A risk optimization-based new energy power station storage configuration method and device

Abstract

The application discloses a new energy power station storage load configuration method and device based on risk optimization, first constructs a storage load scheme library and an uncertain scene library, calculates new energy power generation income of a single scene of a given scheme, and after the calculation, through cyclic iteration, outputs new energy power generation expected income and storage load configuration cost of each scheme. The risk cost performance ratio of all schemes is comprehensively selected to select the optimal storage load configuration scheme. The new energy power station storage load configuration method and device based on risk optimization provided by the application constructs a scene library to quantize the influence of uncertain working conditions on new energy power generation, uses a risk cost performance ratio to quantize the beneficial effect of a storage load scheme on new energy power generation, and is convenient for optimizing and selecting a configuration scheme to prevent and control operation risks and improve power generation income.

Description

Technical Field

[0001] This invention relates to a risk-optimized method and apparatus for configuring storage and load in a new energy power plant, belonging to the field of power energy technology. Background Technology

[0002] As the penetration rate of new energy sources such as wind and solar power increases year by year, the uncertainty and volatility of their power generation are becoming increasingly unavoidable. In June 2021, Jiangsu Province proposed an assessment mechanism for the deviation of wind / solar power generation; in September of the same year, Jiangsu Province required that new projects must be equipped with a certain proportion of energy storage.

[0003] In the past, dispatching departments have used high-quality peak-shaving resources (such as thermal power and hydropower) in conjunction with wind / solar power generation. However, the traditional source-side resource peak-shaving model is becoming increasingly difficult to maintain and is not conducive to implementing the dual-carbon path. Therefore, how to improve the power generation revenue of new energy power plants by rationally and effectively allocating storage and load resources is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] Objective: To overcome the shortcomings of existing technologies, this invention provides a risk-optimized method and device for configuring energy storage and load in new energy power plants. By configuring energy storage and controllable load regulation means near new energy power plants, the volatility of new energy power generation can be effectively reduced through source-storage-load interaction.

[0005] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0006] Firstly, a risk-optimized method for configuring storage and load in new energy power plants includes the following steps:

[0007] The uncertainties in the grid-connected operation of new energy power plants are identified, the characteristic values ​​of these uncertainties are extracted in a certain way, scenarios are constructed, and all scenarios are collected to form a scenario library.

[0008] The baseline operating conditions of the power grid in the area where the new energy power plant is located are set. All scenarios in the scenario library are traversed, and the power grid operation conditions of the power grid in the area where the new energy power plant is located are analyzed for all scenarios. Based on the risk optimization objective function of the no-storage scheme, the expected net income of new energy power generation without considering storage is obtained based on the scenario library.

[0009] Configure typical parameters for energy storage and controllable loads to develop storage and load schemes with different regulation performance, and obtain all storage and load schemes to form a scheme library.

[0010] The baseline operating conditions of the power grid in the area where the new energy power plant is located are set. The storage and load schemes in the scheme library are traversed sequentially. Under a storage and load scheme, all scenarios in the scenario library are traversed to complete the power grid operation condition analysis of the power grid in the area where the new energy power plant is located for all scenarios under a storage and load scheme. Based on the risk optimization objective function that takes storage and load into account, the expected net income of new energy power generation taking storage and load into account under a storage and load scheme based on the scenario library is obtained.

[0011] The risk-cost-performance ratio of a storage scheme is calculated based on the expected net income of renewable energy generation without considering storage capacity, using a scenario library, and the expected net income of renewable energy generation without considering storage capacity under a given storage scheme. The risk-cost-performance ratio of all storage schemes is calculated, and the storage scheme with the lowest risk-cost-performance ratio is selected.

[0012] Secondly, a risk-optimized new energy power plant storage and load configuration device includes the following modules: a scenario library acquisition module, used to acquire uncertain factors in the grid-connected operation of new energy power plants, extract feature values ​​of uncertain factors in a certain way, construct scenarios, and acquire all scenarios to form a scenario library.

[0013] The module for calculating revenue without considering storage capacity is used to set the baseline operating conditions of the power grid in the area where the new energy power plant is located, traverse all scenarios in the scenario library, complete the power grid operation condition analysis of the power grid in the area where the new energy power plant is located for all scenarios, and obtain the expected net revenue of new energy power generation without considering storage capacity based on the risk optimization objective function of the no-storage-capacity scheme.

[0014] The scheme library acquisition module is used to set typical parameters for energy storage and controllable loads to configure storage and load schemes with different regulation performance, and to acquire all storage and load schemes to form a scheme library.

[0015] The module for calculating the revenue from energy storage is used to set the baseline operating conditions of the power grid in the area where the new energy power plant is located. It iterates through the energy storage schemes in the scheme library, and under a single energy storage scheme, it iterates through all scenarios in the scenario library to complete the power grid operation condition analysis of the area where the new energy power plant is located for all scenarios under a single energy storage scheme. Based on the risk optimization objective function that takes energy storage into account, it obtains the expected net revenue of new energy power generation taking energy storage into account under a single energy storage scheme based on the scenario library.

[0016] The risk-cost-performance ratio calculation module is used to calculate the risk-cost-performance ratio of a storage scheme based on the expected net income of new energy power generation without considering storage capacity, which is based on a scenario library, and the expected net income of new energy power generation without considering storage capacity under a storage scheme.

[0017] The storage and load scheme optimization module is used to calculate the risk-cost-performance ratio of all storage and load schemes and select the storage and load scheme with the lowest risk-cost-performance ratio.

[0018] As a preferred approach, the uncertainties in the grid-connected operation of new energy power plants are identified, their characteristic values ​​are extracted in a specific manner, and scenarios are constructed. All scenarios are then compiled into a scenario library, including:

[0019] The grid connection limit of new energy power plants, wind / photovoltaic power generation and power load are quantified respectively, and the quantified characteristic values ​​are obtained.

[0020] The characteristic values ​​of any combination of grid connection limit of new energy power station, wind / photovoltaic power generation and power load are extracted to form a scenario, and the occurrence probability of each scenario is set to build a scenario library.

[0021] As a preferred option, a baseline operating condition for the power grid in the region where the new energy power station is located is established. All scenarios in the scenario library are traversed, and a power grid operation condition analysis of the region where the new energy power station is located is completed for all scenarios. Based on the risk optimization objective function of the no-storage-load scheme, the expected net revenue of new energy power generation without considering storage is obtained based on the scenario library, including:

[0022] The baseline operating conditions of the power grid in the area where the new energy power station is located are set. All scenarios in the scenario library are traversed. Under the power grid constraints without considering the storage load, the power grid operation conditions of the power grid in the area where the new energy power station is located in all scenarios are simulated and analyzed to obtain the new energy grid-connected power and the assessment power. Based on the new energy grid-connected power and the assessment power, the new energy power generation revenue and the power generation deviation assessment cost are obtained.

