Electric power spot market scheduling operation evaluation system based on big data

Abstract

The invention relates to the technical field of electric power spot markets, in particular to an electric power spot market scheduling operation evaluation system based on big data. The system comprises a historical database, a data acquisition module, a data processing module, an early warning analysis module and a warning module. The power supply and demand matching degree is monitored and analyzed in real time, abnormal conditions in market operation are recognized in time, power dispatching is optimized, the overall operation efficiency of the market is improved, and through the real-time data analysis and early warning functions, the real-time fluctuation transaction volume and the allowable fluctuation transaction volume are analyzed, so that the power dispatching efficiency is improved. According to the method, the preset influence factor and the scheduling balance operation index are dynamically adjusted, the flexibility and adaptability of the power market are ensured, and the power supply stability under different demand conditions is ensured by integrating and analyzing historical data and real-time data and analyzing the power demand change rate and optimizing the configuration of power resources.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power spot market, and in particular to an electric power spot market dispatching and operation evaluation system based on big data. Background Art

[0002] With the development of the electricity spot market and the continuous growth of electricity demand, the evaluation of electricity spot market dispatch and operation has become an important issue in the power industry. At present, most monitoring methods are based on post-analysis and lack real-time performance. Therefore, it is particularly important to establish a more real-time monitoring method based on the characteristics and trends of market forces.

[0003] A Chinese patent document with publication number CN116957399A discloses a method for constructing a comprehensive indicator system for the electricity spot market, which includes the following steps: S1. Establishing an electricity spot market operation indicator system, where market operation indicators include market price indicators, market competition indicators, and market efficiency indicators; S2. Establishing an electricity spot market system operation indicator system, where system operation indicators include dispatch reliability indicators, load and new energy forecast indicators, and power grid economic indicators; S3. Preprocessing the system operation indicators in step S2 and calculating the indicator weights; S4. Establishing a comprehensive evaluation model for the electricity spot market; It can be seen that the existing electricity spot market technology lacks a method for accurately analyzing the operation fluctuations of the electricity market and predicting the operation fluctuation trends based on big data, so as to improve the accuracy of market dispatch operation and dispatch evaluation, and thus improve management efficiency. Summary of the invention

[0004] To this end, the present invention provides an electricity spot market dispatching and operation evaluation system based on big data to overcome the lack of prediction of operation fluctuation trend of the electricity market in the prior art, which leads to the inability to timely and effectively evaluate the operation and dispatching situation of the current electricity market when the actual electricity demand changes and environmental factors interfere, thereby resulting in low management efficiency.

[0005] To achieve the above-mentioned purpose, the present invention provides a big data-based power spot market dispatching and operation evaluation system, comprising:

[0006] A historical database for storing historical power data of the power market, wherein the historical power data includes historical power demand and historical transaction volume;

[0007] A data collection module, used to collect corresponding actual power data at each monitoring node, wherein the actual power data includes real-time power demand;

[0008] A data processing module, which is connected to the historical database and the data acquisition module respectively, and is used to determine the corresponding fuzzy dispatch operation index according to the real-time power demand, the historical power demand and the dispatch equilibrium operation index, and to determine the real-time impact factor based on the transaction volume change curve, and determine the real-time supply and demand matching degree according to the fuzzy dispatch operation index and the real-time impact factor;

[0009] The data processing module is used to draw a transaction volume change curve in combination with the historical transaction volume, determine the operation fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operation fluctuation trend of the power market is increasing, compare the actual power generation deviation with the reserved power generation capacity, and when the actual power generation deviation is greater than or equal to the reserved power generation capacity, reduce the dispatch equilibrium operation index;

[0010] An early warning analysis module, which is connected to the data processing module, and is used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and when the real-time supply and demand matching degree is less than the standard supply and demand matching degree, send an early warning prompt indication to the warning module;

[0011] The warning module is connected to the warning analysis module and is used to receive instructions from the warning data processing module and issue warning prompt instructions.

[0012] Furthermore, the early warning analysis module includes a comparison unit and a determination unit.

[0013] The comparison unit is used to compare the real-time supply-demand matching degree with the standard supply-demand matching degree;

[0014] The determination unit is used to determine the operation status of the power market based on the comparison result, wherein:

[0015] If the real-time supply-demand matching degree is less than the standard supply-demand matching degree, it is determined that the operation of the electricity market is abnormal.

[0016] Furthermore, the data processing module includes a trading volume analysis unit, a fluctuation intensity analysis unit, a scheduling operation analysis unit and a control correction unit, wherein:

[0017] The transaction volume analysis unit is used to determine whether to output the preset impact factor as the real-time impact factor based on the comparison result between the real-time fluctuating transaction volume and the allowed fluctuating transaction volume;

[0018] The fluctuation intensity analysis unit is used to generate a trading volume change curve based on the comparison result of the real-time fluctuating trading volume and the allowed fluctuating trading volume, and analyze the trading volume change curve to determine the operation fluctuation of the power market;

[0019] The dispatching operation analysis unit analyzes the operation fluctuation trend of the power market based on the operation fluctuation situation of the power market and the real-time power demand change rate;

[0020] The control and correction unit corrects the preset influencing factor or the dispatching balance operation index based on the operation fluctuation situation and operation fluctuation trend of the power market.

