Regional power development planning evaluation method based on multilevel fuzzy comprehensive evaluation

Abstract

The invention relates to a regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation, and the method comprises the steps: collecting the power development planning data of a target region; then constructing a plurality of hierarchical indexes according to the power development planning data, allocating weights to the hierarchical indexes, calculating numerical values of the indexes, dividing evaluation grades according to the numerical values, and setting fuzzy values; and constructing a fuzzy evaluation matrix of each level index according to the fuzzy values, finally calculating a fuzzy comprehensive evaluation vector of the plurality of level indexes according to the fuzzy evaluation matrix, and calculating a comprehensive evaluation score according to the fuzzy comprehensive evaluation vector to evaluate regional power development planning. According to the method, global evaluation optimization is carried out from the perspective of comprehensively considering multiple factors, and all aspects of the power system are comprehensively evaluated by constructing a multi-level fuzzy comprehensive evaluation model.

Description

Technical Field

[0001] The invention relates to a regional electric power development planning evaluation method based on multi-level fuzzy comprehensive evaluation, belonging to the technical field of electric power development planning evaluation. Background Art

[0002] The existing evaluation methods for power development planning are guided by a single goal, such as reducing power consumption, improving the capacity for new energy consumption, or optimizing power dispatch, and lack comprehensive consideration of the overall high-quality development of energy and power in the target area. This single-goal-oriented optimization strategy is often difficult to take into account multiple needs in practical applications, resulting in unsatisfactory optimization results.

[0003] Taking the Yangtze River Delta region as an example, although the Yangtze River Delta regional energy integration development plan has promoted the optimal allocation of regional power resources to a certain extent, the existing technical solutions are difficult to comprehensively evaluate the development plan in actual implementation, which leads to insufficient regional coordination, waste of resources and imbalance between supply and demand. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a multi-objective comprehensive evaluation method for power development planning taking into account multiple requirements.

[0005] In order to achieve the above object, the technical solution proposed by the present invention is: a regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation, comprising the following steps:

[0006] Collect the power development planning data of the target area; construct multiple levels of indicators based on the power development planning data, and assign weights w to each level of indicators i ; Calculate the value of each indicator and divide the evaluation level according to the value, and set the fuzzy value; construct the fuzzy evaluation matrix R of each level indicator according to the fuzzy value i ; According to the fuzzy evaluation matrix R i Calculate the fuzzy comprehensive evaluation vector B of multiple level indicators i =W·R i ; Where W is the weight vector, W = (w 1 ,w 2 ,w 3 ,w 4 …w i );

[0007] According to the fuzzy comprehensive evaluation vector B i Calculate the comprehensive evaluation score Used to evaluate regional power development plans.

[0008] The further design of the above technical solution is as follows: each level indicator contains at least one sub-indicator, the evaluation level is divided according to the sub-indicator value, and the fuzzy value is set.

[0009] The hierarchical indicators include power supply security, new energy consumption and resource allocation efficiency.

[0010] The power supply guarantee includes two sub-indicators: peak power guarantee rate and load gap rate;

[0011] The peak power consumption guarantee rate is:

[0012]

[0013] The load notch rate is:

[0014]

[0015] Among them, C max is the maximum supply capacity of the power grid, D peak is the peak load demand.

[0016] The peak power consumption guarantee rate is divided into levels according to a threshold value of 90%, a fuzzy value of "1" is set above the threshold, and a fuzzy value of "0" is set below the threshold;

[0017] The load gap is graded according to a 5% standard, with a fuzzy value of "1" being set below 5% and a fuzzy value of "0" being set above 5%.

[0018] The new energy absorption capacity includes two sub-indicators: wind and solar power abandonment rate and new energy utilization rate;

[0019] The wind and solar power abandonment rates are:

[0020]

[0021] The utilization rate of new energy is:

[0022]

[0023] Among them, E curtailment E is the amount of wind and solar power abandoned, renewable The total amount of electricity generated by renewable energy.

