Extra-high voltage direct current matching power supply planning method and system

Abstract

The invention relates to the technical field of power systems, and discloses an extra-high voltage direct current matching power supply planning method and system. The method comprises the following steps: collecting original simulation data required by extra-high voltage direct current project matched power supply planning, and preprocessing the original simulation data to obtain target simulation data; constructing a new energy base matched power supply planning objective function considering extra-high voltage direct current project collaborative optimization; setting a capacity planning constraint condition based on an electric power system operation safety requirement, and setting a direct current power transmission constraint condition in consideration of an extra-high voltage direct current project power transmission operation characteristic and a new energy base electric power delivery requirement; and in combination with the target simulation data, solving the new energy base matched power supply planning target function according to the capacity planning constraint condition and the direct current transmission constraint condition to obtain the new energy base matched power supply planning installed capacity. According to the invention, collaborative planning of the extra-high voltage direct current project and the new energy base matching power supply can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and particularly to a method and system for planning a supporting power source for ultra-high voltage direct current. Background Art

[0002] With the transformation of the energy structure, large-scale wind-solar bases represented by the desert, Gobi, and hilly areas are accelerating development, and their power consumption highly depends on cross-regional ultra-high voltage direct current transmission projects. Ultra-high voltage direct current is not only the core channel connecting the new energy base at the sending end and the load center at the receiving end, but also needs to form a coordinated operation mechanism with the supporting power source of the base to achieve efficient power allocation with source-network linkage.

[0003] Currently, the planning of new energy bases supporting ultra-high voltage direct current projects mostly adopts a mode of separating power source planning and direct current operation optimization. On the one hand, power source planning often aims at the output stability of a single base or the minimization of local costs, without fully connecting with the transmission characteristics of direct current projects, resulting in a mismatch between the installed capacity planned and the direct current transmission capacity. On the other hand, the formulation of the direct current operation curve still uses the traditional two-stage or three-stage constant power mode, simply dividing time periods based on the peak and valley of the load at the receiving end, without considering the intermittency and volatility of the new energy output at the sending end, resulting in a disconnection between the power balance at the sending and receiving ends. At the same time, existing planning methods are mostly based on deterministic simulations and are difficult to cover extreme scenarios with small probabilities and high impacts such as continuous windless and lightless days for multiple days. In such scenarios, if the peak shaving and reserve capacity planning of the supporting power source of the base is insufficient, power shortages are likely to occur, forcing the receiving end to cut loads or the sending end to abandon electricity.

[0004] Therefore, there is an urgent need for a planning method that can achieve coordinated optimization of ultra-high voltage direct current projects and the supporting power sources of new energy bases to adapt to the operation requirements of source-network coordination in the new power system. Summary of the Invention

[0005] In view of the above problems existing in the prior art, the present invention provides a method and system for planning a supporting power source for ultra-high voltage direct current.

[0006] In a first aspect, an embodiment of the present invention provides a method for planning a supporting power source for ultra-high voltage direct current, including: Collecting the original simulation data required for the planning of the supporting power source for ultra-high voltage direct current projects, and preprocessing the original simulation data to obtain target simulation data; Taking the total cost composed of investment cost and operation cost as the objective, constructing an objective function for the planning of the supporting power source of the new energy base considering the coordinated optimization of ultra-high voltage direct current projects, where the operation cost is the multi-scenario probability weighted expected value based on the uncertainty of new energy output; Setting capacity planning constraint conditions based on the operation safety requirements of the power system, and setting direct current transmission constraint conditions considering the transmission operation characteristics of ultra-high voltage direct current projects and the power transmission requirements of new energy bases; Based on the target simulation data, the objective function of the power supply planning for the new energy base is solved according to the capacity planning constraints and the DC transmission constraints, so as to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0007] Preferably, the process of collecting the original simulation data required for the planning of power sources supporting the UHVDC project and preprocessing the original simulation data to obtain the target simulation data includes: The original simulation data is obtained from the database related to the power supply planning of the UHVDC project. The original simulation data includes power supply installed capacity data, grid installed capacity data, new energy power generation time series curves, and load time series curves. The original simulation data is preprocessed to obtain the target simulation data, wherein the preprocessing includes data cleaning, outlier correction, and time series alignment.

[0008] Preferably, the objective function for planning the supporting power supply for the new energy base, with the goal of minimizing the total cost consisting of investment and operating costs, includes: The investment cost is constructed based on the sum of the annualized investment and fixed operation and maintenance costs per unit installed capacity of various supporting power sources in the new energy base, combined with the planned installed capacity of the corresponding supporting power sources. Based on several scenario probabilities, the active power output of the supporting thermal power units of the new energy base and the active power output of the receiving-end grid-regulated thermal power units are weighted and calculated. Combined with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity, the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power is determined. The total cost is obtained by summing the investment cost and the operating cost, and the objective function for planning the supporting power supply of the new energy base is constructed by minimizing the total cost.

