Wind and light storage optimal configuration method and system based on new energy delivery channel

Abstract

The invention discloses a wind and light storage optimization configuration method and system based on a new energy delivery channel. The system comprises the following steps: constructing a direct current delivery power curve optimization model according to the established thermal power generating unit capacity and delivery channel scale in a new energy large base of a target area and the net load demand of a receiving end power grid; according to the planned direct-current delivery power output by the direct-current delivery power curve optimization model and the determined target function with the minimum wind-solar-thermal storage comprehensive on-grid electricity price expectation as the target, a wind-solar-thermal storage optimal configuration model is constructed; solving the wind-light storage optimal configuration model to obtain the installed capacity, the energy storage power capacity and the energy storage energy capacity of the wind-light unit when the wind-light-fire storage comprehensive on-grid electricity price expectation is minimum; and formulating and executing a wind and light storage target configuration strategy output by the wind and light storage optimization configuration model according to the installed capacity, the energy storage power capacity and the energy storage capacity of the wind and light unit. According to the invention, the configuration scheme of wind and light storage can be optimized to meet the requirements of the receiving end.

Description

Technical Field

[0001] The present invention relates to the field 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 inter-provincial and inter-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 the external power resources of large new energy bases have become a key factor, which is directly related to whether the transmission channel can continue to play a role, that is, whether the relevant issues such as electricity price and resource allocation between the sending and receiving ends can be agreed upon. However, the existing technology fails to fully consider the impact of multiple factors such as the demand of the sending and receiving ends, the utilization of the channel, the cost of various power sources and energy storage power generation, especially without considering the economic feasibility of large-scale base transmission, there will be a situation where the sending and receiving provinces cannot reach an agreement on the electricity price, which will lead to the risk of not being able to sign a long-term contract for the DC transmission channel, thereby affecting the progress of the project construction, and the power configuration plan obtained at the sending end cannot meet the actual operation needs of the channel.

[0004] It can be seen 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 technical personnel in this field need to solve urgently. 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 plan 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] In order to solve the above technical problems, an embodiment of the present invention provides a method for optimizing the configuration of wind, solar and energy storage based on a new energy transmission channel, including: 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; 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target, a wind, solar, thermal and storage optimization configuration model is constructed; 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-storage unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and storage is minimum; 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 of the wind-solar-storage units, the energy storage power capacity and the energy storage energy capacity.

[0007] Furthermore, the construction process of the DC transmission power curve optimization model includes: Taking the adjustment times, variation and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints and meeting the net load demand of the receiving power grid as the goal, the DC transmission power curve optimization model is established; 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 in period t, is the DC power in period t, For a period of one year.

[0008] Furthermore, after the output of the planned DC transmission power, the method further comprises: 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.

[0009] Furthermore, the wind-solar-storage optimization configuration model is constructed 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target, including: Acquire the new energy historical output data of the new energy large base, and process the new energy historical output data by using 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; 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.

[0010] Furthermore, 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 light power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the uth thermal power unit in the t period under scenario s; is the optimized DC power in period t.

[0011] Furthermore, the process of constructing the new energy output probability scenario set also includes: The 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.

[0012] Furthermore, 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.

[0013] Furthermore, the wind-solar-storage target configuration strategy is formulated and executed based on the wind-solar-storage optimization configuration model, including: According to the solution results of the wind-solar-storage optimization configuration model, the balanced, resource-biased and dynamic transitional wind-solar-storage ratio strategies of the new energy large base in different scenarios are determined.

[0014] Furthermore, the wind-solar-storage target configuration strategy is formulated and executed based on the wind-solar-storage optimization configuration model, and further includes: Real-time monitoring and collection of load change data, wind and solar power 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.

[0015] Another embodiment of the present invention provides a wind, solar and energy storage optimization configuration system based on a new energy transmission channel, including: The module for constructing the optimization model of the transmission power curve is used to construct the optimization model of the DC transmission power curve according to 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; A wind-solar-storage optimization configuration model construction module is used to construct a wind-solar-storage optimization configuration model 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-storage comprehensive grid-connected electricity price as the goal; 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 storage is minimum; 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.

[0016] Furthermore, the transmission power curve optimization model building module is specifically used for: Taking the adjustment times, variation and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints and meeting the net load demand of the receiving power grid as the goal, the DC transmission power curve optimization model is established; 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 in period t, is the DC power in period t, For a period of one year.

[0017] Furthermore, the wind-solar-storage optimization configuration model building module is specifically used to: Acquire the new energy historical output data of the new energy large base, and process the new energy historical output data by using 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; 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.

