A planning method for multi-DC transmission power grid considering frequency security constraints

Abstract

The invention discloses a multi-DC transmission power grid planning method considering frequency safety constraints, relates to the technical field of power system planning, solves the problem that the planning results of the multi-DC transmission power grid cannot ensure the system frequency safety, and the key points of the technical solution are: selecting a short-term simulated operation scenario of the multi-DC transmission power grid to obtain planning data of the multi-DC transmission power grid; constructing a multi-DC transmission power grid planning model according to the planning data and based on the inertia level constraint and frequency safety constraint of the system; using the Benders decomposition algorithm and the commercial solver GAMS to solve the multi-DC transmission power grid planning model to obtain a power grid planning scheme; the power grid planning scheme obtained by the invention can ensure its frequency safety when it is subjected to the huge power impact caused by the fault disturbance, thereby ensuring the normal operation of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and more specifically, to a multi-DC transmission power grid planning method considering frequency security constraints. Background Art

[0002] In recent years, with the increase in the scale of installed capacity of new energy and ultra-high voltage direct current transmission, the pattern, operation form and stability characteristics of the clean energy-rich transmission grid have undergone profound changes. On the one hand, due to the large-scale access of new energy and the shutdown of a large number of conventional synchronous units, the rotational inertia and frequency regulation capabilities of the multi-DC transmission grid have decreased, and the grid regulation and anti-disturbance capabilities have continued to deteriorate. On the other hand, after the access of new energy, the startup capacity of traditional synchronous units will be squeezed. If the power grid adopts an operating mode of reducing the output of traditional synchronous units, it is difficult to ensure that the system has sufficient peak-shaving capacity and absorption capacity, resulting in the abandonment of new energy. Therefore, the planning of multi-DC transmission grids needs to consider the safety and stability of the grid and the level of new energy absorption on the basis of power balance.

[0003] The current grid planning method does not take into account various scenarios of multiple DC transmission grids and their frequency safety constraints, resulting in the grid scale and structure in the planning results being insufficient to ensure the safe and stable operation of the system under large-scale DC transmission. Summary of the invention

[0004] The technical problem solved by the present invention is that the scale and structure of the power grid obtained by the existing planning method are not sufficient to ensure the safe and stable operation state of the system under large-scale DC transmission; the purpose of the present invention is to provide a multi-DC transmission power grid planning method considering frequency safety constraints; the present invention plans the power structure and grid structure of the multi-DC transmission power grid to achieve the rationality of the power layout in the multi-DC transmission power grid and the adaptability of the grid structure.

[0005] The above technical objectives of the present invention are achieved through the following technical solutions:

[0006] A method for planning a multi-DC transmission power grid considering frequency security constraints, the method comprising the following steps:

[0007] Select a short-term simulation operation scenario of multiple DC transmission grids and obtain planning data of multiple DC transmission grids;

[0008] Constructing a two-level planning model of a multi-DC transmission grid according to the planning data and based on the inertia level constraint and frequency safety constraint of the system;

[0009] The Benders decomposition algorithm and the commercial solver GAMS are used to solve the multi-DC transmission grid planning model and obtain the grid planning solution.

[0010] The present invention selects a short-term simulation operation scenario. Since new energy and hydropower are sensitive to seasonal fluctuations, a variety of typical operation scenarios can be selected according to seasonality for research. Taking the minimization of new energy investment and construction costs, grid investment and construction costs, and thermal power retirement costs as the objective function, the system inertia level, new energy power sources and grid investment and construction constraints, and thermal power unit retirement constraints are modeled, and a long-term power grid planning model considering the system inertia level constraints is constructed as the outer model of the multi-DC transmission power grid planning model. The cost of short-term simulation operation, the output of various power sources in the system, and the line operation are modeled, and a short-term operation simulation considering frequency safety constraints is constructed as the inner model of the multi-DC transmission power grid planning model. Its constraints cover a variety of classic operation scenarios. The multi-stage multi-DC transmission power grid planning model is solved using the Benders decomposition algorithm and the commercial solver GAMS to obtain a grid planning scheme. According to the grid planning scheme, the power structure and grid structure of the multi-DC transmission power grid are planned to achieve the stability of the system's operating state under large-scale DC transmission.