[0009] Preferably, the capacity planning constraints include power balance constraints, thermal power unit operation constraints, new energy operation constraints, and energy storage operation constraints.

[0010] Preferably, the DC transmission constraints include DC power range constraints, DC constant operating time constraints, channel utilization hours constraints, and new energy penetration rate constraints.

[0011] Preferably, the step of combining the target simulation data and solving the objective function of the power supply planning for the new energy base according to the capacity planning constraints and the DC transmission constraints to obtain the planned installed capacity of the power supply for the new energy base adapted to the external transmission needs of the UHVDC project includes: Substituting the target simulation data into the objective function of the power supply planning for the new energy base, and under the boundary constraints of the capacity planning constraints and the DC transmission constraints, the algorithm is used to solve the problem and output the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0012] Secondly, embodiments of the present invention provide an ultra-high voltage direct current (UHVDC) power supply planning system, comprising: The data processing module is used to collect the original simulation data required for the planning of power supply for ultra-high voltage direct current projects, and to preprocess the original simulation data to obtain the target simulation data. The objective construction module is used to construct an objective function for planning the supporting power supply of the new energy base, taking into account the synergistic optimization of the UHVDC project, with the objective of minimizing the total cost consisting of investment cost and operating cost. The operating cost is a multi-scenario probability weighted expectation value based on the uncertainty of new energy output. The constraint setting module is used to set capacity planning constraints based on the power system operation safety requirements, and to set DC transmission constraints taking into account the transmission operation characteristics of UHVDC projects and the power transmission needs of new energy bases. The capacity planning module is used to combine the target simulation data and solve the objective function of the power supply planning for the new energy base according to the capacity planning constraints and the DC transmission constraints, so as to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0013] Preferably, the data processing module includes: The data acquisition unit is used to acquire raw simulation data from a database related to the power supply planning of the UHVDC project. The raw simulation data includes power supply installed capacity data, grid installed capacity data, new energy power generation time series curves, and load time series curves. The preprocessing unit is used to preprocess the original simulation data to obtain the target simulation data, wherein the preprocessing includes data cleaning, outlier correction, and timing alignment.

[0014] Preferably, the target building module includes: The first cost determination unit is used to construct the investment cost based on the sum of the annualized investment and fixed operation and maintenance costs of the unit installed capacity of various supporting power sources in the new energy base, combined with the planned installed capacity of the corresponding supporting power sources. The second cost determination unit is used to perform weighted calculations on the active power output of the supporting thermal power units of the new energy base and the active power output of the receiving-end grid-regulated thermal power units under each scenario based on several scenario probabilities, and to determine the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power in combination with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity. The objective function determination unit is used to sum the investment cost and the operating cost to obtain the total cost, and to construct the objective function for the planning of supporting power sources for the new energy base by minimizing the total cost.

[0015] Preferably, the capacity planning module includes: The solution unit is used to substitute the target simulation data into the objective function of the power supply planning for the new energy base, and solve it through a stochastic programming algorithm under the boundary constraints of the capacity planning constraints and the DC transmission constraints, and output the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0016] Compared with the prior art, the UHVDC power supply planning method and system of this invention has the following advantages at least one point: (1) When constructing the objective function, the collaborative optimization of UHVDC projects is incorporated, and the operating cost is calculated using multi-scenario probability weighting to cope with the uncertainty of new energy output. This avoids the mismatch between installed capacity and external transmission capacity caused by the separation of power source and DC project in traditional planning, and can accurately adapt to the transmission characteristics of DC projects to ensure stable power output from the sending end base to match the DC power transmission curve.

[0017] (2) With the goal of minimizing the total cost of “investment cost + operating cost”, the investment cost covers all types of supporting power sources such as wind, solar, thermal and energy storage, and the operating cost focuses on the variable cost of thermal power and fuel costs. The final installed capacity scheme can control the initial investment by reasonably configuring the power source type and scale, reduce the operating energy consumption and costs by optimizing the dual-end thermal power regulation, and improve the proportion of new energy consumption by relying on the efficient transmission of DC projects. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for planning ultra-high voltage direct current power supply according to an embodiment of the present invention. Figure 2 This is a flowchart illustrating the process of constructing the objective function for planning the supporting power supply for a new energy base, according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the DC power transmission curve and power balance during a typical summer week. Figure 4 This is a schematic diagram of the DC power transmission curve and power balance during a typical week in winter. Figure 5 This is a schematic diagram of the structure of an ultra-high voltage direct current power supply planning system according to an embodiment of the present invention; Figure label: 01. Data Processing Module; 02. Target Construction Module; 03. Constraint Setting Module; 04. Capacity Planning Module. Detailed Implementation

[0019] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0020] In the description of this invention, it should be understood that the terms "first" and "second," etc., are used to distinguish different objects, rather than to describe a specific order.

