CN112290604B - Power distribution network coordination optimization method and device considering load characteristics and storage medium - Google Patents
Power distribution network coordination optimization method and device considering load characteristics and storage medium Download PDFInfo
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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
- 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
- H02J3/50—Controlling the sharing of the out-of-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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Abstract
The invention provides a power distribution network coordination optimization method and device considering load characteristics and a storage medium. The invention establishes a linearization active and reactive coordination optimization model with minimum economic cost and minimum voltage fluctuation of the active power distribution network as targets, and remarkably reduces the economic operation cost of the active power distribution network under the condition of effectively stabilizing the busbar voltage of the sensitive load.
Description
Technical Field
The invention relates to the technical field of power systems and automation thereof, in particular to a coordination optimization method of a power distribution network considering load characteristics, and a device and a storage medium applying the method.
Background
The proportion of renewable energy sources connected into a power grid is gradually increased, renewable energy sources such as wind power and the like have great randomness and fluctuation, and voltage fluctuation can be caused to a certain extent after the renewable energy sources are connected into the power grid, so that the power grid is unstable, and the problem of electric energy quality is caused.
Therefore, many electrical devices are extremely susceptible to voltage changes, which can cause abnormal operation of the device in a short period of time, and cause malfunction of the device in severe cases, thereby causing a large amount of economic loss. The power quality problem has more remarkable influence on the industries of semiconductor manufacture, information, computer or electronic communication and the like, and the equipment and power load of the industries are more sensitive to voltage fluctuation. Once a failure occurs, it can cause a series of sequential safety problems and significant economic losses. The prior art mainly focuses on the overall voltage quality of a power distribution network, and does not consider the static characteristics of the load in the reactive power optimization process, so that better optimization effect can not be ensured in areas with higher industrial load and commercial load.
The existing active power distribution network optimization method mainly has the following problems:
(1) In the optimization process, the sensitive load with higher voltage requirement is not considered; (2) The load static model at the present stage does not consider the time-varying characteristics of the load components; (3) The sensitivity of the sensitive load to the voltage is higher, the fluctuation of the voltage can influence the normal operation of the sensitive load, but the fluctuation cost of the sensitive load is not considered by the optimization objective function at the present stage; (4) No reasonable active and reactive optimization is performed for active distribution networks containing sensitive loads.
Disclosure of Invention
A first object of the present invention is to provide a coordinated optimization method of a power distribution network capable of significantly reducing the economic operation cost of an active power distribution network under the condition of effectively stabilizing the bus voltage of a sensitive load.
A second object of the present invention is to provide a power distribution network coordination optimization device that can significantly reduce the economic running cost of an active power distribution network while taking into account the load characteristics, under the condition of effectively stabilizing the bus voltage of a sensitive load.
A third object of the present invention is to provide a storage medium.
In order to achieve the first object, the present invention provides a power distribution network coordination optimization method taking into account load characteristics, which includes establishing a load linear ZIP model based on taking into account time-varying characteristics; establishing a linearization power flow model of an active power distribution network; establishing an active power and reactive power coordination optimization model of the active power distribution network; solving an established active power and reactive power coordination optimization model of the active power distribution network by using a GAMS system; and dispatching the active power distribution network system according to the solving result.
In a further scheme, a static voltage characteristic model and a linearization load model of the load are constructed, and a load linear ZIP model containing the load time-varying characteristic is obtained based on the time-varying characteristic of the load.
In a further scheme, an objective function with minimized economic cost of the active power distribution network, including electricity purchasing cost, micro gas turbine cost, network loss cost and sensitive load fluctuation cost, is established, and the cost of different parts is reasonably optimized and calculated.
In a further scheme, an active and reactive constraint model of the active power distribution network including load flow balance, micro gas turbine constraint, wind driven generator constraint and SVC constraint is established.
In a further scheme, step S41, an active power and reactive power coordination optimization model of the active power distribution network is input into the GAMS system, variables and constants are defined, and equality and inequality constraints are established according to the active power and reactive power coordination optimization model of the active power distribution network; and S42, solving the active power and reactive power coordination optimization model of the active power distribution network by adopting a linear optimization solver.
