New energy and load uncertainty coordinated power grid carbon reduction capability optimization verification method

Abstract

The invention provides a new energy and load uncertainty coordinated power grid carbon reduction capability optimization verification method, and relates to the technical field of optimization verification, and the method comprises the steps: building a power grid model, carrying out the superposition modeling of the power grid model according to historical new energy data and historical load data, and determining a power grid new energy and load model; obtaining current new energy data and current load data, coordinating the current new energy data and the current load data according to the power grid new energy and load model, and determining a current power grid operation constraint condition; obtaining a power grid carbon reduction demand and a current power grid carbon reduction capability, obtaining predicted new energy data and predicted load data, and optimizing the current power grid carbon reduction capability according to a preset optimization algorithm and a current power grid operation constraint condition; constructing a power grid carbon reduction capability optimization evaluation index, analyzing and verifying a current power grid carbon reduction capability optimization result, and determining the power grid carbon reduction capability optimization effectiveness; and effective optimization of the carbon reduction capability of the power grid is ensured.

Description

Technical Field

[0001] The present invention relates to the field of optimization verification technology, and in particular to a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy sources with load uncertainty. Background Art

[0002] With the continuous development of new energy, the utilization and utilization rate of new energy in power grid operations are constantly increasing. However, the output of new energy is intermittent and random, which seriously affects the load of the power grid and thus affects the stability of the power grid operation. In addition, a large amount of greenhouse gases will be generated during the operation of the power grid, and current development requirements require reducing carbon emissions during the operation of the power grid.

[0003] Therefore, the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy sources with load uncertainty. Summary of the Invention

[0004] The present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid that coordinates new energy and load uncertainty. The method comprises the following steps: constructing a power grid model, superimposing and modeling the power grid model according to historical new energy data and historical load data, and determining the new energy and load model of the power grid; obtaining current new energy data and current load data, coordinating the current new energy data and current load data according to the new energy and load model of the power grid, and determining the current power grid operation constraints; obtaining the carbon reduction demand of the power grid and the current power grid carbon reduction capacity, obtaining predicted new energy data and predicted load data, and optimizing the current power grid carbon reduction capacity according to a preset optimization algorithm and the current power grid operation constraints; constructing a power grid carbon reduction capacity optimization evaluation index, analyzing and verifying the current power grid carbon reduction capacity optimization results, and determining the effectiveness of the power grid carbon reduction capacity optimization; and ensuring the effective optimization of the power grid carbon reduction capacity.

[0005] The present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy sources with load uncertainty, comprising:

[0006] Step 1: Build a power grid model, superimpose the power grid model based on historical new energy data and historical load data, and determine the power grid new energy and load model;

[0007] Step 2: Obtain current renewable energy data and current load data, coordinate the current renewable energy data and current load data according to the grid renewable energy and load model, and determine the current grid operation constraints;

[0008] Step 3: Obtain the grid's carbon reduction demand and current grid carbon reduction capacity, obtain predicted new energy data and predicted load data, and optimize the current grid carbon reduction capacity based on the preset optimization algorithm and current grid operation constraints;

[0009] Step 4: Construct an optimization evaluation index for the grid’s carbon reduction capacity, analyze and verify the current grid’s carbon reduction capacity optimization results, and determine the effectiveness of the grid’s carbon reduction capacity optimization.

[0010] According to the method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty provided by the present invention, a power grid model is constructed, and the power grid model is superimposed and modeled based on historical new energy data and historical load data to determine the new energy and load models of the power grid, including:

[0011] Obtaining grid components, selecting a preset grid model, and obtaining grid operation data to construct a grid model, wherein the grid components include: generator set components, transmission line components, transformer components, and load components;

[0012] Obtain historical renewable energy data and historical load data, and perform a superposition modeling of the power grid model based on the historical renewable energy data and renewable energy output characteristics. The renewable energy output characteristics include: output intermittent characteristics and output random characteristics;

[0013] Input historical load data into the power grid model completed by the primary superposition modeling to perform secondary superposition modeling to obtain the new energy and load model of the power grid;

[0014] Randomly simulate and generate grid operation scenarios based on historical new energy data and historical load data, run the grid new energy and load models in the grid operation scenarios, and evaluate the grid operation status;

[0015] When the evaluation results show that the grid operation state is stable, it is determined that the superposition modeling of the grid new energy and load models is completed.

