Multi-dimensional cost evaluation method and device based on multi-value collaborative scheduling framework

Abstract

The invention relates to the technical field of power system cost analysis, in particular to a multi-dimensional cost evaluation method and device based on a multi-value cooperative scheduling framework, and the method comprises the steps: determining a safety-economy-low carbon multi-value cooperative scheduling framework of a power system; under a multi-value collaborative scheduling framework, based on electric energy scheduling demand information and auxiliary service scheduling demand information, a unit power demand scheduling cost minimization model is constructed, and based on payment information and environmental premium information, a unit participation scheduling gain maximization model is constructed; and constructing a unit cost evaluation model to obtain a total value evaluation result of the power system. Therefore, the problems that in related technologies, cost evaluation combining stable energy supply, ordered resource adjustment, cleanness, environmental protection, low carbon and the like is difficult to comprehensively consider, and comprehensive feedback and cooperation of various main body electric energy values, safety values and green values in an electric power system cannot be achieved are solved.

Description

Technical Field

[0001] The present application relates to the technical field of power system cost analysis, and in particular to a multi-dimensional cost evaluation method and device based on a multi-value collaborative scheduling framework. Background Art

[0002] Under the future energy trend of increasing proportion of new energy, building a new power system that can adapt to the rapid growth of new energy installed capacity and power generation is an important way to achieve the dual carbon goals. In the context of this energy transformation, the construction of the power system is facing new changes and challenges. First, the power structure in the system has changed, adding heavier tasks to ensure supply and consumption; second, the grid form in the system has changed, and multi-level balance needs to be coordinated; third, the main body of system demand and supply has changed, and coordinated interaction needs to be incentivized. In response to the above challenges, the future power system needs to build a multi-value collaborative dispatching framework to obtain the full value assessment results of the endogenous and external comprehensive costs of the power system.

[0003] In the relevant technology, the economic benefit coefficient can be defined to calculate the ratio between the price of the products produced by the cogeneration unit and the price of the consumed fuel within the statistical time, thereby completing the evaluation of the energy utilization efficiency of the cogeneration unit; it is also possible to determine the objective function and constraints of the new energy grid connection and consumption model based on production simulation, and calculate the standby auxiliary service cost after the new energy is connected to the grid, the income of the new energy wind turbine unit, the standby auxiliary service shared cost and the peak load auxiliary service shared cost caused by wind power access.

[0004] However, in the relevant technologies, it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon energy. It is impossible to achieve the comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy. This problem needs to be solved urgently. Summary of the invention

[0005] The present application provides a multi-dimensional cost assessment method and device based on a multi-value collaborative scheduling framework to solve the problems in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon, and it is impossible to achieve comprehensive feedback and coordination of the electric energy value, safety value and green value of various entities in the power system on the basis of meeting safe supply, low-carbon transformation and economy.

[0006] The first aspect of the present application provides a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework, which is applied to the model building stage, wherein the method includes the following steps: determining a safe-economic-low-carbon multi-value collaborative scheduling framework of a power system; obtaining electric energy scheduling demand information and ancillary service scheduling demand information of the power system, and based on the electric energy scheduling demand information and the ancillary service scheduling demand information, in combination with the safe-economic-low-carbon multi-value collaborative scheduling framework, constructing a unit power demand scheduling cost minimization model of the power system; obtaining payment information and environmental premium information of the power system, and based on the payment information and the environmental premium information, in combination with the safe-economic-low-carbon multi-value collaborative scheduling framework, constructing a unit participation scheduling benefit maximization model of the power system; based on the unit power demand scheduling cost minimization model and the unit participation scheduling benefit maximization model, constructing a unit cost evaluation model of the power system under the safe-economic-low-carbon multi-value collaborative scheduling framework, so as to use the unit cost evaluation model to obtain the full value evaluation result of the comprehensive endogenous and external costs of the power system.

[0007] Optionally, in one embodiment of the present application, constructing the unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework includes: obtaining physical architecture information and unit declaration information of the power system; determining constraint information of the power system based on the physical architecture information and the unit declaration information; generating a constraint function of the unit cost assessment model based on the constraint information, so as to generate the unit cost assessment model based on the constraint function.

[0008] Optionally, in one embodiment of the present application, the construction of a safe-economic-low-carbon multi-value collaborative dispatching framework for the power system includes: obtaining a new energy dispatching method that satisfies at least one of the power system operating conditions, policy value conditions and time and space boundary conditions; obtaining an optimal configuration method for electric power resources that coordinates the dispatch varieties of the power system at different time scales; obtaining the probabilistic balance system characteristics and decoupling method of the power system under large-scale access to the grid of new energy; and constructing the safe-economic-low-carbon multi-value collaborative dispatching framework based on the new energy dispatching method, the optimal configuration method for electric power resources and the probabilistic balance system characteristics and decoupling method.

[0009] Optionally, in one embodiment of the present application, the expression of the constraint function may be, but is not limited to:

[0010]

[0011]

[0012]

[0013]

[0014]

[0015]

[0016]

[0017]

[0018] Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

[0019] Optionally, in one embodiment of the present application, the expression of the unit power demand scheduling cost minimization model may be, but is not limited to,:

[0020]

[0021] in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

[0022] Optionally, in one embodiment of the present application, the expression of the model for maximizing the profit of the unit participating in the scheduling may be, but is not limited to,:

[0023]

[0024] in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

[0025] The second aspect of the present application provides a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework, which is applied to the model application stage, wherein the method includes the following steps: obtaining at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information; inputting at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information into a pre-constructed unit cost assessment model to obtain the actual full value assessment result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-constructed unit cost assessment model includes a unit power demand scheduling cost minimization model and a unit participation scheduling benefit maximization model.

[0026] The third aspect of the present application provides a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework, which is applied to the model construction stage, wherein the device includes: a determination module, which is used to determine the safety-economy-low-carbon multi-value collaborative scheduling framework of the power system; a first construction module, which is used to obtain the electric energy scheduling demand information and the auxiliary service scheduling demand information of the power system, and based on the electric energy scheduling demand information and the auxiliary service scheduling demand information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework, construct a unit power demand scheduling cost minimization model of the power system; a second construction module, which is used to obtain the payment information and environmental premium information of the power system, and based on the payment information and the environmental premium information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework, construct a unit participation scheduling benefit maximization model of the power system; a third construction module, which is used to construct a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework based on the unit power demand scheduling cost minimization model and the unit participation scheduling benefit maximization model, so as to use the unit cost evaluation model to obtain the full value evaluation result of the endogenous and external comprehensive costs of the power system.

[0027] Optionally, in one embodiment of the present application, the third construction module includes: a first acquisition unit, used to acquire physical architecture information and unit declaration information of the power system; a determination unit, used to determine constraint information of the power system based on the physical architecture information and the unit declaration information; and a generation unit, used to generate a constraint function of the unit cost assessment model based on the constraint information, so as to generate the unit cost assessment model based on the constraint function.

[0028] Optionally, in one embodiment of the present application, the determination module includes: a second acquisition unit, used to acquire a new energy scheduling method that satisfies at least one of the power system operating conditions, policy value conditions and time and space boundary conditions; a third acquisition unit, used to acquire an electric power resource optimization configuration method that coordinates the power system scheduling varieties at different time scales; a fourth acquisition unit, used to acquire the probabilistic balance system characteristics and decoupling method of the power system under large-scale access to the grid of new energy; and a construction unit, used to construct the safety-economy-low-carbon multi-value collaborative scheduling framework based on the new energy scheduling method, the electric power resource optimization configuration method and the probabilistic balance system characteristics and decoupling method.

[0029] Optionally, in one embodiment of the present application, the expression of the constraint function may be, but is not limited to:

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

[0039] Optionally, in one embodiment of the present application, the expression of the unit power demand scheduling cost minimization model may be, but is not limited to,:

[0040]

[0041] in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

[0042] Optionally, in one embodiment of the present application, the expression of the model for maximizing the profit of the unit participating in the scheduling may be, but is not limited to,:

[0043]

[0044] in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

[0045] The fourth aspect of the present application provides a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework, which is applied to the model application stage, wherein the device includes: an acquisition module, used to obtain at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information; an evaluation module, used to input at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information into a pre-built unit cost evaluation model to obtain the actual full value evaluation result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-built unit cost evaluation model includes a unit power demand scheduling cost minimization model and a unit participation scheduling benefit maximization model.

[0046] The fifth aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described in the above embodiment.

[0047] The sixth aspect embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework.

[0048] The seventh aspect embodiment of the present application provides a computer program product, including a computer program, which, when executed, implements the above-mentioned multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework.

[0049] The embodiment of the present application can first determine the safety-economy-low-carbon multi-value collaborative dispatching framework of the power system, and then construct a power system unit power demand dispatching cost minimization model based on the electric energy dispatching demand information and the auxiliary service dispatching demand information. Through payment information and environmental premium information, a power system unit participation dispatching benefit maximization model is constructed, and then the unit power demand dispatching cost minimization model and the unit participation dispatching benefit maximization model are used to construct a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative dispatching framework, and obtain the full value evaluation result of the endogenous and external comprehensive costs of the power system, comprehensively consider the operation and dispatching of multiple categories of units such as electric energy, auxiliary services, capacity compensation, and carbon trading, integrate the endogenous and external costs including safety, economy, and low carbon, and provide a mechanism for the comprehensive recovery of unit costs and the multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative dispatching framework for large-scale access to the grid of new energy, which can effectively stimulate the participation of units under future energy situations, promote the system to develop in the direction of environmental protection and high efficiency, and ensure that all parties involved benefit. This solves the problem that related technologies are difficult to comprehensively consider cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon energy, and are unable to achieve comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy.

[0050] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0052] Figure 1 A flowchart of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application;

[0053] Figure 2 A schematic block diagram of a safety-economy-low-carbon multi-value collaborative scheduling framework provided according to an embodiment of the present application;

[0054] Figure 3 A flowchart of the working principle of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application;

[0055] Figure 4 A schematic block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application;

[0056] Figure 5 A flowchart of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to another embodiment of the present application;

[0057] Figure 6 A schematic block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework provided according to another embodiment of the present application;

[0058] Figure 7 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0059] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0060] The following describes the multi-dimensional cost assessment method and device based on a multi-value collaborative scheduling framework in an embodiment of the present application with reference to the accompanying drawings. In view of the problem mentioned in the above background technology that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon, and it is impossible to achieve the comprehensive feedback and coordination of the electric energy value, safety value and green value of various entities in the power system on the basis of meeting safe supply, low-carbon transformation and economy, the present application provides a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework. In this method, the safety-economy-low-carbon multi-value collaborative scheduling framework of the power system can be determined first, and then a power demand scheduling cost minimization model of the power system is constructed based on the electric energy scheduling demand information and the auxiliary service scheduling demand information. Through payment information and environmental premium information, a model for maximizing the benefits of the power system unit participating in scheduling is constructed, and then the machine The cost minimization model of group power demand dispatching and the model of maximizing benefits of unit participation in dispatching are constructed, and the unit cost evaluation model under the framework of safe-economic-low-carbon multi-value collaborative dispatching of the power system is constructed to obtain the full value evaluation result of the endogenous and external comprehensive costs of the power system, comprehensively consider the operation and dispatching of the unit in multiple categories such as electric energy, auxiliary services, capacity compensation, carbon trading, etc., integrate the endogenous and external costs including safety, economy, and low carbon, and provide a mechanism for the comprehensive recovery of unit costs and multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative dispatching framework for large-scale access to the grid of new energy, which can effectively stimulate the participation of units under the future energy situation, promote the system to develop in the direction of environmental protection and high efficiency, and ensure that all parties involved benefit. Thus, it solves the problem that it is difficult to comprehensively consider the cost evaluation of the combination of stable energy supply, orderly resource regulation, clean environmental protection and low carbon in the relevant technology, and it is impossible to realize the comprehensive feedback and coordination of the electric energy value, safety value and green value of various entities in the power system on the basis of meeting the safety supply, low-carbon transformation and economy.

[0061] Specifically, Figure 1 This is a flowchart of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application.

[0062] like Figure 1 As shown, the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework is applied to the model building stage, wherein the method includes the following steps:

[0063] In step S101, a safety-economy-low-carbon multi-value coordinated dispatching framework of the power system is determined.

[0064] As a possible implementation method, the embodiment of the present application can construct a safe-economic-low-carbon multi-value collaborative scheduling framework through new energy scheduling methods, power resource optimization configuration methods, and probabilistic balance system characteristics and decoupling methods.

[0065] Optionally, in one embodiment of the present application, a safe-economic-low-carbon multi-value collaborative dispatching framework for the power system is constructed, including: obtaining a new energy dispatching method that satisfies at least one of the power system operating conditions, policy value conditions, and time and space boundary conditions; obtaining an optimal configuration method for electric power resources that coordinates the dispatching varieties of the power system at different time scales; obtaining the probabilistic balance system characteristics and decoupling methods of the power system under large-scale access to the grid of new energy; and constructing a safe-economic-low-carbon multi-value collaborative dispatching framework based on the new energy dispatching method, the optimal configuration method for electric power resources, and the probabilistic balance system characteristics and decoupling methods.

[0066] In some embodiments, the embodiments of the present application propose a new energy dispatching method that meets the conditions of power system operation, policy value, and time and space boundaries. Among them, in the new energy dispatching method of the embodiments of the present application, the connection between the new energy priority plan dispatching and the market transaction demand dispatching can first obtain the coordination of the power matching, profit and loss sharing, and dispatching deviation assessment of the priority power generation dispatching, the priority power purchase dispatching, and the market transaction demand dispatching, and can also include other contents, which can be specifically set by technicians in this field according to actual conditions, and this application does not make specific restrictions.

[0067] The new energy scheduling method proposed in the embodiment of the present application, which meets the conditions of power system operation, policy value, and time and space boundaries, can adapt to the connection between new energy priority plan scheduling and market transaction demand scheduling under the future high proportion of new energy penetration.

[0068] In some embodiments, the embodiments of the present application propose a method for optimizing the configuration of power resources in which the types of power system dispatch are coordinated at different time scales. Among them, the method for optimizing the configuration of power resources in the embodiments of the present application can be understood as a method for strengthening the connection between medium- and long-term operations and spot operations in terms of power matching, organizational cycle, participating devices, safety constraints, and deviation processing.

[0069] Furthermore, the embodiments of the present application obtain a more refined division of operation periods in terms of power matching and organizational cycles. Annual and monthly operations are used to achieve long-term guidance; continuous operations within a month are used to achieve flexible adjustment of medium- and long-term curves to meet the short-term and high-frequency deviation adjustment requirements of new energy entities; and spot operations before and during the day are used to achieve real-time balance of power. The specific settings can be made by technicians in this field according to actual conditions, and this application does not impose specific restrictions.

[0070] In terms of participating devices, the participation and autonomy of the load side are constantly increasing, and the participation has developed from unilateral participation of the power generation end to bilateral participation of generation and use in scheduling.

[0071] In terms of security constraints, multiple constraints including security checks and clearing algorithms are obtained to ensure the feasibility of transaction results.

[0072] In terms of deviation handling, the acquisition system entity adjusts the contract deviations held through operations in various time periods and assumes the responsibility for deviation management.

[0073] In some embodiments, the embodiments of the present application propose probabilistic balance system characteristics and decoupling methods for power systems under large-scale grid-connected renewable energy, that is, decoupling the complex random optimization into two parts: deterministic electric energy interaction and uncertain ramping and backup services.

[0074] Among them, the probability balance system characteristics and decoupling method of the embodiment of the present application first obtains the predicted load and the predicted output of new energy under a certain confidence level, conducts electric energy balance transactions based on the expected value, and then obtains the total demand for ramping and standby services, and allocates the relevant costs to the responsible party for the unbalanced part of the confidence interval caused by the inaccurate prediction of the output of new energy. Among them, the certain confidence level can be set by technicians in this field according to actual conditions, and this application does not make specific restrictions.

[0075] In some embodiments, the embodiments of the present application can construct a safety-economy-low-carbon multi-value collaborative scheduling framework based on the new energy scheduling method, the power resource optimization configuration method, the probability balance system characteristics and the decoupling method, and its flow chart is as follows: Figure 2 shown.

[0076] In step S102, the electric energy dispatch demand information and the auxiliary service dispatch demand information of the power system are obtained, and based on the electric energy dispatch demand information and the auxiliary service dispatch demand information, a unit power demand dispatch cost minimization model of the power system is constructed in combination with the safety-economy-low-carbon multi-value collaborative dispatch framework. The expression of the unit power demand dispatch cost minimization model can be, but is not limited to,:

[0077]

[0078] in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

[0079] As a possible implementation method, the embodiment of the present application obtains the electric energy dispatching demand information and the auxiliary service dispatching demand information of the power system, and based on the safety-economy-low-carbon multi-value collaborative dispatching framework constructed in step S102, considers the electric energy dispatching demand, ramping and standby auxiliary service dispatching demand of the collaborative power system, and constructs a unit power demand dispatching cost minimization model of the power system. Among them, the expression of the unit power demand dispatching cost minimization model can be, but is not limited to:

[0080]

[0081] in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; It represents the electric energy dispatch cost reported by the m-th power unit j, which is obtained from the physical architecture information and the unit reporting information; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the auxiliary service scheduling declared by the n-th power unit j, which is obtained by the physical architecture information and the unit declaration information.

[0082] In step S103, the payment information and environmental premium information of the power system are obtained, and based on the payment information and environmental premium information, a model for maximizing the benefits of the power system's units participating in the dispatch is constructed in combination with the safety-economy-low-carbon multi-value collaborative dispatch framework. The expression of the model for maximizing the benefits of the units participating in the dispatch can be, but is not limited to,:

[0083]

[0084] in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

[0085] It is understandable that the payment information in the embodiments of the present application may include but is not limited to the comprehensive cost that the power system is willing to pay for providing electric energy and auxiliary service units, capacity compensation payments and carbon trading fees within the system, etc., and the present application does not impose specific restrictions.

[0086] In the actual implementation process, the embodiment of the present application can obtain the payment information and environmental premium information of the power system, and can also obtain the environmental premium information declared by new energy in the power system, and combine the constructed safety-economy-low-carbon multi-value collaborative scheduling framework, considering the electric energy scheduling that reflects the value of electric energy, the auxiliary service scheduling and capacity compensation that reflects the safety value, and the new energy premium reflection and carbon trading that reflects the green value in the power system, and construct a model for maximizing the benefits of the unit participating in the scheduling. Among them, the model for maximizing the benefits of the unit participating in the scheduling can include but is not limited to participating in electric energy scheduling, auxiliary service scheduling, capacity compensation and carbon trading, etc., and this application does not make specific restrictions.

[0087] Further, in the embodiment of the present application, the expression of the model for maximizing the profit of the unit participating in the scheduling can be, but is not limited to,:

[0088]

[0089] in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

[0090] In step S104, based on the unit power demand dispatch cost minimization model and the unit participation dispatch benefit maximization model, a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value coordinated dispatch framework is constructed, so as to obtain the full value evaluation result of the endogenous and external comprehensive costs of the power system by using the unit cost evaluation model.

[0091] It can be understood by those skilled in the art that the embodiment of the present application can use the unit power demand dispatching cost minimization model as the lower layer, and the unit participation dispatching benefit maximization model as the upper layer to construct a unit cost evaluation model under the safety-economy-low-carbon multi-value collaborative dispatching framework of the power system. Among them, in the embodiment of the present application, the unit cost evaluation model can obtain the electric energy dispatching amount and auxiliary service dispatching amount of each type of unit through the lower layer unit power demand dispatching cost minimization model, and return to the upper layer unit participation dispatching benefit maximization model, through the recursive optimization process, using the unit cost evaluation model, to obtain the full value evaluation result of the endogenous and external comprehensive costs of the unit participating in the electric energy dispatching and the auxiliary service dispatching.

[0092] Optionally, in one embodiment of the present application, a unit cost evaluation model of a power system under a safety-economy-low-carbon multi-value collaborative dispatch framework is constructed, including: obtaining physical architecture information and unit declaration information of the power system; determining constraint information of the power system based on the physical architecture information and unit declaration information; generating a constraint function of the unit cost evaluation model based on the constraint information, so as to generate a unit cost evaluation model based on the constraint function. The expression of the constraint function may be, but is not limited to,:

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, Li (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

[0102] In some embodiments, the embodiments of the present application can obtain the physical architecture information and unit declaration information held by the system operator of the power system economic dispatch organization and management agency, and obtain the declared costs of all types of resource units. Specifically, the physical architecture information and unit declaration information obtained by the embodiments of the present application may include but are not limited to the number of nodes, the number of lines, the declared cost functions of various types of generator sets, etc., and the present application does not impose specific restrictions.

[0103] Further, in the embodiment of the present application, for a power system having N nodes and K lines, the declared costs of all types of resource units obtained may be expressed as, but not limited to:

[0104]

[0105] in, P represents the cost function reported by generator j of type k; i，j represents the active power of generator j at node i, and the active power of all nodes forms a vector P.

[0106] In some embodiments, the embodiments of the present application can determine the constraint information of the power system based on the physical architecture information and the unit declaration information, and then obtain the constraint function of the unit cost assessment model.

[0107] Among them, in the embodiments of the present application, the constraint information may include but is not limited to the load demand of each node, the line transmission capacity, the power generation transfer distribution factor, the upper and lower limits of the generator power, etc., and the present application does not make specific restrictions.

[0108] Further, in the embodiment of the present application, the expression of the constraint function may be, but is not limited to,:

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

[0118] Among them, formula (4) represents the system supply and demand balance constraint, and the total power generation of the system is the total load demand plus the system loss; formula (5) represents the unit power output constraint, and the power generation power of the single unit is within its minimum and maximum output range; formula (6) represents the unit climbing constraint, and the power change of the unit at two adjacent moments is within its climbing capacity range; formulas (7) and (8) represent the start and stop constraints of thermal power units, namely coal-fired power and gas-fired power units; formula (9) represents the system standby constraint; formulas (10) and (11) represent the system line transmission capacity constraints.

[0119] The working principle of the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework proposed in the embodiment of the present application is introduced in detail below in conjunction with a specific embodiment.

[0120] in, Figure 3 The present invention is a flowchart of the working principle of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application.

[0121] Step S301: Propose a new energy dispatching method that simultaneously satisfies at least one of the power system operating conditions, policy value conditions, and time and space boundary conditions.

[0122] Step S302: Propose a method for optimizing the configuration of electric power resources in a coordinated manner among power system dispatch types at different time scales.

[0123] Step S303: Decouple the complex random optimization under large-scale grid access of new energy into two parts: deterministic electric energy interaction and uncertain ramp-up and backup services, and construct probabilistic balance system characteristics and decoupling methods.

[0124] Step S304: Construct a safety-economy-low-carbon multi-value collaborative scheduling framework based on the new energy scheduling method, the power resource optimization configuration method, the probabilistic balance system characteristics and the decoupling method.

[0125] Step S305: Acquire the physical architecture information and unit declaration information of the power system, determine the constraint information of the power system, and generate the constraint function of the unit cost evaluation model.

[0126] Step S306: construct a unit power demand scheduling cost minimization model.

[0127] Step S307: construct a model for maximizing the benefits of unit participation in scheduling.

[0128] Step S308: Take the unit power demand dispatching cost minimization model as the lower layer and the unit participation dispatching benefit maximization model as the upper layer to construct a unit cost evaluation model under the safety-economy-low-carbon multi-value coordinated dispatching framework of the power system.

[0129] Step S309: Obtain the electric energy dispatching amount and ancillary service dispatching amount of each type of unit through the lower-level unit power demand dispatching cost minimization model, return to the upper-level unit participation dispatching profit maximization model, and through the recursive optimization process, use the unit cost evaluation model to obtain the full value evaluation result of the comprehensive endogenous and external costs of the unit's participation in electric energy dispatching and ancillary service dispatching.

[0130] According to the multi-dimensional cost evaluation method based on the multi-value collaborative dispatching framework proposed in the embodiment of the present application, the safety-economy-low-carbon multi-value collaborative dispatching framework of the power system can be determined first, and then the power demand dispatching cost minimization model of the power system is constructed based on the power energy dispatching demand information and the auxiliary service dispatching demand information. Through payment information and environmental premium information, a model for maximizing the benefits of the power system's unit participation in dispatching is constructed, and then the unit power demand dispatching cost minimization model and the unit participation dispatching benefit maximization model are used to construct a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative dispatching framework, and the full value evaluation result of the endogenous and external comprehensive costs of the power system is obtained. The operation dispatching of the unit in multiple categories such as power energy, auxiliary services, capacity compensation, and carbon trading is comprehensively considered, and the endogenous and external costs including safety, economy, and low carbon are integrated to provide a mechanism for the comprehensive recovery of unit costs and the multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative dispatching framework for large-scale access to the grid of new energy, which can effectively stimulate the participation of units under future energy situations, promote the system to develop in the direction of environmental protection and high efficiency, and ensure that all parties involved benefit. This solves the problem that related technologies are difficult to comprehensively consider cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon energy, and are unable to achieve comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy.

[0131] Next, a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework proposed according to an embodiment of the present application is described with reference to the accompanying drawings.

[0132] Figure 4 It is a block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework provided according to an embodiment of the present application.

[0133] like Figure 4 As shown, the multi-dimensional cost evaluation device 40 based on the multi-value collaborative scheduling framework is applied to the model construction stage, wherein the device 40 includes: a determination module 401, a first construction module 402, a second construction module 403 and a third construction module 404.

[0134] Among them, the determination module 401 is used to determine the safety-economy-low-carbon multi-value coordinated dispatching framework of the power system.

[0135] The first construction module 402 is used to obtain the electric energy dispatching demand information and the auxiliary service dispatching demand information of the power system, and based on the electric energy dispatching demand information and the auxiliary service dispatching demand information, combined with the safety-economy-low-carbon multi-value collaborative dispatching framework, construct a unit power demand dispatching cost minimization model of the power system.

[0136] The second construction module 403 is used to obtain the payment information and environmental premium information of the power system, and based on the payment information and environmental premium information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework, to construct a model for maximizing the benefits of the power system's units participating in scheduling.

[0137] The third construction module 404 is used to construct a unit cost evaluation model for the power system under the safety-economy-low-carbon multi-value coordinated scheduling framework based on the unit power demand scheduling cost minimization model and the unit participation scheduling benefit maximization model, so as to use the unit cost evaluation model to obtain the full value evaluation results of the endogenous and external comprehensive costs of the power system.

[0138] Optionally, in one embodiment of the present application, the third construction module 404 includes: a first acquisition unit, a determination unit and a generation unit.

[0139] Among them, the first acquisition unit is used to obtain the physical structure information and unit declaration information of the power system.

[0140] The determination unit is used to determine the constraint information of the power system based on the physical architecture information and the unit declaration information.

[0141] A generating unit is used to generate a constraint function of a unit cost evaluation model based on constraint information, so as to generate the unit cost evaluation model based on the constraint function.

[0142] Optionally, in one embodiment of the present application, the determination module 401 includes: a second acquisition unit, a third acquisition unit, a fourth acquisition unit and a construction unit.

[0143] Among them, the second acquisition unit is used to obtain a new energy scheduling method that meets at least one of the power system operation conditions, policy value conditions and time and space boundary conditions.

[0144] The third acquisition unit is used to obtain an optimal configuration method for electric power resources in which the types of power system dispatching are coordinated with each other under different time scales.

[0145] The fourth acquisition unit is used to obtain the probabilistic balance system characteristics and decoupling methods of the power system under the large-scale grid-connected renewable energy.

[0146] The construction unit is used to build a safe-economic-low-carbon multi-value collaborative scheduling framework based on new energy scheduling methods, power resource optimization configuration methods, and probabilistic balance system characteristics and decoupling methods.

[0147] Optionally, in one embodiment of the present application, the expression of the constraint function may be, but is not limited to:

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

[0157] Optionally, in one embodiment of the present application, the expression of the unit power demand scheduling cost minimization model may be, but is not limited to,:

[0158]

[0159] in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

[0160] Optionally, in one embodiment of the present application, the expression of the model for maximizing the profit of the unit participating in the scheduling may be, but is not limited to,:

[0161]

[0162] in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

[0163] It should be noted that the above explanation of the embodiment of the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework is also applicable to the multi-dimensional cost evaluation device based on the multi-value collaborative scheduling framework of this embodiment, and will not be repeated here.

[0164] According to the multi-dimensional cost evaluation device based on the multi-value collaborative scheduling framework proposed in the embodiment of the present application, the safety-economy-low-carbon multi-value collaborative scheduling framework of the power system can be determined first, and then the power demand scheduling cost minimization model of the power system is constructed based on the power energy scheduling demand information and the auxiliary service scheduling demand information. Through payment information and environmental premium information, a model for maximizing the benefits of the power system unit participating in scheduling is constructed, and then the unit power demand scheduling cost minimization model and the unit participation scheduling benefit maximization model are used to construct a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework, and the full value evaluation result of the endogenous and external comprehensive costs of the power system is obtained. The operation and scheduling of the unit in multiple categories such as power energy, auxiliary services, capacity compensation, and carbon trading are comprehensively considered, and the endogenous and external costs including safety, economy, and low carbon are integrated to provide a mechanism for the comprehensive recovery of unit costs and the multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative scheduling framework for large-scale access to the grid of new energy, which can effectively stimulate the participation of units under future energy situations, promote the system to develop in the direction of environmental protection and high efficiency, and ensure that all parties involved benefit. This solves the problem that related technologies are difficult to comprehensively consider cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon, and are unable to achieve comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy.

[0165] The above embodiment describes the model building stage, and the following describes an embodiment of the model application stage.

[0166] Figure 5 This is a schematic diagram of a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework provided according to another embodiment of the present application.

[0167] like Figure 5 As shown, the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework is applied in the model application stage, wherein the method includes the following steps:

[0168] In step S501, at least one of actual physical architecture information of an actual power system, actual unit declaration information, actual electric energy dispatch demand information, actual auxiliary service dispatch demand information, actual payment information and actual environmental premium information is obtained.

[0169] In step S502, at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual ancillary service scheduling demand information, the actual payment information and the actual environmental premium information is input into a pre-constructed unit cost assessment model to obtain the actual full value assessment result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-constructed unit cost assessment model includes a unit power demand scheduling cost minimization model and a unit participation scheduling benefit maximization model.

[0170] In some embodiments, the embodiments of the present application can obtain the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual ancillary service scheduling demand information, the actual payment information and the actual environmental premium information, etc., and input the above information into a pre-built unit cost assessment model. The electric energy scheduling amount and ancillary service scheduling amount of each type of unit are obtained through the lower-level unit power demand scheduling cost minimization model in the unit cost assessment model, and then returned to the upper-level unit participation scheduling benefit maximization model in the unit cost assessment model. Through the recursive optimization process, the actual full value assessment results of the comprehensive endogenous and external costs of the unit participating in electric energy scheduling and ancillary service scheduling are obtained.

[0171] According to the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework proposed in the embodiment of the present application, the actual physical architecture of the actual power system, the actual unit declaration, the actual electric energy scheduling demand, the actual auxiliary service scheduling demand, the actual payment and the actual environmental premium and other information can be input into the pre-built unit cost evaluation model. Through the recursive optimization process, the actual full value evaluation result of the comprehensive endogenous and external costs of the unit participating in electric energy scheduling and auxiliary service scheduling is obtained. The unit's operation scheduling in multiple categories such as electric energy, auxiliary services, capacity compensation, carbon trading, etc. is comprehensively considered, and the endogenous and external costs including safety, economy, and low carbon are integrated to provide a mechanism for the comprehensive recovery of unit costs and the multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative scheduling framework for the large-scale access to the grid of new energy, which can effectively stimulate the participation of units under future energy situations, promote the system to develop in the direction of environmental protection and efficiency, and ensure that all participating parties benefit. This solves the problem that related technologies are difficult to comprehensively consider cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon energy, and are unable to achieve comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy.

[0172] Next, a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework proposed according to an embodiment of the present application is described with reference to the accompanying drawings.

[0173] Figure 6 A block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework provided according to another embodiment of the present application.

[0174] like Figure 6 As shown, the multi-dimensional cost evaluation device 60 based on the multi-value collaborative scheduling framework is applied in the model application stage, wherein the device 60 includes: an acquisition module 601 and an evaluation module 602 .

[0175] Among them, the acquisition module 601 is used to obtain at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information.

[0176] The evaluation module 602 is used to input at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual auxiliary service scheduling demand information, the actual payment information and the actual environmental premium information into a pre-constructed unit cost evaluation model to obtain the actual full value evaluation result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-constructed unit cost evaluation model includes a unit power demand scheduling cost minimization model and a unit participation scheduling benefit maximization model.

[0177] It should be noted that the above explanation of the embodiment of the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework is also applicable to the multi-dimensional cost evaluation device based on the multi-value collaborative scheduling framework of this embodiment, and will not be repeated here.

[0178] According to the multi-dimensional cost evaluation device based on the multi-value collaborative scheduling framework proposed in the embodiment of the present application, the actual physical architecture of the actual power system, the actual unit declaration, the actual electric energy scheduling demand, the actual auxiliary service scheduling demand, the actual payment and the actual environmental premium and other information can be input into the pre-built unit cost evaluation model. Through the recursive optimization process, the actual full value evaluation result of the comprehensive endogenous and external costs of the unit participating in the electric energy scheduling and auxiliary service scheduling is obtained. The unit's operation scheduling in multiple categories such as electric energy, auxiliary services, capacity compensation, carbon trading, etc. is comprehensively considered, and the endogenous and external costs including safety, economy, and low carbon are integrated to provide a mechanism for the comprehensive recovery of unit costs and the multi-dimensional evaluation of unit value in the power system. In addition, the embodiment of the present application takes into account the supporting role of the multi-value collaborative scheduling framework for the large-scale access to the grid of new energy, which can effectively stimulate the participation of units under future energy situations, promote the system to develop in the direction of environmental protection and efficiency, and ensure that all participating parties benefit. This solves the problem that related technologies are difficult to comprehensively consider cost assessment that combines stable energy supply, orderly resource regulation, clean, environmentally friendly and low-carbon, and are unable to achieve comprehensive feedback and coordination of the electricity energy value, safety value and green value of various entities in the power system on the basis of ensuring safe supply, low-carbon transformation and economy.

[0179] Figure 7 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. The electronic device may include:

[0180] A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .

[0181] When the processor 702 executes the program, the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework provided in the above embodiment is implemented.

[0182] Furthermore, the electronic device further comprises:

[0183] The communication interface 703 is used for communication between the memory 701 and the processor 702 .

[0184] The memory 701 is used to store computer programs that can be executed on the processor 702 .

[0185] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0186] If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0187] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.

[0188] The processor 702 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0189] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described above.

[0190] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above-mentioned multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework.

[0191] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0192] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0193] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0194] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0195] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0196] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0197] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0198] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework, characterized in that: Applied to the model building stage, wherein the method comprises the following steps: Determine the multi-value coordinated dispatch framework of power system security, economy and low carbon; Obtaining electric energy dispatch demand information and auxiliary service dispatch demand information of the electric power system, and building a unit power demand dispatch cost minimization model of the electric power system based on the electric energy dispatch demand information and the auxiliary service dispatch demand information and in combination with the safety-economy-low-carbon multi-value collaborative dispatch framework; Obtain payment information and environmental premium information of the power system, and based on the payment information and the environmental premium information, and in combination with the safety-economy-low-carbon multi-value collaborative dispatching framework, construct a model for maximizing the benefits of the units participating in the dispatching of the power system; Based on the unit power demand dispatch cost minimization model and the unit participation dispatch benefit maximization model, a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework is constructed, so as to use the unit cost evaluation model to obtain the full value evaluation results of the endogenous and external comprehensive costs of the power system.

2. The method according to claim 1, characterized in that The construction of the unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value coordinated dispatch framework includes: Obtaining physical structure information and unit declaration information of the power system; Determining constraint information of the power system based on the physical architecture information and the unit declaration information; A constraint function of the unit cost assessment model is generated based on the constraint information, so as to generate the unit cost assessment model based on the constraint function.

3. The method according to claim 1, characterized in that The safety-economy-low-carbon multi-value coordinated dispatching framework for the power system includes: Obtaining a new energy dispatching method that satisfies at least one of the power system operation conditions, policy value conditions, and time and space boundary conditions; Obtaining a method for optimizing the configuration of electric resources in which the types of electric power system dispatch are coordinated with each other at different time scales; Obtaining the probabilistic balance system characteristics and decoupling method of the power system under large-scale grid access of renewable energy; The safety-economy-low-carbon multi-value collaborative scheduling framework is constructed based on the new energy scheduling method, the power resource optimization configuration method, and the probabilistic balance system characteristics and decoupling method.

4. The method according to claim 2, characterized in that: The expression of the constraint function is: Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

5. The method according to claim 1, characterized in that: The expression of the unit power demand dispatch cost minimization model is: in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

6. The method according to claim 1, characterized in that The expression of the model for maximizing the benefits of the unit participating in the dispatch is: in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R eN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

7. A multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework, characterized in that: Applied to the model application stage, wherein the method comprises the following steps: Acquire at least one of actual physical architecture information of an actual power system, actual unit declaration information, actual electric energy dispatch demand information, actual auxiliary service dispatch demand information, actual payment information, and actual environmental premium information; At least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy dispatch demand information, the actual ancillary service dispatch demand information, the actual payment information and the actual environmental premium information is input into a pre-constructed unit cost assessment model to obtain the actual full value assessment result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-constructed unit cost assessment model includes a unit power demand dispatch cost minimization model and a unit participation dispatch benefit maximization model.

8. A multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework, characterized in that: Applied to the model building stage, wherein the device comprises: A determination module is used to determine the safety-economy-low-carbon multi-value coordinated dispatch framework of the power system; The first construction module is used to obtain the electric energy dispatch demand information and the auxiliary service dispatch demand information of the power system, and based on the electric energy dispatch demand information and the auxiliary service dispatch demand information, in combination with the safety-economy-low-carbon multi-value collaborative dispatch framework, construct a unit power demand dispatch cost minimization model of the power system; The second construction module is used to obtain the payment information and environmental premium information of the power system, and based on the payment information and the environmental premium information, in combination with the safety-economy-low-carbon multi-value collaborative dispatching framework, to construct a model for maximizing the benefits of the units participating in the dispatching of the power system; The third construction module is used to construct a unit cost evaluation model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework based on the unit power demand scheduling cost minimization model and the unit participation scheduling benefit maximization model, so as to use the unit cost evaluation model to obtain the full value evaluation result of the endogenous and external comprehensive costs of the power system.

9. The device according to claim 8, characterized in that The third building block comprises: A first acquisition unit, used to acquire physical architecture information and unit declaration information of the power system; A determination unit, configured to determine constraint information of the power system based on the physical architecture information and the unit declaration information; A generating unit is used to generate a constraint function of the unit cost evaluation model based on the constraint information, so as to generate the unit cost evaluation model based on the constraint function.

10. The device according to claim 8, characterized in that The determining module comprises: A second acquisition unit is used to acquire a new energy dispatching method that satisfies at least one of the power system operation conditions, policy value conditions, and time and space boundary conditions; A third acquisition unit is used to acquire an optimal configuration method of electric power resources in which the types of power system dispatch are coordinated with each other at different time scales; A fourth acquisition unit is used to acquire the probabilistic balance system characteristics and decoupling method of the power system under the large-scale grid access of new energy; A construction unit is used to construct the safety-economy-low-carbon multi-value collaborative scheduling framework based on the new energy scheduling method, the power resource optimization configuration method and the probabilistic balance system characteristics and decoupling method.

11. The device according to claim 9, characterized in that The expression of the constraint function is: Among them, P ij represents the power generated by generator set j at time t; D i (t) represents the load demand of node i at time t, L i (t) represents the system loss at node i at time t; P j and They represent the lower and upper limits of the output power of generator set j respectively; and Respectively represent the ascending and descending climbing capabilities of the unit; u j (t) represents the power-on status of unit j at time t, 1 for power-on and 0 for power-off; SU j With SD j Respectively represent the start-up and shutdown limits; R ij (t) represents the spare capacity provided by unit j at node i; R SYS Indicates the total spare capacity of the system; F k-i represents the generation transfer distribution factor of node i to line k; Indicates the capacity of the line.

12. The device according to claim 8, characterized in that The expression of the unit power demand dispatch cost minimization model is: in, represents the electric energy dispatch demand of unit j of the mth type of power source, and the types of power sources include coal power, gas power, wind power, photovoltaic power, and hydropower; represents the electric energy dispatch cost reported by the m-th type power unit j; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; It represents the ancillary service dispatch declared by the nth type power unit j.

13. The device according to claim 8, characterized in that The expression of the model for maximizing the benefits of the unit participating in the dispatch is: in, represents the electric energy dispatch demand of the mth type power unit j, and the power types include coal power, gas power, wind power, photovoltaic power, and hydropower; R EN Indicates the cost paid by the system for calling electric energy; represents the auxiliary service dispatch demand of the nth type power unit j, and the power types include coal power, gas power, and hydropower; R ANS Pc represents the cost of the system to pay the unit for calling ancillary services; j Represents the amount of electricity that coal-fired power unit j participates in capacity compensation; R CAP represents the capacity compensation paid by the system; represents the amount of electricity and ancillary services called by the wind turbine; Ew represents the environmental premium declared by the wind turbine; It represents the amount of electricity called by the photovoltaic unit; Es represents the environmental premium declared by the photovoltaic unit; represents the carbon emissions of the g-th unit j; R CAB represents the carbon trading fee within the system; β g It represents the carbon trading coefficient of the g-th type of unit, which includes coal-fired power and gas-fired power.

14. A multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework, characterized in that: Applied to the model application stage, wherein the device comprises: An acquisition module, used to acquire at least one of actual physical architecture information of an actual power system, actual unit declaration information, actual electric energy dispatch demand information, actual auxiliary service dispatch demand information, actual payment information, and actual environmental premium information; An evaluation module is used to input at least one of the actual physical architecture information of the actual power system, the actual unit declaration information, the actual electric energy scheduling demand information, the actual ancillary service scheduling demand information, the actual payment information and the actual environmental premium information into a pre-constructed unit cost evaluation model to obtain the actual full value evaluation result of the endogenous and external comprehensive costs of the actual power system, wherein the pre-constructed unit cost evaluation model includes a unit power demand scheduling cost minimization model and a unit participation scheduling benefit maximization model.

15. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described in any one of claims 1 to 6 or claim 7.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described in any one of claims 1 to 6 or claim 7.

17. A computer program product, characterized in that It includes a computer program which, when executed, is used to implement a multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described in any one of claims 1 to 6 or claim 7.

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