CN108416459B - Site selection method for battery energy storage power station - Google Patents
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Abstract
A method for site selection of a battery energy storage power station. The method comprises the steps of respectively accessing battery energy storage power stations to different power grid nodes containing wind power systems, analyzing and evaluating system wind power consumption capacities under different site selection schemes through a wind power plant outlet PV curve, evaluating system voltage stability capacity through whole network voltage distribution fluctuation before and after the battery energy storage power stations are accessed, and finally comprehensively processing evaluation results by using a weighting optimization method to obtain the site selection scheme with the optimal effect.
Description
Technical Field
The invention relates to a location method of a battery energy storage power station.
Background
In the face of rapid increase of economy and population, the social demand for traditional energy sources is increasing day by day, and the problem of environmental deterioration caused by mass combustion of fuels such as coal, petroleum and the like is also increasing day by day. The emergence of new energy undoubtedly brings about a diligent solution to the above-mentioned problems, and wind energy, one of the important forms of renewable energy and clean energy, has great strategic significance to global sustainable development. However, as more and more wind power plants with large capacity are built and put into a power grid, the technical problems of instability, volatility and the like of wind power output cannot be thoroughly overcome in a short period, and the access of the wind power plants brings many uncertain factors to the safe and stable operation of the system, and even causes the instability and breakdown of the system in severe cases. In addition, due to the influence of uncertainty of wind speed, the fluctuation of wind power output is very obvious, and the phenomenon of wind abandon is more prominent due to insufficient wind power consumption caused by mismatching of wind power and load requirements. In order to break through the bottleneck of wind energy development, the energy storage technology is produced. The primary problem of the battery energy storage technology, which is one of the mainstream energy storage types at present, is site selection and planning of a battery energy storage power station. The battery energy storage power station fully utilizes the energy time shifting characteristic, stores redundant electric energy in a power grid through large-scale battery packs, transformers, converters and the like of different types, is flexible in operation mode, strong in power grid regulation capacity and capable of operating in a four-quadrant mode. And improper site selection of the battery energy storage power station can affect power flow distribution of a power grid to different degrees, so that the transmission capacity of lines near the wind power plant is reduced, the wind power absorption capacity is weakened, and the wind abandon phenomenon is aggravated. Meanwhile, national economy is also damaged correspondingly, and the safe and stable operation of the power grid is more likely to be influenced in serious cases.
At present, relatively few researches are conducted on the site selection problem of a battery energy storage power station, existing researches are mainly conducted from a power distribution network side, certain researches are conducted on site selection of distributed energy storage, and a lumped type energy storage type is not involved. The distributed energy storage generally has a lower access voltage level and a smaller capacity, and the application of the distributed energy storage is limited to a certain extent. The research on the lumped type energy storage site selection problem on the transmission network side is less, the evaluation on the site selection effect is mostly based on the safety stability or the economical efficiency of the power network, such as network loss, site selection cost and the like, and the research on the site selection problem of the battery energy storage power station from the perspective of improving the wind power consumption capability of the system is not available.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a location selection method for a battery energy storage power station. The site selection method evaluates the site selection effect of all possible site selection schemes of the battery energy storage power station under the same standard to obtain a site selection scheme with the best evaluation effect as a final access scheme of the battery energy storage power station.
The battery energy storage power station is mainly formed by combining a battery energy storage element and a current converter with a control system and is connected to a power grid through a step-up transformer. The method can be used for site selection planning of the battery energy storage power station. The method provided by the invention has the advantages that the wind power consumption capability of the system is improved on the premise that the system is safe and stable after the battery energy storage power station is connected to operate, and the method is very significant in terms of economy or new energy development.