In a further scheme, in the step S42, if an error occurs in the solving process or the operation result is not converged, the method returns to the step S41 to modify parameters, and an active power and reactive power coordination optimization model of the active power distribution network is re-established; in the step S42, if the calculation result converges in the solving process, the operation result is returned to MATLAB software, the analysis related result is calculated, and the result visualization chart processing is performed.
In a still further aspect, the method further comprises calculating a load linear ZIP model defining a time-varying characteristic based on the count, according to the following equation:
in a still further aspect, the method further comprises calculating an objective function defining minimization of the economic cost of the active distribution network according to the following formula: min F c ＝F e +F g +F θ +F m 。
In order to achieve the second object, the present invention provides a power distribution network coordination optimization device considering load characteristics, which includes a memory for storing computer readable instructions; and a processor configured to execute the computer readable instructions, so that the power distribution network coordination optimization device executes the power distribution network coordination optimization method as described above.
To achieve the third object described above, the present invention provides a storage medium storing computer readable instructions that, when executed by a computer, cause the computer to perform the instructions of the power distribution network coordination optimization method as described above.
Therefore, according to the active power and reactive power optimization coordination method of the active power distribution network, which takes the minimum economic cost of the active power distribution network as an objective function, an active power and reactive power constraint model of the active power distribution network including load flow balance, SVC constraint and the like is established by constructing a linear ZIP model comprising the static voltage characteristic and time-varying characteristic of the load.
From the safety perspective, the method provided by the invention can well and dynamically regulate the active power and reactive power of the active power distribution network, so that the overall voltage of the active power distribution network is kept stable, the voltage value fluctuation of the sensitive load node is smaller, and the voltage value of the sensitive load node is closer to the standard value.
From the economical point of view, the method provided by the invention not only can reduce the high-sensitivity load loss cost caused by voltage fluctuation, but also can reduce the power consumption cost and the total scheduling cost of the whole system, and can bring objective economic benefit.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for coordinated optimization of a power distribution network that accounts for load characteristics of the present invention.
The invention is further described below with reference to the drawings and examples.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, when active power and reactive power coordination optimization is performed on an active power distribution network, step S1 is executed first, and a load linear ZIP model based on time-varying characteristics is established. The method for establishing the load linear ZIP model based on the time-varying characteristics specifically comprises the following steps: and constructing a static voltage characteristic model and a linearization load model of the load, and obtaining a load linear ZIP model containing the load time-varying characteristic based on the time-varying characteristic of the load.
And then, executing step S2, and establishing a linearization power flow model of the active power distribution network. The method for establishing the active power distribution network linearization power flow model specifically comprises the following steps: and establishing an objective function for minimizing the economic cost of the active power distribution network, including electricity purchasing cost, micro gas turbine cost, network loss cost and sensitive load fluctuation cost, and reasonably optimizing and calculating the cost of different parts.
And then, executing step S3, and establishing an active power and reactive power coordination optimization model of the active power distribution network. The method for establishing the active power and reactive power coordination optimization model of the active power distribution network specifically comprises the following steps: and (3) establishing an active and reactive power constraint model of the active power distribution network including load flow balance, micro gas turbine constraint, wind driven generator constraint and SVC constraint.
And then, executing step S4, and solving the established active power and reactive power coordination optimization model of the active power distribution network by using the GAMS system. Step S4 specifically includes step S41, inputting an active power and reactive power coordination optimization model of the active power distribution network in the GAMS system, defining variables and constants, and establishing equality and inequality constraint according to the active power and reactive power coordination optimization model of the active power distribution network; and S42, solving the active power and reactive power coordination optimization model of the active power distribution network by adopting a linear optimization solver.
In the step S42, if the calculation result converges in the solving process, an active power and reactive power coordination control instruction of the active power distribution network is output according to the solving result.
