CN112311000A - Double-layer optimal configuration method for micro-grid power supply - Google Patents

Double-layer optimal configuration method for micro-grid power supply Download PDF

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CN112311000A
CN112311000A CN202010161643.XA CN202010161643A CN112311000A CN 112311000 A CN112311000 A CN 112311000A CN 202010161643 A CN202010161643 A CN 202010161643A CN 112311000 A CN112311000 A CN 112311000A
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power supply
micro
grid
wind speed
model
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郭亚琴
顾娜
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Nantong Institute of Technology
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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Abstract

The invention discloses a double-layer optimization configuration method for a micro-grid power supply, relates to the technical field of micro-grids, and particularly relates to a double-layer optimization configuration method for the micro-grid power supply, which comprises the following steps of S1, establishing a micro-grid power supply model, wherein the micro-grid power supply model comprises a wind power generator model, a photovoltaic array model and an energy storage model; s2, establishing a micro-grid power supply optimization configuration model; and S3, an HQGA algorithm for optimizing configuration of the micro-grid power supply. According to the double-layer optimization configuration method for the micro-grid power supply, the configuration of the micro-grid power supply is optimized by using a self-adaptive rotation angle adjustment strategy, a quantum bit cross variation operation and a group catastrophe idea, so that the advantage of the micro-grid can be more reasonably utilized to achieve the purpose of reasonably utilizing resources, the convergence speed is high, an optimized scheme can be searched from a global angle, and meanwhile, the error is guaranteed to be small.