[0023] By substituting the revenue from new energy power generation and the cost of power generation deviation assessment into the risk optimization objective function of the no-storage scheme, the expected net revenue of new energy power generation without considering storage capacity is obtained based on the scenario library.

[0024] As a preferred option, the objective function for risk optimization of the no-storage scheme is calculated using the following formula:

[0025]

[0026] In the formula, S represents the total number of scenes, and γ s Let I represent the probability of scenario s occurring, and let I be the expected net revenue from renewable energy generation without considering storage capacity. s.r I s.c These represent the revenue from new energy power generation and the cost of new energy power generation deviation assessment in scenario s, respectively.

[0027] As a preferred option, the benchmark operating conditions include, but are not limited to, the installed capacity of fossil and non-fossil power sources under the regional power grid, the start-up scheme of coal-fired and gas-fired power units and the minimum output coefficient of the units, the grid connection limit of new energy sources, the power generation coefficient of typical wind power / photovoltaic units, the annual maximum load and the power load coefficient of typical days.

[0028] As a preferred embodiment, the grid constraints that do not take into account load storage include:

[0029] Power balance constraints of regional power grids:

[0030]

[0031] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i (t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0032] Power generation constraints of coal-fired power units:

[0033] P tp.i.min ≤P tp.i (t)≤P tp.i.max

[0034] In the formula, P tp.i.min P tp.i.max Let be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0035] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u In the formula, R tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power unit during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints:

[0036] (U i (t-1)-U i (t))·(T on.i (t-1)-M on.i )≥0

[0037] (U i (t)-U i (t-1))·(T off.i (t-1)-M off.i )≥0

[0038] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; T off.i (t-1), M off.i Let be the minimum continuous operating time and minimum continuous downtime of unit i.

[0039] Gas turbine generator power generation constraints:

[0040] P gs.i.min ≤P gs.i (t)≤P gs.i.max

[0041] In the formula, P gs.i.min P gs.i.max These represent the minimum and maximum power generation of the i-th gas turbine unit, respectively; power generation constraints for wind turbine units:

[0042] 0≤P w.i (t)≤P w.i.max

[0043] In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0044] Photovoltaic power generation constraints:

[0045] 0≤P s.i (t)≤P s.i.max

[0046] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0047] New energy grid connection capacity constraints:

[0048]

[0049] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0050] As a preferred option, typical parameters for energy storage include, but are not limited to, energy storage battery type, charge and discharge efficiency, installed capacity, and energy storage capacity. Typical parameters for controllable loads include, but are not limited to, response time, load capacity, and load capacity.

[0051] As a preferred approach, a baseline operating condition for the power grid in the region where the new energy power plant is located is established. The storage and load management schemes in the scheme library are then sequentially traversed. Under a single storage and load management scheme, all scenarios in the scenario library are traversed to complete the power grid operation condition analysis for all scenarios under a given storage and load management scheme. Based on the risk optimization objective function considering storage and load management, the expected net revenue of new energy power generation considering storage and load management under a given storage and load management scheme, based on the scenario library, is obtained, including:

[0052] The baseline operating conditions of the power grid in the area where the new energy power plant is located are set. The storage and load schemes in the scheme library are traversed sequentially. Under a storage and load scheme, all scenarios in the scenario library are traversed. Under the power grid constraints that take storage and load into account, the power grid operation conditions of the power grid in the area where the new energy power plant is located are simulated and analyzed for all scenarios under a storage and load scheme. The grid-connected new energy power, the regulated power, and the assessment power are obtained. Then, based on the grid-connected new energy power, the regulated power, and the assessment power, the new energy power generation revenue, storage and load regulation costs, and power generation deviation assessment costs under all scenarios under a storage and load scheme are obtained.

[0053] By substituting the revenue from new energy power generation, the cost of storage and load regulation, and the cost of power generation deviation assessment into the risk optimization objective function that includes storage and load, we obtain the expected net revenue of new energy power generation that includes storage and load under a storage and load scheme based on a scenario library.

[0054] As a preferred embodiment, the grid constraints taking into account load storage include:

[0055] Power balance constraints of regional power grids:

[0056]

[0057] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i (t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0058] Power generation constraints of coal-fired power units:

[0059] P tp.i.min ≤P tp.i (t)≤P tp.i.max

[0060] In the formula, P tp.i.min P tp.i.maxLet be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0061] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u

[0062] In the formula, R tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power unit during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints:

[0063] (U i (t-1)-U i (t))·(T on.i (t-1)-M on.i )≥0

[0064] (U i (t)-U i (t-1))·(T off.i (t-1)-M off.i )≥0

[0065] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; M on.i M off.i Let be the minimum continuous operating time and minimum continuous downtime of unit i.

[0066] Gas turbine generator power generation constraints:

[0067] P gs.i.min ≤P gs.i (t)≤P gs.i.max

[0068] In the formula, P gs.i.min P gs.i..ax These represent the minimum and maximum power generation of the i-th gas turbine unit, respectively; power generation constraints for wind turbine units:

[0069] 0≤P w.i (t)≤P w.i.max

[0070] In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0071] Photovoltaic power generation constraints:

[0072] 0≤P s.i (t)≤P s.i.max

[0073] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0074] New energy grid connection capacity constraints:

[0075]

[0076] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0077] Energy storage power balance constraints:

[0078]

[0079] In the formula, t i t j For the start and end times of energy storage; E B (t i E B (t j P represents the energy level at the start and end of the energy storage process; B.c (t), P B.d (t) represents the charging and discharging power during time period t; U B (t) represents the energy storage charging / discharging state variable, where 1 indicates charging and 0 indicates discharging; η c η d For charging and discharging efficiency.

[0080] Energy storage power constraints:

[0081] -P B.max ≤P B.c (t)≤0

[0082] 0≤P B.d (t)≤P B.max

[0083] In the formula, P B.max This represents the maximum energy storage capacity.

[0084] Energy storage capacity constraints:

[0085] 0≤E B (t)≤E B.max

[0086] In the formula, EB.max This is the maximum energy storage capacity.

[0087] Controllable load power balance constraints:

[0088]

[0089] In the formula, t i t j E represents the start and end times of the controllable load response. D (t i E D (t j ) represents the controllable load t i Electricity already responded to during the period, t j The amount of electricity that has been responded to during the time period, P D (t) represents the controllable load power of the response during time period t; controllable load power constraints:

[0090] 0≤P D (t)≤P D.max

[0091] In the formula, P D.max This represents the maximum response power of a controllable load.

