CN116054133A - Dynamic simulation modeling method and system for photovoltaic electrolytic aluminum direct-current micro-grid - Google Patents
Dynamic simulation modeling method and system for photovoltaic electrolytic aluminum direct-current micro-grid Download PDFInfo
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- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 90
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 89
- 238000000034 method Methods 0.000 title claims abstract description 34
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- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical compound [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 claims 1
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- 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
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- 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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- 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]
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- 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
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- 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
- H02J2300/28—The renewable source being wind energy
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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
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- 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
Abstract
The invention discloses a dynamic simulation modeling method of a photovoltaic electrolytic aluminum direct current micro-grid, which comprises the following steps: determining a large-scale distributed photovoltaic as a main power supply, and researching an equivalent model for accurately and efficiently simulating the dynamic external characteristics under the condition that other new energy sources are used as auxiliary power supplies for directly supplying power to the electrolytic tank; optimizing the equivalent model based on the characteristics of volatility and randomness of the main power supply and the auxiliary power supply; taking an electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of electrolytic aluminum; and integrating the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum. According to the invention, links of the photovoltaic, electrolytic aluminum system and the direct current micro-grid are comprehensively considered, and the efficient, accurate and wide-applicability modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid is realized. The method realizes the on-site power supply and the distributed photovoltaic on-site digestion of the electrolytic series and the photovoltaic direct current interconnection, and improves the renewable energy utilization level and the energy efficiency level in the electrolytic aluminum industry.
Description
Technical Field
The invention belongs to the technical field of new energy utilization and electrolytic aluminum, and particularly relates to a dynamic simulation modeling method and system for a photovoltaic electrolytic aluminum direct current micro-grid.
Background
At present, large power grids are mostly adopted for supplying power to electrolytic tanks in electrolytic aluminum enterprises in China, so that the electric energy conversion links are many and complex, and the electric energy loss is serious; with the rapid development of new energy in China, some high-energy-consumption production enterprises mainly in nonferrous metal industry plan or already start to build a large amount of new energy to generate electricity in order to reduce electricity cost and effectively improve enterprise competitiveness, and select self-built units or switch from networking operation to isolated network operation. For high-energy-consumption industrial loads of direct current power supply such as electrolytic aluminum, electrolytic hydrogen production and the like, the power consumption range is wider, the control characteristic is better, and the method is suitable for direct current access of new energy without affecting the stability of a power system.
At present, the industry of electrolytic aluminum and electrolytic hydrogen production at home and abroad mainly adopts a grid-connected mode for accessing new energy, no mature case exists in the aspects of off-grid operation and direct current power supply, and no method for dynamic simulation modeling of a photovoltaic electrolytic aluminum direct current micro-grid is provided.
Disclosure of Invention
In order to solve the problems in the prior art, the invention performs research on the distributed photovoltaic direct current access electrolytic aluminum power supply technology, performs dynamic simulation modeling on the photovoltaic electrolytic aluminum direct current micro-grid, and verifies the technical feasibility of the direct current micro-grid electric energy direct current power supply aluminum system under high-capacity distributed photovoltaic access.
The invention aims to provide a dynamic simulation modeling method for a photovoltaic electrolytic aluminum direct current micro-grid, which comprises the following steps:
s1, using a large-scale distributed photovoltaic as a main power supply, directly supplying power to an electrolytic cell by using other new energy sources as auxiliary power supplies, and establishing an equivalent model for simulating the dynamic external characteristics;
s2, optimizing the equivalent model based on the volatility and randomness of the main power supply and the auxiliary power supply;
s3, taking the electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of the electrolytic aluminum;
and S4, integrating the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum, namely comprehensively considering links of the photovoltaic system, the electrolytic aluminum system and the direct current micro-grid, and realizing efficient, accurate and widely applicable modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid.
