Node marginal electricity price-based direct-current transmission control method and system for power system

Abstract

The invention discloses an electric power system direct current delivery control method and system based on node marginal electricity price, and the method comprises the steps: building an electric power system optimization model based on the operation parameter information of an electric power system; constructing a node marginal electricity price model; obtaining a node marginal electricity price according to a node marginal electricity price model based on an output result of the power system optimization model; updating a unit output strategy in the power system optimization model based on the node marginal electricity price, further solving the node marginal electricity price based on the updated power system optimization model, and iterating until the node marginal electricity price and the unit output are unchanged to obtain the unit output at the moment; and controlling the unit output power of the electric power system to output power to the unit, thereby realizing control on the direct-current transmission power of the electric power system. The utilization rate of the hydroelectric generating set can be increased, abandoned water is reduced, power transmission blockage can be effectively reduced, and the stability and economical efficiency of a power system are improved.

Description

Technical Field

[0001] The invention relates to a method and system for controlling direct current transmission of an electric power system based on node marginal electricity price. Background Art

[0002] Building a new power system based on new energy sources such as wind, light, and water to replace the traditional power system based on thermal power will become the top priority of energy transformation. Hydropower accounts for about 71% of all renewable energy on the earth. It has the advantages of strong adaptability, high cost performance, reliability and efficiency, and is the cornerstone of the energy transformation process.

[0003] Due to the obvious seasonal fluctuations of hydropower, the output of hydropower is weak during the dry season, and thermal power is needed to assist the power system; in the flood season, the phenomenon of "water abandonment" is serious, resulting in serious waste of resources and affecting the stable operation of the power system; in addition, new energy and large hydropower bases are usually far away from the load center and are difficult to support the power grid. The cross-regional transmission of clean energy through lines can reduce the loss of water resources and enhance the support capacity of hydropower units for the power system. It is an important means to absorb water and light resources and give full play to the peak load potential of hydropower units.

[0004] Due to the access of a large number of distributed new energy sources and adjustable loads, the "double high" characteristics of the new power system are becoming more and more obvious, and it is gradually entering the "AC / DC hybrid" era with power electronics characteristics. With the development of power electronic devices, based on the original self-parallel excitation system, a new fully controlled device excitation system with high-power power electronic fully controlled device rectification has gradually become the future development trend. The fully controlled excitation system can reduce the low-frequency oscillation of the power system and improve the stability of the system. Furthermore, with the increase in the capacity of power electronic devices, the fully controlled device excitation system can not only provide excitation current for hydropower units, but also provide additional reactive power for the power system, providing stronger reactive support for the DC transmission of hydropower units. Therefore, using fully controlled device excitation technology to construct an economically reasonable DC system transmission strategy will become an important research direction for the development of new power systems.

[0005] With the increase in the proportion of new energy units in new power systems, the uncertainty of power flow in the power grid has increased. Large-scale power transmission has made the transmission line congestion problem more serious, greatly increased the cost of power transmission, and affected the enthusiasm for power market construction. Transmission congestion has become an urgent problem to be solved. Although the transmission congestion problem can be solved by planning and expanding the transmission network, it is easily restricted by objective factors such as the geographical environment. In addition, transmission congestion generally occurs during peak hours or under special operating modes. Blind network expansion cannot fully utilize the transmission capacity of the line and generates redundant investment. In contrast, by designing a reasonable market mechanism, using price signals and other methods to prompt market players to adjust the transmission plan and alleviate the contradiction between it and the system transmission capacity is considered to be a more practical and feasible congestion management method, and has been widely studied and applied. Therefore, the node marginal price, as a price that can reflect the dispatching instructions that can meet the load and the lowest power generation cost at any time and any node, is widely used in power system congestion management.

[0006] In summary, using node marginal electricity price to manage congestion of DC transmission in hydropower system has important research value and application prospects. However, there are few studies on this direction, which led to this case. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for controlling direct current transmission of a power system based on node marginal electricity prices. Taking the minimum electricity cost of power users as the objective function, the node marginal electricity price and the direct current transmission power strategy of the hydropower system are calculated, which can not only improve the utilization rate of hydropower units and reduce water abandonment, but also effectively reduce transmission congestion and improve the stability and economy of the power system.