[0021] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by those skilled in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0022] Ultra-high voltage direct current (UHVDC) projects refer to power transmission infrastructure that uses ±800kV and above DC voltage levels to achieve long-distance, high-capacity power transmission across regions. Their core function is to connect the sending-end renewable energy base with the receiving-end load center, forming a power transmission channel through converter stations, DC transmission lines, and control and protection systems. They require coordinated operation with the base's supporting power sources to ensure stable and efficient power allocation. This invention addresses existing problems in UHVDC project power source planning, such as the disconnect between sending and receiving end operations, insufficient handling of uncertainties in renewable energy output, and inadequate consideration of DC transmission flexibility. It provides a method for planning UHVDC supporting power sources to achieve coordinated optimization of power source planning and DC projects, ensuring that the planning results meet DC transmission needs while also considering system safety, economy, and cleanliness.

[0023] like Figure 1 The diagram shown is a flowchart illustrating a method for planning ultra-high voltage direct current (UHVDC) power supply systems according to an embodiment of the present invention. (Refer to...) Figure 1 This invention provides a method for planning ultra-high voltage direct current (UHVDC) power supply, comprising the following steps: S1. Collect the original simulation data required for the planning of power supply for ultra-high voltage direct current projects, and preprocess the original simulation data to obtain the target simulation data; Specifically, step S1 includes: 11) Obtain the original simulation data from the database related to the power supply planning for the UHVDC project; The original simulation data includes power installation data, grid installation data, new energy power generation time series curves, and load time series curves.

[0024] Specifically, the power installation data and new energy power generation time series curves are obtained from the clean energy power generation basic database. The clean energy power generation basic database is a power generation-side data support library dedicated to serving the new energy bases supporting UHV DC projects, and is the main data source for analyzing the output characteristics of new energy, calculating the installed capacity, and simulating scenarios in power source planning.

[0025] The power installation data includes the initial installed capacity, upper bound of optimized installed capacity, annualized investment per unit of installed capacity, fixed operation and maintenance costs, and key unit parameters of four types of power sources: wind, light, fire, and energy storage (such as the minimum output ratio of thermal power, continuous discharge duration of energy storage, conversion efficiency of wind power / photovoltaic units). The new energy power generation time series curves include hourly measured output curves of wind and light units in the recent 3 - 5 years, hourly output curves under conventional fluctuation scenarios and extreme output scenarios (such as continuous days of no wind and no light) trained based on generative adversarial networks, and typical output sub-curves divided by seasons (spring / summer / autumn / winter).

[0026] Furthermore, the grid installation data and load time series curves are obtained from the load characteristic library. The load characteristic library is an electricity consumption-side data support library dedicated to serving the receiving-end grid of UHV DC projects, and is the core basis for optimizing the DC power transmission curve, matching the receiving-end peak shaving capacity, and setting power balance constraints in power source planning.

[0027] The grid installation data includes the initial transmission channel capacity of the receiving-end grid (including the rated power of UHV DC projects), the installed capacity and peak shaving reserve capacity of regulated thermal power units at the receiving end, and the transmission limit parameters of grid lines. The load time series curves include hourly measured load curves of the receiving-end grid in the recent 3 - 5 years, predicted hourly load curves for the next 5 - 10 years, and typical load sub-curves divided by daily peak, valley, and flat periods, weekly weekdays / holidays, seasons (summer cooling / winter heating), and time series curves of load ratios by industry (industry / residents / commercial).

[0028] 12) Preprocess the original simulation data to obtain the target simulation data.

[0029] The preprocessing includes data cleaning, outlier correction, and time series alignment. The following is a specific description of each preprocessing operation: ① Data cleaning: Missing value handling: If there are hourly data missing in the new energy output time series curve exported from the clean energy power generation basic database, it is filled by the similar day interpolation method (such as using the average value of the同期出力 of adjacent days in the same season and the same weather type) or the machine learning filling method (such as predicting the output of the missing period based on long short-term memory network) to ensure the continuity of time series data.

[0030] Duplicate value removal: Delete duplicate power installed capacity parameters and cost parameters (such as duplicate records of investment cost for the same thermal power unit) to avoid data redundancy and duplicate calculations.

[0031] Invalid value filtering: Remove erroneous data that obviously violates common sense in engineering (such as negative upper limits for new energy installed capacity optimization, zero fuel cost, etc.) to ensure that the data conforms to actual engineering logic.

[0032] ②Outlier correction: Error-type outlier correction: If the output of a single hour is zero (non-nighttime photovoltaic) or the output of a single hour far exceeds the rated power of the unit in the new energy output time series, it is determined to be a monitoring error and corrected by the moving average method (such as replacing the outlier with the average output of the previous 3 hours).