In the step S42, if an error occurs in the solving process or the operation result is not converged, the method returns to the step S41 to modify parameters, and an active power and reactive power coordination optimization model of the active power distribution network is re-established.
In the step S42, if the calculation result converges in the solving process, the operation result is returned to the MATLAB software, the relevant result is calculated and analyzed, and the result visualization chart processing is performed.
And then, executing a step S5, and scheduling the active power distribution network system according to the solving result of the step S4.
Further, the method further comprises the step of calculating and defining a load linear ZIP model based on the time-varying characteristic according to the following formula:
further, an objective function for defining an active distribution grid economic cost minimization is calculated according to the following formula:
Min F c ＝F e +F g +F θ +F m (7)
in practical application, in step S1, a load linear ZIP model based on time-varying characteristics is established, specifically: the traditional load model does not consider the time-varying characteristics of the load, and the accuracy and precision of the established load model are difficult to ensure.
For the load, the actual operating conditions are mostly related to the actual voltage of the connected bus, so the influence of voltage fluctuation on the node load should be considered in the scheduling process. The load models commonly used are ZI model, ZIP model, exponential model, etc., and the ZIP power model of this embodiment is expressed by the formula (1-2):
wherein in the formulas (1) and (2), P m,i And Q m,i Indicating the actual active and reactive power consumed by bus i,
and->
Rated active and reactive power for sensitive loads, v i The voltage of bus i is represented, and the rated voltage of the system is v o ＝1.0p.u，a P 、b P 、c P 、a Q 、b Q 、c Q Respectively representing the proportion of constant impedance, constant current and constant power load in the total load, and a P +b P +c P ＝a Q +b Q +c Q ＝1。
Since the square term of the voltage exists in the formulas (1) and (2) is considered, a nonlinear non-male model is built, and the solution becomes a non-deterministic programming problem. And in the power system, the voltage is very close to the per unit value of 1.0p.u, so the invention adopts Taylor expansion at v o Taylor first order expansion of the quadratic term of the voltage at point=1.0p.u, specifically as follows:
for a pair of
Further Taylor expansion to obtain v i 2 ＝2v i -1, v i 2 ＝2v i -1 back to equation (1-2), resulting in equation (3-4):
in comparison with equation (1-2), the real and reactive powers of the load in equation (3-4) are proportional to the power of the voltage only, and the magnitude of the voltage at that time is linear.
The load change of the power system has randomness, and the characteristic of the load change along with time is called the time-varying characteristic of the load. The power of the sensitive load is continuously changed along with the change of time, so the three components a, b and c are all the time-varying quantities.
Taking into account the time-varying characteristics of the load, the present invention sets a p,t ＝a Q,t 、b p,t ＝b Q,t 、c p,t ＝c Q,t Respectively representing the time-varying conditions of constant impedance, constant current, constant power and other parts in the sensitive load.
Based on the time-varying nature of the load, a linear ZIP model is proposed that takes into account the time-varying nature of the load, as shown in equations (5), (6):
in step S2, an active distribution grid economic cost including electricity purchasing cost, micro gas turbine cost, network loss cost, and sensitive load fluctuation cost is established and minimized, specifically:
in the embodiment, the economic cost is reasonably optimized based on the voltage type sensitive load. The economic cost mainly comprises the purchase electricity quantity cost of the distribution network, the generation cost of a distributed power supply, the unavoidable network loss cost and the sensitive load loss cost of the active distribution network, and the objective function is as shown in the formula (7):
Min F c ＝F e +F g +F θ +F m (7)
wherein F is c Is the overall scheduling cost of the active power distribution network, F e Is the electricity purchasing cost, F g Is the cost of the micro gas turbine, F θ Is the cost of network loss, F m Is the cost of sensitive load loss due to voltage fluctuations.