[0021] Furthermore, the transaction volume analysis unit is used to calculate the real-time fluctuating transaction volume according to the historical transaction volume and the current transaction volume, and to determine the real-time fluctuating transaction volume according to the allowed fluctuating transaction volume.

[0022] If the real-time fluctuating trading volume is greater than the allowed fluctuating trading volume, the real-time fluctuating trading volume of the next monitoring period is obtained to draw a trading volume change curve, and the preset impact factor is corrected based on the trading volume change curve to be a real-time impact factor;

[0023] Among them, the real-time fluctuating trading volume is the value obtained by subtracting the historical trading volume from the current trading volume;

[0024] If the real-time fluctuating trading volume is less than or equal to the allowed fluctuating trading volume, the preset impact factor will not be corrected and the preset impact factor will be output as the real-time impact factor.

[0025] Furthermore, the fluctuation intensity analysis unit is used to draw a curve of the real-time fluctuating trading volume change over time, and the fluctuation intensity analysis unit is also used to determine the real-time trading volume fluctuation intensity based on the trading volume change curve, and to analyze the operating fluctuation of the power market based on the real-time trading volume fluctuation intensity.

[0026] Further, the fluctuation intensity analysis unit obtains the number of monitoring nodes that do not fall into the standard fluctuation range to calculate the real-time trading volume fluctuation intensity, and compares the standard trading volume fluctuation intensity with the real-time trading volume fluctuation intensity, wherein the real-time trading volume fluctuation intensity is the percentage of the number of monitoring nodes that do not fall into the standard fluctuation range to the total number of monitoring nodes:

[0027] If the real-time transaction volume fluctuation intensity is less than or equal to the standard transaction volume fluctuation intensity, it is determined that the operation fluctuation of the power market is normal, and the real-time power demand change rate is obtained;

[0028] If the real-time transaction volume fluctuation intensity is greater than the standard transaction volume fluctuation intensity, it is determined that the operation fluctuation of the power market is abnormal.

[0029] Furthermore, the dispatching operation analysis unit analyzes the real-time power demand change rate, and if the real-time power demand change rate is greater than or equal to zero, it is determined that the operation fluctuation trend of the power market is increasing;

[0030] If the real-time electricity demand change rate is less than zero, it is determined that the operation fluctuation trend of the electricity market is tending to remain unchanged, and the preset impact factor is output as the real-time impact factor.

[0031] Furthermore, the control correction unit includes a first correction subunit and a second correction subunit, wherein:

[0032] The first correction subunit is used to correct the preset impact factor to a real-time impact factor when determining that the operation fluctuation of the power market is abnormal;

[0033] The second correction subunit is used to determine the actual power generation deviation according to the real-time transaction volume fluctuation intensity and the power generation forecast deviation when it is determined that the operation fluctuation trend of the power market is increasing, compare the actual power generation deviation with the reserved power generation capacity, and when the actual power generation deviation is greater than or equal to the reserved power generation capacity, reduce the dispatch equilibrium operation index to the modified dispatch equilibrium operation index;

[0034] Among them, the real-time impact factor is the product of the preset impact factor and the correction step size, the correction step size is the difference between 1 and the percentage of the real-time trading volume fluctuation intensity that exceeds the standard trading volume fluctuation intensity; the corrected scheduling equilibrium operation index is the product of the scheduling equilibrium operation index and the correction step size; the actual power generation deviation is the product of the power generation forecast deviation and the real-time trading volume fluctuation intensity, the power generation forecast deviation is the difference between the actual power generation and the predicted power generation, the actual power generation deviation is the difference between the actual power demand and the predicted power demand, the predicted power demand is the sum of the real-time power demand and the increase in power demand, the increase in power demand is the sum of 1 and the real-time power demand change rate.

[0035] Furthermore, the data processing module further includes a first calculation unit,

[0036] The first calculation unit is used to calculate the fuzzy dispatch operation index at any monitoring node according to the real-time power demand, the historical power demand and the dispatch balance operation index, or according to the real-time power demand, the historical power demand and the modified dispatch balance operation index;

[0037] The fuzzy dispatch operation index is the product of the dispatch equilibrium operation index and the adjustment step, or the fuzzy dispatch operation index is the product of the modified dispatch equilibrium operation index and the adjustment step, and the adjustment step is the difference between 1 and the percentage of the real-time power demand exceeding the historical power demand in the real-time power demand.

[0038] Furthermore, the data processing module further includes a second computing unit,

[0039] The second calculation unit is used to calculate the real-time supply and demand matching degree according to the fuzzy scheduling operation index and the real-time impact factor;

[0040] Among them, the real-time supply and demand matching degree is the sum of the fuzzy scheduling operation index and the real-time impact factor.

