A wind, solar and storage optimization configuration method and system based on new energy transmission channels

Abstract

The present invention discloses a method and system for optimizing the configuration of wind, solar, and storage based on new energy transmission channels. The system comprises: constructing a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in a large new energy base in a target area and the net load demand of the receiving power grid; constructing a wind, solar, and storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and a determined objective function with the minimum expected integrated on-grid electricity price for wind, solar, thermal, and storage as the target; solving the wind, solar, and storage optimization configuration model to obtain the installed capacity, energy storage power capacity, and energy storage capacity of the wind, solar, and thermal units when the expected integrated on-grid electricity price for wind, solar, thermal, and storage is minimized; and formulating and executing a wind, solar, and storage target configuration strategy output by the wind, solar, and storage optimization configuration model based on the installed capacity, energy storage power capacity, and energy storage capacity of the wind, solar, and thermal units. The present invention can optimize the configuration of wind, solar, and storage to meet the needs of the receiving end.

Description

Technical Field

[0001] The present invention relates to the fields of power system planning and renewable energy power generation, and in particular to a method and system for optimizing the configuration of wind, solar and energy storage based on renewable energy transmission channels. Background Art

[0002] In recent years, my country has proposed to accelerate the construction of large-scale wind and solar energy new energy bases with a focus on the "Shagohuang" area. By strengthening the construction of cross-provincial and cross-regional power transmission channels, the abundant clean energy from the "Shagohuang" area can be transported to the load center areas in the central and eastern regions, which can effectively improve my country's ability to optimize the allocation of power resources.

[0003] Based on this, the rationality and efficiency of power transmission resources from large-scale renewable energy bases have become a key factor. It is directly related to the sustainable functioning of the transmission channel, that is, whether the sending and receiving ends can reach consensus on issues such as electricity price and resource allocation. However, existing technologies fail to fully consider the impact of multiple factors such as the needs of the sending and receiving ends, channel utilization, and the costs of various power sources and energy storage generation. In particular, without considering the economic feasibility of large-scale transmission bases, there is a risk that the sending and receiving provinces will not reach an agreement on electricity price. This will lead to the risk of not being able to sign a long-term contract for the DC transmission channel, which will in turn affect the progress of the project and the resulting power configuration plan at the sending end will not meet the actual operation requirements of the channel.

[0004] It can be seen from this that how to reasonably configure the wind, solar and storage for transmission from large new energy bases and improve the rationality and effectiveness of transmission has become a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the Invention

[0005] The present invention provides a method and system for optimizing the configuration of wind, solar and storage based on a new energy transmission channel, so as to solve the problem of how to formulate a reasonable DC transmission power plan and an optimal configuration scheme of wind, solar and storage according to the output characteristics of new energy and the peak load of the receiving end, meet the needs of the receiving end, and ensure the smooth commissioning and operation of the transmission project from the perspective of transmission economy and rationality.

[0006] To solve the above technical problems, an embodiment of the present invention provides a method for optimizing wind, solar, and energy storage configuration based on a new energy transmission channel, including:

[0007] Construct a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in the target area's large new energy base and the net load demand of the receiving power grid;

[0008] Constructing a wind, solar, thermal and storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal and storage as the goal;

[0009] Solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity, and energy storage capacity of the wind-solar unit when the expected integrated on-grid electricity price of wind, solar, thermal, and energy storage is minimized;

[0010] The wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model is formulated and executed based on the installed capacity, energy storage power capacity and energy storage energy capacity of the wind-solar-storage unit.

[0011] Furthermore, the process of constructing the DC transmission power curve optimization model includes:

[0012] The DC transmission power curve optimization model is established with the number of adjustments, variation, and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints, and with the goal of meeting the net load demand of the receiving power grid;

[0013] The DC transmission power curve optimization model is expressed by the following formula:

[0014]

[0015] in, is the objective function, is the actual net load demand of the receiving power grid during period t, is the DC power in period t, For a period of one year.

[0016] Furthermore, after outputting the planned DC transmission power, the method further includes:

[0017] The adjustable multi-dimensional power resources of the receiving-end power grid are analyzed, and the acquired planned DC transmission power is leveled according to the analysis result.

[0018] Furthermore, the wind, solar, thermal and storage optimization configuration model is constructed based on the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal and storage as the goal, including:

[0019] Obtaining historical new energy output data of the large new energy base, and processing the historical new energy output data using a probabilistic scenario method;

[0020] Sampling and simplifying the processing results in sequence to generate a new energy output probability scenario set, and calculating the scenario probability corresponding to each scenario in the new energy output probability scenario set;

[0021] According to the calculated probability of each scenario and the planned DC transmission power, target constraints consisting of new energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints, and power balance constraints are established.

