A source network load storage integrated transaction optimization management and control system

Abstract

The application relates to the technical field of power grid transaction management and control, and discloses a source-grid-load-storage integrated transaction optimization management and control system, which comprises a topological impedance mapping module, a convex hull correction module, a price reference generation module, a deviation power calculation module and a storage offer generation module; the scheme obtains a comprehensive cost coefficient by normalizing and summing the convex vertex price coordinates and impedance values, screens high-risk vertices, replaces the high-risk vertices with medians, and then re-fits, so that the offer curve implicitly contains network constraints, and the defects of traditional physical constraints are overcome; average deviation power is obtained by dividing the new energy prediction deviation by the time period length, the charging and discharging states are determined according to the positive and negative, the initial power is calculated by combining the state of charge and the protection threshold, and the actual power is obtained by comparing the initial power with the maximum power, so that the storage and the new energy fluctuation linkage are avoided to avoid over-limit; the actual power and the standardized price are written into an offer sheet and a priority level is set, so that priority matching is ensured, standby dependence is reduced, and the consumption rate is improved.

Description

Technical Field

[0001] This invention relates to the field of power grid transaction management and control technology, specifically to an integrated source-grid-load-storage transaction optimization and management system. Background Technology

[0002] The power grid transaction management and control technology field encompasses core components such as power market transaction planning, transaction clearing calculation, contract management, settlement and clearing, deviation assessment, risk control, and real-time regulation during transaction execution. This technology field revolves around the entire process of power commodity management from application to delivery, involving transaction matching among multiple market participants, clearing pricing, security verification, and closed-loop processing of execution deviations. Its overall technical system integrates power system operation constraints, market bidding mechanisms, and information-based management and control methods, aiming to support the coordinated operation of various resources (source, grid, load, and storage) under a unified trading framework, ensuring the feasibility, economy, and fairness of transaction results.

[0003] One type of integrated power generation, grid, load, and energy storage trading optimization and management system treats resources from the power generation side, grid side, load side, and energy storage side as unified trading objects. It determines the trading volume and price for each entity through a trading clearing algorithm, generates intraday multi-period trading schemes using trading plan scheduling methods, ensures trading feasibility through constraint verification, and adjusts for actual execution deviations using a deviation handling mechanism. This system covers technical aspects such as trading application reception, clearing calculation, plan generation, security verification, and deviation handling, specifically accomplished through a trading rule engine, clearing mathematical model solving, time-series rolling optimization, constraint verification logic, and deviation allocation rules. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an integrated source-grid-load-storage trading optimization and management system, which integrates network topology constraints into convex hull fitting and enables real-time linkage between energy storage charging and discharging and new energy fluctuations, thus solving the problems mentioned in the background technology.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: An integrated source-grid-load-storage transaction optimization and management system includes the following modules; Topology impedance mapping module: Obtains impedance values ​​and convex hull vertices, normalizes and sums to obtain the node comprehensive cost coefficient and the original convex hull vertex set; Convex Hull Correction Module: Calls the node comprehensive cost coefficient and the original convex hull vertex set, filters high-risk vertices, replaces the price with the median, and refits to obtain the corrected convex hull vertex set, outputting the original and corrected convex hull vertex sets; Price reference generation module: Calls the original and modified convex hull vertex sets. If the number of modified vertices is less than the preset minimum vertex number threshold, the original vertex price is taken; otherwise, the modified vertex price is taken. The average is then multiplied by the impedance correction coefficient to obtain the standardized clearing price reference value. Deviation power calculation module: Obtain the predicted value of new energy and the actual value, subtract them to get the deviation, divide by the time period to get the average deviation power, compare the positive and negative values ​​of the deviation to set the charging and discharging status, and output the average deviation power and charging and discharging status. Energy storage quotation generation module: calls the standardized clearing price reference value, average deviation power and charge / discharge status. If not maintained, it calculates the preliminary power based on the state of charge and protection threshold, takes the smaller of the power and the maximum power as the actual power, writes it into the quotation form and sets the priority level, and outputs the energy storage priority quotation form.

[0006] Preferably, the node comprehensive cost coefficient is the sum of the price normalization coefficient and the impedance normalization coefficient. The price normalization coefficient is obtained by dividing the price coordinate of the convex hull vertex by the maximum value of the price coordinates of all vertices, and the impedance normalization coefficient is obtained by dividing the node impedance value corresponding to the convex hull vertex by the maximum value of the impedance values ​​of all vertices.