[0008] In order to achieve the above object, the solution of the present invention is:

[0009] A method for controlling direct current transmission of a power system based on node marginal electricity price, comprising:

[0010] Construct a power system optimization model based on power system operation parameter information;

[0011] Construct node marginal electricity price model;

[0012] Based on the output result of the power system optimization model, the node marginal electricity price is obtained according to the node marginal electricity price model; then the unit output strategy in the power system optimization model is updated based on the node marginal electricity price, and the node marginal electricity price is further solved based on the updated power system optimization model, and it is iterated until the node marginal electricity price and the unit output remain unchanged, so as to obtain the unit output at this time;

[0013] The output power of the power system unit is controlled to be the output of the unit, thereby realizing the control of the DC output power of the power system.

[0014] Among them, the power system optimization model is constructed with the goal of maximizing the total operating profit of the power system. Its objective function is expressed as follows:

[0015] maxF=f p +f ess -f spill

[0016]

[0017] Where: F is the total operating income of the system; f p 、f ess 、f spill are power generation income, energy storage income and water abandonment penalty, respectively, sell , uess , dess , spill represents the electricity selling price of the generator set, the electricity selling price of the energy storage unit, the electricity purchasing price of the energy storage system and the penalty cost of water abandonment respectively; P hp,i,t , P wt,i,t , P pv,i,t , P uess,i,t , P dess,i,t Respectively represent the output of hydropower units, wind and solar units, and the discharge and charge outputs of energy storage units; L h,t , Respectively represent the power generation flow and maximum flow of the hydropower station; Θ t , Θ hp , Θ ess They represent the collection of operating time, hydropower units, and energy storage units respectively.

[0018] Among them, a power system optimization model is constructed, and its constraints include hydropower unit constraints, wind and solar power output constraints, energy storage system constraints, fully controlled device reactive power output constraints, AC / DC converter station constraints and AC / DC network constraints.

[0019] Among them, the node marginal electricity price model is constructed, with the minimum power system purchase quantity as the target clearing target, which is expressed as follows:

[0020]

[0021] Where: f is the distribution network objective function; c grid The price of electricity purchased by the power system from the upper power grid; The amount of electricity purchased by node i from the upper power grid.

[0022] Among them, a node marginal electricity price model is constructed, and its constraints are the AC and DC network constraints after the output of the generator sets in the power system optimization model is determined.

[0023] A power system DC transmission control system based on node marginal electricity price, comprising:

[0024] A power system optimization model building module is configured to build a power system optimization model based on power system operation parameter information;

[0025] A node marginal electricity price model building module is configured to build a node marginal electricity price model;

[0026] An iterative calculation module is configured to obtain a node marginal electricity price according to the node marginal electricity price model based on the output result of the power system optimization model; then update the unit output strategy in the power system optimization model based on the node marginal electricity price, and further solve the node marginal electricity price based on the updated power system optimization model, iterate until the node marginal electricity price and the unit output remain unchanged, and obtain the unit output at this time; and,

[0027] The control module is configured to control the output power of the power system unit to be the output of the unit, thereby realizing the control of the DC external power of the power system.

[0028] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps of the power system DC transmission control method based on node marginal electricity price as described above are implemented.

[0029] A computer-readable storage medium stores a computer program; when the computer program is executed by a processor, the steps of the power system DC transmission control method based on node marginal electricity price as described above are implemented.

[0030] After adopting the above scheme, the present invention can achieve the following beneficial effects:

[0031] 1. Through the direct current transmission technology of hydropower units, the hydropower units' ability to absorb new energy is effectively improved, and the economic benefits of the system are improved.

[0032] 2. Congestion management through node marginal electricity prices effectively alleviates the transmission congestion phenomenon of the new power system and improves the safety and stability of the system.

[0033] 3. Use fully controlled excitation devices to build an excitation system so that the hydropower unit can provide reactive power through the excitation system, effectively providing reactive power support for the power system while improving the active power output of the hydropower unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the structure of the hydropower system of the present invention;

[0035] Figure 2 It is an iterative flow chart of the present invention;

[0036] Figure 3 It is a schematic diagram of the excitation system of the fully controlled device of the present invention;

[0037] Figure 4 It is a schematic diagram of the equivalent circuit of the converter station of the present invention. DETAILED DESCRIPTION

[0038] The technical solutions and beneficial effects of the present invention will be described in detail below with reference to the accompanying drawings.

