CN111276965A - Electric energy market optimization method, system and equipment based on relaxation penalty factor - Google Patents
Electric energy market optimization method, system and equipment based on relaxation penalty factor Download PDFInfo
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Abstract
The invention discloses an electric energy market optimization method, system and equipment based on relaxation penalty factors, wherein the method comprises the following steps: establishing a transfer factor matrix; setting a relaxation penalty factor M, constructing a market clearing model, and solving the market clearing model to obtain the flow relaxation amount of the line; modifying the market clearing model according to the flow relaxation amount of the line to obtain a modified relaxation penalty factor M' and construct a market pricing model; solving the market pricing model to obtain the shadow price of the power market; and optimizing the electric energy market based on the transfer matrix factor matrix and the shadow price. The method fully considers the influence characteristics of the relaxation penalty factors on the market clearing result, improves the current market clearing model and market pricing model based on the relaxation penalty factors, and ensures the rationality of the node electricity price, so that a more reasonable electric energy market clearing result is obtained, and the economy of power grid operation is improved.
Description
Technical Field
The invention relates to the technical field of electricity price calculation, in particular to an electric energy market optimization method, system and device based on relaxation penalty factors.
Background
The power industry system is undergoing a deep revolution, breaking monopoly and introducing competition, and establishing a unified, open, competitive and ordered power market, which becomes a development trend. The spot market is an important link of an electric power market system, plays a fundamental supporting role in the opening, competition and orderly operation of the electric power market, and is also the key point for coordinating market transaction and system safety. The spot market construction generally comprises a part or all of 3 parts of a day-ahead market, a day-in market and a real-time market, wherein the 3 markets respectively have different function positioning, and the three parts are mutually cooperated and orderly coordinated to form a complete spot market system.
The electric energy market clearing and pricing model is the core of the spot market. The traditional clearing model aims at minimizing the operation cost of a generator set, and comprehensively considers load balance constraint, unit climbing and upper and lower output limit constraint, line and section flow constraint and the like, wherein the flow constraint is usually treated as hard constraint, and when the optimization problem is not converged due to the fact that the flow is out of limit, a dispatcher usually ensures that the line and section flow is within an allowable range by cutting load. In actual grid operation, transmission equipment is usually allowed to operate within a certain proportion range in a short-time out-of-limit mode, namely, the power flow constraint can be physically treated as a soft constraint.
A clearing model based on the soft constraint of power flow relaxation is established in the spot market operation rule of Guangdong delivery, and the elastic processing of the power flow constraint is realized by introducing a relaxation variable into the power flow constraint and adding corresponding relaxation cost into an objective function. However, the current clearing model does not specify a setting method of a relaxation penalty factor in the objective function, the line load flow is severe due to the excessively low setting of the relaxation penalty factor, the safe and stable operation of the system is not facilitated, and the market clearing price is excessively high due to the excessively high setting of the relaxation penalty factor. Therefore, a reasonable and effective solution is not yet available for how to set the relaxation penalty factor in the electric energy market clearing and pricing model.
In summary, in the prior art, in the electric energy market clearing and pricing model, the setting scheme of the relaxation penalty factor is unclear, so that the technical problem that the electric energy market cannot be optimized exists.
Disclosure of Invention
The invention provides an electric energy market optimization method, system and equipment based on relaxation penalty factors, and solves the technical problem that in the prior art, the electric energy market cannot be optimized due to the fact that a setting scheme of the relaxation penalty factors is not clear in an electric energy market clearing and pricing model.
The invention provides an electric energy market optimization method based on relaxation penalty factors, which comprises the following steps:
acquiring parameters of the existing power market, and establishing a transfer factor matrix;
setting a relaxation penalty factor M, constructing a market clearing model with the minimum electric cost and the minimum line power flow relaxation cost as a target on the basis of the relaxation penalty factor M, and solving the market clearing model to obtain the power flow relaxation amount of the line;
modifying the market clearing model according to the flow relaxation amount of the line to obtain a modified relaxation penalty factor M ', and obtaining a market pricing model based on the modified relaxation penalty factor M';
solving the market pricing model to obtain the shadow price of the power market;
and calculating the marginal electricity price of each node in the power grid based on the transfer matrix factor matrix and the shadow price.
