Monitoring system of energy storage station in electric power spot scene

Abstract

The invention, which relates to the technical field of electric power, discloses a monitoring system for an energy storage station in an electric power spot scene, comprising an electric power spot scene monitoring module, an energy storage station regulation and control module, an early warning feedback module and a storage module. The electric power spot scene monitoring module is responsible for extracting electricity price data in a real day from the Internet to construct an electricity price change curve graph, obtaining load power of a power grid and power generation power of a power supply company to construct a load power-power generation power change curve, and transmitting the data to the energy storage station regulation and control module. And the energy storage station regulation and control module analyzes the data in combination with the stored electric quantity of the battery pack, determines the charging time interval of the energy storage station and regulates and controls the energy storage station. And the early warning feedback module monitors the regulation and control execution condition in real time, and triggers early warning if a problem is found. The storage module is used for storing various data, methods and implementation steps in the system; the system can effectively improve the operation monitoring efficiency of the energy storage station in an electric power spot scene, and guarantees the stable operation of a power grid.

Description

Technical Field

[0001] The present invention belongs to the field of electric power technology, and specifically relates to a monitoring system for an energy storage station in an electricity spot market scenario. Background Art

[0002] With the advancement of power market reform, spot electricity trading has gradually become the mainstream model. In this scenario, electricity prices show significant intraday fluctuations, and the dynamic balance between grid load power and power generation power is becoming increasingly stringent.

[0003] The current energy storage station monitoring systems mainly have the following problems: most systems rely only on local sensor data and cannot obtain real-time electricity price dynamics in the electricity spot market, resulting in a disconnect between energy storage strategies and market price signals; traditional monitoring systems use fixed thresholds to judge the supply and demand status of the power grid, which is difficult to adapt to the complex and changeable electricity price-load coupling relationship in the spot market, and often result in misjudgment or delayed response; existing energy storage charging and discharging strategies are mostly based on empirical rules, and do not fully consider multi-dimensional constraints such as the grid's backup capacity and power loss, which can easily lead to waste of energy storage resources or hidden dangers to grid stability; most systems can only monitor equipment failures, and lack effective early warning measures for systemic risks such as failure to execute control instructions, affecting the efficiency of grid emergency response; based on the above content, the present invention proposes a monitoring system for energy storage stations in the electricity spot market scenario. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a monitoring system for an energy storage station in an electricity spot market scenario, which solves the problems existing in the existing technology in solving the dynamic balance between grid load power and generated power.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A monitoring system for energy storage stations in a power spot market scenario includes the following:

[0007] The electricity spot market monitoring module interacts with the internet in real time, extracting the electricity price under the actual daily electricity spot market scenario from the internet, and transmits this electricity price change curve together with the timestamps corresponding to the different electricity prices within the actual day to the energy storage station control module;

[0008] Obtain the load power of the power grid and the power generation power of the power supply company in real time, build a load power-power generation power change curve chart and transmit it to the energy storage station control module;

[0009] The energy storage station control module receives and analyzes the daily data transmitted by the electricity spot scenario monitoring module, determines the charging time interval of the energy storage station, and controls the energy storage station;

[0010] The early warning feedback module monitors the control execution of the energy storage station control module in real time. If it is found that the energy storage station fails to implement the preset control strategy, an early warning will be triggered and the early warning details will be fed back to the energy storage station operator;

[0011] The storage module stores the data obtained through analysis or calculation in any module of the system, and stores the methods and implementation steps involved in any module of the system.

[0012] As a further solution of the present invention, the specific manner in which the electricity spot scene monitoring module interacts with the Internet in real time also includes the following:

[0013] Determine the actual day, extract the electricity price within the actual day at every preset time t, and record it as the electricity price change sequence Q1, Q2, ..., Q j , where j is a counting index, indicating the number of electricity prices, and the operator adjusts the value of j based on actual needs;

[0014] Electricity price change sequence Q1,Q2,...,Q j The corresponding acquisition time is recorded as the time series t1, t2, ..., t j , where Q1 to Q j Corresponding to t1 to t j ;

[0015] A two-dimensional coordinate system is constructed with the timeline as the horizontal axis and the electricity price as the vertical axis. The electricity price change sequence is marked in chronological order. J data points are obtained and fitted with a curve to obtain the electricity price change curve S associated with the actual day. Q .

