A Multi-Entity Business Collaborative Optimization Operation Method Based on Distributed Control (Source, Grid, Load, and Storage)

Abstract

This invention discloses a multi-entity business collaborative optimization operation method based on distributed control, belonging to the field of collaborative optimization technology. The method includes: each distributed business control center determines an acceptable adjustment direction based on a collaborative feasible interval and determines the collaborative pressure level based on a conflict interval; when the pressure threshold is not exceeded, the current operational intention is directionally corrected; when the pressure threshold is exceeded, the operational intention is triggered to revert and switch to a pre-declared secondary business feasible interval, generating corrected operational intention information; when the corrected operational intentions of each distributed business control center reach a preset consistency condition, a stable distributed collaborative operation state is determined. This invention, by determining an acceptable adjustment direction based on a collaborative feasible interval, achieves fine coordination between individual interests and global goals among multiple entities, alleviating the resource inefficiency and interest conflicts caused by insufficient consideration of business-level constraints in traditional methods.

Description

Technical Field

[0001] This invention relates to the field of collaborative optimization technology, and in particular to a multi-entity business collaborative optimization operation method based on distributed control, encompassing source, grid, load, and storage. Background Technology

[0002] With the large-scale integration of distributed photovoltaic, wind power, energy storage, and flexible loads, traditional centralized dispatching models are facing increasingly severe challenges. Existing methods for source-grid-load-storage collaborative optimization mainly rely on regional aggregation platforms. These platforms collect global operating status, prediction models, and constraints through a unified data center, and employ centralized algorithms such as mixed-integer linear programming, particle swarm optimization, or deep reinforcement learning to achieve multi-entity power balance and economic dispatch. These methods demonstrate high optimization accuracy and global optimality in small-to-medium scale or deterministic scenarios, and have been validated in engineering projects such as virtual power plant pilots and distribution network energy management.

[0003] However, existing methods still have some areas for improvement: First, existing optimization methods mostly focus on physical layer power balance and rarely consider heterogeneous constraints among multiple entities from the business perspective (such as energy storage lifetime management, load user comfort, production continuity, etc.), resulting in low efficiency of flexible resource utilization and difficulty in coordinating individual interest conflicts in actual operation; in addition, most schemes require frequent exchange of detailed state variables or gradient information among entities, resulting in limited privacy protection capabilities. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage to solve the problems of insufficient consideration of heterogeneous constraints among multiple entities at the business level and limited privacy protection capabilities.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a method for collaborative optimization of multi-entity services based on distributed control, including: At the start of the operation cycle, corresponding distributed business control centers are built on the source side, network side, load side and storage side respectively, and each distributed business control center generates operation capability description information based on its own operation status and business constraints. Each distributed business control center publishes operational capability description information through a distributed control communication mechanism, and performs aggregated analysis on the operational capabilities of multiple entities including source, network, load, and storage to form a collaborative operational space description result. The collaborative operational space description result includes conflict intervals and collaborative feasible intervals. Each distributed business control center determines the acceptable adjustment direction based on the collaborative feasible range and determines the collaborative pressure level based on the conflict range. When the current operating intention is not exceeded, the current operating intention is directionally corrected. When the preset pressure threshold is exceeded, the operating intention is triggered to turn back and switch to the pre-declared secondary business feasible range, generating corrected operating intention information. When the corrected operation intention information of each distributed business control center reaches the preset consistency condition, it is determined that a stable distributed collaborative operation state has been formed, and the corrected operation intention information is mapped into specific operation control instructions for execution, so as to realize the distributed collaborative optimization operation of multiple entities such as source, grid, load and storage.

[0007] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, wherein: the step of generating operational capability description information by each distributed business control center based on its own operational status and business constraints specifically includes: Each distributed service control center collects the current power level, remaining regulation capacity, and service constraints of its affiliated equipment; The current power level and remaining regulation capacity collected are subjected to boundary verification according to the business constraints to obtain the upper and lower bounds of the adjustable power that do not violate the constraints. The adjustable power upper and lower limits are combined with the corresponding duration range to form the power adjustment range and the time duration range. The unbreakable safe operating limit is calculated according to the safety requirements in the business constraints, and the safe operating limit is used as the rigid operating boundary. The power regulation range, time duration range, and rigid operating boundary are combined and encapsulated into operating capability description information.

[0008] As a preferred embodiment of the multi-entity service collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, wherein: each distributed service control center publishes operational capability description information through a distributed control communication mechanism, specifically: Each distributed service control center only sends its own operational capability description information to its directly adjacent distributed service control centers. After receiving the operational capability description information, the directly adjacent distributed service control centers continue to forward it to their respective directly adjacent distributed service control centers. The dissemination and release of all operational capability description information is completed through a tiered forwarding process with a limited number of hops.

[0009] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, the step of aggregating and analyzing the operational capabilities of the multiple entities (source, grid, load, and storage) to form a collaborative operation space description result specifically includes: After completing the hierarchical forwarding of the operational capability description information, each distributed service control center summarizes the operational capability description information received from all other distributed service control centers as well as the operational capability description information of its own center. Perform an interval intersection operation on the power adjustment intervals of each distributed business control center obtained from the aggregation to obtain the power range that is acceptable to all entities as the collaborative feasible interval; Perform interval difference operation on the power adjustment intervals of each distributed business control center obtained by aggregation, and identify at least one power range that cannot be satisfied by the main body as a conflict interval; The collaborative feasible interval and conflict interval are combined to form the collaborative operational space description result.

