CN111723980A - Power distribution network transformer substation capacity optimization method for large-scale load regulation - Google Patents
Power distribution network transformer substation capacity optimization method for large-scale load regulation Download PDFInfo
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Abstract
The invention discloses a method for optimizing the capacity of a power distribution network and a transformer substation for large-scale load regulation, which comprises the steps of collecting and acquiring relevant parameters of users and the transformer substation; constructing a load regulation compensation cost model and a transformer substation investment cost model; establishing a transformer substation capacity optimization model and enabling the transformer substation capacity optimization model to meet all constraint conditions; and solving and obtaining the minimum cost value of the transformer substation capacity and the corresponding decision variable at the moment. The invention has the beneficial effects that: the method is based on the integration of two parts of load compensation cost and transformer substation initial investment cost as an objective function, various constraint conditions are comprehensively considered to establish a transformer substation capacity optimization model, the balance of compensation of users and construction cost of the transformer substation is considered, user side resources are fully utilized, the transformer substation investment cost is effectively reduced, and the utilization rate of the transformer substation is improved.
Description
Technical Field
The invention relates to the technical field of power distribution network planning, in particular to a power distribution network substation capacity optimization method for large-scale load regulation.
Background
In recent years, the capacity of a transformer substation is determined by considering indexes such as capacity-load ratio, load rate and the like according to a load prediction result and the basic condition of the existing network in the traditional transformer substation capacity planning on the premise of meeting load increase and safe and reliable electric energy supply, and the maximum social and economic benefits are obtained by utilizing system construction investment to the maximum extent. However, with the development of the energy internet, the complexity and randomness of the system has increased greatly in recent years with the increase of flexible load ratio and the push of DSM. The orderly scheduling or optimized placement of flexible loads can achieve significant "peak clipping and valley filling" effects, and as one of the most common measures for DSM, the immediate result of Interruptible Load (IL) project implementation is to affect the value of the maximum load and reduce the load maximum. The electric consumers no longer passively accept the power supply, but participate in the power conditioning, and it is the electric consumers that provide the "negative wattage" to the power system on the demand side. The method can reduce the load predicted value of each planning year, thereby reducing the investment of a power generation side, reducing newly added electric power quantity required by load development and finally influencing a transformer substation planning scheme to a great extent.
The current redundancy planning idea completely does not consider the influence of an IL project on the load prediction precision, and the problems of poor economy and poor flexibility exist. Therefore, in order to maximize the existing resources in the planning, construction and operation of the power system or to meet the market requirement with the minimum market cost, so that the power grid planning is more economic and reasonable, the influence caused by IL needs to be considered in the substation capacity planning, and the capacity optimization is performed on the basis.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned conventional problems.
Therefore, the technical problem solved by the invention is as follows: the method for optimizing the capacity of the power distribution network and the transformer substation based on the large-scale load regulation can be used for building an optimization model based on the compensation of users and the balance of the construction cost of the transformer substation, fully utilizing resources on the user side and effectively reducing the investment cost of the transformer substation.
