Day-ahead power generation plan generation system, electronic equipment and storage medium

Abstract

The invention discloses a day-ahead power generation plan generation system, electronic equipment and a storage medium, and the system comprises a data obtaining module which is used for obtaining basic data; the start-stop coefficient construction module is used for obtaining a unit start-stop comprehensive coefficient according to the basic data; the start-up mode determination module is used for constructing a unit combination model based on the unit start-stop comprehensive coefficient, solving the unit combination model and determining a start-up mode; the power generation coefficient construction module is used for obtaining a unit power generation comprehensive coefficient according to the basic data; and the power generation plan generation module is used for constructing an economic dispatching model based on the unit power generation comprehensive coefficient, solving the economic dispatching model and determining a day-ahead power generation plan. The method can effectively connect the electric power spot market and the traditional plan mode operation, solves the problem of frequent start and stop of the unit possibly occurring in the day-ahead power generation plan generation mode switching, improves the execution efficiency, and can be widely applied to the technical field of electric power dispatching.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of power dispatching, in particular to a day-ahead generation plan generation system, an electronic device and a storage medium. BACKGROUND

[0002] In order to meet the construction requirements of rule optimization and mechanism adjustment, the power grids in each province and region in the construction period will not regularly carry out the trial operation of the electricity spot market, thereby causing the connection problem of the electricity spot market and the traditional plan. The day-ahead generation plan generation overall process under the electricity spot market and the traditional plan mode is similar, but due to the different types of basic data, the specific implementation process is not consistent, and the problem of frequent start and stop of units may occur; meanwhile, the power grids in each province and region in the construction period are in the switching process of the electricity spot market and the traditional plan mode, thereby causing the day-ahead generation plan generation business to run not smoothly and the execution efficiency to be low. SUMMARY

[0003] In order to solve the above technical problems, the purpose of the application is to provide a day-ahead generation plan generation system, an electronic device and a storage medium, which can effectively compatible the electricity spot market and the traditional plan mode, and improve the execution efficiency of the unit.

[0004] In order to achieve the above purpose, one aspect of the embodiment of the application provides a day-ahead generation plan generation system, which comprises:

[0005] A data acquisition module is configured to acquire basic data.

[0006] A start-stop coefficient construction module is configured to obtain a unit start-stop comprehensive coefficient according to the basic data.

[0007] A unit start mode determination module is configured to construct a unit combination model based on the unit start-stop comprehensive coefficient, solve the unit combination model, and determine a start mode.

[0008] A generation coefficient construction module is configured to obtain a unit generation comprehensive coefficient according to the basic data.

[0009] A generation plan generation module is configured to construct an economic dispatching model based on the unit generation comprehensive coefficient, solve the economic dispatching model, and determine a day-ahead generation plan.

[0010] In some embodiments, the basic data in the data acquisition module comprises power generation enterprise market member data, non-market member power generation prediction data, power consumption load prediction data and power grid network frame data.

[0011] In some embodiments, the start-stop coefficient construction module comprises:

[0012] a first coefficient obtaining module, configured to calculate a unit value of a market transaction bidding of a market member of a power generation enterprise and a highest pricing of a market transaction place, to obtain a market transaction bidding coefficient;

[0013] a second coefficient obtaining module, configured to calculate a unit value of a power generation capacity of the market member of the power generation enterprise after a start-stop adjustment of a unit group and a decomposition value of a medium and long term power plan, to obtain a power completion coefficient;

[0014] a coefficient setting module, configured to set an expected transaction cost adjustment coefficient;

[0015] a third coefficient obtaining module, configured to obtain the unit group start-stop comprehensive coefficient according to the market transaction bidding coefficient, the power completion coefficient and the expected transaction cost adjustment coefficient.

[0016] In some embodiments, the start mode determining module comprises:

[0017] a first optimization target determining module, configured to determine a first optimization target, the first optimization target being to minimize the unit group start-stop comprehensive coefficient;

[0018] a first constraint condition determining module, configured to determine a first constraint condition according to the basic data, the first constraint condition comprising a power and power balance constraint, a network transmission capability constraint, a power completion capability constraint, a power generation capability constraint and a ramping capability constraint;

[0019] a unit group combination model constructing module, configured to construct the unit group combination model based on the unit group start-stop comprehensive coefficient according to the first optimization target and the first constraint condition;

[0020] a unit group combination model solving module, configured to solve the unit group combination model, and determine a start mode according to a solving result.