[0016] As a further solution of the present invention, the electricity spot scene monitoring module obtains the load power P in real time during the day. 负 And power generation P 发 ;

[0017] Recorded as load power series and power generation sequence in, to Corresponding in sequence to

[0018] The load power sequence and the power generation sequence both correspond to the time series one by one, that is, to Corresponding to t1 to t j , to Corresponding to t1 to t j ;

[0019] A two-dimensional coordinate system is constructed with the timeline as the horizontal axis and the power value as the vertical axis. The load power sequence and the power generation sequence are marked in the two-dimensional coordinate system, and the load power sequence and the power generation sequence are fitted with curves to obtain the load power-power generation change curve within the actual day, which is recorded as

[0020] As a further solution of the present invention, the energy storage station control module receives and analyzes the various daily data transmitted by the power spot scene monitoring module in the following specific manner:

[0021] To S Q and The values of the data in are normalized together;

[0022] Then S Q as well as Fit it into the same two-dimensional coordinate system and record it as the curve of power generation-load power-electricity price change

[0023] Construct a straight line perpendicular to the horizontal axis and parallel to the vertical axis through time point t1 on the horizontal axis of the coordinate system, recorded as the first time line L1. Copy L1 and shift it backward by time t to t2 on the horizontal axis to obtain a straight line perpendicular to the horizontal axis and parallel to the vertical axis through time point t2, recorded as the second time line L2.

[0024] Record the area of the closed region formed by L1, L2, the power generation curve, and the load power curve as the grid reserve capacity A1 associated with the time interval from time point t1 to time point t2;

[0025] The grid reserve capacity A1 is compared with the grid reserve capacity threshold A preset by the operator. 阈 Compare, if A1≥A 阈 , it is determined that the power generation power in the time interval from t1 to t2 meets the normal power supply demand and no processing is performed;

[0026] Otherwise, it is determined that the generated power in the time interval from t1 to t2 does not meet the normal power supply demand.

[0027] As a further solution of the present invention, if the energy storage station control module determines that the generated power in the time interval from t1 to t2 does not meet the normal power supply demand, L1 is copied to t3 on the horizontal axis to obtain a straight line perpendicular to the horizontal axis and parallel to the vertical axis at t3, which is recorded as the third time line L3;

[0028] Get the closed area composed of L2, L3, power generation curve and load power curve as the grid reserve capacity A2 associated with the time interval from t2 to t3. Similarly, get the area of A3 to A j-1, recorded as the grid reserve capacity sequence A1, A2, ..., A in the order of acquisition j-1 ;

[0029] If i consecutive grid reserve capacities in the grid reserve capacity sequence are all lower than the grid reserve capacity threshold, then the i grid reserve capacities are extracted and the energy storage station is activated for power compensation;

[0030] Determine the time point associated with the last obtained grid reserve capacity among the i grid reserve capacities, denoted as t k , and at t k+1 At this point in time, the energy storage station starts to compensate the power generated by the power grid;

[0031] Among them, i is the threshold of consecutive abnormal times set by the operator, t k t k ∈[t1,t2,...,t j ], and the value range of k is (i, j), and k>i.

[0032] As a further solution of the present invention, the specific manner in which the energy storage station control module performs power compensation operation on the power generation power of the power grid through the energy storage station is:

[0033] t k+1 As the start time, get t in real time k+1 to t k+2 The load power associated with the time interval Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 ;

[0034] And further obtain t k+1 to t k+2 The power compensation demand ΔP associated with any time point in the time interval;

[0035] The power compensation demand ΔP is used as the compensation power of the energy storage station for the power generation power of the grid at the corresponding time point;

[0036] Continuous monitoring k+1 to t k+2 The grid reserve capacity A within the time interval k+1 And check, if A k+1 ≥α*grid reserve capacity threshold A 阈 , operate the energy storage station to gradually reduce the compensation power of the power compensation operation until the compensation power is 0, where α is a coefficient preset by the operator according to the actual situation of the power grid.

[0037] As a further solution of the present invention, the energy storage station control module determines the charging time interval of the energy storage station and controls the energy storage station in the following specific manner:

[0038] Based on the determined Get the time point t1 to time point t i The corresponding electricity prices, if starting from time point t1, the electricity prices in the time interval composed of u consecutive time points are all lower than the average electricity price Q avg , then select from t u The next time point t u+1 Start entering the candidate charging start time interval, where u is the value preset by the operator and the average electricity price Q avg Obtained from the Internet;

[0039] Get t u to t u+1 The associated grid reserve capacity A within the time interval u , if A u >β*Grid reserve capacity threshold A 阈 , then determine t u+1 is the charging start time, where β is the coefficient preset by the operator based on the actual situation of the energy storage station;

[0040] Continuously monitor electricity prices and grid backup capacity. If at any time point t o The electricity price ≥Q avg or time point t o The previous time point t o-1 To time point t o The associated grid reserve capacity A during this time interval o ≤β*grid reserve capacity threshold A 阈 , then lock t o is the charging end time, and the combined time interval [t u+1 , t o ], as the charging time interval of the energy storage station, where t o t u+1 to t j Any one in this time interval, t o ≠t u+1 , o is the counting index, and the value range of o is (u+1, j].