In order to solve the technical problems, the invention provides the following technical scheme: a method for optimizing the capacity of a power distribution network and a transformer substation for large-scale load regulation comprises the steps of collecting and acquiring relevant parameters of users and the transformer substation; constructing a load regulation compensation cost model and a transformer substation investment cost model; establishing a transformer substation capacity optimization model and enabling the transformer substation capacity optimization model to meet all constraint conditions; and solving and obtaining the minimum cost value of the transformer substation capacity and the corresponding decision variable at the moment.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the relevant parameters of the transformer substation comprise the capacity of interrupted load, unit compensation price, power failure willingness factor of interruptible load users and initial load values of nodes of the transformer substation at different moments.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the load regulation and control compensation cost model is constructed on the basis of a marginal cost pricing strategy, and is expressed as follows,
wherein N is the number of users, KItAs a user state vector, K Iit0 denotes that the load of the user i is not interrupted, KIit1 denotes the load of the interrupting user, PItCapacity vector for the interrupted load at time t, p1And ρ2For unit compensation of price,. mu.IiThe power failure willingness factor of the user with interruptible load.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the expression of the substation investment cost model is as follows,
wherein A isItThe initial load value of each node of the substation before interruption at the time t is represented by cos theta as a power factor, and β is represented by 1 × 106Meta/MVA.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the calculation formula of the substation capacity optimization model is as follows,
minC＝Ci+CIt
wherein minC is the minimum cost of the transformer substation capacity, CItCompensating costs for load regulation, CiThe investment cost of the transformer substation is saved.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the constraint conditions which should be met by the substation capacity optimization model comprise system power flow constraint, system power balance constraint, node voltage constraint, substation capacity constraint and interruptible load interruption capacity constraint.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the system power flow constraint includes a power flow constraint,
wherein, PmtAnd QmtNet active and reactive power, U, respectively injected into the substation node m at time tmtAnd UntVoltage amplitudes, G, of the node m and the node n of the substation at time t, respectivelymnAnd BmnRespectively the conductance and susceptance values, theta, of the corresponding branchesmnIs the power angle difference between node m and node n.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the system power balance constraints include that,
wherein the vector Pat＝[Pa1t,...,Pait,...,PaNt]The element is the load value of each node i at the time t after interruption, and N is the total number of the nodes.
The invention relates to a preferable scheme of a power distribution network substation capacity optimization method for large-scale load regulation, wherein the method comprises the following steps: the node voltage constraints, substation capacity constraints and interruptible load interruption capacity constraints further include,
Um,min≤Umt≤Um,max
0≤PIjt≤PIjma
wherein, Um,minAnd Um,maxRespectively the lower limit and the upper limit of the voltage amplitude of a node m in the transformer substation, S is the transformer substation capacity, PIjtFor the interruption load value, P, of user j at time tIjmaxThe upper limit value of the interruptible load for user j during time t.
The invention has the beneficial effects that: according to the method for optimizing the capacity of the power distribution network substation for large-scale load regulation, provided by the invention, the load compensation cost and the initial investment cost of the substation are integrated into a target function, various constraint conditions are comprehensively considered to establish a substation capacity optimization model, the balance of compensation of users and construction cost of the substation is considered, resources on the user side are fully utilized, the investment cost of the substation is effectively reduced, and the utilization rate of the substation is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
fig. 1 is an overall flow diagram of a method for optimizing the capacity of a distribution network substation for large-scale load regulation according to a first embodiment of the present invention;
FIG. 2 is a graph showing a one-day predicted load curve in the experiment according to the first embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to the schematic diagram of fig. 1, the schematic diagram is a flowchart of a method for optimizing the capacity of a distribution network substation for large-scale load regulation and control according to this embodiment, and specifically includes the following steps,
s1: collecting and acquiring relevant parameters of a user and a transformer substation;
specifically, the relevant parameters of the users include the number and the states of the users in the substation system, wherein the states of the users include two states of load interruption and load interruption of the users, and the relevant parameters of the substation include the capacity of interrupted loads at different moments, the unit compensation price, the power outage willingness factor of interruptible load users and the initial load values of nodes of the substation.
S2: constructing a load regulation compensation cost model and a transformer substation investment cost model;
the load regulation and control compensation cost refers to a cost generated by a power grid company giving a certain compensation according to the power loss of a user after a load reduction project is implemented, and the cost is related to a power outage willingness factor and an interruption amount of the user. The interruption amount is the electric quantity loss of the user, and the power failure willingness factor is used for measuring the loss of the interruption amount to the user. The load regulation and control compensation cost model in the embodiment is constructed based on the marginal cost pricing strategy, and the expression is as follows,
wherein N is the number of users, KItAs a user state vector, K Iit0 denotes that the load of the user i is not interrupted, KIit1 denotes the load of the interrupting user, PItCapacity vector for load interruption at time t and vector PIIt＝[PI1t,…,PIit,…,PINt]，ρ1And ρ2For unit compensation of price,. mu.IiThe power failure willingness factor of the user with interruptible load.