[0021] In some embodiments, the unit group combination model solving module comprises:

[0022] a first model adjusting and solving module, configured to adjust an expected transaction cost adjustment coefficient in the unit group start-stop comprehensive coefficient, to solve the unit group combination model based on the adjusted unit group start-stop comprehensive coefficient, to obtain a first solving result;

[0023] a first start mode determining module, configured to determine the start mode as a unit group combination scheme under a power spot market when the first solving result is 1;

[0024] a second start mode determining module, configured to determine the start mode as a unit group combination scheme under a traditional plan mode when the first solving result is 0.

[0025] In some embodiments, the power generation coefficient construction module comprises:

[0026] a fourth coefficient obtaining module configured to obtain a transaction cost coefficient;

[0027] a fifth coefficient obtaining module configured to obtain an electricity quantity plan deviation rate of a power generation enterprise market member, and obtain an electricity quantity completion coefficient according to the electricity quantity plan deviation rate;

[0028] a weight setting module configured to set a unit power generation coefficient weight;

[0029] a sixth coefficient obtaining module configured to obtain the unit power generation comprehensive coefficient according to the transaction cost coefficient, the electricity quantity completion coefficient, and the unit power generation coefficient weight.

[0030] In some embodiments, the power generation plan generation module comprises:

[0031] a second optimization objective determining module configured to determine a second optimization objective, the second optimization objective being to minimize the unit power generation comprehensive coefficient;

[0032] a second constraint condition determining module configured to determine a second constraint condition according to the basic data, the second constraint condition comprising a power and electricity quantity balance constraint, a network transmission capability constraint, a power generation capability constraint, and a ramping capability constraint;

[0033] an economic dispatch model construction module configured to construct the economic dispatch model based on the unit power generation comprehensive coefficient according to the second optimization objective and the second constraint condition;

[0034] an economic dispatch model solving module configured to solve the economic dispatch model, and determine the day-ahead power generation plan according to a solving result.

[0035] In some embodiments, the economic dispatch model solving module comprises:

[0036] a second model adjusting and solving module configured to adjust a unit power generation coefficient weight in the unit power generation comprehensive coefficient, solve the economic dispatch model based on the adjusted unit power generation comprehensive coefficient, and obtain a second solving result;

[0037] a first power generation plan determining module configured to, when the second solving result is 1, determine the day-ahead power generation plan as an economic dispatch scheme under a power spot market;

[0038] a second power generation plan determining module configured to, when the second solving result is 0, determine the day-ahead power generation plan as an economic dispatch scheme under a traditional plan mode.

[0039] To achieve the above object, another aspect of the embodiment of the present application provides an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, and the program is executed by the processor to realize the day-ahead generation plan generation system as described above.

[0040] To achieve the above object, another aspect of the embodiment of the present application provides a storage medium, which is a computer-readable storage medium for computer-readable storage, and the storage medium stores one or more programs executable by one or more processors to realize the day-ahead generation plan generation system as described above.

[0041] The day-ahead generation plan generation system, the electronic device and the storage medium have the following beneficial effects: the day-ahead generation plan generation system, the electronic device and the storage medium comprise a data acquisition module, a start-stop coefficient construction module, a start mode determination module, a generation coefficient construction module and a generation plan generation module. On one hand, a unit combination model based on a unit start-stop comprehensive coefficient is constructed in the module, and according to a solving result of the unit combination model, a selected start mode is determined, which can solve the problem of frequent start-stop of units that may occur in the mode switching of the day-ahead generation plan generation; on the other hand, an economic dispatching model based on the unit generation comprehensive coefficient is constructed in the module, and according to a solving result of the economic dispatching model, a day-ahead generation plan is generated, which can obtain a generation plan compatible with the power spot market and the traditional planning mode, effectively link the power spot market and the traditional planning mode operation, and improve the execution efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following introduces the drawings needed to be used in the embodiments of the present application, and it should be understood that the drawings introduced in the following only for the convenience of clearly describing some embodiments in the technical solutions of the present application, and for those skilled in the art, without creative labor, other drawings can also be obtained from these drawings.

[0043] Figure 1 A structure schematic diagram of a day-ahead generation plan generation system provided by the embodiment of the present application is shown in the figure.