[0092] Controllable load power constraints:

[0093] 0≤E D (t)≤E D.max

[0094] In the formula, E D.max The maximum response power for a controllable load;

[0095] The power generation assessment constraints for new energy power plants that take into account storage resources are shown in the following formula.

[0096] P P (t)-P M (t)·ρ(t)≤P M (t)+P B (t)+P D (t)≤P P (t)+P M (t)·ρ(t)

[0097] In the formula, P B (t), P D (t) represents the energy storage and controllable load regulation power during time period t, respectively.

[0098] As a preferred embodiment, the risk optimization objective function taking into account storage load is calculated using the following formula:

[0099]

[0100] In the formula, S represents the total number of scenes, and γ s I represents the probability of scenario s occurring. x For the expected net revenue of renewable energy power generation considering storage capacity under the scenario library under storage capacity scheme x, I x.s.r I x.s.sl I x.s.c These represent the revenue from renewable energy generation, the cost of energy storage regulation, and the cost of renewable energy generation deviation assessment in scenario s of energy storage scheme x, respectively.

[0101] As a preferred option, the risk-cost-performance ratio calculation formula for the storage and load scheme is as follows:

[0102]

[0103] In the formula, C s C l The configuration costs for energy storage and controllable loads are respectively, I x I and I represent the expected net income of new energy power generation without considering storage capacity based on the scenario library and the expected net income of new energy power generation without considering storage capacity based on the scenario library, respectively.

[0104] Beneficial effects: The present invention provides a method and device for configuring storage and load in new energy power plants based on risk optimization. It constructs a scenario library to quantify the impact of uncertain factors on new energy power generation, and uses the risk-cost-performance ratio to quantify the beneficial effects of storage and load schemes on new energy power generation. This facilitates the selection of optimal storage and load schemes to control operational risks and improve power generation revenue. Attached Figure Description

[0105] Figure 1 This is a schematic diagram of the process of the present invention.

[0106] Figure 2 This is a schematic diagram of the device structure of the present invention. Detailed Implementation

[0107] The present invention will be further described below with reference to specific embodiments.

[0108] The first embodiment discloses a risk-optimized method for configuring storage and load in new energy power plants, used to rationally allocate storage and load resources to improve the economic efficiency of new energy power generation. Its main steps are as follows: Figure 1 As shown:

[0109] Step 1: Configure multiple load storage schemes and build a scheme library.

[0110] By setting typical parameters for energy storage and controllable loads, different load storage schemes with varying regulation performance can be configured, and a scheme library can be built from these schemes. Typical parameters for energy storage include, but are not limited to, energy storage battery type, charge / discharge efficiency, installed capacity, and energy storage capacity. Typical parameters for controllable loads include, but are not limited to, response time, load capacity, and load capacity.

[0111] Step 2: Design uncertain operating conditions related to the grid connection and operation of new energy power plants, build a scenario library, and establish a risk optimization objective function based on the scenario library.

[0112] Uncertain factors affecting the grid connection and operation of new energy power plants include, but are not limited to, the grid connection limit of new energy power plants, wind / photovoltaic power generation capacity, and power load.

[0113] Uncertain factors are quantified, and characteristic values ​​of the quantified uncertain factors are extracted.

[0114] For the grid connection limit of new energy power plants, considering the grid topology of the area where the new energy power plants are located, three grid structures are set: strong support, medium support, and weak support. Under the typical operation mode of the power system, electromechanical transient simulation software is used to calculate the characteristic value of the grid connection safety limit of new energy in the area. Electromechanical transient simulation software includes, but is not limited to, BPA and PSASP.

[0115] For wind / solar power generation, referring to historical data, the historical output coefficient of wind / solar power between "0-1" is obtained by using "historical power generation / installed capacity". The probability distribution of new energy power plants in the intervals of "0-0.2", "0.2-0.4", "0.4-0.6", "0.6-0.8", and "0.8-1" is statistically analyzed according to typical days of spring, summer, autumn and winter. One or more wind / solar power output curves that conform to the probability distribution of each season are generated as characteristic values ​​of wind / solar power generation.

[0116] For the power load, referring to historical power load data, the historical load coefficient between "0-1" is obtained by using "historical power load / annual maximum load". The probability distribution of power load in the intervals of "0-0.2", "0.2-0.4", "0.4-0.6", "0.6-0.8" and "0.8-1" is statistically analyzed according to four typical load conditions: "spring and autumn daily load conditions", "summer extreme load conditions", "winter extreme load conditions" and "holiday load conditions". One or more load curves that conform to the probability distribution of each typical condition are generated as characteristic values ​​of power load.

[0117] A risk factor scenario library is generated by extracting feature values ​​of uncertain factors in a specific manner and constructing scenarios. Extraction methods include, but are not limited to: extracting feature values ​​of one type of uncertain factor, simultaneously extracting feature values ​​of two types of uncertain factors, or simultaneously extracting feature values ​​of all uncertain factors. Based on the results of multiple extractions, a scenario library representing various risk factors for one calculation year is constructed, and the probability of occurrence for each scenario is set.

[0118] Risk optimization objective function based on scenario library and considering storage load.

[0119] By quantifying the uncertainties across multiple scenarios using risk quantification, the economic benefits of new energy power plants in each scenario are first quantified. These benefits are then multiplied by the corresponding scenario probability to obtain the risk value for each scenario. The expected return of the proposed solution is then calculated, as shown in the following formula.

[0120]

[0121] In the formula, S represents the total number of scenes, and γ s I represents the probability of scenario s occurring. x For the expected net revenue from renewable energy generation of storage and load storage scheme x, I x.s.r I x.s.sl I x.s.c These represent the revenue from renewable energy generation, the cost of energy storage regulation, and the cost of renewable energy generation deviation assessment in scenario s of energy storage scheme x, respectively.

[0122] Step 3: Set the baseline operating conditions of the power grid in the area where the new energy power station is located. Without configuring storage resources, complete the power grid operation analysis for all scenarios and output the expected net revenue of new energy power generation without considering storage, based on the scenario library. The baseline operating conditions include, but are not limited to, the installed capacity of fossil fuels and non-fossil fuels in the regional power grid, the start-up schemes and minimum output coefficients of coal-fired and gas-fired power units, the grid connection limit of new energy, the power generation coefficient of typical wind / photovoltaic units, the annual maximum load, and the power load coefficient of typical days.

[0123] The objective function for risk optimization of the no-storage-load scheme is shown in the following equation.

[0124]

[0125] In the formula, S represents the total number of scenes, and γ s Let I represent the probability of scenario s occurring, and let I be the expected net revenue from renewable energy generation without considering storage capacity. s.r I s.c These represent the revenue from new energy power generation and the cost of new energy power generation deviation assessment in scenario s, respectively.