[0010] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, wherein: each distributed business control center determines an acceptable adjustment direction based on a collaborative feasible interval, specifically as follows: Each distributed business control center compares its current local operating intention power value with the collaborative feasible range; When the local operating intention power value is within the cooperative feasible range, the acceptable adjustment direction for this entity is to keep the current operating intention unchanged. When the local operating power value is lower than the lower limit of the cooperative feasible range, the acceptable adjustment direction of this entity is determined to be to increase the output upwards; When the local operating intention power value is higher than the upper limit of the cooperative feasible range, the acceptable adjustment direction of this entity is determined to be to reduce output downwards.

[0011] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, the step of determining the collaborative pressure level based on conflict intervals specifically includes: Each distributed service control center calculates the overlap length between the current operating intention power value and the conflict interval based on the determined acceptable adjustment direction and the local current operating intention power value. The ratio of the overlap length to the total range of local power regulation is used as the overlap ratio; Based on the degree of overlap, pressure levels are divided into three tiers: low pressure, medium pressure, and high pressure, resulting in a coordinated pressure level.

[0012] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, the step of directionally correcting the current operating intention when the preset pressure threshold is not exceeded specifically includes: When the collaborative pressure level of each distributed business control center is low or medium, the local current operating intention is fine-tuned according to the determined acceptable adjustment direction. The direction of fine-tuning is always consistent with the determined acceptable adjustment direction. When the acceptable adjustment direction is to increase output upward, fine-tuning is performed in the direction of the upper limit of the cooperative feasible interval. When the acceptable adjustment direction is to decrease output downward, fine-tuning is performed in the direction of the lower limit of the cooperative feasible interval. The fine-tuning range is controlled within the preset fine-tuning ratio of the local power adjustment range, and multiple fine-tunings are continuously performed in each operating cycle until the adjusted operating intention power value falls within the cooperative feasible range. The finely tuned local current running intent is used as the corrected running intent information.

[0013] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, the step of triggering an operational intention reversal and switching to a pre-declared secondary business feasible range when the preset pressure threshold is exceeded specifically includes: When the collaborative pressure level is high, each distributed business control center should immediately stop adjusting along the determined acceptable adjustment direction. The local current intended power value is adjusted in the opposite direction to the acceptable adjustment direction. The adjustment range is controlled within the preset adjustment ratio of the local power adjustment range. When the acceptable adjustment direction is to increase output upward, the output is reduced downward. When the acceptable adjustment direction is to reduce output downward, the output is increased upward. After the turnaround adjustment, select the secondary service feasible interval that is closest to the current operating state power value from the multiple secondary service feasible intervals declared locally in advance, and switch the operating intention power value after the turnaround adjustment to the selected secondary service feasible interval as the new adjustment target; The operational intent corresponding to the new adjustment target is used as the information for correcting the operational intent.

[0014] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, wherein: when the modified operation intentions of each distributed business control center reach a preset consistency condition, a stable distributed collaborative operation state is determined to be formed, specifically: The collaborative interaction layer continuously collects information on corrective operational intentions released by various distributed business control centers; The intentions of the corrective operation in adjacent cycles are compared one by one, and the average value of the change in the intentions of all subjects is calculated to obtain the average change. When the average change over multiple consecutive cycles is less than the preset consistency threshold, it is determined that the corrective operation intentions of all subjects have become stable, and the current cycle state is determined to be a stable distributed collaborative operation state.

[0015] As a preferred embodiment of the multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage described in this invention, the step of mapping the modified operation intention information into specific operation control commands for execution specifically includes: After determining that a stable distributed collaborative operation state has been formed, each distributed business control center reads the corrective operation intention information in the stable state; Calculate the power target setpoint of the equipment based on the adjustment direction and adjustment range in the revised operation intention information; The power target setpoint is converted into output commands for source-side power generation equipment, voltage control commands for grid-side regulation equipment, load commands for load-side equipment, and charging and discharging power commands for energy storage equipment, and then sent to the corresponding physical execution equipment to complete the actual operation and regulation.

[0016] The beneficial effects of this invention are as follows: By constructing a distributed business control center, and having each center generate abstract operational capability description information, the frequent exchange of detailed state variables or gradient information among various entities is effectively avoided, significantly improving privacy protection capabilities during multi-entity collaboration. Simultaneously, by determining the collaborative pressure level based on conflict intervals and adaptively performing directional fine-tuning or operational intent reversal switching to secondary business feasible intervals under different pressure levels, heterogeneous business constraints such as energy storage lifespan management, load user comfort, and production continuity are fully incorporated. This achieves fine coordination between individual interests and global goals among multiple entities, thereby significantly improving the utilization efficiency of flexible resources and alleviating the resource inefficiency and conflict of interest problems caused by insufficient consideration of business-level constraints in traditional methods. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a multi-entity business collaborative optimization operation method based on distributed control for source, grid, load, and storage.

[0019] Figure 2 A flowchart for generating a description of the collaborative runtime space.

[0020] Figure 3 A flowchart for generating corrected runtime intent information.

[0021] Figure 4 This is a flowchart for determining the collaborative operation status and issuing instructions. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0025] like Figure 1 As shown, this is an embodiment of the present invention, which provides a multi-entity service collaborative optimization operation method based on distributed control, including the following steps: S1: At the start of the operating cycle, corresponding distributed business control centers are built on the source side, network side, load side and storage side respectively, and each distributed business control center generates operating capability description information based on its own operating status and business constraints.