[0024] The wind and solar power abandonment rates are set to evaluation levels of less than 10%, 10%-20%, 20%-30% and greater than 30%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively;

[0025] The new energy utilization rate is set to evaluation levels higher than 80%, 60%-80%, 40%-60% and lower than 40%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively.

[0026] The resource allocation includes two sub-indicators: efficiency inter-provincial power transmission ratio and regional power self-sufficiency rate;

[0027] The inter-provincial power transmission ratio is:

[0028]

[0029] The regional electricity self-sufficiency rate is:

[0030]

[0031] Among them, E transmission To transmit electricity across provinces, E total is the total power generation, E self supply It is the electricity generated and used within the province.

[0032] The inter-provincial power transmission ratio is set to evaluation levels higher than 30%, 20%-30%, 10%-20% and lower than 10%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively.

[0033] The regional electricity self-sufficiency rate is set to evaluation levels greater than 80%, 60%-80%, 40%-60% and less than 40%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively.

[0034] The weights for power supply security, new energy consumption, and resource allocation efficiency are set at 0.4, 0.3, and 0.3 respectively.

[0035] The beneficial effects of the present invention are:

[0036] The present invention is different from the existing single-goal-oriented power development planning evaluation method. The present invention performs global evaluation optimization from the perspective of comprehensive consideration of multiple factors. By constructing a multi-level fuzzy comprehensive evaluation model, it comprehensively evaluates all aspects of the power system and generates comprehensive evaluation results. Based on the evaluation results, targeted optimization strategies are formulated, including power supply guarantee measures, new energy consumption plans, resource allocation optimization plans, etc., so as to achieve the goal of improving the overall coordination and high-quality development of the power system.

[0037] The present invention uses a multi-level fuzzy comprehensive evaluation method to more comprehensively evaluate the stability of the power system and propose corresponding optimization measures. This method provides a new perspective and an effective tool for comprehensive evaluation and forward-looking analysis of the power system, which can provide a scientific basis for the planning and scheduling of the power system, and help decision makers formulate more scientific and reasonable policies and measures to ensure the long-term stable development of the power system, so as to better cope with the increasingly complex and dynamic challenges of the power system and ensure the high-quality development and stable operation of the power system.

[0038] This invention provides effective technical support and implementation path for the evaluation of power development planning. Through precise evaluation and optimization strategies, it promotes the high-quality development of regional power systems and provides a solid guarantee for the smooth implementation of national strategies. DETAILED DESCRIPTION

[0039] The present invention is described in detail below with reference to specific embodiments.

[0040] Embodiment 1

[0041] The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation in this embodiment includes the following steps:

[0042] Collect data on power development planning for energy integration in the target area, including data on power load distribution, power generation, electricity demand, and new energy absorption capacity.

[0043] Comprehensively evaluate various aspects of power development planning based on multi-level fuzzy comprehensive evaluation method;

[0044] Firstly, multiple levels of indicators are constructed based on the power development planning data, and weights W are assigned to each level of indicators;

[0045] Then calculate the value of each indicator and divide the evaluation level according to the value, and set the fuzzy value; then construct the fuzzy evaluation matrix R of each level indicator according to the fuzzy value i ; and according to the fuzzy evaluation matrix R i Calculate the fuzzy comprehensive evaluation vector B of multiple level indicators i =W·R i ;

[0046] Finally, according to the fuzzy comprehensive evaluation vector B i Calculate the comprehensive evaluation score It is used to evaluate regional power development planning. Through the fuzzy evaluation matrix, the evaluation results of each indicator are integrated to obtain the overall evaluation results of the power system and the specific scores of each indicator, so as to conduct a comprehensive evaluation of all aspects of the power system.