[0126] For a single scenario, scenario data is read, and the power grid operation conditions are simulated and analyzed to evaluate the expected net income of new energy power generation;

[0127] Based on the categories of uncertainties included in the scenario, the grid connection limit of the new energy power station, wind / photovoltaic power generation, and power load under the baseline operating conditions are updated to scenario data;

[0128] The process of power grid operation condition analysis is to complete a sequential simulation of the whole day on an hourly time scale, considering the following equality constraints and inequality constraints.

[0129] Power balance constraints of regional power grids:

[0130]

[0131] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i (t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0132] Power generation constraints of coal-fired power units:

[0133] P tp.i.min ≤P tp.i (t)≤P tp.i.max

[0134] In the formula, P tp.i.min P tp.i.max Let be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0135] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u

[0136] In the formula, R tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power unit during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints:

[0137] (U i (t-1)-U i (t))·(T on.i(t-1)-M on.i )≥0

[0138] (U i (t)-U i (t-1))·(T off.i (t-1)-M off.i )≥0

[0139] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; M on.i M off.i Let be the minimum continuous operating time and minimum continuous downtime of unit i.

[0140] Gas turbine generator power generation constraints:

[0141] P gs.i.min ≤P g.i (t)≤P g.i.max

[0142] In the formula, P gs.i.min P gs.i.max These represent the minimum and maximum power generation of the i-th gas turbine unit, respectively; power generation constraints for wind turbine units:

[0143] 0≤P w.i (t)≤P w.i.max In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0144] Photovoltaic power generation constraints:

[0145] 0≤P s.i (t)≤P s.i.max

[0146] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0147] New energy grid connection capacity constraints:

[0148]

[0149] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0150] Based on the principle of "prioritizing the consumption of new energy sources and avoiding power outages", we conduct power grid operation condition analysis and generate source / grid / load output results for 24 hours a day.

[0151] By statistically analyzing the grid-connected electricity and assessed electricity of new energy sources, and multiplying them by the unit economic parameters, we can obtain the revenue from new energy power generation and the assessment cost of power generation deviation under this scenario, and then obtain the net revenue from new energy power generation under this scenario.

[0152] The assessment of new energy power generation refers to the power generation counted during the assessment period when the deviation rate of new energy power generation exceeds the assessment target.

[0153] The deviation rate of new energy power generation is calculated as shown in the following formula.

[0154]

[0155] In the formula, ρ(t) represents the deviation rate for time period t; P M (t), P P (t) represents the actual power and short-term predicted power of new energy generation in time period t, respectively.

[0156] The actual power output of new energy power generation exhibits a fluctuation range as shown in the following formula.

[0157] P P (t)-P M (t)·ρ(t)≤P M (t)≤P P (t)+P M (t)·ρ(t)

[0158] After iterating through other scenarios, the objective function can be optimized based on the risk of no storage load to output the expected net income of the new energy power plant without considering storage load.

[0159] Step 4: Take one storage and load scheme from the scheme library, optimize the objective function that takes storage and load into account and follow the power grid operation condition analysis process in Step 3, traverse all scenarios, and output the expected net revenue of new energy power generation for storage and load scheme x based on the scenario library.

[0160] Among these, the power grid operation condition analysis needs to take into account the equality and inequality constraints related to load storage, as well as the power balance constraints of the regional power grid:

[0161]

[0162] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i(t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0163] Power generation constraints of coal-fired power units:

[0164] P tp.i.min ≤P tp.i (t)≤P tp.i.max

[0165] In the formula, P tp.i.min P tp.i.max Let be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0166] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u

[0167] In the formula, P tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power unit during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints:

[0168] (U i (t-1)-U i (t))·(T on.i (t-1)-M on.i )≥0

[0169] (U i (t)-U i (t-1))·(T off.i (t-1)-M off.i )≥0

[0170] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; M on.i M off.iThese represent the minimum continuous operating time and minimum continuous downtime of unit i. Gas turbine power generation constraints:

[0171] P gs.i.min ≤P gs.i (t)≤P gs.imax

[0172] In the formula, P gs.i.min P gs.i.max These are the minimum and maximum power generation of the i-th gas turbine unit, respectively;

[0173] Wind turbine power generation constraints:

[0174] 0≤P w.i (t)≤P w.i.max

[0175] In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0176] Photovoltaic power generation constraints:

[0177] 0≤P s.i (t)≤P s.i.max

[0178] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0179] New energy grid connection capacity constraints:

[0180]

[0181] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0182] Energy storage power balance constraints:

[0183]

[0184] In the formula, t i t j For the start and end times of energy storage; E B (t i E B (t j P represents the energy level at the start and end of the energy storage process; B.c (t), P B.d (t) represents the charging and discharging power during time period t; U B (t) represents the energy storage charging / discharging state variable, where 1 indicates charging and 0 indicates discharging; η c η d For charging and discharging efficiency.

[0185] Energy storage power constraints:

[0186] -P B.max ≤P B.c (t)≤0

[0187] 0≤P B.d (t)≤P B.max

[0188] In the formula, P B.max This represents the maximum energy storage capacity.

[0189] Energy storage capacity constraints:

[0190] 0≤E B (t)≤E B.max

[0191] In the formula, E B.max This is the maximum energy storage capacity.

[0192] Controllable load power balance constraints:

[0193]

[0194] In the formula, t i t j E represents the start and end times of the controllable load response. D (t i E D (t j ) represents the controllable load t i Electricity already responded to during the period, t j The amount of electricity that has been responded to during the time period, P D (t) represents the controllable load power of the response during time period t; controllable load power constraints:

[0195] 0≤P D (t)≤P D.max

[0196] In the formula, P D.max This represents the maximum response power of a controllable load.

[0197] Controllable load power constraints:

[0198] 0≤E D (t)≤E D.max

[0199] In the formula, E D.max The maximum response power for a controllable load;

[0200] The power generation assessment constraints for new energy power plants that take into account storage resources are shown in the following formula.

[0201] P P (t)-PM (t)·ρ(t)≤P M (t)+P B (t)+P D (t)≤P P (t)+P M (t)·ρ(t)

[0202] In the formula, P B (t), P D (t) represents the energy storage and controllable load regulation power during time period t, respectively.

[0203] Based on the simulation output of source / grid / storage / load power output, the grid-connected renewable energy power, regulated power, and assessed power are statistically analyzed. These are then multiplied by unit economic parameters to obtain the renewable energy generation revenue, storage and load regulation costs, and power generation deviation assessment costs for this scenario. This leads to the net renewable energy generation revenue of storage and load scheme x in this scenario. After analyzing this scenario, the remaining scenarios are iterated. Based on the risk optimization objective function considering storage and load in step 2, the expected net renewable energy generation revenue of storage and load scheme x in this scenario is calculated. Step 5: Evaluate the configuration cost of the storage and load scheme. The energy storage configuration cost includes two investment models: construction or leasing by the power generation company.