In this embodiment, for the electricity purchasing cost, in order to provide the user with enough electricity for producing and living, a certain amount of electricity needs to be purchased from the main power grid to meet the power distribution requirement, as shown in formula (8):
wherein: f (F) e Is the total electricity purchasing cost, P e,j,t And Q e,j,t Is the active and reactive power purchased from the power market of the main power grid in the power distribution network, c ep And c eq Is the price of electricity purchased per unit of active and reactive power.
For the cost of the gas turbine, the electricity generation cost of the micro gas turbine (micro gas turbines, MT) is related to the power it generates, as shown in equation (9).
Wherein Ω g For the collection of all micro gas turbines, C g Is the unit electricity price; p (P) g,t Active power of the busbar i is injected into the micro gas turbine in time t.
For network loss costs, as shown in equation (10):
wherein C is loss Is the unit price cost of electric energy loss, omega ij Is the system line set g ij,t Is the conductance between bus i and bus j, Δθ ij,r,t Is the value of the r-th angle between the two busbars.
For the fluctuation cost of the sensitive load, for the formula (1-2), voltage fluctuation is not desirable in order to secure the stability of the sensitive load. Since small fluctuations in voltage have a large influence on the load, and the losses due to these influences cause serious safety problems and great economic losses.
To obtain the variation of the load, introduce
And->
The two relaxation variables, the fluctuating cost function defining the sensitive load, are shown in equations (11-14):
in the formula (11), C m Is the unit price cost of sensitive load, omega m Is a collection of sensitive loads.
In step S3, an active and reactive power constraint model of the active power distribution network including load flow balance, micro gas turbine constraint, wind power constraint and SVC constraint is established, which specifically includes:
under the condition that the minimum cost objective function of the power distribution network is determined, stable and safe operation of the power distribution network is ensured, and reasonable constraint on power flow, power generation condition, load and the like of the power distribution network is required.
In this embodiment, for a radiation type active power distribution network, the flow constraint equation of the system is shown in formula (15-16):
wherein, omega line,j A group of lines connected with the bus j; omega shape w,j The wind turbine generator is connected with a bus j; omega shape g,j A group of micro gas turbines connected with a bus j; omega shape l,j Is a non-voltage sensitive load group connected with a bus j; omega shape m,j Is a voltage sensitive load group connected with a bus j; omega shape s,j Is a Static Var Compensator (SVC) connected to bus j; p (P) ij,t And Q ij,t Is the active/reactive power of the line at time tij. P (P) e,j,t And Q e,j,t Active power and reactive power of ADN are injected from a bus j into a main power grid at a time t; p (P) g,j,t And Q g,j,t Indicating that the micro gas turbine g outputs active/reactive power at time t; p (P) w,j,t And Q w,j,t Indicating that the fan w outputs active/reactive power at the time t; p (P) l,j,t And Q l,j,t Representing the active/reactive power demand of the non-voltage sensitive load l at time t; p (P) m,j,t And Q m,j,t The actual active/reactive power demand of the indicated voltage sensitive load m at time t; q (Q) s,t The output reactive power of the static var compensation s at time t is indicated.
In this embodiment, the reactive power output by the Static Var Compensation (SVC) at bus j is shown in the formula (17-18):
wherein P is ij,t 、Q ij,t Is the active and reactive power, theta, of the line between nodes i j ij,t Is the voltage phase angle difference between nodes i and j.
Due to the above-mentioned formula
Is nonlinear and requires piecewise fitting to be linear for calculation as shown in equations (19-26):
0≤θ ij,r,t ≤θ ij,max,t (21)
m ij,r ＝(2r-1)θ ij,r (22)
wherein, the liquid crystal display device comprises a liquid crystal display device,r is the value required to model the domain limit of the function as positive; m is m ij,r Is the slope of the R-th block angle between the two buses; variable(s)
And->
Non-negative auxiliary variable to obtain +.>
θ ij,max,t Is the maximum value of each block in the discretization process.
For the main grid injected power, the total power absorbed by the distribution network from the main grid is shown in formula (27):
wherein, the liquid crystal display device comprises a liquid crystal display device,
and->
Is the active and reactive maximum value of the power supplied by the main power grid.