[0041] As a further solution of the present invention, the specific method for the early warning feedback module to monitor the control execution status of the energy storage station control module in real time is:

[0042] The early warning feedback module monitors any operation instruction generated by the energy storage station control module in real time and continuously monitors the feedback signal of the corresponding operation instruction. If it is detected that any operation instruction does not generate a feedback signal within the time limit preset by the operator, it is determined that the energy storage station control module has failed to execute the control strategy;

[0043] The sound and light alarm function provides early warning feedback to the operator when the energy storage station control module fails to execute the operation instructions.

[0044] Beneficial effects of the present invention:

[0045] (1) This system can accurately grasp the charging and discharging timing of the energy storage station by real-time monitoring and analysis of electricity price fluctuations in the electricity spot market and the dynamic changes in grid load and power generation, achieve optimal allocation of energy storage resources, and improve the economic benefits of the energy storage station. Secondly, the present invention can effectively prevent grid failures. When it is detected that the grid backup capacity is lower than the threshold, the energy storage station is quickly activated for power compensation, thereby enhancing the stability and reliability of the grid and reducing the risk of power outages. The present invention helps to extend the service life of the battery pack and reduce operating costs through intelligent planning of the charging time of the energy storage station.

[0046] (2) This system normalizes the electricity price and power change curves and fits them to the same coordinate system to form a power generation power-load power-electricity price change curve, which intuitively displays the operation status of the power grid. At the same time, by constructing a timeline and calculating the area of the closed area, the grid's spare capacity is quantified, and the remaining power of the grid after meeting the load power is accurately evaluated to balance the grid's power loss, including circuit transmission loss and equipment power loss. The present invention can effectively improve the economy and safety of the grid operation and provide a guarantee for the stable power supply of the grid.

[0047] (3) By continuously monitoring the grid's backup capacity and setting a threshold trigger mechanism, the system can accurately identify persistent power supply failures rather than short-term fluctuations, avoiding misoperation caused by instantaneous disturbances and ensuring that energy storage compensation is quickly started when a real failure occurs, effectively ensuring grid stability. At the same time, the system innovatively analyzes electricity price fluctuations and the grid's backup capacity status, prioritizes charging during low electricity price periods, and starts charging in combination with sufficient backup capacity conditions, which not only reduces operating costs but also avoids additional loads during periods of grid tension. When electricity prices rise or backup capacity is insufficient, charging is immediately terminated, further optimizing the economic efficiency of energy storage. Overall, the system described in the present invention achieves a coordinated improvement in grid backup capacity management, power supply stability assurance, and operating cost control through intelligent fault detection, adaptive power regulation, and economical charging and discharging strategies, providing an efficient, economical, and sustainable solution for the integration of traditional power grids and renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below with reference to the accompanying drawings.

[0049] Figure 1 It is a schematic diagram of the structure of the system described in this application;

[0050] Figure 2 Schematic diagram of the process described in Example 2 of the present application;

[0051] Figure 3 Schematic diagram of the process described in Example 3 of the present application;

[0052] Figure 4 This is a schematic diagram of the generation power-load power-electricity price change curve described in Example 2 of this application. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] Example 1

[0055] A monitoring system for energy storage stations in a power spot market scenario, such as Figure 1 As shown, specifically including the following:

[0056] The electricity spot scenario monitoring module uses a standardized API interface to connect to the power market trading platform and third-party power data service providers in real time. This module obtains the real-time electricity price of the day (i.e., within a single day). It combines the timestamp corresponding to the obtained electricity price to generate electricity price-time series data, which is then mapped into an electricity price change curve. The electricity price change curve includes key time nodes (such as peak and valley price switching points and market bidding periods). This is transmitted to the energy storage control module in real time through visualization tools (such as D3.js or ECharts) for subsequent analysis.

[0057] The electricity spot scenario monitoring module also interacts with smart meters, SCADA systems or PMUs (phasor measurement units) in real time to collect grid load power and power generation power in real time, integrates the collected data with the corresponding timestamps, and generates load and power generation change curves respectively; key nodes (such as load peak periods) can be clearly observed in the load and power generation change curves, and support dynamic scaling and historical comparison functions.