[0204] If a company builds energy storage, the construction cost is the product of the amount of energy storage capacity built and the construction cost per unit of energy capacity;

[0205] If a company leases energy storage, the leasing cost is the product of the leased energy storage capacity and the leasing cost per unit of energy.

[0206] The configuration cost of controllable load is divided into capacity compensation cost and scheduling response cost. The capacity compensation cost is the product of the controllable load capacity to be responded to and the unit capacity compensation cost. The scheduling response cost is shown in the following formula.

[0207]

[0208] In the formula, S represents the total number of scenes, p s C represents the probability of scenario s occurring. l.d For the scheduling response cost of controllable load, E s.e.load P represents the controllable load power that has been responded to in scenario s. l.d The unit power dispatch cost for controllable load;

[0209] The configuration cost of the energy storage solution should include the construction cost of energy storage or the cost of leasing energy storage, the capacity compensation cost of controllable load, and the dispatch response cost.

[0210] The risk-cost-performance ratio of this storage and load scheme is calculated as shown in the following formula.

[0211]

[0212] In the formula, C s C l The configuration costs for energy storage and controllable loads are respectively, I x I and I represent the expected net revenue from renewable energy generation, taking into account the energy storage scheme and the expected net revenue from renewable energy generation, respectively.

[0213] Step 7: If there are other load storage solutions, return to the solution library to get the next load storage solution, until all load storage solutions have been traversed, and select the solution with the lowest risk-cost-performance ratio as the best solution.

[0214] like Figure 2 As shown in the second embodiment, a risk-optimized new energy power plant storage and load configuration device includes the following modules:

[0215] The scenario library acquisition module is used to acquire uncertainties in the grid-connected operation of new energy power plants, extract the feature values ​​of uncertainties in a certain way, construct scenarios, and acquire all scenarios to form a scenario library.

[0216] The module for calculating revenue without considering storage capacity is used to set the baseline operating conditions of the power grid in the area where the new energy power plant is located, traverse all scenarios in the scenario library, complete the power grid operation condition analysis of the power grid in the area where the new energy power plant is located for all scenarios, and obtain the expected net revenue of new energy power generation without considering storage capacity based on the risk optimization objective function of the no-storage-capacity scheme.

[0217] The scheme library acquisition module is used to set typical parameters for energy storage and controllable loads to configure storage and load schemes with different regulation performance, and to acquire all storage and load schemes to form a scheme library.

[0218] The module for calculating the revenue from energy storage is used to set the baseline operating conditions of the power grid in the area where the new energy power plant is located. It iterates through the energy storage schemes in the scheme library, and under a single energy storage scheme, it iterates through all scenarios in the scenario library to complete the power grid operation condition analysis of the area where the new energy power plant is located for all scenarios under a single energy storage scheme. Based on the risk optimization objective function that takes energy storage into account, it obtains the expected net revenue of new energy power generation taking energy storage into account under a single energy storage scheme based on the scenario library.

[0219] The risk-cost-performance ratio calculation module is used to calculate the risk-cost-performance ratio of a storage scheme based on the expected net income of new energy power generation without considering storage capacity, which is based on a scenario library, and the expected net income of new energy power generation without considering storage capacity under a storage scheme.

[0220] The storage and load scheme optimization module is used to calculate the risk-cost-performance ratio of all storage and load schemes and select the storage and load scheme with the lowest risk-cost-performance ratio.

[0221] As a preferred approach, the uncertainties in the grid-connected operation of new energy power plants are identified, their characteristic values ​​are extracted in a specific manner, and scenarios are constructed. All scenarios are then compiled into a scenario library, including:

[0222] The grid connection limit of new energy power plants, wind / photovoltaic power generation and power load are quantified respectively, and the quantified characteristic values ​​are obtained.

[0223] The characteristic values ​​of any combination of grid connection limit of new energy power station, wind / photovoltaic power generation and power load are extracted to form a scenario, and the occurrence probability of each scenario is set to build a scenario library.

[0224] As a preferred option, a baseline operating condition for the power grid in the region where the new energy power station is located is established. All scenarios in the scenario library are traversed, and a power grid operation condition analysis of the region where the new energy power station is located is completed for all scenarios. Based on the risk optimization objective function of the no-storage-load scheme, the expected net revenue of new energy power generation without considering storage is obtained based on the scenario library, including:

[0225] The baseline operating conditions of the power grid in the area where the new energy power station is located are set. All scenarios in the scenario library are traversed. Under the power grid constraints without considering the storage load, the power grid operation conditions of the power grid in the area where the new energy power station is located in all scenarios are simulated and analyzed to obtain the new energy grid-connected power and the assessment power. Based on the new energy grid-connected power and the assessment power, the new energy power generation revenue and the power generation deviation assessment cost are obtained.

[0226] By substituting the revenue from new energy power generation and the cost of power generation deviation assessment into the risk optimization objective function of the no-storage scheme, the expected net revenue of new energy power generation without considering storage capacity is obtained based on the scenario library.

[0227] As a preferred option, the objective function for risk optimization of the no-storage scheme is calculated using the following formula:

[0228]

[0229] In the formula, S represents the total number of scenes, and γ s Let I represent the probability of scenario s occurring, and let I be the expected net revenue from renewable energy generation without considering storage capacity. s.r I s.c These represent the revenue from new energy power generation and the cost of new energy power generation deviation assessment in scenario s, respectively.

[0230] As a preferred option, the benchmark operating conditions include, but are not limited to, the installed capacity of fossil and non-fossil power sources under the regional power grid, the start-up scheme of coal-fired and gas-fired power units and the minimum output coefficient of the units, the grid connection limit of new energy sources, the power generation coefficient of typical wind power / photovoltaic units, the annual maximum load and the power load coefficient of typical days.

[0231] As a preferred embodiment, the grid constraints that do not take into account load storage include:

[0232] Power balance constraints of regional power grids:

[0233]

[0234] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i (t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0235] Power generation constraints of coal-fired power units:

[0236] R tp.i.min ≤P tp.i (t)≤R tp.i.max

[0237] In the formula, P tp.i.min P tp.i.max Let be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0238] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u

[0239] In the formula, R tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power plant during time periods t and t-1.

[0240] Coal-fired power unit start-up and shutdown constraints:

[0241] (U i (t-1)-U i (t))·(T on.i (t-1)-M on.i )≥0

[0242] (U i (t)-U i (t-1))·(T off.i(t-1)-M off.i )≥0

[0243] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; M on.i M off.i Let be the minimum continuous operating time and minimum continuous downtime of unit i.

