Electric power cooperative operation method, system and equipment based on new energy, and medium

Abstract

The invention discloses an electric power collaborative operation method, system and device based on new energy and a medium, and belongs to the technical field of electric power collaborative operation, and the method comprises the steps: obtaining the real-time output data of a new energy access point and the demand data of a load node, and constructing a collaborative operation unit according to the topological information of a power grid; evaluating the load regulation capability of each cooperative operation unit in combination with the new energy access condition, and generating a first regulation and control instruction; when the new energy load regulation capacity in the cooperative operation unit is insufficient, a second regulation and control instruction is generated; the scheduling process is monitored in real time, the cooperative operation strategy is dynamically corrected according to the difference between the new energy output and the load demand, and the overall operation efficiency of the power system is improved. According to the method, the cooperative operation unit is constructed, new energy output prediction and load regulation capability evaluation are fused, local quick response and cross-regional intelligent cooperation of new energy fluctuation are realized, and the operation flexibility and new energy consumption capability of a power system are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power coordinated operation, and in particular to a method, system, device and medium for electric power coordinated operation based on new energy. Background Art

[0002] With the large-scale integration of renewable energy sources such as wind power and photovoltaics, the power system is shifting from a traditional centralized, rigid power supply structure to a distributed, flexible, and coordinated one. Renewable energy sources are characterized by high output volatility and uncontrollability, and are easily affected by factors such as the meteorological environment, significantly increasing the difficulty of balancing the source and load of the power grid. Particularly within local regions, there is often a spatial and temporal mismatch between renewable energy output and load demand, resulting in localized oversupply or shortages. To ensure the safe and stable operation of the power system and enhance its capacity to absorb new energy, it is urgent to establish a new operating mechanism with dynamic perception, predictive regulation, and cross-regional coordination capabilities.

[0003] In existing technologies, power dispatching mainly relies on centralized control, which has a long response cycle and low accuracy, making it difficult to respond to the rapid fluctuations of new energy in a timely manner; at the same time, the utilization rate of adjustable resources on the load side is not high, and there is a lack of effective identification and call mechanisms, which makes it impossible to achieve flexible adjustment in local areas; in addition, energy coordination between different regions relies more on static communication channels and lacks intelligent cross-regional dynamic coordination mechanisms, resulting in low global resource utilization efficiency and affecting the level of new energy acceptance.

[0004] Therefore, it is urgent to propose a comprehensive control method that integrates prediction drive, local load regulation and multi-regional energy coordination to adapt to the operation needs of new power systems with a high proportion of new energy access. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is: how to solve the problem that the existing power dispatching mainly relies on centralized control, with a long control response cycle and low precision, and it is difficult to respond to the rapid fluctuations of new energy in a timely manner; at the same time, the utilization rate of adjustable resources on the load side is not high, and there is a lack of effective identification and calling mechanisms, which makes it impossible to achieve flexible adjustment in local areas; in addition, energy coordination between different regions relies more on static communication channels and lacks an intelligent cross-regional dynamic coordination mechanism, resulting in low global resource utilization efficiency and affecting the acceptance level of new energy.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a method for coordinated power operation based on new energy, which includes the following steps: obtaining real-time output data of new energy access points and demand data of load nodes, and constructing a coordinated operation unit based on power grid topology information; evaluating the load regulation capability of each coordinated operation unit in combination with the new energy access situation, generating a first control instruction, and scheduling the load with dispatchable characteristics in the load node to cope with fluctuations in new energy output; when the new energy load regulation capability within the coordinated operation unit is insufficient, generating a second control instruction, calling other coordinated operation units based on the cross-regional coordination mechanism to achieve energy distribution among multiple regions; monitoring the scheduling process in real time, and dynamically correcting the coordinated operation strategy based on the difference between new energy output and load demand, so as to improve the overall operation efficiency of the power system.

[0008] As a preferred embodiment of the method for coordinated power operation based on new energy sources described in the present invention, the method includes acquiring real-time output data of new energy access points and demand data of load nodes, including collecting real-time output power, operating status information, and geographic location information of the new energy access points, as well as real-time power demand data, load type information, and geographic location information of the load nodes; acquiring power grid topology information, including connection relationships and electrical parameters between nodes; constructing an electrical distance matrix based on the power grid topology information to identify electrical coupling relationships between new energy access points and load nodes; and dividing new energy access points with high electrical coupling and several load nodes into coordinated operation units based on the electrical coupling relationships and the operating characteristics of each node, wherein the coordinated operation units include at least one new energy access point and one or more load nodes; and each node includes a new energy access point and a load node.