[0058] The energy storage station control module analyzes the electricity price change curve and load and power generation change curves transmitted from the electricity spot scenario monitoring module to realize the control of the energy storage station and determine the charging time range of the energy storage station in the current day.

[0059] The early warning feedback module is used to monitor the operating instructions and feedback signals involved in the energy storage station control module in real time, set multi-level early warning detection rules and dynamically adjust the detection threshold according to the real-time status of the power grid. When the early warning feedback module detects an anomaly, it pushes the early warning details, including the abnormal time and operating instructions, to the operator through Cloud Home, SMS, email and system message center.

[0060] The storage module, serving as the system data hub, contains multiple databases and must ensure high reliability and scalability. A hybrid storage solution is used, with real-time data (such as electricity prices and power curves) stored in an in-memory database and historical data stored in a relational database or a time series database.

[0061] The storage module is also used to store any one of the methods described in this solution and its implementation steps.

[0062] Example 2

[0063] This embodiment discloses, based on the first embodiment, a method for fitting electricity price data, load power, and generated power into a generated power-load power-electricity price change curve, and judging whether power compensation operation is required based on the curve, such as Figure 2 As shown, the specific steps include:

[0064] The method described in this embodiment is implemented in the energy storage station control module and the power spot scenario monitoring module. First, the power spot scenario monitoring module obtains the real day preset by the operator. The real day starts at 0:00 and ends at 24:00, and the time from 0:00 to 24:00 is considered as a real day.

[0065] The electricity spot scene monitoring module interacts with the electricity market trading platform and third-party electricity data service providers in real time through the Internet, and obtains the current real-time electricity price and the time series t1, t2, ..., t preset by the operator. j , the time series t1,t2,...,t j The time in a real day is evenly divided, and the time difference between each two adjacent time points is the time t preset by the operator. The time sequence t1, t2, ..., t j Each time point in corresponds to an electricity price, so the electricity price change sequence can be obtained, which is expressed as: Q1, Q2, ..., Q j, where j is a counting index, indicating the number of electricity prices and the number of time points. The operator adjusts the value of j based on actual needs.

[0066] The electricity price change sequence Q1, Q2, ..., Q j And the time series t1, t2, ..., t associated with the electricity price change series j After that, we can construct a price change curve to show the change of electricity price over time in a more intuitive form. From the constructed price change curve, we can obtain the real-time electricity price corresponding to any time point, and it is persistent.

[0067] Construct a two-dimensional coordinate system, the horizontal axis of which is the timeline and the vertical axis is the value of the electricity price. After the construction is completed, the electricity price change sequence Q1, Q2, ..., Q j By marking the time point corresponding to each electricity price in the constructed two-dimensional coordinate system, a series of data points can be obtained. Then, the curve fitting technology is used to fit this series of data points. The final fitting result is used as the electricity price change curve associated with the current day, and is recorded as S Q .

[0068] The power spot scene monitoring module then collects the current grid load power and power generation power from the smart meter, SCADA system or PMU in real time, which are recorded as P 负 With P 发 ;

[0069] Based on the determined time series t1, t2, ..., t j And the grid load power P 负 , we get the load power sequence, which is expressed as Similarly, the power generation sequence is obtained, which is expressed as The timestamps of the load power sequence and the power generation sequence correspond one to one, which is represented as to Corresponding to the power generation sequence to

[0070] Then construct a two-dimensional coordinate system with the timeline as the horizontal axis and the power value as the vertical axis, and follow the load power sequence and power generation sequence Each corresponds to the time series t1, t2, ..., t j The power values associated with each time point in the constructed two-dimensional coordinate system are marked, and the curve is used again to fit the load power sequence and the power generation sequence, and finally the load power-power generation power change curve of the current day is obtained, which is recorded as The load power-generation power variation curve There are two curves that theoretically do not interact with each other, that is, at any point in time, the value of the generated power is greater than the value of the load power. Otherwise, the power grid will be considered to have failed. This invention does not delve into the power grid failure, but only analyzes the generated power and load power under normal power generation conditions.