[0041] Compared with the prior art, the beneficial effect of the present invention lies in that, by real-time monitoring and analysis of the degree of matching of electricity supply and demand, abnormal situations in market operation can be identified in time, thereby optimizing power dispatching and improving the overall operation efficiency of the market; through real-time data analysis and early warning functions, the warning module issues an early warning when the real-time supply and demand matching degree is lower than the standard level, helping relevant personnel to take measures quickly to prevent insufficient or excessive electricity supply; through analysis of real-time fluctuating trading volume and allowed fluctuating trading volume, the preset influencing factors and dispatching equilibrium operation index are dynamically adjusted to ensure the flexibility and adaptability of the electricity market; through the integration and analysis of historical data and real-time data, and through the analysis of the rate of change of electricity demand, the allocation of power resources is optimized to ensure the stability of power supply under different demand conditions.

[0042] Furthermore, when it is determined that the real-time supply and demand matching degree is greater than or equal to the standard supply and demand matching degree, it means that the supply and demand match is good, the power supply can meet the demand, and the warning module does not issue a warning prompt. When the real-time supply and demand matching degree is less than the standard supply and demand matching degree, the evaluation system will determine that the operation of the power market is abnormal, and issue a warning prompt through the warning module to remind relevant personnel to take timely measures to prevent the occurrence of insufficient power supply, thereby ensuring the stability and reliability of power supply.

[0043] Furthermore, by setting the allowable fluctuating trading volume to better understand and predict the normal fluctuation range of the market, and by dynamically monitoring and adaptively adjusting the preset influencing factors, the dispatching and operation system of the power market can respond to market changes more flexibly and ensure the stability and reliability of power supply.

[0044] Furthermore, the real-time trading volume fluctuation intensity indicates the degree of fluctuation in the current electricity market. When it is determined that the real-time trading volume fluctuation intensity is less than or equal to the standard trading volume fluctuation intensity, it indicates that the market dispatch operation is stable and the trading volume fluctuation is within an acceptable range. When it is determined that the real-time trading volume fluctuation intensity is greater than the standard trading volume fluctuation intensity, it indicates that the degree of fluctuation in the trading volume is large, that is, the fluctuation is abnormal. In this case, the preset impact factor is adjusted to a smaller value so that the output real-time impact factor is smaller, indicating that the current anti-interference degree is small, that is, the environmental factors have a greater degree of disturbance on the current electricity spot market dispatch operation, and the final calculated real-time supply and demand matching degree is small, so as to better adapt to the current market fluctuations and accurately evaluate the current electricity market dispatch operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a structural diagram of a power spot market dispatching and operation evaluation system based on big data according to an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the structure of the early warning analysis module according to an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the structure of a data processing module according to an embodiment of the present invention;

[0048] Figure 4 It is a structural schematic diagram of a control and correction unit according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0051] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0052] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] See also Figure 1 As shown, it is a structural schematic diagram of an electric power spot market dispatching and operation evaluation system based on big data according to an embodiment of the present invention. The present invention provides an electric power spot market dispatching and operation evaluation system based on big data, including:

[0054] A historical database for storing historical power data of the power market, wherein the historical power data includes historical power demand and historical transaction volume;

[0055] A data collection module, used to collect corresponding actual power data at each monitoring node, wherein the actual power data includes real-time power demand;

[0056] A data processing module, which is connected to the historical database and the data acquisition module respectively, and is used to determine the corresponding fuzzy dispatch operation index according to the real-time power demand, the historical power demand and the dispatch equilibrium operation index, and to determine the real-time impact factor based on the transaction volume change curve, and determine the real-time supply and demand matching degree according to the fuzzy dispatch operation index and the real-time impact factor;

[0057] The data processing module is used to draw a transaction volume change curve in combination with the historical transaction volume, determine the operation fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operation fluctuation trend of the power market is increasing, compare the actual power generation deviation with the reserved power generation capacity, and when the actual power generation deviation is greater than or equal to the reserved power generation capacity, reduce the dispatch equilibrium operation index;

[0058] An early warning analysis module, which is connected to the data processing module, and is used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and when the real-time supply and demand matching degree is less than the standard supply and demand matching degree, send an early warning prompt indication to the warning module;

[0059] The warning module is connected to the warning analysis module and is used to receive instructions from the warning data processing module and issue warning prompt instructions.