[0007] Preferably, the high-risk vertex is a vertex whose node comprehensive cost coefficient is greater than a preset vertex screening threshold, and the corrected convex hull vertex set is obtained by replacing the price coordinates of the high-risk vertex with the median price of the bid point within the corresponding bid segment.

[0008] Preferably, the standardized clearing price reference value is specifically the product of the average price coordinate and the impedance correction coefficient. The impedance correction coefficient is obtained by dividing the base impedance value by the average impedance value of the entire network. The average impedance value of the entire network is the arithmetic mean of the impedance values ​​of all participating clearing resource nodes. The preset minimum number of vertices threshold is used to prevent excessive peak clipping from causing distortion of the convex hull shape.

[0009] Preferably, the average deviation power is obtained by dividing the absolute value of the predicted deviation by the time period, the predicted deviation is obtained by subtracting the predicted value from the actual value of the new energy output, and the charging and discharging state is set as charging state, discharging state or maintenance state according to the comparison result of the predicted deviation with zero.

[0010] Preferably, the initial power includes initial charging power and initial discharging power. The initial charging power is the product of the average deviation power and the ratio of available charging capacity. The ratio of available charging capacity is obtained by dividing the difference between the full charge protection threshold and the current state of charge by the full charge protection threshold. The full charge protection threshold is a preset upper limit value of the state of charge in the energy storage parameter table. The initial discharging power is the product of the average deviation power and the ratio of available discharging capacity. The ratio of available discharging capacity is obtained by dividing the difference between the current state of charge and the no-load protection threshold by the full charge protection threshold. The no-load protection threshold is a preset upper limit value of the state of charge in the energy storage parameter table.

[0011] Preferably, the actual power is obtained by comparing the preliminary power and the maximum power and taking the smaller value, and the maximum power is the maximum charge and discharge power value in the energy storage parameter table.

[0012] Preferably, the energy storage priority quotation includes a power field, a price field, and a priority clearing level setting. The power field is written with the actual power, and the price field is written with a standardized clearing price reference value.

[0013] Preferably, the node comprehensive cost coefficient and the original convex hull vertex set output by the topology impedance mapping module are called by the convex hull correction module, the corrected convex hull vertex set output by the convex hull correction module is called by the price reference generation module, and the standardized clearing price reference value output by the price reference generation module is called by the energy storage quotation generation module.

[0014] Preferably, the average deviation power and charging / discharging status output by the deviation power calculation module are called by the energy storage quotation generation module, and the energy storage quotation generation module determines whether to generate an energy storage priority quotation based on the charging / discharging status.

[0015] Compared with existing technologies, the present invention provides an integrated source-grid-load-storage transaction optimization and management system, which has the following beneficial effects: This scheme obtains a node comprehensive cost coefficient by normalizing and summing the convex hull vertex price coordinates and node impedance values. High-risk vertices are then selected based on this coefficient, and the vertex price is replaced with the median price of the bid points within the bidding segment before refitting. This implicitly incorporates network transmission bottleneck constraints into the bidding curve, overcoming the shortcomings of traditional convex hull fitting that ignores grid physical constraints, leading to infeasible clearing results. The scheme obtains the average deviation power by dividing the predicted deviation of renewable energy output by the time period. Charging and discharging states are set according to the sign of the deviation, and the preliminary power is calculated by combining the state of charge and protection thresholds. This preliminary power is then compared with the maximum power to obtain the actual execution power, enabling real-time linkage between energy storage charging and discharging decisions and renewable energy fluctuations. Simultaneously, state of charge constraints are used to avoid exceeding limits. By writing the actual power and standardized clearing price reference values ​​into the bidding form and setting priority clearing levels, priority matching of energy storage hedging commands is ensured, reducing the system's reliance on spinning reserves and improving renewable energy absorption rates. Overall, rule-driven parameter calculations replace complex iterations, reducing computational complexity and enhancing the physical executability of the clearing results. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the module connection of an integrated source-grid-load-storage transaction optimization and management system according to the present invention. Detailed Implementation

[0017] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0018] Example 1 like Figure 1 As shown, this embodiment provides a specific implementation of an integrated power generation, grid, load, and storage trading optimization and management system, applicable to regional power market operators. The system runs on a trading server, which interacts with external systems through a grid dispatch interface, a new energy forecasting interface, an energy storage monitoring interface, and a clearing calculation engine. Specifically, the grid dispatching interface is used to read grid topology data, the new energy forecasting interface is used to acquire forecast data, and the energy storage monitoring interface is used to collect energy storage operating status.