[0071] Based on the obtained electricity price change curve S Q And the load power-generation power change curve First, extract the electricity price change curve S according to the time point Q And the load power-generation power change curve All the data in the data are normalized, and the electricity price and power are normalized to the same data interval, so that the electricity price change curve S Q And load power-generation power change curve Fit together into the same curve graph or the same two-dimensional coordinate system;

[0072] Construct a two-dimensional coordinate system with the timeline as the horizontal axis and the normalized value as the vertical axis, and plot the normalized electricity price change curve S Q And the load power-generation power change curve At the same time, it is fitted into the constructed two-dimensional coordinate system and recorded as the power generation power-load power-electricity price change curve, recorded as (The subsequent acquisition of electricity price data, load power data, and power generation data all refer to data before normalization. The normalization process here is to fit the power generation, load power, and electricity price into the same curve chart, which is convenient for observing multiple sets of data in the same time interval and comparing their synchronization and correlation. The power generation - load power - electricity price change curve chart Please refer to the example diagram for Figure 4 );

[0073] Then the power generation - load power - electricity price change curve Further processing is performed to determine the curve of power generation-load power-electricity price change The first time point t1 in the 2D coordinate system is constructed by passing through the first time point t1 and constructing a straight line perpendicular to the horizontal axis of the 2D coordinate system and parallel to the vertical axis of the 2D coordinate system, which is recorded as the first time line L1. The constructed first time line L1 is then copied, and the copied first time line L1 is translated in the positive direction of the horizontal axis of the 2D coordinate system by a time t to the time point t2 on the horizontal axis of the 2D coordinate system, thereby obtaining a straight line passing through the time point t2 and perpendicular to the horizontal axis of the 2D coordinate system and parallel to the vertical axis of the 2D coordinate system, which is recorded as the second time line L2.

[0074] After the first time line L1 and the second time line L2 are constructed, the first time line L1, the second time line L2, the load power variation curve, and the power generation variation curve will form a closed area. The area of this closed area is calculated and recorded as the grid backup capacity A1.

[0075] According to the principle of integration, the area of the closed region can be approximately expressed as the result of the accumulation of the difference between the generated power and the load power over time during the period between time point t1 and time point t2 (the time points t1 and t2 in this solution are only illustrative time points, not fixed time points, and can be customized by the operator to determine any two time points). This accumulated difference can be regarded as the backup capacity of the power grid in a physical sense, that is, the remaining power after the power grid load is met, which is used to balance the power loss of the power grid.

[0076] Power generation and load power typically change over time. The above method, by calculating the area of the enclosed region formed by these two curves within a specific time interval, can reflect the dynamic changes in reserve capacity during grid operation in real time. This helps to promptly identify potential problems in grid operation, such as insufficient or excessive reserve capacity, so as to help operators promptly adjust power generation plans or take corresponding preventive control measures.

[0077] After obtaining the grid backup capacity A1 between time point t1 and time point t2, the grid backup capacity A1 is compared with the grid backup capacity threshold A preset by the operator. 阈 Perform comparison operation. If the grid reserve capacity A1 is greater than or equal to the grid reserve capacity threshold value A preset by the operator, 阈 , then it is judged that the power generation in this time interval t1 to t2 meets the normal power supply demand of the power grid and no processing is required;

[0078] If the grid reserve capacity A1 is less than the grid reserve capacity threshold A preset by the operator, 阈 , it is determined that the generated power in the time interval t1 to t2 does not meet the normal power supply demand of the power grid, and the first time line L1 is copied again to the time point t3 on the horizontal axis of the two-dimensional coordinate system to obtain a straight line passing through the time point t3 and perpendicular to the horizontal axis of the two-dimensional coordinate system and parallel to the vertical axis of the two-dimensional coordinate system, which is recorded as the third time line L3;

[0079] At this time, the second time line L2, the third time line L3 power generation curve and the load power change curve will form a closed area. Calculate the area of the closed area and record it as the grid backup capacity A2, that is, the grid backup capacity during the time interval from time point t2 to time point t3. Repeat this step to obtain the grid backup capacity A3 during the time interval from time point t3 to time point t4, until the area of the closed area is A2. j-1 To time point t j The grid reserve capacity A during this period j-1 , and recorded as the grid reserve capacity sequence in the order of timeline: A1, A2, ..., A j-1 ;

[0080] Obtain the continuous abnormality threshold i set by the operator based on the actual situation, and select the grid backup capacity sequence A1, A2, ..., A j-1 Starting from the first grid reserve capacity A1 in the grid, compare it with the grid reserve capacity threshold A preset by the operator. 阈 Perform comparison operation. If the grid reserve capacity A1 is less than the grid reserve capacity threshold A 阈 Then the counter G preset by the operator is incremented by one. The initial value of the counter G is 0. If the grid backup capacity A1 is greater than or equal to the grid backup capacity threshold A 阈 , the value of counter G does not change. Similarly, A2 is obtained in sequence. If counter G continuously increases to i, it is considered that the energy storage station needs to be activated for power compensation. If counter G is interrupted during the counting process, the value of counter G is reset to 0 and the counting starts again.