[0244] Gas turbine generator power generation constraints:

[0245] P gs.i.min ≤P gs.i (t)≤P gs.i.max

[0246] In the formula, P gs.imin P gs.i.max These represent the minimum and maximum power generation of the i-th gas turbine unit, respectively; power generation constraints for wind turbine units:

[0247] 0≤P w.i (t)≤P w.i.max

[0248] In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0249] Photovoltaic power generation constraints:

[0250] 0≤P s.i (t)≤P s.i.max

[0251] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0252] New energy grid connection capacity constraints:

[0253]

[0254] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0255] As a preferred option, typical parameters for energy storage include, but are not limited to, energy storage battery type, charge and discharge efficiency, installed capacity, and energy storage capacity. Typical parameters for controllable loads include, but are not limited to, response time, load capacity, and load capacity.

[0256] As a preferred approach, a baseline operating condition for the power grid in the region where the new energy power plant is located is established. The storage and load management schemes in the scheme library are then sequentially traversed. Under a single storage and load management scheme, all scenarios in the scenario library are traversed to complete the power grid operation condition analysis for all scenarios under a given storage and load management scheme. Based on the risk optimization objective function considering storage and load management, the expected net revenue of new energy power generation considering storage and load management under a given storage and load management scheme, based on the scenario library, is obtained, including:

[0257] The baseline operating conditions of the power grid in the area where the new energy power plant is located are set. The storage and load schemes in the scheme library are traversed sequentially. Under a storage and load scheme, all scenarios in the scenario library are traversed. Under the power grid constraints that take storage and load into account, the power grid operation conditions of the power grid in the area where the new energy power plant is located are simulated and analyzed for all scenarios under a storage and load scheme. The grid-connected new energy power, the regulated power, and the assessment power are obtained. Then, based on the grid-connected new energy power, the regulated power, and the assessment power, the new energy power generation revenue, storage and load regulation costs, and power generation deviation assessment costs under all scenarios under a storage and load scheme are obtained.

[0258] By substituting the revenue from new energy power generation, the cost of storage and load regulation, and the cost of power generation deviation assessment into the risk optimization objective function that includes storage and load, we obtain the expected net revenue of new energy power generation that includes storage and load under a storage and load scheme based on a scenario library.

[0259] As a preferred embodiment, the grid constraints taking into account load storage include:

[0260] Power balance constraints of regional power grids:

[0261]

[0262] In the formula, N tp N gs N w N s These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively; P tp.i (t), P gs.i (t), P w.i (t), P s.i (t) represents the actual power generation of the i-th coal-fired, gas-fired, wind-fired, and photovoltaic units in time period t, respectively; P load (t), P loss (t) represents the power load and power outage load during time period t, respectively.

[0263] Power generation constraints of coal-fired power units:

[0264] P tp.i.min ≤P tp.i (t)≤P tp.i.max

[0265] In the formula, P tp.i.min P tp.i.maxLet be the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. (The rest of the text appears to be a list of constraints related to power generation constraints and grid connection, which are not directly related to the initial statement about coal-fired power unit grid connection constraints.)

[0266] R tp.i.d ≤P tp.i (t)-P tp.i (t-1)≤R tp.i.u

[0267] In the formula, R tp.i.u R tp.i.d P represents the maximum ramping power of the i-th coal-fired power unit during power increase and power decrease within the regulation cycle. tp.i (t), P tp.i (t-1) represents the actual power generation of the i-th coal-fired power unit during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints:

[0268] (U i (t-1)-U i (t))·(T on.i (t-1)-M on.i )≥0

[0269] (U i (t)-U i (t-1))·(T off.i (t-1)-M off.i )≥0

[0270] In the formula, U i (t), U i (t-1) represents the 0-1 start-up / stop status of unit i during the time intervals t and t-1, where 0 indicates shutdown and 1 indicates startup; T on.i (t-1), T off.i (t-1) represents the continuous operating time and continuous downtime of unit i during the time period t-1; M on.i M off.i Let be the minimum continuous operating time and minimum continuous downtime of unit i.

[0271] Gas turbine generator power generation constraints:

[0272] P gs.i.min ≤P gs.i (t)≤P gs.i.max

[0273] In the formula, P gs.i.min P gs.i.max These represent the minimum and maximum power generation of the i-th gas turbine unit, respectively; power generation constraints for wind turbine units:

[0274] 0≤P w.i (t)≤P w.i.max

[0275] In the formula, P w.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0276] Photovoltaic power generation constraints:

[0277] 0≤P s.i (t)≤P s.i.max

[0278] In the formula, P s.i.max These represent the maximum power generation capacity of the i-th wind turbine unit;

[0279] New energy grid connection capacity constraints:

[0280]

[0281] In the formula, P line.max This represents the maximum grid-connected capacity of new energy sources within the region.

[0282] Energy storage power balance constraints:

[0283]

[0284] In the formula, t i t j For the start and end times of energy storage; E B (t i E B (t j P represents the energy level at the start and end of the energy storage process; B.c (t), P B.d (t) represents the charging and discharging power during time period t; U B (t) represents the energy storage charging / discharging state variable, where 1 indicates charging and 0 indicates discharging; η c η d For charging and discharging efficiency.

[0285] Energy storage power constraints:

[0286] -P B.max ≤P B.c (t)≤0

[0287] 0≤P B.d (t)≤P B.max

[0288] In the formula, P B.max This represents the maximum energy storage capacity.

[0289] Energy storage capacity constraints:

[0290] 0≤E B (t)≤E B.max

[0291] In the formula, EB.max This is the maximum energy storage capacity.

[0292] Controllable load power balance constraints:

[0293]

[0294] In the formula, t i t j E represents the start and end times of the controllable load response. D (t i E D (t j ) represents the controllable load t i Electricity already responded to during the period, t j The amount of electricity that has been responded to during the time period, P D (t) represents the controllable load power of the response during time period t; controllable load power constraints:

[0295] 0≤P D (t)≤P D.max

[0296] In the formula, P D.max This represents the maximum response power of a controllable load.

[0297] Controllable load power constraints:

[0298] 0≤E D (t)≤E D.max

[0299] In the formula, E D.max The maximum response power for a controllable load;

[0300] The power generation assessment constraints for new energy power plants that take into account storage resources are shown in the following formula.

[0301] P P (t)-P M (t)·ρ(t)≤P M (t)+P B (t)+P D (t)≤P P (t)+P M (t)·ρ(t)

[0302] In the formula, P B (t), P D (t) represents the energy storage and controllable load regulation power during time period t, respectively.