In the embodiment, the construction and maintenance cost and the low-voltage side line cost of the transformer substation are ignored when the transformer substation investment cost model is established, the expression of the obtained transformer substation investment cost model is as follows,
wherein, CiFor initial investment costs of the substation, AItThe initial load value of each node i of the transformer substation before interruption at the time t, N is the number of the nodes, cos theta is a power factor, β is the cost, and the power factor is 0.95, β is 1 × 106Meta/MVA
S3: establishing a transformer substation capacity optimization model and enabling the transformer substation capacity optimization model to meet all constraint conditions; wherein, the transformer substation capacity optimization model takes the minimum transformer substation capacity planning cost as a target and consists of two parts of interruptible load compensation cost and transformer substation initial investment cost, the calculation formula is as follows,
minC＝Ci+CIt
wherein minC is the minimum cost of the transformer substation capacity, CItCompensating costs for load regulation, CiThe investment cost of the transformer substation is saved. To make the transformer station capacityAnd the quantity planning cost reaches the minimum value, and the constraint conditions which should be met by the transformer substation capacity optimization model comprise system power flow constraint, system power balance constraint, node voltage constraint, transformer substation capacity constraint and interruptible load interruption capacity constraint.
S4: and solving and obtaining the minimum cost value of the transformer substation capacity and the corresponding decision variable at the moment.
Specifically, the solving means that the transformer substation capacity optimization model meets all the constraint conditions, and obtains a transformer substation capacity minimum cost value under the condition and a corresponding decision variable K under the conditionItAnd PItThe value is obtained.
Wherein the system power flow constraint comprises a power flow constraint,
wherein, PmtAnd QmtNet active and reactive power, U, respectively injected into the substation node m at time tmtAnd UntVoltage amplitudes, G, of the node m and the node n of the substation at time t, respectivelymnAnd BmnRespectively the conductance and susceptance values, theta, of the corresponding branchesmnIs the power angle difference between node m and node n.
The system power balance constraints include that,
wherein the vector Pat＝[Pa1t,...,Pait,...,PaNt]The element is the load value of each node i at the time t after interruption, and N is the total number of the nodes.
Node voltage constraints, substation capacity constraints and interruptible load interrupting capacity constraints also include,
Um,min≤Umt≤Um,max
0≤PIjt≤PIjmax
wherein, Um,minAnd Um,maxRespectively the lower limit and the upper limit of the voltage amplitude of a node m in the transformer substation, S is the transformer substation capacity, PIjtFor the interruption load value, P, of user j at time tIjmaxThe upper limit value of the interruptible load for user j during time t.
Scene one:
in order to verify the advantages of the method for optimizing the capacity of the power distribution network substation for large-scale load regulation and control in practical application, the following experiments are carried out for comparison and verification:
a110 kV transformer substation is selected, and a daily predicted load curve is shown in the following figure 2. The maximum hourly load for the day was 277MW, with a peak load duration of about 1 hour. Referring to the capacity setting method of the backup market, the peak load period interrupt capacity is up to 45 MW. Parameters such as the unit compensation price of the interruptible load, the relationship between the load interruption amount and the user outage intention factor are shown in table 1 below, assuming that the power factors of the loads of the nodes are all 0.95, the total number T of the studied periods is 24, and the unit time interval Δ T is 1 h.
Table 1: interruptible load user parameter table
And solving the established optimization method in MATLAB by adopting an improved particle swarm optimization algorithm. In the example, 3 single load interruption amount ranges are set, and since the interruption capacity upper limit is 45MW, more user response IL items can be selected when the single interruption amount range is small. The load interruption situation for different numbers of interruption users is shown in table 2 below, where the optimization result takes three digits after the decimal point,
table 2: implementation comparison table for different IL items
Referring to table 3 below, compensation costs corresponding to different load interruption amounts, a total planned cost of the substation considering IL, which is composed of two parts, i.e., the compensation cost and the required construction cost of the substation capacity considering the interruption capacity, and a percentage of the saved capacity investment cost to the total cost are listed in table 3.