Preferably, the S1 includes:
(1) Photovoltaic power fluctuation characteristic analysis: the change influencing factors in the balance system are called disturbance elements, and the micro-grid system is connected with other intermittent new energy sources and photovoltaics, so that the effect is equivalent to adding the disturbance elements of the other new energy sources and the photovoltaic power disturbance elements in the system;
(2) Determining an impact index of power fluctuation characteristics of wind power and photovoltaic power generation on micro-grid frequency stabilization, thereby quantitatively describing fluctuation characteristics of wind power and photovoltaic treatment based on the impact index, comprising:
a fluctuation amount
ΔP n ＝P t -P t-1 (1)；
Wherein DeltaP n For the fluctuation amount of wind power and photovoltaic power in n time periods, P t For the wind power and photovoltaic output value at time t, P t-1 The wind power and photovoltaic output value at the moment t-1;
b fluctuation ratio
Wherein x is n For the fluctuation value of wind power and photovoltaic power at time n, P N Rated values for wind power and photovoltaic output;
c fluctuation rate:
wherein V is n The change rate of wind power and photovoltaic power fluctuation in n time periods is given, and delta t is a time interval;
d power permeability:
wherein epsilon is the permeability of wind power and photovoltaic power and P Load.max The load maximum value of the system is calculated when the permeability of wind power and photovoltaic treatment is calculated;
(3) The equivalent model for accurately and efficiently simulating the dynamic external characteristics of the output comprises a load, a transformer and a motor part.
Preferably, the optimizing the equivalent model based on the characteristics of the volatility and randomness of the primary power source and the secondary power source S2 includes:
the direct current micro-grid system comprises a photovoltaic power generation unit, a wind power generation unit and a load.
Preferably, the optimizing of the equivalent model of S2 comprises:
(1) Objective function: based on the direct current micro grid system under the time-of-use electricity price, the maximum daily gain of a user side is achieved by optimizing the power of the storage battery in 24 hours, and the objective function of optimizing and scheduling is as follows:
and if P at time t inv (t) < 0, then C (t) =C sell (t), conversely, C (t) =c buy (t)；
In the formula (5), F represents the gain of the direct current micro-grid in the whole dispatching period of 24 hours; t is the whole dispatching cycle; c (C) sell (t)、C buy (t) the peak-valley time-of-use electricity price of electricity selling and purchasing at the moment t respectively; p (P) inv (t) is the interaction power of the direct current micro-grid and the electrolytic aluminum system at the moment t;
(2) Constraint conditions: in order to ensure the running stability of the system, in the process of solving the objective function, reasonable constraint conditions are selected to effectively control each unit of the system, and the constraint conditions of optimizing the scheduling comprise:
A. active power balance constraint conditions:
P pv (t)+P wind (t)-P load (t)+ε 1 P bat (t)＝P inv (t)(6)；
wherein P is pv (t) is the photovoltaic power generation power (P) pv (t)<0)；P wind (t) is the wind power generation power (P) at time t wind (t)<0)；P load (t) load power consumption at time t; p (P) bat (t) is the charge and discharge power of the storage battery at the moment t; epsilon 1 Taking 1 as a charge and discharge coefficient, and taking-1 as discharge; the formula (6) shows that the system must meet energy conservation during operation;
B. maximum capacity constraint condition of exchange of direct current micro-grid and large grid and electrolytic aluminum system:
P min_inv ≤P inv (t)≤P max_inv (7)；
wherein P is min_inv Minimum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system; p (P) max_inv Maximum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system;
C. battery capacity constraint conditions:
E bat,min ≤E bat (t)≤E bat,max (8)；
during charging E bat (t)＝E bat (t-1)-P bat (t-1)·Δt·β ch (9)；
Upon discharge E bat (t)＝E bat (t)-P bat (t-1)·Δt/β dis (10)；
In the formulae (8) to (10), E bat (t) is the electric quantity of the storage battery at the moment t; e (E) bat,min An upper limit of capacity set for preventing overcharge of the battery; e (E) bat,max A lower limit of capacity set to prevent overdischarge of the battery; p (P) bat (t) is the charge and discharge power of the storage battery; Δt is the scheduling period length; beta ch And beta dis Is the charge and discharge efficiency of the storage battery.
Preferably, the step S3 of determining the off-load characteristics and the system structure by using the electrolytic aluminum system as a typical impact load, and the modeling of the electrolytic aluminum characteristics includes:
and (3) equivalent load of wind power and photovoltaic power is equivalent to negative load, and equivalent load power of the system is obtained by making difference between the load power and wind power photovoltaic power.
Preferably, after the output power of the wind power plant and the photovoltaic power station is regarded as a negative load, the equivalent load of the system is as follows:
P E ＝P L -P W -P S (11)
wherein P is E Equivalent load power of system containing wind power and photovoltaic, P L For the whole network load power, P W For wind power fluctuation power, P S Is photovoltaic fluctuating power.