[0044] Figure 2 A hardware structure schematic diagram of an electronic device provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0045] For the purpose, technical solutions and advantages of the present application to be more clearly understood, the present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific examples described herein are intended to explain the present application only and are not intended to limit the present application. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with embodiments of the present application. They are merely examples of apparatuses and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0046] It can be understood that the terms "first", "second" and the like used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "when" or "in response to determining".

[0047] The terms "at least one", "multiple", "each", "any" and the like used in the present application include one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0048] To meet the requirements of rule optimization, mechanism adjustment and other construction requirements, the power grids in each province and region in the construction period will not be carried out power spot market trial operation from time to time, thereby generating the connection problem between power spot and traditional planning. The overall process of day-ahead generation plan generation under power spot market and traditional planning mode is similar, but due to the different types of basic data, the specific implementation process is not consistent, which may cause frequent start-stop of units; At the same time, the power grids in each province and region in the construction period are in the switching process between power spot market and traditional planning mode, which leads to poor operation of day-ahead generation plan generation business and low execution efficiency.

[0049] To this end, the embodiment of the present application provides a day-ahead generation plan generation system, comprising a data acquisition module, a start-stop coefficient construction module, a start mode determination module, a generation coefficient construction module and a generation plan generation module. On the one hand, a unit combination model based on a unit start-stop comprehensive coefficient is constructed in the module, and according to the solving result of the unit combination model, the selected start mode is determined, which can solve the problem of frequent start-stop of units that may occur in the mode switching of day-ahead generation plan generation; on the other hand, an economic dispatching model based on a unit generation comprehensive coefficient is constructed in the module, and according to the solving result of the economic dispatching model, a day-ahead generation plan is generated, which can obtain a generation plan compatible with the power spot market and the traditional planning mode, effectively link the power spot market and the traditional planning mode operation, and improve the execution efficiency.

[0050] Reference Figure 1 , Figure 1 The structure schematic diagram of the day-ahead generation plan generation system provided by the embodiment of the present application, the embodiment of the present application provides a day-ahead generation plan generation system, the system comprises:

[0051] The data acquisition module is used for acquiring basic data;

[0052] The start-stop coefficient construction module is used for obtaining a unit start-stop comprehensive coefficient according to the basic data;

[0053] The start mode determination module is used for constructing a unit combination model based on the unit start-stop comprehensive coefficient, solving the unit combination model, and determining a start mode;

[0054] The generation coefficient construction module is used for obtaining a unit generation comprehensive coefficient according to the basic data;

[0055] The generation plan generation module is used for constructing an economic dispatching model based on the unit generation comprehensive coefficient, solving the economic dispatching model, and determining a day-ahead generation plan.

[0056] Further, as an optional implementation, the basic data in the data acquisition module comprises power generation enterprise market member data, non-market member power generation prediction data, power consumption load prediction data and power grid network data.

[0057] Specifically, the basic data and its sources comprise:

[0058] (1) the power generation enterprise market member related data, comprising a medium and long term power consumption plan, a medium and long term power consumption plan execution data, a maintenance plan and a transaction bidding data. Among them, the medium and long term power consumption plan, the medium and long term power consumption plan execution data and the maintenance plan data are the existing data of the power generation plan management system under the traditional planning mode, the transaction bidding data is declared by the market member, and during the simulation test, it can be set according to the evaluation and estimation of the market member power generation cost;

[0059] (2) New energy and other non-market power generation member power generation prediction data, from the new energy management system;

[0060] (3) Power load prediction data, from the load management system;

[0061] (4) Power grid network related data, including network connection topology, transmission capacity data, etc., from the power generation plan management system under the traditional planning mode.

[0062] Further, as an optional implementation, the start-stop coefficient construction module comprises:

[0063] The first coefficient acquisition module is configured to calculate the market transaction bidding of the market member of the power generation enterprise and the unit value of the highest price of the market transaction, and obtain the market transaction bidding coefficient;

[0064] Specifically, the start-stop coefficient construction module is configured to comprehensively consider the market transaction bidding optimization target under the power spot market and the power generation completion rate optimization target under the traditional planning mode, and construct a unit start-stop comprehensive coefficient optimization target item.

[0065] The market transaction bidding coefficient is defined as the unit value generated by comparing the market transaction bidding of the market member of the power generation enterprise with the highest price specified by the market transaction rule, and can be expressed as:

[0066]

[0067] In the formula, denotes the market transaction bidding coefficient of the power generation enterprise g, p SMax respectively denote the market transaction bidding declared by the power generation enterprise g and the highest price specified by the market transaction rule.