Table 3: transformer substation capacity planning cost comparison table
As can be seen from the results of table 3, the total cost of the substation planning decreases as the amount of load interruption increases. After partial load is interrupted, the maximum load value is reduced, the required transformer substation capacity scale is reduced, the cost for compensating the power failure loss of a user is far less than that of a newly-built transformer substation, and therefore the economic benefit of transformer substation capacity planning considering load regulation is obvious.
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein. A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
As used in this application, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (9)
1. A method for optimizing the capacity of a power distribution network substation for large-scale load regulation is characterized by comprising the following steps of: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
collecting and acquiring relevant parameters of a user and a transformer substation;
constructing a load regulation compensation cost model and a transformer substation investment cost model;
establishing a transformer substation capacity optimization model and enabling the transformer substation capacity optimization model to meet all constraint conditions;
and solving and obtaining the minimum cost value of the transformer substation capacity and the corresponding decision variable at the moment.
2. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 1, wherein the method comprises the following steps: the relevant parameters of the transformer substation comprise the capacity of interrupted load, unit compensation price, power failure willingness factor of interruptible load users and initial load values of nodes of the transformer substation at different moments.
3. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 2, characterized by comprising the following steps: the load regulation and control compensation cost model is constructed on the basis of a marginal cost pricing strategy, and is expressed as follows,
wherein N is the number of users, KItAs a user state vector, KIit0 denotes that the load of the user i is not interrupted, KIit1 denotes the load of the interrupting user, PItCapacity vector for the interrupted load at time t, p1And ρ2For unit compensation of price,. mu.IiThe power failure willingness factor of the user with interruptible load.
4. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 2 or 3, wherein the method comprises the following steps: the expression of the substation investment cost model is as follows,
wherein A isItFor each substation before interruptionThe initial load value of the node at the time t, cos theta is a power factor, β is 1 × 106Meta/MVA.
5. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 4, wherein the method comprises the following steps: the calculation formula of the substation capacity optimization model is as follows,
minC＝Ci+CIt
wherein minC is the minimum cost of the transformer substation capacity, CItCompensating costs for load regulation, CiThe investment cost of the transformer substation is saved.
6. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 5, wherein the method comprises the following steps: the constraint conditions which should be met by the substation capacity optimization model comprise system power flow constraint, system power balance constraint, node voltage constraint, substation capacity constraint and interruptible load interruption capacity constraint.
7. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 5 or 6, wherein the method comprises the following steps: the system power flow constraint includes a power flow constraint,
wherein, PmtAnd QmtNet active and reactive power, U, respectively injected into the substation node m at time tmtAnd UntVoltage amplitudes, G, of the node m and the node n of the substation at time t, respectivelymnAnd BmnRespectively the conductance and susceptance values, theta, of the corresponding branchesmnIs the power angle difference between node m and node n.
8. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 7, wherein the method comprises the following steps: the system power balance constraints include that,
wherein the vector Pat＝[Pa1t,...,Pait,...,PaNt]The element is the load value of each node i at the time t after interruption, and N is the total number of the nodes.
9. The method for optimizing the capacity of the distribution network substation for large-scale load regulation and control according to claim 8, wherein the method comprises the following steps: the node voltage constraints, substation capacity constraints and interruptible load interruption capacity constraints further include,
Um,min≤Umt≤Um,max
0≤PIjt≤PIjm
wherein, Um,minAnd Um,maxRespectively the lower limit and the upper limit of the voltage amplitude of a node m in the transformer substation, S is the transformer substation capacity, PIjtFor the interruption load value, P, of user j at time tIjmaxThe upper limit value of the interruptible load for user j during time t.
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