[0011] Furthermore, a long-term power grid planning model considering the system inertia level constraint is constructed with the minimization of the investment and construction cost of new energy, grid investment and construction cost, and thermal power decommissioning cost as the objective function, as the outer model of the multi-DC transmission power grid planning model, that is, the objective function is Where y represents the yth planning stage in the planning; Y is the number of planning stages; μ y is the present value coefficient, f re 、f l and f g The investment costs of new energy units and grid, and the decommissioning costs of thermal power units are respectively.

[0012] Furthermore, in each planning stage of the outer model, the system inertia level must be greater than the system minimum inertia requirement, that is, the system inertia level calculation formula is in is the retirement state variable of the i-th thermal power unit in the y-th phase, is the inertia time constant of the i-th thermal power unit, is the inertia time constant of the hydropower unit, is the maximum output of the i-th thermal power unit; is the maximum output of the jth hydropower unit, is the maximum unbalanced power of the system, f0 is the initial value of the system frequency, RoCoF max is the maximum value of the frequency change rate.

[0013] Furthermore, a thermal power unit retirement model is constructed in the outer model, and the minimum cost of thermal power unit retirement is Among them, Ω g is the collection of thermal power units, is the retirement state variable of the i-th thermal power unit in the y-th phase, is the retirement state variable of the i-th thermal power unit in the y-1th stage, is the disposal cost of the i-th thermal power unit, is the recovery cost of the i-th thermal power unit, is the maximum output of the i-th thermal power unit, is the operating life of the i-th thermal power unit.

[0014] Furthermore, according to the fairness of the retirement path of thermal power units, the upper and lower limits of the number of thermal power units retired by each thermal power plant in each stage and the upper and lower limits of the total number of thermal power units retired by the entire power grid in each stage are set. In each stage, the total amount of subsidies for the retirement of thermal power plants should be limited to the upper limit, that is, In the formula, and are the upper and lower limits of the number of retired generating units of thermal power plant T in stage y, respectively. T is the correlation matrix between thermal power plant T and the i-th thermal power unit, and They represent the upper and lower limits of the total number of thermal power generating units retired in the yth stage, The upper limit of the subsidy for decommissioning thermal power plants.

[0015] Furthermore, a short-term operation model considering frequency constraints is constructed with the cost of short-term simulation operation, the output of various power sources in the system and the operating status of the lines as constraints, as the inner model of the multi-DC transmission network planning model.

[0016] Furthermore, a primary frequency regulation reserve constraint at the lowest frequency point in the inner model is obtained according to the frequency safety constraint under the anticipated accident, and the system's accident reserve power is greater than the unbalanced power under the anticipated accident.

[0017] Furthermore, the opportunity constraints of upper and lower spinning reserves are constructed according to the uncertainty of renewable energy output.

[0018] To cope with the uncertainty of renewable energy output, the spinning reserve in, is the reserve of the i-th thermal power unit at time t in scenario s to cope with the uncertainty of new energy output, is the reserve of the i-th hydropower unit at time t in scenario s to cope with the uncertainty of new energy output, α s,t,i is the participation factor of the i-th thermal power unit in the total wind and solar forecast error at time t in scenario s, β s,t,i is the participation factor of the i-th hydropower unit in the total wind and solar forecast error at time t in scenario s, Ω w and Ω pvThey are wind turbine set and photovoltaic set respectively. is the predicted output error of the i-th wind turbine at time t in scenario s, is the predicted output error of the i-th photovoltaic generator group at time t in scenario s;

[0019] The backup opportunity constraint to deal with system uncertainty is in, is the reserve capacity of the i-th thermal power unit at time t in scenario s, is the distribution function of new energy uncertainty, is the distribution function set of new energy uncertainty, is the reserve capacity of the ith hydropower unit at time t in scenario s, and 1-η is the maximum confidence rate of the fuzzy uncertain set Ξ.

[0020] Furthermore, Wasserstein distance quantization is used to process the nonlinear backup opportunity constraint to obtain the linear backup opportunity constraint.