[0009] As a preferred solution of the method for coordinated power operation based on new energy described in the present invention, the method comprises: generating a first control instruction, including, based on the real-time output power of the new energy access point, constructing an output prediction model to predict the short-term output change trend of the new energy; obtaining the current operating status and response capability parameters of the load with dispatchable characteristics in the load node within the coordinated operation unit, and evaluating the load regulation capability of the coordinated operation unit; calculating the regulation margin of the coordinated operation unit according to the matching relationship between the predicted short-term output change trend of the new energy and the load regulation capability; generating a first control instruction when the regulation margin of the coordinated operation unit satisfies the deviation compensation between the predicted short-term output of the new energy and the real-time electricity demand data of the load node, and sending start-stop control, power increase or decrease or peak-to-valley shifting instructions to the load with dispatchable characteristics in the load node, so as to realize load regulation within the coordinated operation unit and respond to the output fluctuation of the new energy.

[0010] As a preferred embodiment of the method for coordinated power operation based on new energy sources described in the present invention, the method further comprises: predicting the short-term output change trend of the new energy sources includes constructing an output prediction model using a time series model based on the real-time output power, resource characteristic parameters, and historical output data of the new energy access point, and predicting the output power change trend of the new energy sources within a preset time window; and calculating the regulation margin includes separately calculating the upward power and downward power of the loads with dispatchable characteristics in the load nodes within the coordinated operation unit, and determining the regulation margin at the current moment based on the short-term output change trend of the new energy sources predicted by the new energy access point.

[0011] As a preferred solution of the electric power collaborative operation method based on new energy described in the present invention, the insufficient load regulation capability includes judging the energy balance state of the current collaborative operation unit based on the predicted short-term output change trend of the new energy, the real-time output power and the currently executed load regulation; if the actual output of the current new energy is lower than the total load demand, and the current regulation margin cannot cover the difference, or it is predicted that the new energy will continue to fluctuate in the short term, exceeding the maximum load regulation range, or the load response is delayed or the unavailable ratio increases, resulting in the inability to execute the regulation command in time, then it is determined that the internal regulation capability of the collaborative operation unit is insufficient.

[0012] As a preferred solution of the method for coordinated power operation based on new energy described in the present invention, the generating of the second control instruction includes sending a dispatch request to other coordinated operation units when insufficient load regulation capability is detected, the dispatch request including power gap, request time limit, acceptable support mode and support priority information; determining other coordinated operation units to be supported based on the received dispatch request information, combined with the current regulation margin of other coordinated operation units, the capacity constraint of the power grid transmission path, the electrical distance and the response capability parameters; generating a second control instruction, and issuing the second control instruction to other coordinated operation units to support, so as to realize dynamic energy distribution and regulation between regions.

[0013] As a preferred solution of the new energy-based electric power collaborative operation method described in the present invention, the real-time monitoring includes real-time monitoring of the actual output of the new energy access point in the collaborative operation unit and the response results of the load node to the first control instruction or the second control instruction; based on the difference between the predicted output and the actual output of the new energy access point, and the difference between the expected response and the actual execution of the dispatchable load in the collaborative operation unit, the power imbalance of the current collaborative operation unit is calculated; when the power imbalance exceeds a preset threshold, the current collaborative operation strategy is dynamically corrected, including adjusting the execution parameters of the control instruction and reallocating the regulation tasks between the collaborative operation units, so as to improve the overall operation efficiency of the power system.

[0014] Another object of the present invention is to provide a power coordinated operation system based on new energy.

[0015] To solve the above technical problems, the present invention provides the following technical solutions: a new energy-based power collaborative operation system, comprising: a collaborative operation unit construction module, a first control module, a second control module and a correction module; the collaborative operation unit construction module is used to obtain real-time output data of new energy access points and demand data of load nodes, and construct a collaborative operation unit based on power grid topology information; the first control module is used to evaluate the load regulation capability of each collaborative operation unit in combination with the new energy access situation, generate a first control instruction, and dispatch the load with dispatchable characteristics in the load node to cope with fluctuations in new energy output; the second control module is used to generate a second control instruction when the new energy load regulation capability within the collaborative operation unit is insufficient, and call other collaborative operation units based on the cross-regional collaborative mechanism to realize energy distribution among multiple regions; the correction module is used to monitor the scheduling process in real time, and dynamically correct the collaborative operation strategy according to the difference between new energy output and load demand, so as to improve the overall operation efficiency of the power system.