[0060] In this embodiment, the power spot market dispatching operation evaluation system relies on the existing big data platform. First, it relies on a historical database, which is used to store the historical power data of the power market, laying the foundation for subsequent analysis. Through the data acquisition module, the system collects power data in real time at each monitoring node, including real-time power demand. These real-time data are combined with historical data to form a comprehensive data set. Through the data processing module, the fuzzy dispatching operation index is calculated using the real-time power demand and the historical power demand, and the real-time supply and demand matching degree is determined according to the index and the real-time impact factor. This process relies on the computing power of the big data platform, which can quickly process a large amount of data, and relies on the real-time data processing capability of the big data platform to ensure the timeliness and accuracy of the early warning. Since the power demand is dynamically changing in actual operation, the deviation between the real-time power demand and the historical power demand is inevitable. By analyzing this deviation, not only can the abnormal situation in the market operation be identified, but also the supply and demand matching degree of the current power market can be calculated by combining the real-time impact factor that characterizes the degree of anti-interference that affects the supply and demand relationship, so that the supply and demand matching situation of the final analysis and judgment is More accurate, that is, when the real-time supply and demand matching degree is lower than the standard level, the warning module will issue an early warning prompt to help relevant personnel take prompt measures to prevent power supply shortages; the system draws transaction volume change curves and analyzes the operating fluctuations of the power market based on these curves. This visual method can intuitively display market dynamic data. By combining the fuzzy dispatch operation index and the real-time impact factor, the real-time supply and demand matching degree is calculated to accurately evaluate the current market environment. According to the actual dispatch operation of the power spot market, the preset impact factor is adaptively adjusted. In the face of environmental changes, such as weather changes, equipment failures, etc., the evaluation results are accurately output to maintain the stability of power supply. Through the integration and analysis of historical data and real-time data, the allocation of power resources can be optimized to ensure the stability of power supply under different demand conditions; by integrating historical and real-time data, dynamic monitoring and analysis are carried out, market anomalies are identified in a timely manner, power dispatch is optimized, and the overall operating efficiency of the market is improved. The advantages of big data technology are fully utilized to ensure the flexibility and adaptability of the power market, thereby effectively responding to complex market environments; the monitoring nodes are time nodes.

[0061] By real-time monitoring and analysis of the degree of power supply and demand matching, and timely identification of abnormal situations in market operation, power dispatching can be optimized and the overall operating efficiency of the market can be improved. Through real-time data analysis and early warning functions, the warning module will issue an early warning when the real-time supply and demand matching degree is lower than the standard level, helping relevant personnel to take prompt measures to prevent power supply shortages or surpluses. By analyzing the real-time fluctuating trading volume and the allowed fluctuating trading volume, the preset influencing factors and dispatch equilibrium operation index are dynamically adjusted to ensure the flexibility and adaptability of the power market. Through the integration and analysis of historical data and real-time data, and through the analysis of the rate of change of power demand, the allocation of power resources is optimized to ensure the stability of power supply under different demand conditions.

[0062] See also Figure 2 As shown, it is a schematic diagram of the structure of the early warning analysis module according to an embodiment of the present invention;

[0063] Specifically, the early warning analysis module includes a comparison unit and a determination unit.

[0064] The comparison unit is used to compare the real-time supply-demand matching degree with the standard supply-demand matching degree;

[0065] The determination unit is used to determine the operation status of the power market based on the comparison result, wherein:

[0066] If the real-time supply-demand matching degree is less than the standard supply-demand matching degree, the operation of the power market is judged to be abnormal, and an early warning is issued by the warning module;

[0067] If the real-time supply-demand matching degree is greater than or equal to the standard supply-demand matching degree, it is determined that the operation of the power market is normal, and the warning module does not issue an early warning prompt.

[0068] The standard supply-demand matching degree in this embodiment refers to the matching degree between the actual electricity supply and demand in the electricity market within a specific time period. The setting value of the standard supply-demand matching degree is affected by the actual electricity supply situation. The more electricity that can be supplied, the looser the requirements for supply-demand matching are, that is, the smaller the setting value of the standard supply-demand matching degree is. Generally, it is set between 0.5-0.95, and is adjusted according to the changes in actual electricity demand. For example, during peak demand periods, the standard supply-demand matching degree is set higher to ensure that the market can respond to changes in demand in a timely manner.

[0069] When it is determined that the real-time supply and demand matching degree is greater than or equal to the standard supply and demand matching degree, it means that the supply and demand match is good, the power supply can meet the demand, and the warning module does not issue a warning prompt. When the real-time supply and demand matching degree is less than the standard supply and demand matching degree, the evaluation system will determine that the operation of the power market is abnormal, and issue a warning prompt through the warning module to remind relevant personnel to take timely measures to prevent the occurrence of insufficient power supply, thereby ensuring the stability and reliability of power supply.

