CN114039350A - Energy storage point selection method and system for improving new energy station group absorption capacity - Google Patents
Energy storage point selection method and system for improving new energy station group absorption capacity Download PDFInfo
- Publication number
- CN114039350A CN114039350A CN202111396601.5A CN202111396601A CN114039350A CN 114039350 A CN114039350 A CN 114039350A CN 202111396601 A CN202111396601 A CN 202111396601A CN 114039350 A CN114039350 A CN 114039350A
- Authority
- CN
- China
- Prior art keywords
- power
- energy storage
- new energy
- node
- energy station
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 111
- 238000010187 selection method Methods 0.000 title claims abstract description 17
- 238000010521 absorption reaction Methods 0.000 title claims description 13
- 238000004088 simulation Methods 0.000 claims abstract description 12
- 238000007781 pre-processing Methods 0.000 claims abstract description 9
- 238000000034 method Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 11
- 230000005611 electricity Effects 0.000 claims description 7
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 238000005457 optimization Methods 0.000 claims description 5
- 238000005206 flow analysis Methods 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 2
- 230000005540 biological transmission Effects 0.000 claims description 2
- 230000002068 genetic effect Effects 0.000 claims description 2
- 239000002245 particle Substances 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 230000009466 transformation Effects 0.000 claims description 2
- 238000004804 winding Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
-
- 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
-
- 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]
-
- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Power Engineering (AREA)
- Strategic Management (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Public Health (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to an energy storage point selection method and system for improving the consumption capability of a new energy station group, which comprises the following steps: step 1, loading basic data of a new energy station group and basic data of a local power grid, preprocessing the data of the new energy station group, and calculating a discarded electric power time sequence of the new energy station; step 2, setting the scale of an energy storage module, setting a curtailment rate boundary for energy storage and promotion of new energy station group consumption, and optimizing the energy storage capacity requirement according to the boundary; step 3, constructing a local area power grid simulation system model, forming a local area power grid new energy station output and load demand time sequence in an operation mode, calculating power transfer distribution between each node power and each branch power flow, and calculating a node abandoned electric power time sequence to obtain a node abandoned electric power index value; and 4, determining the number of the nodes to be selected for energy storage and the number of the nodes to be selected, and outputting and storing the result of the energy storage selection.
Description
Technical Field
The invention belongs to the field of new energy, energy storage and electric power, and particularly relates to an energy storage point selection method and system for improving the absorption capacity of a new energy station group.
Background
The energy storage power station is connected to a local power grid, stores electricity during the peak time period of light abandonment and wind abandonment, and sends the electricity to the power grid during the off-peak time period of light abandonment and wind abandonment, so that the problems of light abandonment and wind abandonment of new energy field stations in peripheral areas can be solved. How to consider the electricity abandonment characteristics, the distribution characteristics and the network characteristics of the new energy station group, optimize the site selection of the stored energy in the local power grid, improve the efficiency of the energy abandonment, and have certain practical significance.
Disclosure of Invention
In order to solve the technical problems, the invention provides an energy storage point selection method and an energy storage point selection system for improving the new energy station group absorption capacity, and provides an energy storage point selection method and an energy storage point selection system for improving the new energy station group absorption capacity by considering the requirement of energy storage capacity. The method is based on basic data of a new energy station group and a local area power grid, the number of nodes to be selected for energy storage and the number of the nodes to be selected are determined by analyzing the requirement of energy storage capacity and combining the electricity abandoning characteristic of the new energy station and the distribution characteristic of the new energy station in the network, and the absorption capacity of the new energy station group is improved.
The technical scheme of the invention is as follows: an energy storage point selection method for improving consumption capability of a new energy station group comprises the following steps:
step 1, loading basic data of a new energy station group and basic data of a local power grid, preprocessing the data of the new energy station group, and calculating a discarded electric power time sequence of the new energy station;
step 2, setting the scale of an energy storage module, setting a curtailment rate boundary for energy storage and promotion of new energy station group consumption, and optimizing the energy storage capacity requirement according to the boundary;
step 3, constructing a local area power grid simulation system model, forming a local area power grid new energy station output and load demand time sequence in an operation mode, calculating power transfer distribution between each node power and each branch power flow, and calculating a node abandoned electric power time sequence to obtain a node abandoned electric power index value;
and 4, determining the number of the nodes to be selected for energy storage and the number of the nodes to be selected, and outputting and storing the result of the energy storage selection.