[0047] Embodiment 2

[0048] This embodiment is further designed on the basis of the first embodiment, specifically:

[0049] Set up an evaluation index system: Construct an evaluation index system, including indicators at multiple levels such as power supply security, new energy consumption, and resource allocation efficiency. Weights are assigned to indicators at each level based on importance and relevance.

[0050] The specific calculation formula is as follows:

[0051] The evaluation index system is: A={A1 ,A 2 ,A 3 ,A 4 …A i}

[0052] The evaluation level is: B = {B 1 ,B 2 ,B 3 ,B 4 ,B 5 …B i}

[0053] The weight vector is: W = (w 1 ,w 2 ,w 3 ,w 4 …w i ).

[0054] Fuzzy evaluation matrix: Establish a fuzzy evaluation matrix to conduct fuzzy comprehensive evaluation on indicators at all levels. Through fuzzy matrix operations, comprehensive evaluation results are obtained to provide a basis for the diagnosis of power system problems.

[0055] The fuzzy evaluation matrix is:

[0056] Fuzzy comprehensive operation: The fuzzy comprehensive operation method is used to obtain the comprehensive score of each indicator and the overall evaluation result.

[0057] The fuzzy comprehensive evaluation vector is:

[0058] The comprehensive evaluation score is:

[0059] Among them, i is the indicator number, m is the sub-indicator number, r im It is the fuzzy value of the corresponding sub-indicator.

[0060] In this embodiment, the multi-level evaluation index is specifically set to include three main aspects: power supply guarantee (A 1 ), new energy consumption capacity (A 2 ), and resource allocation efficiency (A 3 ), the sub-indicators and calculation formulas of each evaluation indicator are as follows:

[0061] 1. Power supply security (A 1 )

[0062] Peak power consumption guarantee rate: Calculate the ratio of peak load to grid supply capacity. The formula is:

[0063]

[0064] Among them, Cmax is the maximum supply capacity of the power grid, D peak The peak load demand is the peak load demand. The peak power guarantee rate is divided into levels according to the 90% threshold. The fuzzy value is set to "1" when it is higher than the threshold, and the fuzzy value is set to "0" when it is lower than the threshold.

[0065] Load gap rate: measures the shortage of the power grid during peak load period, the formula is:

[0066]

[0067] The evaluation level is divided according to the proportion of the load gap. The load gap is divided into levels according to the 5% standard. If it is lower than 5%, the fuzzy value is set to "1" and if it is higher than 5%, the fuzzy value is set to "0".

[0068] 2. New energy consumption capacity (A 2 )

[0069] Abandonment rate of wind and solar power: It indicates the waste rate of renewable energy power generation due to insufficient grid absorption capacity. The calculation formula is:

[0070]

[0071] Among them, E curtailment E is the amount of wind and solar power abandoned, renewable is the total amount of renewable energy power generation. If the wind and solar power abandonment rate is less than 10%, it is evaluated as "excellent"; 10%-20% is "good"; 20%-30% is "average"; greater than 30% is "poor", and the fuzzy values ​​are set as 1.0, 0.8, 0.5 and 0.2 respectively;

[0072] New energy utilization rate: Calculate the ratio of actual power generation to theoretical power generation of new energy installed capacity that has been connected to the grid:

[0073]

[0074] A utilization rate above 80% is “excellent”, 60%-80% is “good”, 40%-60% is “fair”, and below 40% is “poor”, and the fuzzy values ​​are set to 1.0, 0.8, 0.5, and 0.2 respectively.

[0075] 3. Resource allocation efficiency (A 3 )

[0076] Inter-provincial power transmission ratio: reflects the inter-provincial flow of power resources in the Yangtze River Delta region. The calculation formula is:

[0077]

[0078] Among them, E transmission To transmit electricity across provinces, E totalIf the inter-provincial power transmission ratio is higher than 30%, it is evaluated as "excellent"; 20%-30% is "good"; 10%-20% is "average"; and below 10% is "poor", and the fuzzy values ​​are set as 1.0, 0.8, 0.5 and 0.2 respectively.

