CN109818361A - Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network - Google Patents
Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network Download PDFInfo
- Publication number
- CN109818361A CN109818361A CN201910206437.3A CN201910206437A CN109818361A CN 109818361 A CN109818361 A CN 109818361A CN 201910206437 A CN201910206437 A CN 201910206437A CN 109818361 A CN109818361 A CN 109818361A
- Authority
- CN
- China
- Prior art keywords
- energy storage
- power loss
- network
- loss sensitivity
- sensitivity
- 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
Landscapes
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention belongs to power transmission network energy storage siteselecting planning technical field, the energy storage site selecting method based on power loss sensitivity in a kind of power transmission network is proposed, comprising the following steps: input network parameter, energy storage installation number, load operation data etc.；Node admittance matrix is formed, and then forms Jacobian matrix, Load flow calculation is carried out to network；Network loss is found out to the local derviation and network loss of phase angle to the local derviation of voltage magnitude by Jacobian matrix, calculates the power loss sensitivity of each node injecting power；Day part energy storage substantially charging and discharging state is judged by load curve；Then power loss sensitivity is constant for energy storage charging, and the then power loss sensitivity that discharges takes negative；Power loss sensitivity is summed according to timing and sorts to obtain best energy storage position.The present invention has rational design, that is, finding makes the node of the whole network loss minimization configure energy storage, and reduces solution room when configuration energy storage, improves computational efficiency.
Description
Technical field
The invention belongs to power transmission network energy storage siteselecting planning technical fields.
Background technique
When energy storage technology is applied in power transmission network, the direction of the trend of power transmission network and size can change, therewith can be right
The network loss of power transmission network has an impact.Domestic and foreign scholars have carried out many researchs to the addressing configuration method of energy storage.For example, by addressing
Configuration is used as upper layer target, and operation is used as lower layer's target, and the optimum programming that energy storage is obtained by solving the double-deck target configures.Example
Such as, addressing is carried out to energy storage using voltage sensibility, energy storage is configured using economic index.
In conclusion less to the research of power loss sensitivity in power transmission network at present, existing research distributes that time-consuming rationally
It is not applicable to large scale system.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, and addressing and configuration are separated, reduces variable number, mentions
High calculating speed, and be exactly found and influence optimal cloth office point on network loss.
The present invention solves its technical problem and adopts the following technical solutions to achieve:
1. the energy storage site selecting method in a kind of power transmission network based on power loss sensitivity, it is characterised in that the following steps are included:
Step 1, input network parameter, energy storage installation number, load operation data etc.；
Step 2 forms node admittance matrix, and then forms Jacobian matrix, carries out Load flow calculation to network；
Step 3 finds out network loss by Jacobian matrix to the local derviation and network loss of phase angle to the local derviation of voltage magnitude, calculates each node
The power loss sensitivity of injecting power；
Step 4 judges day part energy storage substantially charging and discharging state by load curve；
Then power loss sensitivity is constant for step 5, energy storage charging, and the then power loss sensitivity that discharges takes negative；
Power loss sensitivity is summed according to timing and sorts to obtain best energy storage position by step 6.
2. the site selecting method of energy storage in the power transmission network according to claim, it is characterised in that the network loss in the step
The calculation method of sensitivity is as follows:
Step 2.1, basisCalculate Losses；
Wherein Ui, UjFor node voltage amplitude, Gi, BijFor the conductance susceptance on route ij, δij=δi-δjFor node voltage phase angle
Difference.
Step 2.2, basisTo calculate power loss sensitivity；
Wherein J is Jacobian matrix,H, N are the element in Jacobian matrix.
Step 2.3 judges energy storage substantially charging and discharging state according to load, and charging power loss sensitivity is constant, electric discharge network loss spirit
Sensitivity takes negative, and each node is chronologically summed and sorted to power loss sensitivity, obtains energy storage the best site selection position.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the energy storage site selecting method based on power loss sensitivity in power transmission network
Specific embodiment
The embodiment of the present invention is further described below in conjunction with attached drawing.
It is an object of the invention to overcome the deficiencies in the prior art, and addressing and configuration are separated, reduces variable number, mentions
High calculating speed, and be exactly found and influence optimal cloth office point on network loss.
