A big data-based power spot market dispatch operation evaluation system

Abstract

The application relates to the technical field of power spot market, in particular to a power spot market dispatching operation evaluation system based on big data. The system comprises a historical database, a data acquisition module, a data processing module, a pre-warning analysis module and a warning module. The application can timely identify abnormal conditions in market operation by real-time monitoring and analyzing the power supply-demand matching degree, thereby optimizing power dispatching and improving the overall operation efficiency of the market. Through real-time data analysis and pre-warning functions, the preset influence factors and dispatching balance operation indexes are dynamically adjusted by analyzing real-time fluctuation transaction volume and allowable fluctuation transaction volume, so that the flexibility and adaptability of the power market are ensured. Through integration and analysis of historical data and real-time data, the power resource configuration is optimized by analyzing the power demand change rate, so that the power supply stability under different demand conditions is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity spot market, and in particular to an electricity 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 dispatching 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 dispatching and operation evaluation, and thus improve management efficiency. Summary of the Invention

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

[0005] To achieve the above objectives, the present invention provides a big data-based electricity 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 acquisition module is 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, connected to the historical database and the data acquisition module, respectively, for determining a corresponding fuzzy dispatch operation index based on real-time power demand, historical power demand, and a dispatch equilibrium operation index, and for determining a real-time impact factor based on a transaction volume change curve, and determining a real-time supply and demand matching degree based on the fuzzy dispatch operation index and the real-time impact factor;

[0009] The data processing module is configured to draw a transaction volume change curve based on historical transaction volumes, determine the operational fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operational 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 connected to the data processing module, the early warning analysis module being used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and to issue an early warning prompt indication to the warning module when the real-time supply and demand matching degree is less than the standard supply and demand matching degree;

[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 and demand matching degree with the standard supply and 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 and demand matching degree is less than the standard supply and demand matching degree, it is determined that the operation of the power 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 trading 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 of the real-time fluctuating trading volume and the allowed fluctuating trading 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 operating 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 equilibrium operation index based on the operation fluctuation situation and operation fluctuation trend of the power market.

[0021] Furthermore, the trading volume analysis unit is used to calculate the real-time fluctuating trading volume based on the historical trading volume and the current trading volume, and to determine the real-time fluctuating trading volume based on the allowed fluctuating trading 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 the real-time impact factor;

[0023] 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 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 changes over time. 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 fluctuations of the power market based on the real-time trading volume fluctuation intensity.

[0026] Furthermore, the fluctuation intensity analysis unit obtains the number of monitoring nodes that do not fall within 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 within 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 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.

[0029] Furthermore, the scheduling 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 and 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 configured to, when determining that the operational fluctuation trend of the power market is increasing, determine the actual power generation deviation based on the real-time transaction volume fluctuation intensity and the power generation forecast deviation, 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 a 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, 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; 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, and 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 scheduling operation index at any monitoring node according to the real-time power demand, the historical power demand and the scheduling balance operation index, or according to the real-time power demand, the historical power demand and the revised scheduling 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 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 calculation 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 existing technology, the beneficial effect of the present invention is that it optimizes power dispatching and improves the overall operation efficiency of the market by real-time monitoring and analysis of the degree of power supply and demand matching, and timely identifying abnormal situations in market operation. 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 power supply shortages or surpluses. Through analysis of real-time fluctuating trading volume and 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 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.

[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 matching is good and 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 the 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 trading volume is large, that is, the fluctuation is abnormal. In this case, the preset impact factor is adjusted to be smaller 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 large degree of disturbance on the current electricity spot market dispatch operation. 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 schematic diagram of the structure of a big data-based electricity spot market dispatching and operation evaluation system 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 Schematic diagram of the structure of the 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 merely used to explain the present invention and are not intended 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 scope of protection 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 accompanying drawings. This is only 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] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0053] See also Figure 1 As shown, it is a structural 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, comprising:

[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 acquisition module is 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, connected to the historical database and the data acquisition module, respectively, for determining a corresponding fuzzy dispatch operation index based on real-time power demand, historical power demand, and a dispatch equilibrium operation index, and for determining a real-time impact factor based on a transaction volume change curve, and determining a real-time supply and demand matching degree based on the fuzzy dispatch operation index and the real-time impact factor;