[0039] like Figure 1 As shown, the power system containing the hydropower unit used in the present invention includes: a fully controlled device excitation hydropower unit; and a receiving end system, including: a wind and solar unit, an AC / DC coupling network, an energy storage unit and a load; the hydropower system and the receiving end system together constitute a power system. Figure 3 The structure of the fully controlled device excitation system is shown;

[0040] The load consists of interruptible load, transferable load and fixed load;

[0041] Energy is transferred between the fully controlled device excitation hydroelectric generator set, wind and solar generator set, energy storage generator set and load via an AC / DC coupling network.

[0042] like Figure 2 As shown, the present invention provides a method for controlling direct current transmission of a power system based on node marginal electricity prices, including: first, the hydropower system formulates an output strategy with the goal of optimizing its own operating income, and transmits the output strategy to the power system operator; at the same time, based on the fully controlled device excitation system, the hydropower unit can provide reactive support services to the power system more flexibly; further, the power system formulates a node marginal electricity price according to the output strategy of each unit, thereby affecting the output of each unit; finally, the hydropower system and the power system operator achieve stability through iteration, and obtain a pricing scheme for the output strategy of the hydropower system and the node marginal electricity price. Specifically, the control method of the present invention includes the optimization of the output strategy of the fully controlled device excitation hydropower unit and the wind and solar unit, as well as the optimization of the node marginal electricity price of the power system. While meeting the needs of the power system, it improves the operating efficiency of each unit and ensures the safe and stable operation of the power system.

[0043] An embodiment provided by the present invention comprises the following steps:

[0044] 1) Obtain power system operation parameter information, including hydropower unit parameters, wind and solar unit parameters, various load information, economic costs, safe operation constraints, etc.;

[0045] 2) Construct an optimization model for the power system, including hydropower units, wind and solar units, energy storage units, and AC and DC network systems;

[0046] The power system aims to maximize the total operating profit, including the following objective functions:

[0047] maxF=f p +f ess -f spill

[0048]

[0049] Where: F is the total operating income of the system; f p 、f ess 、f spill are power generation income, energy storage income and water abandonment penalty, respectively, sell , uess , dess , spill represents the electricity selling price of the generator set, the electricity selling price of the energy storage unit, the electricity purchasing price of the energy storage system and the penalty cost of water abandonment respectively; P hp,i,t , P wt,i,t , P pv,i,t , P uess,i,t , P dess,i,t Respectively represent the output of hydropower units, wind and solar units, and the discharge and charge outputs of energy storage units; L h,t , Respectively represent the power generation flow and maximum flow of the hydropower station; Θ t , Θ hp , Θ ess They represent the collection of operating time, hydropower units, and energy storage units respectively.

[0050] The following constraints are also included:

[0051] (1) Constraints on hydropower units

[0052] The output constraints and up and down ramp constraints of the fully controlled device excitation hydropower station are similar to those of thermal power units. In addition, there are hydropower conversion constraints, power generation flow constraints, water balance constraints, reservoir capacity constraints, and excitation reactive power constraints.

[0053]

[0054] Where η h represents the water-to-electricity conversion efficiency of cascade hydropower station h; L h,t is the power generation flow of hydropower station h during period t; Hh,t H is the generating head of the hydropower station h during period t; h0 、a h are the initial water head and water head coefficient of the hydropower station h, which are related to the physical characteristics of the hydropower station itself; V h,t represents the storage capacity of hydropower station h in period t; I h,t Indicates the operating status of the hydropower station h during period t, "1" indicates startup and "0" indicates shutdown; are the maximum and minimum power generation flows allowed by the hydropower station h; q h,t is the inflow flow of hydropower station h during period t; S h,t is the abandoned water flow of hydropower station h during period t; τ h It indicates the time it takes for water from a hydropower station h to flow to the immediate downstream; They represent the power generation flow and abandoned water flow of the direct upstream power station h' of the hydropower station h in period t, considering the water flow lag; n h,t is the natural water inflow of hydropower station h during period t; They represent the maximum and minimum storage capacities allowed by the hydropower station h during period t; V h0 、V h,NT are the storage capacities at the beginning and end of dispatch respectively; Q ht,i,t is the reactive power output by the hydropower unit, It is the upper limit of reactive power output of hydropower unit.