Preferably, the equivalent load fluctuation quantity delta P of the system after wind power and photovoltaic are connected E ：
ΔP E ＝ΔP L -ΔP W -ΔP S (12)；
Wherein DeltaP L Delta P is the change of the load of the whole network W Delta P is the wind power variation S Is the photovoltaic power variation.
The second aspect of the invention provides a photovoltaic electrolytic aluminum direct current micro-grid dynamic simulation modeling system, which comprises:
the equivalent model building module is used for directly supplying power to the electrolytic tank by taking the large-scale distributed photovoltaic as a main power supply and other new energy sources as auxiliary power supplies, and building an equivalent model for accurately and efficiently simulating and outputting dynamic external characteristics;
the equivalent model optimization module is used for optimizing the equivalent model based on the volatility and the randomness of the main power supply and the auxiliary power supply;
the electrolytic aluminum system modeling module is used for taking an electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of electrolytic aluminum;
and the comprehensive dynamic simulation modeling module is used for integrating the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum, namely comprehensively considering links of a photovoltaic system, an electrolytic aluminum system and a direct current micro-grid, and realizing efficient, accurate and wide-applicability modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid.
A third aspect of the invention provides an electronic device comprising a processor and a memory, the memory storing a plurality of instructions, the processor being for reading the instructions and performing the method according to the first aspect.
A fourth aspect of the invention provides a computer readable storage medium storing a plurality of instructions readable by a processor and for performing the method of the first aspect.
The method, the device, the electronic equipment and the computer readable storage medium provided by the invention have the following beneficial technical effects:
according to the invention, links of the photovoltaic, electrolytic aluminum system and the direct current micro-grid are comprehensively considered, and the efficient, accurate and wide-applicability modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid is realized. The method realizes the interconnection power supply of the electrolytic series and the photovoltaic direct current and the on-site consumption of the distributed photovoltaic, improves the renewable energy utilization level and the energy efficiency level of the electrolytic aluminum industry, provides technical support for the direct supply of green electricity, and provides green development of service.
Drawings
FIG. 1 is a schematic diagram of an equivalent model of the dynamic external characteristics of the accurate and efficient simulation output in the invention;
fig. 2 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
Example 1
The dynamic simulation modeling method for the photovoltaic electrolytic aluminum direct-current micro-grid of the embodiment comprises the following steps:
s1, using a large-scale distributed photovoltaic as a main power supply, directly supplying power to an electrolytic tank by using other new energy sources as auxiliary power supplies, and establishing an equivalent model for accurately and efficiently simulating the dynamic external characteristics;
s2, optimizing the equivalent model based on the characteristics of volatility and randomness of the main power supply and the auxiliary power supply;
s3, taking the electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of the electrolytic aluminum;
and S4, integrating the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum, namely comprehensively considering links of the photovoltaic system, the electrolytic aluminum system and the direct current micro-grid, and realizing efficient, accurate and widely applicable modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid.
The S1 comprises the following steps:
(1) Photovoltaic power fluctuation characteristic analysis: the change influencing factors in the balance system are called disturbance elements, and other new energy sources (wind power is taken as an example in the embodiment) with intermittence and photoelectricity are connected into the micro-grid system, so that the micro-grid system is equivalent to adding other new energy source disturbance elements (wind power disturbance elements) and photovoltaic disturbance elements into the system; therefore, determining control measures for suppressing the influence of such disturbance on the frequency fluctuation of the power grid system requires analyzing the wind-light power fluctuation characteristics in the power grid from the control disturbance source. The embodiment mainly surrounds the power unbalance factor causing the frequency instability of the power grid system, analyzes the power fluctuation characteristics of new energy power generation such as wind power, photovoltaic and the like based on actual measurement data of the power grid in the current year, determines the fluctuation characteristics of load power and the power fluctuation characteristics of equivalent load formed by wind-light as negative electricity load and original electricity load, and lays a foundation for analyzing the frequency influence rule of wind-light access on the electrolytic aluminum micro-grid;
(2) Determining an impact index for quantitatively determining the stability of power fluctuation characteristics of wind power and photovoltaic power generation on the frequency of the micro-grid, so as to quantitatively describe the fluctuation characteristics of wind power and photovoltaic treatment based on the impact index, wherein the method comprises the following steps of:
a fluctuation amount
ΔP n ＝P t -P t-1 (1)；
Wherein DeltaP n For the fluctuation amount of wind power and photovoltaic power in n time periods, P t For the wind power and photovoltaic output value at time t, P t-1 The wind power and photovoltaic output value at the moment t-1;
b fluctuation ratio
Wherein x is n For the fluctuation value of wind power and photovoltaic power at time n, P N Rated values for wind power and photovoltaic output;
c wave rate
Wherein V is n The change rate of wind power and photovoltaic power fluctuation in n time periods is given, and delta t is a time interval;
d power permeability
Wherein epsilon is the permeability of wind power and photovoltaic power and P Load.max To calculate the maximum load of the system when wind power and photovoltaic process penetration are calculated.