The technical scheme adopted by the invention is as follows:
the battery energy storage power station site selection method for improving the wind power absorption capacity comprises the steps of firstly, building a simulation model of a power grid system, determining a site selection sequence of the battery energy storage power station according to actual requirements, and simulating the built power grid system model to obtain a power voltage PV curve of an original power grid system wind power plant outlet; then, according to actual requirements, an addressing sequence of the battery energy storage power station is established, and the battery energy storage power station is sequentially accessed to all addressing points in the addressing sequence; scanning power voltage PV curves of outlets of wind power plants under different site selection schemes to obtain wind power grid-connected limit capacity corresponding to PV curve inflection points under n site selection schemes; then, counting inflection points of a power voltage PV curve at an outlet of a wind power plant, calculating to obtain the percentage of the difference of wind power integration limit capacity before and after the battery energy storage power station is accessed relative to the increase of the wind power integration limit capacity before the battery energy storage power station is accessed, taking the percentage as a site selection basis 1, evaluating the wind power consumption capacity of the system, carrying out voltage scanning on all bus nodes of the whole network under different site selection schemes before the battery energy storage power station is accessed and under the condition that the capacity of the battery energy storage power station is not changed, and taking the voltage distribution deviation index of the whole network after the battery energy storage power station is accessed into a power grid system and runs; then, weight is distributed according to the ratio of the evaluation effect and the optimal effect of the corresponding site selection basis after the battery energy storage power station is accessed, and the evaluation value under each site selection scheme is calculated according to the final site selection evaluation function; and finally, sequencing the evaluation values of all the site selection schemes, and selecting the site selection scheme with the highest evaluation value as the site selection scheme of the battery energy storage power station.
The method comprises the following specific steps:
firstly, a simulation model of the power grid system is built. After the model is built, a power grid system is simulated by using a load flow calculation module, and a power voltage PV curve of an original system wind power plant outlet is obtained.
Then, an address selection sequence of the battery energy storage power station is established according to actual requirements, and an n-dimensional vector A is used for representing the address selection sequence:
A＝(a1,a2,…,ai,…,an)
wherein i is the serial number of the bus, i is more than or equal to 1 and less than or equal to n, n is the number of the access buses selected by the battery energy storage power station, aiRepresenting the state of the battery storage station of the ith bus, aiAnd 1 represents that the battery energy storage power station state of the ith bus is an access state. Except elements at the corresponding positions of the buses accessed into the battery energy storage power station in the addressing sequence are nonzero, the rest elements are zero.
And then sequentially accessing the battery energy storage power station into the n address selection points in the address selection sequence, wherein the operation modes of the battery energy storage power station are respectively set to be an active power absorption mode and a reactive power generation mode. And completing PV curve scanning of the outlets of the wind power plant under different site selection schemes by using a software power flow simulation function, and further obtaining wind power grid-connected limit capacity corresponding to PV curve inflection points under n site selection schemes.
And then, counting the inflection points of the PV curve, calculating to obtain the percentage of the difference of the wind power grid-connected limit capacity before and after the battery energy storage power station is accessed relative to the increase of the wind power grid-connected limit capacity before the battery energy storage power station is accessed, and evaluating the wind power consumption capacity of the power grid system by taking the difference as a site selection basis 1.
Evaluating function f according to the addressing criterion 11(xi) Calculating to obtain an evaluation value x of an address selection basis 1 corresponding to the ith bus accessed in the battery energy storage power station under the address selection schemeiAnd the ith bus is accessed to the representative battery energy storage power station. Where the function f1(xi) Is represented as follows:
in the above formula pmaxThe limit of the original wind power integration capacity of a power grid system before the battery energy storage power station is accessed,
and the wind power grid-connected capacity limit of the power grid system is set under the site selection scheme of accessing the ith bus corresponding to the battery energy storage power station.
Furthermore, under the condition that the capacity of the battery energy storage power station is kept unchanged, load flow simulation is carried out on power grid systems before and after the battery energy storage power station is accessed, and voltage scanning is carried out on all bus nodes of the whole network before the battery energy storage power station is accessed and under different addressing schemes.
