Embedded DC operation optimization method for wide-area distributed new energy consumption

Abstract

The invention relates to an embedded DC operation optimization method for wide-area distributed new energy consumption, and the method comprises the steps: firstly constructing an embedded DC power flow equation, and determining an embedded DC operation constraint based on the embedded DC power flow equation; secondly, minimizing the total operation cost and the total power loss of the power system as a target function, and determining a power system operation constraint set suitable for new energy consumption, so as to establish a power system operation optimization model; the embedded direct current operation constraint is incorporated into the power system operation optimization model to form an embedded direct current system operation optimization model oriented to wide-area distributed new energy consumption; and then solving the established optimization model to obtain an optimal operation scheme of the power system. According to the method, the operation condition of the system can be effectively evaluated, the effect of the embedded direct current is maximized, and technical support is provided for wide-area distributed new energy consumption.

Description

Technical Field

[0001] The invention relates to an embedded direct current operation optimization method for wide-area distributed new energy consumption, and belongs to the field of power system operation optimization. Background Art

[0002] In order to accelerate the green and low-carbon transformation of energy, the traditional power system needs to transform and upgrade to a new power system with new energy as the main body. However, the power generation of new energy is intermittent, volatile and unpredictable, which brings huge challenges to the operation of the power system, especially in the scenario of wide-area distribution. DC technology has the advantages of fast and flexible power regulation, low loss and small footprint. It has been widely used in long-distance large-capacity transmission and asynchronous networking, and is suitable for the consumption of wide-area distributed new energy. Compared with the long-distance and large-capacity DC transmission technology of traditional interconnection, the converter stations at both ends of the embedded DC transmission technology are built in the same AC power grid. It usually uses the existing overhead transmission lines to "convert AC to DC" and the existing or reserved AC cable channels, which can greatly improve the power grid transmission capacity, controllability and flexibility within the limited transmission corridor space.

[0003] With the rapid development of new energy and the gradual advancement of energy transformation, AC / DC hybrid power grids with embedded DC have become a new stage in the development of power systems. The traditional AC power grid and DC transmission system operate independently of each other, which limits the large-scale consumption of new energy and the flexible allocation of energy. The AC / DC hybrid power grid with embedded DC has the characteristics of multi-type DC participation and large-scale AC / DC interconnection. The research and application in this field are of great significance to the safe and stable operation of my country's power grid, the realization of large-scale new energy consumption and the low-carbon transformation of the power system, but there is currently no reasonable operation optimization strategy. In practical applications, how to achieve efficient operation optimization of embedded DC transmission systems in a widely distributed new energy environment, and how to evaluate the impact of its access to the system on regional power flow, system economy and new energy consumption are key issues that need to be solved urgently. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides an operation optimization method which can effectively evaluate the system operation status and maximize the role of embedded direct current.

[0005] In order to achieve the above-mentioned purpose, the technical solution proposed in the present invention is: an embedded DC operation optimization method for wide-area distributed new energy consumption, comprising the following steps:

[0006] Constructing embedded DC power flow equations, and determining embedded DC operation constraints based on the embedded DC power flow equations;

[0007] Establish a power system operation constraint set suitable for renewable energy consumption, take minimizing the overall operating cost and total power loss of the power system as the objective function, and establish a power system operation optimization model suitable for renewable energy consumption;

[0008] Incorporate embedded DC operation constraints into the power system operation optimization model suitable for new energy consumption, and form an embedded DC system operation optimization model for wide-area distributed new energy consumption;

[0009] The established embedded DC system operation optimization model for wide-area distributed renewable energy consumption is solved to obtain the optimal operation plan of the power system.

[0010] A further design of the above technical solution is as follows: the embedded DC power flow equation includes an AC side power flow equation, a DC side power flow equation, a converter side power flow equation, a transformer side power flow equation and a phase reactor side power flow equation.