[0055] (2) Wind and solar power output constraints

[0056] 0≤P pv,i,t ≤P pv,max

[0057] 0≤P wt,i,t ≤P wt,max

[0058] Where P pv,max , P wt,max They represent the upper limits of photovoltaic and wind power output respectively.

[0059] (3) Energy storage system constraints

[0060] The energy storage system model includes SOC constraints, charge and discharge constraints, and power constraints, as follows:

[0061]

[0062] P ess,min ≤P dess,i,t ,P uess,i,t ≤P ess,max

[0063] SOC min ≤SOC i,t ≤SOC max

[0064] In the formula, SOC i,t represents the state of charge of the i-th energy storage system in period t; E max is the maximum capacity of the energy storage system; η is the energy storage charging and discharging system; P ess,max , P ess,min Indicates the upper and lower limits of charge and discharge power; SOC max , SOC min Indicates the upper and lower limits of the state of charge.

[0065] (4) Reactive output constraints of fully controlled devices

[0066] 0≤Q exc,i,t ≤Q exc,max

[0067] In the formula, Q exc,i,t Indicates the reactive output of the excitation system; Q exc,max It is the upper limit of output reactive power.

[0068] (5) AC / DC converter station constraints

[0069] The AC and DC networks need to be transferred through the converter station to transmit DC. It is assumed that the internal power conversion is equivalent to the ideal VSC with equivalent impedance. Therefore, the constraints of the converter station include the active and reactive power flow constraints on the converter station, the power constraints on the AC and DC sides, and the upper and lower safety limits of the node voltage.

[0070]

[0071] In the formula, They represent the active power and reactive power input to the AC side of converter station c during period t respectively; represents the active power output on the DC side of converter station c during period t; They represent the active and reactive losses on the line (j, j') during period t, respectively, and are related to the equivalent impedance inside the converter station; P j',c,t , Q j',c,t They represent the active and reactive power of the power input node j' of the converter station c during period t respectively; They represent the upper and lower limits of the active power on the AC side of converter station c respectively; They represent the upper and lower limits of the active power on the DC side of converter station c respectively; represents the AC side voltage of converter station c during period t; They respectively represent the upper and lower limits of the voltage amplitude on the AC side of converter station c.

[0072] It should be pointed out that after adding the converter station, the AC side and the DC side are two relatively independent parts in the power flow calculation. Therefore, we ignore the internal structure of the converter station and only consider the input node of the AC side and the output node of the DC side. The equivalent power input node j' of the converter station is set. The above formula shows that if the active power loss inside the converter station is very low, its input active power is equal to its output active power. Figure 4 shown.

[0073] To optimize the power on the DC transmission line to replace the traditional fixed power transmission mode, it is also necessary to consider the power adjustment amplitude constraint, the power unidirectional adjustment constraint, the power cannot be adjusted in the opposite direction during adjacent time periods, and the transmission line adjustment times limit, as shown below:

[0074]

[0075] In the formula, are the maximum upward and downward adjustment limits of the transmission power of converter station c respectively; They represent the upward and downward adjustment status of the outgoing line c during period t, respectively. "1" represents that the transmission direction is adjusted, and "0" represents that it remains unchanged. are the maximum downward and upward adjustment times of converter station c respectively; T represents the scheduling period.

[0076] (6) AC / DC network constraints

[0077] The AC / DC network model includes power flow constraints, voltage constraints, active / reactive balance constraints, and second-order cone relaxation constraints, as follows.