[0018] Furthermore, 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 light power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the uth thermal power unit in the t period under scenario s; is the optimized DC power in period t.

[0019] Furthermore, the process of constructing the new energy output probability scenario set also includes: The 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.

[0020] Furthermore, 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.

[0021] Furthermore, the strategy formulation module is specifically used to: According to the solution results of the wind-solar-storage optimization configuration model, the balanced, resource-biased and dynamic transitional wind-solar-storage ratio strategies of the new energy large base in different scenarios are determined.

[0022] Furthermore, the system also includes a strategy dynamic adjustment module, which is specifically used to: Real-time monitoring and collection of load change data, wind and solar power 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.

[0023] Compared with the prior art, the beneficial effects of the embodiments of the present invention are as follows: The embodiment of the present invention formulates a two-stage optimization configuration strategy. Starting from the needs of the receiving power grid, considering 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 power supply; starting from the power supply configuration of the large base at the sending end, considering 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

[0024] Figure 1 It is a flow chart of a method for optimizing the configuration of wind, solar and energy storage based on a new energy transmission channel in one embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of a large-scale new energy base transmission model in one embodiment of the present invention; Figure 3 It is a structural schematic 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

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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 creative work are within the scope of protection of the present invention.

[0026] In the description of this application, the terms "first", "second", "third", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of the feature. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0027] In the description of the present application, it should be noted that, unless otherwise clearly 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 it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. The terms "vertical", "horizontal", "left", "right", "upper", "lower" and similar expressions used herein are only for illustrative purposes, and do not indicate or imply that the device or element 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.

[0028] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0029] In the construction sequence of large-scale new energy bases, the capacity of thermal power and transmission channels is generally planned in advance. The main reason is that on the one hand, the construction period of thermal power and channels is long and they need to be built in advance, and thermal power indicators are often planned in advance under the emission reduction target; on the other hand, the channel capacity is mainly affected by factors such as transmission distance and voltage level. Therefore, the planning and configuration of power sources for large bases mainly focuses on planning the proportion of new energy and energy storage under the given conditions of the scale of thermal power units and transmission channels. In the future, the transmission of large bases will gradually shift to a pure new energy model. Although with the retirement of thermal power units, the configuration of new energy and energy storage will still be based on the known scale of thermal power and channels, and the configuration plan will be further formulated based on the overall needs of the sending and receiving ends.

[0030] Based on this, an embodiment of the present invention provides a method for optimizing the configuration of wind, solar and storage based on a new energy transmission channel. For details, please refer to Figure 1 , Figure 1 The figure shows a flow chart of a method for optimizing the configuration of wind, solar and energy storage based on a new energy transmission channel in one embodiment of the present invention, which includes the following steps: S1. 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.

[0031] 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 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 to the net load demand of the receiving power grid as possible. 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 light resources in the vicinity of the base and the uncertainty of wind and light output, and taking the minimum expected comprehensive on-grid electricity price of the large base as the goal, constructing a random optimization model for the optimal configuration of wind, light and storage, so as to reasonably plan and configure the wind and light 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.

[0032] 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, UHV DC, receiving-end power grids, and new energy storage (such as ESS) in the vicinity of the base. The collection station collects wind and solar resources and thermal power units in the vicinity, that is, the large new energy base, and will transmit them to the receiving area in a point-to-point manner under the two-stage planning mode.

[0033] This step is the first stage - the process of determining the planned DC transmission power.

[0034] 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.

[0035] The annual DC transmission power curve generally requires reasonable annual utilization hours, and the constraints are: In the formula, is the time interval, usually 1 hour, For a period of one year, For 1 hour, It is 8760 time periods; is the reasonable annual utilization hours of the DC transmission channel, which is 4500 hours in this embodiment.

[0036] It should be understood that DC transmission usually adopts a multi-stage operation mode. In order to ensure the safe and stable operation of the DC channel, the relevant dispatching department generally requires that the DC power adjustment should not exceed 6 times a day. Based on this, the constraints on the DC transmission power curve for the day are as follows: 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; Formula , to ensure 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.

[0037] In the formula, For a day, press For 1 hour, There are 24 time 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.

[0038] Then, the DC transmission power curve optimization model is constructed with the following formula as the goal: in, is the objective function, which represents the sum of squares of deviations between the planned DC transmission power curve and the actual net load demand of the receiving power grid; is the actual net load demand of the receiving grid in period t, which means the power required by the receiving grid in a given period.

[0039] In this embodiment, the planned DC transmission power curve is obtained by solving the DC transmission power curve optimization model through mixed integer programming to obtain the required planned DC transmission power that meets the needs of the receiving end. It should be understood that there will be a deviation between the planned DC transmission power calculated according to the above process and the net load demand of the receiving end, which can be further balanced by the adjustable resources of the receiving end power grid.