[0070] See also Figure 3 As shown, it is a structural diagram of a data processing module according to an embodiment of the present invention;

[0071] Specifically, the data processing module includes a trading volume analysis unit, a fluctuation intensity analysis unit, a scheduling operation analysis unit, and a control correction unit, wherein:

[0072] The transaction volume analysis unit is used to determine whether to output the preset impact factor as the real-time impact factor based on the comparison result between the real-time fluctuating transaction volume and the allowed fluctuating transaction volume;

[0073] The fluctuation intensity analysis unit is used to generate a trading volume change curve based on the comparison result of the real-time fluctuating trading volume and the allowed fluctuating trading volume, and analyze the trading volume change curve to determine the operation fluctuation of the power market;

[0074] The dispatching operation analysis unit analyzes the operation fluctuation trend of the power market based on the operation fluctuation situation of the power market and the real-time power demand change rate;

[0075] The control and correction unit corrects the preset influencing factor or the dispatching equilibrium operation index based on the operation fluctuation situation and operation fluctuation trend of the power market to determine the real-time supply and demand matching degree of the current monitoring node.

[0076] Specifically, the transaction volume analysis unit is used to calculate the real-time fluctuating transaction volume according to the historical transaction volume and the current transaction volume, and to determine the real-time fluctuating transaction volume according to the allowed fluctuating transaction volume.

[0077] If the real-time fluctuating trading volume is greater than the allowed fluctuating trading volume, the real-time fluctuating trading volume of the next monitoring period is obtained to draw a trading volume change curve, and the preset impact factor is corrected based on the trading volume change curve to be a real-time impact factor;

[0078] If the real-time fluctuating trading volume is less than or equal to the allowed fluctuating trading volume, the preset impact factor will not be corrected and the preset impact factor will be output as the real-time impact factor;

[0079] Among them, the real-time fluctuating trading volume is the value obtained by subtracting the historical trading volume from the current trading volume.

[0080] The allowable fluctuating trading volume in this embodiment is related to the characteristics of the electricity spot market and historical data. Generally, the allowable fluctuating trading volume is set between 5% and 10% of the historical trading volume, and is adjusted according to the actual electricity spot market. For example, due to seasonal demand changes or special events such as weather changes, holidays, etc., it is necessary to adjust the range of the allowable fluctuating trading volume.

[0081] By setting the allowable fluctuating trading volume to better understand and predict the normal fluctuation range of the market, and by dynamically monitoring and adaptively adjusting the preset influencing factors, the dispatching and operation system of the power market can respond to market changes more flexibly and ensure the stability and reliability of power supply.

[0082] Specifically, the fluctuation intensity analysis unit is used to draw a curve of the real-time fluctuation trading volume changing over time to obtain the trading volume change curve, determine the real-time trading volume fluctuation intensity based on the trading volume change curve, and analyze the operating fluctuation of the power market based on the real-time trading volume fluctuation intensity.

[0083] Specifically, the fluctuation intensity analysis unit obtains the number of monitoring nodes that do not fall into the standard fluctuation range to calculate the real-time trading volume fluctuation intensity, and compares the standard trading volume fluctuation intensity with the real-time trading volume fluctuation intensity.

[0084] If the real-time transaction volume fluctuation intensity is less than or equal to the standard transaction volume fluctuation intensity, it is determined that the operation fluctuation of the power market is normal, and the real-time power demand change rate is obtained;

[0085] If the real-time trading volume fluctuation intensity is greater than the standard trading volume fluctuation intensity, it is determined that the operation fluctuation of the power market is abnormal;

[0086] Among them, the real-time trading volume fluctuation intensity is the percentage of the number of monitoring nodes that do not fall into the standard fluctuation range to the total number of monitoring nodes; the real-time impact factor is the product of the preset impact factor and the correction step size, and the correction step size is the difference between 1 and the percentage of the real-time trading volume fluctuation intensity that exceeds the standard trading volume fluctuation intensity to the real-time trading volume fluctuation intensity.

[0087] In this embodiment, the standard trading volume fluctuation intensity is the allowable degree of fluctuation of trading volume, that is, the percentage of monitoring nodes that do not fall into the standard fluctuation range to the total number of monitoring nodes, which is generally set to 3%-10%. The real-time trading volume fluctuation intensity indicates the degree of fluctuation of the current electricity market. When it is determined that the real-time trading volume fluctuation intensity is less than or equal to the standard trading volume fluctuation intensity, it indicates that the market dispatch operation is stable and the trading volume fluctuation is within an acceptable range. When it is determined that the real-time trading volume fluctuation intensity is greater than the standard trading volume fluctuation intensity, it indicates that the degree of fluctuation of the trading volume is large, that is, the fluctuation is abnormal. In this case, the preset impact factor is adjusted to a smaller value so that the output real-time impact factor is smaller, indicating that the current anti-interference degree is small, that is, the environmental factors have a greater degree of disturbance on the current electricity spot market dispatch operation, and the final calculated real-time supply and demand matching degree is smaller, so as to better adapt to the current market fluctuations and accurately evaluate the current electricity market dispatch operation.

[0088] Specifically, the dispatching operation analysis unit analyzes the real-time power demand change rate.

[0089] If the real-time rate of change of electricity demand is greater than or equal to zero, it is determined that the operating fluctuation trend of the electricity market is increasing, so the dispatch equilibrium operation index is adjusted down.