[0016] According to the method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty provided by the present invention, current new energy data and current load data are obtained, and the current new energy data and current load data are coordinated according to the power grid new energy and load model to determine the current power grid operation constraints, including:

[0017] Obtain current new energy data and current load data and perform data preprocessing to remove erroneous data and abnormal data in the current new energy data and current load data;

[0018] Input the current new energy data and current load data after data preprocessing into the power grid new energy and load model to determine the current operating status of the power grid;

[0019] determining overall grid operation constraints based on grid operation data, wherein the overall grid operation constraints include: generator set output constraints, generator set output fluctuation constraints, grid voltage constraints, grid frequency constraints, grid redundancy constraints, and grid load constraints;

[0020] When the current operation state of the power grid is a stable operation state, the current new energy data and the current load data are coordinated according to the overall operation constraint conditions of the power grid, so that the current new energy data and the current load data change within the overall operation constraint conditions of the power grid;

[0021] The current grid operation constraints are determined based on the overall grid operation constraints and coordination results.

[0022] The method for optimizing and verifying the carbon reduction capacity of a power grid in coordination with new energy and load uncertainty provided by the present invention further includes:

[0023] Compare the total grid operation constraints with the current grid operation constraints, obtain the relevant constraints in the current grid operation constraints that are not less than the total grid operation constraints, and determine the optimizable items of the current grid operation.

[0024] The method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty provided by the present invention obtains the carbon reduction demand of the power grid and the current carbon reduction capacity of the power grid, including:

[0025] Obtain grid carbon reduction needs, determine grid carbon reduction indicators, and assess the current grid carbon reduction capacity. Grid carbon reduction indicators include: renewable energy installed capacity, renewable energy utilization, carbon emissions, and grid redundancy.

[0026] When the assessment results show that the current grid's carbon reduction capacity is qualified, there is no need to optimize the current grid's carbon reduction capacity;

[0027] When the evaluation results show that the current power grid's carbon reduction capacity is unqualified, the current power grid's carbon reduction capacity is optimized, and the current power grid's carbon reduction optimizable items are determined based on the current power grid's operation optimizable items.

[0028] The method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty provided by the present invention obtains predicted new energy data and predicted load data, and optimizes the carbon reduction capacity of the current power grid according to a preset optimization algorithm and current power grid operation constraints, including:

[0029] Determine the forecast time based on the grid's carbon reduction needs, input the pre-processed current renewable energy data and current load data into the grid's renewable energy and load model, and obtain forecasted renewable energy data and forecasted load data;

[0030] Input historical renewable energy data and historical load data into the grid renewable energy and load model to determine the prediction error;

[0031] Determine a preset optimization algorithm for optimizing the carbon reduction capacity of the current power grid from the optimization algorithms based on the power grid's renewable energy and load model and the current power grid operation constraints, wherein the optimization algorithms include: linear programming algorithm, quadratic programming algorithm, nonlinear programming algorithm, and stochastic programming algorithm;

[0032] The current power grid carbon reduction capacity is optimized based on the preset optimization algorithm, predicted new energy data and predicted load data, prediction error, current power grid carbon reduction optimizable items and current power grid operation constraints.

[0033] According to the method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty provided by the present invention, an optimization evaluation index for the carbon reduction capacity of a power grid is constructed, and the current optimization results of the carbon reduction capacity of the power grid are analyzed and verified to determine the effectiveness of the optimization of the carbon reduction capacity of the power grid, including:

[0034] Determine the grid's carbon reduction capacity optimization assessment indicators based on the grid's carbon reduction needs. These indicators include: new energy installed capacity optimization assessment indicators, new energy utilization optimization assessment indicators, carbon emissions optimization assessment indicators, and grid redundancy optimization assessment indicators.

[0035] Normalize the optimization evaluation indicators of the power grid's carbon reduction capacity;

[0036] Performing subjective and objective weighting processing on the normalized grid carbon reduction capacity optimization evaluation indicators to determine the indicator weights of the normalized grid carbon reduction capacity optimization evaluation indicators;

[0037] Obtain the indicator range of the normalized grid carbon reduction capacity optimization evaluation indicator, obtain the normalized value of the current grid carbon reduction capacity optimization result in the normalized grid carbon reduction capacity optimization evaluation indicator, and the optimization ratio of the current grid carbon reduction capacity optimization result within the indicator range;

[0038] Analyze and verify the optimization results of the current grid carbon reduction capacity, and determine the current optimized value of the grid carbon reduction capacity based on the optimization ratio and indicator weights;

[0039] Among them, F represents the current optimization value of the grid's carbon reduction capacity; w1(i1,j1) represents the j1th subjective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; w2(i1,j1) represents the j1th objective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; xi1 represents the normalized value of the current grid's carbon reduction capacity optimization result in the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y1i1 represents the lower threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y2i1 represents the upper threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; n1 represents the number of indicators of the grid's carbon reduction capacity optimization evaluation index after the normalization process; m1 represents the number of subjective and objective weights of the subjective and objective weighted processing of the grid's carbon reduction capacity optimization evaluation index after the normalization process;

[0040] When the current optimized value of the grid's carbon reduction capacity is not lower than the preset optimized value, it is determined that the optimization of the grid's carbon reduction capacity is effective.

