Multi-virtual power plant energy optimization method and device based on energy-carbon sharing

Abstract

The embodiment of the invention discloses a multi-virtual power plant energy optimization method and device based on energy-carbon sharing. The method comprises the steps of establishing a master-slave game architecture of a power distribution system operator and each virtual power plant based on a transaction electricity price and a transaction carbon price of the power distribution system operator, and a transaction electricity quantity, a transaction carbon quota and equipment output of each virtual power plant; a dynamic pricing model for maximizing the income of a power distribution system operator is constructed based on a master-slave game architecture, an energy management model for minimizing the operation cost of the virtual power plant is constructed based on the master-slave game architecture, and a master-slave game double-layer optimization model for energy-carbon sharing of the multiple virtual power plants is determined based on the dynamic pricing model and the energy management model; and equivalently converting the master-slave game double-layer optimization model into a single-layer optimization model based on a Carlo-demander-Kuhn-Tuck condition, and solving the single-layer optimization model to obtain a target energy management strategy of each virtual power plant, thereby giving consideration to economic benefits and carbon emission reduction.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of energy technology, and in particular to a multi-virtual power plant energy optimization method and device based on energy-carbon sharing. Background Art

[0002] With the development of technology and the promotion of clean energy, virtual power plant technology has been applied to the power industry. Virtual power plant technology can integrate distributed energy and energy storage to form a virtual entity to participate in the power market and help the development of smart grids. Since small virtual power plants are limited by resources when operating independently, a multi-virtual power plant alliance has been formed. Multiple virtual power plants can achieve resource complementarity and enhance synergy through peer-to-peer transactions.

[0003] At present, in the coordination process of multiple virtual power plants, economic dispatch is usually the mainstream. However, with the integration of the carbon trading market into the power sector, optimized dispatch needs to take into account both economic benefits and carbon emission reduction. Through the reasonable allocation and trading of carbon quotas, the system carbon emissions can be optimized to achieve a win-win situation for the economy and the environment. It can be seen that an optimization strategy that takes into account both economic benefits and carbon emission reduction is now needed. Summary of the invention

[0004] The embodiments of the present invention provide a multi-virtual power plant energy optimization method and device based on energy-carbon sharing, so as to accurately and conveniently determine the target energy management strategy of each virtual power plant, thereby taking into account both economic benefits and carbon emission reduction.

[0005] In a first aspect, an embodiment of the present invention provides a multi-virtual power plant energy optimization method based on energy-carbon sharing, comprising:

[0006] Based on the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity volume, transaction carbon quota and equipment output of each virtual power plant, a master-slave game architecture between the distribution system operator and each virtual power plant is established;

[0007] A dynamic pricing model for maximizing the revenue of distribution system operators is constructed based on the master-slave game architecture, and an energy management model for minimizing the operating costs of virtual power plants is constructed based on the master-slave game architecture, and a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants is determined based on the dynamic pricing model and the energy management model;

[0008] Based on the Carlo-Kuhn-Tucker condition, the master-slave game two-layer optimization model is equivalently transformed into a single-layer optimization model, and the single-layer optimization model is solved to obtain the target energy management strategy of each virtual power plant.

[0009] Optionally, the method also includes: the trading electricity price includes: the market trading electricity price between the distribution system operator and the electricity market and the power plant trading electricity price between the distribution system operator and each virtual power plant; the trading carbon price includes: the market trading carbon price between the distribution system operator and the carbon market and the power plant trading carbon price between the distribution system operator and each virtual power plant.

[0010] Optionally, the method also includes: the traded electricity includes: the market traded electricity between the distribution system operator and the electricity market and the power plant traded electricity between the distribution system operator and each virtual power plant; the traded carbon quota includes: the market traded carbon quota between the distribution system operator and the electricity market and the power plant traded carbon quota between the distribution system operator and each virtual power plant.

[0011] Optionally, the method further includes: converting the energy management model in the master-slave game two-layer optimization model into constraint conditions; and converting the dynamic pricing model in the master-slave game two-layer optimization model into a single-layer optimization model.