[0021] Furthermore, system data, equipment parameters and operating parameters of the multi-DC transmission power grid are input, and the two-level planning model of the multi-DC transmission power grid is solved using the Benders decomposition algorithm and the commercial solver GAMS to obtain a power grid planning scheme, and the power supply structure and grid structure of the multi-DC transmission power grid are constructed according to the power grid planning scheme.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. A multi-DC transmission power grid planning method considering frequency safety constraints can achieve mutual matching among the decommissioning route of thermal power units, new energy power source planning, 500kV grid planning and multi-DC transmission capacity;

[0024] 2. The present invention provides a multi-DC transmission power grid planning method that takes frequency safety constraints into consideration, so that the planned power grid can ensure its frequency safety when it is subjected to a huge power impact caused by a fault disturbance, thereby ensuring the normal operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0026] Figure 1 A schematic diagram of a planning method according to an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of a multi-DC transmission grid planning model flow chart provided by an embodiment of the present invention;

[0028] Figure 3 A frequency simulation diagram of a power grid system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0030] It should be noted that when a component is referred to as being "fixed to" or "disposed on" another component, it can be directly on the other component or indirectly on the other component. When a component is referred to as being "connected to" another component, it can be directly or indirectly connected to the other component.

[0031] It should be understood that the orientation or position relationship indicated by terms such as "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0032] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0033] Embodiment 1

[0034] This embodiment 1 provides a multi-DC transmission grid planning method considering frequency safety constraints, such as Figure 1 As shown, the method comprises the following steps:

[0035] S1, selecting a short-term simulation operation scenario of multiple DC transmission grids and obtaining planning data of multiple DC transmission grids;

[0036] S2, constructing a two-level planning model of a multi-DC transmission grid according to the planning data and based on the inertia level constraint and frequency safety constraint of the system;

[0037] S3, uses the Benders decomposition algorithm and the commercial solver GAMS to solve the two-level planning model of the multi-DC transmission grid and obtain the grid planning scheme.

[0038] The technical solutions involved in steps S1, S2, and S3 are further explained below. As described below, for step S1, the planning data obtained include the installed capacity and construction site of the hydropower station, the location of the DC landing point, the scale of DC transmission, the installed capacity and location of the existing coal-fired power units, the distribution points and installed capacity of wind power plants and photovoltaic power plants, etc.; the power grid data of the target planning year is collected, including the load of the target year, the candidate locations for the planned new energy units, the candidate lines for the planned 500kV / 1000kV lines, etc.; the historical forecast data and historical output data of wind power and photovoltaic power output in various regions are collected; the daily scheduling data, hydropower machine flow, and 24h daily load of typical scenarios are collected.

[0039] A long-term power grid planning model considering the system inertia level constraint is constructed with the minimization of the investment and construction cost of new energy, grid investment and construction cost, and thermal power decommissioning cost as the objective function. This model is used as the outer model of the multi-DC transmission power grid planning model. That is, the objective function is Where y represents the yth planning stage in the planning; Y is the number of planning stages; μ y is the present value coefficient, f re 、f l and f g The investment costs of new energy units and grid, and the decommissioning costs of thermal power units are respectively.

[0040] For step 2, the outer model - the grid planning model considering the inertia level, the first step of the key technology of multi-stage grid planning is to establish the corresponding grid planning model. This section considers the costs of decommissioning thermal power units, investing in new energy grids and grid construction, as well as the related constraints of decommissioning thermal power units, investing in new energy and grid construction, and establishes the first-level planning model of multi-stage grid planning. The model takes the minimum present value of the total cost as the optimization goal, and the total cost is divided into the investment cost of new energy units and grids, and the decommissioning cost of coal-fired power units. On this basis, the objective function is defined as follows:

[0041]

[0042] Among them, μ y is the present value coefficient, which can be calculated by (2); f re 、f l and f g The investment costs of new energy units and grid, and the decommissioning costs of coal-fired power units are calculated using formulas (3)-(5) respectively.

[0043] μ y =(1+r) -[(y-1)Y+n] (2)

[0044]

[0045]

[0046] In the above formula, and The cost of investing in a single wind turbine in the i-th wind farm and the cost of investing in a single photovoltaic unit in the i-th photovoltaic farm; Represents the number of wind turbines invested and built by the i-th wind farm in the y-th phase; represents the number of photovoltaic units invested and built in the i-th PV power station in the y-th phase; the subscript l represents the line between nodes i and j; Ω l is a set of transmission lines; subscript k represents the kth line to be selected on line l; The set of routes to be selected; c l,k is the investment cost of the k-th line; z y,l,k It is a 0-1 variable for line construction decision; Maintenance and management costs for the new lines; is the operating life of the i-th thermal power unit; is the disposal cost of the i-th thermal power unit; is the recovery cost of the i-th thermal power unit; is the capacity of the i-th thermal power unit; τ is the capital recovery coefficient; TL is the operating life of the newly built wind / solar unit and the line.