[0019] The topology impedance mapping module reads the impedance values ​​of each resource node under the current topology from the power grid dispatching system and obtains the convex hull vertices and their corresponding resource node numbers from the convex hull fitting results of the source-load joint bidding curve from the clearing calculation stage. This module pairs the resource node number corresponding to each convex hull vertex with its impedance value and normalizes the price coordinates and impedance values ​​of each vertex separately: the price normalization coefficient is the convex hull vertex price coordinate divided by the maximum price coordinate of all vertices, and the impedance normalization coefficient is the convex hull vertex corresponding node impedance value divided by the maximum impedance value of all vertices. The sum of the price normalization coefficient and the impedance normalization coefficient yields the node's comprehensive cost coefficient, which comprehensively reflects the node's electrical distance and market bidding level in the network topology. A larger coefficient indicates that the node is in a more sensitive position in the network and its bidding is higher. Simultaneously, the original convex hull vertex set is output.

[0020] The convex hull correction module calls the node comprehensive cost coefficient and the original convex hull vertex set, sorts all vertices by their comprehensive cost coefficients from largest to smallest, and selects vertices with coefficients greater than a preset vertex screening threshold as high-risk nodes. The preset vertex screening threshold is set by the system operator based on historical network congestion frequency, for example, between 0.6 and 0.8. When the comprehensive cost coefficients of all vertices are equal, peak shaving is not performed by default, and the original convex hull vertex set is directly used as the corrected convex hull vertex set. If the screening result is empty, the original convex hull vertex set is directly used as the corrected convex hull vertex set; otherwise, peak shaving is performed on the price segment corresponding to each high-risk node, extracting the price values ​​of all bid points within that price segment and taking the median, replacing the vertex price coordinates of the high-risk vertex. The median is used instead of the mean because the median is not sensitive to extreme prices and can more robustly reflect the overall price level of the price segment. The replaced vertex set is merged with the remaining vertex set, and the convex hull fitting operation is performed again to obtain the corrected convex hull vertex set. The original convex hull vertex set and the corrected convex hull vertex set are then output.

[0021] The price reference generation module calls the original convex hull vertex set and the modified convex hull vertex set, counts the number of vertices in the modified convex hull vertex set, and compares it with a preset minimum vertex count threshold. The preset minimum vertex count threshold can be set to, for example, one-third of the number of vertices in the original convex hull, to prevent excessive peak clipping that could distort the convex hull shape. When the number of modified vertices is exactly equal to the threshold, it is considered to have passed the verification, and vertex price coordinates are extracted from the modified convex hull vertex set. If the number of modified vertices is less than the threshold, it is determined that peak clipping has been excessive, the correction result is discarded, and vertex price coordinates are extracted from the original convex hull vertex set; otherwise, vertex price coordinates are extracted from the modified convex hull vertex set. The average value of the extracted price coordinates is calculated, and the impedance correction coefficient is obtained by dividing the reference impedance value by the network-wide average impedance value. The network-wide average impedance value is the arithmetic mean of the impedance values ​​of all participating clearing resource nodes, and the reference impedance value is a preset reference impedance constant, such as the per-unit impedance value of a typical transmission line. The average price coordinate value is multiplied by the impedance correction coefficient to obtain the standardized clearing price reference value, which eliminates the influence of different network sizes on the price level.

[0022] The deviation power calculation module obtains the predicted wind or solar power output for the previous period from the new energy forecasting system and the actual output for the same period from the new energy measurement system. Both predicted and actual values ​​are in MW, and the period length is in hours, ensuring the average deviation power is in MW. Subtracting the predicted value from the actual value yields the prediction deviation. A positive value indicates actual output is higher than predicted, indicating excess power in the system; a negative value indicates actual output is lower than predicted, indicating a power deficit. Dividing the absolute value of the prediction deviation by the period length yields the average deviation power, reflecting the average intensity of new energy output fluctuations. Comparing the prediction deviation to zero: a positive value sets the charging / discharging state to charging; a negative value sets it to discharging; and zero sets it to maintenance. The module outputs the average deviation power and the charging / discharging state.