[0303] As a preferred embodiment, the risk optimization objective function taking into account storage load is calculated using the following formula:

[0304]

[0305] In the formula, S represents the total number of scenes, and γ s I represents the probability of scenario s occurring. x For the expected net revenue of renewable energy power generation considering storage capacity under the scenario library under storage capacity scheme x, I x.s.r I x.s.sl I x.s.c These represent the revenue from renewable energy generation, the cost of energy storage regulation, and the cost of renewable energy generation deviation assessment in scenario s of energy storage scheme x, respectively.

[0306] As a preferred option, the risk-cost-performance ratio calculation formula for the storage and load scheme is as follows:

[0307]

[0308] In the formula, C s C l The configuration costs for energy storage and controllable loads are respectively, I x I and I represent the expected net income of new energy power generation without considering storage capacity based on the scenario library and the expected net income of new energy power generation without considering storage capacity based on the scenario library, respectively.

[0309] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0310] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0311] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0312] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0313] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A risk-optimized method for configuring storage and load in new energy power plants, characterized in that: Includes the following steps: The uncertainties in the grid-connected operation of new energy power plants are identified, the characteristic values ​​of these uncertainties are extracted in a certain way, scenarios are constructed, and all scenarios are collected to form a scenario library. Set the baseline operating conditions of the power grid in the area where the new energy power station is located, traverse all scenarios in the scenario library, complete the power grid operation condition analysis of the power grid in the area where the new energy power station is located for all scenarios, and obtain the expected net income of new energy power generation without considering storage based on the risk optimization objective function of the no-storage scheme. Configure storage and controllable load typical parameters to select storage and load schemes with different regulation performance, and obtain all storage and load schemes to form a scheme library; Set the baseline operating conditions of the power grid in the area where the new energy power station is located, traverse the storage schemes in the scheme library in turn, and traverse all scenarios in the scenario library under a storage scheme to complete the power grid operation condition analysis of the power grid in the area where the new energy power station is located under all scenarios of a storage scheme. Based on the risk optimization objective function that takes storage into account, obtain the expected net income of new energy power generation taking storage into account under a storage scheme based on the scenario library. The risk-cost-performance ratio of the storage scheme is calculated based on the expected net income of new energy power generation without storage capacity based on the scenario library, and the expected net income of new energy power generation with storage capacity based on the scenario library under a storage scheme. Calculate the risk-cost-performance ratio of all storage and load options, and select the storage and load option with the lowest risk-cost-performance ratio. The formula for calculating the risk-cost-performance ratio of the storage and load scheme is as follows: ； In the formula, These are the configuration costs for energy storage and controllable load, respectively. These represent the expected net revenue from renewable energy generation, taking into account the energy storage scheme and excluding energy storage, respectively.

2. The method for configuring storage and load in a new energy power plant based on risk optimization according to claim 1, characterized in that: Uncertain factors in the grid-connected operation of new energy power plants are identified, and characteristic values ​​of these uncertain factors are extracted in a certain way. Scenarios are then constructed, and all scenarios are collected to form a scenario library, including: The grid connection limit of new energy power plants, wind / photovoltaic power generation and power load are quantified respectively, and the quantified characteristic values ​​are obtained. The characteristic values ​​of any combination of grid connection limit of new energy power station, wind / photovoltaic power generation and power load are extracted to form a scenario, and the occurrence probability of each scenario is set to build a scenario library.

3. The method for configuring storage and load in a new energy power plant based on risk optimization according to claim 1, characterized in that: The baseline operating conditions of the power grid in the region where the new energy power plant is located are established. All scenarios in the scenario library are traversed, and the power grid operation conditions of the region where the new energy power plant is located are analyzed for all scenarios. Based on the risk optimization objective function of the no-storage scheme, the expected net revenue of new energy power generation without considering storage is obtained based on the scenario library, including: Set the baseline operating conditions of the power grid in the area where the new energy power station is located, traverse all scenarios in the scenario library, and simulate and analyze the power grid operation conditions of the power grid in the area where the new energy power station is located in all scenarios without considering the power grid constraints of the storage load. Obtain the new energy grid-connected power and the assessment power. Based on the new energy grid-connected power and the assessment power, obtain the new energy power generation revenue and the power generation deviation assessment cost. By substituting the revenue from new energy power generation and the cost of power generation deviation assessment into the risk optimization objective function of the no-storage scheme, the expected net revenue of new energy power generation without considering storage capacity is obtained based on the scenario library.

4. The risk-optimized new energy power plant storage and load configuration method according to claim 3, characterized in that: The objective function for risk optimization of the no-storage scheme is calculated as follows: ； In the formula, S represents the total number of scenes. This represents the probability of scenario S occurring. To exclude the expected net income from renewable energy generation based on storage capacity, , These represent the revenue from new energy power generation and the cost of new energy power generation deviation assessment in scenario S, respectively.

5. The risk-optimized new energy power plant storage-load configuration method according to claim 3, characterized in that: The grid constraints that do not take into account load storage include: Power balance constraints of regional power grids: ； In the formula, , , , These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively. , , , These represent the actual power generation of the i-th coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively, during time period t. , These represent the power load and power outage load during time period t, respectively. Power generation constraints of coal-fired power units: ； In the formula, , These are the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. Power constraints for coal-fired power units climbing slopes: ； In the formula, , Let be the maximum ramp power of the i-th coal-fired power unit during power increase and power decrease within the adjustment cycle, respectively. Let t be the actual power generation of the i-th coal-fired power plant during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints: ； ； In the formula, The 0-1 start-up and stop status of unit i during the time periods t and t-1, where 0 represents shutdown and 1 represents startup; , For unit i, this represents the continuous operating time and continuous downtime during the time period t-1. , Let i be the minimum continuous operating time and minimum continuous downtime of unit i. Gas turbine generator power generation constraints: ； In the formula, , These are the minimum and maximum power generation of the i-th gas turbine unit, respectively; Wind turbine power generation constraints: ； In the formula, This represents the maximum power generation of the i-th wind turbine. Photovoltaic power generation constraints: ； In the formula, This represents the maximum power generation of the i-th wind turbine. New energy grid connection capacity constraints: ； In the formula, This represents the maximum grid-connected capacity of new energy sources within the region.

6. The method for configuring storage and load in a new energy power plant based on risk optimization according to claim 1, characterized in that: Typical parameters for energy storage include battery type, charge / discharge efficiency, installed capacity, and energy storage capacity. Typical parameters for controllable loads include response time, load capacity, and load power.