[0040] Specifically, the adjustable multi-dimensional power resources of the receiving power grid are analyzed, such as the power generation capacity of the conventional power sources of the receiving power grid, the capacity / charging and discharging rate of the energy storage system, the demand-side response potential, and the output characteristics of renewable energy power generation, etc. The acquired planned DC transmission power is leveled according to the analysis results to balance the various deviations between the power transmission plan and the receiving-end demand.

[0041] This embodiment takes into account factors such as DC transmission operation characteristics, channel utilization requirements, and channel capacity limitations, and formulates a DC transmission power curve close to actual demand, which can improve the reliability and accuracy of the power transmission plan based on the transmission channel of a large new energy base.

[0042] S2. 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target.

[0043] This step is the process of building the wind, solar and storage optimization configuration model in the second phase.

[0044] In order to cope with the uncertainty of wind and solar output, the embodiment of the present invention will use the probabilistic scenario method to model the optimal configuration of wind, solar and storage for large renewable energy bases. Specifically, the embodiment of the present invention will establish target constraints based on the planned DC transmission power, including the following steps: 1. Obtain the historical output data of new energy from the large new energy base, including hourly power and meteorological data such as wind speed and irradiance. After preprocessing these data to remove abnormal values, they are processed by the probabilistic scenario method. During the processing, the historical output data of wind and light resources obtained are input into the preset generative network, and the output is a random output scenario set containing multiple groups of output scenarios and covering extreme scenarios.

[0045] 2. Sample and simplify the random output scenario set in turn. As an example, Monte Carlo sampling can be used to randomly select 500 preliminary scenarios from the generated scenario set. Then, the K-means clustering simplification method is selected to retain 10-20 typical scenarios (such as high wind and high light, low wind and low light, and violent fluctuations), so as to generate the required new energy output probability scenario set, and assign weights to each scenario in the random output scenario set to obtain the scenario probability corresponding to each scenario.

[0046] 3. 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.

[0047] Among them, the new energy output constraint is expressed as: In the formula, , are the wind and solar output values ​​in the s scenario at the t period, and the scene probability corresponding to the s scenario is ; , They are the power of wind and solar energy sent to the new energy storage system in the s scenario at the t period, both of which are greater than or equal to 0; , They are the wind and solar power transmitted to the receiving grid in the s scenario at time t, both greater than or equal to 0; , is the solar and wind power abandonment power of the large base in the s scenario at the t period, both greater than or equal to 0; , They are respectively the wind and solar installed capacities in scenario s.

[0048] The requirements for wind and solar power abandonment in large new energy bases are as follows: In the formula, It is the power abandonment coefficient of new energy, which is generally 10%.

[0049] The operating constraints of thermal power units are expressed as: In the formula, and are the minimum and maximum output coefficients of the uth 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.

[0050] The thermal power output can be further sent to the receiving end and the new energy storage according to the power flow direction, which is expressed by the following formula: In the formula, is the power delivered to the receiving area by the uth thermal power unit in the s scenario during the t period; It is the power delivered to the new energy storage by the u-th thermal power unit in the s scenario during the t period.

[0051] This embodiment takes the electrochemical energy storage ESS as an example, and its energy storage charge and discharge constraints are expressed as: In the formula, , are the charging and discharging power of ESS in time period t under scenario s, respectively; is the ESS charging and discharging power limit in scenario s; is a Boolean variable. 0 hours ,when 1 hour ; is the ESS energy leakage coefficient, which is generally taken as 0.001; , are the charging and discharging efficiencies of ESS respectively; U means there are U thermal power units in total. 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.

[0052] 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: In the formula, 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.

[0053] After the constraints of the wind, solar, and thermal storage optimization configuration model are established, in order to ensure that the power transmitted by large bases to the receiving areas has market competitiveness, the large base wind, solar, and thermal storage configuration plan should minimize the comprehensive grid-connected electricity price of large bases 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 bases, which is expressed as: 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; is the annual power transmission of the large base in year tu, which can be obtained from the first stage Sure.

[0054] Then, the annual power transmission of large bases It is expressed as: .

[0055] Expand the description of each item in the above objective function: In the formula, , , , , They are the unit power investment of photovoltaic stations, the unit power investment of wind power stations, the unit power investment of ESS, the unit capacity investment of ESS, and the unit power cost of thermal power units.

[0056] In the formula, , , They 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.