[0068] Further, for the power generation enterprise adopting a multi-segment declaration mode, the average value of the multi-segment declaration price can be adopted, which can be expressed as:

[0069]

[0070] In the formula, denotes the power generation capacity variation range of the power generation enterprise g under the multi-segment declaration mode, and NA denotes the number of declaration segments, respectively denote the power generation capacity variation range and the declared market transaction bidding under the number of declaration segments a.

[0071] The second coefficient acquisition module is configured to calculate the unit value of the power generation capacity of the market member of the power generation enterprise after the unit start-stop adjustment and the long-term power plan decomposition value, and obtain the power generation completion coefficient;

[0072] Specifically, the power generation completion coefficient is defined as a normalized value of the power generation of the market member after the unit start-stop adjustment compared with the decomposition value of the medium and long-term power generation plan, and can be expressed as:

[0073]

[0074] In the formula, represents the power generation completion coefficient of the power generation enterprise g, respectively represent the power generation of the power generation enterprise after considering the unit start-stop adjustment and the decomposition value of the medium and long-term power generation plan.

[0075] The coefficient setting module is configured to set an expected transaction cost adjustment coefficient;

[0076] The third coefficient obtaining module is configured to obtain a unit start-stop comprehensive coefficient according to the market transaction bidding coefficient, the power generation completion coefficient, and the expected transaction cost adjustment coefficient.

[0077] Specifically, the unit start-stop comprehensive coefficient is defined as a weighted average value of the expected transaction cost and the power generation completion balance degree, and can be expressed as:

[0078]

[0079] In the formula, represents the unit start-stop comprehensive coefficient, α1 represents the expected transaction cost adjustment coefficient, and the value range is 0-1, represents the average value of the power generation completion coefficients of all power generation enterprises, and NG represents the number of power generation enterprises participating in market transactions.

[0080] It should be noted that the value of the expected transaction cost adjustment coefficient α1 reflects the fitting degree of the system proposed in the embodiment of the application to the power spot market mode. The greater the value, the higher the fitting degree. When the value is 1, it is converted into the power spot market mode. If the value is 0, it is converted into the traditional planning mode.

[0081] Further, as an optional implementation, the unit start mode determination module comprises:

[0082] The first optimization target determination module is configured to determine a first optimization target, and the first optimization target is to minimize the unit start-stop comprehensive coefficient;

[0083] The first constraint condition determination module is configured to determine a first constraint condition according to the basic data, and the first constraint condition comprises a power and power balance constraint, a network transmission capability constraint, a power generation capability constraint, a power generation capability constraint, and a ramping capability constraint;

[0084] The unit combination model construction module is configured to construct a unit combination model based on the unit start-stop comprehensive coefficient according to the first optimization target and the first constraint condition;

[0085] The unit commitment model solving module is configured to solve the unit commitment model and determine the unit startup mode based on a solving result.

[0086] Specifically, the unit startup mode determining module is configured to construct a unit commitment model based on a unit startup and shutdown comprehensive coefficient to determine the unit startup and shutdown mode. The first optimization target of the unit commitment model is to minimize the unit startup and shutdown comprehensive coefficient, and the mode can be adjusted by setting the expected transaction cost adjustment coefficient.

[0087] In some optional embodiments, the unit commitment model constraint conditions are the same as those in the unit commitment model in the power spot market and the traditional planning mode, including power and energy balance constraints, network transmission capacity constraints, energy completion capacity constraints, power generation capacity constraints, and ramping capacity constraints. The constructed unit commitment model based on the unit startup and shutdown comprehensive coefficient can be expressed as:

[0088]

[0089] In the formula, C represents the unit startup and shutdown comprehensive coefficient, NG, NN, and NB represent the number of power generation enterprises, the number of new energy power stations, and the number of load nodes, respectively, P represent the power generation output of the power generation enterprise g at the t time period, the power generation output of the new energy power station n at the t time period, and the power consumption load of the load node b at the t time period, respectively, and γ g,s , γ n,s , and γ b,s represent the transfer distribution factors of the power generation enterprise g, the new energy power station n, and the load node b to the operation section s, respectively, P s Cmax and P s Cmin represent the upper and lower flow limit values of the operation section s, respectively, and represent the upper and lower power generation output limit values of the power generation enterprise g, respectively, and represent the upper and lower ramping capacity limit values of the power generation enterprise g, respectively, NT and ΔT represent the number of optimization time periods and the time interval, respectively, and μ g represents the startup and shutdown state variable of the power generation enterprise g.