[0081] When the counter G continuously increases to i, the time point at this time is extracted and recorded as t k , and at time t k The next time point t k+1 The power storage station starts to compensate the power generated by the power grid, and the time point t k ∈[t1,t2,...,t j ], and the value range of k is (i, j), and k>i.

[0082] This embodiment constructs an electricity price variation curve by acquiring a real-time sequence of electricity price changes and a time series. It also collects grid load power and generated power to form a load-generated power variation curve. Both are normalized and fitted to the same coordinate system. The area of the enclosed region formed by the cumulative difference between generated power and load power within a specific time interval is calculated as the grid's reserve capacity, reflecting the dynamic changes in reserve capacity based on the integration principle. If the reserve capacity continues to fall below a preset threshold for a continuous number of abnormalities, i, the energy storage station power compensation mechanism is triggered, and the energy storage station is activated at the next time point to adjust the grid power, ensuring that the grid's reserve capacity meets power supply needs and improving the safety and economy of grid operation.

[0083] Example 3

[0084] This embodiment further discloses a method for compensating the power generation power of the power grid through an energy storage station based on the embodiment 1 and the embodiment 2. Figure 3 As shown, the specific steps include:

[0085] Based on the time point t determined in Example 2 k The next time point t k+1 , from the time point t k+1 Start and get the time point t in real time k+1 To time point t k+2 The associated load power during this period Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 , the load power Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 It does not refer to the data corresponding to a single time point. In this embodiment, the load power Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 Refers to the time point t k+1 To time point t k+2 The load power, power generation power, electricity price and grid reserve capacity corresponding to any time point during this period;

[0086] Based on the load power obtained Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 , using the formula:

[0087]

[0088] Calculate the time point tk+1 To time point t k+2 The power compensation demand ΔP associated with any time point Δt in the grid, and the compensation power of the energy storage station for the power generation power of the grid when the power compensation demand ΔP corresponds to the time point Δt;

[0089] Continue to monitor k+1 To time point t k+2 The grid reserve capacity A during this period k+1 , if the grid reserve capacity A is found k+1 ≥α*grid reserve capacity threshold A 阈 , it means that the power generation power of the power grid no longer requires the energy storage station to perform power compensation operation. The energy storage station is operated to gradually reduce the power of the power compensation operation until the compensation power is reduced to 0, where α is the coefficient preset by the operator according to the actual situation of the power grid.

[0090] When the grid reserve capacity A is found k+1 ≥α*grid reserve capacity threshold A 阈 Afterwards, if the generated power is higher than the grid reserve capacity threshold A 阈 In the case of much larger, it is necessary to store the excess power generation in the energy storage station to avoid the waste of power generation. In the operation steps of power storage, it is necessary to combine the power generation power-load power-electricity price change curve For detailed analysis, in this embodiment, for the convenience of explanation and processing, another real day different from the one described above is selected, and the associated generation power-load power-electricity price change curve graph within the real day is obtained.

[0091] from Determine the electricity price corresponding to the first time point t1 in the actual day, and continue to obtain the electricity price backward. If it is found that the electricity price in the time interval composed of u consecutive time points starting from the first time point t1 is lower than the average electricity price Q avg , then it is judged that the electricity price is in a continuous low price period, then from t u The next time point t u+1 Start entering the candidate charging start time interval, where u is the counting index, the value interval of u is (1, j), the average electricity price Q avg Obtained from the Internet in real time;

[0092] Re-determine the time point t u To time point t u The next time point t u+1 The associated grid reserve capacity during this time interval is recorded as A u , the grid reserve capacity A u The grid reserve capacity threshold A preset by the operator阈 Perform the following comparison operations:

[0093] If the grid reserve capacity A u >β*Grid reserve capacity threshold A 阈 , then determine the time point t u+1 is the charging start time, the energy storage station starts at time t u+1 Start charging operation, where β is the coefficient preset by the operator based on the actual situation of the energy storage station;

[0094] Based on the determined time point t at which the charging operation is started u+1 Start, continue to monitor the electricity price and grid reserve capacity at subsequent time points, if the monitoring time point t u+1 At any time point t o The electricity price is greater than or equal to the average electricity price Q avg Or at the time point t o The previous time point t o-1 To time point t o The associated grid reserve capacity A during this time interval o ≤β*grid reserve capacity threshold A 阈 , then determine the time point t o is the charging end time of the energy storage station, and the combined time point t u+1 and time point t o Get the time interval [t u+1 , t o ], as the charging time interval of the energy storage station, where time point t o is time point t u+1 To time point t j Any time within this time interval, excluding time point t u+1 , that is, t o ≠t u+1 , o is the counting index, and the value range of o is (u+1, j].