[0026] S1.1: At the start of the operating cycle, the source-side distributed service control center, the grid-side distributed service control center, the load-side distributed service control center, and the storage-side distributed service control center shall respectively obtain the current power level, remaining regulation capacity, and corresponding service constraints of their respective equipment in the current operating cycle. The service constraints shall at least include equipment rated capacity limits, operating safety limits, and constraints related to service continuity.

[0027] Each distributed service control center compares the current power level with the remaining adjustment capacity item by item according to the power limit requirements specified in the service constraints. The comparison process is as follows: the current power level is compared with the upper and lower limits of the equipment's rated capacity. If the current power level reaches or exceeds the upper limit of the rated capacity, the possibility of further upward adjustment is ruled out; if the current power level reaches or falls below the lower limit of the rated capacity, the possibility of further downward adjustment is ruled out. The remaining adjustment capacity is compared with the maximum allowable adjustment amount in the operation safety constraints. If the remaining adjustment capacity is less than the safety margin specified in the operation safety constraints, the adjustment direction that exceeds the safety margin is ruled out accordingly. The comparison results are comprehensively judged in conjunction with the constraints related to service continuity (such as minimum continuous operating time or maximum number of interruptions), and only the adjustment direction that simultaneously satisfies all constraints is retained, thereby determining the adjustable power upper and lower limits that do not violate the service constraints within the current operating cycle.

[0028] To further clarify, the current power level and the upper and lower limits of the equipment's rated capacity are directly obtained from the parameters on the equipment's nameplate; the safety margin is determined according to the equipment's safety standards and operating procedures. The safety margin for energy storage equipment is 10% to 20% of the rated capacity, which can effectively prevent battery life degradation and safety hazards caused by overcharging / over-discharging, while maintaining a high capacity utilization rate. For power generation equipment, the safety margin is 5% to 15% of the rated capacity, which avoids thermal stress or mechanical fatigue caused by frequently approaching the rated limit and extends the equipment's life.

[0029] S1.2: Each distributed service control center further combines the time information of its affiliated equipment that can continuously maintain operation under the corresponding states of adjustable power upper and lower limits, and associates the adjustable power upper and lower limits with the sustainable operating time to form a time duration interval corresponding to the power regulation capability, which is used to limit the effective range of power regulation in the time dimension.

[0030] While forming the time duration interval, each distributed business control center determines the operating limits that its equipment must not exceed during power adjustment, based on the operational safety-related restrictions in the business constraints. The operating limits include the safe power boundaries that the equipment is not allowed to exceed under any circumstances, and the operating limits are clearly marked as rigid operating boundaries to constrain all subsequent adjustment behaviors.

[0031] After determining the adjustable power upper limit, adjustable power lower limit, time duration interval, and rigid operating boundary, each distributed business control center uses a unified information organization method and a JSON structured format to combine and encapsulate the power adjustment interval, time duration interval, and rigid operating boundary to form complete operating capability description information, which is used to characterize the range of adjustment capabilities that the equipment has under the premise of meeting business constraints within the current operating cycle.

[0032] Preferably, this invention enables distributed business control centers on the source, grid, load, and storage sides to autonomously generate operational capability description information at the start of the operational cycle. This avoids the complexity of centralized aggregation of equipment parameters and unified modeling, allowing each entity to participate in collaborative operation without exposing internal operational details. By uniformly encapsulating power regulation capabilities, time-duration characteristics, and rigid operational boundaries, operational capabilities are simultaneously constrained in both power and time dimensions, effectively improving the accuracy and executability of collaborative operation judgments. Furthermore, by fully considering equipment rated capacity, operational safety limitations, and business continuity requirements during the generation phase, this helps reduce ineffective adjustments and conflicts in subsequent collaborative processes, enhancing the stability and reliability of multi-entity distributed collaborative optimization operation of the source, grid, load, and storage sides.

[0033] S2: As Figure 2 As shown, each distributed business control center publishes operational capability description information through a distributed control communication mechanism, and performs aggregated analysis on the operational capabilities of multiple entities including source, network, load, and storage to form a collaborative operational space description result. The collaborative operational space description result includes conflict intervals and collaborative feasible intervals.

[0034] S2.1: Each distributed business control center selects only the collaborative interaction nodes that have a direct communication connection with its own distributed business control center as the sending targets according to the pre-established distributed control communication relationship, and sends the operation capability description information to the directly adjacent collaborative interaction nodes. The sending process does not include cross-border sending to non-directly adjacent nodes.

[0035] To further explain, the pre-established distributed control communication relationships are configured before the start of the operation cycle by the source-side distributed service control center, network-side distributed service control center, load-side distributed service control center, and storage-side distributed service control center based on whether there are physical communication links or logical communication connections between them (referring to logical reachability relationships established based on IP addresses, MQTT topics, or custom node IDs, with the judgment criterion being the direct neighbor list confirmed through network topology scanning or manual configuration during the initial configuration phase). Specifically, during the initial configuration phase, a one-to-one communication connection identifier is established between the distributed service control centers that can directly exchange information and the corresponding collaborative interaction nodes, and the communication connection identifier is stored in each distributed service control center and collaborative interaction node. This is used to determine the range of directly adjacent collaborative interaction nodes during operation, thereby ensuring that the operational capability description information is sent and forwarded only between directly adjacent collaborative interaction nodes.