7. The method for configuring storage and load in a new energy power plant based on risk optimization according to claim 1, characterized in that: The baseline operating conditions of the power grid in the region where the new energy power plant is located are set. The storage and load management schemes in the scheme library are iterated sequentially. Under a single storage and load management scheme, all scenarios in the scenario library are traversed to complete the power grid operation condition analysis of the region where the new energy power plant is located for all scenarios under a single storage and load management scheme. Based on the risk optimization objective function considering storage and load management, the expected net revenue of new energy power generation considering storage and load management under a single storage and load management scheme, based on the scenario library, is obtained, including: Set the baseline operating conditions of the power grid in the area where the new energy power station is located, traverse the storage schemes in the scheme library in turn, and traverse all scenarios in the scenario library under a storage scheme. Under the power grid constraints that take storage into account, simulate and analyze the power grid operation conditions of the power grid in the area where the new energy power station is located under all scenarios of a storage scheme to obtain the new energy grid-connected power, the regulated power, and the assessment power. Then, based on the new energy grid-connected power, the regulated power, and the assessment power, obtain the new energy power generation revenue, storage regulation cost, and power generation deviation assessment cost under all scenarios of a storage scheme. By substituting the revenue from new energy power generation, the cost of storage and load regulation, and the cost of power generation deviation assessment into the risk optimization objective function that includes storage and load, we obtain the expected net revenue of new energy power generation that includes storage and load under a storage and load scheme based on a scenario library.

8. The method for configuring storage and load in a new energy power plant based on risk optimization according to claim 7, characterized in that: The grid constraints that take into account load storage include: Power balance constraints of regional power grids: ； In the formula, , , , These represent the total number of coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively. , , , These represent the actual power generation of the i-th coal-fired power, gas-fired power, wind power, and photovoltaic power units, respectively, during time period t. , These represent the power load and power outage load during time period t, respectively. Power generation constraints of coal-fired power units: ； In the formula, , These are the minimum and maximum generating capacities of the i-th coal-fired power unit, respectively. Power constraints for coal-fired power units climbing slopes: ； In the formula, , Let be the maximum ramp power of the i-th coal-fired power unit during power increase and power decrease within the adjustment cycle, respectively. Let t be the actual power generation of the i-th coal-fired power plant during time periods t and t-1. Coal-fired power unit start-up and shutdown constraints: ； ； In the formula, The 0-1 start-up and stop status of unit i during the time periods t and t-1, where 0 represents shutdown and 1 represents startup; , For unit i, this represents the continuous operating time and continuous downtime during the time period t-1. , Let i be the minimum continuous operating time and minimum continuous downtime of unit i. Gas turbine generator power generation constraints: ； In the formula, , These are the minimum and maximum power generation of the i-th gas turbine unit, respectively; Wind turbine power generation constraints: ； In the formula, This represents the maximum power generation of the i-th wind turbine. Photovoltaic power generation constraints: ； In the formula, This represents the maximum power generation of the i-th wind turbine. New energy grid connection capacity constraints: ； In the formula, This represents the maximum grid-connected capacity of new energy sources within the region. Energy storage power balance constraints: ； In the formula, , The start and end times of energy storage; , This represents the energy level at the start and end of energy storage. , The charging and discharging power during time period t; For energy storage charging / discharging state variables, 1 represents charging and 0 represents discharging; , For charging and discharging efficiency; Energy storage power constraints: ； ； In the formula, This represents the maximum energy storage capacity. Energy storage capacity constraints: ； In the formula, This is the maximum energy storage capacity. Controllable load power balance constraints: ； In the formula, , The start and end times of the controllable load response. , For controllable load The amount of electricity that has been responded to during the period The amount of electricity that has been responded to during the specified time period, The controllable load power for the response time period t; Controllable load power constraints: ； In the formula, This represents the maximum response power of a controllable load. Controllable load power constraints: ； In the formula, The maximum response power for a controllable load; The power generation assessment constraints for new energy power plants that take into account storage resources are shown in the following formula. ； In the formula, , These represent the energy storage and controllable load regulation power during time period t, respectively. This represents the deviation rate for time period t; , These represent the actual power and short-term predicted power of renewable energy generation during time period t, respectively.

9. A risk-optimized method for configuring storage and load in a new energy power plant according to claim 7, characterized in that: The risk optimization objective function taking into account storage and load is calculated using the following formula: ； In the formula, S represents the total number of scenes. This represents the probability of scenario S occurring. The expected net revenue of renewable energy power generation, taking into account storage capacity, is calculated based on a scenario library under storage capacity scheme x. , , These represent the revenue from renewable energy generation, the cost of energy storage regulation, and the cost of renewable energy generation deviation assessment in scenario S of the energy storage scheme x, respectively.

10. A risk-optimized method for configuring storage and load in a new energy power plant, as described in claim 3 or 7, characterized in that: The benchmark operating conditions include the installed capacity of fossil and non-fossil power sources under the regional power grid, the start-up scheme of coal-fired and gas-fired power units and the minimum output coefficient of the units, the grid connection limit of new energy sources, the power generation coefficient of typical wind power / photovoltaic units, the annual maximum load and the power load coefficient of typical days.

11. A risk-optimized new energy power plant storage and load configuration device, characterized in that: Includes the following modules: The scenario library acquisition module is used to acquire uncertainties in the grid-connected operation of new energy power plants, extract the feature values ​​of uncertainties in a certain way, construct scenarios, and acquire all scenarios to form a scenario library; The module for calculating revenue without considering storage load is used to set the baseline operating conditions of the power grid in the area where the new energy power station is located, traverse all scenarios in the scenario library, complete the power grid operation condition analysis of the power grid in the area where the new energy power station is located for all scenarios, and obtain the expected net revenue of new energy power generation without considering storage load based on the scenario library according to the risk optimization objective function of the no-storage load scheme. The scheme library acquisition module is used to set typical parameters for energy storage and controllable loads to configure storage and load schemes with different regulation performance, and acquire all storage and load schemes to form a scheme library; The module for calculating the revenue from storage is used to set the baseline operating conditions of the power grid in the area where the new energy power station is located. It iterates through the storage schemes in the scheme library, and under a storage scheme, it iterates through all scenarios in the scenario library to complete the power grid operation condition analysis of the power grid in the area where the new energy power station is located for all scenarios under a storage scheme. Based on the risk optimization objective function that takes storage into account, it obtains the expected net revenue of new energy power generation taking storage into account under a storage scheme based on the scenario library. The risk-cost-performance ratio calculation module is used to calculate the risk-cost-performance ratio of the storage scheme based on the expected net income of new energy power generation without storage capacity based on the scenario library, and the expected net income of new energy power generation with storage capacity based on the scenario library under a storage scheme. The storage and load scheme optimization module is used to calculate the risk-cost-performance ratio of all storage and load schemes and select the storage and load scheme with the lowest risk-cost-performance ratio. The formula for calculating the risk-cost-performance ratio of the storage and load scheme is as follows: ； In the formula, These are the configuration costs for energy storage and controllable load, respectively. These represent the expected net income of new energy power generation based on the scenario library, excluding storage capacity, and the expected net income of new energy power generation based on the scenario library, excluding storage capacity, respectively.

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