According to another aspect of the invention, an energy storage point selection system for improving the consumption capability of a new energy station group is provided, which comprises a loading processing unit, a setting unit, a calculating unit and an energy storage point selection output unit;
the loading processing unit is used for loading the basic data of the new energy station group, preprocessing the data of the new energy station group and processing the basic data of the local power grid.
The setting unit is used for setting a curtailment rate boundary for increasing the consumption of the new energy station group by the stored energy and optimizing the requirement of the stored energy capacity according to the boundary; and setting the scale of the energy storage module and determining the number of nodes to be selected for energy storage.
The calculation unit is used for calculating a power abandoning time sequence of the new energy station, constructing a local power grid simulation system model, forming a time sequence of output and load demand of the new energy station of the local power grid in an operation mode, calculating power transfer distribution between power of each node and power flow of each branch, calculating a power abandoning time sequence of each node, and obtaining an index value of the power abandoning of the node.
And the energy storage point selection output unit is used for obtaining the point selection sequence of the energy storage at the new energy station side and the power grid side, and outputting and storing the energy storage point selection result.
Has the advantages that:
the invention provides an energy storage point selection method and system for improving the absorption capacity of a new energy station group based on new energy station groups and local area power grid basic data, considering the electricity abandoning characteristics of new energy stations of different grid-connected nodes and combining the energy storage capacity requirement and the power transfer distribution between the power of each node and the power flow of each branch. Firstly, loading basic data of a new energy station group and basic data of a local power grid, preprocessing the data of the new energy station group, and calculating a discarded electric power time sequence of the new energy station; secondly, setting the scale of an energy storage module, setting a curtailment rate boundary for energy storage and promotion of new energy station group consumption, and optimizing the energy storage capacity requirement according to the boundary; then, constructing a local power grid simulation system model, running to form a local power grid new energy station output and load demand time sequence, calculating power transfer distribution between each node power and each branch power flow, and calculating each node abandoned electric power time sequence to obtain a node abandoned electric power index value; and finally, determining the number of nodes to be selected for energy storage, obtaining the point selection sequence of the energy storage at the new energy station side and the power grid side, and outputting and storing the energy storage point selection result.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
According to an embodiment of the present invention, an energy storage point selection method for improving the absorption capability of a new energy station group is provided, which includes the following steps:
step 1, loading basic data of a new energy station group and basic data of a local power grid, preprocessing the data of the new energy station group, and calculating a discarded electric power time sequence of the new energy station;
step 2, setting the scale of an energy storage module, setting a curtailment rate boundary for energy storage and promotion of new energy station group consumption, and optimizing the energy storage capacity requirement according to the boundary;
step 3, constructing a local area power grid simulation system model, forming a local area power grid new energy station output and load demand time sequence in an operation mode, calculating power transfer distribution between each node power and each branch power flow, and calculating a node abandoned electric power time sequence to obtain a node abandoned electric power index value;
and 4, determining the number of the nodes to be selected for energy storage and the number of the nodes to be selected, and outputting and storing the result of the energy storage selection.
The point selection in the invention comprises the steps of determining the number and the sequence of the energy storage site selection points, thereby obtaining the point selection sequence.
The new energy station group basic data comprises: the method comprises the steps of new energy station grid-connected nodes, new energy installation scale of each grid-connected node, new energy historical output time sequence and actual output and theoretical output corresponding to each time point.
The local area power grid basic data comprises: physical bus, generator, load, AC line, parallel capacitance reactance, two-winding transformer, three-winding transformer, PV node, node type, etc.
The new energy station group data preprocessing method comprises the following steps: and filling missing data and deleting repeated data for the historical output time sequence of each new energy station and the actual output and theoretical output corresponding to each time point.
The electric power abandonment time sequence calculation method of the new energy station comprises the following steps:
based on the actual output and the theoretical output of each new energy station at the same sampling time point, calculating the power error between the actual output and the theoretical output to obtain a discarded electric power time sequence of each new energy station:
for new energy station jwvThe theoretical output at the time t is,for new energy station jwvThe actual output at time T, where T is 1,2, …, T being the end time.