[0036] After receiving the operational capability description information from the distributed business control center, directly adjacent collaborative interaction nodes retain the received operational capability description information completely and, in accordance with the forwarding rules specified in the distributed control communication mechanism, continue to send the operational capability description information to other directly adjacent collaborative interaction nodes that have not yet received the current operational capability description information, thereby realizing the hierarchical propagation of operational capability description information among collaborative interaction nodes.

[0037] To further explain, the forwarding rules are configured together with the distributed control communication relationship before the start of the operation cycle. Specifically, during the initial configuration phase, based on the direct communication connection relationship between the distributed service control center and the collaborative interaction nodes (referring to the relationship between nodes directly connected by physical layer Ethernet, fiber optic, or wireless LAN links), the scope of objects allowed for forwarding (forward neighbors and backward neighbors), the forwarding order (first forward neighbors, then backward neighbors), and the forwarding limit (maximum two times) are set for each collaborative interaction node. The forwarding rules include at least allowing forwarding only to directly adjacent collaborative interaction nodes, disallowing repeated forwarding to collaborative interaction nodes that have already completed receiving, and stopping forwarding after reaching a preset number of forwarding hops. The forwarding rules are stored in each collaborative interaction node in a parameterized manner to guide the hierarchical forwarding behavior of the operational capability description information during operation.

[0038] To further explain, the preset forwarding hop count is pre-set based on the network topology depth. In a typical distribution network chain structure, the value is 1.5 times the network diameter, that is, between 5 and 15 hops, to ensure that information covers all nodes while avoiding infinite loops.

[0039] During the hierarchical propagation of operational capability description information, each collaborative interaction node marks and records the operational capability description information that has been received and forwarded to avoid communication redundancy caused by repeated forwarding. After all collaborative interaction nodes have completed receiving the information, the forwarding of operational capability description information is stopped. Thus, the dissemination and publication of all operational capability description information within the scope of distributed control communication is completed through hierarchical forwarding with a limited number of hops.

[0040] S2.2: After completing the hierarchical forwarding of the operational capability description information, each distributed service control center shall summarize the operational capability description information received from all other distributed service control centers and the operational capability description information of its own center. The summary shall include at least the power adjustment range, time duration range and rigid operating boundary corresponding to each subject, and maintain the independence between the operational capability description information of each subject, without modifying the operational capability description information of a single subject.

[0041] Each distributed service control center extracts the power adjustment ranges of the source-side, grid-side, load-side, and storage-side distributed service control centers from the aggregated operational capability description information. These power adjustment ranges are then uniformly aligned within the same power dimension. Each distributed service control center uses a unified power adjustment reference direction as its power reference coordinate benchmark. This unified power adjustment reference direction is defined as positive for increasing power supply to the source side and negative for increasing power consumption to the load side. The power adjustment ranges submitted by each distributed service control center in the operational capability description information are expressed according to this positive and negative direction convention. Based on this, each distributed service control center maps the power adjustment ranges of the source side, grid side, load side, and storage side to the same power reference coordinate system with the power adjustment reference direction as the benchmark, thus completing the directional consistency processing of the power adjustment ranges of different entities.

[0042] Within the aligned power range, the overlap of each main body's power adjustment range is compared one by one. Only the power portion that falls within the power adjustment range of all main bodies is retained to form a power range that is acceptable to all main bodies. This acceptable power range is then determined as the cooperatively feasible range.

[0043] To further explain, mapping the power adjustment ranges of different entities to the same power reference coordinate system involves each distributed service control center converting the power adjustment ranges submitted by each distributed service control center into an interval expression form under the same power reference direction according to a unified power positive and negative direction agreement, thereby achieving direct alignment and comparison of power adjustment ranges on the same power axis.

[0044] While forming a collaborative feasible range, each distributed business control center further compares the power adjustment ranges of each entity and marks the power ranges that are not simultaneously covered by all entity power adjustment ranges. The marked power ranges correspond to at least one entity that cannot adjust under the premise of meeting its own operational capability description information. Each distributed business control center identifies the marked power ranges as conflict ranges to reflect the inconsistent power ranges between the operational capabilities of multiple entities.

[0045] Each distributed business control center combines and organizes the feasible and conflicting intervals to form a collaborative operation space description result, which describes the overall collaborative and non-collaborative range of multiple entities (source, grid, load, and storage) within the current operating cycle. The collaborative operation space description result is used as the basic input for subsequent collaborative pressure determination and operational intention adjustment.

[0046] S3: As Figure 3As shown, each distributed business control center determines the acceptable adjustment direction based on the collaborative feasible range and determines the collaborative pressure level based on the conflict range. When the pressure threshold is not exceeded, the current operation intention is directionally corrected. When the pressure threshold is exceeded, the operation intention is triggered to turn back and switch to the pre-declared secondary business feasible range, generating corrected operation intention information.