For micro gas turbine output, as shown in equation (28):
(P g,t ) 2 +(Q g,t ) 2 ≤(S g,max ) 2 (28)
wherein P is g,t 、Q g,t 、S g,max Active, reactive and maximum apparent power of the micro gas turbine, respectively.
In this example, after linearizing equation (28) using the hexagonal relaxation method, the following constraints are obtained, yielding equations (29-31):
for wind generator output, wind generators typically convert wind energy into electrical energy through power electronics. The wind speed is related to the output of the wind driven generator, and the power output expression of the wind driven generator is shown as a formula (32):
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the rated power of the wind turbine generator; v w,ip 、v w,op 、/>
The fans are switched in, out and rated wind speed, respectively. a. b is a parameter related to the cut-in rated wind speed, and is a fixed constant: />
Because the fan needs to be connected with a power electronic device to be connected with a power grid, the inverter has a capacity S w,max Is limited by the reactive power flowing through the converter being Q w Equation (33) is obtained:
the fan of the invention operates at Q under variable power factor cos omega w,t As shown in equation (34):
in the formula (33-34), ω is the power factor angle, cos ω min And cos omega max Is the minimum and maximum of the power factor.
To facilitate scheduling computation, Q w,t Expressed as formula (35):
P w,t tan(arccosω min )≤Q w,t ≤P w,t tan(arccosω max ) (35)
for SVC constraints, in order to further guarantee the voltage quality of the distribution network, reasonable reactive power regulation of the system is required. The invention adopts a static reactive compensation device (static var compensation, SVC) to perform reactive regulation in an active power distribution network.
Reactive output Q of SVC at t moment s,t The range of (2) is shown in formula (36):
Q s,min ≤Q s,t ≤Q s,max (36)
wherein Q is s,min And Q s,max Respectively represent Q s,t Upper and lower limits of reactive power output at time t.
For transformer regulation, in order to regulate the voltage of the main grid connected to the distribution network, an on-load tap changer (OLTC) is connected to the system, as shown in the formula (37-38):
V i0,t ＝V i,t (T ij,1 β ij,1,t +T ij,2 β ij,2,t +…+T ij,H β ij,H,t ) (37)
wherein V is i,t And V j,t The voltages at nodes i and j, respectively; vi0 is auxiliary voltage, T ij For the transformation ratio of OLTC, assuming that OLTC has H taps, transformation ratio T ij ∈{T ij,1 ,T ij,2 ,…,T ij,H }. To represent the transformation ratio of the H tap, H binary variables are introduced at time t, i.e. beta ij,1,t ,β ij,2,t ,…,β ij,H,t 。
In actual operation, frequent operation of the tap of the transformer reduces the service life of the tap and increases the probability of failure of the switching device. The present invention sets the number of daily operations N T For 4, the constraint on the splice control is expressed as equation (39):
it can be seen that the present invention is highly susceptible to voltage fluctuations for voltage sensitive loads, resulting in safety issues and economic losses for the power system. The voltage sensitive load model taking time characteristics into consideration is provided by considering that load components of the voltage sensitive load change at different moments, and a linearized active and reactive coordination optimization model is established by taking minimum economic cost and minimum voltage fluctuation of an active power distribution network as targets.
A power distribution network coordination optimization device that accounts for load characteristics according to an embodiment of the present disclosure includes a memory and a processor. The components of the power distribution network coordination optimization device are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
The memory is for storing non-transitory computer readable instructions. In particular, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the power distribution network coordination and optimization device to perform desired functions. In one embodiment of the disclosure, the processor is configured to execute the computer readable instructions stored in the memory, so that the power distribution network coordination optimization device performs the power distribution network coordination optimization method described above. The power distribution network coordination optimization method is the same as the embodiment described in the power distribution network coordination optimization method, and a repetitive description thereof will be omitted herein.
A storage medium according to an embodiment of the present disclosure has computer-readable instructions stored thereon. When executed by a processor, perform a power distribution network coordination optimization method according to embodiments of the present disclosure as described above with reference to the above.