[0023] The energy storage quotation generation module calls the standardized clearing price reference value, average deviation power, and charge / discharge status. If the charge / discharge status is in a maintenance state, no quotation is generated; if it is in a charging or discharging state, the current state of charge (SOC) is read from the energy storage monitoring system. The SOC ranges from 0% to 100%, with a full-charge protection threshold, for example, set to 90%, and an no-load protection threshold, for example, set to 20%. In the charging state, the current SOC is subtracted from the full-charge protection threshold. If the difference is greater than zero, it is divided by the full-charge protection threshold to obtain the available charging capacity ratio; otherwise, it is set to zero. The average deviation power is multiplied by this ratio to obtain the initial charging power. When the SOC is exactly equal to the full-charge protection threshold, the difference is zero, the available charging capacity ratio is set to zero, the initial charging power is zero, and no quotation is generated. In the discharging state, the no-load protection threshold is subtracted from the current SOC. If the difference is greater than zero, it is divided by the full-charge protection threshold to obtain the available discharge capacity ratio; otherwise, it is set to zero. The average deviation power is multiplied by this ratio to obtain the initial discharge power. If the initial power is zero, no bid is generated; otherwise, the maximum power is read from the energy storage parameter table, and the smaller value between the initial power and the maximum power is taken as the actual power. The actual power is written to the power field, the standardized clearing price reference value is written to the price field, the priority clearing level is set, and the priority energy storage bid is output. After the bid is sent to the clearing system, it is matched according to the priority matching mechanism. The clearing system maintains a priority queue, and the bid with the highest priority clearing level participates in the matching first. After the matching is completed, the cleared energy and clearing price of the energy storage are output. This reduces the system's dependence on spinning reserve and improves the renewable energy consumption rate.

[0024] Example 2 This embodiment is designed for a campus-level microgrid scenario. The system is deployed on an edge computing gateway and interacts with photovoltaic inverters, energy storage converters and load controllers through a local communication protocol, featuring low latency and high reliability.

[0025] The topology impedance mapping module reads the line impedance values ​​of each node in the microgrid topology through the local communication protocol and receives the convex hull fitting results of the source-load joint bidding curve sent by the local clearing agent. This module normalizes the price coordinates of the convex hull vertices and the corresponding node impedance values, then sums them to output the node comprehensive cost coefficient and the original convex hull vertex set. Unlike Example 1, because the microgrid lines are shorter and the impedance differences are smaller, the normalized impedance normalization coefficient has a narrower range. Therefore, the node comprehensive cost coefficient is mainly dominated by the price normalization coefficient, reflecting the characteristic that electrical distance has a relatively small impact on bidding in a microgrid.

[0026] The convex hull correction module sorts nodes based on their comprehensive cost coefficients and identifies vertices with coefficients greater than a preset threshold as high-risk nodes. In microgrid scenarios, the preset threshold can be appropriately lowered, for example, set to 0.4 to 0.6, to more sensitively identify potential market power abuse. For the price segment corresponding to a high-risk node, the median of all bid prices within that segment is extracted to replace the vertex price coordinates. The replaced vertex set is then merged with the remaining vertex set and refitted to output the original convex hull vertex set and the corrected convex hull vertex set.

[0027] The price reference generation module counts the number of vertices in the corrected convex hull. If the number is less than a preset minimum threshold, price coordinates are extracted from the original convex hull vertex set; otherwise, they are extracted from the corrected convex hull vertex set. The average value of the extracted price coordinates is calculated and multiplied by the ratio of the reference impedance value to the average impedance value of the entire network to obtain the standardized clearing price reference value. The average impedance value of the entire network is the arithmetic mean of the impedance values ​​of all participating clearing nodes. The reference impedance value is set by the system operator based on typical microgrid operating conditions; for example, it can be the average impedance value from the beginning to the end of a feeder.

[0028] The deviation power calculation module obtains the predicted and actual photovoltaic output values ​​from the previous time period, calculates the prediction deviation, and divides its absolute value by the time period length to obtain the average deviation power. Based on the sign of the prediction deviation, the charging / discharging state is set to either charging or discharging; if the deviation is zero, it is set to maintenance state. The module outputs the average deviation power and the charging / discharging state.

[0029] The energy storage quotation generation module calls upon the standardized clearing price reference value, average deviation power, and charge / discharge status. In non-maintenance mode, it reads the current state of charge and calculates the available charging capacity ratio or available discharging capacity ratio based on the charge / discharge status, multiplying it by the average deviation power to obtain the preliminary power. The preliminary power is compared with the maximum power in the energy storage parameter table, and the smaller value is taken as the actual power. The actual power and the standardized clearing price reference value are written into the quotation form, a priority clearing level is set, and a priority energy storage quotation form is output. This quotation form is sent to the clearing system and matched according to the priority matching mechanism, outputting the cleared energy storage capacity and clearing price.