[0012] Optionally, the method further includes: converting the energy management model in the master-slave game two-level optimization model into equality constraints and complementary relaxation conditions; and converting the complementary relaxation conditions into linear inequality constraints.

[0013] Optionally, the method also includes: linearizing the nonlinear terms of the dynamic pricing model in the master-slave game two-layer optimization model based on the duality theorem of linear programming to determine the equivalent linearized expression of the nonlinear terms; and determining the single-layer optimization model based on the equivalent linearized expression and the linear terms of the dynamic pricing model in the master-slave game two-layer optimization model.

[0014] In a second aspect, an embodiment of the present invention further provides a multi-virtual power plant energy optimization device based on energy-carbon sharing, the device comprising:

[0015] A master-slave game architecture establishment module is used to establish a master-slave game architecture between the distribution system operator and each virtual power plant based on the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity, transaction carbon quota and equipment output of each virtual power plant;

[0016] A master-slave game two-layer optimization model determination module is used to construct a dynamic pricing model that maximizes the benefits of distribution system operators based on the master-slave game architecture, and to construct an energy management model that minimizes the operating costs of virtual power plants based on the master-slave game architecture, and to determine a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model;

[0017] The target energy management strategy determination module is used to convert the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition, and solve the single-layer optimization model to obtain the target energy management strategy of each virtual power plant.

[0018] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0019] one or more processors;

[0020] A memory for storing one or more programs;

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-virtual power plant energy optimization method based on energy-carbon sharing as provided in any embodiment of the present invention.

[0022] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a multi-virtual power plant energy optimization method based on energy-carbon sharing as provided in any embodiment of the present invention.

[0023] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements a multi-virtual power plant energy optimization method based on energy-carbon sharing as provided in any embodiment of the present invention.

[0024] The technical solution of the embodiment of the present invention is to establish a master-slave game framework between the distribution system operator and each virtual power plant based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant; construct a dynamic pricing model that maximizes the profit of the distribution system operator based on the master-slave game framework, and construct an energy management model that minimizes the operating cost of the virtual power plant based on the master-slave game framework, and determine a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model; based on the Carlo-Kuhn-Tucker condition, the master-slave game two-layer optimization model is equivalently converted into a single-layer optimization model, so that multi-objective optimization can be converted into single-objective optimization, and the single-layer optimization model is solved to determine the optimal solution corresponding to the Stackelberg equilibrium, and then obtain the target energy management strategy of each virtual power plant, so as to achieve both economic benefits and carbon emission reduction.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 is a flow chart of a multi-virtual power plant energy optimization method based on energy-carbon sharing provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is an example diagram of a master-slave game architecture between a distribution system operator and multiple virtual power plants involved in the first embodiment of the present invention;

[0029] Figure 3 is a flow chart of a multi-virtual power plant energy optimization method based on energy-carbon sharing provided in Embodiment 2 of the present invention;

[0030] Figure 4 It is a structural schematic diagram of a multi-virtual power plant energy optimization device based on energy-carbon sharing provided in Embodiment 3 of the present invention;

[0031] Figure 5 It is a structural schematic diagram of an electronic device for implementing the multi-virtual power plant energy optimization method based on energy-carbon sharing according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] Embodiment 1

[0035] Figure 1 A flowchart of a multi-virtual power plant energy optimization method based on energy-carbon sharing is provided for the first embodiment of the present invention. This embodiment can be applied to the case of determining the target energy management strategy of each virtual power plant that takes into account both economic benefits and carbon emission reduction. The method can be executed by a multi-virtual power plant energy optimization device based on energy-carbon sharing. The multi-virtual power plant energy optimization device based on energy-carbon sharing can be implemented in the form of hardware and / or software. The multi-virtual power plant energy optimization device based on energy-carbon sharing can be configured in an electronic device. Figure 1 As shown, the method includes:

[0036] S110. Based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant, a master-slave game architecture is established between the distribution system operator and each virtual power plant.

[0037] In the master-slave game architecture, the distribution system operator (DSO) acts as a leader. In the master-slave game architecture, each virtual power plant (VPP) acts as a follower. The device may refer to a power generation device. For example, the power generation device may be, but is not limited to, a micro gas turbine.