(3) The equivalent model of the accurate and efficient analog output dynamic external characteristics comprises a load, a transformer and a motor part, as shown in fig. 1:
as a preferred embodiment, the optimizing the equivalent model based on the characteristics of the volatility and the large randomness of the main power supply and the auxiliary power supply S2 includes:
the direct-current micro-grid system comprises a photovoltaic power generation unit, a wind power generation unit and a load; the preferred embodiment also comprises an energy storage unit, and under the condition of determining the output force of the distributed power supply, the power sent by the storage unit of the storage battery is regulated and controlled to directly relate to the output power condition of the direct current micro-grid to the electrolytic tank. In order to utilize the distributed photovoltaic and wind energy output power at different times of the day, the system obtains the highest benefit in the aluminum electrolysis process, the system is divided into 24 scheduling stages by taking one day as a scheduling period, a proper objective function and related constraint conditions are formulated based on a genetic algorithm, an MATLAB development tool is utilized to obtain an optimal solution, an optimal scheduling strategy of the distributed photovoltaic and energy storage units is obtained, and the operation efficiency and the economy of the electrolytic tank of the aluminum electrolysis are improved as a whole.
(1) Objective function: based on the direct current micro grid system under the time-of-use electricity price, the maximum daily gain of a user side is achieved by optimizing the power of the storage battery in 24 hours, and the objective function of optimizing and scheduling is as follows:
and if P at time t inv (t) < 0, then C (t) =C sell (t), conversely, C (t) =c buy (t)；
In the formula (5), F represents the gain of the direct current micro-grid in the whole dispatching period of 24 hours; t is the whole dispatching cycle; c (C) sell (t)、C buy (t) the peak-valley time-of-use electricity price of electricity selling and purchasing at the moment t respectively; p (P) inv (t) is the interaction power of the direct current micro-grid and the electrolytic aluminum system at the moment t;
(2) Constraint conditions: in order to ensure the running stability of the system, in the process of solving the objective function, reasonable constraint conditions are selected to effectively control each unit of the system, and the constraint conditions of optimizing the scheduling comprise:
A. active power balance constraint conditions:
P pv (t)+P wind (t)-P load (t)+ε 1 P bat (t)＝P inv (t)(6)；
wherein P is pv (t) is the photovoltaic power generation power (P) pv (t)<0)；P wind (t) is the wind power generation power (P) at time t wind (t)<0)；P load (t) load power consumption at time t; p (P) bat (t) is the charge and discharge power of the storage battery at the moment t; epsilon 1 Taking 1 as a charge and discharge coefficient, and taking-1 as discharge; the formula (5) shows that the system must meet energy conservation during operation;
B. maximum capacity constraint condition of exchange of direct current micro-grid and large grid and electrolytic aluminum system:
P min_inv ≤P inv (t)≤P max_inv (7)；
wherein P is min_inv Minimum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system; p (P) max_inv Maximum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system;
C. battery capacity constraint (optional):
E bat,min ≤E bat (t)≤E bat,max (8)；
during charging E bat (t)＝E bat (t-1)-P bat (t-1)·Δt·β ch (9)；
Upon discharge E bat (t)＝E bat (t)-P bat (t-1)·Δt/β dis (10)；
In the formulae (8) to (10), E bat (t) is the electric quantity of the storage battery at the moment t; e (E) bat,min An upper limit of capacity set for preventing overcharge of the battery; e (E) bat,max A lower limit of capacity set to prevent overdischarge of the battery; p (P) bat (t) is the charge and discharge power of the storage battery; Δt is the scheduling period length, Δt is 1h in this embodiment, and the capacity of the battery is E bat,min ＝20，E bat,max ＝100；β ch And beta dis For the charge and discharge efficiency of the accumulator, takeThe value was 95%.