[0011] when The AC side power flow equation is as follows:

[0012]

[0013] The power flow equation on the converter side is as follows:

[0014]

[0015] The power flow equation on the transformer side is as follows:

[0016]

[0017] The power flow equation on the phase reactor side is as follows:

[0018]

[0019] In the formula, are the voltage phasors on the AC side and the transformer side respectively; P s , Q s , P c , Q c , P sf , Q sf , P cf , Q cf are the active and reactive power injection on the AC side, converter side, transformer side and phase reactor side respectively; G c , B c , G tf , B tf are the conductance and susceptance of the converter side and transformer side respectively; U s ,δ s , U f ,δf , U c ,δ c are the controllable voltage amplitude and voltage angle on the AC side, transformer side and converter side respectively.

[0020] The DC side power flow equation is as follows:

[0021]

[0022] Where U dci ,I dci are the voltage and current at DC node i respectively; G dcij , Y dcij are the line conductance and susceptance of DC grid nodes i and j respectively; p is the number of poles of the DC grid; P dci is the active power at DC node i; ΔP dci is the mismatched active power of DC node i; P cdci The active power injected into the DC network by the converter at DC node i; P gdci is the active power emitted by DC node i; P ldci is the active power absorbed by DC node i.

[0023] The embedded DC operation constraints include upper and lower limit constraints of converter voltage and power, power adjustment direction constraints, power adjustment number constraints, power regulation continuity constraints, power adjustment rate constraints and converter step-by-step operation characteristic constraints.

[0024] The expressions for the upper and lower limits of the converter voltage and power are as follows:

[0025]

[0026] In the formula, is the minimum and maximum voltage amplitude of the converter, U vsc,i is the converter voltage amplitude; are the minimum and maximum power of the converter, P vsc,i is the converter power; Nk is the total number of converters;

[0027] The expression of the power adjustment direction constraint is as follows:

[0028]

[0029] In the formula, the binary variable x t , They represent the power adjustment state, upward adjustment and downward adjustment of the converter respectively, and t represents the time;

[0030] The expression of the power adjustment times constraint is as follows:

[0031]

[0032] Where S is the number of power adjustments of the HVDC line in one day;

[0033] The expression of the power regulation continuity constraint is as follows:

[0034]

[0035] The expression of the power adjustment rate constraint is as follows:

[0036]

[0037] In the formula, is the transmission power of the high-voltage DC line ij at time t; and are the minimum and maximum power regulation rates of the high-voltage DC line ij, respectively.

[0038] The expression of the step-by-step operation characteristic constraint of the converter is as follows:

[0039]

[0040] Where N T is the converter power adjustment time interval; binary variable and They respectively indicate the start and end of converter power adjustment.

[0041] The overall operating cost of the power system consists of the line and generator installation cost, wind turbine power generation cost, photovoltaic power station power generation cost, thermal power generation cost and energy storage system operation cost; the total power loss consists of the active power loss of AC transmission lines, DC transmission lines and converters.

[0042] The objective function is:

[0043]

[0044]

[0045] Where, T is the number of time periods divided by the 24-hour plan; f1 is the overall operating cost of the system; C install , C wt,t , C pv,t , C g,t , C ess,t are the line and generator installation costs, wind turbine generation costs, photovoltaic power station generation costs, thermal power generation costs, and energy storage system operation costs; k is the total number of AC generators in the power grid; l is the total number of expansion lines; C liis the unit construction cost of line i; L li is the length of the i-th new line; C Gi is the unit power construction cost of the AC generator at busbar i; P Gi is the active power of the newly built AC generator at bus i; N wt is the total number of wind turbines; wt , Whe are the unit power generation cost of wind turbines and government subsidies respectively; Δt is the duration of time period t; P wt,i,t is the power generated by the wind turbine in time period t; k wt is the penalty coefficient for wind abandonment; P wt,i,t are the predicted output and actual output of the i-th wind turbine generator set in time period t; N pv is the total number of photovoltaic power stations; pv , phe are the unit power generation cost of the photovoltaic power station and the government subsidy respectively; Δt is the duration of time period t; P pv,i,t k is the power generated by the photovoltaic generator set in time period t; pv is the penalty coefficient for abandoning light; P pv,i,t are the predicted output and actual output of the ith photovoltaic generator set in time period t; N g is the total number of thermal power units; U i,t is the start / stop status of thermal power unit i in time period t determined by the 24h plan of the previous day; P g,i,t S is the output of thermal power unit i in time period t determined by the 24-hour plan on the previous day; i is the startup cost of thermal power unit i; a i , b i 、c i is the economic characteristic parameter of thermal power unit; N ess is the number of energy storage systems; C eo,j is the unit electricity operation cost of energy storage system j; W is the charging and discharging power of energy storage system j in time period t; ess,j is the installation cost of energy storage system j; L j Service life of energy storage system j;