[0041] The method for optimizing and verifying the carbon reduction capacity of a power grid in coordination with new energy and load uncertainty provided by the present invention further includes:

[0042] When it is determined that the optimization of the grid's carbon reduction capacity is effective, an operation test is performed in the actual grid based on the current grid's carbon reduction capacity optimization results and the actual grid operation status is monitored in real time.

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] By constructing a power grid model, the power grid model is superimposed and modeled according to historical new energy data and historical load data to determine the power grid new energy and load model; the current new energy data and current load data are obtained, and the current new energy data and current load data are coordinated according to the power grid new energy and load model to determine the current power grid operation constraints; the power grid carbon reduction demand and the current power grid carbon reduction capacity are obtained, the predicted new energy data and predicted load data are obtained, and the current power grid carbon reduction capacity is optimized according to the preset optimization algorithm and the current power grid operation constraints; the power grid carbon reduction capacity optimization evaluation index is constructed, the current power grid carbon reduction capacity optimization results are analyzed and verified, and the effectiveness of the power grid carbon reduction capacity optimization is determined; and the effective optimization of the power grid carbon reduction capacity is ensured.

[0045] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0046] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 It is a flow chart of a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0050] Example 1:

[0051] The embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty, such as Figure 1 Shown, including:

[0052] Step 1: Build a power grid model, superimpose the power grid model based on historical new energy data and historical load data, and determine the power grid new energy and load model;

[0053] Step 2: Obtain current renewable energy data and current load data, coordinate the current renewable energy data and current load data according to the grid renewable energy and load model, and determine the current grid operation constraints;

[0054] Step 3: Obtain the grid's carbon reduction demand and current grid carbon reduction capacity, obtain predicted new energy data and predicted load data, and optimize the current grid carbon reduction capacity based on the preset optimization algorithm and current grid operation constraints;

[0055] Step 4: Construct an optimization evaluation index for the grid’s carbon reduction capacity, analyze and verify the current grid’s carbon reduction capacity optimization results, and determine the effectiveness of the grid’s carbon reduction capacity optimization.

[0056] In this embodiment, the power grid model refers to a model for simulating power grid operation that is constructed based on power grid components, a preset power grid model, and power grid operation data.

[0057] In this embodiment, superposition modeling refers to the operation of superimposing new energy data and load data on the basis of the power grid model.

[0058] In this embodiment, the grid new energy and load model refers to a grid model determined based on quadratic superposition modeling.

[0059] In this embodiment, the current new energy data refers to the new energy data of the power grid in the current period.

[0060] In this embodiment, the current load data refers to the load data of the power grid in the current period.

[0061] In this embodiment, the current power grid operation constraint condition refers to the operation constraint condition that the power grid is in a stable operation state in the current period.

[0062] In this embodiment, the grid carbon reduction demand refers to the demand for reducing greenhouse gases generated during grid operation.

[0063] In this embodiment, the current grid carbon reduction capability refers to the grid carbon reduction capability of the grid in the current period.

[0064] In this embodiment, the predicted new energy data and the predicted load data refer to the predicted data obtained by inputting the current new energy data and the current load data after data preprocessing into the new energy and load model of the power grid.

[0065] In this embodiment, the preset optimization algorithm refers to an optimization algorithm that can be used to optimize the carbon reduction capacity of the current power grid, determined from the optimization algorithm based on the new energy and load model of the power grid and the current power grid operation constraints.

[0066] In this embodiment, the grid carbon reduction capability optimization evaluation index refers to an index used to evaluate the grid carbon reduction capability optimization result.

[0067] In this embodiment, the effectiveness of the optimization of the carbon reduction capacity of the power grid refers to whether the optimization of the carbon reduction capacity of the power grid is effective.

[0068] The working principle and beneficial effects of the above technical solution are: by constructing a power grid model, superimposing and modeling the power grid model according to historical new energy data and historical load data, and determining the power grid new energy and load model; obtaining current new energy data and current load data, and coordinating the current new energy data and current load data according to the power grid new energy and load model, and determining the current power grid operation constraints; obtaining the power grid carbon reduction demand and the current power grid carbon reduction capacity, obtaining predicted new energy data and predicted load data, and optimizing the current power grid carbon reduction capacity according to the preset optimization algorithm and the current power grid operation constraints; constructing a power grid carbon reduction capacity optimization evaluation index, analyzing and verifying the current power grid carbon reduction capacity optimization results, and determining the effectiveness of the power grid carbon reduction capacity optimization; ensuring the effective optimization of the power grid carbon reduction capacity.