[0090] Further, as an optional implementation, the unit commitment model solving module comprises:

[0091] The first model adjusting and solving module is configured to adjust the expected transaction cost adjustment coefficient in the unit startup and shutdown comprehensive coefficient, solve the unit commitment model based on the adjusted unit startup and shutdown comprehensive coefficient, and obtain a first solving result.

[0092] The first start-up mode determining module is configured to determine the start-up mode as the unit commitment scheme under the electricity spot market when the first solving result is 1.

[0093] The second start-up mode determining module is configured to determine the start-up mode as the unit commitment scheme under the traditional planning mode when the first solving result is 0.

[0094] Specifically, the unit commitment model is essentially a mixed integer programming problem, and can be solved by using a branch and bound method or calling a commercial software package such as Cplex to obtain a unit commitment scheme based on a unit start-stop comprehensive coefficient. By adjusting the expected transaction cost adjustment coefficient, the above unit commitment scheme can be adjusted. When it is adjusted to 1, it is equivalent to the unit commitment scheme under the electricity spot market; when it is adjusted to 0, it is equivalent to the unit commitment scheme under the traditional planning mode. Since the model only adjusts the optimization objective relative to the traditional planning mode, the optimization objective coefficient can be adjusted manually to achieve convenient adjustment of the mode, and the problem of frequent start-stop of units that may occur when the day-ahead generation plan generation mode is switched can be avoided.

[0095] Further, as an optional implementation, the power generation coefficient construction module comprises:

[0096] The fourth coefficient obtaining module is configured to obtain a transaction cost coefficient;

[0097] Specifically, the power generation coefficient construction module is configured to comprehensively consider the transaction cost and the power completion situation, and propose a unit power generation comprehensive coefficient to meet the connection needs under the electricity spot market and the traditional planning mode.

[0098] The transaction cost coefficient is defined as the expected transaction cost, and can be expressed as:

[0099]

[0100] In the formula, λ F represents the transaction cost coefficient, μ g represents the start-stop state variable of the power generation enterprise g, represents the power generation price function declared by the power generation enterprise g, and ΔT represents the time interval.

[0101] The fifth coefficient obtaining module is configured to obtain a power plan deviation rate of the power generation enterprise market member, and obtain a power completion coefficient according to the power plan deviation rate;

[0102] Specifically, the power completion coefficient is defined as the power plan deviation rate variance of the power generation enterprise, and can be expressed as:

[0103]

[0104] In the formula, λ Q represents the power completion coefficient, This represents the deviation rate of the power generation plan for power generation company g. Let represent the average power generation plan deviation rate of all power generation enterprises, and NG represent the number of power generation enterprises. The power generation plan deviation rate of power generation enterprise g can be expressed as the ratio of the difference between the medium- and long-term power generation plan breakdown value and the expected power generation to the medium- and long-term power generation plan breakdown value, as shown in the following formula:

[0105]

[0106] In the formula, Represents the breakdown value of the medium- and long-term electricity consumption plan, μ g Let g represent the start-up and shutdown state variables of power generation enterprise g. ΔT represents the power output of power generation company g during time period t, where ΔT represents the time interval.

[0107] The weight setting module is used to set the weight of the unit's power generation coefficient;

[0108] The sixth coefficient acquisition module is used to obtain the comprehensive power generation coefficient of the unit based on the transaction cost coefficient, the power completion coefficient, and the weight of the unit power generation coefficient.

[0109] Specifically, the comprehensive power generation coefficient of the generating unit is defined as the weighted average of the transaction cost coefficient and the power completion coefficient, which can be expressed as:

[0110]

[0111] In the formula, α1 represents the overall power generation coefficient of the generating unit, and α2 represents the weight of the power generation coefficient of the generating unit. The value range is 0-1, which reflects the degree of fit between the system proposed in this embodiment of the invention and the electricity spot market model. The larger the value, the higher the degree of fit. When the value is 1, it is converted to the electricity spot market model; when the value is 0, it is converted to the traditional planning model.

[0112] As a further optional implementation, the power generation plan generation module includes:

[0113] The second optimization objective determination module is used to determine the second optimization objective, which is to minimize the overall power generation coefficient of the unit.