[0057] The data processing module is configured to draw a transaction volume change curve based on historical transaction volumes, determine the operational fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operational 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 connected to the data processing module, the early warning analysis module being used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and to issue an early warning prompt indication to the warning module when the real-time supply and demand matching degree is less than the standard supply and demand matching degree;

[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] The power spot market dispatch operation evaluation system in the embodiment first relies on a historical database for storing historical power data of the power market, laying a foundation for subsequent analysis, by relying on an existing big data platform. Real-time power data, including real-time power demand, is collected by the system at each monitoring node through a data collection module. These real-time data are combined with historical data to form a comprehensive data set. A fuzzy dispatch operation index is calculated by a data processing module using real-time power demand and historical power demand. The real-time supply-demand matching degree is determined according to the index and real-time influence factors. This process relies on the computing power of the big data platform to quickly process large amounts of data and on the real-time data processing capability of the big data platform to ensure the timeliness and accuracy of the early warning. Since power demand is dynamically changing in actual operation, deviation between real-time power demand and historical power demand is inevitable. By analyzing this deviation, not only can abnormal situations in market operation be identified, but also the real-time supply-demand matching degree of the current power market can be calculated by combining the real-time influence factor representing the anti-interference degree of the supply-demand relationship, making the supply-demand matching situation of the final analysis and judgment more accurate. When the real-time supply-demand matching degree is lower than the standard level, the warning module will issue a warning prompt to help relevant personnel take prompt measures to prevent power supply shortages. The system draws transaction volume change curves to analyze the running fluctuation of the power market based on these curves. This visual method can intuitively display market dynamic data. The real-time supply-demand matching degree is calculated by combining the fuzzy dispatch operation index and the real-time influence factor to accurately evaluate the current market environment. According to the dispatch operation situation of the actual power spot market, the preset influence factor is adaptively adjusted to accurately output evaluation results to maintain the stability of power supply when facing environmental changes such as weather changes and equipment failures. By integrating and analyzing 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 for dynamic monitoring and analysis, market abnormalities can be identified in a timely manner, power dispatch can be optimized, and the overall operation efficiency of the market can be 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 node is a time node.

[0061] By real-time monitoring and analysis of the degree of matching between electricity supply and demand, 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 quick measures to prevent insufficient or excessive power supply. 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. By integrating and analyzing historical data and real-time data, and analyzing 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.

[0062] See Figure 2 As shown, it is a structural diagram 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 and demand matching degree with the standard supply and 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 lower than the standard supply-demand matching degree, the operation of the power market is judged to be abnormal, and an early warning prompt is issued by the warning module;

[0067] If the real-time supply and demand matching degree is greater than or equal to the standard supply and 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] In this embodiment, the standard supply and demand matching degree is the matching degree between the actual power supply and demand in the power market within a specific time period. The setting value of the standard supply and demand matching degree is affected by the actual power supply situation. The more power that can be supplied, the looser the supply and demand matching requirements are, that is, the smaller the setting value of the standard supply and demand matching degree is. Generally, it is set between 0.5-0.95 and is adjusted according to the changes in actual power demand. For example, during peak demand periods, the standard supply and 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 matching is good, the power supply can meet the demand, and the warning module does not issue an early 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 an early warning prompt through the warning module to remind relevant personnel to take timely measures to prevent insufficient power supply, thereby ensuring the stability and reliability of the power supply.

[0070] See Figure 3 , which 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 trading 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 of the real-time fluctuating trading volume and the allowed fluctuating trading 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 operating 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 trading volume analysis unit is used to calculate the real-time fluctuating trading volume based on the historical trading volume and the current trading volume, and to determine the real-time fluctuating trading volume based on the allowed fluctuating trading 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 the 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 modified and will be output as the real-time impact factor;

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

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

[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 showing the change of real-time fluctuation trading volume 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 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 1 and the difference between the part of the real-time trading volume fluctuation intensity that exceeds the standard trading volume fluctuation intensity and the percentage of 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 at 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 scheduling 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 situation is abnormal. In this case, the preset impact factor is adjusted to be smaller 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 large degree of disturbance on the current electricity spot market scheduling operation. 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 scheduling operation.

[0088] Specifically, the scheduling 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, and 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 power market operation fluctuation trend 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 scheduling balance operation index to accurately assess the current market fluctuations in order to more flexibly respond 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 in the market is relatively sufficient. Even under the influence of environmental factors such as weather changes and equipment failures, the power dispatching 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 scheduling operation of the electricity spot market.