[0095] This embodiment calculates power compensation requirements by real-time monitoring of key data such as grid load power, generated power, electricity prices, and grid backup capacity. A formula is then used to determine the compensation power for the energy storage station's power compensation operation, ensuring grid power balance. Simultaneously, the grid's backup capacity is monitored to determine whether energy storage station intervention is necessary. When sufficient backup capacity is available, the energy storage station's power output is reduced to avoid wasted resources. Furthermore, this embodiment considers storing excess generated power in the energy storage station to avoid waste. By combining a generation power-load power-electricity price curve, this embodiment identifies periods when electricity prices are continuously below the average price as candidate charging time intervals. This further optimizes the energy storage station's charging operations and improves its utilization efficiency.

[0096] Some of the data in the formulas described above are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0097] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in similar ways. As long as they do not deviate from the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

[0098] It is important to note that all user data collected in this application is collected with the user's consent and authorization. Furthermore, the use of user data is legal and compliant, and the use and processing of user data complies with the relevant laws, regulations, and standards of the relevant regions.

Claims

1. A monitoring system for energy storage stations in a power spot market scenario, characterized in that: This system includes the following: The electricity spot market monitoring module interacts with the internet in real time, extracting the electricity price under the actual daily electricity spot market scenario from the internet, and transmits this electricity price change curve together with the timestamps corresponding to the different electricity prices within the actual day to the energy storage station control module; Obtain the load power of the power grid and the power generation power of the power supply company in real time, build a load power-power generation power change curve chart and transmit it to the energy storage station control module; The energy storage station control module receives and analyzes the daily data transmitted by the electricity spot scenario monitoring module, determines the charging time interval of the energy storage station, and controls the energy storage station; The early warning feedback module monitors the control execution of the energy storage station control module in real time. If it is found that the energy storage station fails to implement the preset control strategy, an early warning will be triggered and the early warning details will be fed back to the energy storage station operator; The storage module stores the data obtained through analysis or calculation in any module of the system, and stores the methods and implementation steps involved in any module of the system.

2. The artificial intelligence-based online equipment monitoring system according to claim 1 is characterized in that: The specific method of real-time interaction between the electricity spot scene monitoring module and the Internet also includes the following: Determine the actual day, extract the electricity price within the actual day at every preset time t, and record it as the electricity price change sequence Q1, Q2, ..., Q j , where j is a counting index, indicating the number of electricity prices, and the operator adjusts the value of j based on actual needs; Electricity price change sequence Q1,Q2,...,Q j The corresponding acquisition time is recorded as the time series t1, t2, ..., t j , where Q1 to Q j Corresponding to t1 to t j ; A two-dimensional coordinate system is constructed with the timeline as the horizontal axis and the electricity price as the vertical axis. The electricity price change sequence is marked in chronological order. J data points are obtained and fitted with a curve to obtain the electricity price change curve S associated with the actual day. Q .

3. The artificial intelligence-based online equipment monitoring system according to claim 1, characterized in that: The electricity spot scenario monitoring module obtains the load power P in real time during the day 负 And power generation P 发 ; Recorded as load power series and power generation sequence in, to Corresponding in sequence to The load power sequence and the power generation sequence both correspond to the time series one by one, that is, to Corresponding to t1 to t j , to Corresponding to t1 to t j ; A two-dimensional coordinate system is constructed with the timeline as the horizontal axis and the power value as the vertical axis. The load power sequence and the power generation sequence are marked in the two-dimensional coordinate system, and the load power sequence and the power generation sequence are fitted with curves to obtain the load power-power generation change curve within the actual day, which is recorded as 4. The artificial intelligence-based equipment online monitoring system according to claim 1, characterized in that: The specific method in which the energy storage station control module receives and analyzes the various daily data transmitted by the power spot scenario monitoring module is as follows: To S Q and The values of the data in are normalized together; Then S Q as well as Fit it into the same two-dimensional coordinate system and record it as the curve of power generation-load power-electricity price change Construct a straight line perpendicular to the horizontal axis and parallel to the vertical axis through time point t1 on the horizontal axis of the coordinate system, recorded as the first time line L1. Copy L1 and shift it backward by time t to t2 on the horizontal axis to obtain a straight line perpendicular to the horizontal axis and parallel to the vertical axis through time point t2, recorded as the second time line L2. Record the area of the closed region formed by L1, L2, the power generation curve, and the load power curve as the grid reserve capacity A1 associated with the time interval from time point t1 to time point t2; The grid reserve capacity A1 is compared with the grid reserve capacity threshold A preset by the operator. 阈 Compare, if A1≥A 阈 , it is determined that the power generation power in the time interval from t1 to t2 meets the normal power supply demand and no processing is performed; Otherwise, it is determined that the generated power in the time interval from t1 to t2 does not meet the normal power supply demand.