[0047] S3.1: Each distributed business control center obtains the collaborative operation space description results, reads the upper and lower bounds of the power corresponding to the collaborative feasible interval, and synchronously reads the current operation intention power value of its own distributed business control center. The current operation intention power value is compared with the upper and lower boundaries of the collaborative feasible interval one by one. When the current operation intention power value is between the lower and upper boundaries of the collaborative feasible interval, the distributed business control center confirms that the current operation intention meets the multi-entity collaboration requirements and determines the acceptable adjustment direction as maintaining the current operation intention unchanged. When the current operation intention power value is less than the lower boundary of the collaborative feasible interval, the distributed business control center confirms that the current operation intention is below the common acceptable range for multiple entities and determines the acceptable adjustment direction as increasing output upwards. When the current operation intention power value is greater than the upper boundary of the collaborative feasible interval, the distributed business control center confirms that the current operation intention is above the common acceptable range for multiple entities and determines the acceptable adjustment direction as decreasing output downwards. This provides a clear directional basis for subsequent collaborative pressure determination and operation intention adjustment.

[0048] To further explain, the current intended power value is the power output (or consumption) target value that the distributed business control center determines to be achieved in the current cycle, based on its own business objectives, economic scheduling strategy, or local optimization needs, before the start of the current cycle or at the end of the previous cycle.

[0049] S3.2: After determining the acceptable adjustment direction, each distributed service control center reads the corresponding conflict interval from the collaborative operation space description result and, in conjunction with the current operation intention power value of its own distributed service control center, determines whether there is an overlap between the current operation intention power value and the conflict interval in the acceptable adjustment direction. When the current operation intention power value and the adjustment range along the acceptable adjustment direction enter the conflict interval, the power range entering the conflict interval is determined as the overlap length with the conflict interval. Each distributed service control center compares the overlap length with the total power adjustment interval corresponding to its own distributed service control center to obtain the overlap ratio used to characterize the degree of conflict, expressed as: ; in, Indicates the overlap ratio. This indicates the overlap length corresponding to the current intended operating power value entering the conflict zone in the acceptable adjustment direction. This indicates the total length of the power regulation range corresponding to this distributed service control center.

[0050] Each distributed service control center determines the collaborative pressure level based on its position within the total power regulation range according to the overlap ratio. The determination method is based on the proportional division of the total power regulation range reflected in the operational capability description information: when the overlap length corresponding to the overlap ratio is in the low-proportion segment of the total power regulation range, the collaborative pressure level corresponding to the current operating state is determined to be low pressure level; when the overlap length corresponding to the overlap ratio is in the medium-proportion segment of the total power regulation range, the collaborative pressure level corresponding to the current operating state is determined to be medium pressure level; when the overlap length corresponding to the overlap ratio is in the high-proportion segment of the total power regulation range, the collaborative pressure level corresponding to the current operating state is determined to be high pressure level. This results in a collaborative pressure level used to guide subsequent adjustments to operational intentions.

[0051] To further clarify, the low-proportion, medium-proportion, and high-proportion segments are obtained by proportionally dividing the total power adjustment range determined in the operational capability description information. The total power adjustment range is jointly determined by the upper and lower limits of adjustable power and is divided into three consecutive proportional segments along the adjustment direction. Specifically, when the overlap ratio is between 0 and one-third of the total power adjustment range, it corresponds to the low-proportion segment; when the overlap ratio is between one-third and two-thirds of the total power adjustment range, it corresponds to the medium-proportion segment; and when the overlap ratio is between two-thirds and one-third of the total power adjustment range, it corresponds to the high-proportion segment. Each distributed service control center determines the corresponding collaborative pressure level based on the proportional segment in which the overlap ratio is located.

[0052] S3.3: Each distributed service control center obtains the collaborative pressure level and determines whether a directional correction to the current operational intent is needed based on the collaborative pressure level. When the collaborative pressure level is determined to be low or medium, it indicates that the preset pressure threshold has not been triggered. Each distributed service control center reads the determined acceptable adjustment direction and, while maintaining the acceptable adjustment direction unchanged, makes a small adjustment to the local current operational intent power value. The small adjustment is always made along the acceptable adjustment direction. When the acceptable adjustment direction is to increase output upwards, the distributed service control center moves the current operational intent power value towards the upper limit of the collaborative feasible range. When the acceptable adjustment direction is to decrease output downwards, the distributed service control center moves the current operational intent power value towards the lower limit of the collaborative feasible range, while limiting the adjustment range to the corresponding value in the operational capability description information. Within the preset fine-tuning ratio range allowed by the power adjustment range, after each small adjustment, each distributed business control center compares the adjusted operating intention power value with the upper and lower boundaries of the collaborative feasible range. When the adjusted operating intention power value is between the lower and upper boundaries of the collaborative feasible range, the verification is confirmed to be successful. When the adjusted operating intention power value exceeds the lower or upper boundary of the collaborative feasible range, the adjustment is immediately cancelled, and the operating intention power value is directly limited to the boundary position of the collaborative feasible range corresponding to the adjustment direction. That is, when the adjustment direction is to increase output upward, the operating intention power value is set as the upper boundary value of the collaborative feasible range; when the adjustment direction is to decrease output downward, the operating intention power value is set as the lower boundary value of the collaborative feasible range. This avoids boundary oscillation and ensures that the corrected operating intention information is always within the collaborative feasible range.

[0053] To further explain, minor adjustments refer to proportional step adjustments based on the power adjustment interval length determined in the operational capability description information. When performing directional corrections, each distributed service control center determines the permissible power change range for a single advance based on the total length of the power adjustment interval, ensuring that the intended power value moves gradually towards the target direction without crossing the boundary of the collaborative feasible interval. The preset fine-tuning ratio is a portion of the power adjustment interval length. Within an operational cycle, the power change corresponding to a single minor adjustment does not exceed one-tenth of the power adjustment interval length, thereby preventing excessive jumps in the intended power value within a single operational cycle. The preset pressure threshold is a key dividing line used to distinguish between "minor deviations within acceptable limits" (low / medium pressure) and "severe conflicts requiring immediate concessions" (high pressure). Low or medium pressure levels indicate that the pressure threshold has not been triggered, as it is necessary to ensure that fine-tuning can converge within the remaining cycle under low / medium pressure. High pressure levels indicate that the pressure threshold has been triggered, which is to ensure that the turnaround can quickly escape the conflict under high pressure.