[0069] Example 2:

[0070] The embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty. The method constructs a power grid model, performs superposition modeling on the power grid model based on historical new energy data and historical load data, and determines the power grid new energy and load model, including:

[0071] Obtaining grid components, selecting a preset grid model, and obtaining grid operation data to construct a grid model, wherein the grid components include: generator set components, transmission line components, transformer components, and load components;

[0072] Obtain historical renewable energy data and historical load data, and perform a superposition modeling of the power grid model based on the historical renewable energy data and renewable energy output characteristics. The renewable energy output characteristics include: output intermittent characteristics and output random characteristics;

[0073] Input historical load data into the power grid model completed by the primary superposition modeling to perform secondary superposition modeling to obtain the new energy and load model of the power grid;

[0074] Randomly simulate and generate grid operation scenarios based on historical new energy data and historical load data, run the grid new energy and load models in the grid operation scenarios, and evaluate the grid operation status;

[0075] When the evaluation results show that the grid operation state is stable, it is determined that the superposition modeling of the grid new energy and load models is completed.

[0076] In this embodiment, the grid components refer to components of the grid operation, such as generator components, transmission line components, transformer components, and load components.

[0077] In this embodiment, the preset power grid model refers to a preset model for constructing a power grid model.

[0078] In this embodiment, the power grid operation data refers to data generated during the operation of the power grid.

[0079] In this embodiment, the power grid model refers to a model for simulating power grid operation that is constructed based on power grid components, a preset power grid model, and power grid operation data.

[0080] In this embodiment, the historical new energy data refers to new energy data of the power grid within a historical period obtained based on the power grid operation data, such as historical wind energy data.

[0081] In this embodiment, the historical load data refers to the load data of the power grid within a historical period obtained based on the power grid operation data.

[0082] In this embodiment, the primary superposition modeling refers to the superposition modeling of the power grid model based on the historical new energy data and the new energy output characteristics, so as to ensure that the primary superposition modeling result is adapted to the new energy data.

[0083] In this embodiment, the secondary superposition modeling refers to superimposing historical load data on the basis of the primary superposition modeling, so as to ensure that the secondary superposition modeling result is adapted to the load data.

[0084] In this embodiment, the grid new energy and load model refers to a grid model determined based on quadratic superposition modeling.

[0085] In this embodiment, the grid operation state includes: a stable operation state and an abnormal operation state.

[0086] In this embodiment, when the evaluation result shows that the grid operation state is a stable operation state, it is determined that the grid new energy and load model superposition modeling is completed, that is, the grid new energy and load model can effectively adapt to the new energy data and effectively adapt to the load data.

[0087] The working principle and beneficial effects of the above technical solution are: by constructing a power grid model, superimposing the power grid model based on historical new energy data and historical load data, determining the power grid new energy and load model, and laying the model foundation for subsequent optimization and verification of the power grid's carbon reduction capacity.

[0088] Example 3:

[0089] The embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty. The method obtains current new energy data and current load data, coordinates the current new energy data and current load data according to a power grid new energy and load model, and determines the current power grid operation constraints, including:

[0090] Obtain current new energy data and current load data and perform data preprocessing to remove erroneous data and abnormal data in the current new energy data and current load data;

[0091] Input the current new energy data and current load data after data preprocessing into the power grid new energy and load model to determine the current operating status of the power grid;

[0092] determining overall grid operation constraints based on grid operation data, wherein the overall grid operation constraints include: generator set output constraints, generator set output fluctuation constraints, grid voltage constraints, grid frequency constraints, grid redundancy constraints, and grid load constraints;

[0093] When the current operation state of the power grid is a stable operation state, the current new energy data and the current load data are coordinated according to the overall operation constraint conditions of the power grid, so that the current new energy data and the current load data change within the overall operation constraint conditions of the power grid;

[0094] The current grid operation constraints are determined based on the overall grid operation constraints and coordination results.

[0095] In this embodiment, the current new energy data refers to the new energy data of the power grid in the current period.

[0096] In this embodiment, the current load data refers to the load data of the power grid in the current period.

[0097] In this embodiment, the current operating state of the power grid refers to the operating state of the power grid in the current period.

[0098] In this embodiment, the overall operation constraint condition of the power grid refers to the operation constraint condition when the power grid is in a stable operation state in each period.

[0099] In this embodiment, the operating constraints refer to the conditions that must be met for stable operation of the power grid, such as generator set output constraints, generator set output fluctuation constraints, grid voltage constraints, grid frequency constraints, grid redundancy constraints, and grid load constraints.

[0100] In this embodiment, coordinating the current new energy data and the current load data according to the overall operation constraints of the power grid means controlling the changes of the current new energy data and the current load data according to the overall operation constraints of the power grid, ensuring that the current new energy data and the current load data change within the overall operation constraints of the power grid, and thus ensuring the stable operation state of the power grid.

[0101] In this embodiment, the coordination result refers to the result of coordinating the current new energy data and the current load data according to the total constraint conditions of the power grid operation, for example, the current new energy data is coordinated from a1 data to a2 data.