[0038] Based on the above technical solution, the trading electricity price includes: the market trading electricity price between the distribution system operator and the electricity market and the power plant trading electricity price between the distribution system operator and each virtual power plant; the trading carbon price includes: the market trading carbon price between the distribution system operator and the carbon market and the power plant trading carbon price between the distribution system operator and each virtual power plant.

[0039] Based on the above technical solution, the traded electricity volume includes: the market traded electricity volume between the distribution system operator and the electricity market and the power plant traded electricity volume between the distribution system operator and each virtual power plant; the traded carbon quota includes: the market traded carbon quota between the distribution system operator and the electricity market and the power plant traded carbon quota between the distribution system operator and each virtual power plant.

[0040] Specifically, the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity, transaction carbon quota and equipment output of each virtual power plant are obtained. Based on the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity, transaction carbon quota and equipment output of each virtual power plant, a master-slave game architecture between the distribution system operator and each virtual power plant is established. Figure 2 An example diagram of a master-slave game architecture between a distribution system operator and multiple virtual power plants is given. Figure 2 In the master-slave game architecture, the distribution system operator acts as a leader, aggregates the power plant transaction electricity and power plant transaction carbon quotas of each virtual power plant, combines the market transaction electricity price of the power market and the market transaction carbon price of the carbon market, considers the price response behavior of the virtual power plant, and specifies the power plant transaction electricity price and power plant transaction carbon price for the virtual power plant with the goal of maximizing its own interests. Each virtual power plant acts as a follower, accepts the power plant transaction electricity price and power plant transaction carbon price set by the distribution system operator, and reasonably arranges the internal equipment output, and sets the power plant transaction electricity and power plant transaction carbon quota with the distribution system operator with the goal of minimizing its own operating costs.

[0041] S120. Construct a dynamic pricing model that maximizes the revenue of distribution system operators based on the master-slave game architecture, and construct an energy management model that minimizes the operating costs of virtual power plants based on the master-slave game architecture, and determine a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model.

[0042] Among them, the upper layer of the master-slave game two-layer optimization model is the dynamic pricing model, and the lower layer is the energy management model.

[0043] Specifically, the objective function of the dynamic pricing model is as follows:

[0044]

[0045] The values ​​of the parameters in the objective function of the dynamic pricing model are determined as follows:

[0046]

[0047] Among them, U DSO is the profit of DSO, T is the maximum time of the scheduling cycle, I represents the number of VPPs, is the on-grid electricity price in the power market at time t, is the grid electricity price in the power market at time t, is the carbon price sold in the carbon market at time t, is the carbon purchase price in the carbon market at time t, is the electricity purchase price set by DSO at time t, is the electricity price set by DSO at time t, is the carbon purchase price set by DSO at time t, is the carbon price set by DSO at time t, P t DSO,s is the electric power sold by DSO to the electricity market at time t, P t DSO,b is the electric power purchased by DSO from the electricity market at time t, is the carbon quota sold by DSO to the carbon market at time t, is the carbon quota purchased by DSO from the carbon market at time t, is the electric power purchased by the ith VPP from the DSO at time t, is the electric power sold by the ith VPP to the DSO at time t, is the carbon quota purchased by the ith VPP from the DSO at time t, is the carbon quota sold by the ith VPP to the DSO at time t, P t DSO is the total electric power traded between DSO and the power market at time t. If it is greater than zero, it means purchasing electricity from the power market; if it is less than zero, it means selling electricity to the power market. is the total carbon quota traded between DSO and the carbon market at time t.

[0048] It should be noted that in order to ensure that VPPs are willing to trade with DSOs, the electricity and carbon prices set by DSOs should meet the following conditions:

[0049]

[0050] Specifically, the objective function of the energy management model is as follows:

[0051]

[0052] The values ​​of various parameters in the objective function of the energy management model are determined as follows:

[0053]

[0054] in, is the microturbine cost of the ith VPP at time t, is the energy storage cost of the ith VPP at time t, is the interruptible load cost of the ith VPP at time t, ai is the quadratic cost coefficient of the micro gas turbine of the i-th VPP, b i is the first-order cost coefficient of the micro gas turbine of the i-th VPP, c i is the constant cost coefficient of the micro gas turbine of the i-th VPP, is the output power of the micro gas turbine of the i-th VPP at time t, is the energy storage dispatch cost coefficient of the i-th VPP, is the charging and discharging power of the energy storage of the i-th VPP at time t, is the interruption compensation price of the interruptible load of the i-th VPP, is the interruption power of the interruptible load of the i-th VPP at time t.