For each access scheme, function f is evaluated according to 2 according to the site selection2(xi) Calculating the voltage distribution deviation index of the whole network after access, and using the voltage distribution deviation index as the evaluation value of the address selection basis 2, xiAnd the ith bus is accessed to the representative battery energy storage power station. Where the addressing is based on an evaluation function f of 22(xi) Is represented as follows:
in the above formula, i is the serial number of the bus, i is more than or equal to 1 and less than or equal to n, n is the number of the access buses selected by the battery energy storage power station, and the initial voltage per unit value of the p-th bus of the power grid before the battery energy storage power station is accessed to the system is VpAnd p belongs to D, and D is the set of all bus bars of the system. And the p-th bus voltage per unit value of the power grid after the battery energy storage power station is connected into the system in an operation mode of increasing the wind power consumption capacity of the system is Vp', p belongs to D, and m is the number of system buses.
After the construction of the address selection basis evaluation function is completed, different weights omega are respectively assigned to the basis 1 and the basis 21And ω2，ω1+ω21, where ω1And ω2Respectively representing the importance levels of the addressing basis 1 and the addressing basis 2 when comprehensively considering the final addressing effect. The larger the weight is, the corresponding selection is performed when the final addressing effect is evaluatedThe more important the address basis.
Further, when the site selection effect under a certain site selection scheme is comprehensively evaluated, special processing is carried out on the site selection obtained before according to the evaluation values of 1 and 2, namely, the weights are distributed proportionally according to the ratio of the evaluation effect and the optimal effect of the corresponding basis after the battery energy storage power station is accessed into the bus. The final addressing evaluation function under the addressing scheme corresponding to the battery energy storage power station accessing the ith bus is expressed as follows:
in the above formula, n is the number of the access buses selected by the battery energy storage power station.
According to the final site selection evaluation function F (x)i) And calculating to obtain an evaluation result under each address selection scheme. And searching and sequencing the evaluation values of all the site selection schemes, and selecting the site selection scheme with the highest evaluation value as the site selection scheme of the battery energy storage power station.
Drawings
FIG. 1 is a flowchart of a battery energy storage power station site selection method for improving wind power absorption capacity according to an embodiment of the invention.
Detailed Description
The invention is further described with reference to the accompanying drawings and the detailed description.
The embodiment of the invention adopts an EPRI-36 node system which comprises 36 nodes and has the highest voltage level of 500 kV. And building simulation models of the system, the wind power plant and the battery energy storage power station on a simulation platform. The construction of the wind power plant model adopts a single machine equivalence method, and a double-fed direct-drive wind driven generator is adopted as a fan; the battery energy storage power station model is established mainly by considering the charge and discharge characteristics of the battery energy storage power station model.
As shown in fig. 1, the method for locating a battery energy storage power station for improving wind power absorption capacity of the invention comprises the following steps:
1. and simulating the built system by using a power system analysis integrated program (PSASP for short) to obtain a PV curve of the wind power plant outlet of the original system.
2. And establishing an address selection sequence of the battery energy storage power station. The access voltage level of the battery energy storage power station is 220kV, the EPRI-36 node system comprises 15 220kV buses, and therefore the address selection sequence of the battery energy storage power station is represented by a 15-dimensional vector A:
A＝(a1,a2,…,ai,…,a15)
wherein i is the serial number of the bus, i is more than or equal to 1 and less than or equal to 15, aiThe battery energy storage power station state of the ith bus is represented as an access state, and other elements in the vector are all zero.
3. And sequentially accessing the battery energy storage power station to 15 site selection points in the site selection sequence, wherein the operation modes are respectively set to be an active power output operation mode and a reactive power output operation mode. And PV curve scanning of the wind power plant outlet of each access scheme under different operation modes is completed through simulation.
4. And counting the wind power grid-connected limit capacity corresponding to the inflection point of the PV curve, calculating to obtain the percentage of the difference of the wind power grid-connected limit capacity before and after the battery energy storage power station is accessed relative to the wind power grid-connected limit capacity before the battery energy storage power station is accessed, and taking the percentage as the site selection basis 1. And calculating to obtain an evaluation value of an address selection basis 1 corresponding to each address selection scheme by using the address selection basis 1 evaluation function.