Preferably, the parameters of the power market comprise output data of the A-type unit, western power input data and quoted price data of the B-type unit.
Preferably, the value of the relaxation penalty factor M is set to a value which exceeds the price quoted by the B-type unit by more than 2 orders of magnitude.
Preferably, the transfer factor matrix includes topology information of the power network, each row in the transfer factor matrix represents one transmission line of the power network, and each column represents one node in each transmission line.
Preferably, the constraint conditions of the market clearing model comprise active balance constraint, line power flow relaxation constraint, class B unit output upper limit constraint, class B unit output upper and lower limit constraint, unit climbing rate constraint and relaxation amount lower limit constraint.
Preferably, the solution obtains a power flow relaxation amount of the line, if the power flow relaxation amount is 0, it indicates that the market clearing model has a feasible solution under the original constraint of the power flow relaxation of the line, and if the relaxation amount is not 0, the numerical value represents a minimum threshold value of the power flow of the line on the premise of ensuring that the market clearing model has a feasible solution.
Preferably, the market clearing model is corrected according to the flow relaxation amount of the line to obtain a corrected relaxation penalty factor M ', and the price of the electric power market clearing is adjusted by setting M' to be more than or equal to 0 and less than or equal to M; when M' is 0, the market pricing model does not consider the relaxation cost item any more, the node power price is completely decoupled from the relaxation cost, and only contains an energy component and a blocking component; when M' >0, the node electricity price in the market pricing model comprises an energy component, a blocking component and a relaxation component, and the larger M is, the larger the corresponding relaxation component is; when M' is equal to M, the unit relaxation cost in the market pricing model and the market clearing model is equal, and the node electricity price is higher than the unit electricity generation cost of the unit.
Preferably, the shadow prices of the electricity market comprise shadow prices of load balancing constraints, shadow prices of line forward power flow constraints and shadow prices of line reverse power flow constraints.
An electric energy market optimization system based on relaxation penalty factors comprises a transfer factor matrix module, a market clearing model module, a market pricing model module, a shadow price solving module and an electric energy market optimization module;
the transfer factor matrix module is used for acquiring parameters of the existing electric power market and establishing a transfer factor matrix;
the market clearing model module is used for setting a relaxation penalty factor M, constructing a market clearing model with the minimum electric cost and the minimum line power flow relaxation cost as a target on the basis of the relaxation penalty factor M, and solving the market clearing model to obtain the power flow relaxation amount of the line;
the market pricing model module is used for correcting the market clearing model according to the flow relaxation amount of the line to obtain a corrected relaxation penalty factor M ', and obtaining the market pricing model based on the corrected relaxation penalty factor M';
the shadow price solving module is used for solving the market pricing model to obtain the shadow price of the electric power market;
the electric energy market optimization module is used for optimizing the electric energy market based on the transfer matrix factor matrix and the shadow price.
An electric energy market optimization device based on relaxation penalty factors comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute a relaxation penalty factor based electric energy market optimization method as described above according to instructions in the program code.
According to the technical scheme, the embodiment of the invention has the following advantages:
the embodiment of the invention fully considers the influence characteristics of the relaxation penalty factors on the market clearing result, and improves the current market clearing model and the market pricing model based on the relaxation penalty factors, thereby optimizing the electric energy market, ensuring the minimum out-of-limit tidal current of the tide line, obtaining more reasonable electric energy market clearing result and being beneficial to improving the economical efficiency of the power grid operation.
Another embodiment of the invention has the following further advantages:
according to the embodiment of the invention, through the improved market clearing model, the minimum value of the line power flow out-of-limit under the condition that the clearing problem has a feasible solution can be obtained, the line power flow soft constraint is corrected into the hard constraint, and the electric power system can be ensured to operate safely and stably as far as possible.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a method flowchart of a method, a system, and an apparatus for electric energy market optimization based on slack penalty factors according to an embodiment of the present invention.
Fig. 2 is a system structure diagram of an electric energy market optimization method, system and apparatus based on slack penalty factors according to an embodiment of the present invention.