[0102] In this embodiment, the current power grid operation constraint condition refers to the operation constraint condition that the power grid is in a stable operation state in the current period.

[0103] The working principle and beneficial effects of the above technical solution are: by obtaining current new energy data and current load data, coordinating the current new energy data and current load data according to the power grid new energy and load model, determining the current power grid operation constraints, and laying the constraint foundation for subsequent optimization of the power grid's carbon reduction capacity.

[0104] Example 4:

[0105] An embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy sources with load uncertainty, further comprising:

[0106] Compare the overall grid operation constraints with the current grid operation constraints, obtain the relevant constraints in the current grid operation constraints that are not lower than the overall grid operation constraints, and determine the items that can be optimized in the current grid operation.

[0107] In this embodiment, the relevant constraints in the current grid operation constraints that are not lower than the overall grid operation constraints, for example, the constraint on the output fluctuation of generating units d1 in the overall grid operation constraints, and the constraint on the output fluctuation of generating units d2 in the current grid operation constraints, where d1 < d2, indicating that the current grid operation constraints are more relaxed and there is room for further optimization.

[0108] In this embodiment, the items that can be optimized in the current grid operation refer to the operation constraints that can be optimized while ensuring the stable operation of the grid, determined by comparing the overall grid operation constraints with the current grid operation constraints.

[0109] The working principle and beneficial effects of the above technical solution are: By comparing the overall grid operation constraints with the current grid operation constraints, determine the items that can be optimized in the current grid operation, laying a foundation for optimizing the carbon reduction capacity of the grid in the follow-up.

[0110] Embodiment 5:

[0111] The embodiment of the present invention provides a method for verifying the optimization of the carbon reduction capacity of the grid coordinated with the uncertainty of new energy and load, which obtains the carbon reduction demand of the grid and the current carbon reduction capacity of the grid, including:

[0112] Obtain the carbon reduction demand of the grid, determine the carbon reduction indicators of the grid, and evaluate the current carbon reduction capacity of the grid. Among them, the carbon reduction indicators of the grid include: new energy installed capacity indicator, new energy utilization rate indicator, carbon emission indicator, and grid redundancy indicator;

[0113] When the evaluation result shows that the current carbon reduction capacity of the grid is qualified, there is no need to optimize the current carbon reduction capacity of the grid;

[0114] When the evaluation result shows that the current carbon reduction capacity of the grid is unqualified, then optimize the current carbon reduction capacity of the grid, and determine the items that can be optimized for the current grid carbon reduction according to the items that can be optimized in the current grid operation.

[0115] In this embodiment, the carbon reduction demand of the grid refers to the demand for reducing greenhouse gas emissions during the operation of the grid, for example, the demand for minimizing carbon emissions and maximizing the utilization rate of new energy.

[0116] In this embodiment, the carbon reduction indicators of the grid refer to the indicators used to evaluate the carbon reduction capacity of the grid, including: new energy installed capacity indicator, new energy utilization rate indicator, carbon emission indicator, and grid redundancy indicator.

[0117] In this embodiment, the carbon reduction capability of the power grid refers to the ability of the power grid to reduce carbon emissions.

[0118] In this embodiment, the current grid carbon reduction capability refers to the grid carbon reduction capability of the grid in the current period.

[0119] In this embodiment, the current grid carbon reduction optimizable items refer to the corresponding items for optimizing the current grid carbon reduction capacity, such as the generator set output fluctuation optimization items, which optimize the generator set output fluctuation and thus optimize the current grid carbon reduction capacity.

[0120] The working principle and beneficial effects of the above technical solution are: by obtaining the carbon reduction demand of the power grid and the current carbon reduction capacity of the power grid, it is conducive to the subsequent optimization and optimization verification of the carbon reduction capacity of the power grid.

[0121] Example 6:

[0122] The embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy and load uncertainty. The method obtains predicted new energy data and predicted load data, and optimizes the carbon reduction capacity of the current power grid according to a preset optimization algorithm and current power grid operation constraints, including:

[0123] Determine the forecast time based on the grid's carbon reduction needs, input the pre-processed current renewable energy data and current load data into the grid's renewable energy and load model, and obtain forecasted renewable energy data and forecasted load data;

[0124] Input historical renewable energy data and historical load data into the grid renewable energy and load model to determine the prediction error;

[0125] Determine a preset optimization algorithm for optimizing the carbon reduction capacity of the current power grid from the optimization algorithms based on the power grid's renewable energy and load model and the current power grid operation constraints, wherein the optimization algorithms include: linear programming algorithm, quadratic programming algorithm, nonlinear programming algorithm, and stochastic programming algorithm;

[0126] The current power grid carbon reduction capacity is optimized based on the preset optimization algorithm, predicted new energy data and predicted load data, prediction error, current power grid carbon reduction optimizable items and current power grid operation constraints.