In a preferred embodiment, the step S3 of determining the off-load characteristics and the system structure using the electrolytic aluminum system as a typical impact load, and the step of modeling the electrolytic aluminum system to conform to the characteristics of the electrolytic aluminum comprises:
the current power grid system is a complex and comprehensive multi-energy conversion dynamic system. Before new energy power generation is raised, the power grid system is provided with a set of load-frequency control system which belongs to the power grid system, so that the power generation power can be quickly tracked and matched with the load, the balance of power generation and power utilization is achieved, and the stability of the power grid frequency is maintained. The balancing mechanism is realized by the following means: firstly, the power grid side can accurately predict the load of the next day in the power grid; the power grid dispatching mechanism then arranges an output plan according to the capacity of the units in the grid so as to balance the predicted daily power grid load, and only leaves a small part of standby margin in the actual power grid operation process to cope with the deviation amount between the actual power grid load and the daily predicted load. However, along with the economic development, the proportion of the fluctuation load in the power grid is also increased, the power consumption of the electrolytic aluminum is increased, and due to the change of a working system and the fluctuation frequency of the load, the larger active power unbalance is extremely easy to be caused, and the system frequency is caused to be over-line, so that the system load change rule is an important task for carrying out frequency control, and the load fluctuation characteristic of the photovoltaic direct-current micro-grid system is necessary to be analyzed.
For continuously produced electrolytic aluminum enterprises, the annual load characteristic shows the characteristic of summer and winter double peaks, the daily load change of the power grid is very stable, the time sequence distribution is mainly concentrated between 0.84p.u. and 94p.u., the maximum value of the load is 0.935p.u., the minimum value is 0.844p.u., and the average accord with 0.899p.u. The load valley peak difference of the power grid is small, the maximum valley peak difference is about 9%, the load rate is high, and the average coincidence rate is close to 0.9p.u.. And the load is discharged from the furnace at three points of 8, 16 and 24 per day, so that the load fluctuation of the power grid is large.
Therefore, the step S3 requires the analysis of the time-equivalent load fluctuation characteristic. And (3) equivalent load power of the system is obtained by making a difference between the load power and the wind power photovoltaic power by equivalent load of wind power and photovoltaic power, and at the moment, the equivalent load power of the system is a main factor influencing the frequency change of the power grid.
(1) After the output power of the wind power plant and the photovoltaic power station is regarded as a negative load, the equivalent load of the system is as follows:
P E ＝P L -P W -P S (11)
wherein P is E Equivalent load power of system containing wind power and photovoltaic, P L For the whole network load power, P W For wind power fluctuation power (if any), P S Is photovoltaic fluctuation power;
(2) Equivalent load fluctuation quantity delta P of system after wind power and photovoltaic are connected E ：
ΔP E ＝ΔP L -ΔP W -ΔP S (12)；
Wherein DeltaP L Delta P is the change of the load of the whole network W Delta P is the wind power variation S Is the photovoltaic power variation;
as can be seen from the formula (11), if the wind power change trend is consistent with the load change trend, the equivalent load power change curve is slower than the load power curve, so that an equivalent load power fluctuation curve which is favorable for stabilizing the frequency of the power grid is obtained; on the contrary, the wind power change condition is opposite to the load change condition, so that the change range of the equivalent load curve is large, and the stable operation of the power system is not facilitated.
In this example, the equivalent load and the original load fluctuation value are compared as shown in table 1 below.
TABLE 1 comparison of equivalent load and raw load fluctuation values
The second aspect of the invention provides a photovoltaic electrolytic aluminum direct current micro-grid dynamic simulation modeling system, which comprises:
the equivalent model preliminary building module is used for determining that the large-scale distributed photovoltaic is used as a main power supply, and researching an equivalent model for accurately and efficiently simulating and outputting dynamic external characteristics under the condition that other new energy sources are used as auxiliary power supplies for directly supplying power to the electrolytic tank;
the equivalent model optimization module is used for optimizing the equivalent model based on the characteristics of volatility and large randomness of the main power supply and the auxiliary power supply;
the electrolytic aluminum system modeling module is used for taking an electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of electrolytic aluminum;
and the comprehensive dynamic simulation modeling module is used for integrating the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum, namely comprehensively considering links of a photovoltaic system, an electrolytic aluminum system and a direct current micro-grid, and realizing efficient, accurate and wide-applicability modeling simulation of the photovoltaic electrolytic aluminum direct current micro-grid.