Description

Double-layer optimal configuration method for micro-grid power supply
Technical Field
The invention relates to the technical field of micro-grids, in particular to a micro-grid power supply double-layer optimal configuration method.
Background
With the rapid development of economic society, the traditional energy is gradually exhausted, a centralized power system in a single power supply mode causes problems such as environmental pollution, resource and energy waste, poor stability and economy and the like, a micro-grid refers to a small power distribution system formed by collecting a distributed power supply, an energy storage device, an energy conversion device, a load, a monitoring and protecting device and the like, and is an autonomous system capable of realizing self control, protection and management, the micro-grid in China mainly has two forms of wind power and photovoltaic, the wind power and the photovoltaic are connected into a main grid to play an important role in improving the voltage of the grid and reducing the long-distance power transmission loss, the micro-grid can meet the requirements of power supply in remote areas and improving the flexibility of an urban power grid, saves the investment of a large power grid, improves the power supply reliability, has wide development and application prospects, and the configuration method of the existing micro-grid power supply, resource waste is caused, and aiming at the problems, a double-layer optimization configuration method for a micro-grid power supply is provided.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a micro-grid power supply double-layer optimization configuration method, which solves the problem that the prior micro-grid power supply configuration method proposed in the background art is not accurate enough, so that resources are wasted.
In order to achieve the purpose, the invention is realized by the following technical scheme: a microgrid power supply double-layer optimal configuration method comprises the following steps:
s1, establishing a micro-grid power supply model, which comprises a wind power generator model, a photovoltaic array model and an energy storage model;
s2, establishing a micro-grid power supply optimization configuration model;
and S3, an HQGA algorithm for optimizing configuration of the micro-grid power supply.
Preferably, the step S1 specifically includes:
output power P of wind driven generator in wind driven generator modelWTAnd the wind speed at the hub height v is:
Figure BDA0002406013600000021
wherein, PNRated output power of the fan, v is the wind speed at the height of the fan hub, vNRated wind speed, vinFor cutting into the wind speed, voutThe wind speed is cut out, the rated power of a fan is 30KW, the rated wind speed is 12m/s, the cut-out wind speed is 2.5m/s, and the cut-in wind speed is 25 m/s;
converting the wind speed to a wind speed value at the height of the fan hub by a conversion formula:
Figure BDA0002406013600000022
wherein: v is the wind speed value at the height of the hub of the fan,v0the wind speed value provided by the weather bureau, H is the hub height value, H0Is equivalent height, H is 27m, H010m, ξ is the correction index 1/7.
Preferably, the step S1 specifically includes:
and taking the power of the micro power supply and the energy storage device scheduled in the micro power grid as optimization variables, wherein each optimization variable corresponds to one dimension of the particles.
The calculation formula of the working temperature of the component is as follows:
Figure BDA0002406013600000023
in the formula, TaIs ambient temperature, GcIs the intensity of the light.
Preferably, the step S1 specifically includes:
the energy storage model adopts a storage battery as an energy storage element:
PR(t)＝Pwt(t)+Ppv(t)
in the formula: pwt(t) is the output of a single fan at time t, PpvAnd (t) is the output of the photovoltaic at the time t.
Preferably, the objective function of the microgrid power supply optimization configuration model in S2 is as follows:
Figure BDA0002406013600000024
in the formula: t is the simulation period of the system, PREt is the sum of the electric power generated by all renewable energy sources at time t, PwasteThe value of the electric quantity which is not utilized in the electric quantity generated by the renewable energy source is the difference between the sum of the electric quantity generated by the renewable energy source and the load.
Preferably, the grid-connected micro-grid system can acquire energy from a main grid, the scene takes the longest cycle life of the energy storage system as an optimization target, and the maximum power and fluctuation conditions of photovoltaic power generation and wind power generation select the energy storage type meeting the operation conditions.
Preferably, in the off-grid power grid, the energy storage system independently provides the power demand of the load.
Preferably, the correction of the objective function adopts an adaptive penalty term to introduce the objective function to construct an adaptive function formula as follows:
minC＝Ctotal+10γ·max{0,LPSP-LPSPsct}；
in the formula: gamma is more than or equal to 1 and less than or equal to 10.
Preferably, the HQGA algorithm for the optimized configuration of the microgrid power supply in S3 includes qubit crossing and qubit variation.
The invention provides a double-layer optimal configuration method for a micro-grid power supply, which has the following beneficial effects: this application utilizes self-adaptation rotation angle adjustment strategy, qubit cross variation operation and crowd catastrophe thought, optimizes the configuration of little electric wire netting power, thereby can be more reasonable utilize little electric wire netting's advantage reach the purpose of rational utilization resource, convergence rate is very fast, can follow the scheme of global angle looking for the optimization moreover, guarantees simultaneously that the error is less.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments.
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper," "lower," "left," "right," "inner," "outer," "front," "rear," "leading," "trailing," and the like are used in an orientation or positional relationship indicated for convenience in describing the invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and are not to be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "connected" and "connected" are to be interpreted broadly, e.g., as being fixed or detachable or integrally connected; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The invention provides a technical scheme that: a microgrid power supply double-layer optimal configuration method comprises the following steps:
s1, establishing a micro-grid power supply model, which comprises a wind power generator model, a photovoltaic array model and an energy storage model;
s2, establishing a micro-grid power supply optimization configuration model;
and S3, an HQGA algorithm for optimizing configuration of the micro-grid power supply.
Step S1 specifically includes:
output power P of wind driven generator in wind driven generator modelWTAnd the wind speed at the hub height v is:
Figure BDA0002406013600000041
wherein, PNRated output power of the fan, v is the wind speed at the height of the fan hub, vNRated wind speed, vinFor cutting into the wind speed, voutThe wind speed is cut out, the rated power of a fan is 30KW, the rated wind speed is 12m/s, the cut-out wind speed is 2.5m/s, and the cut-in wind speed is 25 m/s;
converting the wind speed to a wind speed value at the height of the fan hub by a conversion formula:
Figure BDA0002406013600000042
wherein: v is the wind speed value at the height of the fan hub, v0The wind speed value provided by the weather bureau, H is the hub height value, H0Is equivalent height, H is 27m, H010m, ξ is the correction index 1/7.
Step S1 specifically includes:
and taking the power of the micro power supply and the energy storage device scheduled in the micro power grid as optimization variables, wherein each optimization variable corresponds to one dimension of the particles.
The calculation formula of the working temperature of the component is as follows:
Figure BDA0002406013600000051
in the formula, TaIs ambient temperature, GcIs the intensity of the light.
Step S1 specifically includes:
the energy storage model adopts a storage battery as an energy storage element:
PR(t)＝Pwt(t)+Ppv(t)
in the formula: pwt(t) is the output of a single fan at time t, PpvAnd (t) is the output of the photovoltaic at the time t.
The objective function of the microgrid power supply optimization configuration model in the step S2 is as follows:
Figure BDA0002406013600000052
in the formula: t is the simulation period of the system, PRE(t) is the sum of the power generated by all renewable energy sources at time t, PwasteThe value of the electric quantity which is not utilized in the electric quantity generated by the renewable energy source is the difference between the sum of the electric quantity generated by the renewable energy source and the load.
The grid-connected micro-grid system can acquire energy from a main grid, the scene takes the longest cycle life of the energy storage system as an optimization target, and the maximum power and fluctuation conditions of photovoltaic and wind power generation select the energy storage type meeting the operation conditions.
In an off-grid type power grid, an energy storage system independently provides the power demand of a load.
The correction of the objective function adopts a self-adaptive penalty term to introduce the objective function to construct a self-adaptive function formula which is as follows:
minC＝Ctotal+10γ·max{0,LPSP-LPSPsct}；
in the formula: gamma is more than or equal to 1 and less than or equal to 10.
The HQGA algorithm for optimal configuration of the microgrid power supply in S3 includes qubit crossing and qubit variation.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical scope of the present invention and the equivalent alternatives or modifications according to the technical solution and the inventive concept of the present invention within the technical scope of the present invention.