[0016] The present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method for coordinated operation of electric power based on new energy are implemented.

[0017] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for coordinated operation of electric power based on new energy are implemented.

[0018] Beneficial effects of the present invention: The present invention realizes local rapid response and cross-regional intelligent coordination of new energy fluctuations by constructing collaborative operation units and integrating new energy output forecasting and load regulation capability evaluation, effectively improving the operational flexibility and new energy absorption capacity of the power system.

[0019] The present invention collects the operating status, geographic information and grid topology of new energy access points and load nodes, and constructs a collaborative operation unit based on the electrical coupling relationship, so that new energy and loads have regional binding characteristics, which facilitates the implementation of regional autonomous regulation and improves the response efficiency of the local system.

[0020] The present invention combines the prediction of new energy output with the real-time capacity assessment of adjustable loads, calculates the regulation margin, and actively generates the first regulation instruction to achieve precise matching of local sources and loads, avoid waste of new energy, and reduce dependence on external support.

[0021] When the regulation demand cannot be met within the collaborative operation unit, a second regulation instruction can be automatically generated. Through inter-regional scheduling requests and support matching, the energy distribution among multiple units can be coordinated to form cross-regional flexible mutual assistance and enhance the overall operational stability of the system.

[0022] During operation, the present invention monitors renewable energy output, load response, and transmission status in real time, calculates power imbalance based on prediction and execution deviation, dynamically adjusts control strategies, and realizes adaptive optimization of scheduling instructions, prediction models, and control cycles.

[0023] The present invention can be widely used in scenarios such as distribution networks, microgrids, and regional power grids where wind power and photovoltaic power account for a high proportion, thereby improving the system's ability to handle the uncertainty of new energy and achieving the goal of safe, efficient, and low-carbon power operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 The present invention provides an overall flow chart of a method for coordinated operation of electric power based on new energy sources according to an embodiment of the present invention.

[0026] Figure 2 A system solution module diagram of a new energy-based electric power coordinated operation system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0027] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0028] Example 1, with reference to Figure 1 , which is the first embodiment of the present invention, provides a method for coordinated operation of electric power based on new energy, including:

[0029] With the large-scale integration of renewable energy sources such as wind power and photovoltaics, grid output volatility has increased, leading to frequent source-load imbalances. Traditional centralized dispatch models, with their delayed response and limited control range, struggle to meet the flexibility and intelligence demands of the new power system. Against the backdrop of uncertain renewable energy output, underutilized load-side resource regulation capabilities, and imperfect inter-regional dispatch mechanisms, power system operations face significant challenges such as reduced reliability, wasted resources, and low dispatch efficiency.

[0030] Therefore, to address the aforementioned issues of unstable grid operation, delayed control response, and weak overall system coordination capabilities under the integration of new energy, a new energy-based power coordinated operation method described in this embodiment is proposed. The following steps are used to achieve rapid perception of new energy fluctuations, local regulation, and cross-regional energy coordination, thereby improving system operation efficiency and new energy absorption capabilities:

[0031] S1. Obtain real-time output data of new energy access points and demand data of load nodes, and build collaborative operation units based on grid topology information.

[0032] S2. Evaluate the load regulation capability of each collaborative operation unit based on the new energy access situation, generate a first control instruction, and dispatch the load with dispatchable characteristics in the load node to cope with the fluctuation of new energy output.

[0033] S3. When the new energy load regulation capacity within the collaborative operation unit is insufficient, a second control instruction is generated, and other collaborative operation units are called based on the cross-regional collaborative mechanism to achieve energy distribution among multiple regions.

[0034] S4. Monitor the dispatching process in real time and dynamically adjust the coordinated operation strategy based on the difference between renewable energy output and load demand to improve the overall operating efficiency of the power system.

[0035] Example 2, reference Figure 1 , which is the second embodiment of the present invention, provides a method for coordinated operation of electric power based on new energy based on the above embodiment.