[0090] If the real-time power demand change rate is less than zero, it is determined that the operation fluctuation trend of the power market is tending to remain unchanged, and the preset impact factor is output as the real-time impact factor;

[0091] The real-time power demand change rate is the ratio of the difference between the real-time power demand of the current monitoring node and the next monitoring node to the interval time; the interval time is the time length between the current monitoring node and the next monitoring node;

[0092] The real-time electricity demand change rate in this embodiment represents the changing trend of electricity demand in the current electricity spot market. If the real-time electricity demand change rate is determined to be greater than or equal to zero, it means that electricity demand continues to increase and more electricity supply may be required. Therefore, it is necessary to reduce the dispatch equilibrium operation index to accurately assess the current market fluctuations so as to respond more flexibly to the increasing demand and ensure the stability of electricity supply. If the real-time electricity demand change rate is determined to be less than zero, it means that compared with historical situations, the current market fluctuations are due to reduced electricity demand, which may lead to an oversupply of electricity. In this case, the electricity available on the market is relatively sufficient. Even under the influence of environmental factors such as weather changes and equipment failures, the power dispatch system can still meet the demand. The real-time impact factor is output at the size of the preset impact factor, indicating that the default environmental factors have no interference with the dispatch operation of the electricity spot market.

[0093] See also Figure 4As shown, it is a schematic diagram of the structure of the control and correction unit according to an embodiment of the present invention;

[0094] Specifically, the control correction unit includes a first correction subunit and a second correction subunit, wherein:

[0095] The first correction subunit is used to correct the preset impact factor to a real-time impact factor when determining that the operation fluctuation of the power market is abnormal;

[0096] The second correction subunit is used to determine the actual power generation deviation according to the real-time transaction volume fluctuation intensity and the power generation forecast deviation when it is determined that the operation fluctuation trend of the power market is increasing, and compare the actual power generation deviation with the reserved power generation capacity.

[0097] When the actual power generation deviation is less than the reserved power generation capacity, the dispatch equilibrium operation index will not be corrected;

[0098] When the actual power generation deviation is greater than or equal to the reserved power generation capacity, the dispatching equilibrium operation index is reduced to the modified dispatching equilibrium operation index;

[0099] Among them, the real-time impact factor is the product of the preset impact factor and the correction step size, the correction step size is the difference between 1 and the percentage of the real-time trading volume fluctuation intensity that exceeds the standard trading volume fluctuation intensity; the modified dispatch equilibrium operation index is the product of the dispatch equilibrium operation index and the correction step size; the actual power generation deviation is the product of the power generation forecast deviation and the real-time trading volume fluctuation intensity, the power generation forecast deviation is the difference between the actual power generation and the predicted power generation, the actual power generation deviation is the difference between the actual power demand and the predicted power demand, the predicted power demand is the sum of the real-time power demand and the increase in power demand, the increase in power demand is the sum of 1 and the real-time power demand change rate;

[0100] The reserved power generation capacity set in this embodiment is the power generation capacity reserved for responding to fluctuations in the electricity market, and is set to 5% to 20% of the total power generation capacity. The specific ratio depends on the stability requirements of the power system and the degree of load fluctuation. For example, during peak load periods, the reserved capacity may need to be higher to ensure that the power demand can be met when demand surges. If the calculated actual power generation deviation is less than the reserved power generation capacity, it means that the actual power generation is higher than the predicted power generation; if the calculated actual power generation deviation is greater than or equal to the reserved power generation capacity, it means that the actual power generation is lower than the predicted power generation. In this case, the dispatch equilibrium operation index is reduced to accurately assess the current market fluctuations so as to more flexibly respond to the increasing demand and ensure the stability of power supply.

[0101] Specifically, the data processing module further includes a first computing unit,

[0102] The first calculation unit is used to calculate the fuzzy dispatch operation index at any monitoring node according to the real-time power demand, the historical power demand and the dispatch balance operation index, or according to the real-time power demand, the historical power demand and the modified dispatch balance operation index;

[0103] The fuzzy dispatch operation index is the product of the dispatch equilibrium operation index and the adjustment step, or the fuzzy dispatch operation index is the product of the modified dispatch equilibrium operation index and the adjustment step, and the adjustment step is the difference between 1 and the percentage of the real-time power demand exceeding the historical power demand in the real-time power demand.

[0104] The dispatching balanced operation index in this embodiment indicates the proportion of the number of times that the historical electricity spot market dispatching operation evaluation system accurately monitors the historical electricity demand in the historical monitoring nodes to the total historical monitoring nodes. The accurately monitored historical electricity demand indicates an accurate prediction of abnormal or normal conditions in the electricity spot market dispatching operation. The larger the dispatching balanced operation index, the more stable the spot market dispatching operation is, and the market dispatching operation meets the electricity demand. The dispatching balanced operation index is set between 0.7 and 0.9.