[0022] Furthermore, the power balance constraint is expressed by the following formula:

[0023]

[0024] in, is the power of the energy storage system in time period t under scenario s; 、 are the wind and solar power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the u-th thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

[0025] Furthermore, the process of constructing the new energy output probability scenario set further includes:

[0026] The acquired historical output data of wind and solar resources are input into the preset generative network, and a set of random output scenarios is output;

[0027] A weight is assigned to each scenario in the random output scenario set to obtain the new energy output probability scenario set.

[0028] Furthermore, the construction process of the wind-solar-storage optimization configuration model includes the following objective functions:

[0029]

[0030] in, is the objective function, is the scene probability, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in the tu year.

[0031] Furthermore, formulating and executing a target wind, solar, and energy storage configuration strategy based on the wind, solar, and energy storage optimization configuration model includes:

[0032] According to the solution results of the wind, solar and storage optimization configuration model, the balanced, resource-biased and dynamic transition wind, solar and storage ratio strategies of the new energy base in different scenarios are determined.

[0033] Furthermore, the formulating and executing of a target wind, solar, and energy storage configuration strategy based on the wind, solar, and energy storage optimization configuration model further includes:

[0034] Real-time monitoring and collection of load change data, wind and solar output change data, and grid operation fluctuation data of the receiving-end power grid and analysis;

[0035] According to the analysis results, the wind, solar and energy storage target configuration strategy is dynamically adjusted and executed.

[0036] Another embodiment of the present invention provides a wind, solar, and energy storage optimization configuration system based on a new energy transmission channel, including:

[0037] The module for constructing a DC transmission power curve optimization model is used to construct a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in the target area's large new energy base and the net load demand of the receiving power grid.

[0038] a wind-solar-storage optimization configuration model construction module, configured to construct a wind-solar-storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and a determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal and storage as the goal;

[0039] A model operation module is used to solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity and energy storage capacity of the wind-solar unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and energy storage is minimized;

[0040] A strategy formulation module is used to formulate and execute the wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model based on the installed capacity, energy storage power capacity and energy storage energy capacity of the wind-solar-storage unit.

[0041] Furthermore, the transmission power curve optimization model construction module is specifically used to:

[0042] The DC transmission power curve optimization model is established with the number of adjustments, variation, and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints, and with the goal of meeting the net load demand of the receiving power grid;

[0043] The DC transmission power curve optimization model is expressed by the following formula:

[0044]

[0045] in, is the objective function, is the actual net load demand of the receiving power grid during period t, is the DC power in period t, For a period of one year.

[0046] Furthermore, the wind, solar and energy storage optimization configuration model construction module is specifically used to:

[0047] Obtaining historical new energy output data of the large new energy base, and processing the historical new energy output data using a probabilistic scenario method;

[0048] Sampling and simplifying the processing results in sequence to generate a new energy output probability scenario set, and calculating the scenario probability corresponding to each scenario in the new energy output probability scenario set;

[0049] According to the calculated probability of each scenario and the planned DC transmission power, target constraints consisting of new energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints, and power balance constraints are established.

[0050] Furthermore, the power balance constraint is expressed by the following formula:

[0051]

[0052] in, is the power of the energy storage system in time period t under scenario s; 、 are the wind and solar power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the u-th thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

[0053] Furthermore, the process of constructing the new energy output probability scenario set further includes:

[0054] The acquired historical output data of wind and solar resources are input into the preset generative network, and a set of random output scenarios is output;

[0055] A weight is assigned to each scenario in the random output scenario set to obtain the new energy output probability scenario set.

[0056] Furthermore, the construction process of the wind-solar-storage optimization configuration model includes the following objective functions:

[0057]

[0058] in, is the objective function, is the scene probability, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in the tu year.

[0059] Furthermore, the policy formulation module is specifically used to:

[0060] According to the solution results of the wind, solar and storage optimization configuration model, the balanced, resource-biased and dynamic transition wind, solar and storage ratio strategies of the new energy base in different scenarios are determined.

[0061] Furthermore, the system also includes a policy dynamic adjustment module, specifically configured to:

[0062] Real-time monitoring and collection of load change data, wind and solar output change data, and grid operation fluctuation data of the receiving-end power grid and analysis;

[0063] According to the analysis results, the wind, solar and energy storage target configuration strategy is dynamically adjusted and executed.