[0036] In the embodiment of the present application, step S1 collects the real-time output power, operating status information and geographic location information of the new energy access points, as well as the real-time power demand data, load type information and geographic location information of the load nodes; the new energy access points include photovoltaic power stations, wind farms, energy storage systems, etc., and the load nodes include industrial users, residential communities, commercial complexes, etc.

[0037] In an optional embodiment, the information of all nodes can be collected through the SCADA (Supervisory Control and Data Acquisition) system and the user-side smart terminal. New energy access points are usually deployed with a SCADA system for real-time monitoring of the operating status and power output of the station. The SCADA system is connected to the on-site sensors through the acquisition terminal to obtain the active power, reactive power, equipment status, fault information, and environmental parameters (including wind speed, irradiance, temperature, etc.) of each new energy equipment in real time. The collected data is uploaded to the dispatching control center or cloud platform through a communication link (including optical fiber, industrial Ethernet or 4G / 5G private network). The control system completes the real-time collection and update of data from the new energy access point by docking with the interface protocol of the SCADA platform, which is used for subsequent collaborative operation unit construction and control decision-making.

[0038] On the load node side, real-time electricity consumption data collection can be achieved by deploying user intelligent power management terminals. This terminal is generally integrated into the advanced metering infrastructure or energy management system and has collection, storage, communication and control functions. The terminal obtains real-time data such as the operating status, active / reactive power, load type, voltage and current of various electrical equipment through smart meters or load monitoring modules. At the same time, the terminal can collect dispatchability information of user loads, such as response level, equipment control authority, adjustment time window, etc. The collected data is transmitted back to the regional control node or cloud platform through the edge communication module. After summarizing and analyzing, the system uses it to identify load nodes with dispatchable characteristics and evaluate their response capabilities for participating in collaborative operations.

[0039] Obtain grid topology information, including the connection relationship between nodes and electrical parameters such as line impedance, voltage level, substation ownership, etc.

[0040] Based on the aforementioned grid topology information, an electrical distance matrix is ​​constructed to assess the electrical coupling between renewable energy access points and load nodes. Electrical distance is a measure of the strength of the power transmission coupling between two nodes. It is typically calculated based on equivalent impedance or power flow sensitivity and is used to determine the ease of energy exchange and regulatory response between different nodes.

[0041] In an optional embodiment, based on the electrical distance of equivalent impedance, the total number of nodes in the power system is n, and its node admittance matrix Y is constructed. bus , and then find its inverse to get the node impedance matrix Z bus , expressed as:

[0042]

[0043] Among them, Z bus is the node impedance matrix, is the inverse of the node admittance matrix.

[0044] For any two nodes i and j, their electrical distance D ij It can be expressed as:

[0045] D ij =|Z ii +Z jj -2Z ij |

[0046] Among them, D ij is the electrical distance between any two nodes i and j, Z ii is the self-impedance of node i, Z jj is the self-impedance of node j, Z ij is the impedance between nodes i and j.

[0047] In another optional embodiment, an electrical distance based on power flow sensitivity is defined based on the sensitivity of power flow changes between nodes to power injection, and is expressed as:

[0048]

[0049] Where θ is the voltage phase angle and P is the active power.

[0050] By calculating D for all new energy access points and load nodes ij , an electrical distance matrix can be constructed:

[0051]

[0052] The rows represent m new energy access points, and the columns represent n load nodes.

[0053] Based on the electrical coupling relationship and the operating characteristics of each node, new energy access points with high electrical coupling and several load nodes are divided into collaborative operation units. A collaborative operation unit consists of at least one new energy access point and one or more load nodes. It has a certain degree of internal supply and demand self-balancing capability and can independently undertake some new energy regulation tasks, reducing reliance on unified scheduling across the entire network.

[0054] Set the electrical distance threshold. ij When the electrical distance is less than or equal to the electrical distance threshold, it is considered that the electrical coupling between nodes i and j is high and they can be classified into the same collaborative operation unit.

[0055] Each node includes a new energy access point and a load node.

[0056] Node operational characteristics include capacity (such as maximum output and maximum load), dispatchability (whether it possesses responsive control capabilities), and the degree of electrical coupling with other nodes in the grid. These parameters are used to determine the node's role and regulatory value in coordinated operation and guide the rationality of unit division.