The scale of the energy storage module to be set comprises the power P of the energy storage modulemodCapacity Emod。
According to one embodiment of the invention, the wind field capacity of a typical new energy station is 50MW, for example, and the energy storage module size can be set to 5MW/10 MWh.
The energy storage capacity demand optimization method comprises the following steps: the optimization target is that the energy storage cost is minimum, the constraint condition considers that the power abandonment rate is smaller than a set power abandonment rate boundary and the theoretical output constraint of the new energy station, if the power abandonment rate boundary condition can be set to be 5 percent,
the optimization algorithm includes, but is not limited to, genetic algorithm, particle swarm algorithm and the like, and the decision variable is the power P of the stored energytotalAnd capacity Etotal。
The local area power grid simulation system model construction method comprises the following steps: based on the basic data of the local area power grid, the number of system nodes and the number of branches are determined, and reference capacity, maximum iteration times, iteration precision and balance nodes are set; then, numbering each item in the local area power grid basic data, establishing an incidence relation between nodes and branches, and reading branch impedance and admittance data, transformer impedance and transformation ratio data and transmission capacity of each line.
The method for forming the time sequence of the output and load demands of the new energy station of the local power grid comprises the following steps: and establishing a time sequence of the new energy and the load based on the output curve and the load demand curve of the new energy station. Output time sequence of new energy stationThe method comprises the following steps: new energy station node number jwvTime t and new energy station j at the timewvThe output of (2); load demand time sequenceThe method comprises the following steps: the load node number l, the time t and the power requirement corresponding to the load l at the moment.
The power transfer distribution calculation method between the power of each node and the power flow of each branch circuit comprises the following steps: based on the constructed local power grid simulation system model, based on the actual output of the new energy station group, the branch power flow is calculated by combining power flow analysisSetting power change deltaP of each nodej,tCalculating branch power flow by combining power flow analysisComputingAnd power transfer distribution between the power of each node and the power flow of each branch circuit:
the method for calculating the electric power abandoning time sequence of each node comprises the following steps: calculating the power flow distribution of the abandoned electric power of each branch according to the power transfer distribution between the power of each node and the power flow of each branch, and the abandoned electric power of the new energy stationThe calculation formula of the power flow distribution of the curtailed power flow of each branch circuit caused by the power flow is as follows:
secondly, calculating a discarded electric power time sequence of each node according to the discarded electric power flow distribution of each branch flow, wherein the calculation formula is as follows:
where K is the branch flowing into node j and K is the total number of branches.
The node electric power abandonment index calculation method of the energy storage point selection comprises the following steps: the node electric power abandoning index comprises electric power abandoning quantity and electric power abandoning quantity mean value, and the electric power abandoning quantity mean value weight alpha are respectively endowed1、α2In which α is1+α21 and α1∈[0,1],α2∈[0,1]And obtaining a comprehensive index value of the abandoned electric power of the energy storage point selection node through weighted summation, wherein the average values of the abandoned electric power and the abandoned electric power are calculated by time integral summation and integral summation averaging according to the sequence of the abandoned electric power time sequence of each node.
The method for determining the number of the nodes to be selected is energy storage power PtotalAnd the power P of the energy storage modulemodRatio of (D) and energy storage capacity EtotalAnd capacity E of energy storage modulemodMaximum value of the ratio of (a).
The method for establishing the point selection sequence of the stored energy at the new energy station side and the power grid side comprises the following steps: and sequencing the node abandoned electric power comprehensive index values of the energy storage selection points from high to low, and obtaining the point selection sequence of the energy storage at the new energy station side and the power grid side by considering the limitation of the number of the nodes to be selected.
Such as the stored energy power PtotalIs 80MW, the power P of the energy storage modulemod5MW, energy storage capacity Etotal200MWh, energy storage Module Capacity Emod10MWh, the number N of the nodes to be selected for energy storage is 20, and the sequence of the nodes is J1、J2……J20。
The step of outputting and storing the energy storage point selection result specifically comprises the following steps: setting the type of an energy storage selection point node, searching out a new energy station grid-connected node, marking the new energy station grid-connected node as a new energy station side, searching out an independent load node, marking the independent load node as a load side, searching out a conventional unit grid-connected node, marking the conventional unit grid-connected node as a power plant side, and marking the rest nodes as a power grid side; outputting energy storage point selection results, including an energy storage point selection sequence, node electric power abandon comprehensive indexes and node types; and storing the energy storage point selection result for improving the consumption capability of the new energy station group to a local file.