[0030] This embodiment reduces communication latency through localized deployment, shortening the response time for energy storage charging and discharging decisions and new energy fluctuations to the second level, making it suitable for distributed scenarios with high real-time requirements. Simultaneously, the small impedance differences within the microgrid mean that price reference generation relies more heavily on the quoted price itself, which is beneficial for promoting price discovery in the local market.

[0031] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A source-grid-load-storage integrated transaction optimization and management system, characterized in that, Includes the following modules; Topology impedance mapping module: Obtains impedance values ​​and convex hull vertices, normalizes and sums to obtain the node comprehensive cost coefficient and the original convex hull vertex set; Convex Hull Correction Module: Calls the node comprehensive cost coefficient and the original convex hull vertex set, filters high-risk vertices, replaces the price with the median, and refits to obtain the corrected convex hull vertex set, outputting the original and corrected convex hull vertex sets; Price reference generation module: Calls the original and modified convex hull vertex sets. If the number of modified vertices is less than the preset minimum vertex number threshold, the original vertex price is taken; otherwise, the modified vertex price is taken. The average is then multiplied by the impedance correction coefficient to obtain the standardized clearing price reference value. Deviation power calculation module: Obtain the predicted value of new energy and the actual value, subtract them to get the deviation, divide by the time period to get the average deviation power, compare the positive and negative values ​​of the deviation to set the charging and discharging status, and output the average deviation power and charging and discharging status. Energy storage quotation generation module: calls the standardized clearing price reference value, average deviation power and charge / discharge status. If not maintained, it calculates the preliminary power based on the state of charge and protection threshold, takes the smaller of the power and the maximum power as the actual power, writes it into the quotation form and sets the priority level, and outputs the energy storage priority quotation form.

2. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The node comprehensive cost coefficient is the sum of the price normalization coefficient and the impedance normalization coefficient. The price normalization coefficient is obtained by dividing the price coordinate of the convex hull vertex by the maximum value of the price coordinates of all vertices. The impedance normalization coefficient is obtained by dividing the node impedance value corresponding to the convex hull vertex by the maximum value of the impedance values ​​of all vertices.

3. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The high-risk vertex is a vertex whose node comprehensive cost coefficient is greater than a preset vertex screening threshold. The corrected convex hull vertex set is obtained by replacing the price coordinates of the high-risk vertex with the median price of the bid point within the corresponding bid segment.

4. The integrated source-grid-load-storage transaction optimization and control system according to claim 1, characterized in that: The standardized clearing price reference value is specifically the product of the average price coordinate and the impedance correction coefficient. The impedance correction coefficient is obtained by dividing the base impedance value by the average impedance value of the entire network. The average impedance value of the entire network is the arithmetic mean of the impedance values ​​of all participating clearing resource nodes. The preset minimum number of vertices threshold is used to prevent excessive peak clipping from causing distortion of the convex hull shape.

5. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The average deviation power is obtained by dividing the absolute value of the predicted deviation by the time period. The predicted deviation is obtained by subtracting the predicted value from the actual value of the new energy output. The charging and discharging state is set as charging state, discharging state, or maintenance state based on the comparison result of the predicted deviation with zero.

6. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The initial power includes initial charging power and initial discharging power. The initial charging power is the product of the average deviation power and the ratio of available charging capacity. The ratio of available charging capacity is obtained by dividing the difference between the full charge protection threshold and the current state of charge by the full charge protection threshold, which is a preset upper limit value of the state of charge in the energy storage parameter table. The initial discharging power is the product of the average deviation power and the ratio of available discharging capacity. The ratio of available discharging capacity is obtained by dividing the difference between the current state of charge and the no-load protection threshold by the full charge protection threshold, which is a preset upper limit value of the state of charge in the energy storage parameter table.

7. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The actual power is obtained by comparing the preliminary power with the maximum power and taking the smaller value. The maximum power is the maximum charge and discharge power value in the energy storage parameter table.

8. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The energy storage priority bid includes a power field, a price field, and a priority clearing level setting. The power field is filled with the actual power, and the price field is filled with a standardized clearing price reference value.

9. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The node comprehensive cost coefficient and the original convex hull vertex set output by the topology impedance mapping module are called by the convex hull correction module. The corrected convex hull vertex set output by the convex hull correction module is called by the price reference generation module. The standardized clearing price reference value output by the price reference generation module is called by the energy storage quotation generation module.

10. The integrated source-grid-load-storage transaction optimization and management system according to claim 1, characterized in that: The average deviation power and charging / discharging status output by the deviation power calculation module are called by the energy storage quotation generation module, which determines whether to generate an energy storage priority quotation based on the charging / discharging status.

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