[0054] When the collaborative pressure level is determined to be high, it indicates that a preset pressure threshold has been triggered. Each distributed service control center immediately stops the adjustment process along the predetermined acceptable adjustment direction and performs a reverse adjustment based on the current intended power value. The reverse adjustment amplitude is controlled within the preset reverse ratio of the local power adjustment range (not exceeding one-fifth of the power adjustment range length, to balance rapid exit from the conflict zone and avoid oscillations caused by excessive reverse adjustment). When the acceptable adjustment direction is to increase output, the distributed service control center reverses the current intended power value in the direction of decreasing output. In the backtracking adjustment, when the acceptable adjustment direction is downward reduction of output, the distributed service control center will backtrack the current operating intention power value towards the direction of increasing output. After the backtracking adjustment is completed, each distributed service control center will select the secondary service feasible interval that is numerically closest to the operating intention power value after the backtracking adjustment from multiple secondary service feasible intervals pre-declared in the operating capability description information, and switch the operating intention power value after the backtracking to the internal range of the selected secondary service feasible interval as the new operating intention adjustment target. Finally, the operating intention corresponding to the new adjustment target will be determined as the corrected operating intention information.

[0055] To further clarify, the multiple secondary business feasible intervals declared in advance are determined by each distributed business control center before the start of the operating cycle based on the power adjustment interval, time duration interval, and rigid operating boundary in the operating capability description information. Each distributed business control center, without violating its own business constraints, divides the acceptable operating range within the power adjustment interval, excluding the main business operating interval, and identifies them as multiple secondary business feasible intervals in sequence according to their distance relationship with the main business operating interval. Each secondary business feasible interval contains a clear upper and lower power limit range and a corresponding time duration interval that meets the requirements of business continuity and operational safety. It is used to characterize the backup feasible adjustment range that can still maintain stable operation of the equipment when the current main operating intention is abandoned.

[0056] Preferably, this invention achieves the hierarchical dissemination of operational capability description information through a distributed control communication mechanism, avoiding the single point of failure and privacy leakage risks of centralized data aggregation. It determines acceptable adjustment directions and collaborative pressure levels based on collaborative feasible intervals and conflict intervals, and adaptively selects directional fine-tuning or operational intent reversal to switch secondary business feasible intervals according to the pressure level, realizing privacy-preserving collaborative optimization among multiple entities under limited information interaction. Compared with existing centralized optimization methods, this invention eliminates the need for global data sharing and unified calculation, significantly reducing communication burden and computational complexity. Simultaneously, through pressure level-based decision-making and boundary constraint verification, it enhances the adaptability and real-time response capabilities of this invention in high-proportion renewable energy access scenarios, effectively promoting collaborative operation among multiple entities including source, grid, load, and storage.

[0057] S4: As Figure 4 As shown, when the modified operation intentions of each distributed business control center reach the preset consistency conditions, a stable distributed collaborative operation state is determined to be formed, and the modified operation intention information is mapped into specific operation control instructions for execution, so as to realize the distributed collaborative optimization operation of multiple entities such as source, network, load and storage.

[0058] S4.1: At the end of each operating cycle, the collaborative interaction layer continuously collects the revised operating intent information released by the source-side distributed business control center, the network-side distributed business control center, the load-side distributed business control center, and the storage-side distributed business control center, and compares all the revised operating intent information collected in the current cycle with the revised operating intent information collected in the previous cycle one by one.

[0059] The collaborative interaction layer calculates the difference between the corrected operation intention information of the source-side distributed service control center, network-side distributed service control center, load-side distributed service control center, and storage-side distributed service control center in two adjacent cycles to obtain the change magnitude of the corrected operation intention of each distributed service control center. The expression is as follows: ; in, Indicates the first Each distributed business control center in the current cycle Compared with the previous cycle The magnitude of the change in the power value between the corrected operating intentions Indicates the first Each distributed business control center in the current cycle The revised intended power values ​​for operation have been released. Indicates the first Each distributed business control center in the previous cycle The revised intended power value for operation has been released.

[0060] The average change magnitude is obtained by averaging the changes in the modified operation intentions of the four distributed business control centers.

[0061] When the average change is less than the preset consistency condition for three consecutive operating cycles, the collaborative interaction layer determines that the corrective operation intentions of the source-side distributed business control center, network-side distributed business control center, load-side distributed business control center, and storage-side distributed business control center have become stable, and determines the current operating cycle state that meets the condition as a stable distributed collaborative operation state.

[0062] To further explain, the preset consistency condition is used to determine whether the corrective operation intentions of multiple distributed business control centers have become stable. It is set based on the measurement error and noise level of distributed communication. Therefore, the value range of the preset consistency condition is usually set to 0.02 to 0.05 (i.e. 2% to 5%) of the local power adjustment interval length to balance convergence speed and stability. The preset consistency threshold can be adjusted according to specific scenarios (such as new energy penetration rate, communication quality, etc.).