Fig. 3 is an apparatus framework diagram of a method, a system, and an apparatus for electric energy market optimization based on slack penalty factors according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides an electric energy market optimization method, system and device based on relaxation penalty factors, and solves the technical problem that in the prior art, the electric energy market clearing and pricing model has unreasonable electricity price due to the fact that the setting scheme of the relaxation penalty factors is unclear.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a method, a system and an apparatus for electric energy market optimization based on slack penalty factors according to an embodiment of the present invention.
In the day-ahead market stage, a scheduling transaction mechanism firstly issues boundary conditions, a power generation enterprise declares power generation capacity and quotation, and the scheduling transaction mechanism gives clearance to the day-ahead electric energy market according to quotation information of a power generation company and by combining real-time and future operation states of a power grid and comprehensively considering load balance constraints, line tide constraints, unit operation constraints and the like.
As shown in fig. 1, the method for optimizing the electric energy market based on the slack penalty factor provided by the invention comprises the following steps:
acquiring parameters of the existing power market, and establishing a transfer factor matrix according to the parameters of the existing power market;
setting a relaxation penalty factor M, constructing a market clearing model with the minimum electric cost and the minimum line power flow relaxation cost as a target on the basis of the relaxation penalty factor M, and solving the market clearing model to obtain the power flow relaxation amount of the line;
modifying the market clearing model according to the flow relaxation amount of the line to obtain a modified relaxation penalty factor M ', and obtaining a market pricing model based on the modified relaxation penalty factor M';
solving the market pricing model to obtain the optimal output of the unit under the constraint of no tidal current relaxation; because the market pricing model is not an integer programming problem any more but a basic linear programming, the shadow price of the power market can be obtained in the solving process;
and optimizing the electric energy market based on the transfer matrix factor matrix and the shadow price, thereby calculating the marginal electricity price of each node in the power grid.
As a preferred embodiment, the parameters of the electricity market include class a unit output data, western electricity input data, and class B unit quote data.
As a preferred embodiment, the value of the slack penalty factor M is set to a value that exceeds the B-class unit price by more than 2 orders of magnitude.
As a preferred embodiment, the transfer factor matrix includes topology information of the power network, each row in the transfer factor matrix represents one transmission line of the power network, each column represents one node in each transmission line, and an element in the transfer factor matrix represents a power transfer distribution factor of a node to a line;
as a preferred embodiment, the constraint conditions of the market clearing model include active balance constraint, line power flow relaxation constraint, class B unit output upper and lower limit constraint, unit climbing rate constraint, and relaxation lower limit constraint;
the market clearing optimization model is as follows:
an objective function:
the constraint conditions are as follows:
the system comprises a power balance constraint, a line power flow relaxation constraint, a B-type unit output upper limit constraint, a B-type unit output lower limit constraint, and a unit climbing rate constraint, wherein the formula (2) is an active power balance constraint, the formula (3) is a line power flow relaxation constraint, the formula (4) is a B-type unit output upper limit and lower limit constraint, and the formula (5) is a unit; equation (6) is a lower bound on the amount of relaxation.
NB is the total number of B-type units participating in bidding in the system; NA is the total number of the A type units; NT is the sum of the number of west power feeding nodes; ND is the total number of the load nodes; NL is the total number of lines; t is the total number of time periods contained in one clearing period; ci,t，
And
respectively representing the electric energy running cost, the starting cost and the no-load cost of the ith B-type unit in the time period t, αi,tThe starting and stopping states of the ith B-type unit in the time period t are represented, and the starting and stopping states belong to 0-1 integer variables; pi,tAnd Pj,tRespectively outputting the output of the ith B type unit and the jth A type unit in a time period t; t isk,tRepresenting the injection power of the kth out-of-zone link in a time period t; dm,tRepresenting the active consumption of the mth load node in the time period t;
respectively representing the forward and reverse power flow relaxation amount of the ith line in a time period t; m is a coefficient for measuring the relaxation cost, namely a relaxation penalty factor; gl-iRepresenting the output power transfer distribution factor of the node i to the line l; pl maxRepresenting the power flow transmission limit value of the first line;
respectively representing the minimum active output and the maximum active output of the ith B-type unit in a time period t; RPi maxAnd the maximum climbing speed of the ith class B unit is shown.