[0055] It should be noted that the following conditions must be met for VPP to operate internally:

[0056]

[0057]

[0058] in, is the output power of the wind turbine of the i-th VPP at time t, is the predicted value of the load of the ith VPP at time t, is the maximum transaction power between the ith VPP and the DSO, is the maximum output power of the micro gas turbine of the i-th VPP, is the output power of the micro gas turbine of the i-th VPP at time t-1, is the downward ramp rate limit of the micro-turbine of the i-th VPP, is the upward ramp rate limit of the micro gas turbine of the i-th VPP, P i ES is the minimum charging and discharging power of the energy storage of the i-th VPP, is the maximum charging and discharging power of the energy storage of the i-th VPP, is the state of charge of the energy storage of the i-th VPP at time t, is the state of charge of the energy storage of the i-th VPP at time t-1, E i is the energy storage capacity of the i-th VPP, is the lower limit of the energy storage charge state of the i-th VPP, is the upper limit of the energy storage charge state of the i-th VPP, is the initial state of charge of the energy storage of the i-th VPP, is the state of charge of the energy storage of the i-th VPP at time T, is the maximum interruptible load of the i-th VPP, is the maximum output power of the wind turbine of the i-th VPP at time t, MT is the carbon quota coefficient per unit power supply of the micro gas turbine, χ g is the carbon quota coefficient per unit power supply of the grid, δ MT is the carbon emission coefficient per unit power supply of the micro gas turbine, δ g It is the carbon emission coefficient per unit power supply of the power grid. is the dual variable of formula (14), v i,t , is the dual variable of formula (15), u i,t , is the dual variable of formula (16), is the dual variable of formula (17), is the dual variable of formula (18), is the dual variable of formula (19), μ i,t is the dual variable of formula (20), η i,t , is the dual variable of formula (21), σ i is the dual variable of formula (22), is the dual variable of formula (23), is the dual variable of formula (24), is the dual variable of formula (25).

[0059] S130. Based on the Carlo-Kuhn-Tucker condition, the master-slave game two-layer optimization model is equivalently converted into a single-layer optimization model, and the single-layer optimization model is solved to obtain the target energy management strategy of each virtual power plant.

[0060] Among them, the Karush-Kuhn-Tucker Conditions (KKT Conditions) are necessary and sufficient conditions for a nonlinear programming problem to have an optimal solution under certain regular conditions.

[0061] Specifically, the objective function of the energy management model in the master-slave game two-layer optimization model is transformed into the constraint condition of the master-slave game two-layer optimization model by using the Carlo-Kuhn-Tucker condition, thereby converting the master-slave game two-layer optimization model into a single-layer optimization model. The single-layer optimization model is solved, and the power plant transaction electricity price and power plant transaction carbon price are determined based on the optimal solution, and then the power plant transaction electricity price and power plant transaction carbon quota are determined through the power plant transaction electricity price and power plant transaction carbon price, that is, the target energy management strategy of each virtual power plant is obtained.

[0062] On the basis of the above technical scheme, "converting the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition" can include: converting the energy management model in the master-slave game two-layer optimization model into constraints; converting the dynamic pricing model in the master-slave game two-layer optimization model into a single-layer optimization model.

[0063] The technical solution of the embodiment of the present invention establishes a master-slave game framework between the distribution system operator and each virtual power plant based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant; constructs a dynamic pricing model that maximizes the profit of the distribution system operator based on the master-slave game framework, and constructs an energy management model that minimizes the operating cost of the virtual power plant based on the master-slave game framework, and determines a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model; converts the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition, so that multi-objective optimization can be converted into single-objective optimization, and solves the single-layer optimization model to determine the optimal solution corresponding to the Stackelberg equilibrium, and then obtains the target energy management strategy of each virtual power plant, so as to achieve both economic benefits and carbon emission reduction.