[0033] Scenario-based outlier retention: If an outlier corresponds to an extreme scenario (such as wind power output continuously falling below 5% of the rated value due to seven consecutive days of no wind) and is supported by historical meteorological data, the outlier will be retained and marked as extreme scenario data, and included in subsequent stochastic planning calculations.

[0034] ③ Timing alignment: Time series data from different sources are uniformly converted into timestamps in the same time zone to avoid deviations in power supply and demand calculations caused by time misalignment.

[0035] It should be noted that preprocessing includes, but is not limited to, the three operations mentioned above, as well as data correlation verification and data standardization, all of which are existing conventional techniques and will not be elaborated upon here. By preprocessing the original simulation data, target simulation data that is easier to use for subsequent simulation calculations is obtained.

[0036] S2. With the goal of minimizing the total cost consisting of investment cost and operating cost, construct an objective function for planning the supporting power supply of the new energy base, taking into account the synergistic optimization of the UHVDC project. Because renewable energy output is subject to fluctuations, intermittent nature, and extreme scenarios such as multiple consecutive days without wind or solar power, a single deterministic calculation cannot accurately reflect the actual operating cost. Furthermore, it is necessary to take into account the peak-shaving costs of the thermal power units supporting the sending end and the regulating thermal power units at the receiving end in coordination with the UHVDC project. Therefore, the operating cost is a probability-weighted expected value based on the uncertainty of renewable energy output across multiple scenarios.

[0037] like Figure 2 As shown, this is a flowchart illustrating step S2. (Refer to...) Figure 2 Step S2 includes: S201. Based on the sum of the annualized investment and fixed operation and maintenance costs of the unit installed capacity of various supporting power sources in the new energy base, and combined with the planned installed capacity of the corresponding supporting power sources, the investment cost is constructed. Specifically, the investment cost is calculated using the following formula: in, This indicates the total investment cost of the power supply system for the new energy base. This indicates the investment cost of power supplies. This indicates the investment cost of energy storage. This represents the sum of the annualized investment per unit installed capacity and the fixed operation and maintenance costs of a thermal power unit. This indicates the planned installed capacity of thermal power units. This represents the sum of the annualized investment per unit installed capacity and the fixed operation and maintenance costs of a wind turbine. This indicates the planned installed capacity of wind turbine units. This represents the sum of the annualized investment per unit installed capacity and the fixed operation and maintenance costs of a photovoltaic (PV) unit. This indicates the planned installed capacity of photovoltaic (PV) units. This represents the sum of the annualized investment per unit installed capacity and the fixed operation and maintenance costs of energy storage equipment. This indicates the planned installed capacity of energy storage equipment. , , , These are decision variables.

[0038] S202. Based on several scenario probabilities, the active power output of the supporting thermal power units of the new energy base and the active power output of the grid-regulated thermal power units at the receiving end are weighted and calculated. Combined with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity, the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power is determined. Specifically, the operating cost is calculated using the following formula: in, This indicates the total operating cost of the power supply supporting the new energy base. This indicates the variable operating cost of thermal power plants. Indicates the cost of fuel for thermal power generation. This indicates the number of operating scenarios, covering both normal fluctuation scenarios and extreme output scenarios (such as scenarios with no wind and no light for several consecutive days). This indicates the amount of time in an annual cycle, typically 8760 hours per year. Representing a scene The probability of occurrence is obtained from historical data statistics or generative adversarial network training; the sum of the probabilities of all scenarios is 1. This represents the annual cycle ratio coefficient, used to extend the time dimension of typical scenarios to a full-year cycle, ensuring that cost calculations cover the entire year. This indicates the variable operating cost per unit of electricity generated by thermal power units. This represents the fuel cost per unit of electricity generated by a thermal power unit. Represents the scenario , time Under the circumstances, the active power output of the thermal power units supporting the new energy base at the sending end Represents the scenario , time Under the circumstances, the active power output of the regulating thermal power units in the receiving-end power grid

[0039] It should be noted that since new energy has no variable operating cost, the operating cost only includes the variable operating cost of thermal power and the fuel cost of thermal power

[0040] S203. Accumulate the investment cost and the operating cost to obtain the total cost, and construct the planning objective function of the power sources supporting the new energy base by minimizing the total cost

[0041] Specifically, the following formula is used to represent the planning objective function of the power sources supporting the new energy base Among them Represents the total cost

[0042] S3. Set the capacity planning constraint conditions based on the requirements of the safe operation of the power system, and considering the transmission operation characteristics of the UHVDC project and the power transmission demand of the new energy base, set the DC transmission constraint conditions , Specifically, the capacity planning constraint conditions include power balance constraint conditions, thermal power unit operation constraint conditions, new energy operation constraint conditions, and energy storage operation constraint conditions

[0043] The following is a specific description of the capacity planning constraint conditions 1) Power balance constraint conditions Among them Represents the scenario , time Under the circumstances, the active power output of the wind turbines supporting the new energy base at the sending end Represents the scenario , time Under the circumstances, the active power output of the photovoltaic units supporting the new energy base at the sending end Represents the scenario , time [[ID=]]Under the circumstances, the discharge power of the energy storage equipment supporting the new energy base at the sending end Represents the scenario , time Under the circumstances, the charging power of the energy storage equipment supporting the new energy base at the sending end< / / Represents the scenario , time The formula represents the power transmitted by an ultra-high voltage direct current (UHVDC) project. It indicates the power balance at the sending end, meaning that the active power output of the generating units at the sending end equals the power transmitted through the transmission channel at each time point in each scenario.