The invention also provides a memory storing a plurality of instructions for implementing the method according to embodiment one.
As shown in fig. 2, the present invention further provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301, where the memory 302 stores a plurality of instructions, and the instructions may be loaded and executed by the processor, so that the processor can perform the method according to the embodiment.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A dynamic simulation modeling method for a photovoltaic electrolytic aluminum direct current micro-grid is characterized by comprising the following steps:
s1, using distributed photovoltaic as a main power supply, directly supplying power to an electrolytic aluminum cell by using other new energy sources as auxiliary power supplies, and establishing an equivalent model for simulating output dynamic external characteristics;
s2, optimizing the equivalent model based on the volatility and randomness of the main power supply and the auxiliary power supply;
s3, taking the electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of the electrolytic aluminum;
and S4, synthesizing the optimized equivalent model and the model conforming to the characteristics of electrolytic aluminum, and modeling and simulating the photovoltaic electrolytic aluminum direct current micro-grid.
2. The method for dynamically simulating and modeling a photovoltaic electrolytic aluminum direct current micro-grid according to claim 1, wherein the equivalent model simulating the output dynamic external characteristics in S1 comprises a load, a transformer and a motor, wherein other new energy sources are wind energy, and an influence index of the power fluctuation characteristics of wind power and photovoltaic power generation on the frequency stabilization of the direct current micro-grid is determined, so that the fluctuation characteristics of wind power and photovoltaic processing are quantitatively described based on the influence index, and the method comprises the following steps:
a fluctuation amount
ΔP n ＝P t -P t-1
Wherein DeltaP n For the fluctuation amount of wind power and photovoltaic power in n time periods, P t For the wind power and photovoltaic output value at time t, P t-1 The wind power and photovoltaic output value at the moment t-1;
b fluctuation ratio
Wherein x is n For the fluctuation value of wind power and photovoltaic power at time n, P N Rated values for wind power and photovoltaic output;
c wave rate
Wherein V is n The change rate of wind power and photovoltaic power fluctuation in n time periods is given, and delta t is a time interval;
d power permeability
Wherein epsilon is the permeability of wind power and photovoltaic power and P Load.max To calculate the maximum load of the system when wind power and photovoltaic process penetration are calculated.
3. The method for dynamically simulating and modeling a photovoltaic aluminum electrolysis direct current micro-grid according to claim 1, wherein optimizing the equivalent model based on the characteristics of volatility and randomness of the main power supply and the auxiliary power supply in S2 comprises:
the distributed photovoltaic and wind energy output power at different moments is utilized, so that the direct current micro-grid system obtains the highest benefit in the aluminum electrolysis process, and the direct current micro-grid system comprises a photovoltaic power generation unit, a wind power generation unit and a load.
4. The method for dynamically simulating and modeling a photovoltaic aluminum electrolysis direct current micro-grid according to claim 3, wherein optimizing the equivalent model based on the characteristics of volatility and randomness of the main power supply and the auxiliary power supply in S2 comprises:
(1) Objective function: based on the direct current micro grid system under the time-of-use electricity price, the maximum daily gain of a user side is achieved by optimizing the power of the storage battery in 24 hours, and the objective function of optimizing and scheduling is as follows:
and if P at time t inv (t) < 0, then C (t) =C sell (t), conversely, C (t) =c buy (t)；
In the formula (5), F represents the gain of the direct current micro-grid in the whole dispatching period of 24 hours; t is the whole dispatching cycle; c (C) sell (t)、C buy (t) the peak-valley time-of-use electricity price of electricity selling and purchasing at the moment t respectively; p (P) inv (t) is the interaction power of the direct current micro-grid and the electrolytic aluminum system at the moment t;
(2) Constraint conditions: in order to ensure the running stability of the system, in the process of solving the objective function, reasonable constraint conditions are selected to effectively control each unit of the system, and the constraint conditions of optimizing the scheduling comprise:
a active Power balance constraint
P pv (t)+P wind (t)-P load (t)+ε 1 P bat (t)＝P inv (t)
Wherein P is pv (t) is the photovoltaic power generation power at the moment t, P pv (t)<0；P wind (t) is the wind power generation power at the moment t, P wind (t)<0；P load (t) load power consumption at time t; p (P) bat (t) is the charge and discharge power of the storage battery at the moment t; epsilon 1 Taking 1 as a charge and discharge coefficient, and taking-1 as discharge;
and B, maximum capacity constraint conditions of exchange of the direct current micro-grid and the large grid and the electrolytic aluminum system are as follows:
P min_inv ≤P inv (t)≤P max_inv
wherein P is min_inv Minimum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system; p (P) max_inv Maximum power allowed to be exchanged for the direct current micro-grid and the large grid and the electrolytic aluminum system;
c, constraint conditions of storage battery capacity:
E bat,min ≤E bat (t)≤E bat,max
during charging E bat (t)＝E bat (t-1)-P bat (t-1)·Δt·β ch
Upon discharge E bat (t)＝E bat (t)-P bat (t-1)·Δt/β dis
The seed is7) - (9) in, E bat (t) is the electric quantity of the storage battery at the moment t; e (E) bat,min An upper limit of capacity set for preventing overcharge of the battery; e (E) bat,max A lower limit of capacity set to prevent overdischarge of the battery; p (P) bat (t) is the charge and discharge power of the storage battery; beta ch And beta dis Is the charge and discharge efficiency of the storage battery.