[0047] In each planning stage of the outer model, the system's inertia level must be greater than the system's minimum inertia requirement, that is, the system's inertia level calculation formula is among them is the retirement state variable of the i-th thermal power unit in the y-th phase, is the inertia time constant of the i-th thermal power unit, is the inertia time constant of the hydropower unit, is the maximum output of the i-th thermal power unit; is the maximum output of the jth hydropower unit, is the maximum unbalanced power of the system, f0 is the initial value of the system frequency, RoCoF max The maximum frequency change rate

[0048] Constraints of grid planning: Inertia is an inherent property of the power system, which is manifested as the damping effect of the system on external interference and is the basic guarantee for the safe and stable operation of the system. Therefore, the system inertia level at each stage can be calculated using the following formula:

[0049]

[0050] At each planning stage, the inertia time constant of the system must satisfy the frequency change rate constraint at the initial stage of the disturbance:

[0051]

[0052] Due to the limitations of new energy investment and construction technology, the amount of new energy invested and constructed by power plants each year must be limited to a certain range:

[0053]

[0054] In the above formula, and They are the upper and lower limits of the number of wind turbines to be built in the i-th wind farm in the y-th phase respectively; and They are respectively the upper and lower limits of the number of photovoltaic units to be built in the i-th photovoltaic power station in the y-th stage.

[0055] Since the investment and construction costs of new energy are subject to local investment decisions and investment and construction funds, the investment and construction costs of new energy in each stage need to be limited below the maximum investment cost:

[0056]

[0057] In the above formula, is the maximum investment cost in stage y.

[0058] The line investment cost at each stage has certain budget constraints

[0059]

[0060] The number of lines allowed for construction in each line corridor is limited:

[0061]

[0062] In the above formula, and The maximum and maximum values ​​of the construction routes allowed for the (i, j) corridor in stage y respectively.

[0063] Furthermore, a thermal power unit retirement model is constructed in the outer model, and the minimum cost of thermal power unit retirement is Among them, Ω g is the collection of thermal power units, is the retirement state variable of the i-th thermal power unit in the y-th phase, is the retirement state variable of the i-th thermal power unit in the y-1th stage, is the disposal cost of the i-th thermal power unit, is the recovery cost of the i-th thermal power unit, is the maximum output of the i-th thermal power unit, is the operating life of the i-th thermal power unit.

[0064] According to the fairness of the retirement path of thermal power units, the upper and lower limits of the number of thermal power units retired by each thermal power plant in each stage and the upper and lower limits of the total number of thermal power units retired by the entire power grid in each stage are set. In each stage, the total amount of subsidies for the retirement of thermal power plants should be limited to the upper limit, that is,

[0065]

[0066] In the formula, and are the upper and lower limits of the number of retired generating units of thermal power plant T in stage y, respectively. T is the correlation matrix between thermal power plant T and the i-th thermal power unit, and They represent the upper and lower limits of the total number of thermal power generating units retired in the yth stage, The upper limit of the subsidy for decommissioning thermal power plants.

[0067] A good and feasible coal-fired power retirement path needs to be fair and ensure that its economic burden is not borne by individual regions and groups. Here we set the upper and lower limits of the number of coal-fired power units to be retired in each stage of each thermal power plant and the upper and lower limits of the total number of coal-fired power units to be retired in each stage of the entire power grid:

[0068]

[0069] In the above formula, and are the upper and lower limits of the number of retired generating units of thermal power plant T in stage y, respectively. T is the correlation matrix between thermal power plant T and the i-th thermal power unit, and They respectively represent the upper and lower limits of the total number of thermal power generating units retired in stage y.

[0070] In each phase, the total amount of government subsidies for decommissioning thermal power plants should be limited to an upper limit. Inside, as follows:

[0071]

[0072] A short-term operation model considering frequency constraints is constructed based on the cost of short-term simulation operation, the output of various power sources in the system and the operating status of the lines, which serves as the inner model of the multi-DC transmission network planning model.

[0073] For step 2, the inner model - short-term operation simulation considering frequency constraints, the inner model is as follows:

[0074]

[0075] In the above formula, Ωs is a set of scenes on a typical day, the subscript s represents the scene; Ω t is the time set of a typical day, and the subscript t represents the time; is the unit cost of the output of the i-th thermal power unit; is the unit cost of the standby of the i-th thermal power unit; is the unit cost of the standby of the i-th hydropower unit.