[0105] Specifically, the data processing module further includes a second computing unit,

[0106] The second calculation unit is used to calculate the real-time supply and demand matching degree according to the fuzzy scheduling operation index and the real-time impact factor;

[0107] Among them, the real-time supply and demand matching degree is the sum of the fuzzy scheduling operation index and the real-time impact factor.

[0108] The preset impact factor in this embodiment is affected by the stability of the actual electricity spot market dispatching and operation conditions. It is generally set to 1, indicating that the default environmental factors have no interference with the electricity spot market dispatching and operation conditions. If in the electricity spot market dispatching link, the disturbance of environmental factors to the dispatching and operation is unavoidable, then the preset impact factor can be adaptively adjusted to 0.9. The real-time impact factor represents the value obtained after correcting the preset impact factor based on the current electricity spot market dispatching and operation conditions. The smaller the calculated real-time impact factor, the smaller the degree of anti-interference, that is, the greater the degree of disturbance of environmental factors to the current electricity spot market dispatching and operation conditions, the smaller the real-time supply and demand matching degree calculated in the end.

[0109] Specifically, the real-time power demand is calculated as follows:

[0110]

[0111] Wherein, Ds is the real-time power demand, n is the number of currently operating power equipment, Hi is the operating time coefficient of the i-th equipment, Fi is the usage frequency of the i-th equipment, Pi is the maximum power of the i-th equipment, and the operating time coefficient is the actual operating proportion of the continuous operating time within the preset time.

[0112] In this embodiment, the unit of real-time power demand is MW, and the preset duration can be a few hours or a few days. It is selected according to the monitoring needs. The real-time power demand is characterized according to the number of operating devices, operating duration coefficient, usage frequency and maximum power in the monitoring area of ​​the current electricity spot market to adapt to changes in different regions. For example, there are 3 devices in the monitoring area of ​​the current electricity spot market. Device 1: maximum power is 5MW, operating duration coefficient is 0.8, and usage frequency is 2; Device 2: maximum power is 3MW, operating duration coefficient is 0.6, and usage frequency is 3; Device 3: maximum power is 4MW, operating duration coefficient is 1, and usage frequency is 1, then the calculated real-time power demand is 17.4MW.

[0113] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A power spot market dispatching and operation evaluation system based on big data, characterized in that: include, A historical database for storing historical power data of the power market, wherein the historical power data includes historical power demand and historical transaction volume; A data collection module, used to collect corresponding actual power data at each monitoring node, wherein the actual power data includes real-time power demand; A data processing module, which is connected to the historical database and the data acquisition module respectively, and is used to determine the corresponding fuzzy dispatch operation index according to the real-time power demand, the historical power demand and the dispatch equilibrium operation index, and to determine the real-time impact factor based on the transaction volume change curve, and determine the real-time supply and demand matching degree according to the fuzzy dispatch operation index and the real-time impact factor; The data processing module is used to draw a transaction volume change curve in combination with the historical transaction volume, determine the operation fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operation fluctuation trend of the power market is increasing, compare the actual power generation deviation with the reserved power generation capacity, and when the actual power generation deviation is greater than or equal to the reserved power generation capacity, reduce the dispatch equilibrium operation index; An early warning analysis module, which is connected to the data processing module, and is used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and when the real-time supply and demand matching degree is less than the standard supply and demand matching degree, send an early warning prompt indication to the warning module; The warning module is connected to the early warning analysis module and is used to receive instructions from the early warning data processing module and issue early warning prompt instructions.

2. The power spot market dispatching and operation evaluation system based on big data according to claim 1 is characterized in that: The early warning analysis module includes a comparison unit and a determination unit. The comparison unit is used to compare the real-time supply-demand matching degree with the standard supply-demand matching degree; The determination unit is used to determine the operation status of the power market based on the comparison result, wherein: If the real-time supply-demand matching degree is less than the standard supply-demand matching degree, it is determined that the operation of the electricity market is abnormal.

3. The big data-based electricity spot market dispatching and operation evaluation system according to claim 2 is characterized in that: The data processing module includes a transaction volume analysis unit, a fluctuation intensity analysis unit, a scheduling operation analysis unit and a control correction unit, wherein: The transaction volume analysis unit is used to determine whether to output the preset impact factor as the real-time impact factor based on the comparison result between the real-time fluctuating transaction volume and the allowed fluctuating transaction volume; The fluctuation intensity analysis unit is used to generate a trading volume change curve based on the comparison result of the real-time fluctuating trading volume and the allowed fluctuating trading volume, and analyze the trading volume change curve to determine the operation fluctuation of the power market; The dispatching operation analysis unit analyzes the operation fluctuation trend of the power market based on the operation fluctuation situation of the power market and the real-time power demand change rate; The control and correction unit corrects the preset influencing factor or the dispatching balance operation index based on the operation fluctuation situation and operation fluctuation trend of the power market.