[0057] In the embodiment of the present application, in step S2:

[0058] Based on the real-time output power of new energy access points, an output prediction model is constructed to predict the short-term output change trend of new energy. Based on the real-time output power, resource characteristic parameters and historical output data of new energy access points, an output prediction model is constructed using a time series model to predict the output power change trend of new energy within a preset time window.

[0059] Specifically, an output prediction model is constructed based on the real-time output power of renewable energy access points. This model utilizes the current operating status data (such as active power and reactive power), resource characteristic parameters (such as wind speed, solar irradiance, and ambient temperature), and historical operating data of renewable energy access points. It employs time series forecasting methods (such as ARIMA and LSTM) to create a model that predicts the output trends of renewable energy in the short term, forming a predicted output curve that serves as the basis for control input.

[0060] In an optional embodiment, an autoregressive moving average model is used to construct an output forecast model, which is applicable to output time series with trend and autocorrelation characteristics and is suitable for modeling short-term changes in photovoltaic or wind power under relatively stable weather conditions. It is expressed as:

[0061] Φ(B)(1-B) d P(t)=Θ(B)ε(t)

[0062] Where P(t) is the actual output of renewable energy at time t, B is the hysteresis factor, BP(t) = P(t-1), d is the difference order used to eliminate non-stationarity, and ε() is white noise.

[0063] Φ(B)=1-φ1B-φ2B 2 -…-φ p B p

[0064] Θ(B)=1+θ1B+θ2B 2 +…+θ q B q

[0065] Among them, Φ(B) is the autoregressive part and Θ(B) is the moving average part.

[0066] The power output at the next short time t+Δt is predicted by fitting the model parameters using the historical output power sequence P(tn)~P(t) of the new energy access point in the past.

[0067] In another optional embodiment, a seasonal exponential smoothing model is used to construct an output forecasting model, which is suitable for scenarios where the output of renewable energy has periodic fluctuation characteristics. It is a weighted recursive smoothing forecasting model, which is expressed as:

[0068]

[0069] Among them, L t is the smoothed output level, T t is the trend term, S t is a seasonal term (with a period of s, such as 24 hours per day for photovoltaics), α, β, and γ are smoothing coefficients, and m is the prediction time step. This method predicts renewable energy output at the mth step in the future. It is suitable for predicting the periodic changes in photovoltaic output over different time periods. Combined with real-time irradiance correction, it can effectively track power generation fluctuations under changing sunshine trends.

[0070] Obtain the current operating status and response capability parameters of the loads with dispatchable characteristics in the load nodes within the collaborative operation unit, and evaluate the load regulation capability of the collaborative operation unit.

[0071] Specifically, the current operating status and response capability parameters of dispatchable loads within the coordinated operation unit are obtained. Dispatched loads include industrial interruptible loads, electric vehicle charging loads, building air conditioning systems, water heaters, and others. Response capability parameters include maximum adjustable power, response delay, maximum adjustment duration, and adjustment direction (upward / downward). Operating status includes whether the load is currently running, whether it is adjustable, and remaining adjustment capacity.

[0072] In an optional embodiment, suppose there are N load nodes in the collaborative operation unit, and each load node has M i The parameters of the qth adjustable load device in the pth load node are as follows:

[0073] Current operating power:

[0074] Minimum power allowed (load lower limit):

[0075] Maximum power allowed (load limit):

[0076] The upward adjustment capacity (reduction amount) is:

[0077]

[0078] The downward adjustment capacity (increase amount) is:

[0079]

[0080] The load regulation capability of the entire coordinated operation unit is:

[0081]

[0082] in, is the total adjustable capacity of the collaborative operation unit, It is the total adjustable capacity of the collaboratively operated units.

[0083] Based on the matching relationship between the predicted short-term output change trend of renewable energy and the load regulation capability, the regulation margin of the collaborative operation unit is calculated. The upward and downward power regulation of the load with dispatchable characteristics in the load nodes within the collaborative operation unit are calculated separately, and the regulation margin at the current moment is determined based on the predicted short-term output change trend of renewable energy at the renewable energy access point.

[0084] Specifically, the regulation margin of the current collaborative unit is calculated based on the matching relationship between the predicted trend of renewable energy output and the load regulation capability. The regulation margin is divided into upward and downward margins, representing the adjustable power capacity that can be released or absorbed without affecting the normal energy consumption of users.