[0064] Embodiment 2

[0065] Figure 3 This is a flowchart of a multi-virtual power plant energy optimization method based on energy-carbon sharing provided in the second embodiment of the present invention. Based on the above embodiment, this embodiment describes in detail the process of determining a single-layer optimization model. The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here. Figure 3 As shown, the method includes:

[0066] S310. Based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant, a master-slave game architecture is established between the distribution system operator and each virtual power plant.

[0067] S320. Construct a dynamic pricing model that maximizes the revenue of distribution system operators based on the master-slave game architecture, and construct an energy management model that minimizes the operating costs of virtual power plants based on the master-slave game architecture, and determine a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model.

[0068] S330, converting the energy management model in the master-slave game two-layer optimization model into equality constraints and complementary relaxation conditions.

[0069] The VPP energy management model is replaced by its KKT condition. The lower VPP energy management model is converted into constraint conditions, and its KKT conditions include equality constraint conditions and complementary relaxation conditions.

[0070] The equality constraints are as follows:

[0071]

[0072]

[0073] The complementary relaxation conditions are as follows:

[0074]

[0075] S340. Convert the complementary slack conditions into linear inequality constraints.

[0076] The linear inequality constraints are as follows:

[0077]

[0078]

[0079] in, to are the Boolean variables corresponding to equations (37) to (52), Q (1) To Q (14) are sufficiently large positive numbers corresponding to equations (37) to (52) respectively.

[0080] S350. Based on the duality theorem of linear programming, the nonlinear terms of the dynamic pricing model in the master-slave game two-level optimization model are linearized to determine the equivalent linearized expression of the nonlinear terms.

[0081] Among them, the duality theorem of linear programming shows that at the optimal solution, the objective function values ​​of the original problem and the dual problem are equal. The nonlinearity of the objective function comes from the nonlinear term The nonlinear term can be linearized by the duality theorem to obtain the equivalent linearized expression as follows:

[0082]

[0083] Where f represents the equivalent linearized expression of the nonlinear term.

[0084] S360. Determine a single-layer optimization model based on an equivalent linearized expression and the linear term of a dynamic pricing model in a master-slave game two-layer optimization model.

[0085] Among them, the linear term is The objective function of the single-layer optimization model is as follows:

[0086]

[0087] Among them, the constraints of the objective function of the single-layer optimization model are equations (8) to (9), equations (26) to (36), and equations (53) to (80). The optimal solution of the objective function of the single-layer optimization model constitutes the Stackelberg equilibrium of the master-slave game two-layer optimization model of energy-carbon sharing of multiple virtual power plants.

[0088] S370. Solve the single-layer optimization model to obtain the target energy management strategy of each virtual power plant.

[0089] The technical solution of the embodiment of the present invention converts the energy management model in the master-slave game two-layer optimization model into equality constraints and complementary relaxation conditions; converts the complementary relaxation conditions into linear inequality constraints, thereby converting the two-layer model into a single-layer optimization model. Based on the duality theorem of linear programming, the nonlinear terms of the dynamic pricing model in the master-slave game two-layer optimization model are linearized to determine the equivalent linearized expressions of the nonlinear terms; based on the equivalent linearized expressions and the linear terms of the dynamic pricing model in the master-slave game two-layer optimization model, the single-layer optimization model is determined. Thus, the nonlinear model is converted into a mixed integer linear programming through the KKT condition and the duality theorem, without any approximation, and the optimal solution can be determined accurately and quickly.

[0090] The following is an embodiment of a multi-virtual power plant energy optimization device based on energy-carbon sharing provided by an embodiment of the present invention. The device and the multi-virtual power plant energy optimization method based on energy-carbon sharing in the above-mentioned embodiments belong to the same inventive concept. For details not fully described in the embodiment of the multi-virtual power plant energy optimization device based on energy-carbon sharing, please refer to the above-mentioned embodiment of the multi-virtual power plant energy optimization method based on energy-carbon sharing.