[0076] Considering the operation constraints of the inner model, the actual output of thermal power units and hydropower units is subject to the upper and lower limits of the unit output:

[0077]

[0078] In the above formula, and is the upper and lower limits of the active output of the i-th thermal power unit; and are the upper and lower limits of the active output of the i-th hydropower unit.

[0079] Considering the limited regulation capacity of the unit, the climbing constraints need to be met. The climbing constraints of thermal power units and hydropower units are:

[0080]

[0081] In the above formula, and is the upward climbing capacity and downward climbing capacity of the i-th thermal power unit; and is the upward climbing capacity and downward climbing capacity of the i-th hydropower unit.

[0082] At time t, node i needs to satisfy the power balance constraint, and the node power constraint is:

[0083]

[0084] In the above formula, F s,t,l,k is the active power of the line; K y,l is the collection of all lines.

[0085] For lines in the grid structure, the line flow constraints must also be met during operation:

[0086]

[0087]

[0088] In the above formula, and b is the upper and lower limits of the line active power; l,k is the susceptance value of the line; θs,t,l is the voltage phase angle difference; θ s,t,i is the voltage phase angle value of node i; Indicates the minimum phase angle allowed for node i; Indicates the maximum phase angle allowed for node i

[0089] It should be noted that in the expression Existence The nonlinear term can be processed by the big-M method:

[0090] -M(1-z y,l,k )≤z y,l,k b l,k θ s,t,l ≤M(1-z y,l,k ).

[0091] According to the frequency safety constraint under the expected accident, the primary frequency regulation reserve constraint at the lowest frequency point in the inner model is obtained, and the system's accident reserve power is greater than the unbalanced power under the expected accident.

[0092] When a DC fault or generator outage occurs in the power grid, the system will experience power surplus or shortage, and the system frequency will rise or fall accordingly. In order to ensure the safe and stable operation of the power grid, frequency safety constraints must be introduced. The expression of unbalanced power and system frequency change can be expressed by a first-order differential equation.

[0093]

[0094] In the above formula, is the system inertia time constant at time t; D is the damping coefficient; is the state coefficient of the thermal power unit at time t; is the state coefficient of the hydropower unit at time t.

[0095] When a fault occurs, the frequency change rate RoCoF is the largest. During a frequency modulation process, RoCoF needs to be limited to the maximum frequency change rate RoCoF allowed by the system. max Within.

[0096]

[0097] During a frequency regulation process, in order to ensure that the system has sufficient peak-shaving and absorption capabilities, a certain amount of power abandonment from renewable energy sources is required to meet the frequency safety constraint. The expression of the frequency safety constraint is as follows.

[0098]

[0099] In the above formula, Total modulation of DC; is the climbing speed of the thermal generator under fault; It is the climbing speed of the faulty water motor.

[0100] The modulation amount of the i-th DC line will be limited by the DC capacity:

[0101]

[0102] In the above formula, is the modulation amount of the ith DC line; is the capacity of the ith DC line.

[0103] The system's emergency reserve must be greater than the unbalanced power under anticipated accidents.

[0104]

[0105] Since equations (30) and (31) contain bilinear variables and McCormick relaxation is used here to handle bilinear terms.

[0106]

[0107]

[0108] According to the uncertainty of renewable energy output, the opportunity constraints of upper and lower spinning reserves are constructed.

[0109] To cope with the uncertainty of renewable energy output, the following spinning reserves need to be preset:

[0110] Among them, α s,t,i is the participation factor of thermal power unit i in dealing with the total error of wind and solar power forecast, β s,t,i is the participation factor of hydropower unit i in dealing with the total error of wind and solar power forecast, and Contribute to the uncertainty of the scenery;

[0111] The backup opportunity constraint to deal with system uncertainty is in, is the reserve capacity of the i-th thermal power unit at time t in scenario s, is the distribution function of new energy uncertainty, is the distribution function set of new energy uncertainty, is the reserve capacity of the ith hydropower unit at time t in scenario s, and 1-η is the maximum confidence rate of the fuzzy uncertain set Ξ.