[0046] f2 is the total power loss; P acloss is the active power loss of the AC transmission line; P dcloss is the active power loss of the DC transmission line; P vscloss is the active power loss of the converter; Na is the collection of AC busbars; V i 、V j are the voltage amplitudes of DC busbars i and j respectively; δ i ,δj are the voltage angles at the AC busbars i and j respectively; G ij is the conductance of the AC grid admittance matrix; Nd is the set of DC buses; The DC bus i dc and j dc The voltage amplitude of G idcjdc is the conductance of the DC network admittance matrix; A lossi , B lossi , C lossi are VSC loss coefficient; I vi is the phase current of the VSC valve.

[0047] The power system operation constraint set suitable for new energy consumption includes power balance constraints, system safety operation constraints, generator output constraints, unit climbing constraints, unit minimum start and stop time constraints, wind / solar abandonment constraints, energy storage system constraints and system spinning reserve constraints;

[0048] The power system operation constraint set applicable to the consumption of new energy is:

[0049]

[0050] Where P ac,i,t , P dc,i,t , P loss,i,t are the active power losses of the AC / DC system and the converter in time period t respectively; U i is the voltage of node i; I Li is the current of the DC transmission line; S ij is the actual power flow of AC transmission line i-j; R u,i , R d,i are the maximum values ​​of the upward and downward climbing rates of the i-th thermal power unit; P max,i is the maximum output of thermal power unit i; are the start / stop time of thermal power unit i up to time t-1; are the minimum continuous start / stop time of thermal power unit i; δ1 and δ2 are the maximum allowable wind and solar abandonment rates; are the maximum available wind power and photovoltaic power output in time period t; SOC t , SOC t+1 is the state of charge of the energy storage device at the tth and t+1th time periods; Q SB is the rated capacity of the energy storage device; η ch , η dis is the charging and discharging efficiency of the energy storage device; μ ch , μ dis It is the charge and discharge mark; PSB ,t ≥0, μch =1, μ dis =0;P SB,t When <0, μ ch =0, μ dis =1;P SB,max The upper limit of the charging power of the energy storage device; SOC min , SOC max The upper and lower limits of the state of charge; SOC initial , SOC end R is the charge state of the energy storage device at the beginning and end of the dispatch; st is the total spinning reserve capacity that can be added to the system during period t, R g,st , R soc,st are the spinning reserve amounts that can be added by thermal power units and energy storage systems during period t; α and β are the demands for spinning reserve caused by wind power output forecast error and photovoltaic output forecast error, respectively.

[0051] The CPLEX solver or IPOPT solver is used to solve the embedded DC system operation optimization model for wide-area distributed renewable energy consumption.

[0052] The beneficial effects of the present invention are:

[0053] The embedded DC operation strategy optimization method provided by the present invention, combined with the operating characteristics of embedded DC, establishes an embedded DC system operation optimization model for wide-area distributed new energy consumption, which can effectively evaluate the system operation status, maximize the role of embedded DC, and provide technical support for wide-area distributed new energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of the present invention;

[0055] Figure 2 It is the overall topology model of voltage source converter (VSC);

[0056] Figure 3 is the equivalent model of the i-th VSC as a whole;

[0057] Figure 4 This is a simplified steady-state model for a DC network. DETAILED DESCRIPTION

[0058] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] Example

[0060] The embedded DC operation strategy optimization method for wide-area distributed new energy consumption in this embodiment is as follows: Figure 1 As shown, the following steps are included:

[0061] Step 1: Consider the electrical characteristic parameters of the power system components, establish the embedded DC power flow equation, combine the embedded DC operation characteristics, analyze its power adjustment direction, adjustment times, adjustment continuity, adjustment rate, and converter step-by-step operation characteristics, and determine the embedded DC operation constraints.