[0044] in, Representing a scene ,time The following is the load demand of the receiving-end power grid. This formula represents the power balance at the receiving end. To ensure fairness, it is required that the power transmitted through the transmission channel and the regulating thermal power at the receiving end jointly meet a portion of the receiving-end load. The maximum value of this portion of the load is the same as the rated capacity of the DC transmission channel, and its characteristics are the same as the receiving-end load curve.

[0045] 2) Operating constraints of thermal power units: in, This represents the minimum output coefficient of a thermal power unit, which is the ratio of the minimum output of a thermal power unit to its rated installed capacity. This formula is a constraint on the output range of thermal power units.

[0046] in, This represents the downward ramp rate coefficient of a thermal power unit, which is the maximum percentage decrease in the output of a thermal power unit per unit time. This represents the upward ramp rate coefficient of a thermal power unit, which is the maximum percentage increase in output of the thermal power unit per unit time. This formula represents the ramp constraint for thermal power units.

[0047] It should be noted that, in order to simplify the model complexity, the start-up and shutdown of thermal power units are not considered in the capacity planning problem. Therefore, the operating constraints of thermal power units only include the above-mentioned output range constraints and ramp-up constraints of thermal power units.

[0048] 3) Constraints on the operation of new energy sources: in, Representing a scene ,time Below, the output coefficient of the generator set, Representing a scene ,time Below, the output coefficient of the photovoltaic unit.

[0049] 4) Constraints on energy storage operation: This formula represents the power constraint for energy storage charging and discharging.

[0050] in, Representing a scene ,time Next state of charge of energy storage This represents the energy storage charging and discharging efficiency. This formula is the energy storage capacity balance equation for adjacent time periods.

[0051] in, This represents the continuous discharge duration of the energy storage device. The formula represents the energy storage capacity constraint.

[0052] in, Representing a scene Initial time The state of charge of energy storage, Representing a scene End of the cycle The state of charge of energy storage, This represents the initial state of charge (SFC) of an energy storage device, which is the proportion of the initial electrical charge stored at the beginning of a cycle to its rated energy capacity. This formula indicates that the energy storage device should maintain the same state of charge at the beginning and end of the cycle.

[0053] Furthermore, the constraints on DC transmission include DC power range constraints, DC constant operating time constraints, channel utilization hours constraints, and new energy penetration rate constraints.

[0054] The following is a detailed explanation of the constraints for DC transmission: 1) DC power range constraints: in, This indicates the rated power of the ultra-high voltage direct current (UHVDC) project.

[0055] 2) DC constant operating time constraint conditions: in, Representing a scene ,time The DC operating status indicator variable has a value of 1 indicating that the DC is in constant power operation and a value of 0 indicating that it is in power regulation operation. The time window representing the duration of constant DC operation. This represents the rate of change of DC power downwards, i.e., the maximum allowable decrease in DC power per unit time. It represents the DC upward power change rate coefficient, which is the maximum allowable increase in DC power per unit time.

[0056] 3) Channel utilization hours constraint: in, Indicates time Below, the external power transmitted by ultra-high voltage direct current (UHVDC) projects, This indicates the rated power of the ultra-high voltage direct current (UHVDC) project.

[0057] 4) Constraints on the penetration rate of new energy sources: in, Represents a set of running scenarios. Representing a scene The time scaling factor is used to expand the time dimension of typical scenarios to a full-year cycle. This refers to a collection of new energy units in a new energy base, encompassing wind power, photovoltaic, and other renewable energy units. Representing a scene ,time The active power output of the new energy units.

[0058] It should be noted that the constructed objective function for power supply planning supporting new energy bases deeply integrates the transmission characteristics of UHVDC projects, the multi-scenario impact of uncertainties in new energy output, and the power balance requirements at both the sending and receiving ends while minimizing the total cost. Specifically, the optimization of investment costs ensures a precise match between the installed capacity of wind, solar, thermal, and energy storage facilities and the transmission capacity of the DC project. The calculation of operating costs comprehensively considers the peak-shaving costs of both the sending-end supporting thermal power units and the receiving-end regulating thermal power units, ensuring that the DC transmission curve is coordinated with the trends of new energy output and receiving-end load changes, and reducing the risk of frequent DC regulation. Ultimately, within the boundaries of capacity planning constraints and DC transmission constraints, this objective function achieves synergistic optimization of power supply planning and UHVDC projects.