[0064] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0065] The embodiment of the present invention formulates a two-stage optimization configuration strategy. Starting from the needs of the receiving power grid, taking into account factors such as channel capacity, utilization rate and DC operating characteristics, a planned DC transmission power curve is formulated, so that the planned DC transmission power can meet the net load demand of the receiving power grid as much as possible, thereby ensuring the stability and economy of the power supply; starting from the power supply configuration of the large base at the sending end, taking into account the uncertainty of wind and solar power output and the operation constraints of thermal storage, a random optimization model for the optimal configuration of wind, solar and storage is constructed, thereby formulating the optimal configuration plan of wind, solar and storage, thereby improving the utilization rate of energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 This is a flow chart of a method for optimizing wind, solar, and energy storage configuration based on a new energy transmission channel in one embodiment of the present invention;

[0067] Figure 2 This is a schematic diagram of the structure of a large-scale new energy base delivery model in one embodiment of the present invention;

[0068] Figure 3 It is a structural diagram of a wind, solar and storage optimization configuration system based on a new energy transmission channel in one embodiment of the present invention. DETAILED DESCRIPTION

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0070] In the description of this application, the terms "first," "second," "third," etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first," "second," "third," etc. may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0071] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the two components. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0072] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meanings as those commonly understood by those skilled in the art. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. Those skilled in the art will understand the specific meanings of the above terms in this application in specific circumstances.

[0073] During the construction of large-scale renewable energy bases, the capacity of thermal power plants and transmission channels is generally planned in advance. This is primarily due to the long construction cycles of thermal power plants and transmission channels, which necessitate advance construction. Furthermore, thermal power generation targets are often planned in advance to meet emission reduction targets. Furthermore, transmission channel capacity is primarily influenced by factors such as transmission distance and voltage level. Therefore, power generation planning for large-scale bases primarily focuses on determining the proportion of renewable energy and energy storage within a given scale of thermal power units and transmission channels. In the future, transmission from large-scale bases will gradually shift toward a purely renewable energy model. Despite the retirement of thermal power units, the allocation of renewable energy and energy storage will continue to be based on the known scale of thermal power plants and transmission channels, with configuration plans further developed based on the needs of both the transmitter and receiver.

[0074] Based on this, an embodiment of the present invention provides a method for optimizing the configuration of wind, solar and storage based on the new energy transmission channel. For details, please refer to Figure 1 , Figure 1 The figure shows a flow chart of a method for optimizing wind, solar and energy storage configuration based on a new energy transmission channel in one embodiment of the present invention, which includes the following steps:

[0075] S1. Construct a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in the target area's large new energy base and the net load demand of the receiving power grid.

[0076] The embodiment of the present invention formulates a two-stage planning strategy. The planning of the first stage is mainly based on the needs of the receiving-end power grid, fully considering factors such as channel capacity and utilization, DC operating characteristics, and formulating a planned DC transmission power that is as close as possible to the net load demand of the receiving-end power grid. The planning of the second stage is mainly based on the power supply configuration of the large base at the sending end, coordinating the exploitable capacity of wind and solar resources in the vicinity of the base and the uncertainty of wind and solar output, with the goal of minimizing the expected comprehensive on-grid electricity price of the large base, constructing a stochastic optimization model for the optimal configuration of wind, solar and energy storage, and rationally planning and configuring the wind and solar ratio and energy storage ratio in the vicinity of the base, so that the base's transmitted power meets the DC transmission plan formulated in the first stage.

[0077] This embodiment will provide Figure 2 The large-scale new energy base transmission model shown in the figure implements the above two-stage planning process. It can be seen that the large-scale new energy base transmission model is mainly composed of photovoltaic and wind power, thermal power units, collection stations, ultra-high voltage direct current, receiving-end power grids, and new energy storage (such as ESS) in the vicinity of the base. The collection stations collect wind and solar resources and thermal power units in the vicinity of the new energy base, and transmit them to the receiving area in a point-to-point transmission manner under the two-stage planning mode.

[0078] This step is the first stage - the process of determining the planned DC transmission power.

[0079] In some embodiments of the present invention, a DC transmission power curve optimization model is established with the number of adjustments, variation, and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints, with the goal of meeting the net load demand of the receiving power grid.

[0080] The annual DC transmission power curve generally requires a reasonable annual utilization hour, with the following constraints:

[0081]

[0082] Where, is the time interval, usually 1 hour, For a period of one year, For 1 hour, 8760 time periods; is the reasonable annual utilization hours of the DC transmission channel, which is 4500 hours in this embodiment.

[0083] It should be understood that DC transmission typically uses a multi-stage operation mode. To ensure the safe and stable operation of the DC channel, the relevant dispatching department generally requires that the DC power adjustment be no more than 6 times a day. Based on this, the constraints for the DC transmission power curve within the day are shown in the following formula:

[0084]

[0085]

[0086]

[0087]

[0088] It should be understood that , ensuring that the number of DC power adjustments per day is within 6 times; , represents the DC transmission power switching constraint, which ensures that the power change is limited to a certain range; Eq. , ensuring that the DC power is within the rated power range of the transmission channel; , indicating that the power at the end of the i-th day is consistent with the power at the beginning of the i+1-th day, making the power curve more continuous.