5. The method for dynamically simulating and modeling a photovoltaic aluminum electrolysis direct current micro-grid according to claim 1, wherein the step of determining the off-load characteristics and the system structure by using the aluminum electrolysis system as a typical impact load in the step of S3, and the step of establishing a model conforming to the aluminum electrolysis characteristics comprises the following steps:
and (3) equivalent load of the wind power and the photovoltaic power is obtained by making a difference between the load power and the wind power photovoltaic power.
6. The method for dynamically simulating and modeling a photovoltaic aluminum electrolysis direct current micro-grid according to claim 5, wherein after the output power of the wind power plant and the photovoltaic power station is regarded as a negative load, the equivalent load of the system is as follows:
P E ＝P L -P W -P S
wherein P is E Equivalent load power of system containing wind power and photovoltaic, P L For the whole network load power, P W For wind power fluctuation power, P S Is photovoltaic fluctuating power.
7. The method for dynamically simulating and modeling a photovoltaic electrolytic aluminum direct current micro-grid according to claim 6, wherein the equivalent load fluctuation amount delta P of the system after wind power and photovoltaic are connected E ：
ΔP E ＝ΔP L -ΔP W -ΔP S
Wherein DeltaP L Delta P is the change of the load of the whole network W Delta P is the wind power variation S Is the photovoltaic power variation.
8. A photovoltaic electrolytic aluminum direct current micro-grid dynamic simulation modeling system, comprising:
the equivalent model building module is used for directly supplying power to the electrolytic tank by taking the large-scale distributed photovoltaic as a main power supply and other new energy sources as auxiliary power supplies, and building an equivalent model for simulating the dynamic external characteristics;
the equivalent model optimization module is used for optimizing the equivalent model based on the characteristics of volatility and randomness of the main power supply and the auxiliary power supply;
the electrolytic aluminum system modeling module is used for taking an electrolytic aluminum system as a typical impact load, determining the external characteristics of the load and the system structure, and establishing a model conforming to the characteristics of electrolytic aluminum;
and the comprehensive dynamic simulation modeling module is used for integrating the optimized equivalent model and the model conforming to the characteristics of the electrolytic aluminum, and modeling and simulating the photovoltaic electrolytic aluminum direct current micro-grid.
9. An electronic device comprising a processor and a memory, the memory storing a plurality of instructions, the processor configured to read the instructions and perform the method of any of claims 1-7.
10. A computer readable storage medium storing a plurality of instructions readable by a processor and for performing the method of any one of claims 1-7.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170104363A1 (en) * | 2015-10-08 | 2017-04-13 | Everon24 Llc | Rechargeable aluminum ion battery |
| CN209233479U (en) * | 2018-12-28 | 2019-08-09 | 贵州省六盘水双元铝业有限责任公司 | Electrolytic aluminium load participates in frequency modulation device in a kind of low power consuming electrolytic aluminium power supply system |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170104363A1 (en) * | 2015-10-08 | 2017-04-13 | Everon24 Llc | Rechargeable aluminum ion battery |
| CN209233479U (en) * | 2018-12-28 | 2019-08-09 | 贵州省六盘水双元铝业有限责任公司 | Electrolytic aluminium load participates in frequency modulation device in a kind of low power consuming electrolytic aluminium power supply system |
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