[0062] The embedded DC power flow equation includes the AC side, DC side, converter side, transformer side and phase reactor side, as follows:

[0063] To show the applicability and generality of embedded DC systems, the overall topology model of VSC is established as follows: Figure 2 As shown, it includes a converter, a phase reactor, an AC filter and a transformer.

[0064] The overall equivalent model of the VSC includes a controlled voltage source Phase reactor impedance Z c =R c +jX c , AC filter B f , transformer impedance Z tf =R tf +jX tf ,like Figure 3 shown.

[0065] when The AC side power flow equation is as follows:

[0066]

[0067]

[0068] The power flow equation on the converter side is as follows:

[0069]

[0070]

[0071] The power flow equation on the transformer side is as follows:

[0072]

[0073]

[0074] The power flow equation on the phase reactor side is as follows:

[0075]

[0076]

[0077] In the formula, are the voltage phasors on the AC side and the transformer side respectively; Ps , Q s , P c , Q c , P sf , Q sf , P cf , Q cf are the active and reactive power injection on the AC side, converter side, transformer side and phase reactor side respectively; G c , B c , G tf , B tf are the conductance and susceptance of the converter side and transformer side respectively; U s ,δ s , U f ,δ f , U c ,δ c are the controllable voltage amplitude and voltage angle on the AC side, transformer side and converter side respectively.

[0078] The DC network power flow calculation does not involve reactive power. Therefore, its node variables only include two variables, P and U. When performing DC power flow calculation, the admittance matrix only contains the G matrix. Figure 4 It is a steady-state power flow model for DC network.

[0079] Depend on Figure 4 The DC power flow calculation equation is as follows:

[0080]

[0081]

[0082]

[0083] In the formula, G dcij is the line conductance between DC node i and DC node j in the DC grid; p is the number of poles in the DC grid; ΔP dci is the mismatched active power of DC node i; P gdci is the active power emitted by DC node i; P ldci is the active power absorbed by DC node i.

[0084] The embedded DC operation constraints based on the above power flow equations and embedded DC operation characteristics include upper and lower limit constraints of converter voltage and power, power adjustment direction constraints, power adjustment number constraints, power regulation continuity constraints, power adjustment rate constraints, and converter step-by-step operation characteristic constraints, as follows:

[0085] The expressions for the upper and lower limits of converter voltage and power are as follows:

[0086]

[0087] In the formula, are the minimum and maximum voltage amplitudes of the converter; are the minimum and maximum power of the converter respectively; Nk is the total number of converters.

[0088] The expression of power adjustment direction constraint is as follows:

[0089]

[0090] The power adjustment direction of the converter cannot be reversed in adjacent cycles to ensure the reliable operation of the converter. Therefore, it is necessary to constrain the power adjustment direction of the converter. t , They respectively represent the power adjustment status of the converter, upward adjustment and downward adjustment.

[0091] The expression of power adjustment times constraint is as follows:

[0092]

[0093] The number of power adjustments of the converter is limited within the dispatching period to ensure the service life of the converter; where S is the number of power adjustments of the high-voltage DC line in one day.

[0094] The expression of power regulation continuity constraint is as follows:

[0095]

[0096] The high voltage DC power supply cannot be adjusted up and down continuously in adjacent time periods, where: The value of is represented by the change in the power of the high-voltage DC line.

[0097] The expression of power adjustment rate constraint is as follows:

[0098]

[0099] In order to avoid repeated small adjustments of high-voltage DC power, it is necessary to constrain the minimum / maximum power regulation rate of the converter; where, is the transmission power of the high-voltage DC line ij at time t; are the minimum and maximum power regulation rates of the high-voltage DC line ij, respectively.