[0112] Taking into account the forecast error of renewable energy output and load, the system needs to ensure a certain amount of spinning reserve during operation, including upper spinning reserve and lower spinning reserve. The forecast error constraint of renewable energy output is:

[0113]

[0114] In the above formula, and are the boundary values ​​of the budget uncertainty set composed of the actual wind power output; and They are the boundary values ​​of the budget uncertainty set composed of the actual photovoltaic output.

[0115] The spinning reserves that each thermal power unit and hydropower unit needs to preset to respond to the uncertainty of renewable energy output are:

[0116]

[0117] In the above formula, is the reserve of the i-th thermal power unit at time t in scenario s to cope with the uncertainty of new energy output, is the reserve of the i-th hydropower unit at time t in scenario s to cope with the uncertainty of new energy output, α s,t,i is the participation factor of the i-th thermal power unit in the total wind and solar forecast error at time t in scenario s, β s,t,i is the participation factor of the i-th hydropower unit in the total wind and solar forecast error at time t in scenario s, Ω w and Ω pv They are wind turbine set and photovoltaic set respectively. is the predicted output error of the i-th wind turbine at time t in scenario s, is the predicted output error of the i-th PV generator group at time t in scenario s.

[0118] The alternative adoption opportunity constraint to cope with system uncertainty is expressed as:

[0119]

[0120] In the above formula, is the reserve capacity of the i-th thermal power unit at time t in scenario s, is the distribution function of new energy uncertainty, is the distribution function set of new energy uncertainty, is the reserve capacity of the ith hydropower unit at time t in scenario s, and 1-η is the maximum confidence rate of the fuzzy uncertain set Ξ.

[0121] Based on the historical data of wind power, a probability distribution confidence set of wind power scenarios is established, and the Wasserstein distance is used to quantify the distance between the true distribution of renewable energy output errors and the historical empirical distribution of renewable energy output errors:

[0122]

[0123] In the above formula: The empirical distribution function representing the error in the output of renewable energy; The true distribution function representing the error in the output of renewable energy; represents the historical sample parameter of the new energy output error; M represents the number of historical samples of the new energy output error; The random parameter representing the error of renewable energy output; The joint distribution function representing the two probabilities of the empirical distribution and the true distribution; Represents the distance function between the empirical distribution and the true distribution. In order to approximate the true distribution of the new energy output parameters that conforms to the rules behind the historical data and obtain the true distribution of the regional new energy output parameters with uncertainty, the Wasserstein ball expression is used, that is, the empirical distribution is the center of the sphere, the true distribution Restricted to a sphere of radius ε(N):

[0124]

[0125] In the above formula: Ω is the set of uncertain parameters of new energy output; represents the set of all distribution functions containing uncertain parameters of renewable energy output; β r is the confidence interval, and here it takes a fixed value of 0.95.

[0126] Wasserstein distance quantization is used to process nonlinear backup opportunity constraints to obtain linear backup opportunity constraints.

[0127] Since the calculation formulas (39) and (40) of the above opportunity constraints are difficult to handle, the Wasserstein distance is used for quantization, as follows. For the convenience of explanation, the opportunity constraints (39) and (40) can be expressed as express.

[0128] Step 1: Standardize the sample set: in is the sample size after standardization, is the variance of the error sample parameter, is the average value of the error sample parameter. Similarly, the standardized processing of the uncertainty parameters of new energy is

[0129] Step 2: Use Γ max express The maximum boundary value of The boundary adjustment amount is used to construct the uncertain set Θ:

[0130] Step 3: Construct the model To solve the boundary Γσ. According to the duality theory, it can be transformed into model 2:

[0131]

[0132] Step 4: Solve Model 2 using the nested dichotomy method.

[0133] The system data, equipment parameters and operation parameters of the multi-DC transmission power grid are input, and the two-level planning model of the multi-DC transmission power grid is solved by using the Benders decomposition algorithm and the commercial solver GAMS to obtain the power grid planning scheme. The power supply structure and grid structure of the multi-DC transmission power grid are constructed according to the power grid planning scheme.

[0134] For step S3, the above-mentioned two-layer linear programming model and Benders decomposition method are used to obtain a planning scheme for a multi-DC transmission power grid, and a power source structure and a grid structure of the multi-DC transmission power grid are constructed according to the planning scheme.