According to another embodiment of the invention, an energy storage point selection system for improving the consumption capability of a new energy station group is provided, which comprises a loading processing unit, a setting unit, a calculating unit and an energy storage point selection output unit;
the loading processing unit is used for loading the basic data of the new energy station group, preprocessing the data of the new energy station group and processing the basic data of the local power grid.
The setting unit is used for setting a curtailment rate boundary for increasing the consumption of the new energy station group by the stored energy and optimizing the requirement of the stored energy capacity according to the boundary; and setting the scale of the energy storage module and determining the number of nodes to be selected for energy storage.
The calculation unit is used for calculating a power abandoning time sequence of the new energy station, constructing a local power grid simulation system model, forming a time sequence of output and load demand of the new energy station of the local power grid, calculating power transfer distribution between power of each node and power flow of each branch, calculating the power abandoning time sequence of each node, and obtaining an index value of the power abandoning of the node.
And the energy storage point selection output unit is used for obtaining the point selection sequence of the energy storage at the new energy station side and the power grid side, and outputting and storing the energy storage point selection result.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but various changes may be apparent to those skilled in the art, and it is intended that all inventive concepts utilizing the inventive concepts set forth herein be protected without departing from the spirit and scope of the present invention as defined and limited by the appended claims.
Claims (9)
1. An energy storage point selection method for improving consumption capability of a new energy station group is characterized by comprising the following steps:
step 1, loading basic data of a new energy station group and basic data of a local power grid, preprocessing the data of the new energy station group, and calculating a discarded electric power time sequence of the new energy station;
step 2, setting the scale of an energy storage module, setting a curtailment rate boundary for energy storage and promotion of new energy station group consumption, and optimizing the energy storage capacity requirement according to the boundary;
step 3, constructing a local area power grid simulation system model, forming a local area power grid new energy station output and load demand time sequence in an operation mode, calculating power transfer distribution between each node power and each branch power flow, and calculating a node abandoned electric power time sequence to obtain a node abandoned electric power index value;
and 4, determining the number of the nodes to be selected for energy storage and the number of the nodes to be selected, and outputting and storing the result of the energy storage selection.
2. The energy storage point selection method for improving the new energy station group absorption capacity according to claim 1, wherein in the step 2, a power abandonment time sequence of the new energy station is calculated, and specifically:
based on the actual output and the theoretical output of each new energy station at the same sampling time point, calculating the power error between the actual output and the theoretical output to obtain a discarded electric power time sequence of each new energy station:
3. The energy storage point selection method for improving the consumption capability of the new energy station group according to claim 1, wherein in the step 2, the scale of the energy storage modules to be set comprises the power P of the energy storage modulesmodCapacity Emod。
4. The energy storage point selection method for improving the new energy station group absorption capacity according to claim 1, wherein in the step 2, the energy storage capacity requirement is optimized according to a boundary, the optimization target is that the energy storage cost is minimum, the constraint condition considers that the electricity abandonment rate is smaller than a set electricity abandonment rate boundary and the theoretical output constraint of the new energy station, the optimization algorithm comprises a genetic algorithm and a particle swarm algorithm, and the decision variable is the power P of the energy storagetotalAnd capacity Etotal。
5. The energy storage point selection method for improving the new energy station group absorption capacity according to claim 1, wherein in the step 3, a local area network simulation system model is constructed, and a local area network new energy station output and load demand time sequence is formed through operation, specifically: based on the basic data of the local area power grid, the number of system nodes and the number of branches are determined, and reference capacity, maximum iteration times, iteration precision and balance nodes are set; then numbering each item in the local area power grid basic data, establishing an incidence relation between nodes and branches, and reading branch impedance and admittance data, transformer impedance and transformation ratio data and transmission capacity of each line;
establishing a new energy and load time sequence based on the new energy station output curve and the load demand curve, and establishing a new energy station output time sequenceThe method comprises the following steps: new energy station node number jwvTime t and new energy station j at the timewvThe output of (2); load demand time sequenceThe method comprises the following steps: the load node number l, the time t and the power requirement corresponding to the load node l at the moment.