[0100] The expression of the step-by-step operation characteristic constraint of the converter is as follows:

[0101]

[0102] After the high voltage DC power supply is adjusted, it should be kept for a minimum duration N TKeep constant to ensure the reliable operation and service life of the converter. T The binary variable introduced is the time interval for the converter power adjustment. They respectively indicate the start and end of converter power adjustment.

[0103] Step 2: Taking minimizing the overall operating cost and total power loss of the power system as the objective function, determine the set of power system operation constraints applicable to the power system considering the consumption of new energy, and further establish a power system operation optimization model considering the consumption of new energy.

[0104] The overall operating cost of the system includes the line and generator installation costs, wind turbine power generation costs, photovoltaic power station power generation costs, thermal power generation costs and energy storage system operation costs, as follows:

[0105] Based on the output of distributed renewable energy and the day-ahead load forecast results, the day-ahead dispatch is carried out with the overall operating cost and total power loss of the power system in a complete cycle as the objective function. A 24-hour day is divided into T time periods. Assuming that the power of each unit remains basically unchanged in each time period, the objective function based on the overall operating cost of the system is:

[0106] (1) Minimize overall operating costs

[0107]

[0108] Where, T is the number of time periods divided by the 24-hour plan; f1 is the overall operating cost of the system; C install , C wt,t , C pv,t , C g,t , C ess,t They are the line and generator installation cost, wind turbine power generation cost, photovoltaic power station power generation cost, thermal power generation cost and energy storage system operation cost.

[0109] Line and generator installation costs:

[0110]

[0111] Where k is the total number of AC generators in the power grid; l is the total number of expansion lines; C li is the unit construction cost of line i; L li is the length of the i-th new line; C Gi is the unit power construction cost of the AC generator at busbar i; P Gi is the active power of the new AC generator at bus i.

[0112] Wind turbine power generation cost:

[0113] The costs of wind power and photovoltaic power generation include construction costs and operating costs, which are estimated based on the total power generation over their entire life cycle and converted into unit power generation.

[0114]

[0115] Where N wt is the total number of wind turbines; wt , Whe are the unit power generation cost of wind turbines and government subsidies respectively; Δt is the duration of time period t; P wt,i,t is the power generated by the wind turbine in time period t; k wt is the penalty coefficient for wind abandonment; P wt,i,t are the predicted output and actual output of the i-th wind turbine generator set in time period t respectively.

[0116] Photovoltaic power station power generation cost:

[0117]

[0118] Where N pv is the total number of photovoltaic power stations; pv , phe are the unit power generation cost of the photovoltaic power station and the government subsidy respectively; Δt is the duration of time period t; P pv,i,t k is the power generated by the photovoltaic generator set in time period t; pv is the penalty coefficient for abandoning light; P pv,i,t are the predicted output and actual output of the i-th photovoltaic generator set in time period t, respectively.

[0119] Power generation cost of thermal power units:

[0120]

[0121] Where N g is the total number of thermal power units; U i,t is the start / stop status of thermal power unit i in time period t determined by the 24h plan of the previous day; P g,i,t S is the output of thermal power unit i in time period t determined by the 24-hour plan on the previous day; i is the startup cost of thermal power unit i; a i , b i 、c i It is the economic characteristic parameter of thermal power unit.

[0122] Energy storage system operating costs:

[0123]

[0124] Where Ness is the number of energy storage systems; C eo,j is the unit electricity operation cost of energy storage system j; W is the charging and discharging power of energy storage system j in time period t; ess,j is the installation cost of energy storage system j; L j Service life of energy storage system j.

[0125] The total power loss includes the active power loss of AC transmission lines, DC transmission lines and converters. The specific objective function based on the total power loss is as follows:

[0126] (2) Minimize total power loss

[0127]

[0128] Active power loss of AC transmission line:

[0129]

[0130] Where f2 is the total power loss; P acloss is the active power loss of the AC transmission line; Na is the collection of AC busbars; V i 、V j are the voltage amplitudes of DC busbars i and j respectively; δ i ,δ j are the voltage angles at the AC busbars i and j respectively; G ij is the conductance of the AC grid admittance matrix.