The present invention solves its technical problem and adopts the following technical solutions to achieve:
1. the energy storage site selecting method in a kind of power transmission network based on power loss sensitivity, it is characterised in that the following steps are included:
Step 1, input network parameter, energy storage installation number, load operation data etc.；
Step 2 forms node admittance matrix, and then forms Jacobian matrix, carries out Load flow calculation to network；
Step 3 finds out network loss by Jacobian matrix to the local derviation and network loss of phase angle to the local derviation of voltage magnitude, calculates each node
The power loss sensitivity of injecting power；
Step 4 judges day part energy storage substantially charging and discharging state by load curve；
Then power loss sensitivity is constant for step 5, energy storage charging, and the then power loss sensitivity that discharges takes negative；
Power loss sensitivity is summed according to timing and sorts to obtain best energy storage position by step 6.
2. the site selecting method of energy storage in the power transmission network according to claim, it is characterised in that the network loss in the step
The calculation method of sensitivity is as follows:
Step 2.1, basisCalculate Losses；
Wherein Ui, UjFor node voltage amplitude, Gi, BijFor the conductance susceptance on route ij, δij=δi-δjFor node voltage phase angle
Difference.
Step 2.2, basisTo calculate power loss sensitivity；
Wherein J is Jacobian matrix,H, N are the element in Jacobian matrix.
Step 2.3 judges energy storage substantially charging and discharging state according to load, and charging power loss sensitivity is constant, electric discharge network loss spirit
Sensitivity takes negative, and each node is chronologically summed and sorted to power loss sensitivity, obtains energy storage the best site selection position.
Claims (2)
1. the energy storage site selecting method in a kind of power transmission network based on power loss sensitivity, it is characterised in that the following steps are included:
Step 1, input network parameter, energy storage installation number, load operation data etc.；
Step 2 forms node admittance matrix, and then forms Jacobian matrix, carries out Load flow calculation to network；
Step 3 finds out network loss by Jacobian matrix to the local derviation and network loss of phase angle to the local derviation of voltage magnitude, calculates each node
The power loss sensitivity of injecting power；
Step 4 judges day part energy storage substantially charging and discharging state by load curve；
Then power loss sensitivity is constant for step 5, energy storage charging, and the then power loss sensitivity that discharges takes negative；
Power loss sensitivity is summed according to timing and sorts to obtain best energy storage position by step 6.
2. the site selecting method of energy storage in the power transmission network according to claim, it is characterised in that the network loss in the step is sensitive
The calculation method of degree is as follows:
Step 2.1, basisCalculate Losses；
Wherein,For node voltage amplitude,,For the conductance susceptance on route ij,For node voltage phase
Angular difference；
Step 2.2, basisTo calculate power loss sensitivity；
Wherein J is Jacobian matrix,,H, N are the element in Jacobian matrix；
Step 2.3 judges energy storage substantially charging and discharging state according to load, and charging power loss sensitivity is constant, and discharge power loss sensitivity
It takes negative, each node is chronologically summed and sorted to power loss sensitivity, energy storage the best site selection position is obtained.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910206437.3A CN109818361A (en) | 2019-03-19 | 2019-03-19 | Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910206437.3A CN109818361A (en) | 2019-03-19 | 2019-03-19 | Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109818361A true CN109818361A (en) | 2019-05-28 |
Family
ID=66609397
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910206437.3A Pending CN109818361A (en) | 2019-03-19 | 2019-03-19 | Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109818361A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110739695A (en) * | 2019-09-17 | 2020-01-31 | 杭州电子科技大学 | HELM-based power distribution network loss sensitivity calculation method |
| CN110852495A (en) * | 2019-10-28 | 2020-02-28 | 国网新疆电力有限公司电力科学研究院 | Site selection method for distributed energy storage power station |
| CN111030146A (en) * | 2019-11-25 | 2020-04-17 | 国网新疆电力有限公司电力科学研究院 | Energy storage device address selection method considering network loss and wide area node voltage deviation |