[0135] Embodiment 2

[0136] This second embodiment further illustrates the method based on the first embodiment, and applies it to an actual provincial power grid system to realize multi-DC transmission power grid planning. The system parameters are shown in Table 1:

[0137] Table 1 System parameters

[0138] parameter Numeric Number of nodes 168 Number of branches 389 Load 92.78GW Delivery volume 66.6GW

[0139] According to the above objective function and constraints, a two-level planning model is established, and the planning scheme of the multi-DC transmission power grid is solved. Since the method involves the retirement of thermal power units, the deployment of new energy sources and the strengthening of 500kV grid, the obtained scheme realizes the mutual matching between the retirement route of thermal power units, the planning of new energy sources, the planning of 500kV grid and the multi-DC transmission volume. In the planning scheme of the multi-DC transmission power grid, the retirement of thermal power units is divided into two stages: during the first stage, a total of 8 thermal power plants were closed, 13 thermal power units were retired, and the total retired capacity of thermal power units was 4830WM; during the second stage, 9 thermal power plants were closed, 17 thermal power units were retired, and the total retired capacity of thermal power units was 9300WM. The specific retirement routes are shown in Table 2.

[0140] Table 2: Decommissioning of thermal power units in the power grid in two stages

[0141] Power plant area Number of units*Capacity (MW) Retirement stage Power Plant 1 2*1000 Phase 2 Power Plant 2 2*600 Phase 2 Power Plant 3 2*600 Phase 1 Power Plant 4 2*300 Phase 1 Power Plant 5 2*300、2*600 Phase 2 Power Plant 6 2*600 Phase 2 Power Plant 7 2*330 Phase 1 Power Plant 8 2*600 Phase 1 Power Plant 9 1*600 Phase 2 Power Plant 10 1*600 Phase 2 Power Plant 11 1*700 Phase 2 Power Plant 12 2*300 Phase 2 Power Plant 13 2*300 Phase 2 Power Plant 14 1*135 Phase 1 Power Plant 15 1*135 Phase 1 Power Plant 16 1*300 Phase 1 Power Plant 17 2*330 Phase 1

[0142] In the multi-DC transmission grid planning scheme, the new energy points are mainly concentrated in three areas in the southwest. The new energy power source point plan includes two stages: During the first stage, the grid plans to add 31,000 MW of new energy, including 23,000 MW of wind power and 8,000 MW of photovoltaic power. During the second stage, the total installed capacity of the new energy planned by the grid is 62,000 MW, including 48,000 MW of new wind turbines and 14,000 MW of new photovoltaic units. The specific results of new energy investment and construction are shown in Table 3.

[0143] Table 3 Results of investment and construction of new energy units in two phases

[0144]

[0145] In the multi-DC transmission grid planning scheme, the grid reinforcement planning results are as follows: in the first phase, two new 1000 kV lines and four new 500 kV lines are planned to be built, with a new line length of 1248.8 kilometers; in the second phase, five new 1000 kV lines and 11 new 500 kV lines are planned to be built, with a new line length of 2614 kilometers. The planned grid structure can guarantee the transmission of 66.5GW of DC capacity. The specific grid planning results are shown in Table 4.

[0146] Table 4 Results of grid planning in two stages

[0147]

[0148] For the planned power grid, simulate the expected faults to verify the safety of its frequency. Set a large-capacity DC line in the system to have a bipolar locking fault. Use the simulation software to get the system frequency. Figure 3 The results show that after a large-capacity DC line in the system has a bipolar locking fault, the frequency change is within the range of 50.5Hz, indicating that the planned power grid can ensure its frequency safety when it is subjected to the huge power impact caused by the fault disturbance, thus ensuring the normal operation of the power grid.