[0085] In an optional embodiment, the adjustment margin reflects the total adjustable capacity of the cooperative operation unit at the current time point that can be used to cope with the fluctuation of new energy, which is generally divided into an upward adjustment margin and a downward adjustment margin. The current adjustment margin is determined according to the predicted fluctuation direction of the new energy, and is expressed as:

[0086]

[0087] Among them, M adj To adjust the margin.

[0088] When the adjustment margin of the collaborative operation unit satisfies the deviation compensation between the predicted short-term output of renewable energy and the real-time electricity demand data of the load node, a first control instruction is generated, and a start-stop control, power increase or decrease, or peak-to-valley shifting instruction is issued to the load with dispatchable characteristics in the load node to realize the internal load adjustment of the collaborative operation unit and respond to the fluctuation of renewable energy output.

[0089] Specifically, when the aforementioned regulation margin is sufficient to compensate for the deviation between the predicted short-term output of renewable energy and the predicted short-term output of renewable energy, a first regulation instruction is generated. This first regulation instruction, which includes start-stop control, power ramping, peak-to-valley shifting, and other methods, is tailored to the regulation capability characteristics of a specific adjustable load. This instruction is sent to specific load terminals via a load aggregation platform or edge controller, driving them to participate in local regulation according to a specified strategy, absorb fluctuations in renewable energy, and achieve energy self-balancing within the collaborative operation unit.

[0090] In an optional embodiment, assume that a building load node within the collaborative operation unit has the following adjustable equipment: an air-conditioning group with a total load of 300kW, of which 100kW is adjustable and supports a temperature setting range of ±2°C; an electric vehicle charging station with a current power of 80kW, which can be increased to a maximum of 120kW, or decreased to 50kW.

[0091] It is predicted that the output of renewable energy will drop by 150kW in the next 10 minutes. After the adjustment margin is evaluated to meet the compensation demand, the following first control instruction is generated as shown in Table 1.

[0092] Table 1 Example of the first control instruction

[0093]

[0094]

[0095] A total of 100kW of load is released, partially offsetting the 150kW fluctuation in power consumption at the renewable energy access point due to reduced sunlight. The remaining power consumption can be compensated by energy storage or inter-regional compensation.

[0096] In the embodiment of the present application, in step S3:

[0097] Based on the predicted short-term output change trend of new energy, real-time output power and the currently executed load regulation, the energy balance status of the current collaborative operation unit is judged; if the actual output of the current new energy is lower than the total load demand, and the current regulation margin cannot cover the difference, or it is predicted that the new energy will continue to fluctuate in the short term, exceeding the maximum load regulation range, or the load response is delayed or the unavailable ratio increases, resulting in the inability to execute the regulation command in a timely manner, then it is determined that the internal regulation capacity of the collaborative operation unit is insufficient.

[0098] In an optional embodiment, during the coordinated operation process, it is determined whether the coordinated operation unit has insufficient adjustment capability according to the following formula:

[0099] If the difference between the actual output of renewable energy P(t) and the load demand D(t) ΔP(t) = D(t) - P(t) exceeds the current regulation margin M adj (t), that is:

[0100] ΔD(t)>M adj (t)

[0101] Or if the new energy output is predicted Unable to cover future load demand and meet the following requirements:

[0102]

[0103] Or if some adjustable loads fail to respond, resulting in a reduction in actual regulation capability, then calculate the effective regulation margin when:

[0104]

[0105] It is considered to be insufficient regulatory capacity.

[0106] When insufficient load regulation capability is detected, a dispatch request is sent to other collaborative operation units, the dispatch request including power gap, request time limit, acceptable support mode and support priority information; based on the received dispatch request information, combined with the current regulation margin of other collaborative operation units, the capacity constraint of the power grid transmission path, the electrical distance and the response capability parameters, the other collaborative operation units to be supported are determined; a second regulation instruction is generated and issued to the other collaborative operation units to achieve dynamic energy allocation and regulation between regions.

[0107] Specifically, after determining that the regulation capacity is insufficient, the cross-region coordination mechanism is activated to generate a second regulation instruction to achieve multi-region energy optimization and allocation. Specifically, it includes:

[0108] A dispatch request is sent to other collaborative operation units, which includes the current power gap (in MW or kW), the request response time limit (such as completing support within 5 minutes), the acceptable support method (increasing power supply or reducing remote loads), and the control priority information (used to optimize the resource call order); after receiving the dispatch request, the regional control platform evaluates the operating status of other collaborative operation units, including: the output and trend of the current new energy access point; the regulation margin of the load nodes within the unit; the available transmission capacity, line impedance, and voltage stability constraints of the support path in the grid topology; the response time and regulation continuity capability of the participating support, etc.