[0089] Where, For a day, press For 1 hour, There are 24 periods; It is a Boolean variable. When it is 0, it means that the original power transmission state is maintained. When it is 1, it means that the original power transmission state can be adjusted. is the DC power in period t, which represents the power transmitted through the DC channel in a given period; M is a sufficiently large positive number; is the rated power of the transmission channel; i is the number of days, i=1, 2,…, 365.

[0090] Furthermore, the DC transmission power curve optimization model is constructed with the following formula as the goal:

[0091]

[0092] in, is the objective function, which represents the sum of squares of the deviations between the planned DC transmission power curve and the actual net load demand of the receiving grid; is the actual net load demand of the receiving grid in period t, which represents the power required by the receiving grid in a given period.

[0093] In this embodiment, a planned DC transmission power curve is obtained by solving a DC transmission power curve optimization model using mixed integer programming to obtain the planned DC transmission power required to meet the receiving end's requirements. It should be understood that deviations may occur between the planned DC transmission power calculated using the above process and the receiving end's net load demand, which can be further balanced using the adjustable resources of the receiving end's power grid.

[0094] Specifically, the receiving grid's adjustable, multi-dimensional power resources are analyzed, including the receiving grid's conventional power generation capacity, the energy storage system's capacity and charge / discharge rate, demand-side response potential, and renewable energy generation output characteristics. Based on the analysis results, the acquired planned DC transmission power is adjusted to balance any deviations between the transmission plan and the receiving grid's demand.

[0095] This embodiment considers factors such as DC transmission operating characteristics, channel utilization requirements, and channel capacity limitations to formulate a DC transmission power curve that is close to actual demand. This can improve the reliability and accuracy of power transmission plans based on transmission channels for large-scale new energy bases.

[0096] S2. Construct a wind, solar, thermal and storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal and storage as the goal.

[0097] This step is the process of building the wind, solar and storage optimization configuration model in the second phase.

[0098] To address the uncertainty of wind and solar output, the present invention adopts a probabilistic scenario approach to model the optimal configuration of wind, solar, and energy storage for large-scale renewable energy bases. Specifically, the present invention establishes target constraints based on the planned DC transmission power, including the following steps:

[0099] 1. Obtain historical renewable energy output data from the major renewable energy base, including hourly power and meteorological data such as wind speed and irradiance. This data is preprocessed to remove outliers and then processed using a probabilistic scenario approach. During this process, the acquired historical wind and solar resource output data is fed into a pre-set generative network, which outputs a set of randomized output scenarios, including multiple output scenarios and covering extreme scenarios.

[0100] 2. Sequentially sample and reduce the set of random output scenarios. For example, Monte Carlo sampling can be used to randomly select 500 preliminary scenarios from the generated scenario set. Next, a K-means clustering reduction method is used to retain 10-20 typical scenarios (e.g., high wind and high solar power, low wind and low solar power, and severe fluctuations) to generate the desired set of renewable energy output probability scenarios. Each scenario in the random output scenario set is weighted to determine the corresponding scenario probability.

[0101] 3. Based on the calculated probability of each scenario and the planned DC transmission power, target constraints consisting of new energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints, and power balance constraints are established.

[0102] Among them, the new energy output constraint is expressed as:

[0103]

[0104]

[0105] Where, 、 are the wind and solar output values in the t period under the s scenario, and the scene probability corresponding to the s scenario is ; 、 are the power of wind and solar energy sent to the new energy storage system in the t period under scenario s, both greater than or equal to 0; 、 are the wind and solar power transmitted to the receiving grid in time period t under scenario s, both greater than or equal to 0; 、 is the solar and wind power curtailment power of the large base in the s scenario at time t, both greater than or equal to 0; 、 They are the wind and solar installed capacities under scenario s respectively.

[0106] The requirements for wind and solar power curtailment at large new energy bases are as follows:

[0107]

[0108] Where, It is the new energy curtailment coefficient, which is generally 10%.

[0109] The operating constraints of thermal power units are expressed as:

[0110]

[0111]

[0112] Where, and are the minimum and maximum output coefficients of the u-th thermal power unit respectively; is the capacity of the uth thermal power unit; is the output of the uth thermal power unit in period t under scenario s; is the ramp rate limit of the u-th thermal power unit.