[0131] When the system operates in bipolar mode, the active power loss in the DC current is obtained as follows:

[0132]

[0133] Where P dcloss is the active power loss in DC current; Nd is the collection of DC bus; The DC bus i dc and j dc The voltage amplitude of G idcjdc is the conductance of the DC network admittance matrix.

[0134] The active power loss in VSC can be expressed as follows:

[0135]

[0136]

[0137] Where P vscloss is the active power loss in VSC; A lossi , Blossi , C lossi are VSC loss coefficient; I vi is the phase current of the VSC valve; V vsc is the voltage amplitude of the VSC AC bus; P vsc , Q vsc are the active and reactive powers of the VSC AC bus respectively.

[0138] The constraint set of the power system operation optimization model considering the consumption of new energy includes power balance constraint, system safe operation constraint, generator output constraint, unit ramp constraint, unit minimum start-up and shutdown time constraint, wind and solar curtailment constraint, energy storage system constraint and system spinning reserve constraint. The specific expression of the constraint set is as follows:

[0139]

[0140] Where P ac,i,t , P dc,i,t , P loss,i,t are the active power losses of the AC / DC system and the converter in time period t respectively; U i is the voltage of node i; I Li is the current of the DC transmission line; S ij is the actual power flow of AC transmission line i-j; R u,i , R d,i are the maximum values ​​of the upward and downward climbing rates of the i-th thermal power unit; P max,i is the maximum output of thermal power unit i; are the start / stop time of thermal power unit i up to time t-1; are the minimum continuous start / stop time of thermal power unit i; δ1 and δ2 are the maximum allowable wind and solar abandonment rates; are the maximum available wind power and photovoltaic power output in time period t; SOC t , SOC t+1 is the state of charge of the energy storage device at the tth and t+1th time periods; Q SB is the rated capacity of the energy storage device; η ch , η dis is the charging and discharging efficiency of the energy storage device; μ ch , μ dis P is the charge and discharge mark; SB,t ≥0, μ ch =1, μ dis =0;P SB,t When <0, μ ch =0, μ dis =1;P SB,max The upper limit of the charging power of the energy storage device; SOC min , SOCmax The upper and lower limits of the state of charge; SOC initial , SOC end R is the charge state of the energy storage device at the beginning and end of the dispatch; st is the total spinning reserve capacity that can be added to the system during period t, R g,st , R soc,st are the spinning reserve amounts that can be added by thermal power units and energy storage systems during period t; α and β are the demands for spinning reserve caused by wind power output forecast error and photovoltaic output forecast error, respectively.

[0141] Step 3: Incorporate the embedded DC operation-related constraints into the power system operation optimization model to form an embedded DC system operation optimization model for wide-area distributed new energy consumption.

[0142] Based on the power system operation optimization model considering the consumption of new energy, the embedded DC operation related constraints are incorporated into the operation optimization model to form an embedded DC system operation optimization model for wide-area distributed new energy consumption as follows:

[0143]

[0144] Step 4: Use the selected optimization algorithm to solve the embedded DC system operation optimization model for wide-area new energy consumption, and obtain the power system operation efficiency maximization and economic cost optimization solution taking into account the embedded DC operation characteristics.

[0145] The optimization problem of the above-mentioned embedded DC system operation optimization model for wide-area distributed new energy consumption is a large-scale mixed integer optimization problem. This embodiment calls one of the CPLEX solver or IPOPT solver, or other solvers to solve and obtain the optimal planning and operation plan of the embedded DC system (economic performance).

[0146] The technical solutions of the present invention are not limited to the above-mentioned embodiments, and any technical solutions obtained by equivalent replacement methods fall within the scope of protection required by the present invention.