[0149] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for planning a multi-DC transmission network considering frequency security constraints, characterized in that: The method comprises the following steps, Select a short-term simulation operation scenario of multiple DC transmission grids and obtain planning data of multiple DC transmission grids; According to the planning data and based on the system's inertia level constraint and frequency safety constraint, a two-level planning model of a multi-DC transmission power grid is constructed; wherein, a long-term power grid planning model considering the system inertia level constraint is constructed with the minimization of the new energy investment and construction cost, the grid investment and construction cost, and the thermal power decommissioning cost as the objective function, as the outer model of the multi-DC transmission power grid planning model, that is, the objective function is Where y represents the yth planning stage in the planning; Y is the number of planning stages; μ y is the present value coefficient, f re 、f l and f g The investment cost of new energy units and grid, and the retirement cost of thermal power units are respectively; in each planning stage of the outer model, the inertia level of the system needs to be greater than the minimum inertia requirement of the system, that is, the inertia level calculation formula of the system is in is the retirement state variable of the i-th thermal power unit in the y-th phase, is the inertia time constant of the i-th thermal power unit, is the inertia time constant of the hydropower unit, is the maximum output of the i-th thermal power unit; is the maximum output of the jth hydropower unit, is the maximum unbalanced power of the system, f0 is the initial value of the system frequency, RoCoF max is the maximum value of the frequency change rate; a thermal power unit retirement model is constructed in the outer model, and the minimum cost of thermal power unit retirement is: ； Among them, Ω g is the collection of thermal power units, is the retirement state variable of the i-th thermal power unit in the y-th phase, is the retirement state variable of the i-th thermal power unit in the y-1th stage, is the disposal cost of the i-th thermal power unit, is the recovery cost of the i-th thermal power unit, is the maximum output of the i-th thermal power unit, is the operating life of the i-th thermal power unit; A short-term operation model considering frequency constraints is constructed based on the cost of short-term simulation operation, the output of various power sources in the system, and the operating status of the lines, as the inner model of the multi-DC transmission grid planning model. The Benders decomposition algorithm and the commercial solver GAMS are used to solve the two-level planning model of multiple DC transmission grids and obtain the planning scheme of multiple DC transmission grids.

2. A method for planning a multi-DC transmission network considering frequency security constraints according to claim 1, characterized in that: According to the fairness of the retirement path of thermal power units, the upper and lower limits of the number of thermal power units retired by each thermal power plant in each stage and the upper and lower limits of the total number of thermal power units retired by the entire power grid in each stage are set. In each stage, the total amount of subsidies for the retirement of thermal power plants should be limited to the upper limit, that is, In the formula, and are the upper and lower limits of the number of retired generating units of thermal power plant T in stage y, respectively. T is the correlation matrix between thermal power plant T and the i-th thermal power unit, and They represent the upper and lower limits of the total number of thermal power generating units retired in the yth stage, The upper limit of the subsidy for decommissioning thermal power plants.

3. A method for planning a multi-DC transmission network considering frequency security constraints according to claim 1, characterized in that: According to the frequency safety constraint under the expected accident, the primary frequency regulation reserve constraint at the lowest frequency point in the inner model is obtained, and the system's accident reserve power is greater than the unbalanced power under the expected accident.

4. The method for planning a multi-DC transmission network considering frequency security constraints according to claim 1, characterized in that: According to the uncertainty of renewable energy output, the opportunity constraints of upper and lower spinning reserves are constructed. To cope with the uncertainty of renewable energy output, the following spinning reserves need to be preset: in, is the reserve of the i-th thermal power unit at time t in scenario s to cope with the uncertainty of new energy output, is the reserve of the i-th hydropower unit at time t in scenario s to cope with the uncertainty of new energy output, α s,t,i is the participation factor of the i-th thermal power unit in the total wind and solar forecast error at time t in scenario s, β s,t,i is the participation factor of the i-th hydropower unit in the total wind and solar forecast error at time t in scenario s, Ω w and Ω pv They are wind turbine set and photovoltaic set respectively. is the predicted output error of the i-th wind turbine at time t in scenario s, is the predicted output error of the i-th photovoltaic generator group at time t in scenario s; The backup opportunity constraint to deal with system uncertainty is in, is the reserve capacity of the i-th thermal power unit at time t in scenario s, is the distribution function of new energy uncertainty, is the distribution function set of new energy uncertainty, is the reserve capacity of the ith hydropower unit at time t in scenario s, and 1-η is the maximum confidence rate of the fuzzy uncertain set Ξ.

5. A method for planning a multi-DC transmission network considering frequency security constraints according to claim 4, characterized in that: Wasserstein distance quantization is used to process nonlinear backup opportunity constraints to obtain linear backup opportunity constraints.

6. A method for planning a multi-DC transmission network considering frequency security constraints according to claim 1, characterized in that: The system data, equipment parameters and operation parameters of the multi-DC transmission power grid are input, and the multi-stage multi-DC transmission power grid planning model is solved by using the Benders decomposition algorithm and the commercial solver GAMS to obtain the power grid planning scheme, and the power supply structure and grid structure of the multi-DC transmission power grid are constructed according to the power grid planning scheme.

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