[0093] See Figure 4, which is a schematic structural diagram of a 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, 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; 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, and 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 set 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 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 scheduling balance operation index is adjusted down 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 scheduling operation index at any monitoring node according to the real-time power demand, the historical power demand and the scheduling balance operation index, or according to the real-time power demand, the historical power demand and the revised scheduling 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 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 the historical electricity spot market dispatching operation evaluation system accurately monitors the historical electricity demand in the historical monitoring nodes to the total number of 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 operation. It is generally set to 1, indicating that the default environmental factors have no interference with the electricity spot market dispatching operation. If the disturbance of environmental factors to the dispatching operation is unavoidable in the electricity spot market dispatching link, 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 operation. 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 operation, the smaller the final calculated real-time supply and demand matching degree.

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

[0110]

[0111] Where Ds is the real-time power demand, n is the number of currently running 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 device, and the operating time coefficient is the actual operating ratio 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, which 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] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0114] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A big data-based electricity spot market dispatching and operation evaluation system, characterized by: 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 acquisition module is used to collect corresponding actual power data at each monitoring node, wherein the actual power data includes real-time power demand; The power demand is the sum of the power demands of all operating equipment within the monitoring area of ​​the power spot market. The power demand of any operating equipment is the product of the corresponding operating time coefficient, usage frequency, and maximum power. a data processing module, connected to the historical database and the data acquisition module, respectively, for determining a corresponding fuzzy dispatch operation index based on real-time power demand, historical power demand, and a dispatch equilibrium operation index, and for determining a real-time impact factor based on a transaction volume change curve, and determining a real-time supply and demand matching degree based on the fuzzy dispatch operation index and the real-time impact factor; The data processing module is configured to draw a transaction volume change curve based on historical transaction volumes, determine the operational fluctuation trend of the power market based on the transaction volume change curve, and, when it is determined that the operational 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; The data processing module includes a first computing unit and a second computing unit; The first calculation unit is used to calculate the fuzzy scheduling operation index at any monitoring node according to the real-time power demand, the historical power demand and the scheduling balance operation index, or according to the real-time power demand, the historical power demand and the revised scheduling balance operation index; 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; The fuzzy dispatch operation index is the product of the dispatch equilibrium operation index and the adjustment step size, or the fuzzy dispatch operation index is the product of the modified dispatch equilibrium operation index and the adjustment step size, and the adjustment step size is the difference between 1 and the percentage of the portion of the real-time power demand that exceeds the historical power demand in the real-time power demand; The real-time supply-demand matching degree is the sum of the fuzzy scheduling operation index and the real-time impact factor; the real-time impact factor is the product of the preset impact factor and the correction step length; an early warning analysis module connected to the data processing module, the early warning analysis module being used to compare the real-time supply and demand matching degree with the standard supply and demand matching degree, and to issue an early warning prompt indication to the warning module when the real-time supply and demand matching degree is less than the standard supply and demand matching degree; 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 big data-based electricity spot market dispatching and operation evaluation system 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 and demand matching degree with the standard supply and 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 and demand matching degree is less than the standard supply and demand matching degree, it is determined that the operation of the power 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 trading volume analysis unit, a fluctuation intensity analysis unit, a scheduling operation analysis unit, and a control correction unit, wherein: The trading 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 of the real-time fluctuating trading volume and the allowed fluctuating trading 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 operating 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 equilibrium 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 trading volume analysis unit is used to calculate the real-time fluctuating trading volume based on the historical trading volume and the current trading volume, and to determine the real-time fluctuating trading volume based on the allowed fluctuating trading 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 the real-time impact factor; 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 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 fluctuating trading volume changes over time. 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.

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 within 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 within 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 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.

7. The big data-based electricity spot market dispatching and operation evaluation system according to claim 6 is characterized in that: The scheduling 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 power market operation fluctuation trend 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 and 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 configured to, when determining that the operational fluctuation trend of the power market is increasing, determine the actual power generation deviation based on the real-time transaction volume fluctuation intensity and the power generation forecast deviation, 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 a modified dispatch equilibrium operation index; Among them, the correction step 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 dispatch equilibrium operation index is the product of the dispatch equilibrium operation index and the correction step; 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, and the increase in power demand is the sum of 1 and the real-time power demand change rate.

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