[0057] The above items are specifically expressed as follows: ) In the formula, , , , is the operation and maintenance cost coefficient of the tu year. Generally, wind, solar and ESS are considered at 5% of the investment cost, and thermal power units are generally considered at 10%; , , , , are the cost coefficients corresponding to the u-th thermal power unit.

[0058] The life cycle of thermal power units is generally 15-20 years, the life cycle of photovoltaic power stations and wind farms is generally 20-25 years, and the life cycle of ESS is generally 10-15 years. Therefore, during the calculation period of the comprehensive grid-connected electricity price of wind, solar, thermal and storage projects in this article, ESS needs to consider a power replacement.

[0059] but, Where Te is the full life cycle of ESS; and They are the battery replacement cost per unit power and per unit capacity of ESS respectively.

[0060] In the formula, is the capital cost expenditure in year t.

[0061] 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 according to their operating years. Then: In the formula, , , , They are the residual value recovery rates of photovoltaic stations, wind power stations, ESS and thermal power units respectively.

[0062] In order to further optimize the configuration scheme to take into account both the 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: In the formula, , They are the available capacity of wind and solar power in the vicinity of the base; is the maximum continuous discharge time of ESS.

[0063] The embodiment of the present invention constructs a typical scenario set through a generative network, integrates physical constraints and economic goals, and establishes a corresponding wind, solar and storage optimization configuration model, so as to obtain the optimal configuration plan of wind, solar and storage, and minimize the comprehensive on-grid electricity price while ensuring the reliability of external transmission.

[0064] 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 minimum, and 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 capacity of the wind-solar unit.

[0065] After obtaining the wind, solar, and energy storage optimization configuration model, as an example, the model can be solved by planning software such as CPLEX and Gurobi to obtain decision variables such as the installed capacity of wind and solar units, energy storage power capacity, and energy storage energy capacity when the expected comprehensive on-grid electricity price of wind, solar, and energy storage is minimized.

[0066] By adjusting the above decision variables, the wind, solar and storage optimization configuration model can output the optimal installed capacity and ratio of new energy and energy storage, thereby determining the wind, solar and storage ratio strategies of the new energy base in different scenarios, including balanced, resource-biased and dynamic transition types.

[0067] As an example, the wind-solar-storage ratio strategy can be formulated as follows: 1. Wind and solar ratio Balanced type: The ratio of wind and solar installed capacity is 1:1 (such as 5GW wind power + 5GW photovoltaic power), suitable for areas with balanced resources.

[0068] Resource-biased solution: If wind resources are better (e.g. annual utilization hours 3000+): 7GW wind power + 3GW photovoltaic power. If light resources are better (e.g. irradiance 2000kWh / m²): 8GW photovoltaic power + 2GW wind power.

[0069] 2. Energy storage ratio 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).

[0070] Adaptation solution for high-fluctuation scenarios: If the output fluctuates violently, the energy storage capacity is increased to 20%-25% (e.g. 2-2.5GWh).

[0071] 3. Flexible reserve capacity of thermal power Thermal power is configured at 20% of the total installed capacity of wind, solar and storage (for example, 10GW of wind, solar and storage with 2GW of thermal power) to be used for peak regulation in extreme weather or during periods of low output.

[0072] As for the formulation of comprehensive on-grid electricity price, it can be formulated according to the above-mentioned matching method.

[0073] It is understandable that different scenarios include extreme scenarios. As an example, the following methods can be used to deal with them: In extreme low wind and low light scenarios, start the thermal power backup units, extend the energy storage discharge time to 6 hours, and call on cross-regional backup power supplies.

[0074] In scenarios with high risk of power abandonment, the power abandonment rate will be strictly controlled within 5%, and local consumption methods such as hydrogen production will be adopted.

[0075] 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-end power grid and the uncertainty of wind-solar output to make it more conducive to improving the reliability of transmission. The embodiment of the present invention monitors and collects the load change data, wind and solar output change data and grid operation fluctuation data of the receiving-end power grid in real time and analyzes them, and dynamically adjusts and optimizes the wind, solar and storage target configuration strategy according to the analysis results. The corresponding construction and planning work is performed according to the optimized wind, solar and storage configuration strategy.

[0076] In summary, the two-stage configuration strategy proposed in the embodiment of the present invention comprehensively considers the demand of the sending and receiving ends, channel utilization, DC operation characteristics, technical limitations of the maximum continuous discharge time of ESS, uncertainty of wind and solar output and other factors 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 performed with the minimum comprehensive grid-connected 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 the transmission of large new energy bases, and ensure the reliability of power transmission.