[0127] In this embodiment, the prediction time, for example, predicts the new energy data and load data for the next week.

[0128] In this embodiment, the predicted new energy data and the predicted load data refer to the predicted data obtained by inputting the current new energy data and the current load data after data preprocessing into the new energy and load model of the power grid.

[0129] In this embodiment, the prediction error refers to the error degree of the prediction data determined by inputting historical new energy data and historical load data into the grid new energy and load model. The larger the prediction error, the lower the credibility of the prediction data.

[0130] In this embodiment, the optimization algorithm refers to an algorithm that can be used to optimize the carbon reduction capacity of the power grid.

[0131] In this embodiment, the preset optimization algorithm refers to an optimization algorithm that can be used to optimize the carbon reduction capacity of the current power grid, determined from the optimization algorithm based on the new energy and load model of the power grid and the current power grid operation constraints.

[0132] In this embodiment, the current power grid carbon reduction capacity is optimized based on the preset optimization algorithm, predicted new energy data and predicted load data, prediction error, current power grid carbon reduction optimizable items and current power grid operating constraints. For example, the predicted new energy data and predicted load data are determined to be credible based on the prediction error, and then the optimization content is determined based on the preset optimization algorithm and the current power grid carbon reduction optimizable items and current power grid operating constraints. For example, the output fluctuation of the generator set is optimized, and then the current power grid carbon reduction capacity is optimized.

[0133] The working principle and beneficial effects of the above technical solution are: obtaining predicted new energy data and predicted load data, optimizing the current power grid's carbon reduction capacity according to the preset optimization algorithm and the current power grid operation constraints, thereby achieving the optimization of the power grid's carbon reduction capacity.

[0134] Example 7:

[0135] The embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid that coordinates new energy and load uncertainty, constructs a power grid carbon reduction capacity optimization evaluation index, analyzes and verifies the current power grid carbon reduction capacity optimization results, and determines the effectiveness of the power grid carbon reduction capacity optimization, including:

[0136] Determine the grid's carbon reduction capacity optimization assessment indicators based on the grid's carbon reduction needs. These indicators include: new energy installed capacity optimization assessment indicators, new energy utilization optimization assessment indicators, carbon emissions optimization assessment indicators, and grid redundancy optimization assessment indicators.

[0137] Normalize the optimization evaluation indicators of the power grid's carbon reduction capacity;

[0138] Performing subjective and objective weighting processing on the normalized grid carbon reduction capacity optimization evaluation indicators to determine the indicator weights of the normalized grid carbon reduction capacity optimization evaluation indicators;

[0139] Obtain the indicator range of the normalized grid carbon reduction capacity optimization evaluation indicator, obtain the normalized value of the current grid carbon reduction capacity optimization result in the normalized grid carbon reduction capacity optimization evaluation indicator, and the optimization ratio of the current grid carbon reduction capacity optimization result within the indicator range;

[0140] Analyze and verify the optimization results of the current grid carbon reduction capacity, and determine the current optimized value of the grid carbon reduction capacity based on the optimization ratio and indicator weights;

[0141] Among them, F represents the current optimization value of the grid's carbon reduction capacity; w1(i1,j1) represents the j1th subjective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; w2(i1,j1) represents the j1th objective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; xi1 represents the normalized value of the current grid's carbon reduction capacity optimization result in the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y1i1 represents the lower threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y2i1 represents the upper threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; n1 represents the number of indicators of the grid's carbon reduction capacity optimization evaluation index after the normalization process; m1 represents the number of subjective and objective weights of the subjective and objective weighted processing of the grid's carbon reduction capacity optimization evaluation index after the normalization process;

[0142] When the current optimized value of the grid's carbon reduction capacity is not lower than the preset optimized value, it is determined that the optimization of the grid's carbon reduction capacity is effective.

[0143] In this embodiment, the grid carbon reduction capacity optimization evaluation index refers to an index used to evaluate the optimization results of the grid carbon reduction capacity, such as the new energy installed capacity optimization evaluation index, the new energy utilization rate optimization evaluation index, the carbon emissions optimization evaluation index and the grid redundancy optimization evaluation index.

[0144] In this embodiment, the grid carbon reduction capability optimization evaluation index is normalized to unify the grid carbon reduction capability optimization evaluation index for subsequent unified analysis and processing.

[0145] In this embodiment, the subjective and objective weighting process refers to a comprehensive weighting process performed by a plurality of subjective weighting processes and a corresponding plurality of objective weighting processes.

[0146] In this embodiment, the indicator weight refers to the indicator weight of the power grid carbon reduction capacity optimization evaluation indicator completed through normalization processing determined by subjective and objective weighted processing.

[0147] In this embodiment, the normalized value refers to a value determined by normalizing the current grid carbon reduction capacity optimization result in the grid carbon reduction capacity optimization evaluation index after the normalization process is completed.