[0091] Embodiment 3

[0092] Figure 4 This is a schematic diagram of the structure of a multi-virtual power plant energy optimization device based on energy-carbon sharing provided in the third embodiment of the present invention. Figure 4 As shown, the device includes: a master-slave game architecture establishment module 410, a master-slave game two-layer optimization model determination module 420 and a target energy management strategy determination module 430.

[0093] Among them, the master-slave game architecture establishment module 410 is used to establish a master-slave game architecture between the distribution system operator and each virtual power plant based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant; the master-slave game two-layer optimization model determination module 420 is used to construct a dynamic pricing model that maximizes the benefits of the distribution system operator based on the master-slave game architecture, and to construct an energy management model that minimizes the operating costs of the virtual power plant based on the master-slave game architecture, and to determine the master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model; the target energy management strategy determination module 430 is used to convert the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo Demand-Kuhn-Tucker condition, and to solve the single-layer optimization model to obtain the target energy management strategy of each virtual power plant.

[0094] The technical solution of the embodiment of the present invention establishes a master-slave game framework between the distribution system operator and each virtual power plant based on the trading electricity price and trading carbon price of the distribution system operator, as well as the trading electricity volume, trading carbon quota and equipment output of each virtual power plant; constructs a dynamic pricing model that maximizes the profit of the distribution system operator based on the master-slave game framework, and constructs an energy management model that minimizes the operating cost of the virtual power plant based on the master-slave game framework, and determines a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model; converts the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition, so that multi-objective optimization can be converted into single-objective optimization, and solves the single-layer optimization model to determine the optimal solution corresponding to the Stackelberg equilibrium, and then obtains the target energy management strategy of each virtual power plant, so as to achieve both economic benefits and carbon emission reduction.

[0095] Based on the above technical solution, the trading electricity price includes: the market trading electricity price between the distribution system operator and the electricity market and the power plant trading electricity price between the distribution system operator and each virtual power plant; the trading carbon price includes: the market trading carbon price between the distribution system operator and the carbon market and the power plant trading carbon price between the distribution system operator and each virtual power plant.

[0096] Based on the above technical solution, the traded electricity volume includes: the market traded electricity volume between the distribution system operator and the electricity market and the power plant traded electricity volume between the distribution system operator and each virtual power plant; the traded carbon quota includes: the market traded carbon quota between the distribution system operator and the electricity market and the power plant traded carbon quota between the distribution system operator and each virtual power plant.

[0097] Based on the above technical solution, the target energy management strategy determination module 430 may include:

[0098] The constraint condition determination submodule is used to convert the energy management model in the master-slave game two-layer optimization model into constraint conditions;

[0099] The single-layer optimization model determines the submodule, which is used to transform the dynamic pricing model in the master-slave game two-layer optimization model into a single-layer optimization model.

[0100] On the basis of the above technical solution, the constraint determination submodule is specifically used for: converting the energy management model in the master-slave game two-layer optimization model into equality constraints and complementary relaxation conditions; converting the complementary relaxation conditions into linear inequality constraints.

[0101] On the basis of the above technical scheme, the single-layer optimization model determination submodule is specifically used for: linearizing the nonlinear terms of the dynamic pricing model in the master-slave game two-layer optimization model based on the duality theorem of linear programming, and determining the equivalent linearized expression of the nonlinear terms; determining the single-layer optimization model based on the equivalent linearized expression and the linear terms of the dynamic pricing model in the master-slave game two-layer optimization model.

[0102] The multi-virtual power plant energy optimization device based on energy-carbon sharing provided in an embodiment of the present invention can execute the multi-virtual power plant energy optimization method based on energy-carbon sharing provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the multi-virtual power plant energy optimization method based on energy-carbon sharing.

[0103] It is worth noting that in the above-mentioned embodiment of multi-virtual power plant energy optimization based on energy-carbon sharing, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0104] Embodiment 4

[0105] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0106] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0107] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0108] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a multi-virtual power plant energy optimization method based on energy-carbon sharing.

[0109] In some embodiments, a multi-virtual power plant energy optimization method based on energy-carbon sharing may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the multi-virtual power plant energy optimization method based on energy-carbon sharing described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute a multi-virtual power plant energy optimization method based on energy-carbon sharing in any other appropriate manner (e.g., by means of firmware).