[0059] S4. Based on the target simulation data, solve the objective function of the power supply planning for the new energy base according to the capacity planning constraints and DC transmission constraints to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0060] Specifically, the target simulation data is substituted into the objective function of the power supply planning for the new energy base. Under the boundary constraints of capacity planning and DC transmission constraints, the solution is obtained through stochastic programming algorithm, and the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project is output.

[0061] The stochastic programming algorithm first generates multiple sets of scenario data covering both normal and extreme scenarios based on historical wind and solar power output data through generative adversarial networks, assigning a probability to each scenario. Then, it deeply integrates the scenario data, capacity planning constraints, and DC transmission constraints, iteratively solving the problem with the goal of minimizing the total cost. The final output is the planned installed capacity of wind, solar, thermal, and energy storage that meets the UHVDC transmission demand. This solution process balances computational efficiency and result reliability, significantly reducing the total cost and shortening the solution time compared to deterministic simulation.

[0062] To verify the effectiveness of the ultra-high voltage DC power supply planning method of this invention, another embodiment will be described below.

[0063] In this embodiment, a large-scale wind, solar and energy storage base supplying power to load centers in central and eastern China is selected as the research object. The base is equipped with an ultra-high voltage direct current transmission project with a rated power of 8 million kW to realize cross-regional power transmission. During the simulation, the load curve is constructed based on the actual load characteristics of the receiving end power grid. At the same time, combined with the measured wind and solar power output data of the sending end over the past two years (8760 hours), multiple sets of operation scenario data covering conventional fluctuation scenarios and extreme scenarios such as multiple consecutive days without wind and solar power are generated through generative adversarial networks. This provides comprehensive data support for verifying the effectiveness of the planning method.

[0064] The specific power supply planning scheme for the base obtained based on the optimization of this invention is shown in Table 1: Table 1. Base Supporting Power Supply Planning Scheme Optimized by the Invention Figure 3 and Figure 4 The figures show the DC power transmission curves and power balance diagrams for typical weeks in summer and winter, with the vertical axis representing power (MW) and the horizontal axis representing time (h), illustrating the coordinated output relationship between thermal power, wind power, photovoltaic power, energy storage charging, energy storage discharging, DC transmission lines, and peak shaving at the receiving end.

[0065] from Figures 3 to 4 As can be seen, the output of new energy sources such as wind power and photovoltaics is coordinated with the output of thermal power through flexible adjustment of energy storage charging and discharging, matching the DC transmission curve. Specifically, in summer... Figure 3 During peak power generation periods, energy storage discharge works in conjunction with thermal power to ensure full DC power generation; in winter... Figure 4 In this process, energy storage charging smooths out fluctuations in renewable energy output and reduces wind curtailment. Multi-scenario analysis shows that the total utilization rate of renewable energy reaches 95.67%, and the receiving end only needs to start regulating thermal power units to participate in peak shaving during a few periods. This fully demonstrates the synergistic optimization effect of the sending-end power source, energy storage, ultra-high voltage DC project, and receiving-end power grid, and achieves a balance between efficient renewable energy consumption and stable power transmission.

[0066] To further verify the effectiveness, the stochastic programming algorithm used in this invention was compared with a deterministic simulation based on 8760 hours of historical data over two years. The comparison results are shown in Table 2. Table 2 Comparison Results of Stochastic Programming and Deterministic Simulation The total cost, investment cost, and operating cost are all expressed in tens of millions of yuan, and the solution time is expressed in seconds. As shown in Table 2, the total cost under stochastic programming is reduced by more than 10% compared to historical level year 1 and historical level year 2; the solution time of stochastic programming is only 54 seconds, which is 93% reduced compared to historical level year 1 and historical level year 2, and because it covers extreme scenarios, it avoids high-risk decisions that may be caused by single historical data.

[0067] This invention provides a method for planning ultra-high voltage direct current (UHVDC) power supply. The method incorporates collaborative optimization of UHVDC projects during the objective function construction and employs multi-scenario probability weighted calculation of operating costs to address the uncertainty of renewable energy output. This avoids the mismatch between installed capacity and transmission capacity caused by the separation of power supply and DC projects in traditional planning, while accurately adapting to the transmission characteristics of DC projects to ensure stable power output from the sending-end base to match the DC transmission curve. The goal is to minimize the total cost of "investment cost + operating cost." Investment costs cover all types of supporting power sources, including wind, solar, thermal, and energy storage. Operating costs focus on the variable costs of thermal power and fuel costs. The final calculated installed capacity scheme not only controls initial investment through reasonable allocation of power source types and scales but also reduces operating energy consumption and costs through optimized dual-end thermal power regulation, while simultaneously increasing the proportion of renewable energy consumption through efficient transmission of DC projects.