6. The energy storage point selection method for improving the new energy station group absorption capacity according to claim 1, wherein in the step 3, the power transfer distribution between the power of each node and the power flow of each branch is calculated, and a power abandonment time sequence of each node is calculated, specifically:
based on the constructed local power grid simulation system model, based on the actual output of the new energy station group, the branch power flow is calculated by combining power flow analysisSetting power change deltaP of each nodej,tCalculating branch power flow by combining power flow analysisCalculating the power transfer distribution between the power of each node and the power flow of each branch circuit:
calculating the power flow distribution of the abandoned electric power of each branch according to the power transfer distribution between the power of each node and the power flow of each branch, and the abandoned electric power of the new energy stationThe calculation formula of the power flow distribution of the curtailed power flow of each branch circuit caused by the power flow is as follows:
secondly, calculating a power abandoning time sequence of the nodes of the non-new energy station according to the power abandoning power flow distribution of each branch, wherein the calculation formula is as follows:
where K is the branch flowing into node j and K is the total number of branches.
7. The energy storage point selection method for improving the consumption capability of the new energy station group according to claim 1, wherein the node electric power abandonment index calculation method of the energy storage point selection comprises the following steps: the node electric power abandoning index comprises electric power abandoning quantity and electric power abandoning quantity mean value, and the electric power abandoning quantity mean value weight alpha are respectively endowed1、α2In which α is1+α21 and α1∈[0,1],α2∈[0,1]And obtaining a comprehensive index value of the abandoned electric power of the energy storage point selection node through weighted summation, wherein the average values of the abandoned electric power and the abandoned electric power are calculated by time integral summation and integral summation averaging according to the sequence of the abandoned electric power time sequence of each node.
8. The energy storage point selection method for improving the new energy station group absorption capacity according to claim 1, wherein in the step 4, the determining of the number N of nodes to be selected for energy storage is specifically:
stored energy power PtotalAnd the power P of the energy storage modulemodRatio of (A) to (B), energy storage capacity EtotalAnd capacity E of energy storage modulemodThe maximum value of the two ratios, namely the number N of the nodes to be selected for energy storage:
the specific number of the energy storage node to be selected is determined as follows: and sequencing the node abandoned electric power comprehensive index values of the energy storage selection points from high to low, and taking the number and the limitation of the nodes to be selected for energy storage into consideration to obtain the point selection sequence of the energy storage at the new energy station side and the power grid side.
9. An energy storage point selection system for improving consumption capability of a new energy station group is characterized by comprising:
the loading processing unit is used for loading the basic data of the new energy station group, preprocessing the data of the new energy station group and storing the basic data of the local power grid;
the setting unit is used for setting a curtailment rate boundary for increasing the consumption of the new energy station group by the stored energy and optimizing the requirement of the stored energy capacity according to the boundary; setting the scale of an energy storage module, and determining the number of nodes to be selected for energy storage;
the calculation unit is used for calculating a power abandoning time sequence of the new energy station, constructing a local power grid simulation system model, forming a power output and load demand time sequence of the new energy station of the local power grid in an operation mode, calculating power transfer distribution between power of each node and power flow of each branch, calculating a power abandoning time sequence of each node, and obtaining an index value of the power abandoning of the node;
and the energy storage point selection output unit is used for obtaining the point selection sequence of the energy storage at the new energy station side and the power grid side, and outputting and storing the energy storage point selection result.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111396601.5A CN114039350A (en) | 2021-11-23 | 2021-11-23 | Energy storage point selection method and system for improving new energy station group absorption capacity |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111396601.5A CN114039350A (en) | 2021-11-23 | 2021-11-23 | Energy storage point selection method and system for improving new energy station group absorption capacity |