[0113] Thermal power output can be further sent to the receiving end and to new energy storage according to the power flow direction, which is expressed by the following formula:

[0114]

[0115] Where, is the power delivered to the receiving area by the u-th thermal power unit in the s scenario during the t period; is the power delivered to the new energy storage unit by the uth thermal power unit in the s scenario during the t period.

[0116] This embodiment takes the electrochemical energy storage ESS as an example, and its energy storage charge and discharge constraints are expressed as:

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125] Where, 、 are the charging and discharging power of ESS in time period t under scenario s; is the ESS charging and discharging power limit in scenario s; is a Boolean variable, when 0 o'clock ,when 1 o'clock ; is the ESS energy leakage coefficient, which is generally taken as 0.001; 、 are the charging and discharging efficiencies of ESS respectively; U represents a total of U thermal power units. is the power consumption of ESS in period t under scenario s; is the ESS capacity under scenario s; 、 are the upper and lower limit coefficients of ESS power respectively.

[0126] In any period of time, the sum of the power transmitted by wind, solar, and ESS to the receiving area should be equal to the planned DC transmission power obtained in the first stage. The power balance constraint is expressed as:

[0127]

[0128] Where, The transmission power plan for period t obtained by solving the planned DC transmission power curve optimization model in the first stage is the optimized DC power in period t.

[0129] After establishing the constraints of the wind, solar, thermal, and storage optimization configuration model, in order to ensure that the power transmitted from large bases to the receiving areas is competitive in the market, the large base wind, solar, thermal, and storage configuration plan should minimize the comprehensive grid-connected electricity price of the large base as much as possible during the planning stage. Based on this, the objective function is established with the minimum expected comprehensive grid-connected electricity price of large base transmission, which is expressed as:

[0130]

[0131] in, is the corresponding objective function, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in the tu year can be obtained from the first phase Sure.

[0132] Then, the annual power transmission of large bases Expressed as: .

[0133] Expand the description of each item in the above objective function:

[0134]

[0135] Where, 、 、 、 、 They are the unit power investment of photovoltaic stations, unit power investment of wind power stations, unit power investment of ESS, unit capacity investment of ESS, and unit power cost of thermal power units.

[0136]

[0137] Where, 、 、 are the operation and maintenance costs of the photovoltaic station, wind farm station, and ESS in year tu under scenario s; The operation and maintenance expenses of the thermal power units in year tu; is the fuel cost of the thermal power unit in year tu under scenario s.

[0138] The above items are specifically expressed as follows:

[0139]

[0140]

[0141] )

[0142]

[0143]

[0144] Where, 、 、 、 is the operation and maintenance cost coefficient for year tu. Generally, wind power, solar power, and ESS are considered at 5% of the investment cost, and thermal power units are generally considered at 10%; 、 、 、 、 Both are the cost coefficients corresponding to the u-th thermal power unit.

[0145] The lifecycle of a thermal power unit is generally 15-20 years, that of a photovoltaic power station or wind farm is generally 20-25 years, and that of an ESS is generally 10-15 years. Therefore, during the calculation period for the comprehensive on-grid electricity price for wind, solar, thermal, and energy storage projects in this article, the ESS needs to be replaced once.

[0146] but,

[0147] Where Te is the full life cycle of ESS; and are the battery replacement costs per unit power and per unit capacity of ESS respectively.

[0148]

[0149] Where, is the capital cost expenditure in year t.

[0150] Finally, in the last year of the calculation period, the asset residual value recovery needs to be considered. All types of power supplies and ESS are recovered based on their operating years. Then:

[0151]

[0152] Where, 、 、 、 They are the residual value recovery rates of photovoltaic stations, wind power stations, ESS, and thermal power units respectively.

[0153] In order to further optimize the configuration scheme to take into account both the requirements of reliable power supply to the receiving area and the economic efficiency of external transmission, the technical level limit of the maximum discharge time of ESS in scenario s is also increased, which is expressed as:

[0154]

[0155]

[0156]

[0157] Where, 、 They are the open capacity of wind and solar power in the vicinity of the base; is the maximum continuous discharge time of ESS.

[0158] The embodiments of the present invention construct a typical scenario set through a generative network, integrate physical constraints and economic goals, and establish a corresponding wind, solar and storage optimization configuration model, so as to obtain the optimal wind, solar and storage configuration solution, while ensuring the reliability of external transmission and minimizing the comprehensive on-grid electricity price.

[0159] S3~S4, solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity and energy storage capacity of the wind-solar unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and storage is minimized, and formulate and implement the wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model based on the installed capacity, energy storage power capacity and energy storage capacity of the wind-solar unit.