Solving the optimization problem by adopting a mixed integer programming method, and calculating the active power output of the unit in each time period and the power flow relaxation amount of the line
As a preferred embodiment, the power flow relaxation amount of the line is obtained by solving, and if the power flow relaxation amount is 0, it indicates that the market clearance model has a feasible solution under the existing line power flow relaxation constraint, and if the relaxation amount is not 0, the numerical value indicates the minimum threshold value of the line power flow on the premise of ensuring that the market clearance model has a feasible solution.
As a preferred embodiment, the market clearing model is modified according to the power flow relaxation amount of the line, and the market pricing model is as follows:
an objective function:
the constraint conditions are as follows:
the active power balance constraint is represented by a formula (8), the line power flow relaxation constraint is represented by a formula (9), the output upper and lower limits of the B-type unit are represented by a formula (10), and the climbing rate constraint of the unit is represented by a formula (11); the formula (12) represents the upper and lower limit correction quantity of the line tide constraint, the numerical value is k times of the minimum threshold quantity in the clearing model, and the influence of the blocking component on the clearing price of the market can be further relieved by relaxing the threshold quantity; equations (13) and (14) represent the actual line power flow and the allowable value Pl maxThe more limited the forward and reverse directions of the phase.
Obtaining a corrected relaxation penalty factor M ', setting M ' to be more than or equal to 0 and less than or equal to M ' and adjusting the clearing price of the electric power market to a reasonable level; when M' is 0, the market pricing model does not consider the relaxation cost item any more, the node power price is completely decoupled from the relaxation cost, and only contains an energy component and a blocking component; when M' >0, the node electricity price in the market pricing model comprises an energy component, a blocking component and a relaxation component, and the larger M is, the larger the corresponding relaxation component is; when M' is equal to M, the unit relaxation cost in the market pricing model and the market clearing model is equal, and the node electricity price is higher than the unit electricity generation cost of the unit.
As a preferred embodiment, the shadow price of the electricity market comprises a shadow price of a load balancing constraint λtShadow price of line forward flow constraint
Shadow price constrained by line reverse current
The calculation formula of the node marginal electricity price is as follows:
wherein, LMPk,tThe node margin electricity prices.
As shown in fig. 2, the electric energy market optimization system based on the slack penalty factor includes a transfer factor matrix module 201, a market clearing model module 202, a market pricing model module 203, a shadow price solving module 204 and an electric energy market optimization module 205;
the transfer factor matrix module 201 is configured to obtain parameters of an existing power market and establish a transfer factor matrix;
the market clearing model module 202 is configured to set a relaxation penalty factor M, construct a market clearing model with the minimum electricity cost and line power flow relaxation cost as a target based on the relaxation penalty factor M, and solve the market clearing model to obtain a line power flow relaxation amount;
the market pricing model module 203 is used for correcting the market clearing model according to the flow relaxation amount of the line to obtain a corrected relaxation penalty factor M ', and obtaining a market pricing model based on the corrected relaxation penalty factor M';
the shadow price solving module 204 is used for solving the market pricing model to obtain the shadow price of the electric power market,
the electric energy market optimization module 205 optimizes the electric energy market based on the transfer matrix factor matrix and the shadow price.
As shown in fig. 3, an electric energy market optimization device 30 based on relaxation penalty factors, the device comprises a processor 300 and a memory 301;
the memory 301 is used for storing a program code 302 and transmitting the program code 302 to the processor;
the processor 300 is configured to execute the steps of one of the above-described relaxation penalty factor-based electric energy market optimization method embodiments according to the instructions in the program code 302.
Illustratively, the computer program 302 may be partitioned into one or more modules/units that are stored in the memory 301 and executed by the processor 300 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 302 in the terminal device 30.
The terminal device 30 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 300, a memory 301. Those skilled in the art will appreciate that fig. 3 is merely an example of a terminal device 30 and does not constitute a limitation of terminal device 30 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal device may also include input-output devices, network access devices, buses, etc.
The Processor 300 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 301 may be an internal storage unit of the terminal device 30, such as a hard disk or a memory of the terminal device 30. The memory 301 may also be an external storage device of the terminal device 30, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 30. Further, the memory 301 may also include both an internal storage unit and an external storage device of the terminal device 30. The memory 301 is used for storing the computer program and other programs and data required by the terminal device. The memory 301 may also be used to temporarily store data that has been output or is to be output.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A relaxation penalty factor-based electric energy market optimization method is characterized in that parameters of an existing electric power market are obtained in advance, a transfer factor matrix is established, and the method comprises the following steps:
setting a relaxation penalty factor M, constructing a market clearing model with the minimum electric cost and the minimum line power flow relaxation cost as a target on the basis of the relaxation penalty factor M, and solving the market clearing model to obtain the power flow relaxation amount of the line;
modifying the market clearing model according to the flow relaxation amount of the line to obtain a modified relaxation penalty factor M ', and obtaining a market pricing model based on the modified relaxation penalty factor M';
solving the market pricing model to obtain the shadow price of the power market;
and optimizing the electric energy market based on the transfer matrix factor matrix and the shadow price.
2. The method according to claim 1, wherein the parameters of the electric power market comprise class a unit output data, west electric input data and class B unit quote data.
3. The electric energy market optimization method based on the relaxation penalty factor according to claim 2, wherein the value of the relaxation penalty factor M is set to a value more than 2 orders of magnitude higher than the price quoted by the B-type unit.
4. The method according to claim 3, wherein the transition factor matrix comprises topology information of the power network, each row of the transition factor matrix represents a transmission line of the power network, and each column represents a node of each transmission line.
5. The electric energy market optimization method based on the relaxation penalty factor according to claim 4, wherein the constraint conditions of the market clearing model comprise active power balance constraint, line power flow relaxation constraint, class B set output upper limit constraint, class B set output upper and lower limit constraint, set ramp rate constraint and relaxation amount lower limit constraint.
6. The method for optimizing the electric energy market based on the slack penalty factor according to claim 5, wherein the solution obtains the power flow slack of the line, if the power flow slack is 0, it indicates that the market clearing model has a feasible solution under the original constraint of power flow slack of the line, and if the slack is not 0, the value represents the minimum threshold value of the power flow of the line on the premise of ensuring that the market clearing model has a feasible solution.
7. The electric energy market optimization method based on the relaxation penalty factors is characterized in that the market clearing model is modified according to the tidal current relaxation amount of the line to obtain a modified relaxation penalty factor M ', and the electric power market clearing price is adjusted by setting M ' to be more than or equal to 0 and less than or equal to M '; when M' is 0, the market pricing model does not consider the relaxation cost item any more, the node power price is completely decoupled from the relaxation cost, and only contains an energy component and a blocking component; when M' >0, the node electricity price in the market pricing model comprises an energy component, a blocking component and a relaxation component, and the larger M is, the larger the corresponding relaxation component is; when M' is equal to M, the unit relaxation cost in the market pricing model and the market clearing model is equal, and the node electricity price is higher than the unit electricity generation cost of the unit.
8. The electrical energy market optimization method based on slack penalty factors according to claim 7, wherein the shadow prices of the electrical power market comprise shadow prices of load balancing constraints, shadow prices of line forward power flow constraints and shadow prices of line reverse power flow constraints.
9. An electric energy market optimization system based on relaxation penalty factors is characterized by comprising a transfer factor matrix module, a market clearing model module, a market pricing model module, a shadow price solving module and an electric energy market optimization module;
the transfer factor matrix module is used for acquiring parameters of the existing electric power market and establishing a transfer factor matrix;
the market clearing model module is used for setting a relaxation penalty factor M, constructing a market clearing model with the minimum electric cost and the minimum line power flow relaxation cost as a target on the basis of the relaxation penalty factor M, and solving the market clearing model to obtain the power flow relaxation amount of the line;
the market pricing model module is used for correcting the market clearing model according to the flow relaxation amount of the line to obtain a corrected relaxation penalty factor M ', and obtaining the market pricing model based on the corrected relaxation penalty factor M';
the shadow price solving module is used for solving the market pricing model to obtain the shadow price of the electric power market;
the electric energy market optimization module is used for optimizing the electric energy market based on the transfer matrix factor matrix and the shadow price.
10. An electric energy market optimization device based on relaxation penalty factors is characterized by comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute a relaxation penalty factor based electric energy market optimization method according to any one of claims 1 to 8 according to instructions in the program code.
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