[0063] S4.2: After determining that a stable distributed collaborative operation state has been formed, each distributed business control center reads the modified operation intention information of the bound device in the current stable state.

[0064] The source-side distributed business control center calculates the power target setpoint for the source-side power generation equipment based on the adjustment direction and adjustment range in the source-side corrected operation intention information; the grid-side distributed business control center calculates the power target setpoint for the grid-side control device based on the adjustment direction and adjustment range in the grid-side corrected operation intention information; the load-side distributed business control center calculates the power target setpoint for the load-side load based on the adjustment direction and adjustment range in the load-side corrected operation intention information; and the energy storage-side distributed business control center calculates the power target setpoint for the energy storage device based on the adjustment direction and adjustment range in the energy storage-side corrected operation intention information.

[0065] To further explain, calculating the power target setpoint means adding or subtracting the current power level from the corresponding adjustment range based on the adjustment direction and adjustment range in the modified operation intention information, thereby obtaining the power target setpoint.

[0066] The source-side distributed business control center converts the power target setpoint of the source-side power generation equipment into the output command of the source-side power generation equipment and sends it to the source-side power generation equipment for execution; the grid-side distributed business control center converts the power target setpoint of the grid-side regulation device into the voltage control command or power flow control command of the grid-side regulation device and sends it to the grid-side regulation device for execution; the load-side distributed business control center converts the power target setpoint of the load-side load into the load reduction command or load increase command of the load-side load and sends it to the load actuator for execution; the storage-side distributed business control center converts the power target setpoint of the energy storage device into the charging and discharging power command of the energy storage device and sends it to the energy storage device actuator for execution, thereby completing the actual operation and regulation of multiple entities including source, grid, load and storage.

[0067] This embodiment also provides a computer device applicable to the multi-entity business collaborative optimization operation method based on distributed control of source, grid, load and storage, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the multi-entity business collaborative optimization operation method based on distributed control of source, grid, load and storage proposed in the above embodiment.

[0068] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0069] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the multi-entity business collaborative optimization operation method based on distributed control proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0070] In summary, this invention effectively avoids frequent exchanges of detailed state variables or gradient information among stakeholders by constructing a distributed business control center, with each center generating abstract operational capability description information, thus significantly improving privacy protection during multi-stakeholder collaboration. Simultaneously, by determining the collaborative pressure level based on conflict intervals and adaptively fine-tuning directions or switching operational intentions back to secondary business feasible intervals under different pressure levels, it fully incorporates heterogeneous business constraints such as energy storage lifespan management, load user comfort, and production continuity. This achieves fine-grained coordination between individual interests and global goals among multiple stakeholders, thereby significantly improving the utilization efficiency of flexible resources and alleviating the resource inefficiency and conflict of interest problems caused by insufficient consideration of business-level constraints in traditional methods.

[0071] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A multi-entity business collaborative optimization operation method based on distributed control for source, grid, load, and storage, characterized by: Comprising, At the beginning of the operation cycle, the source side, the network side, the load side and the storage side are respectively constructed corresponding distributed business control centers, and the distributed business control centers generate operation capability description information based on their own operation state and business constraints; The distributed business control centers generate operation capability description information based on their own operation state and business constraints, specifically: Each distributed business control center collects the current power level, residual adjustment capacity and business constraint conditions of the equipment it belongs to; The collected current power level and residual adjustment capacity are boundary checked according to the business constraint conditions to obtain the upper and lower bounds of the adjustable power that do not violate the constraints; The upper and lower bounds of the adjustable power are combined with the corresponding time duration range to form the power adjustment interval and time duration interval, and the safe operation limit that cannot be broken is calculated according to the safety requirements in the business constraint conditions, and the safe operation limit is taken as the rigid operation boundary; The power adjustment interval, time duration interval and rigid operation boundary are combined and packaged as operation capability description information; Each distributed business control center publishes operation capability description information through a distributed control communication mechanism, and aggregates and analyzes the operation capability of the source network load storage multi-agent to form a collaborative operation space description result, which contains a conflict interval and a collaborative feasible interval; Each distributed business control center determines the acceptable adjustment direction based on the collaborative feasible interval, and determines the collaborative pressure level based on the conflict interval. When the preset pressure threshold is not exceeded, the current operation intention is directionally corrected, and when the preset pressure threshold is exceeded, the operation intention is returned and switched to the pre-declared secondary business feasible interval to generate corrected operation intention information; When the corrected operation intention information of each distributed business control center reaches the preset consistency condition, it is determined that a stable distributed collaborative operation state is formed, and the corrected operation intention information is mapped to specific operation control instructions for execution, realizing the distributed collaborative optimization operation of the source network load storage multi-agent.

2. The multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage as described in claim 1, characterized in that: Each distributed business control center publishes operation capability description information through a distributed control communication mechanism, specifically: Each distributed business control center only sends its own operation capability description information to the directly adjacent distributed business control center, and the directly adjacent distributed business control center continues to forward the operation capability description information to its own directly adjacent distributed business control center after receiving it; The diffusion and publication of all operation capability description information are completed through limited number of hops of step-by-step forwarding.