[0160] After obtaining the wind, solar, and energy storage optimization configuration model, the model can be solved using planning software such as CPLEX or Gurobi, as an example, to obtain decision variables such as the installed capacity of the wind and solar generators, the energy storage power capacity, and the energy storage capacity when the expected combined on-grid electricity price of wind, solar, and energy storage is minimized.

[0161] By adjusting the above decision variables, the wind, solar, and storage optimization configuration model can output the optimal installed capacity and ratio of renewable energy and energy storage. This can determine the wind, solar, and storage ratio strategies for the large renewable energy base under different scenarios, including balanced, resource-biased, and dynamic transition strategies.

[0162] As an example, the wind-solar-storage ratio strategy can be formulated as follows:

[0163] 1. Wind-solar ratio

[0164] Balanced type: The wind and solar installed capacity ratio is 1:1 (such as 5GW wind power + 5GW photovoltaic power), suitable for resource-balanced areas.

[0165] Resource-biased solution: If wind resources are superior (e.g., annual utilization hours of 3,000+), 7GW of wind power + 3GW of photovoltaic power. If solar resources are superior (e.g., irradiance of 2,000 kWh / m²), 8GW of photovoltaic power + 2GW of wind power.

[0166] 2. Energy storage ratio

[0167] Basic ratio: Energy storage capacity accounts for 15% of the total installed capacity of wind and solar power (for example, 10GW of wind and solar power is matched with 1.5GWh of energy storage).

[0168] Adaptation solution for high-fluctuation scenarios: If the output fluctuates sharply, the energy storage capacity is increased to 20%-25% (e.g. 2-2.5GWh).

[0169] 3. Flexible reserve capacity of thermal power

[0170] Thermal power will be configured at 20% of the total installed capacity of wind, solar and storage (for example, 10GW of wind, solar and storage combined with 2GW of thermal power) to be used for peak regulation in extreme weather or during periods of low output.

[0171] As for the formulation of comprehensive on-grid electricity prices, it can be formulated according to the above-mentioned matching method.

[0172] It is understandable that different scenarios include extreme scenarios. As an example, the following approaches can be taken to deal with them:

[0173] In extreme low wind and low solar power scenarios, the thermal power backup units are started, the energy storage discharge time is extended to 6 hours, and cross-regional backup power supplies are called upon.

[0174] In scenarios with high risk of power abandonment, the power abandonment rate will be strictly controlled within 5%, and on-site consumption methods such as hydrogen production will be adopted.

[0175] It is worth noting that in some embodiments of the present invention, the wind-solar-storage ratio strategy can be dynamically adjusted according to the demand changes of the receiving power grid and the uncertainty of wind-solar output to make it more conducive to improving the reliability of transmission.

[0176] This embodiment of the present invention monitors and collects real-time data on load changes, wind and solar output changes, and grid operation fluctuations from the receiving grid, analyzes the data, and dynamically adjusts and optimizes the wind, solar, and storage target configuration strategy based on the analysis results. Construction and planning work is then carried out based on the optimized wind, solar, and storage configuration strategy.

[0177] In summary, the two-stage configuration strategy proposed in the embodiment of the present invention comprehensively considers factors such as the demand of the transmitting and receiving ends, channel utilization, DC operating characteristics, technical limitations of the maximum continuous discharge time of the ESS, and uncertainty in wind and solar output to optimize the configuration of wind, solar and energy storage resources. In the first stage, under the given conditions of the scale of thermal power and transmission channels, the planned DC transmission power curve is optimized. In the second stage, the uncertainty of wind and solar output is considered, and the optimization configuration is carried out with the minimum comprehensive on-grid electricity price as the goal. The proposed configuration strategy can provide theoretical support for the base wind and solar ratio and energy storage ratio schemes for power transmission from large new energy bases, ensuring the reliability of power transmission.

[0178] An embodiment of the present invention provides a wind, solar and storage optimization configuration system based on the new energy transmission channel. For details, please refer to Figure 3 , Figure 3 The figure shows a schematic diagram of the structure of a wind, solar and storage optimization configuration system based on a new energy transmission channel in one embodiment of the present invention, including:

[0179] The transmission power curve optimization model construction module M1 is used to construct a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in the large new energy base in the target area and the net load demand of the receiving power grid;

[0180] A wind-solar-storage optimization configuration model construction module M2 is used to construct a wind-solar-storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal and storage as the goal;

[0181] The model operation module M3 is used to solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity and energy storage capacity of the wind-solar unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and energy storage is minimized;

[0182] The strategy formulation module M4 is used to formulate and execute the wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model based on the installed capacity, energy storage power capacity and energy storage energy capacity of the wind-solar generator set.