[0068] like Figure 5 The diagram shown is a structural schematic of an ultra-high voltage direct current (UHVDC) power supply planning system according to an embodiment of the present invention. (Refer to...) Figure 5 An embodiment of the present invention provides an ultra-high voltage direct current (UHVDC) power supply planning system, comprising: Data processing module 01 is used to collect the original simulation data required for the planning of power supply for ultra-high voltage direct current projects, and to preprocess the original simulation data to obtain the target simulation data. Specifically, the data processing module includes: The data acquisition unit is used to acquire raw simulation data from the database related to the power planning of the UHVDC project. The raw simulation data includes power generation capacity data, grid capacity data, new energy power generation time series curves, and load time series curves. The preprocessing unit is used to preprocess the original simulation data to obtain the target simulation data. The preprocessing includes data cleaning, outlier correction, and timing alignment.

[0069] The objective construction module 02 is used to construct an objective function for planning the supporting power supply of the new energy base, taking into account the synergistic optimization of the UHVDC project, with the goal of minimizing the total cost consisting of investment cost and operating cost. The operating cost is a multi-scenario probability weighted expectation based on the uncertainty of new energy output. Specifically, the target building module includes: The first cost determination unit is used to construct the investment cost based on the sum of the annualized investment and fixed operation and maintenance costs of the unit installed capacity of various supporting power sources in the new energy base, combined with the planned installed capacity of the corresponding supporting power sources. The second cost determination unit is used to perform weighted calculations on the active power output of the supporting thermal power units of the new energy base and the active power output of the receiving-end grid-regulated thermal power units under each scenario based on several scenario probabilities, and to determine the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power in combination with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity. The objective function determination unit is used to sum up the investment cost and operating cost to obtain the total cost, and to construct the objective function for the planning of supporting power sources for the new energy base by minimizing the total cost.

[0070] The constraint setting module 03 is used to set capacity planning constraints based on the power system operation safety requirements, and to set DC transmission constraints considering the transmission operation characteristics of UHVDC projects and the power transmission needs of new energy bases. The capacity planning module 04 is used to combine the target simulation data and solve the objective function of the power supply planning for the new energy base according to the capacity planning constraints and DC transmission constraints, so as to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0071] Specifically, the capacity planning module includes: The solution unit is used to substitute the target simulation data into the objective function of the power supply planning for the new energy base. Under the boundary constraints of capacity planning and DC transmission constraints, it solves the problem through a stochastic programming algorithm and outputs the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

[0072] It should be noted that each module in the aforementioned UHVDC power supply planning system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module. For specific limitations regarding the UHVDC power supply planning system, please refer to the limitations regarding the UHVDC power supply planning method described above; both have the same function and role, and will not be repeated here.

[0073] In summary, the present invention provides a method and system for planning UHVDC supporting power sources. This method incorporates collaborative optimization of UHVDC projects during the objective function construction and employs multi-scenario probability weighted calculation of operating costs to address the uncertainty of renewable energy output. This avoids the mismatch between installed capacity and transmission capacity caused by the separation of power sources and DC projects in traditional planning, while accurately adapting to the transmission characteristics of DC projects to ensure stable power output from the sending-end base to match the DC transmission curve. With the goal of minimizing the total cost of "investment cost + operating cost," the investment cost covers all types of supporting power sources including wind, solar, thermal, and energy storage, while the operating cost focuses on the variable costs of thermal power and fuel costs. The final calculated installed capacity scheme not only controls initial investment through reasonable configuration of power source types and scale but also reduces operating energy consumption and costs through optimized dual-end thermal power regulation, while simultaneously increasing the proportion of renewable energy consumption through efficient transmission of DC projects.

[0074] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0075] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A method for planning ultra-high voltage direct current (UHVDC) power supply systems, characterized in that, include: Collect the original simulation data required for the planning of supporting power sources for ultra-high voltage direct current projects, and preprocess the original simulation data to obtain target simulation data; With the goal of minimizing the total cost consisting of investment cost and operating cost, an objective function for planning the supporting power supply of new energy bases is constructed, taking into account the collaborative optimization of UHVDC projects. The operating cost is a multi-scenario probability-weighted expected value based on the uncertainty of new energy output. Based on the requirements for power system operation safety, capacity planning constraints are set, and DC transmission constraints are set considering the transmission operation characteristics of UHVDC projects and the power transmission needs of new energy bases. Based on the target simulation data, the objective function of the power supply planning for the new energy base is solved according to the capacity planning constraints and the DC transmission constraints, so as to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

2. The ultra-high voltage direct current (UHVDC) power supply planning method according to claim 1, characterized in that, The process of collecting the original simulation data required for the planning of power sources supporting ultra-high voltage direct current (UHVDC) projects and preprocessing the original simulation data to obtain target simulation data includes: The original simulation data is obtained from the database related to the power supply planning of the UHVDC project. The original simulation data includes power supply installed capacity data, grid installed capacity data, new energy power generation time series curves, and load time series curves. The original simulation data is preprocessed to obtain the target simulation data, wherein the preprocessing includes data cleaning, outlier correction, and time series alignment.