[0079] Regional power self-sufficiency rate: Calculate the power self-sufficiency rate of a province using the formula:

[0080]

[0081] Among them, E self supply The self-generated and self-used electricity in the province. A self-sufficiency rate greater than 80% is "excellent", 60%-80% is "good", 40%-60% is "average", and less than 40% is "poor", and the fuzzy values ​​are set as 1.0, 0.8, 0.5, and 0.2 respectively.

[0082] In this embodiment, weights are allocated according to the importance of indicators. Specifically, the weights of power supply guarantee, new energy consumption, and resource allocation efficiency are w and w respectively. 1 =0.4,w 2 =0.3,w 3 =0.3.

[0083] According to the actual data performance of the indicators, the fuzzy value of the evaluation level is set, and the fuzzy evaluation matrix R is constructed, for example:

[0084]

[0085] The fuzzy evaluation vector is used to calculate the weighted score of each indicator, that is, the fuzzy comprehensive evaluation vector B, and the comprehensive evaluation score S is calculated.

[0086] Through the above steps, the comprehensive evaluation results of high-quality power development in the target area can be obtained, providing a basis for further optimization strategies.

[0087] In the multi-level fuzzy comprehensive evaluation method of this embodiment, the identification of weak links and problems depends on the decomposition and analysis of a single evaluation index. By comparing the comprehensive evaluation results with the single index, the specific weak links can be determined.

[0088] Weak link identification criteria: When a single indicator B i When the score is lower than a certain threshold (for example, lower than 0.5), for each evaluation indicator A i , if B i ≤0.5, it means that the indicator is a weak link and needs to be optimized as a priority.

[0089] The method of this embodiment combines the index score division and the evaluation level, and realizes the identification of the weak links of the power system through clear threshold setting.

[0090] According to the identification results of weak links, targeted optimization strategies are formulated, including power supply guarantee measures, new energy consumption plans, resource allocation optimization plans, etc.

[0091] Application Examples

[0092] In order to verify the effectiveness of the multi-level fuzzy comprehensive evaluation method proposed in this patent, this example applies the above method to the development plan of the power system in the Yangtze River Delta region, and verifies and analyzes the evaluation results of the model.

[0093] The actual power load data, new energy power generation data and power supply data of the Yangtze River Delta region were collected to verify the model. The specific data are shown in Tables 1, 2 and 3.

[0094] Table 1 Power supply security data in the Yangtze River Delta region

[0095]

[0096] Table 2 Data on the new energy consumption capacity in the Yangtze River Delta region

[0097]

[0098]

[0099] Table 3 Data on resource allocation efficiency in the Yangtze River Delta region

[0100]

[0101] By comparing the model prediction results and actual data, the accuracy and reliability of the model can be verified.

[0102] This embodiment uses the multi-level fuzzy evaluation method of the above-mentioned embodiment 2 to conduct a detailed analysis of the model evaluation results and identify the key factors affecting power development; the evaluation results are shown in Table 4.

[0103] Table 4 The scores of various indicators and comprehensive scores in the Yangtze River Delta region in each year

[0104]

[0105] Judging from the comprehensive evaluation results, the power supply guarantee of the power system in the Yangtze River Delta region during peak load periods is relatively sufficient, but there is still room for improvement in the consumption of new energy and inter-provincial power dispatching. With the increase in the installed capacity of new energy, the abandonment rate of wind and solar power has increased, resulting in a decrease in the utilization rate of new energy, indicating the need to further improve energy storage capacity or optimize the dispatching strategy. At the same time, the proportion of inter-provincial power transmission is low, and it is recommended to strengthen the coordinated sharing of power resources between regions to achieve more efficient allocation of power resources. Overall, the overall health level of the power system has fluctuated, and targeted optimization is needed in the consumption of new energy and regional power dispatching.