4. The big data-based electricity spot market dispatching and operation evaluation system according to claim 3 is characterized in that: The transaction volume analysis unit is used to calculate the real-time fluctuating transaction volume according to the historical transaction volume and the current transaction volume, and to determine the real-time fluctuating transaction volume according to the allowed fluctuating transaction volume. If the real-time fluctuating trading volume is greater than the allowed fluctuating trading volume, the real-time fluctuating trading volume of the next monitoring period is obtained to draw a trading volume change curve, and the preset impact factor is corrected based on the trading volume change curve to be a real-time impact factor; Among them, the real-time fluctuating trading volume is the value obtained by subtracting the historical trading volume from the current trading volume; If the real-time fluctuating trading volume is less than or equal to the allowed fluctuating trading volume, the preset impact factor will not be corrected and the preset impact factor will be output as the real-time impact factor.

5. The big data-based electricity spot market dispatching and operation evaluation system according to claim 4 is characterized in that: The fluctuation intensity analysis unit is used to draw a curve of the real-time fluctuation transaction volume over time. The fluctuation intensity analysis unit is also used to determine the real-time transaction volume fluctuation intensity based on the transaction volume change curve, and to analyze the operation fluctuation of the power market based on the real-time transaction volume fluctuation intensity.

6. The big data-based electricity spot market dispatching and operation evaluation system according to claim 5 is characterized in that: The fluctuation intensity analysis unit obtains the number of monitoring nodes that do not fall into the standard fluctuation range to calculate the real-time trading volume fluctuation intensity, and compares the standard trading volume fluctuation intensity with the real-time trading volume fluctuation intensity, wherein the real-time trading volume fluctuation intensity is the percentage of the number of monitoring nodes that do not fall into the standard fluctuation range to the total number of monitoring nodes: If the real-time transaction volume fluctuation intensity is less than or equal to the standard transaction volume fluctuation intensity, it is determined that the operation fluctuation of the power market is normal, and the real-time power demand change rate is obtained; If the real-time transaction volume fluctuation intensity is greater than the standard transaction volume fluctuation intensity, it is determined that the operation fluctuation of the power market is abnormal.

7. The big data-based electricity spot market dispatching and operation evaluation system according to claim 6 is characterized in that: The dispatching operation analysis unit analyzes the real-time power demand change rate. If the real-time power demand change rate is greater than or equal to zero, it is determined that the operation fluctuation trend of the power market is increasing; If the real-time electricity demand change rate is less than zero, it is determined that the operation fluctuation trend of the electricity market is tending to remain unchanged, and the preset impact factor is output as the real-time impact factor.

8. The big data-based electricity spot market dispatching and operation evaluation system according to claim 7 is characterized in that: The control correction unit includes a first correction subunit and a second correction subunit, wherein: The first correction subunit is used to correct the preset impact factor to a real-time impact factor when determining that the operation fluctuation of the power market is abnormal; The second correction subunit is used to determine the actual power generation deviation according to the real-time transaction volume fluctuation intensity and the power generation forecast deviation when it is determined that the operation fluctuation trend of the power market is increasing, compare the actual power generation deviation with the reserved power generation capacity, and when the actual power generation deviation is greater than or equal to the reserved power generation capacity, reduce the dispatch equilibrium operation index to the modified dispatch equilibrium operation index; Among them, the real-time impact factor is the product of the preset impact factor and the correction step size, the correction step size is the difference between 1 and the percentage of the real-time trading volume fluctuation intensity that exceeds the standard trading volume fluctuation intensity; the corrected scheduling equilibrium operation index is the product of the scheduling equilibrium operation index and the correction step size; the actual power generation deviation is the product of the power generation forecast deviation and the real-time trading volume fluctuation intensity, the power generation forecast deviation is the difference between the actual power generation and the predicted power generation, the actual power generation deviation is the difference between the actual power demand and the predicted power demand, the predicted power demand is the sum of the real-time power demand and the increase in power demand, the increase in power demand is the sum of 1 and the real-time power demand change rate.

9. The big data-based electricity spot market dispatching and operation evaluation system according to claim 8 is characterized in that: The data processing module further includes a first computing unit, The first calculation unit is used to calculate the fuzzy dispatch operation index at any monitoring node according to the real-time power demand, the historical power demand and the dispatch balance operation index, or according to the real-time power demand, the historical power demand and the modified dispatch balance operation index; The fuzzy dispatch operation index is the product of the dispatch equilibrium operation index and the adjustment step, or the fuzzy dispatch operation index is the product of the modified dispatch equilibrium operation index and the adjustment step, and the adjustment step is the difference between 1 and the percentage of the real-time power demand exceeding the historical power demand in the real-time power demand.

10. The big data-based electricity spot market dispatching and operation evaluation system according to claim 9 is characterized in that: The data processing module further includes a second computing unit, The second calculation unit is used to calculate the real-time supply and demand matching degree according to the fuzzy scheduling operation index and the real-time impact factor; Among them, the real-time supply and demand matching degree is the sum of the fuzzy scheduling operation index and the real-time impact factor.

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