3. The multi-entity business collaborative optimization operation method based on distributed control for source-grid-load-storage as described in claim 1, characterized in that: The operation capability of the source network load storage multi-agent is aggregated and analyzed to form a collaborative operation space description result, specifically: After completing the step-by-step forwarding of the operation capability description information, each distributed business control center collects all the operation capability description information of other distributed business control centers received by the center and the operation capability description information of the center; The power adjustment interval of each distributed business control center obtained by the center is subjected to interval intersection operation to obtain the power range acceptable to all agents as the collaborative feasible interval; performing interval difference set operation on the power adjustment intervals of the distributed business control centers to identify at least one power range that cannot be satisfied by the subject as a conflict interval; combining the cooperative feasible interval and the conflict interval to form a cooperative operation space description result.

4. The method of claim 1, wherein the method further comprises: determining a plurality of candidate solutions for the multi-agent service coordination optimization problem; and selecting a solution from the plurality of candidate solutions. The distributed business control centers determine an acceptable adjustment direction based on the cooperative feasible interval, specifically: The distributed business control centers compare the local current operation intention power value with the cooperative feasible interval; when the local operation intention power value is within the cooperative feasible interval, it is determined that the acceptable adjustment direction of the subject is to keep the current operation intention unchanged; when the local operation intention power value is lower than the lower limit of the cooperative feasible interval, it is determined that the acceptable adjustment direction of the subject is to increase the output; when the local operation intention power value is higher than the upper limit of the cooperative feasible interval, it is determined that the acceptable adjustment direction of the subject is to decrease the output.

5. The method of claim 1, wherein the method further comprises: determining a plurality of candidate solutions for the multi-agent service coordination optimization problem; and selecting a solution from the plurality of candidate solutions. The cooperative stress level is determined based on the conflict interval, specifically: The distributed business control centers calculate the overlap length of the current operation intention power value and the conflict interval according to the determined acceptable adjustment direction and the local current operation intention power value; the overlap length and the local power adjustment total interval are used as an overlap ratio; the overlap ratio is divided into low stress level, medium stress level and high stress level in order to obtain the cooperative stress level.

6. The method of claim 1, wherein the method further comprises: determining a plurality of candidate solutions for the multi-agent service coordination optimization problem; and selecting a solution from the plurality of candidate solutions. When the preset stress threshold is not exceeded, the current operation intention is directionally corrected, specifically: When the cooperative stress level of the distributed business control centers is low stress and medium stress, the local current operation intention is fine-tuned according to the determined acceptable adjustment direction; The direction of fine-tuning is always consistent with the determined acceptable adjustment direction. When the acceptable adjustment direction is to increase the output, the upper limit of the cooperative feasible interval is fine-tuned. When the acceptable adjustment direction is to decrease the output, the lower limit of the cooperative feasible interval is fine-tuned; The fine-tuning amplitude is controlled within the preset fine-tuning ratio of the local power adjustment interval, and multiple fine-tunings are continuously performed in each operation cycle until the adjusted operation intention power value falls within the cooperative feasible interval; The local current operation intention after fine-tuning is used as the corrected operation intention information.

7. The method of claim 1, wherein the method further comprises: determining a plurality of candidate solutions for the multi-agent service coordination optimization problem; and selecting a solution from the plurality of candidate solutions. When the preset stress threshold is exceeded, the operation intention is triggered to return and switch to a pre-declared secondary business feasible interval, specifically: When the cooperative stress level of the distributed business control centers is high stress, the adjustment in the determined acceptable adjustment direction is immediately stopped; The local current operation intention power value is adjusted in the opposite direction of the acceptable adjustment direction. The return adjustment amplitude is controlled within the preset return ratio of the local power adjustment interval. When the acceptable adjustment direction is to increase the output, the output is decreased downward. When the acceptable adjustment direction is to decrease the output, the output is increased upward; After return adjustment, one of the multiple secondary business feasible intervals closest to the current operation state power value is selected from the local pre-declared secondary business feasible intervals, and the operation intention power value after return adjustment is switched to the selected secondary business feasible interval as a new adjustment target; The operation intention corresponding to the new adjustment target is taken as the correction operation intention information. 8.The method of claim 1, wherein the method further comprises: determining a running state of each of the plurality of multi-agent services; and determining a running state of each of the plurality of multi-agent services based on the running state of each of the plurality of multi-agent services. When the correction operation intentions of the distributed business control centers reach a preset consistency condition, it is determined that a stable distributed collaborative operation state is formed, and specifically: The collaborative interaction layer continuously collects the correction operation intention information published by each distributed business control center; The correction operation intentions of adjacent periods are compared one by one, the average value of the change amplitudes of all subject intentions is calculated, and the average change amplitude is obtained; When the average change amplitude in the last three consecutive periods is less than a preset consistency threshold, it is determined that the correction operation intentions of all subjects have tended to be stable, and the current operation period state at this time is determined as a stable distributed collaborative operation state. 9.The method of claim 1, wherein the method further comprises: determining a running state of each of the plurality of multi-agent services; and determining a running state of each of the plurality of multi-agent services based on the running state of each of the plurality of multi-agent services. The correction operation intention information is mapped to specific operation control instructions and is executed, and specifically: After it is determined that a stable distributed collaborative operation state is formed, each distributed business control center reads the correction operation intention information in the stable state; According to the adjustment direction and the adjustment amplitude in the correction operation intention information, the power target set value of the device is calculated; The power target set value is converted into an output instruction of a source-side power generation device, a voltage control instruction of a network-side regulation and control device, a load instruction, and a charge and discharge power instruction of an energy storage device, and is respectively executed to the corresponding physical execution device to complete actual operation adjustment.

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