5. And (5) simulating to obtain the whole network voltage distribution of the original system.
6. And selecting an operation mode with better evaluation effect according to the evaluation result of the site selection basis 1, respectively accessing the battery energy storage power station into 15 220kV buses of the system under the condition of certain capacity of the battery energy storage power station, operating the wind power station in a rated mode, and performing voltage scanning on all the buses of the system through power flow simulation to obtain the voltage distribution of the whole network.
7. And counting the voltage distribution data of the whole network, and calculating to obtain an evaluation value of an address selection basis 2 corresponding to each address selection scheme by utilizing an address selection basis 2 evaluation function.
8. Assigning weights, specifically ω, to the addressing bases 1 and 21＝0.65，ω2＝0.35。
9. And (3) carrying out dimension unification processing on the evaluation values of the addressing basis 1 and the addressing basis 2 by depending on the evaluation values of the addressing basis 1 and the addressing basis 2 and the weights thereof, and calculating by using a final addressing evaluation function to obtain an addressing comprehensive evaluation value under 15 addressing schemes.
10. Searching and sequencing the comprehensive evaluation values of the selected sites under all the schemes to obtain a scheme with the highest comprehensive evaluation value, and using the scheme as the optimal site selection scheme of the battery energy storage power station in the system used by the embodiment of the invention.
Claims (5)
1. A location method of a battery energy storage power station is characterized by comprising the following steps: the site selection method comprises the steps of firstly, building a simulation model of a power grid system, establishing a site selection sequence of a battery energy storage power station according to actual requirements, and simulating the built power grid system model to obtain a power voltage PV curve of an original system wind power plant outlet; then, according to actual requirements, an addressing sequence of the battery energy storage power station is established, and the battery energy storage power station is sequentially accessed to all addressing points in the addressing sequence; scanning power voltage PV curves of outlets of wind power plants under different site selection schemes to obtain wind power grid-connected limit capacity corresponding to PV curve inflection points under various site selection schemes; then, counting the inflection points of a power voltage PV curve at the outlet of the wind power plant, calculating to obtain the percentage of the difference of the wind power integration limit capacity before and after the battery energy storage power station is accessed relative to the increase before the battery energy storage power station is accessed, and taking the percentage as the addressing basis 1 to evaluate the wind power consumption capacity of the power grid system; then, under the condition that the capacity of the battery energy storage power station is kept unchanged, voltage scanning is carried out on all bus nodes of the whole network before the battery energy storage power station is connected and under different site selection schemes, and the whole network voltage distribution deviation index is used as a site selection basis 2 after the battery energy storage power station is connected into a power grid system to operate; then, weight is distributed according to the ratio of the evaluation effect and the optimal effect of the corresponding site selection basis after the battery energy storage power station is accessed, and the evaluation value under each site selection scheme is calculated according to the final site selection evaluation function; and finally, searching and sequencing the evaluation values of all the site selection schemes, and selecting the site selection scheme with the highest evaluation value as the site selection scheme of the battery energy storage power station.
2. The method of addressing a battery energy storage power station of claim 1, wherein: the method for determining the address selection sequence of the battery energy storage power station comprises the following steps:
on the basis of considering actual requirements, a battery energy storage power station address selection sequence is represented by an n-dimensional vector A:
A＝(a1,a2,…,ai,…,an)
wherein i is the serial number of the bus, i is more than or equal to 1 and less than or equal to n, n is the number of the access buses selected by the battery energy storage power station, aiRepresenting the state of the battery storage station of the ith bus, ai1 represents that the battery energy storage power station state of the ith bus is an access state; except elements at the corresponding positions of the buses accessed into the battery energy storage power station in the addressing sequence are nonzero, the rest elements are zero.