[0183] Exemplarily, an embodiment of the present invention establishes a DC transmission power curve optimization model through a transmission power curve optimization model construction module, with the number of adjustments, change amount and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints, and with the goal of meeting the net load demand of the receiving power grid.

[0184] The DC transmission power curve optimization model is expressed by the following formula:

[0185]

[0186] in, is the objective function, is the actual net load demand of the receiving power grid during period t, is the DC power in period t, For a period of one year.

[0187] Exemplarily, the embodiment of the present invention constructs a wind-solar-storage optimization configuration model through a wind-solar-storage optimization configuration model construction module, specifically:

[0188] Obtaining historical new energy output data of the large new energy base, and processing the historical new energy output data using a probabilistic scenario method;

[0189] Sampling and simplifying the processing results in sequence to generate a new energy output probability scenario set, and calculating the scenario probability corresponding to each scenario in the new energy output probability scenario set;

[0190] According to the calculated probability of each scenario and the planned DC transmission power, target constraints consisting of new energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints, and power balance constraints are established.

[0191] The wind, solar and energy storage optimization configuration model includes the following objective functions:

[0192]

[0193] in, is the objective function, is the scene probability, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in the tu year.

[0194] The power balance constraint is expressed by the following formula:

[0195]

[0196] in, is the power of the energy storage system in time period t under scenario s; 、 are the wind and solar power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the u-th thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

[0197] In the embodiment of the present invention, illustratively, the process of constructing the new energy output probability scenario set is specifically as follows:

[0198] The acquired historical output data of wind and solar resources are input into the preset generative network, and a set of random output scenarios is output;

[0199] A weight is assigned to each scenario in the random output scenario set to obtain the new energy output probability scenario set.

[0200] For example, the embodiment of the present invention uses a strategy formulation module to formulate an accurate and reliable wind-solar-storage ratio strategy, specifically:

[0201] According to the solution results of the wind, solar and storage optimization configuration model, the balanced, resource-biased and dynamic transition wind, solar and storage ratio strategies of the new energy base in different scenarios are determined.

[0202] In some other embodiments of the present invention, the system further includes a policy dynamic adjustment module, specifically configured to:

[0203] Real-time monitoring and collection of load change data, wind and solar output change data, and grid operation fluctuation data of the receiving power grid and analysis are carried out. Based on the analysis results, the wind, solar, and energy storage target configuration strategy is dynamically adjusted and executed.

[0204] The technical features and technical effects of the wind, solar and storage optimization configuration system based on the new energy transmission channel proposed in the embodiment of the present invention are the same as the technical features and technical effects of the wind, solar and storage optimization configuration method based on the new energy transmission channel proposed in the embodiment of the present invention, and will not be repeated here.

[0205] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for optimizing the configuration of wind, solar and storage based on new energy transmission channels, characterized in that: include: A DC transmission power curve optimization model is constructed based on the established thermal power unit capacity and transmission channel scale of the target region's large new energy base and the net load demand of the receiving power grid. Specifically, the model is constructed using the number of DC transmission power adjustments, the amount of change, and the adjustment range, as well as the annual utilization hours of the DC transmission channel, with the goal of meeting the net load demand of the receiving power grid. The DC transmission power curve optimization model is expressed by the following formula: in, is the objective function, is the actual net load demand of the receiving power grid during period t, is the DC power in period t, For a period of one year; According to the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected wind, solar, thermal and storage integrated grid-connected electricity price as the goal, a wind, solar and storage optimization configuration model is constructed; specifically comprising: obtaining the historical new energy output data of the large new energy base, processing the historical new energy output data by a probability scenario method; sampling and simplifying the processing results in turn to generate a new energy output probability scenario set, and calculating the scenario probability corresponding to each scenario in the new energy output probability scenario set; establishing target constraint conditions consisting of new energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints and power balance constraints based on the calculated probability of each scenario and the planned DC transmission power; The construction process of the wind-solar-storage optimization configuration model includes the following objective functions: in, is the objective function, is the scene probability, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in year tu; Solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity, and energy storage capacity of the wind-solar unit when the expected integrated on-grid electricity price of wind, solar, thermal, and energy storage is minimized; The wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model is formulated and executed based on the installed capacity, energy storage power capacity and energy storage energy capacity of the wind-solar-storage unit.

2. The method for optimizing wind, solar and energy storage configuration based on the new energy transmission channel according to claim 1, characterized in that: The power balance constraint is expressed by the following formula: in, is the power of the energy storage system in time period t under scenario s; 、 are the wind and solar power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the u-th thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

3. The method for optimizing wind, solar and energy storage configuration based on new energy transmission channels according to claim 1, characterized in that: The process of constructing the new energy output probability scenario set further includes: The acquired historical output data of wind and solar resources are input into the preset generative network, and a set of random output scenarios is output; A weight is assigned to each scenario in the random output scenario set to obtain the new energy output probability scenario set.