[0148] In this embodiment, the indicator range refers to the range of the power grid carbon reduction capacity optimization evaluation indicator after normalization processing.

[0149] In this embodiment, the optimization ratio refers to the ratio of the normalized value within the index range, which is used to indicate the degree of optimization. The higher the optimization ratio, the closer the normalized value is to the lower threshold of the index range, which indicates that the corresponding optimization effect is better.

[0150] In this embodiment, the current optimization value refers to analyzing and verifying the optimization results of the current power grid carbon reduction capacity, and determining the optimization value of the power grid carbon reduction capacity according to the optimization ratio and indicator weight, which is used to indicate the degree of optimization of the power grid carbon reduction capacity.

[0151] In this embodiment, the preset optimization value refers to a preset value for determining whether the optimization of the carbon reduction capacity of the power grid is effective.

[0152] The working principle and beneficial effects of the above technical solution are: by constructing an optimization evaluation index for the grid's carbon reduction capacity, analyzing and verifying the current optimization results of the grid's carbon reduction capacity, determining the effectiveness of the grid's carbon reduction capacity optimization, and realizing the optimization verification of the grid's carbon reduction capacity.

[0153] Example 8:

[0154] An embodiment of the present invention provides a method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy sources with load uncertainty, further comprising:

[0155] When it is determined that the optimization of the grid's carbon reduction capacity is effective, an operation test is performed in the actual grid based on the current grid's carbon reduction capacity optimization results and the actual grid operation status is monitored in real time.

[0156] In this embodiment, by real-time monitoring of the actual grid operation status, it is ensured that the current grid carbon reduction capacity optimization result can be used for actual grid operation.

[0157] The working principle and beneficial effects of the above technical solution are: in this embodiment, by conducting an operation test in the actual power grid and monitoring the actual power grid operation status in real time according to the current power grid carbon reduction capacity optimization results when it is determined that the power grid carbon reduction capacity optimization is effective, the effectiveness of the power grid carbon reduction capacity optimization verification is further ensured.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for optimizing and verifying the carbon reduction capacity of power grids by coordinating new energy and load uncertainty, characterized by: include: Step 1: Build a power grid model, superimpose the power grid model based on historical new energy data and historical load data, and determine the power grid new energy and load model; Step 2: Obtain current renewable energy data and current load data, coordinate the current renewable energy data and current load data according to the grid renewable energy and load model, and determine the current grid operation constraints; Step 3: Obtain the grid's carbon reduction demand and current grid carbon reduction capacity, obtain predicted new energy data and predicted load data, and optimize the current grid carbon reduction capacity based on the preset optimization algorithm and current grid operation constraints; Step 4: Construct an optimization evaluation index for the grid’s carbon reduction capacity, analyze and verify the current grid’s carbon reduction capacity optimization results, and determine the effectiveness of the grid’s carbon reduction capacity optimization.

2. The method for optimizing and verifying the carbon reduction capacity of power grids by coordinating new energy and load uncertainty according to claim 1 is characterized in that: Construct a power grid model, superimpose the model on the historical new energy data and historical load data, and determine the new energy and load models of the power grid, including: Obtaining grid components, selecting a preset grid model, and obtaining grid operation data to construct a grid model, wherein the grid components include: generator set components, transmission line components, transformer components, and load components; Obtain historical renewable energy data and historical load data, and perform a superposition modeling of the power grid model based on the historical renewable energy data and renewable energy output characteristics. The renewable energy output characteristics include: output intermittent characteristics and output random characteristics; Input historical load data into the power grid model completed by the primary superposition modeling to perform secondary superposition modeling to obtain the new energy and load model of the power grid; Randomly simulate and generate grid operation scenarios based on historical new energy data and historical load data, run the grid new energy and load models in the grid operation scenarios, and evaluate the grid operation status; When the evaluation results show that the grid operation state is stable, it is determined that the superposition modeling of the grid new energy and load models is completed.

3. The method for optimizing and verifying the carbon reduction capacity of power grids by coordinating new energy and load uncertainty according to claim 1 is characterized in that: Obtain current renewable energy data and current load data, coordinate them according to the grid renewable energy and load model, and determine the current grid operation constraints, including: Obtain current new energy data and current load data and perform data preprocessing to remove erroneous data and abnormal data in the current new energy data and current load data; Input the current new energy data and current load data after data preprocessing into the power grid new energy and load model to determine the current operating status of the power grid; determining overall grid operation constraints based on grid operation data, wherein the overall grid operation constraints include: generator set output constraints, generator set output fluctuation constraints, grid voltage constraints, grid frequency constraints, grid redundancy constraints, and grid load constraints; When the current operation state of the power grid is a stable operation state, the current new energy data and the current load data are coordinated according to the overall operation constraint conditions of the power grid, so that the current new energy data and the current load data change within the overall operation constraint conditions of the power grid; The current grid operation constraints are determined based on the overall grid operation constraints and coordination results.