3. The method of addressing a battery energy storage power station of claim 1, wherein: evaluating a function f according to the address selection criterion 11(xi) Evaluating the wind power consumption capacity of the power grid system under the site selection scheme corresponding to the battery energy storage power station access ith bus:
in the formula, pmaxThe limit of the original wind power integration capacity of a power grid system before the battery energy storage power station is accessed,
the method is characterized in that the wind power grid-connected capacity limit, x, of a power grid system under a site selection scheme corresponding to the ith bus accessed by a battery energy storage power stationiAnd the ith bus is accessed to the representative battery energy storage power station.
4. The method of addressing a battery energy storage power station of claim 1, wherein: evaluating a function f according to the addressing basis 22(xi) Obtaining a full-network voltage distribution deviation index corresponding to the addressing scheme of the battery energy storage power station accessed to the ith bus:
in the formula, i is more than or equal to 1 and less than or equal to n, n is the number of the access buses selected by the battery energy storage power station, and the initial voltage per unit value of the p-th bus of the power grid before the battery energy storage power station is accessed into the power grid system is VpP belongs to D, and D is a set of all buses of the power grid system; after the battery energy storage power station is connected into the power grid system in an operation mode of increasing the wind power consumption capacity of the system, the p-th bus voltage per unit value of the power grid is Vp', p belongs to D, and the number of the buses of the power grid system is m.
5. The method of addressing a battery energy storage power station of claim 1, wherein: the final site selection evaluation function is shown as the following formula:
in the above formula, n is the number of access buses, omega, selected by the battery energy storage power station1Is a weight according to 1, ω2Is a weight according to 2, ω1+ω2＝1。
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103353979A (en) * | 2013-05-31 | 2013-10-16 | 国家电网公司 | Optimization method for locating and sizing of distributed power |
| CN104636824A (en) * | 2015-01-26 | 2015-05-20 | 国家电网公司 | Distributed photovoltaic siting and sizing method for determining minimum permeability |
| CN106786734A (en) * | 2016-12-13 | 2017-05-31 | 国家电网公司 | Power grid wind accesses site selecting method |
| CN106874630A (en) * | 2017-03-28 | 2017-06-20 | 上海理工大学 | Based on the regional power grid new energy development potential evaluation method that electricity is dissolved |
| CN107403289A (en) * | 2017-09-19 | 2017-11-28 | 合肥工业大学 | A kind of highway charging station addressing constant volume method for considering access photo-voltaic power generation station |
| CN107482660A (en) * | 2017-09-04 | 2017-12-15 | 国网江苏省电力公司经济技术研究院 | A kind of active distribution network energy storage configuration method based on double-energy storage system |
-
2018
- 2018-01-19 CN CN201810051400.3A patent/CN108416459B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103353979A (en) * | 2013-05-31 | 2013-10-16 | 国家电网公司 | Optimization method for locating and sizing of distributed power |
| CN104636824A (en) * | 2015-01-26 | 2015-05-20 | 国家电网公司 | Distributed photovoltaic siting and sizing method for determining minimum permeability |
| CN106786734A (en) * | 2016-12-13 | 2017-05-31 | 国家电网公司 | Power grid wind accesses site selecting method |
| CN106874630A (en) * | 2017-03-28 | 2017-06-20 | 上海理工大学 | Based on the regional power grid new energy development potential evaluation method that electricity is dissolved |
| CN107482660A (en) * | 2017-09-04 | 2017-12-15 | 国网江苏省电力公司经济技术研究院 | A kind of active distribution network energy storage configuration method based on double-energy storage system |
| CN107403289A (en) * | 2017-09-19 | 2017-11-28 | 合肥工业大学 | A kind of highway charging station addressing constant volume method for considering access photo-voltaic power generation station |
Non-Patent Citations (2)
| Title |
|---|
| 基于信息熵的光伏发电选址与定容规划;李宏仲，等.;《南方电网技术》;20170930;第11卷(第9期);第54-61页 * |
| 风储一体化电站容量双层优化规划研究;袁铁江，等.;《高电压技术》;20151031;第41卷(第10期);第3204-3212页 * |
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