4. The method for optimizing wind, solar and energy storage configuration based on new energy transmission channels according to claim 1, characterized in that: The process of formulating the wind, solar and energy storage target configuration strategy includes: According to the solution results of the wind, solar and storage optimization configuration model, the balanced, resource-biased and dynamic transition wind, solar and storage ratio strategies of the new energy base in different scenarios are determined.

5. The method for optimizing wind, solar and energy storage configuration based on new energy transmission channels according to claim 1, characterized in that: The method further comprises: Real-time monitoring and collection of load change data, wind and solar output change data, and grid operation fluctuation data of the receiving-end power grid and analysis; According to the analysis results, the wind, solar and energy storage target configuration strategy is dynamically adjusted and executed.

6. A wind, solar and storage optimization configuration system based on new energy transmission channels, characterized by: include: A transmission power curve optimization model construction module is used to construct a DC transmission power curve optimization model based on the established thermal power unit capacity and transmission channel scale in the target area's large new energy base and the net load demand of the receiving power grid. The DC transmission power curve optimization model is established based on the number of DC transmission power adjustments, the amount of change, and the adjustment range, as well as the annual utilization hours of the DC transmission channel, with the goal of meeting the net load demand of the receiving power grid. The DC transmission power curve optimization model is expressed by the following formula: in, is the objective function, is the actual net load demand of the receiving power grid during period t, is the DC power in period t, For a period of one year; A wind, solar, and storage optimization configuration model construction module is used to construct a wind, solar, and storage optimization configuration model based on the planned DC transmission power output by the DC transmission power curve optimization model and the determined objective function with the minimum expected integrated on-grid electricity price of wind, solar, thermal, and storage as the goal; specifically, the module includes: obtaining the historical new energy output data of the large new energy base, and processing the historical new energy output data using a probabilistic scenario method; Sampling and simplifying the processing results in sequence to generate a new energy output probability scenario set, and calculating the scenario probability corresponding to each scenario in the new energy output probability scenario set; Based on the calculated probability of each scenario and the planned DC transmission power, target constraints consisting of renewable energy output constraints, thermal power unit operation constraints, energy storage charging and discharging constraints, and power balance constraints are established. The construction process of the wind, solar, and storage optimization configuration model includes the following objective function: in, is the objective function, is the scene probability, is the construction investment cost of wind, solar, thermal and energy storage under scenario s; is the present value of the operating expenses of wind, solar, thermal and energy storage during the operation period under scenario s; is the present value of the battery replacement cost of ESS during the operation period under scenario s; is the present value of the capital cost of wind, solar, thermal and energy storage during the operation period; is the present value of the residual value of fixed assets under scenario s. In this paper, the full life cycle of thermal power units is considered as the operating period for calculating the comprehensive grid-connected electricity price of large bases; is other income during the operation period under scenario s; The annual power transmission of the large base in year tu; A model operation module is used to solve the wind-solar-storage optimization configuration model to obtain the installed capacity, energy storage power capacity and energy storage capacity of the wind-solar unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and energy storage is minimized; A strategy formulation module is used to formulate and execute the wind-solar-storage target configuration strategy output by the wind-solar-storage optimization configuration model based on the installed capacity, energy storage power capacity and energy storage energy capacity of the wind-solar-storage unit.

7. The wind, solar and storage optimization configuration system based on the new energy transmission channel according to claim 6 is characterized in that: The power balance constraint is expressed by the following formula: in, is the power of the energy storage system in time period t under scenario s; 、 are the wind and solar power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the u-th thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

8. The wind, solar and storage optimization configuration system based on the new energy transmission channel according to claim 6 is characterized in that: The process of constructing the new energy output probability scenario set further includes: The acquired historical output data of wind and solar resources are input into the preset generative network, and a set of random output scenarios is output; A weight is assigned to each scenario in the random output scenario set to obtain the new energy output probability scenario set.

9. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 6 is characterized in that: The strategy formulation module is specifically used to: According to the solution results of the wind, solar and storage optimization configuration model, the balanced, resource-biased and dynamic transition wind, solar and storage ratio strategies of the new energy base in different scenarios are determined.

10. The wind, solar and storage optimization configuration system based on the new energy transmission channel according to claim 6, characterized in that: The system also includes a policy dynamic adjustment module, specifically configured to: Real-time monitoring and collection of load change data, wind and solar output change data, and grid operation fluctuation data of the receiving-end power grid and analysis; According to the analysis results, the wind, solar and energy storage target configuration strategy is dynamically adjusted and executed.

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