[0110] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0112] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0113] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0114] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0115] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0116] An embodiment of the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the multi-virtual power plant energy optimization method based on energy-carbon sharing as provided in any embodiment of the present application.

[0117] During the implementation of the computer program product, the computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or a combination thereof, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or a similar programming language. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). The program product and the multi-virtual power plant energy optimization method based on energy-carbon sharing disclosed in each embodiment of the present application belong to the same inventive concept, so it will not be repeated here.

[0118] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0119] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-virtual power plant energy optimization method based on energy-carbon sharing, characterized in that: include: Based on the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity volume, transaction carbon quota and equipment output of each virtual power plant, a master-slave game architecture between the distribution system operator and each virtual power plant is established; A dynamic pricing model for maximizing the revenue of distribution system operators is constructed based on the master-slave game architecture, and an energy management model for minimizing the operating costs of virtual power plants is constructed based on the master-slave game architecture, and a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants is determined based on the dynamic pricing model and the energy management model; Based on the Carlo-Kuhn-Tucker condition, the master-slave game two-layer optimization model is equivalently transformed into a single-layer optimization model, and the single-layer optimization model is solved to obtain the target energy management strategy of each virtual power plant.

2. The method according to claim 1, characterized in that: The transaction electricity price includes: the market transaction electricity price between the distribution system operator and the electricity market and the power plant transaction electricity price between the distribution system operator and each virtual power plant; The trading carbon price includes: the market trading carbon price between the distribution system operator and the carbon market and the power plant trading carbon price between the distribution system operator and each virtual power plant.

3. The method according to claim 1, characterized in that The transaction volume includes: the market transaction volume between the distribution system operator and the power market and the power plant transaction volume between the distribution system operator and each virtual power plant; The trading carbon quotas include: market trading carbon quotas between distribution system operators and electricity markets and power plant trading carbon quotas between distribution system operators and various virtual power plants.

4. The method according to claim 1, characterized in that The method of converting the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition includes: Converting the energy management model in the master-slave game two-layer optimization model into constraint conditions; The dynamic pricing model in the master-slave game two-layer optimization model is converted into a single-layer optimization model.

5. The method according to claim 4, characterized in that The step of converting the energy management model in the master-slave game two-layer optimization model into constraint conditions includes: Converting the energy management model in the master-slave game two-level optimization model into equality constraints and complementary relaxation conditions; The complementary slack conditions are converted into linear inequality constraints.

6. The method according to claim 4, characterized in that The step of converting the dynamic pricing model in the master-slave game two-layer optimization model into a single-layer optimization model includes: Based on the duality theorem of linear programming, the nonlinear terms of the dynamic pricing model in the master-slave game two-level optimization model are linearized to determine an equivalent linearized expression of the nonlinear terms; Based on the equivalent linearized expression and the linear term of the dynamic pricing model in the master-slave game two-layer optimization model, a single-layer optimization model is determined.

7. A multi-virtual power plant energy optimization device based on energy-carbon sharing, characterized in that: The device comprises: A master-slave game architecture establishment module is used to establish a master-slave game architecture between the distribution system operator and each virtual power plant based on the transaction electricity price and transaction carbon price of the distribution system operator, as well as the transaction electricity, transaction carbon quota and equipment output of each virtual power plant; A master-slave game two-layer optimization model determination module is used to construct a dynamic pricing model that maximizes the benefits of distribution system operators based on the master-slave game architecture, and to construct an energy management model that minimizes the operating costs of virtual power plants based on the master-slave game architecture, and to determine a master-slave game two-layer optimization model for energy-carbon sharing of multiple virtual power plants based on the dynamic pricing model and the energy management model; The target energy management strategy determination module is used to convert the master-slave game two-layer optimization model into a single-layer optimization model based on the Carlo-Kuhn-Tucker condition, and solve the single-layer optimization model to obtain the target energy management strategy of each virtual power plant.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-virtual power plant energy optimization method based on energy-carbon sharing as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the multi-virtual power plant energy optimization method based on energy-carbon sharing as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the multi-virtual power plant energy optimization method based on energy-carbon sharing as described in any one of claims 1 to 6.

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