The basic principles of the present disclosure have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.
The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
Therefore, according to the active power and reactive power optimization coordination method of the active power distribution network, which takes the minimum economic cost of the active power distribution network as an objective function, an active power and reactive power constraint model of the active power distribution network including load flow balance, SVC constraint and the like is established by constructing a linear ZIP model comprising the static voltage characteristic and time-varying characteristic of the load.
From the safety perspective, the method provided by the invention can well and dynamically regulate the active power and reactive power of the active power distribution network, so that the overall voltage of the active power distribution network is kept stable, the voltage value fluctuation of the sensitive load node is smaller, and the voltage value of the sensitive load node is closer to the standard value.
From the economical point of view, the method provided by the invention not only can reduce the high-sensitivity load loss cost caused by voltage fluctuation, but also can reduce the power consumption cost and the total scheduling cost of the whole system, and can bring objective economic benefit.
It should be noted that the foregoing is only a preferred embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications made to the present invention by using the concept fall within the scope of the present invention.
Claims (8)
1. The coordination optimization method of the power distribution network considering the load characteristics is characterized by comprising the following steps of:
establishing a load linear ZIP model based on the time-varying characteristics, wherein a static voltage characteristic model and a linearization load model of the load are established, and the load linear ZIP model containing the time-varying characteristics of the load is obtained based on the time-varying characteristics of the load; specifically, a load linear ZIP model based on accounting for time-varying characteristics is defined according to the following formula:
establishing a linearization power flow model of an active power distribution network;
establishing an active power and reactive power coordination optimization model of the active power distribution network;
solving an established active power and reactive power coordination optimization model of the active power distribution network by using a GAMS system;
and dispatching the active power distribution network system according to the solving result.
2. The method for coordinated optimization of a power distribution network according to claim 1, wherein the establishing an active power distribution network linearization power flow model specifically comprises:
and establishing an objective function for minimizing the economic cost of the active power distribution network, including electricity purchasing cost, micro gas turbine cost, network loss cost and sensitive load fluctuation cost, and reasonably optimizing and calculating the cost of different parts.
3. The power distribution network coordination optimization method according to claim 1, wherein the establishing an active power distribution network active and reactive power coordination optimization model specifically comprises:
and (3) establishing an active and reactive power constraint model of the active power distribution network including load flow balance, micro gas turbine constraint, wind driven generator constraint and SVC constraint.
4. The coordination optimization method of a power distribution network according to claim 1, wherein the solving the established active power and reactive power coordination optimization model of the active power distribution network by using a GAMS system specifically comprises:
s41, inputting an active power and reactive power coordination optimization model of the active power distribution network in the GAMS system, defining variables and constants, and establishing equality and inequality constraint according to the active power and reactive power coordination optimization model of the active power distribution network;
and S42, solving the active power and reactive power coordination optimization model of the active power distribution network by adopting a linear optimization solver.
5. The power distribution network coordinated optimization method according to claim 4, wherein:
in the step S42, if an error occurs in the solving process or the operation result is not converged, returning to the step S41 to modify parameters, and reestablishing an active power and reactive power coordination optimization model of the active power distribution network;
in the step S42, if the calculation result converges in the solving process, the operation result is returned to MATLAB software, the analysis related result is calculated, and the result visualization chart processing is performed.
6. The power distribution network coordination optimization method according to claim 2, wherein:
further comprising means for calculating an objective function defining an active distribution network economic cost minimization according to the following formula:
Min F c ＝F e +F g +F θ +F m 。
7. the power distribution network coordination optimization device considering load characteristics comprises:
a memory for storing computer readable instructions; and
a processor for executing the computer readable instructions to cause the power distribution network coordination optimization device to perform the power distribution network coordination optimization method of any one of claims 1 to 6.
8. A storage medium storing computer readable instructions which, when executed by a computer, cause the computer to perform the instructions of the power distribution network coordinated optimization method of any one of claims 1 to 6.
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