| CN111355251A (en) * | 2020-04-14 | 2020-06-30 | 北方工业大学 | Energy storage site selection method and system based on power distribution network |
| CN111682546A (en) * | 2020-06-01 | 2020-09-18 | 国网河北省电力有限公司石家庄供电分公司 | DC power flow improvement algorithm based on sensitivity analysis |
-
2019
- 2019-03-19 CN CN201910206437.3A patent/CN109818361A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110739695A (en) * | 2019-09-17 | 2020-01-31 | 杭州电子科技大学 | HELM-based power distribution network loss sensitivity calculation method |
| CN110739695B (en) * | 2019-09-17 | 2021-08-10 | 杭州电子科技大学 | HELM-based power distribution network loss sensitivity calculation method |
| CN110852495A (en) * | 2019-10-28 | 2020-02-28 | 国网新疆电力有限公司电力科学研究院 | Site selection method for distributed energy storage power station |
| CN111030146A (en) * | 2019-11-25 | 2020-04-17 | 国网新疆电力有限公司电力科学研究院 | Energy storage device address selection method considering network loss and wide area node voltage deviation |
| CN111355251A (en) * | 2020-04-14 | 2020-06-30 | 北方工业大学 | Energy storage site selection method and system based on power distribution network |
| CN111682546A (en) * | 2020-06-01 | 2020-09-18 | 国网河北省电力有限公司石家庄供电分公司 | DC power flow improvement algorithm based on sensitivity analysis |
| CN111682546B (en) * | 2020-06-01 | 2021-11-12 | 国网河北省电力有限公司石家庄供电分公司 | DC power flow improvement algorithm based on sensitivity analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109818361A (en) | Energy storage site selecting method based on power loss sensitivity in a kind of power transmission network | |
| CN104037776B (en) | The electric network reactive-load capacity collocation method of random inertial factor particle swarm optimization algorithm | |
| CN103872678B (en) | A kind of load model identification method measured based on transformer station | |
| CN105631528B (en) | Multi-target dynamic optimal power flow solving method based on NSGA-II and approximate dynamic programming | |
| CN106446467B (en) | The Optimal Configuration Method of fault current limiter based on APSO algorithm | |
| Zeng et al. | A dynamic multi-objective evolutionary algorithm based on an orthogonal design | |
| CN108695902A (en) | A kind of Cascade Reservoirs ecology-mutual feedback regulation and control method of power generation dynamic | |
| CN105186525A (en) | Reactive voltage control partitioning method under wind power integration | |
| CN110135662B (en) | Energy storage site selection constant volume multi-objective optimization method considering reduction of peak-valley difference | |
| CN108964102A (en) | The position of distributed energy storage and capacity configuration optimizing method in power distribution network | |
| CN108183488B (en) | High-permeability distributed energy system intelligent pressure regulating method based on cluster division | |
| CN105138849A (en) | Reactive voltage control partitioning method based on AP clustering | |
| CN109783902B (en) | Battery dynamic grouping method for balance control | |
| CN105447082A (en) | Distributed clustering method for mass load curves | |
| CN105243432A (en) | NSGA-III-based UPFC (unified power flow controller) location and capacity multi-target configuration method | |
| CN108717608A (en) | Million kilowatt beach photovoltaic plant accesses electric network synthetic decision-making technique and system | |
| CN106443276A (en) | Radio interference computing method and radio interference computing system for alternating-current high-voltage multi-loop electric transmission line | |
| CN106712019B (en) | A kind of active filter Optimal Configuration Method | |
| CN109816555A (en) | A kind of load modeling method based on support vector machines | |
| CN104408531B (en) | A kind of uniform dynamic programming method of multidimensional multistage complicated decision-making problems | |
| CN109066709B (en) | Meta-model-based distributed power supply in-situ voltage control strategy improvement method | |
| CN105470948B (en) | Flow controller power injection model and site selecting method under DC flow model | |
| CN103617325A (en) | Method for building model of influences of electricity environment on load characteristics | |
| CN110210072A (en) | The method for solving high-dimensional optimization based on approximate model and differential evolution algorithm | |
| CN105576653A (en) | 220kV district power grid power supply capacity optimization method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190528 |
|
| WD01 | Invention patent application deemed withdrawn after publication |