5. The artificial intelligence-based online equipment monitoring system according to claim 4 is characterized in that: If the energy storage station control module determines that the generated power in the time interval from t1 to t2 does not meet the normal power supply demand, it copies L1 to t3 on the horizontal axis to obtain a straight line perpendicular to the horizontal axis and parallel to the vertical axis at t3, which is recorded as the third time line L3; Get the closed area composed of L2, L3, power generation curve and load power curve as the grid reserve capacity A2 associated with the time interval from t2 to t3. Similarly, get the area of A3 to A j-1 , recorded as the grid reserve capacity sequence A1, A2, ..., A in the order of acquisition j-1 ; If i consecutive grid reserve capacities in the grid reserve capacity sequence are all lower than the grid reserve capacity threshold, then the i grid reserve capacities are extracted and the energy storage station is activated for power compensation; Determine the time point associated with the last obtained grid reserve capacity among the i grid reserve capacities, denoted as t k , and at t k+1 At this point in time, the energy storage station starts to compensate the power generated by the power grid; Among them, i is the threshold of consecutive abnormal times set by the operator, t k t k ∈[t1,t2,...,t j ], and the value range of k is (i, j), and k>i.

6. The artificial intelligence-based online equipment monitoring system according to claim 5, characterized in that: The specific way in which the energy storage station control module performs power compensation operations on the power generation power of the power grid through the energy storage station is as follows: t k+1 As the start time, get t in real time k+1 to t k+2 The load power associated with the time interval Power generation Electricity Price Q k+1 and the grid reserve capacity A k+1 ; And further obtain t k+1 to t k+2 The power compensation demand ΔP associated with any time point in the time interval; The power compensation demand ΔP is used as the compensation power of the energy storage station for the power generation power of the grid at the corresponding time point; Continuous monitoring k+1 to t k+2 The grid reserve capacity A within the time interval k+1 And check, if A k+1 ≥α*grid reserve capacity threshold A 阈 , operate the energy storage station to gradually reduce the compensation power of the power compensation operation until the compensation power is 0, where α is a coefficient preset by the operator according to the actual situation of the power grid.

7. The artificial intelligence-based online equipment monitoring system according to claim 4, characterized in that: The energy storage station control module determines the charging time interval of the energy storage station and controls the energy storage station in the following specific ways: Based on the determined Get time point t i To time point t j The corresponding electricity prices, if starting from time point t1, the electricity prices in the time interval composed of u consecutive time points are all lower than the average electricity price Q avg , then select from t u The next time point t u+1 Start entering the candidate charging start time interval, where u is the value preset by the operator and the average electricity price Q avg Obtained from the Internet; Get t u to t u+1 The associated grid reserve capacity A within the time interval u , if A u >β*Grid reserve capacity threshold A 阈 , then determine t u+1 is the charging start time, where β is the coefficient preset by the operator based on the actual situation of the energy storage station; Continuously monitor electricity prices and grid backup capacity. If at any time point t o The electricity price ≥Q av g or time point t o The previous time point t o-1 To time point t o The associated grid reserve capacity A during this time interval o ≤β*grid reserve capacity threshold A 阈 , then lock t o is the charging end time, and the combined time interval [t u+1 , t o ], as the charging time interval of the energy storage station, where t o t u+1 to t j Any one in this time interval, t o ≠t u+1 , o is the counting index, and the value range of o is (u+1, j].

8. The artificial intelligence-based online equipment monitoring system according to claim 1, characterized in that: The specific method for the early warning feedback module to monitor the control execution status of the energy storage station control module in real time is: The early warning feedback module monitors any operation instruction generated by the energy storage station control module in real time and continuously monitors the feedback signal of the corresponding operation instruction. If it is detected that any operation instruction does not generate a feedback signal within the time limit preset by the operator, it is determined that the energy storage station control module has failed to execute the control strategy; The sound and light alarm function provides early warning feedback to the operator when the energy storage station control module fails to execute the operation instructions.

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