution network and requiring the electrical load at the kth node; n is wp 、n load Respectively counting the total number of the grid nodes which incorporate wind power in the distribution network and the total number of the grid nodes with loads; epsilon wp 、
Wind power permeability factors and wind power permeability factor upper limit values acceptable to a distribution network are respectively set; j. k is different power grid nodes in the distribution network;
the conventional generator set safe operation constraint expression is as follows:
in the formula:
generating output power for a conventional generator set at the mth node in the distribution network;
respectively is the lower limit and the upper limit of the power output generated by the conventional generator set; x is the number of gen The value of the starting and stopping state variable of the conventional generator set is 0 during operation and 1 during shutdown;
the physical transmission constraint expression of the distribution network tie line is as follows:
in the formula:
electric energy power transmitted for the nth tie line in the distribution network, wherein in the virtual power plant
When in use
When the value is negative, the distribution network sells electricity to a large power grid,
when the value is positive, the distribution network purchases electricity to the large power grid;
respectively transmitting a lower limit and an upper limit of power for the distribution network tie line;
the constraint conditions of the safe operation at the power grid side are as follows:
the node voltage constraint expression is as follows:
in the formula: u shape p 、
Respectively representing the voltage amplitude at the distribution network node p, the lower limit of the voltage amplitude and the upper limit of the voltage amplitude;
the branch power flow constraint expression is as follows:
in the formula: s pq 、
Respectively indicating the apparent power of the distribution network branch pq, the lower limit of the apparent power and the upper limit of the apparent power;
the controllable load adjustment factor constraint expression is as follows:
in the formula:
respectively setting a controllable load adjustment factor, a lower limit of the controllable load adjustment factor and an upper limit of the controllable load adjustment factor at a distribution network node p;
the electric energy storage charging and discharging power constraint expression is as follows:
in the formula:
respectively providing electric energy storage discharge power and electric energy storage charging power at the p-th node in the distribution network;
the upper limit of the electrical energy storage discharge power and the upper limit of the electrical energy storage charging power at the p-th node in the distribution network are respectively set.
6. The fine-grained calculation method for the distribution network admission distributed power generation capacity in the virtual power plant according to claim 1, characterized by comprising the following steps: the specific expression of the pre-constructed optimal coordination scheduling model for the accepting capacity of the distributed power generation is as follows:
in the formula: ABI is an index of the distributed generation receiving capacity of a distribution network in a virtual power plant; alpha is alpha re The importance factor of distributed power generation of new energy is defined;
respectively providing photovoltaic power generation output at the ith node and fan power generation output at the jth node in the distribution network; n is a radical of an alkyl radical pv 、n wp The total number of grid nodes which are merged into photovoltaic and the total number of grid nodes which are merged into wind power in the distribution network are respectively; i. j is different grid nodes in the distribution network.
7. The fine-grained calculation method for distribution network admission distributed power generation capacity in the virtual power plant according to claim 6, characterized by comprising the following steps: new energy distributed power generation importance factor alpha re Determining a distributed generation admission capacity optimal coordination scheduling mode with a series of specific settings through artificial setting or directly distributing new energy sources through non-artificial setting to generate an importance factor alpha re And performing coordinated scheduling as an optimization variable.
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