[0078] AC Network Constraints

[0079]

[0080] Where: t = 1, 2, ..., 24 means that a scheduling period is 24 hours, and the scheduling periods of the three stages are the same; P ij,t and Q ij,t are the active power and reactive power of branch ij respectively; P ki,t and Q ki,t are the active power and reactive power of branch ki respectively; and are the active power and reactive power injected into node i respectively; and are the total active output and reactive output of the power supply in the AC power grid respectively; and are the active load and reactive load of node i respectively; P D,tis the flexible load response in the real-time stage. In this embodiment, the flexible load is a direct interruption load, which is essentially the power injection of the node; M(i) is the set of end nodes of the branch whose first node is i in the AC power grid; N(i) is the set of first nodes of the branch whose last node is i in the AC power grid; R ij and R ki is the branch resistance; X ij and X ki is the branch reactance; I ki,t ,I ij,t Respectively represent the current flowing through the branches ki and ij; Respectively represent the active and reactive power input from the upper branch; U i,t , U j,t Represent the node voltages of nodes i and j respectively.

[0081] DC network constraints

[0082]

[0083] Where: X(i) is the set of end nodes of the branch whose first node is i in the DC power grid; Y(i) is the set of first nodes of the branch whose last node is i in the DC power grid; and are the charging and discharging power of the energy storage device respectively.

[0084] 3) Construct a node marginal electricity price model based on the output results of the power system optimization model and solve it through iteration.

[0085] Through step 2, the power scheme that benefits the power system the most is obtained. On the basis of the output scheme, the node marginal electricity price is calculated by constructing a node marginal electricity price model, as follows:

[0086] The power system takes the minimum amount of purchased electricity as the target clearing target, and the corresponding node marginal electricity price objective function is as follows:

[0087]

[0088] Where: f is the distribution network objective function; c grid The price of electricity purchased by the power system from the upper power grid; The amount of electricity purchased by node i from the upper power grid.

[0089] Among them, the constraint conditions consist of the AC and DC network constraints after the output of the generator sets is determined in the power system model in step 2.

[0090] The above model can be simplified as follows:

[0091] minf(x)

[0092]

[0093] Where: f(x) represents the objective function; g i (x) represents the i-th inequality constraint; h i (x) represents the i-th equality constraint.

[0094] By reconstructing the above model according to the KKT condition, the Lagrangian function of the above model is as follows:

[0095]

[0096] Where: i , μ j denote the dual variables of inequality constraints and equality constraints respectively.

[0097] The node marginal price refers to the price at a specific location that takes into account all transmission constraints and utilizes all available power generation resources to minimize transmission costs; it measures the energy value of a node at this moment under the current system operating state. Therefore, according to the definition of the node marginal price, the node marginal price is equivalent to the derivative of the Lagrangian function of the power system relative to the active output of the power source, that is:

[0098]

[0099] The unit price of power generation and purchase of wind, solar, hydropower and energy storage units is the node marginal electricity price of the node where they are located.

[0100] Finally, the node marginal electricity price obtained in step 3 is transferred to the power system optimization model in step 2, and the output strategy P of the hydropower unit is updated. hp,i,t , and transmit it to the node marginal electricity price model to change the corresponding After getting the update Finally, the corresponding node marginal electricity price is updated according to the node marginal electricity price model to form an iteration; finally, it is iterated step by step until the electricity price and output strategy remain unchanged, the iteration converges, and the result is output.

[0101] The embodiment of the present invention further provides a power system DC transmission control system based on node marginal electricity price, comprising:

[0102] A power system optimization model building module is configured to build a power system optimization model based on power system operation parameter information;

[0103] A node marginal electricity price model building module is configured to build a node marginal electricity price model;

[0104] An iterative calculation module is configured to obtain a node marginal electricity price according to the node marginal electricity price model based on the output result of the power system optimization model; then update the unit output strategy in the power system optimization model based on the node marginal electricity price, and further solve the node marginal electricity price based on the updated power system optimization model, iterate until the node marginal electricity price and the unit output remain unchanged, and obtain the unit output at this time; and,

[0105] The control module is configured to control the output power of the power system unit to be the output of the unit, thereby realizing the control of the DC external power of the power system.

[0106] An embodiment of the present invention further provides another computer device, including a processor and a memory configured to store a computer program that can be run on the processor; wherein, when the processor is configured to run the computer program, the method steps in the aforementioned embodiment are executed.