[0077] An embodiment of the present invention provides a wind, solar and storage optimization configuration system based on a new energy transmission channel. For details, see 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: The transmission power curve optimization model building module M1 is used to build a DC transmission power curve optimization model according to 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; The wind-solar-storage optimization configuration model building module M2 is used to build a wind-solar-storage optimization configuration model 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target; 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 storage is minimum; 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-storage unit.

[0078] Exemplarily, the embodiment of the present invention establishes the DC transmission power curve optimization model through a transmission power curve optimization model construction module, 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.

[0079] 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 in period t, is the DC power in period t, For a period of one year.

[0080] 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: Acquire the new energy historical output data of the new energy large base, and process the new energy historical output data by using 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; 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.

[0081] Among them, the wind, solar and energy 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.

[0082] 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 light power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the uth thermal power unit in the t period under scenario s; is the optimized DC power in period t.

[0083] In the embodiment of the present invention, illustratively, the process of constructing the new energy output probability scenario set is specifically as follows: The 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.

[0084] For example, the embodiment of the present invention provides an accurate and reliable wind-solar-storage ratio strategy through a strategy formulation module, specifically: According to the solution results of the wind-solar-storage optimization configuration model, the balanced, resource-biased and dynamic transitional wind-solar-storage ratio strategies of the new energy large base in different scenarios are determined.

[0085] In some other embodiments of the present invention, the system further includes a strategy dynamic adjustment module, which is specifically used to: The load change data, wind / solar output change data and grid operation fluctuation data of the receiving power grid are monitored and collected in real time and analyzed. According to the analysis results, the wind / solar / storage target configuration strategy is dynamically adjusted and executed.

[0086] 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.

[0087] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for optimizing the configuration of wind, solar and energy storage based on a new energy transmission channel, characterized in that: include: 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; 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target, a wind, solar, thermal and storage optimization configuration model is constructed; 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-storage unit when the expected comprehensive on-grid electricity price of wind, solar, thermal and storage is minimum; 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 of the wind-solar-storage units, the energy storage power capacity and the energy storage energy capacity.

2. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 1, characterized in that: The construction process of the DC transmission power curve optimization model includes: Taking the adjustment times, variation and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints and meeting the net load demand of the receiving power grid as the goal, the DC transmission power curve optimization model is established; 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 in period t, is the DC power in period t, For a period of one year.

3. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 1, characterized in that: The method of constructing a wind-solar-storage optimization configuration model 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target comprises: Acquire the new energy historical output data of the new energy large base, and process the new energy historical output data by using 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; 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.

4. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 3, 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 light power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the uth thermal power unit in the t period under scenario s; is the optimized DC power in period t.

5. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 3, characterized in that: The process of constructing the new energy output probability scenario set also includes: The 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.

6. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 1, characterized in that: 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.

7. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel 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-storage optimization configuration model, the balanced, resource-biased and dynamic transitional wind-solar-storage ratio strategies of the new energy large base in different scenarios are determined.

8. The method for optimizing the configuration of wind, solar and energy storage based on the new energy transmission channel according to claim 1, characterized in that: The method further comprises: Real-time monitoring and collection of load change data, wind and solar power 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.

9. A wind, solar and energy storage optimization configuration system based on the economic efficiency of new energy transmission, characterized in that: include: The module for constructing the optimization model of the transmission power curve is used to construct the optimization model of the DC transmission power curve according to 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; A wind-solar-storage optimization configuration model construction module is used to construct a wind-solar-storage optimization configuration model 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 comprehensive on-grid electricity price of wind, solar, thermal and storage as the target; 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 storage is minimum; 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.

10. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 9, characterized in that: The transmission power curve optimization model building module is specifically used for: Taking the adjustment times, variation and adjustment range of the DC transmission power and the annual utilization hours of the DC transmission channel as constraints and meeting the net load demand of the receiving power grid as the goal, the DC transmission power curve optimization model is established; 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 in period t, is the DC power in period t, For a period of one year.

11. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 9, characterized in that: The wind-solar-storage optimization configuration model building module is specifically used for: Acquire the new energy historical output data of the new energy large base, and process the new energy historical output data by using 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; 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.

12. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 11, 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 light power transmitted to the receiving end in time period t under scenario s; is the power delivered to the receiving end by the uth thermal power unit in the s scenario during the t period; is the optimized DC power in period t.

13. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 11, characterized in that: The process of constructing the new energy output probability scenario set also includes: The 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.

14. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 9, characterized in that: 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.

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

16. The wind, solar and energy storage optimization configuration system based on the new energy transmission channel according to claim 9, characterized in that: The system also includes a strategy dynamic adjustment module, which is specifically used to: Real-time monitoring and collection of load change data, wind and solar power 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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