Power system supply scheduling method suitable for electricity selling platform

Abstract

The invention belongs to the field of power dispatching, relates to a data analysis technology, and aims to solve the problem that scientific and reasonable instant power dispatching analysis cannot be performed by combining predicted power consumption data, actual power consumption data and energy storage data in the prior art, in particular to a power system supply dispatching method suitable for an electricity selling platform. Comprising the following steps: performing periodic statistical analysis on historical reference data of a power system; performing supply prediction analysis on the power system; comparing the air temperature prediction curve with the air temperature curve of the evaluation area in the historical reference data of all the evaluation periods to obtain predicted power consumption; according to the method, the power supply state in the evaluation subarea can be regularly analyzed, the power supply state of the evaluation subarea is fed back according to a comparison result, the supply demand characteristics of the evaluation subarea are marked when the power supply state is abnormal, power dispatching analysis is carried out according to the supply demand characteristics, and the processing efficiency of supply dispatching is improved.

Claims

1. A power system supply dispatching method applicable to a power selling platform, characterized in that: It includes the following steps: Step 1: Conduct periodic statistical analysis on the historical reference data of the power system; Step 2: Conduct supply prediction analysis on the power system: After the execution quantity in the evaluation period reaches L1, generate a prediction period with the same duration as the evaluation period. At the start moment of the prediction period, obtain the predicted temperature data of the evaluation area in the prediction period and draw a temperature prediction curve. Compare the temperature prediction curve with the temperature curves in the historical reference data of all evaluation periods of the evaluation area to obtain the predicted power consumption; Step 3: Allocate tasks to the power generation end of the power system: Obtain the predicted power generation FD of the evaluation area in the prediction period through the formula FD = t1×YD, where YD is the value of the predicted power consumption and t1 is the proportionality coefficient; Step 4: Regularly analyze the power supply status in the evaluation area: Set several analysis time points within the prediction period. At the analysis time points, draw the actual power consumption curve from the start moment of the prediction period to the analysis time point. Starting from the starting point of the power consumption prediction curve of the evaluation area, intercept a part with the same duration as the actual power consumption curve as the power consumption comparison curve. Mark the power consumption of the power consumption comparison curve and the actual power consumption curve of the evaluation area at the analysis time point as the predicted comparison value and the actual comparison value respectively. Mark the absolute value of the difference between the predicted comparison value and the actual comparison value as the comparison deviation value. Determine whether the power supply status of the evaluation area at the analysis time point meets the requirements through the comparison deviation value. When the requirements are not met, execute Step 5; Step 5: Mark the supply demand characteristics of the evaluation area, and mark the evaluation area where the power supply does not meet the requirements as the shortage area or the surplus area; Step 6: Conduct supply scheduling analysis on the shortage area according to the supply demand characteristics.

2. A method for dispatching power system supply applicable to a power selling platform according to claim 1, characterized in that: In Step 1, the process of obtaining the historical reference data specifically includes: Divide the power supply area into several evaluation areas, generate an evaluation period. After each evaluation period ends, generate the temperature curve and the power consumption curve of the evaluation area in the evaluation period. The historical reference data of the evaluation period is composed of the temperature curve and the power consumption curve of the evaluation period.

3. A method for dispatching power system supply applicable to a power selling platform according to claim 2, characterized in that: In Step 2, the process of obtaining the predicted power consumption includes: Mark the power consumption curve in the historical reference data corresponding to the temperature curve with the highest coincidence degree with the temperature prediction curve as the power consumption prediction curve of the evaluation area in the prediction period, and generate the predicted power consumption of the evaluation area in the prediction period according to the power consumption prediction curve.

4. A method for dispatching power system supply applicable to a power selling platform according to claim 3, characterized in that: In Step 3, the specific process of setting the value of t1 includes: Obtain the ratio of the energy storage capacity of the energy storage station in the power supply area to the maximum energy storage capacity and mark it as the storage ratio CX of the energy storage station. Compare the storage ratio CX with the preset storage thresholds CXmin and CXmax: If CX ≤ CXmin, then t1 = 1.15; If CXmin < CX < CXmax, then t1 = 1.1; If CX ≥ CXmax, then t1 = 1.05; Allocate power generation tasks to each power generation station in the evaluation area according to the predicted power generation FD.

5. A method for dispatching power system supply applicable to a power selling platform according to claim 4, characterized in that: In step four, the specific process of determining whether the power supply status of the evaluation partition at the analysis time point meets the requirements includes: comparing the comparison deviation value with the preset comparison deviation threshold: if the comparison deviation value is less than the comparison deviation threshold, it is determined that the power supply status of the evaluation partition at the analysis time point meets the requirements; if the comparison deviation value is greater than or equal to the comparison deviation threshold, it is determined that the power supply status of the evaluation partition at the analysis time point does not meet the requirements.

6. A method for dispatching power system supply applicable to a power selling platform according to claim 5, characterized in that: In step five, the specific process of marking the supply and demand characteristics of the evaluation partition includes: marking the power consumption corresponding to the power consumption comparison curve and the actual power consumption curve of the evaluation partition whose power supply status does not meet the requirements as predicted comparison values ​​and actual comparison values ​​respectively, and comparing the predicted comparison value with the actual comparison value: if the predicted comparison value is less than the actual comparison value, the supply and demand characteristics of the corresponding evaluation partition are marked as insufficient supply, the corresponding evaluation partition is marked as an insufficient partition, and the difference between the actual comparison value and the predicted comparison value is marked as the supplementary value of the insufficient partition; if the predicted comparison value is greater than the actual comparison value, the supply and demand characteristics of the corresponding evaluation partition are marked as excessive supply, the corresponding evaluation partition is marked as an excessive partition, and the difference between the predicted comparison value and the actual comparison value is marked as the saturation value of the excessive partition.

7. A method for dispatching power system supply applicable to a power selling platform according to claim 6, characterized in that: In step six, the specific process of supply scheduling analysis for the insufficient partitions includes: sorting the insufficient partitions in descending order according to the supplementary value values ​​to obtain a insufficient sequence, selecting the first insufficient partition in the insufficient sequence and marking it as the analysis object, and obtaining the matching coefficient PP of all excess partitions relative to the analysis object; arranging the excess partitions in descending order according to the matching coefficient PP values ​​to obtain an excess sequence, and then marking the first-ranked excess partition in the excess sequence as a matching partition and determining whether the matching is completed: if the sum of the saturation values ​​of all matching partitions is greater than or equal to the saturation value of the excess partition, then determining that the matching is completed; otherwise, determining that the matching is incomplete, and marking the first and second-ranked excess partitions in the excess sequence as matching partitions at the same time, and determining again whether the matching is completed, and so on, until the matching is completed or the number of partitions marked as matching at the same time is not less than L2, and if the matching is completed, the second-ranked insufficient partition in the insufficient sequence is selected for scheduling matching; when the number of partitions marked as matching at the same time is not less than L2, the scheduling matching of the analysis object is completed, and the energy storage station directly performs power scheduling and supply for the analysis object.

8. A method for dispatching power system supply applicable to a power selling platform according to claim 7, characterized in that: The process of obtaining the matching coefficient PP of the excess partition relative to the analysis object includes: obtaining the straight-line data ZJ and saturation data BH of the excess partition, the straight-line data ZJ is the straight-line distance value between the center position of the excess partition and the center position of the analysis object, and the saturation data BH is the saturation value of the excess partition; the matching coefficient PP of the excess partition relative to the analysis object is obtained by the formula PP=k1×BH-k2×ZJ, wherein k1 and k2 are both proportional coefficients, and k1>k2>1.

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