Claims (9)

1. A double-layer optimal configuration method for a micro-grid power supply is characterized by comprising the following steps:
s1, establishing a micro-grid power supply model, which comprises a wind power generator model, a photovoltaic array model and an energy storage model;
s2, establishing a micro-grid power supply optimization configuration model;
and S3, an HQGA algorithm for optimizing configuration of the micro-grid power supply.
2. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the step S1 specifically includes:
output power P of wind driven generator in wind driven generator modelWTAnd the wind speed at the hub height v is:
Figure FDA0002406013590000011
wherein, PNRated output power of the fan, v is the wind speed at the height of the fan hub, vNRated wind speed, vinFor cutting into the wind speed, voutThe wind speed is cut out, the rated power of a fan is 30KW, the rated wind speed is 12m/s, the cut-out wind speed is 2.5m/s, and the cut-in wind speed is 25 m/s;
converting the wind speed to a wind speed value at the height of the fan hub by a conversion formula:
Figure FDA0002406013590000012
wherein: v is the wind speed value at the height of the fan hub, v0The wind speed value provided by the weather bureau, H is the hub height value, H0Is equivalent height, H is 27m, H010m, ξ is the correction index 1/7.
3. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the step S1 specifically includes:
and taking the power of the micro power supply and the energy storage device scheduled in the micro power grid as optimization variables, wherein each optimization variable corresponds to one dimension of the particles.
The calculation formula of the working temperature of the component is as follows:
Figure FDA0002406013590000021
in the formula, TaIs ambient temperature, GcIs the intensity of the light.
4. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the step S1 specifically includes:
the energy storage model adopts a storage battery as an energy storage element:
PR(t)＝Pwt(t)+Ppv(t)
in the formula: pwt(t) is the output of a single fan at time t, PpvAnd (t) is the output of the photovoltaic at the time t.
5. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the objective function of the microgrid power supply optimization configuration model in the step S2 is as follows:
Figure FDA0002406013590000022
in the formula: t is the simulation period of the system, PRE(t) is the sum of the power generated by all renewable energy sources at time t, PwasteAnd (t) the amount of electricity which is not utilized in the amount of electricity generated by the renewable energy sources, and the value of the amount of electricity is the difference between the sum of the amounts of electricity generated by the renewable energy sources and the load.
6. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the grid-connected micro-grid system can acquire energy from a main grid, the scene takes the longest cycle life of the energy storage system as an optimization target, and the maximum power and fluctuation conditions of photovoltaic and wind power generation select the energy storage type meeting the operation conditions.
7. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: in the off-grid type power grid, an energy storage system independently provides the power demand of the load.
8. The microgrid power supply double-layer optimization configuration method of claim 5, characterized in that: the correction of the objective function adopts a self-adaptive penalty term to introduce the objective function to construct a self-adaptive function formula as follows:
minC＝Ctotal+10γ·max{0,LPSP-LPSPsct}；
in the formula: gamma is more than or equal to 1 and less than or equal to 10.
9. The microgrid power supply double-layer optimization configuration method of claim 1, characterized in that: the HQGA algorithm for optimizing configuration of the microgrid power supply in S3 includes qubit crossing and qubit variation.
CN202010161643.XA 2020-03-10 2020-03-10 Double-layer optimal configuration method for micro-grid power supply Pending CN112311000A (en)

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CN104184170A (en) * 2014-07-18 2014-12-03 国网上海市电力公司 Independent microgrid configuration optimization method based on improved adaptive genetic algorithm
CN104881716A (en) * 2015-05-28 2015-09-02 贵州电网公司电网规划研究中心 Optimization programming and evaluation method of micro-grid power supply
CN107508303A (en) * 2017-08-09 2017-12-22 国电南瑞科技股份有限公司 A kind of modularization energy storage device towards micro-capacitance sensor is distributed rationally and control method
CN109687444A (en) * 2018-12-27 2019-04-26 广东电网有限责任公司 A kind of micro-capacitance sensor power supply multiple target dual-layer optimization configuration method
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Application publication date: 20210202