Claims

1. An embedded DC operation optimization method for wide-area distributed new energy consumption, characterized in that: The steps include: Constructing embedded DC power flow equations, and determining embedded DC operation constraints based on the embedded DC power flow equations; Establish a power system operation constraint set suitable for renewable energy consumption, take minimizing the overall operating cost and total power loss of the power system as the objective function, and establish a power system operation optimization model suitable for renewable energy consumption; Incorporate embedded DC operation constraints into the power system operation optimization model for renewable energy consumption, and form an embedded DC system operation optimization model for wide-area distributed renewable energy consumption; The established embedded DC system operation optimization model for wide-area distributed renewable energy consumption is solved to obtain the optimal operation plan of the power system.

2. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 1 is characterized in that: The embedded DC power flow equation includes an AC side power flow equation, a DC side power flow equation, a converter side power flow equation, a transformer side power flow equation and a phase reactor side power flow equation.

3. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 2 is characterized in that: when The AC side power flow equation is as follows: The power flow equation on the converter side is as follows: The power flow equation on the transformer side is as follows: The power flow equation on the phase reactor side is as follows: In the formula, are the voltage phasors on the AC side and the transformer side respectively; P s , Q s , P c , Q c , P sf , Q sf , P cf , Q cf are the active and reactive power injection on the AC side, converter side, transformer side and phase reactor side respectively; G c , B c , G tf , B tf are the conductance and susceptance of the converter side and transformer side respectively; U s ,δ s , U f ,δ f , U c ,δ c are the controllable voltage amplitude and voltage angle on the AC side, transformer side and converter side respectively; The DC side power flow equation is as follows: Where U dci ,I dci are the voltage and current at DC node i respectively; G dcij , Y dcij are the line conductance and susceptance of DC grid nodes i and j respectively; p is the number of poles of the DC grid; P dci is the active power at DC node i; ΔP dci is the mismatched active power of DC node i; P cdci The active power injected into the DC network by the converter at DC node i; P gdci is the active power emitted by DC node i; P ldci is the active power absorbed by DC node i.

4. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 3 is characterized by: The embedded DC operation constraints include upper and lower limit constraints of converter voltage and power, power adjustment direction constraints, power adjustment number constraints, power regulation continuity constraints, power adjustment rate constraints and converter step-by-step operation characteristic constraints.

5. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 4 is characterized in that: The expressions for the upper and lower limits of the converter voltage and power are as follows: In the formula, is the minimum and maximum voltage amplitude of the converter, U vsc,i is the converter voltage amplitude; are the minimum and maximum power of the converter, P vsc,i is the converter power; Nk is the total number of converters; The expression of the power adjustment direction constraint is as follows: In the formula, the binary variable x t , They represent the power adjustment state, upward adjustment and downward adjustment of the converter respectively, and t represents the time; The expression of the power adjustment times constraint is as follows: Where S is the number of power adjustments of the HVDC line in one day; The expression of the power regulation continuity constraint is as follows: The expression of the power adjustment rate constraint is as follows: In the formula, is the transmission power of the high-voltage DC line ij at time t; and are the minimum and maximum power regulation rates of the HVDC line ij, respectively; The expression of the step-by-step operation characteristic constraint of the converter is as follows: Where N T a time interval for adjusting the converter power; Binary variables and Respectively indicate the start and end of converter power adjustment.

6. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 5 is characterized by: The overall operating cost of the power system consists of the line and generator installation cost, wind turbine power generation cost, photovoltaic power station power generation cost, thermal power generation cost and energy storage system operation cost; the total power loss of the power system consists of the active power loss of AC transmission lines, DC transmission lines and converters.

7. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 6 is characterized by: The objective function is: Where, T is the number of time periods divided by the 24-hour plan; f1 is the overall operating cost of the system; C install , C wt,t , C pv,t , C g,t , C ess,t are the line and generator installation costs, wind turbine generation costs, photovoltaic power station generation costs, thermal power generation costs, and energy storage system operation costs; k is the total number of AC generators in the power grid; l is the total number of expansion lines; C li is the unit construction cost of line i; L li is the length of the i-th new line; C Gi is the unit power construction cost of the AC generator at busbar i; P Gi is the active power of the newly built AC generator at bus i; N wt is the total number of wind turbines; wt , Whe are the unit power generation cost of wind turbines and government subsidies respectively; Δt is the duration of time period t; P wt,i,t is the power generated by the wind turbine in time period t; k wt is the penalty coefficient for wind abandonment; P wt,i,t are the predicted output and actual output of the i-th wind turbine generator set in time period t; N pv is the total number of PV power stations; ρ pv , phe are the unit power generation cost of the photovoltaic power station and the government subsidy respectively; Δt is the duration of time period t; P pv,i,t k is the power generated by the photovoltaic generator set in time period t; pv is the penalty coefficient for abandoning light; P pv,i,t are the predicted output and actual output of the ith photovoltaic generator set in time period t; N g is the total number of thermal power units; U i,t is the start / stop status of thermal power unit i in time period t determined by the 24h plan of the previous day; P g,i,t S is the output of thermal power unit i in time period t determined by the 24-hour plan on the previous day; i is the startup cost of thermal power unit i; a i 、b i 、c i is the economic characteristic parameter of thermal power unit; N ess is the number of energy storage systems; C eo,j is the unit electricity operation cost of energy storage system j; W is the charging and discharging power of energy storage system j in time period t; ess,j is the installation cost of energy storage system j; L j Service life of energy storage system j; f2 is the total power loss; P acloss is the active power loss of the AC transmission line; P dcloss is the active power loss of the DC transmission line; P vscloss is the active power loss of the converter; Na is the collection of AC busbars; V i 、V j are the voltage amplitudes of DC busbars i and j respectively; δ i ,δ j are the voltage angles at the AC busbars i and j respectively; G ij is the conductance of the AC grid admittance matrix; Nd is the set of DC buses; The DC bus i dc and j dc The voltage amplitude of G idcjdc is the conductance of the DC network admittance matrix; A lossi , B lossi , G lossi are VSC loss coefficient; I vi is the phase current of the VSC valve.

8. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 7 is characterized in that: The power system operation constraint set suitable for the consumption of new energy includes power balance constraints, system safe operation constraints, generator output constraints, unit climbing constraints, unit minimum start and stop time constraints, wind and solar power abandonment constraints, energy storage system constraints and system rotating reserve constraints.

9. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 8 is characterized by: The power system operation constraint set applicable to the consumption of new energy is: Where P ac,i,t , P dc,i,t , P loss,i,t are the active power losses of the AC / DC system and the converter in time period t respectively; U i is the voltage of node i; I Li is the current of the DC transmission line; S ij is the actual power flow of AC transmission line i-j; R u,i , R d,i are the maximum values ​​of the upward and downward climbing rates of the i-th thermal power unit; P max,i is the maximum output of thermal power unit i; are the start / stop time of thermal power unit i up to time t-1; are the minimum continuous start / stop time of thermal power unit i respectively; δ1 and δ2 are the maximum allowable wind and solar power abandonment rates, respectively; and are the maximum available wind power and photovoltaic power output in time period t; SOC t , SOC t+1 is the state of charge of the energy storage device at the tth and t+1th time periods; Q SB is the rated capacity of the energy storage device; η ch , η dis is the charging and discharging efficiency of the energy storage device; μ ch , μ dis P is the charge and discharge mark; SB,t ≥0, μ ch =1, μ dis =0;P SB,t When <0, μ ch =0, μ dis =1;P SB,max The upper limit of the charging power of the energy storage device; SOC min , SOC max The upper and lower limits of the state of charge; SOC initial , SOC end R is the charge state of the energy storage device at the beginning and end of the dispatch; st is the total spinning reserve capacity that can be added to the system during period t, R g,st , R soc,st are the spinning reserve amounts that can be added by thermal power units and energy storage systems during period t; α and β are the demands for spinning reserve caused by wind power output forecast error and photovoltaic output forecast error, respectively.

10. The embedded DC operation optimization method for wide-area distributed new energy consumption according to claim 9 is characterized in that: The CPLEX solver or IPOPT solver is used to solve the embedded DC system operation optimization model for wide-area distributed renewable energy consumption.

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