3. The ultra-high voltage direct current (UHVDC) power supply planning method according to claim 1, characterized in that, The objective function for planning the supporting power supply for new energy bases, which aims to minimize the total cost consisting of investment and operating costs, and considers the synergistic optimization of ultra-high voltage direct current (UHVDC) projects, includes: The investment cost is constructed based on the sum of the annualized investment and fixed operation and maintenance costs per unit installed capacity of various supporting power sources in the new energy base, combined with the planned installed capacity of the corresponding supporting power sources. Based on several scenario probabilities, the active power output of the supporting thermal power units of the new energy base and the active power output of the receiving-end grid-regulated thermal power units are weighted and calculated. Combined with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity, the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power is determined. The total cost is obtained by summing the investment cost and the operating cost, and the objective function for planning the supporting power supply of the new energy base is constructed by minimizing the total cost.

4. The ultra-high voltage direct current (UHVDC) power supply planning method according to claim 1, characterized in that, The capacity planning constraints include power balance constraints, thermal power unit operation constraints, new energy operation constraints, and energy storage operation constraints.

5. The ultra-high voltage direct current (UHVDC) power supply planning method according to claim 1, characterized in that, The DC transmission constraints include DC power range constraints, DC constant operating time constraints, channel utilization hours constraints, and new energy penetration rate constraints.

6. The ultra-high voltage direct current (UHVDC) power supply planning method according to claim 1, characterized in that, The objective function for the power supply planning of the new energy base is solved by combining the target simulation data and according to the capacity planning constraints and the DC transmission constraints, to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project, including: Substituting the target simulation data into the objective function of the power supply planning for the new energy base, and under the boundary constraints of the capacity planning constraints and the DC transmission constraints, the algorithm is used to solve the problem and output the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

7. A UHVDC power supply planning system, characterized in that, include: The data processing module is used to collect the original simulation data required for the planning of power supply for ultra-high voltage direct current projects, and to preprocess the original simulation data to obtain the target simulation data. The objective construction module is used to construct an objective function for planning the supporting power supply of the new energy base, taking into account the synergistic optimization of the UHVDC project, with the objective of minimizing the total cost consisting of investment cost and operating cost. The operating cost is a multi-scenario probability weighted expectation value based on the uncertainty of new energy output. The constraint setting module is used to set capacity planning constraints based on the power system operation safety requirements, and to set DC transmission constraints taking into account the transmission operation characteristics of UHVDC projects and the power transmission needs of new energy bases. The capacity planning module is used to combine the target simulation data and solve the objective function of the power supply planning for the new energy base according to the capacity planning constraints and the DC transmission constraints, so as to obtain the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

8. The UHVDC power supply planning system according to claim 7, characterized in that, The data processing module includes: The data acquisition unit is used to acquire raw simulation data from a database related to the power supply planning of the UHVDC project. The raw simulation data includes power supply installed capacity data, grid installed capacity data, new energy power generation time series curves, and load time series curves. The preprocessing unit is used to preprocess the original simulation data to obtain the target simulation data, wherein the preprocessing includes data cleaning, outlier correction, and timing alignment.

9. The ultra-high voltage direct current power supply planning system according to claim 7, characterized in that, The target building module includes: The first cost determination unit is used to construct the investment cost based on the sum of the annualized investment and fixed operation and maintenance costs of the unit installed capacity of various supporting power sources in the new energy base, combined with the planned installed capacity of the corresponding supporting power sources. The second cost determination unit is used to perform weighted calculations on the active power output of the supporting thermal power units of the new energy base and the active power output of the receiving-end grid-regulated thermal power units under each scenario based on several scenario probabilities, and to determine the operating cost including the variable operating cost of thermal power and the fuel cost of thermal power in combination with the annual cycle ratio coefficient, the variable operating cost of thermal power per unit of electricity and the fuel cost of thermal power per unit of electricity. The objective function determination unit is used to sum the investment cost and the operating cost to obtain the total cost, and to construct the objective function for the planning of supporting power sources for the new energy base by minimizing the total cost.

10. The ultra-high voltage direct current power supply planning system according to claim 7, characterized in that, The capacity planning module includes: The solution unit is used to substitute the target simulation data into the objective function of the power supply planning for the new energy base, and solve it through a stochastic programming algorithm under the boundary constraints of the capacity planning constraints and the DC transmission constraints, and output the planned installed capacity of the power supply for the new energy base that meets the external transmission needs of the UHVDC project.

Images