[0106] Through practical application and model verification, the effectiveness and applicability of the multi-level fuzzy comprehensive evaluation method proposed in this patent in the planning and scheduling of high-quality power development in the Yangtze River Delta region have been verified.

[0107] The method of the present invention can more comprehensively evaluate the stability of the power system through a multi-level fuzzy comprehensive evaluation method and propose corresponding optimization measures. The optimization strategy includes power supply guarantee measures, new energy consumption schemes and resource allocation optimization schemes. The implementation of these measures will effectively reduce the operation risk of the power grid and improve the stability and reliability of the system.

[0108] The technical solutions of the present invention are not limited to the above-mentioned embodiments, and any technical solutions obtained by equivalent replacement methods fall within the scope of protection required by the present invention.

Claims

1. A regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation, characterized in that: The steps include: collecting power development planning data for the target area; According to the power development planning data, multiple levels of indicators are constructed, and weights w are assigned to each level of indicators. i ; Calculate the value of each indicator and divide the evaluation level according to the value, and set the fuzzy value; Construct the fuzzy evaluation matrix R of each level index according to the fuzzy value i ; According to the fuzzy evaluation matrix R i Calculate the fuzzy comprehensive evaluation vector B of multiple level indicators i =W·R i ; Where W is the weight vector, W = (w1,w2,w3,w4…w i ); According to the fuzzy comprehensive evaluation vector B i Calculate the comprehensive evaluation score Used to evaluate regional power development plans.

2. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 1 is characterized by: Each level indicator contains at least one sub-indicator. The evaluation level is divided according to the value of the sub-indicator and a fuzzy value is set.

3. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 2 is characterized by: The hierarchical indicators include power supply security, new energy consumption and resource allocation efficiency.

4. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 2 is characterized by: The power supply guarantee includes two sub-indicators: peak power guarantee rate and load gap rate; The peak power consumption guarantee rate is: The load notch rate is: Among them, C max is the maximum supply capacity of the power grid, D peak is the peak load demand.

5. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 4 is characterized by: The peak power consumption guarantee rate is divided into levels according to a threshold value of 90%, a fuzzy value of "1" is set above the threshold, and a fuzzy value of "0" is set below the threshold; The load gap is graded according to a 5% standard, with a fuzzy value of "1" being set below 5% and a fuzzy value of "0" being set above 5%.

6. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 5 is characterized by: The new energy absorption capacity includes two sub-indicators: wind and solar power abandonment rate and new energy utilization rate; The wind and solar power abandonment rates are: The utilization rate of new energy is: Among them, E curtailment E is the amount of wind and solar power abandoned, renewable The total amount of electricity generated by renewable energy.

7. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 6 is characterized by: The wind and solar power abandonment rates are set to evaluation levels of less than 10%, 10%-20%, 20%-30% and greater than 30%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively; The new energy utilization rate is set to evaluation levels higher than 80%, 60%-80%, 40%-60% and lower than 40%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively.

8. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 7 is characterized by: The resource allocation includes two sub-indicators: efficiency inter-provincial power transmission ratio and regional power self-sufficiency rate; The inter-provincial power transmission ratio is: The regional electricity self-sufficiency rate is: Among them, E transmission To transmit electricity across provinces, E total is the total power generation, E selfsupply It is the electricity generated and used within the province.

9. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 8 is characterized by: The inter-provincial power transmission ratio is set to evaluation levels higher than 30%, 20%-30%, 10%-20% and lower than 10%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively. The regional electricity self-sufficiency rate is set to evaluation levels greater than 80%, 60%-80%, 40%-60% and less than 40%, and fuzzy values ​​are set to 1.0, 0.8, 0.5 and 0.2 respectively.

10. The regional power development planning evaluation method based on multi-level fuzzy comprehensive evaluation according to claim 9 is characterized by: The weights for power supply security, new energy consumption, and resource allocation efficiency are set to 0.4, 0.3, and 0.3 respectively.

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