[0114] The second constraint determination module is used to determine the second constraint based on the basic data. The second constraint includes power balance constraint, network transmission capacity constraint, power generation capacity constraint, and ramping capacity constraint.

[0115] The economic dispatch model construction module is used to construct an economic dispatch model based on the comprehensive power generation coefficient of the generating units, according to the second optimization objective and the second constraint.

[0116] The economic dispatch model solution module is used to solve the economic dispatch model and determine the day-ahead power generation plan based on the solution results.

[0117] Specifically, the power generation plan generation module is used to construct a unit combination model based on the unit power generation comprehensive coefficient to determine the unit power generation plan. The optimization objective of the economic dispatch model is to minimize the unit power generation comprehensive coefficient. Its mode can be adjusted by setting the weight values ​​of the unit power generation coefficient.

[0118] In some optional embodiments, the constraints of the economic dispatch model are the same as those of the unit combination model in the electricity spot market and the economic dispatch model in the traditional planning mode, including power balance constraints, network transmission capacity constraints, generation capacity constraints, and ramp-up capacity constraints. The constructed unit combination model based on the comprehensive generation coefficient of the units can be expressed as:

[0119]

[0120]

[0121] In the formula, This represents the overall power generation coefficient of the generating unit, where NG, NN, and NB represent the number of power generation enterprises, the number of new energy power plants, and the number of load nodes, respectively. γ represents, in turn, the power generation output of power generation enterprise g, the power generation output of new energy power plant n, and the power consumption of load node b during time period t. g,s γ n,s γ b,s P represents the transfer distribution factor between power generation enterprise g, new energy power plant n, load node b, and operating section s, respectively. s Cmax and P s Cmin These represent the upper and lower limits of the power flow at the operating section s, respectively. and Let these represent the upper limit and lower limit of the power generation output of power generation enterprise g, respectively. and These represent the upper limit and lower limit of the ramp-up capability of power generation enterprise g, respectively.

[0122] As an optional implementation, the economic scheduling model solving module includes:

[0123] The second model adjustment and solution module is used to adjust the weight of the unit power generation coefficient in the unit power generation comprehensive coefficient, and solve the economic dispatch model based on the adjusted unit power generation comprehensive coefficient to obtain the second solution result;

[0124] The first generation plan determination module is configured to determine the day-ahead generation plan as an economic dispatch scheme under an electricity spot market when the second solving result is 1.

[0125] The second generation plan determination module is configured to determine the day-ahead generation plan as an economic dispatch scheme under a traditional planning mode when the second solving result is 0.

[0126] Specifically, the economic dispatch model is essentially a linear programming problem, and can be solved by using a simplex method or calling a commercial software package such as Cplex to obtain a generation plan scheme based on a unit generation comprehensive coefficient. By adjusting the unit generation coefficient weight, the above economic dispatch scheme can be adjusted. When the unit generation coefficient weight is adjusted to 1, it is equivalent to an economic dispatch scheme under an electricity spot market, and when the unit generation coefficient weight is adjusted to 0, it is equivalent to an economic dispatch scheme under a traditional planning mode. Since the model only adjusts the optimization objective relative to the traditional planning mode, the mode can be conveniently adjusted by manually adjusting the optimization objective coefficient, and a generation plan compatible with the electricity spot market and the traditional planning mode can be obtained, effectively connecting the operation of the electricity spot market and the traditional planning mode, and improving the execution efficiency.

[0127] The day-ahead generation plan generation system of the embodiment of the present application is described above. It can be recognized that, on one hand, the unit start-stop comprehensive coefficient based on the declared price and the unit power is completed in the module, as the basis for unit commitment optimization, a unit commitment model based on the unit start-stop comprehensive coefficient is constructed, according to the solving result of the unit commitment model, the selected start mode is determined, and the problem of frequent start-stop of units that may occur in the mode switching of the day-ahead generation plan generation can be solved; on the other hand, the unit generation comprehensive coefficient is proposed in the module, as the basis for economic dispatch optimization, an economic dispatch model based on the unit generation comprehensive coefficient is constructed, according to the solving result of the economic dispatch model, the day-ahead generation plan is generated, and a generation plan compatible with the electricity spot market and the traditional planning mode can be obtained, effectively connecting the operation of the electricity spot market and the traditional planning mode, and improving the execution efficiency.