4. The method for optimizing and verifying the carbon reduction capacity of a power grid by coordinating new energy with load uncertainty according to claim 3 is characterized in that: Also includes: Compare the total grid operation constraints with the current grid operation constraints, obtain the relevant constraints in the current grid operation constraints that are not less than the total grid operation constraints, and determine the optimizable items of the current grid operation.

5. The method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty according to claim 4 is characterized in that: Obtain the grid's carbon reduction needs and current grid carbon reduction capabilities, including: Obtain grid carbon reduction needs, determine grid carbon reduction indicators, and assess the current grid carbon reduction capacity. Grid carbon reduction indicators include: renewable energy installed capacity, renewable energy utilization, carbon emissions, and grid redundancy. When the assessment results show that the current grid's carbon reduction capacity is qualified, there is no need to optimize the current grid's carbon reduction capacity; When the evaluation results show that the current power grid's carbon reduction capacity is unqualified, the current power grid's carbon reduction capacity is optimized, and the current power grid's carbon reduction optimizable items are determined based on the current power grid's operation optimizable items.

6. The method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty according to claim 5 is characterized in that: Obtain forecasted new energy data and forecasted load data, and optimize the current grid's carbon reduction capacity based on preset optimization algorithms and current grid operation constraints, including: Determine the forecast time based on the grid's carbon reduction needs, input the pre-processed current renewable energy data and current load data into the grid's renewable energy and load model, and obtain forecasted renewable energy data and forecasted load data; Input historical renewable energy data and historical load data into the grid renewable energy and load model to determine the prediction error; Determine a preset optimization algorithm for optimizing the carbon reduction capacity of the current power grid from the optimization algorithms based on the power grid's renewable energy and load model and the current power grid operation constraints, wherein the optimization algorithms include: linear programming algorithm, quadratic programming algorithm, nonlinear programming algorithm, and stochastic programming algorithm; The current power grid carbon reduction capacity is optimized based on the preset optimization algorithm, predicted new energy data and predicted load data, prediction error, current power grid carbon reduction optimizable items and current power grid operation constraints.

7. The method for optimizing and verifying the carbon reduction capacity of power grids coordinated with new energy and load uncertainty according to claim 1 is characterized in that: Construct an optimization evaluation index for the grid's carbon reduction capacity, analyze and verify the current grid's carbon reduction capacity optimization results, and determine the effectiveness of the grid's carbon reduction capacity optimization, including: Determine the grid's carbon reduction capacity optimization assessment indicators based on the grid's carbon reduction needs. These indicators include: new energy installed capacity optimization assessment indicators, new energy utilization optimization assessment indicators, carbon emissions optimization assessment indicators, and grid redundancy optimization assessment indicators. Normalize the optimization evaluation indicators of the power grid's carbon reduction capacity; Performing subjective and objective weighting processing on the normalized grid carbon reduction capacity optimization evaluation indicators to determine the indicator weights of the normalized grid carbon reduction capacity optimization evaluation indicators; Obtain the indicator range of the normalized grid carbon reduction capacity optimization evaluation indicator, obtain the normalized value of the current grid carbon reduction capacity optimization result in the normalized grid carbon reduction capacity optimization evaluation indicator, and the optimization ratio of the current grid carbon reduction capacity optimization result within the indicator range; Analyze and verify the optimization results of the current grid carbon reduction capacity, and determine the current optimized value of the grid carbon reduction capacity based on the optimization ratio and indicator weights; Among them, F represents the current optimization value of the grid's carbon reduction capacity; w1(i1,j1) represents the j1th subjective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; w2(i1,j1) represents the j1th objective weight of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; xi1 represents the normalized value of the current grid's carbon reduction capacity optimization result in the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y1i1 represents the lower threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; y2i1 represents the upper threshold of the indicator range of the grid's carbon reduction capacity optimization evaluation index after the i1th normalization process; n1 represents the number of indicators of the grid's carbon reduction capacity optimization evaluation index after the normalization process; m1 represents the number of subjective and objective weights of the subjective and objective weighted processing of the grid's carbon reduction capacity optimization evaluation index after the normalization process; When the current optimized value of the grid's carbon reduction capacity is not lower than the preset optimized value, it is determined that the optimization of the grid's carbon reduction capacity is effective.

8. The method for optimizing and verifying the carbon reduction capacity of a power grid coordinated with new energy and load uncertainty according to claim 7 is characterized in that: Also includes: When it is determined that the optimization of the grid's carbon reduction capacity is effective, an operation test is performed in the actual grid based on the current grid's carbon reduction capacity optimization results and the actual grid operation status is monitored in real time.

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