[0107] In practical applications, the processor includes a field programmable gate array (FPGA), and the processor may be a central processing unit (CPU) or a digital signal processor (DSP). It is understandable that for different devices, the electronic device used to implement the function of the processor may be other, and the embodiment of the present invention does not specifically limit it.

[0108] The above-mentioned memory can be a volatile memory (volatile memory), such as a random access memory (RAM); or a non-volatile memory (non-volatile memory), such as a read-only memory (ROM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD); or a combination of the above-mentioned types of memory, and provide instructions and data to the processor.

[0109] In an exemplary embodiment, an embodiment of the present invention further provides a computer-readable storage medium for storing a computer program.

[0110] Optionally, the computer-readable storage medium can be applied to any one of the methods in the embodiments of the present invention, and the computer program enables the computer to execute the corresponding processes implemented by the processor in each method in the embodiments of the present invention. For the sake of brevity, they are not described here.

[0111] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0112] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0113] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0117] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling direct current transmission of a power system based on node marginal electricity price, characterized in that: include, Construct a power system optimization model based on power system operation parameter information; Construct node marginal electricity price model; Based on the output result of the power system optimization model, the node marginal electricity price is obtained according to the node marginal electricity price model; then the unit output strategy in the power system optimization model is updated based on the node marginal electricity price, and the node marginal electricity price is further solved based on the updated power system optimization model, and it is iterated until the node marginal electricity price and the unit output remain unchanged, so as to obtain the unit output at this time; The output power of the power system unit is controlled to be the output of the unit, thereby realizing the control of the DC output power of the power system.

2. The method according to claim 1, characterized in that: The power system optimization model is constructed with the goal of maximizing the total operating profit of the power system. The objective function is expressed as follows: maxF=f p +f ess -f spill Where: F is the total operating income of the system; f p 、f ess 、f spill are power generation income, energy storage income and water abandonment penalty, respectively, sell , uess , dess , spill represents the electricity selling price of the generator set, the electricity selling price of the energy storage unit, the electricity purchasing price of the energy storage system and the penalty cost of water abandonment respectively; P hp,i,t , P wt,i,t , P pv,i,t , P uess,i,t , P dess,i,t Respectively represent the output of hydropower units, wind and solar units, and the discharge and charge outputs of energy storage units; L h,t , Respectively represent the power generation flow and maximum flow of the hydropower station; Θ t , Θ hp , Θ ess They represent the collection of operating time, hydropower units, and energy storage units respectively.

3. The method according to claim 2, characterized in that: Construct a power system optimization model, whose constraints include hydropower unit constraints, wind and solar power output constraints, energy storage system constraints, fully controlled device reactive power output constraints, AC / DC converter station constraints and AC / DC network constraints.

4. The method according to claim 1, characterized in that: The node marginal electricity price model is constructed, with the minimum power system purchase quantity as the target clearing target, which is expressed as follows: Where: f is the distribution network objective function; c grid The price of electricity purchased by the power system from the upper power grid; The amount of electricity purchased by node i from the upper power grid.

5. The method according to claim 4, characterized in that: A node marginal electricity price model is constructed, and its constraints are the AC and DC network constraints after the output of the generator sets in the power system optimization model is determined.

6. A power system DC transmission control system based on node marginal electricity price, characterized by: include, A power system optimization model building module is configured to build a power system optimization model based on power system operation parameter information; A node marginal electricity price model building module is configured to build a node marginal electricity price model; An iterative calculation module is configured to obtain a node marginal electricity price according to the node marginal electricity price model based on the output result of the power system optimization model; then update the unit output strategy in the power system optimization model based on the node marginal electricity price, and further solve the node marginal electricity price based on the updated power system optimization model, iterate until the node marginal electricity price and the unit output remain unchanged, and obtain the unit output at this time; as well as, The control module is configured to control the output power of the power system unit to be the output of the unit, thereby realizing the control of the DC external power of the power system.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that: When the processor executes the computer program, the steps of the method for controlling direct current transmission of a power system based on node marginal electricity price as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program; characterized in that: When the computer program is executed by a processor, the steps of the method for controlling direct current transmission of a power system based on node marginal electricity price as described in any one of claims 1 to 5 are implemented.

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