[0128] The embodiment of the present application further provides an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, and the program is executed by the processor to realize the day-ahead generation plan generation system. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0129] As Figure 2 Fig. 1 shows a hardware structure schematic diagram of an electronic device provided by the embodiment of the present application, and Figure 2 The embodiment of the present application provides an electronic device, which comprises:

[0130] The processor 1001 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is configured to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0131] The memory 1002 can be implemented by a ROM (Read Only Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory), and the like. The memory 1002 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 1002 and are called and executed by the processor 1001 to implement the day-ahead generation plan generation system of the embodiments of the present application.

[0132] The input / output interface 1003 is configured to implement information input and output.

[0133] The communication interface 1004 is configured to implement the communication interaction between the device and other devices, and can realize the communication through a wired manner (for example, a USB, a network cable, or the like) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, or the like).

[0134] The bus 1005 is configured to transmit information between various components (for example, the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004) of the device.

[0135] The processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 are connected to each other through the bus 1005 to realize the communication connection between the device.

[0136] The embodiments of the present application also provide a storage medium, which is a computer readable storage medium, and is configured to store computer readable information. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the day-ahead generation plan generation system.

[0137] Memory, as used in the specification, includes both volatile and nonvolatile memory, and can include but is not limited to removable memory and non-removable memory such as RAM, ROM, EEPROM, flash memory or other memory technology. Memory can also include other forms of computer-readable media, such as a storage device, for example, a hard disk drive or other storage device. Memory can be removable and / or non-removable. Memory can be volatile and / or non-volatile. Memory can be internal and / or external to the processor. Memory can be local and / or remote to the processor. Examples of a network include, but are not limited to, the Internet, an intranet, a local area network, a wide area network, a mobile communication network, and combinations thereof.

[0138] The embodiments of the present application further disclose a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device can read the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform the functions of the system shown in the embodiments. Figure 1 The embodiments of the present application further disclose a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device can read the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform the functions of the system shown in the embodiments.

[0139] In some alternative embodiments, the functions / operations mentioned in the block diagrams can not occur in the order mentioned in the operational diagrams. For example, depending on the functions / operations involved, two blocks shown in succession can actually be executed substantially concurrently or the blocks can sometimes be executed in reverse order. Alternative embodiments are contemplated where the order of various operations is changed and where sub-operations described as part of larger operations are independently executed.

[0140] Furthermore, although the present application is described in the context of functional modules, it is to be understood that one or more of the functions and / or features described above can be integrated in a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It is also to be understood that detailed discussion of the actual implementation of each module is unnecessary to an understanding of the present application. Rather, the actual implementation is to be understood in terms of the specifications, applications, and relationships of the various functional modules disclosed herein, within the context of an engineer's customary technical knowledge. Thus, the present application is to be implemented in a manner that includes ordinary skill in the art, with the benefit of the present disclosure, and without undue experimentation. It is also to be understood that the particular concepts disclosed are illustrative only and are not intended to limit the scope of the present application, which is defined only by the claims, and equivalents thereof.

[0141] If the above functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the technical solutions that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above-mentioned method of each embodiment of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0142] It should be understood that parts of the present application can be realized in hardware, software, firmware, or a combination thereof. In the above-described embodiments, a plurality of steps or methods can be realized by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if realized in hardware, as in another embodiment, it can be realized by any one or a combination of the following technologies known in the art: discrete logic circuit with logic gate circuit for implementing logic functions on data signals, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA), etc.

[0143] Although the embodiments of the present application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the claims and their equivalents.

[0144] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the embodiments, and those skilled in the art can make various equivalent modifications or replacements without departing from the spirit of the present application, and these equivalent modifications or replacements are all included in the scope defined by the claims of the present application.

Claims

1. A day-ahead power generation plan generation system, characterized in that, include: The data acquisition module is used to acquire basic data; The start-up and shutdown coefficient construction module is used to obtain the comprehensive start-up and shutdown coefficient of the unit based on the basic data; The start-up mode determination module is used to construct a unit combination model based on the unit start-up and shutdown comprehensive coefficients, solve the unit combination model, and determine the start-up mode. The power generation coefficient construction module is used to obtain the comprehensive power generation coefficient of the unit based on the basic data; The power generation plan generation module is used to construct an economic dispatch model based on the comprehensive power generation coefficient of the unit, solve the economic dispatch model, and determine the day-ahead power generation plan.