Publications (1)
Publication Number | Publication Date |
---|---|
CN114039350A true CN114039350A (en) | 2022-02-11 |
Family
ID=80138586
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111396601.5A Pending CN114039350A (en) | 2021-11-23 | 2021-11-23 | Energy storage point selection method and system for improving new energy station group absorption capacity |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114039350A (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111626645A (en) * | 2020-07-01 | 2020-09-04 | 国网新疆电力有限公司 | Method and system for measuring and calculating future-year energy storage configuration capacity |
CN111769602A (en) * | 2020-07-12 | 2020-10-13 | 国网山西省电力公司电力科学研究院 | Optimized scheduling method for multi-time-scale wind storage combined system |
CN112072703A (en) * | 2020-09-10 | 2020-12-11 | 华北电力大学 | Flexibility evaluation method and system suitable for new energy access planning |
CN112487752A (en) * | 2020-11-26 | 2021-03-12 | 国网江苏省电力有限公司经济技术研究院 | Energy storage power station site selection method based on optimal power flow |
-
2021
- 2021-11-23 CN CN202111396601.5A patent/CN114039350A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111626645A (en) * | 2020-07-01 | 2020-09-04 | 国网新疆电力有限公司 | Method and system for measuring and calculating future-year energy storage configuration capacity |
CN111769602A (en) * | 2020-07-12 | 2020-10-13 | 国网山西省电力公司电力科学研究院 | Optimized scheduling method for multi-time-scale wind storage combined system |
CN112072703A (en) * | 2020-09-10 | 2020-12-11 | 华北电力大学 | Flexibility evaluation method and system suitable for new energy access planning |
CN112487752A (en) * | 2020-11-26 | 2021-03-12 | 国网江苏省电力有限公司经济技术研究院 | Energy storage power station site selection method based on optimal power flow |
Non-Patent Citations (1)
Title |
---|
郭威;修晓青;李文启;李建林;: "计及多属性综合指标与经济性的电网侧储能***选址配置方法", 电力建设, no. 04, 1 April 2020 (2020-04-01), pages 57 - 66 * |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yan et al. | Stochastic multi-scenario optimization for a hybrid combined cooling, heating and power system considering multi-criteria | |
CN110119886B (en) | Active distribution network dynamic planning method | |
CN111639870B (en) | Multi-target flexible planning method and system for power transmission network considering source load uncertainty | |
CN104578157B (en) | Load flow calculation method of distributed power supply connection power grid | |
CN104600713A (en) | Device and method for generating day-ahead reactive power dispatch of power distribution network containing wind/photovoltaic power generation | |
WO2021253291A1 (en) | Wind farm layout optimization method and optimization system, and computer-readable storage medium | |
CN107681655B (en) | Tidal current energy power generation field coordination planning method | |
Shanmugapriya et al. | IoT based approach in a power system network for optimizing distributed generation parameters | |
CN109193643B (en) | Method and system for calculating power distribution and distribution system network loss and reliability | |
CN111082446B (en) | Energy storage optimal configuration method considering battery self-consumption | |
CN111835003A (en) | Method and system for calculating theoretical line loss of medium-voltage distribution network in real time under multi-power-supply power supply | |
CN114243766B (en) | Regional multi-energy system optimal configuration method and system | |
CN116488206A (en) | Energy storage optimization configuration method for active power distribution network based on multi-target particle swarm algorithm | |
Han et al. | Analysis of economic operation model for virtual power plants considering the uncertainties of renewable energy power generation | |
CN114039350A (en) | Energy storage point selection method and system for improving new energy station group absorption capacity | |
CN113361805B (en) | Power distribution network planning method and system | |
CN115549138A (en) | Energy storage capacity optimal configuration method and system in multiple complementary delivery systems | |
CN115313508A (en) | Microgrid energy storage optimal configuration method, device and storage medium | |
CN111262239B (en) | Energy storage power station site selection scheme evaluation method, device and system | |
CN113536581A (en) | Energy storage system multi-state reliability modeling method considering operation strategy | |
Alguhi et al. | Battery energy storage planning in distribution network with renewable resources | |
Huo et al. | Reliability of distribution systems considering photovoltaic-wind power generation systems' complementary characteristics | |
Su et al. | Cluster division and optimal scheduling of offshore wind power with energy storage based on fast unfolding algorithm | |
Chen et al. | Research on Optimal Configuration of Battery Energy Storage System for Photovoltaic Systems with Different Load Demand | |
Li et al. | The Fuzzy Power Flow Based Network Planning of Distribution Networks with Distributed Generation |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |