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

Abstract

The application relates to the technical field of power system cost analysis, in particular to a multi-dimension cost evaluation method and device based on a multi-value coordinated dispatching framework, wherein the method comprises the following steps: determining a safety-economy-low-carbon multi-value coordinated dispatching framework of a power system; under the multi-value coordinated dispatching framework, constructing a unit power demand dispatching cost minimization model based on power energy dispatching demand information and auxiliary service dispatching demand information, and constructing a unit participating dispatching maximum income model based on payment information and environmental premium information; and constructing a unit cost evaluation model to obtain a full-value evaluation result of the power system. Therefore, the problems that in the related art, the cost evaluation cannot comprehensively consider the combination of stable energy supply, orderly resource regulation, clean and environment-friendly low carbon, and the comprehensive feedback and coordination of the power energy value, safety value and green value of various subjects in the power system cannot be realized are solved.

Description

Technical Field

[0001] This application relates to the field of power system cost analysis technology, and in particular to a multi-dimensional cost assessment method and device based on a multi-value collaborative scheduling framework. Background Technology

[0002] With the increasing proportion of new energy sources in the future energy landscape, building a new power system capable of adapting to the rapid growth in installed capacity and power generation of new energy sources is a crucial pathway to achieving dual-carbon goals. Against this backdrop of energy transition, power system construction is facing entirely new changes and challenges. First, changes in the power source structure within the system have added a heavier burden of ensuring supply and consumption. Second, changes in the grid structure within the system necessitate coordinated multi-level balancing. Third, changes in the main entities responsible for system demand and supply require incentives for coordinated interaction. To address these challenges, the future power system needs to establish a multi-value collaborative dispatch framework to obtain a comprehensive value assessment of the power system's endogenous and external costs.

[0003] In related technologies, the energy utilization efficiency of cogeneration units can be evaluated by defining an economic benefit coefficient and calculating the ratio between the price of the products produced by the cogeneration unit and the price of the fuel consumed within a statistical period. Alternatively, the standby ancillary service cost, the revenue of the new energy wind turbine unit, the standby ancillary service allocation cost, and the peak-shaving ancillary service allocation cost caused by wind power access can be calculated by determining the objective function and constraints of the new energy grid connection and consumption model based on production simulation.

[0004] However, the relevant technologies struggle to comprehensively consider cost assessments that combine stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon practices. They also fail to achieve comprehensive feedback and synergy of the energy value, safety value, and green value of various entities within the power system while satisfying the needs of safe supply, low-carbon transformation, and economic efficiency. This issue urgently needs to be addressed. Summary of the Invention

[0005] This 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, such as the difficulty in comprehensively considering the combination of stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon cost assessment, and the inability to achieve comprehensive feedback and coordination of the value of various main electrical energy, safety value, and green value in the power system while meeting the requirements of safe supply, low-carbon transformation, and economy.

[0006] The first aspect of this application provides a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework, applied in the model building stage. The method includes the following steps: determining a safety-economy-low-carbon multi-value collaborative scheduling framework for a power system; acquiring power dispatch demand information and ancillary service dispatch demand information of the power system, and based on the power dispatch demand information and the ancillary service dispatch demand information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework, constructing a unit power demand dispatch cost minimization model for the power system; acquiring 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, constructing a unit participation in dispatch benefit maximization model for the power system; and based on the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, constructing a unit cost assessment model for the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework, so as to obtain a full-value assessment result of the comprehensive cost of the power system's endogenous and externalities using the unit cost assessment model.

[0007] Optionally, in one embodiment of this application, constructing the unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework includes: obtaining the physical architecture information and unit application information of the power system; determining the constraint information of the power system based on the physical architecture information and the unit application information; generating the 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 this application, the construction of a safety-economy-low-carbon multi-value collaborative dispatch framework for a power system includes: acquiring a new energy dispatch method that satisfies at least one of the power system operating conditions, policy value conditions, and time-space boundary conditions; acquiring a power resource optimization allocation method that coordinates the dispatch types of the power system under different time scales; acquiring the probabilistic balance system characteristics and decoupling method of the power system under large-scale grid connection of new energy sources; and constructing the safety-economy-low-carbon multi-value collaborative dispatch framework based on the new energy dispatch method, the power resource optimization allocation method, and the probabilistic balance system characteristics and decoupling method.

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

[0010]

[0011]

[0012]

[0013]

[0014]

[0015]

[0016]

[0017]

[0018] Among them, P ij D represents the power output of generator set j at time t; i (t) represents the load demand of node i at time t, L i (t) represents the system loss at time t on node i; P j and These represent the lower and upper limits of the output power of generator set j, respectively. and These represent the unit's ascent and descent ramping capabilities, respectively; u j (t) represents the operating state of unit j at time t, where 1 indicates operation and 0 indicates shutdown; SU j With SD j These represent start-up and stop restrictions, respectively; R ij (t) represents the reserve capacity provided by unit j at node i; R SYS Indicates the total reserve capacity of the system; F k-i This represents the power generation transfer distribution factor of node i to line k; This indicates the capacity of the line.

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

[0020]

[0021] in, This represents the electrical energy dispatch demand of unit j of the m-th power source, where the power source types include coal power, gas power, wind power, photovoltaic power, and hydropower. This represents the energy dispatch cost declared by power generation unit j of type m; This represents the ancillary service scheduling demand of the nth type of power unit j, where the power types include coal power, gas power, and hydropower. This indicates the ancillary service scheduling result declared by power unit j of type n.

[0022] Optionally, in one embodiment of this application, the expression for the model that maximizes the benefits of the unit participating in scheduling can be, but is not limited to, the following:

[0023]

[0024] in, This represents the electrical energy dispatch demand of power generation unit j of type m, where the power sources include coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower; R EN This represents the cost the system pays for accessing electrical energy; R represents the ancillary service dispatch demand of power generation unit j of type n, where the power types include coal-fired power, gas-fired power, and hydropower; ANS This indicates the system's cost for calling ancillary service payment units; Pc j R represents the amount of electricity generated by coal-fired power unit j that participates in capacity compensation; CAP This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine; Ew represents the environmental premium declared by the wind turbine itself. This indicates the amount of electricity used by the photovoltaic (PV) generator; Es represents the environmental premium declared by the PV generator itself. R represents the carbon emissions of unit j in class g; CAB Indicates the carbon trading cost within the system; β g This represents the carbon trading factor for Class g generating units, which include both coal-fired and gas-fired power plants.

[0025] A second aspect of this application provides a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework, applied in the model application stage. The method includes the following steps: obtaining at least one of the following: actual physical architecture information of the actual power system, actual generating unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information; inputting at least one of the following into a pre-built generating unit cost assessment model to obtain the actual full-value assessment result of the comprehensive cost of the endogenous and externalities of the actual power system. The pre-built generating unit cost assessment model includes a generating unit power demand dispatch cost minimization model and a generating unit participation in dispatch benefit maximization model.

[0026] A third aspect of this application provides a multi-dimensional cost assessment device based on a multi-value collaborative scheduling framework, applied in the model building stage. The device includes: a determination module for determining the safety-economy-low-carbon multi-value collaborative scheduling framework of a power system; a first construction module for acquiring power dispatch demand information and ancillary service dispatch demand information of the power system, and constructing a unit power demand dispatch cost minimization model of the power system based on the power dispatch demand information and the ancillary service dispatch demand information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework; a second construction module for acquiring payment information and environmental premium information of the power system, and constructing a unit participation in dispatch benefit maximization model of the power system based on the payment information and the environmental premium information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework; and a third construction module for constructing a unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework based on the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, so as to obtain a full-value assessment result of the comprehensive cost of the power system's endogenous and externalities using the unit cost assessment model.

[0027] Optionally, in one embodiment of this application, the third construction module includes: a first acquisition unit, configured to acquire the physical architecture information and unit application information of the power system; a determination unit, configured to determine the constraint information of the power system based on the physical architecture information and the unit application information; and a generation unit, configured 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 this application, the determining module includes: a second acquisition unit, used to acquire a new energy dispatching method that satisfies at least one of the power system operating conditions, policy value conditions, and time-space boundary conditions; a third acquisition unit, used to acquire a power resource optimization allocation method that coordinates the dispatching types of the power system under 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 grid connection of new energy; and a construction unit, used to construct the safe-economic-low-carbon multi-value collaborative dispatching framework based on the new energy dispatching method, the power resource optimization allocation method, and the probabilistic balance system characteristics and decoupling method.

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

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] Among them, P ij D represents the power output of generator set j at time t; i (t) represents the load demand of node i at time t, L i (t) represents the system loss at time t on node i; P j and These represent the lower and upper limits of the output power of generator set j, respectively. and These represent the unit's ascent and descent ramping capabilities, respectively; u j (t) represents the operating state of unit j at time t, where 1 indicates operation and 0 indicates shutdown; SU j With SD j These represent start-up and stop restrictions, respectively; R ij (t) represents the reserve capacity provided by unit j at node i; R SYS Indicates the total reserve capacity of the system; F k-i This represents the power generation transfer distribution factor of node i to line k; This indicates the capacity of the line.

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

[0040]

[0041] in, This represents the electrical energy dispatch demand of unit j of the m-th power source, where the power source types include coal power, gas power, wind power, photovoltaic power, and hydropower. This represents the energy dispatch cost declared by power generation unit j of type m; This represents the ancillary service scheduling demand of the nth type of power unit j, where the power types include coal power, gas power, and hydropower. This indicates the ancillary service scheduling result declared by power unit j of type n.

[0042] Optionally, in one embodiment of this application, the expression for the model that maximizes the benefits of the unit participating in scheduling can be, but is not limited to, the following:

[0043]

[0044] in, This represents the electrical energy dispatch demand of power generation unit j of type m, where the power sources include coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower; R EN This represents the cost the system pays for accessing electrical energy; R represents the ancillary service dispatch demand of power generation unit j of type n, where the power types include coal-fired power, gas-fired power, and hydropower; ANS This indicates the system's cost for calling ancillary service payment units; Pc j R represents the amount of electricity generated by coal-fired power unit j that participates in capacity compensation; CAP This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine; Ew represents the environmental premium declared by the wind turbine itself. This indicates the amount of electricity used by the photovoltaic (PV) generator; Es represents the environmental premium declared by the PV generator itself. R represents the carbon emissions of unit j in class g; CAB Indicates the carbon trading cost within the system; β g This represents the carbon trading factor for Class g generating units, which include both coal-fired and gas-fired power plants.

[0045] The fourth aspect of this application provides a multi-dimensional cost assessment device based on a multi-value collaborative scheduling framework, applied in the model application stage. The device includes: an acquisition module for acquiring at least one of the following: actual physical architecture information of the actual power system, actual generating unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information; and an assessment module for inputting at least one of the following into a pre-built generating unit cost assessment model to obtain the actual full-value assessment result of the combined endogenous and externality costs of the actual power system. The pre-built generating unit cost assessment model includes a generating unit power demand dispatch cost minimization model and a generating unit participation in dispatching benefit maximization model.

[0046] A fifth aspect of this 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 the multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described in the above embodiments.

[0047] A sixth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described above.

[0048] A seventh aspect of this application provides a computer program product, including a computer program that, when executed, implements the multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework as described above.

[0049] This application embodiment first determines the safety-economy-low-carbon multi-value collaborative dispatch framework of the power system. Then, based on the power energy dispatch demand information and ancillary service dispatch demand information, it constructs a model for minimizing the unit power demand dispatch cost of the power system. Through payment information and environmental premium information, it constructs a model for maximizing the benefits of unit participation in dispatch. Furthermore, using the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, it constructs a unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework. This yields a full-value assessment result of the comprehensive cost of the power system's endogenous and externalities. It comprehensively considers the operation and dispatch of units in multiple categories such as power energy, ancillary services, capacity compensation, and carbon trading, integrating the endogenous and external costs including safety, economy, and low carbon. This provides a mechanism for the comprehensive recovery of unit costs and the multi-dimensional assessment of unit value in the power system. In addition, this application embodiment considers the supporting role of the multi-value collaborative dispatch framework for the large-scale grid connection of new energy sources, which can effectively incentivize unit participation under the future energy situation, promote the development of the system towards environmental protection and efficiency, and ensure that all participating entities benefit. This solves the problem in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that it is impossible to achieve comprehensive feedback and synergy of the value, safety value, and green value of various main electrical energy components in the power system while meeting the requirements of safe supply, low-carbon transformation, and economy.

[0050] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

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

[0052] Figure 1 This is a flowchart illustrating a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework, according to an embodiment of this application.

[0053] Figure 2 A block diagram illustrating a safe-economic-low-carbon multi-value collaborative scheduling framework according to an embodiment of this application;

[0054] Figure 3 A flowchart illustrating the working principle of a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework provided in one embodiment of this application;

[0055] Figure 4 This is a block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework according to an embodiment of this application;

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

[0057] Figure 6 This is a block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework according to another embodiment of this application;

[0058] Figure 7 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

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

[0060] The following describes a multi-dimensional cost assessment method and apparatus based on a multi-value collaborative scheduling framework, according to embodiments of this application, with reference to the accompanying drawings. Addressing the problem mentioned in the background art of cost assessment that makes it difficult to comprehensively consider the combination of stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that fails to achieve comprehensive feedback and coordination of the energy value, safety value, and green value of various entities in the power system while satisfying the requirements of safe supply, low-carbon transformation, and economy, this application provides a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework. In this method, a safety-economy-low-carbon multi-value collaborative scheduling framework for the power system is first determined. Then, based on energy scheduling demand information and ancillary service scheduling demand information, a model for minimizing the unit power demand scheduling cost of the power system is constructed. Furthermore, a model for maximizing the benefits of unit participation in scheduling is constructed using payment information and environmental premium information. Finally, the method utilizes the... This paper proposes a power demand dispatch cost minimization model and a unit participation dispatch benefit maximization model. It constructs a unit cost assessment model within a multi-value collaborative dispatch framework of safety, economy, and low carbon, obtaining a comprehensive value assessment result of the power system's endogenous and external costs. This model comprehensively considers the unit's operation and dispatch across multiple categories, including electrical energy, ancillary services, capacity compensation, and carbon trading, integrating endogenous and external costs encompassing safety, economy, and low carbon. This provides a mechanism for the comprehensive recovery of unit costs and multi-dimensional assessment of unit value within the power system. Furthermore, considering the supporting role of the multi-value collaborative dispatch framework for the large-scale grid connection of new energy sources, this application can effectively incentivize unit participation under future energy conditions, promoting the system's development towards environmental protection and efficiency while ensuring benefits for all participating entities. Therefore, it solves the problems in related technologies where cost assessments cannot comprehensively consider the combination of stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and where comprehensive feedback and synergy of the electrical energy value, safety value, and green value of various entities within the power system cannot be achieved while satisfying safety supply, low-carbon transformation, and economic requirements.

[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 this application.

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

[0063] In step S101, a safety-economy-low-carbon multi-value collaborative dispatch framework for the power system is determined.

[0064] As one possible approach, embodiments of this application can construct a safe-economic-low-carbon multi-value collaborative scheduling framework using new energy scheduling methods, power resource optimization allocation methods, and probabilistic balance system characteristics and decoupling methods.

[0065] Optionally, in one embodiment of this application, a safety-economy-low-carbon multi-value collaborative dispatch framework for a power system is constructed, including: acquiring a new energy dispatch method that satisfies at least one of power system operating conditions, policy value conditions, and time-space boundary conditions; acquiring a power resource optimization allocation method that coordinates the dispatch types of the power system under different time scales; acquiring the probabilistic balance system characteristics and decoupling method of the power system under large-scale grid connection of new energy; and constructing a safety-economy-low-carbon multi-value collaborative dispatch framework based on the new energy dispatch method, the power resource optimization allocation method, and the probabilistic balance system characteristics and decoupling method.

[0066] In some embodiments, this application proposes a renewable energy dispatching method that satisfies power system operating conditions, policy value conditions, and time and space boundaries. Specifically, in this renewable energy dispatching method, the connection between renewable energy priority planning dispatching and market transaction demand dispatching can be achieved by first obtaining coordination in terms of power matching, profit and loss sharing, and dispatching quantity deviation assessment between priority generation dispatching, priority power purchase dispatching, and market transaction demand dispatching. Other aspects may also be included, and the specific details can be set by those skilled in the art according to actual conditions; this application does not impose specific limitations.

[0067] The renewable energy dispatching method proposed in this application, which satisfies the conditions of power system operation, policy value, and time and space boundaries, can adapt to the connection between renewable energy priority planning dispatching and market transaction demand dispatching under the future high proportion of renewable energy penetration.

[0068] In some embodiments, this application proposes a method for optimizing the allocation of power resources by coordinating different types of power system dispatching at different time scales. This method can be understood as a way to strengthen the connection between medium- and long-term operations and spot operations in terms of power matching, organizational cycles, participating devices, safety constraints, and deviation handling.

[0069] Furthermore, this application embodiment achieves a more refined division of operating periods in terms of power matching and organizational cycles. Annual and monthly operations provide long-term guidance; continuous monthly operations enable flexible adjustments to medium- and long-term curves, meeting the short-cycle, high-frequency deviation adjustment requirements of new energy entities; and day-ahead and intraday spot operations achieve real-time power balance. Specific settings can be configured by those skilled in the art according to actual conditions, and this application does not impose specific limitations.

[0070] In terms of participating devices, the load-side participation and autonomy are constantly increasing, evolving from unilateral participation at the generation end to bilateral participation and dispatch between generation and consumption.

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

[0072] Regarding deviation handling, the system entity obtains the deviations of its contracts through operational adjustments over various time periods and assumes responsibility for deviation management.

[0073] In some embodiments, this application proposes a probabilistic balance system characteristic and decoupling method for power systems under large-scale grid connection of new energy sources, that is, decoupling the complex stochastic optimization into two parts: deterministic energy interaction and uncertain ramp-up and backup services.

[0074] The probability balancing system characteristics and decoupling method in this application first obtain the predicted load and predicted output of new energy sources at a certain confidence level, and then conducts power balance trading based on the expected values. Next, it obtains the total demand for ramp-up and standby services, and addresses the imbalance in the confidence interval caused by inaccurate predictions of new energy output by allocating the relevant costs to the responsible parties. The certain confidence level can be set by those skilled in the art according to actual conditions, and this application does not impose specific limitations.

[0075] In some embodiments, this application can construct a safe-economic-low-carbon multi-value collaborative scheduling framework based on new energy dispatching methods, power resource optimization allocation methods, and probabilistic balance system characteristics and decoupling methods, as shown in the flowchart below. Figure 2 As shown.

[0076] In step S102, the power system's energy dispatch demand information and ancillary service dispatch demand information are obtained. Based on these information and combined with a safety-economy-low-carbon multi-value collaborative dispatch framework, a unit power demand dispatch cost minimization model is constructed. The expression for this model can be, but is not limited to, the following:

[0077]

[0078] in, This represents the electrical energy dispatch demand of unit j of the m-th power source, where the power source types include coal power, gas power, wind power, photovoltaic power, and hydropower. This represents the energy dispatch cost declared by power generation unit j of type m; This represents the ancillary service scheduling demand of the nth type of power unit j, where the power types include coal power, gas power, and hydropower. This indicates the ancillary service scheduling result declared by power unit j of type n.

[0079] As one possible implementation, this application embodiment obtains the power system's energy dispatch demand information and ancillary service dispatch demand information. Based on the safety-economy-low-carbon multi-value collaborative dispatch framework constructed in step S102, it considers the collaborative power system's energy dispatch demand, ramp-up and reserve ancillary service dispatch demand, and constructs a unit power demand dispatch cost minimization model for the power system. The expression for the unit power demand dispatch cost minimization model can be, but is not limited to, as follows:

[0080]

[0081] in, This represents the electrical energy dispatch demand of unit j of the m-th power source, where the power source types include coal power, gas power, wind power, photovoltaic power, and hydropower. The energy dispatch cost declared by power unit j of type m is obtained from the physical architecture information and the unit declaration information. This represents the ancillary service scheduling demand of the nth type of power unit j, where the power types include coal power, gas power, and hydropower. This indicates the ancillary service scheduling result declared by power unit j of type n, which is obtained from the physical architecture information and the unit declaration information.

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

[0083]

[0084] in, This represents the electrical energy dispatch demand of power generation unit j of type m, where the power sources include coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower; R EN This represents the cost the system pays for accessing electrical energy; R represents the ancillary service dispatch demand of power generation unit j of type n, where the power types include coal-fired power, gas-fired power, and hydropower; ANS This indicates the system's cost for calling ancillary service payment units; Pc j R represents the amount of electricity generated by coal-fired power unit j that participates in capacity compensation; CAP This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine; Ew represents the environmental premium declared by the wind turbine itself. This indicates the amount of electricity used by the photovoltaic (PV) generator; Es represents the environmental premium declared by the PV generator itself. R represents the carbon emissions of unit j in class g; CAB Indicates the carbon trading cost within the system; β g This represents the carbon trading factor for Class g generating units, which include both coal-fired and gas-fired power plants.

[0085] It is understood that the payment information in the embodiments of this application may include, but is not limited to, the comprehensive cost of the power system's willingness to pay for providing electrical energy and ancillary services, capacity compensation payments, and carbon trading fees within the system, etc., and this application does not impose specific limitations.

[0086] In practical implementation, the embodiments of this application can obtain payment information and environmental premium information of the power system, as well as environmental premium information declared by new energy sources in the power system. Combined with the constructed safety-economy-low-carbon multi-value collaborative dispatch framework, considering the power system's power energy dispatch reflecting the value of electricity, ancillary service dispatch and capacity compensation reflecting the safety value, and new energy premium reflection and carbon trading reflecting the green value, a model for maximizing the benefits of generating units participating in dispatch is constructed. This model for maximizing the benefits of generating units participating in dispatch may include, but is not limited to, participation in power energy dispatch, ancillary service dispatch, capacity compensation, and carbon trading; this application does not impose specific limitations.

[0087] Furthermore, in the embodiments of this application, the expression for the model that maximizes the benefits of unit participation in scheduling can be, but is not limited to, as follows:

[0088]

[0089] in, This represents the electrical energy dispatch demand of power generation unit j of type m, where the power sources include coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower; R EN This represents the cost the system pays for accessing electrical energy; R represents the ancillary service dispatch demand of power generation unit j of type n, where the power types include coal-fired power, gas-fired power, and hydropower; ANS This indicates the system's cost for calling ancillary service payment units; Pc j R represents the amount of electricity generated by coal-fired power unit j that participates in capacity compensation; CAP This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine; Ew represents the environmental premium declared by the wind turbine itself. This indicates the amount of electricity used by the photovoltaic (PV) generator; Es represents the environmental premium declared by the PV generator itself. R represents the carbon emissions of unit j in class g; CAB Indicates the carbon trading cost within the system; β g This represents the carbon trading factor for Class g generating units, which include both coal-fired and gas-fired power plants.

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

[0091] Those skilled in the art will understand that the embodiments of this application can use a unit power demand dispatch cost minimization model as the lower layer and a unit participation in dispatch benefit maximization model as the upper layer to construct a unit cost assessment model under the power system's safety-economy-low-carbon multi-value collaborative dispatch framework. Specifically, in the embodiments of this application, the unit cost assessment model can obtain the power dispatch amount and ancillary service dispatch amount of each type of unit through the lower-level unit power demand dispatch cost minimization model, and return it to the upper-level unit participation in dispatch benefit maximization model. Through a recursive optimization process, using the unit cost assessment model, the full value assessment result of the comprehensive cost of the endogenous and externalities of unit participation in power dispatch and ancillary service dispatch is obtained.

[0092] Optionally, in one embodiment of this application, constructing a unit cost assessment model for a power system under a safety-economy-low-carbon multi-value collaborative dispatch framework includes: acquiring physical architecture information and unit application information of the power system; determining constraint information of the power system based on the physical architecture information and unit application information; generating constraint functions for the unit cost assessment model based on the constraint information, and generating the unit cost assessment model based on the constraint functions. The expression of the constraint functions may be, but is not limited to, the following:

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] Among them, P ij D represents the power output of generator set j at time t; i (t) represents the load demand of node i at time t, Li (t) represents the system loss at time t on node i; P j and These represent the lower and upper limits of the output power of generator set j, respectively. and These represent the unit's ascent and descent ramping capabilities, respectively; u j (t) represents the operating state of unit j at time t, where 1 indicates operation and 0 indicates shutdown; SU j With SD j These represent start-up and stop restrictions, respectively; R ij (t) represents the reserve capacity provided by unit j at node i; R SYS Indicates the total reserve capacity of the system; F k-i This represents the power generation transfer distribution factor of node i to line k; This indicates the capacity of the line.

[0102] In some embodiments, the present application can obtain physical architecture information and generator unit application information held by the power system economic dispatch organization and management agency system operator to obtain the application cost of all types of resource generator units. Specifically, the physical architecture information and generator unit application information obtained in the present application can include, but are not limited to, the number of nodes, the number of lines, and the application cost function of each type of generator unit, etc. The present application does not impose specific limitations.

[0103] Furthermore, in this embodiment of the application, for a power system with N nodes and K lines, the declared cost of all types of resource units can be, but is not limited to, expressed as:

[0104]

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

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

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

[0108] Furthermore, in the embodiments of this application, the expression of the constraint function may be, but is not limited to, as follows:

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] Among them, P ij D represents the power output of generator set j at time t; i (t) represents the load demand of node i at time t, L i (t) represents the system loss at time t on node i; P j and These represent the lower and upper limits of the output power of generator set j, respectively. and These represent the unit's ascent and descent ramping capabilities, respectively; u j (t) represents the operating state of unit j at time t, where 1 indicates operation and 0 indicates shutdown; SU j With SD j These represent start-up and stop restrictions, respectively; R ij (t) represents the reserve capacity provided by unit j at node i; R SYS Indicates the total reserve capacity of the system; F k-i This represents the power generation transfer distribution factor of node i to line k; This indicates the capacity of the line.

[0118] Equation (4) represents the system supply and demand balance constraint, where the total power generation of the system is the total load demand plus system losses; Equation (5) represents the unit power generation output constraint, where the power generation of a single unit is within its minimum and maximum output range; Equation (6) represents the unit ramping constraint, where the power change of the unit between two adjacent moments is within its ramping capacity range; Equations (7) and (8) represent the start-up and shutdown constraints of thermal power units, namely coal-fired power and gas-fired power units; Equation (9) represents the system reserve constraint; Equations (10) and (11) represent the system line transmission capacity constraint.

[0119] The working principle of the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework proposed in this application will be described in detail below with reference to a specific embodiment.

[0120] in, Figure 3 This is a flowchart illustrating the working principle of a multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework provided in one embodiment of this application.

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

[0122] Step S302: Propose a method for optimizing the allocation of power resources by coordinating the different types of power system dispatching under different time scales.

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

[0124] Step S304: Construct a safe, economical, low-carbon, multi-value collaborative scheduling framework based on new energy dispatching methods, power resource optimization allocation methods, and probabilistic balance system characteristics and decoupling methods.

[0125] Step S305: Obtain the physical architecture information and unit application information of the power system, determine the constraints of the power system, and generate the constraint function of the unit cost assessment model.

[0126] Step S306: Construct a model for minimizing the power demand scheduling cost of generating units.

[0127] Step S307: Construct a model to maximize the benefits of unit participation in scheduling.

[0128] Step S308: Using the unit power demand dispatch cost minimization model as the lower layer and the unit participation in dispatch benefit maximization model as the upper layer, construct a unit cost evaluation model under the power system's safety-economy-low-carbon multi-value collaborative dispatch framework.

[0129] Step S309: Obtain the power dispatch amount and ancillary service dispatch amount of each type of unit through the lower-level unit power demand dispatch cost minimization model, return to the upper-level unit participation in dispatch to maximize benefits model, and through a recursive optimization process, use the unit cost evaluation model to obtain the full value evaluation result of the endogenous and external comprehensive cost of unit participation in power dispatch and ancillary service dispatch.

[0130] According to the multi-dimensional cost assessment method based on the multi-value collaborative dispatch framework proposed in this application, the safety-economy-low-carbon multi-value collaborative dispatch framework of the power system can be determined first. Then, based on the power energy dispatch demand information and ancillary service dispatch demand information, a model for minimizing the unit power demand dispatch cost of the power system can be constructed. Through payment information and environmental premium information, a model for maximizing the benefits of unit participation in dispatch can be constructed. Then, using the unit power demand dispatch cost minimization model and the model for maximizing the benefits of unit participation in dispatch, a unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework can be constructed to obtain the full value assessment result of the comprehensive cost of the power system's endogenous and externalities. It comprehensively considers the operation and dispatch of units in multiple categories such as power energy, ancillary services, capacity compensation, and carbon trading, and integrates the endogenous and external costs including safety, economy, and low carbon. This provides a mechanism for the comprehensive recovery of unit costs and the multi-dimensional assessment of unit value in the power system. In addition, considering the supporting role of the multi-value collaborative dispatch framework for the large-scale grid connection of new energy, this application embodiment can effectively incentivize unit participation under the future energy situation, promote the development of the system towards environmental protection and efficiency, and ensure that all participating entities benefit. This solves the problem in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that it is impossible to achieve comprehensive feedback and synergy of the value, safety value, and green value of various main electrical energy components in the power system while meeting the requirements of safe supply, low-carbon transformation, and economy.

[0131] Next, referring to the accompanying drawings, a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework proposed in this application is described.

[0132] Figure 4 This is a block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework provided in an embodiment of this application.

[0133] like Figure 4 As shown, the multi-dimensional cost evaluation device 40 based on the multi-value collaborative scheduling framework is applied in the model building stage. 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 collaborative dispatch framework of the power system.

[0135] The first construction module 402 is used to obtain the power energy dispatch demand information and ancillary service dispatch demand information of the power system, and based on the power energy dispatch demand information and ancillary service dispatch demand information, combined with the safety-economy-low carbon multi-value collaborative dispatch framework, to construct a unit power demand dispatch 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 assessment model for the power system under the framework of safe-economic-low-carbon multi-value collaborative dispatch, based on the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, so as to obtain the full value assessment result of the power system's endogenous and external comprehensive costs using the unit cost assessment model.

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

[0139] The first acquisition unit is used to acquire the physical architecture information of the power system and the unit application information.

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

[0141] The generation unit is used to generate constraint functions for the unit cost assessment model based on constraint information, and then generate the unit cost assessment model based on the constraint functions.

[0142] Optionally, in one embodiment of this application, the determining module 401 includes: a second obtaining unit, a third obtaining unit, a fourth obtaining unit, and a constructing unit.

[0143] The second acquisition unit is used to acquire a new energy dispatching method that satisfies at least one of the following: power system operating conditions, policy value conditions, and time and space boundary conditions.

[0144] The third acquisition unit is used to acquire methods for optimizing the allocation of power resources by coordinating different types of power system dispatching at different time scales.

[0145] The fourth acquisition unit is used to acquire the probabilistic balance system characteristics and decoupling methods of the power system under the large-scale grid connection of new energy sources.

[0146] The building blocks are used to construct a safe, economical, low-carbon, multi-value collaborative scheduling framework based on new energy scheduling methods, power resource optimization allocation methods, and probabilistic balance system characteristics and decoupling methods.

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

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] Among them, P ij D represents the power output of generator set j at time t; i (t) represents the load demand of node i at time t, L i (t) represents the system loss at time t on node i; P j and These represent the lower and upper limits of the output power of generator set j, respectively. and These represent the unit's ascent and descent ramping capabilities, respectively; u j (t) represents the operating state of unit j at time t, where 1 indicates operation and 0 indicates shutdown; SU j With SD j These represent start-up and stop restrictions, respectively; R ij (t) represents the reserve capacity provided by unit j at node i; R SYS Indicates the total reserve capacity of the system; F k-i This represents the power generation transfer distribution factor of node i to line k; This indicates the capacity of the line.

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

[0158]

[0159] in, This represents the electrical energy dispatch demand of unit j of the m-th power source, where the power source types include coal power, gas power, wind power, photovoltaic power, and hydropower. This represents the energy dispatch cost declared by power generation unit j of type m; This represents the ancillary service scheduling demand of the nth type of power unit j, where the power types include coal power, gas power, and hydropower. This indicates the ancillary service scheduling result declared by power unit j of type n.

[0160] Optionally, in one embodiment of this application, the expression for the model that maximizes the benefits of unit participation in scheduling can be, but is not limited to, the following:

[0161]

[0162] in, This represents the electrical energy dispatch demand of power generation unit j of type m, where the power sources include coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower; R EN This represents the cost the system pays for accessing electrical energy; R represents the ancillary service dispatch demand of power generation unit j of type n, where the power types include coal-fired power, gas-fired power, and hydropower; ANS This indicates the system's cost for calling ancillary service payment units; Pc j R represents the amount of electricity generated by coal-fired power unit j that participates in capacity compensation; CAP This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine; Ew represents the environmental premium declared by the wind turbine itself. This indicates the amount of electricity used by the photovoltaic (PV) generator; Es represents the environmental premium declared by the PV generator itself. R represents the carbon emissions of unit j in class g; CAB Indicates the carbon trading cost within the system; β g This represents the carbon trading factor for Class g generating units, which include both coal-fired and gas-fired power plants.

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

[0164] According to the multi-dimensional cost assessment device based on the multi-value collaborative scheduling framework proposed in this application, the safety-economy-low-carbon multi-value collaborative scheduling framework of the power system can be determined first. Then, based on the power energy scheduling demand information and the ancillary service scheduling demand information, a model for minimizing the unit power demand scheduling cost of the power system is constructed. Through payment information and environmental premium information, a model for maximizing the benefits of unit participation in scheduling is constructed. Then, using the model for minimizing the unit power demand scheduling cost and the model for maximizing the benefits of unit participation in scheduling, a unit cost assessment model of the power system under the safety-economy-low-carbon multi-value collaborative scheduling framework is constructed. The result is a full-value assessment of the comprehensive cost of the power system's endogenous and externalities. It comprehensively considers the operation and scheduling of units in multiple categories such as power energy, ancillary services, capacity compensation, and carbon trading, and integrates the endogenous and external costs including safety, economy, and low carbon. This provides a mechanism for the comprehensive recovery of unit costs and the multi-dimensional assessment of unit value in the power system. In addition, considering the supporting role of the multi-value collaborative scheduling framework for the large-scale grid connection of new energy, this application embodiment can effectively incentivize unit participation under the future energy situation, promote the development of the system towards environmental protection and efficiency, and ensure that all participating entities benefit. This solves the problem in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that it is impossible to achieve comprehensive feedback and synergy of the value, safety value, and green value of various main electrical energy components in the power system while meeting the requirements of safe supply, low-carbon transformation, and economy.

[0165] The above embodiments describe the model building stage. The following describes embodiments of the model application stage.

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

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

[0168] In step S501, at least one of the following is obtained: actual physical architecture information of the actual power system, actual generating unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information.

[0169] In step S502, at least one of the following information is input into the pre-built unit cost assessment model: actual physical architecture information of the actual power system, actual unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information. This is to obtain the actual full value assessment result of the comprehensive cost of the endogenous and externalities of the actual power system. The pre-built unit cost assessment model includes a unit power demand dispatch cost minimization model and a unit participation in dispatch benefit maximization model.

[0170] In some embodiments, this application can obtain actual physical architecture information of the actual power system, actual unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information, and input the above information into a pre-built unit cost assessment model. The power dispatch amount and ancillary service dispatch amount of each type of unit are obtained through the unit power demand dispatch cost minimization model in the lower layer of the unit cost assessment model. This is then returned to the unit participation in dispatch benefit maximization model in the upper layer of the unit cost assessment model. Through a recursive optimization process, the actual full value assessment result of the comprehensive cost of the endogenous and externalities of the unit's participation in power dispatch and ancillary service dispatch is obtained.

[0171] According to the multi-value collaborative scheduling framework proposed in this application, the multi-dimensional cost assessment method can input information such as the actual physical architecture of the actual power system, actual unit applications, actual power dispatching needs, actual ancillary service dispatching needs, actual payments, and actual environmental premiums into a pre-built unit cost assessment model. Through a recursive optimization process, the actual full-value assessment result of the comprehensive cost of the unit's participation in power dispatching and ancillary service dispatching, including both endogenous and external costs, is obtained. This method comprehensively considers the unit's operation and dispatching across multiple categories such as power, ancillary services, capacity compensation, and carbon trading, integrating endogenous and external costs including safety, economy, and low carbon emissions. This provides a mechanism for the comprehensive recovery of unit costs and the multi-dimensional assessment of unit value in the power system. Furthermore, considering the supporting role of the multi-value collaborative scheduling framework for the large-scale grid connection of new energy sources, this application can effectively incentivize unit participation under future energy conditions, promote the system's development towards environmental protection and efficiency, and ensure that all participating entities benefit. This solves the problem in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that it is impossible to achieve comprehensive feedback and synergy of the value, safety value, and green value of various main electrical energy components in the power system while meeting the requirements of safe supply, low-carbon transformation, and economy.

[0172] Next, referring to the accompanying drawings, a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework proposed in this application is described.

[0173] Figure 6 This is a block diagram of a multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework according to another embodiment of this 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. The device 60 includes an acquisition module 601 and an evaluation module 602.

[0175] The acquisition module 601 is used to acquire at least one of the following: actual physical architecture information of the actual power system, actual unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information.

[0176] The evaluation module 602 is used to input at least one of the following into a pre-built unit cost evaluation model: actual physical architecture information of the actual power system, actual unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information, so as to obtain the actual full value evaluation result of the comprehensive cost of the endogenous and externalities of the actual power system. The pre-built unit cost evaluation model includes a unit power demand dispatch cost minimization model and a unit participation in dispatch benefit maximization model.

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

[0178] The multi-dimensional cost assessment device based on the multi-value collaborative scheduling framework proposed in this application can input information such as the actual physical architecture of the actual power system, actual unit applications, actual power dispatching needs, actual ancillary service dispatching needs, actual payments, and actual environmental premiums into a pre-built unit cost assessment model. Through a recursive optimization process, the actual full-value assessment result of the comprehensive cost of the unit's participation in power dispatching and ancillary service dispatching, including both endogenous and external costs, is obtained. This comprehensively considers the unit's operation and dispatching across multiple categories such as power, ancillary services, capacity compensation, and carbon trading, integrating endogenous and external costs including safety, economy, and low carbon emissions. This provides a mechanism for the comprehensive recovery of unit costs and the multi-dimensional assessment of unit value in the power system. Furthermore, considering the supporting role of the multi-value collaborative scheduling framework for the large-scale grid connection of new energy sources, this application embodiment can effectively incentivize unit participation under future energy conditions, promote the system's development towards environmental protection and efficiency, and ensure that all participating entities benefit. This solves the problem in related technologies that it is difficult to comprehensively consider the cost assessment that combines stable energy supply, orderly resource regulation, and clean, environmentally friendly, and low-carbon aspects, and that it is impossible to achieve comprehensive feedback and synergy of the value, safety value, and green value of various main electrical energy components in the power system while meeting the requirements of 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 this application. The electronic device may include:

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

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

[0182] Furthermore, electronic devices also include:

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

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

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

[0186] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

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

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

[0189] This application also provides a computer-readable storage medium storing a computer program 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] This application also provides a computer program product, including a computer program that, when executed, implements the multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework as described above.

[0191] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

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

[0193] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0194] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0195] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0196] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0197] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0198] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this 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 phase, the method includes the following steps: Establish a multi-value collaborative dispatch framework for the power system, encompassing security, economy, and low carbon emissions. Obtain the power energy dispatch demand information and ancillary service dispatch demand information of the power system, and based on the power energy dispatch demand information and the ancillary service dispatch demand information, and in conjunction with the safety-economy-low-carbon multi-value collaborative dispatch framework, construct a unit power demand dispatch cost minimization model for the power system. The payment information and environmental premium information of the power system are obtained, and based on the payment information and environmental premium information, combined with the safety-economy-low-carbon multi-value collaborative scheduling framework, a model for maximizing the benefits of the power system's units participating in scheduling is constructed. Based on the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, a unit cost assessment model for the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework is constructed to obtain the full value assessment result of the power system's endogenous and external comprehensive costs using the unit cost assessment model. The expression for the unit power demand dispatch cost minimization model is as follows: ， in, Indicates the first Units with similar power supplies The demand for electricity dispatch includes coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower. Indicates the first Type of power supply unit The declared power dispatch cost; Indicates the first Type of power supply unit The ancillary service scheduling demand includes coal-fired power, gas-fired power, and hydropower. Indicates the first Type of power supply unit The reported cost of dispatching auxiliary services; The expression for the model that maximizes the benefits of unit participation in scheduling is: ， in, This represents the cost the system pays for accessing electrical energy; This indicates the system's cost for calling auxiliary service payment units; Indicates coal-fired power units The amount of electricity used for capacity compensation; This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine generator; This refers to the environmental premium declared by the wind turbine generator itself. This indicates the amount of electrical energy utilized by the photovoltaic (PV) generator. This refers to the environmental premium declared by the photovoltaic power generation unit itself; Indicates the first Type of unit Carbon emissions; This indicates the carbon trading fees within the system; Indicates the first Carbon trading coefficients for different types of generating units, including coal-fired and gas-fired power plants.

2. The method according to claim 1, characterized in that, The construction of the unit cost assessment model for the power system under the framework of safe-economic-low-carbon multi-value collaborative dispatch includes: Obtain the physical architecture information and unit application information of the power system; Based on the physical architecture information and the unit application information, the binding information of the power system is determined; The constraint function of the unit cost assessment model is generated based on the constraint information, and the unit cost assessment model is generated based on the constraint function.

3. The method according to claim 1, characterized in that, The framework for determining the safety-economy-low-carbon multi-value coordinated dispatch of the power system includes: A new energy dispatching method that satisfies at least one of the power system operating conditions, policy value conditions, and time-space boundary conditions; A method for optimizing the allocation of power resources by coordinating the various dispatching methods of the power system at different time scales; Obtain the probabilistic balance system characteristics and decoupling method of the power system under large-scale grid connection of new energy sources; Based on the new energy dispatching method, the power resource optimization allocation method, and the probabilistic balance system characteristics and decoupling method, the safe-economic-low-carbon multi-value collaborative dispatching framework is constructed.

4. The method according to claim 2, characterized in that, The expression for the constraint function is: ， ， ， ， ， ， ， ， in, Represents a node generator set At any moment The power generation capacity; Represents a node At any moment The load demand, Represents a node Last moment System losses; and They represent generator sets respectively. The lower and upper limits of output power; and These represent the unit's climbing and descent ramping capabilities, respectively. express Time crew The power-on status is indicated by 1 for power-on and 0 for power-off. and These represent the start-up and stop restrictions, respectively. Represents a node unit At any moment Provided spare capacity; This indicates the total reserve capacity of the system; Represents a node For the line The power generation transfer distribution factor; Indicates the capacity of the line; Represents a node The power generation capacity; Represents a node The load power.

5. A multi-dimensional cost evaluation method based on a multi-value collaborative scheduling framework, characterized in that, When applied to the model application phase, the method includes the following steps: Obtain at least one of the following: actual physical architecture information of the actual power system, actual unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information; At least one of the following information is input into a pre-built unit cost assessment model: the actual physical architecture information of the actual power system, the actual unit application information, the actual power dispatch demand information, the actual ancillary service dispatch demand information, the actual payment information, and the actual environmental premium information. This results in the actual full value assessment of the endogenous and external costs of the actual power system. The pre-built unit cost assessment model includes a unit power demand dispatch cost minimization model and a unit participation in dispatch benefit maximization model. The expression for the unit power demand dispatch cost minimization model is as follows: ， in, Indicates the first Units with similar power supplies The demand for electricity dispatch includes coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower. Indicates the first Type of power supply unit The declared power dispatch cost; Indicates the first Type of power supply unit The ancillary service scheduling demand includes coal-fired power, gas-fired power, and hydropower. Indicates the first Type of power supply unit The reported cost of dispatching auxiliary services; The expression for the model that maximizes the benefits of unit participation in scheduling is: ， in, This represents the cost the system pays for accessing electrical energy; This indicates the system's cost for calling auxiliary service payment units; Indicates coal-fired power units The amount of electricity used for capacity compensation; This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine generator; This refers to the environmental premium declared by the wind turbine generator itself. This indicates the amount of electrical energy utilized by the photovoltaic (PV) generator. This refers to the environmental premium declared by the photovoltaic power generation unit itself; Indicates the first Type of unit Carbon emissions; This indicates the carbon trading fees within the system; Indicates the first Carbon trading coefficients for different types of generating units, including coal-fired and gas-fired power plants.

6. A multi-dimensional cost evaluation device based on a multi-value collaborative scheduling framework, characterized in that, Applied to the model building phase, wherein the apparatus includes: The module is used to determine the safety-economic-low-carbon multi-value collaborative dispatch framework for the power system. The first construction module is used to obtain the power energy dispatch demand information and ancillary service dispatch demand information of the power system, and based on the power energy dispatch demand information and the ancillary service dispatch demand information, combined with the safety-economy-low carbon multi-value collaborative dispatch framework, to 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 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. The third construction module is used to construct a unit cost assessment model for the power system under the safety-economy-low-carbon multi-value collaborative dispatch framework based on the unit power demand dispatch cost minimization model and the unit participation in dispatch benefit maximization model, so as to obtain the full value assessment result of the power system's endogenous and external comprehensive costs using the unit cost assessment model. The expression for the unit power demand dispatch cost minimization model is as follows: ， in, Indicates the first Units with similar power supplies The demand for electricity dispatch includes coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower. Indicates the first Type of power supply unit The declared power dispatch cost; Indicates the first Type of power supply unit The ancillary service scheduling demand includes coal-fired power, gas-fired power, and hydropower. Indicates the first Type of power supply unit The reported cost of dispatching auxiliary services; The expression for the model that maximizes the benefits of unit participation in scheduling is: ， in, This represents the cost the system pays for accessing electrical energy; This indicates the system's cost for calling auxiliary service payment units; Indicates coal-fired power units The amount of electricity used for capacity compensation; This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine generator; This refers to the environmental premium declared by the wind turbine generator itself. This indicates the amount of electrical energy utilized by the photovoltaic (PV) generator. This refers to the environmental premium declared by the photovoltaic power generation unit itself; Indicates the first Type of unit Carbon emissions; This indicates the carbon trading fees within the system; Indicates the first Carbon trading coefficients for different types of generating units, including coal-fired and gas-fired power plants.

7. The apparatus according to claim 6, characterized in that, The third building module includes: The first acquisition unit is used to acquire the physical architecture information and unit application information of the power system; The determining unit is used to determine the binding information of the power system based on the physical architecture information and the unit application information; The generation unit is used to generate constraint functions for the unit cost assessment model based on the constraint information, so as to generate the unit cost assessment model based on the constraint functions.

8. The apparatus according to claim 6, characterized in that, The determining module includes: The second acquisition unit is used to acquire 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. The third acquisition unit is used to acquire the power resource optimization allocation method that coordinates the power system dispatch types under different time scales; The fourth acquisition unit is used to acquire the probabilistic balance system characteristics and decoupling method of the power system under the large-scale grid connection of new energy sources; The construction unit is used to construct the safe-economic-low-carbon multi-value collaborative scheduling framework based on the new energy scheduling method, the power resource optimization allocation method, and the probabilistic balance system characteristics and decoupling method.

9. The apparatus according to claim 7, characterized in that, The expression for the constraint function is: ， ， ， ， ， ， ， ， in, Represents a node generator set At any moment The power generation capacity; Represents a node At any moment The load demand, Represents a node Last moment System losses; and They represent generator sets respectively. The lower and upper limits of output power; and These represent the unit's climbing and descent ramping capabilities, respectively. express Time crew The power-on status is indicated by 1 for power-on and 0 for power-off. and These represent the start-up and stop restrictions, respectively. Represents a node unit At any moment Provided spare capacity; This indicates the total reserve capacity of the system; Represents a node For the line The power generation transfer distribution factor; Indicates the capacity of the line; Represents a node The power generation capacity; Represents a node The load power.

10. 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 includes: The acquisition module is used to acquire at least one of the following: actual physical architecture information of the actual power system, actual generating unit application information, actual power dispatch demand information, actual ancillary service dispatch demand information, actual payment information, and actual environmental premium information. The evaluation module is used to input at least one of the actual physical architecture information of the actual power system, the actual unit application information, the actual power dispatch demand information, the actual ancillary service dispatch 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 comprehensive cost of the endogenous and externalities of the actual power system. The pre-built unit cost evaluation model includes a unit power demand dispatch cost minimization model and a unit participation in dispatch benefit maximization model. The expression for the unit power demand dispatch cost minimization model is as follows: ， in, Indicates the first Units with similar power supplies The demand for electricity dispatch includes coal-fired power, gas-fired power, wind power, photovoltaic power, and hydropower. Indicates the first Type of power supply unit The declared power dispatch cost; Indicates the first Type of power supply unit The ancillary service scheduling demand includes coal-fired power, gas-fired power, and hydropower. Indicates the first Type of power supply unit The reported cost of dispatching auxiliary services; The expression for the model that maximizes the benefits of unit participation in scheduling is: ， in, This represents the cost the system pays for accessing electrical energy; This indicates the system's cost for calling auxiliary service payment units; Indicates coal-fired power units The amount of electricity used for capacity compensation; This indicates the capacity compensation paid by the system. This indicates the amount of electrical energy and ancillary services requested by the wind turbine generator; This refers to the environmental premium declared by the wind turbine generator itself. This indicates the amount of electrical energy utilized by the photovoltaic (PV) generator. This refers to the environmental premium declared by the photovoltaic power generation unit itself; Indicates the first Type of unit Carbon emissions; This indicates the carbon trading fees within the system; Indicates the first Carbon trading coefficients for different types of generating units, including coal-fired and gas-fired power plants.

11. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework as described in any one of claims 1-4 or claim 5.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the multi-dimensional cost evaluation method based on the multi-value collaborative scheduling framework as described in any one of claims 1-4 or claim 5.

13. A computer program product, characterized in that, Includes a computer program, which, when executed, is used to implement the multi-dimensional cost assessment method based on a multi-value collaborative scheduling framework as described in any one of claims 1-4 or claim 5.

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