2. The day-ahead power generation plan generation system according to claim 1, characterized in that, The basic data in the data acquisition module includes power generation enterprise market member data, non-market member power generation forecast data, electricity load forecast data, and power grid structure data.

3. The day-ahead power generation plan generation system according to claim 1, characterized in that, The start / stop coefficient construction module includes: The first coefficient acquisition module is used to calculate the per-unit value of the market transaction bids of power generation enterprise market members and the highest price of the market exchange, and obtain the market transaction bid coefficient. The second coefficient acquisition module is used to obtain the per-unit value of the power generation of market members of power generation enterprises and the decomposition value of medium and long-term power plans after the computer group starts and stops, so as to obtain the power completion coefficient. The coefficient setting module is used to set the expected transaction cost adjustment coefficient; The third coefficient acquisition module is used to obtain the unit start-up and shutdown comprehensive coefficient based on the market transaction bidding coefficient, the electricity completion coefficient, and the expected transaction cost adjustment coefficient.

4. The day-ahead power generation plan generation system according to claim 1, characterized in that, The power-on method determination module includes: The first optimization objective determination module is used to determine the first optimization objective, which is to minimize the overall start-up and shutdown coefficient of the unit. The first constraint determination module is used to determine the first constraint based on the basic data. The first constraint includes power balance constraint, network transmission capacity constraint, power completion capacity constraint, power generation capacity constraint, and ramping capacity constraint. The unit combination model construction module is used to construct the unit combination model based on the unit start-up and shutdown comprehensive coefficients according to the first optimization objective and the first constraint conditions. The unit combination model solving module is used to solve the unit combination model and determine the start-up mode based on the solution results.

5. The day-ahead power generation plan generation system according to claim 4, characterized in that, The unit combination model solution module includes: The first model adjustment and solution module is used to adjust the expected transaction cost adjustment coefficient in the unit start-up and shutdown comprehensive coefficient, and solve the unit combination model based on the adjusted unit start-up and shutdown comprehensive coefficient to obtain the first solution result. The first start-up mode determination module is used to determine that the start-up mode is a unit combination scheme under the electricity spot market when the first solution result is 1. The second start-up mode determination module is used to determine that the start-up mode is the unit combination scheme under the traditional planning mode when the first solution result is 0.

6. The day-ahead power generation plan generation system according to claim 1, characterized in that, The power generation coefficient construction module includes: The fourth coefficient acquisition module is used to obtain the transaction fee coefficient; The fifth coefficient acquisition module is used to acquire the power plan deviation rate of the power generation enterprise market members, and to obtain the power completion coefficient based on the power plan deviation rate; The weight setting module is used to set the weight of the unit's power generation coefficient; The sixth coefficient acquisition module is used to obtain the comprehensive power generation coefficient of the generating unit based on the transaction cost coefficient, the power completion coefficient, and the weight of the generating unit's power generation coefficient.

7. The day-ahead power generation plan generation system according to claim 1, characterized in that, The power generation plan generation module includes: The second optimization objective determination module is used to determine the second optimization objective, which is to minimize the comprehensive power generation coefficient of the unit. The second constraint determination module is used to determine the second constraint based on the basic data. The second constraint includes power balance constraint, network transmission capacity constraint, power generation capacity constraint, and ramping capacity constraint. An economic dispatch model construction module is used to construct an economic dispatch model based on the comprehensive power generation coefficient of the generating unit, according to the second optimization objective and the second constraint. The economic dispatch model solving module is used to solve the economic dispatch model and determine the day-ahead power generation plan based on the solution results.

8. The day-ahead power generation plan generation system according to claim 7, characterized in that, The economic scheduling model solution module includes: The second model adjustment and solution module is used to adjust the weight of the unit power generation coefficient in the unit power generation comprehensive coefficient, and solve the economic dispatch model based on the adjusted unit power generation comprehensive coefficient to obtain the second solution result. The first power generation plan determination module is used to determine that the day-ahead power generation plan is an economic dispatch scheme under the electricity spot market when the second solution result is 1. The second power generation plan determination module is used to determine that the day-ahead power generation plan is an economic dispatch scheme under the traditional planning mode when the second solution result is 0.

9. An electronic device, characterized in that, The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory. When the program is executed by the processor, it implements the day-ahead power generation plan generation system as described in any one of claims 1 to 8.

10. A storage medium, said storage medium being a computer-readable storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the day-ahead power generation plan generation system as described in any one of claims 1 to 8.

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