[0109] After comprehensive evaluation, one or more support units with regulation capabilities are selected, and second control instructions are generated and issued separately. The specific contents include: instructing the support unit to increase local renewable energy output (such as increasing wind power / photovoltaic output, releasing stored energy); or reducing local load, releasing power capacity, and supporting the target unit through the grid transmission path; at the same time, receiving support instructions are issued to the original target unit to adjust the load power distribution strategy and complete energy docking.

[0110] Through the above mechanism, when local regulation capabilities cannot meet the supply and demand matching requirements, it can dynamically link resources between multiple collaborative operation units to complete inter-regional optimized response to fluctuations in new energy output, thereby improving the overall power grid's carrying capacity for new energy fluctuations and system-level operating efficiency.

[0111] In the embodiment of the present application, in step S4:

[0112] The actual output of the new energy access point within the collaborative operation unit and the response results of the load node to the first control instruction or the second control instruction are monitored in real time.

[0113] Based on the difference between the predicted output and the actual output of the new energy access point, and the difference between the expected response and the actual execution of the dispatchable load in the collaborative operation unit, the power imbalance of the current collaborative operation unit is calculated.

[0114] When the power imbalance exceeds the preset threshold, the current collaborative operation strategy is dynamically corrected, including adjusting the execution parameters of the control instructions and reallocating the regulation tasks between the collaborative operation units to improve the overall operation efficiency of the power system.

[0115] In an optional embodiment, in a scenario of new energy fluctuations, real-time monitoring needs to continuously track the operating status of each core element in the collaborative operation unit, including the output changes of the new energy access point, the response of the load node to the control instructions, and the power transmission status on the transmission path, so as to fully grasp the deviation between the execution results and the expected strategy during the system operation process, and provide basic data support for subsequent corrections to the control strategy.

[0116] Real-time monitoring includes the following data collection objects: actual output P(t) of the new energy access point within the collaborative operation unit; predicted output at the same time point; The actual response power change of the load node after receiving the first control instruction or the second control instruction; the response amplitude, response delay and incomplete ratio of the dispatchable load; the actual power flow and line capacity constraint status of the transmission path.

[0117] Through the above monitoring data, the new energy prediction error ε is calculated in real time gen (t) and load response error ε load (t), respectively represents the degree of deviation between the output of new energy and load execution and the dispatch target, and the calculation formula is as follows:

[0118]

[0119] ε load (t) = R expected (t)-R actual (t)

[0120] Among them, R expected (t) is the target response power of the expected regulation afterload, R actual (t) is the actual power regulation amount occurring at the load node.

[0121] Furthermore, the power imbalance ΔP is calculated imb (t), used to assess whether the collaborative operation unit is in an unbalanced state:

[0122] ΔP imb (t) = D(t) - P(t) - R actual (t)

[0123] When the power imbalance ΔP imb (t) exceeds the preset threshold. In this embodiment, 5% of the rated power is selected, that is:

[0124] |ΔP imb (t)|>δ th

[0125] It is determined that the current control strategy has not achieved the expected effect, and the current collaborative operation strategy needs to be dynamically revised.

[0126] The content of the revised strategy includes but is not limited to:

[0127] Adjust the control instruction parameters, such as increasing the load adjustment range, adjusting the control priority, or increasing the issuance frequency.

[0128] Redistribute the regulation tasks and reallocate the load regulation targets according to the current status and remaining regulation capacity of each load node.

[0129] Activate backup resources, such as calling on energy storage systems and adding local power regulation equipment to participate in regulation.

[0130] Optimize the control cycle, shorten the feedback loop time, and improve the strategy response speed.

[0131] Correct the prediction model parameters based on the current deviation The prediction model is retrained or revised to improve prediction accuracy.

[0132] Through the above-mentioned real-time deviation analysis and strategy adaptive correction mechanism, the supply and demand balance of the collaborative operation units can be continuously maintained when the new energy output changes rapidly or the load side response capability is unstable, thereby improving the utilization efficiency of new energy resources and the overall operation stability of the system.

[0133] Example 3 is the third embodiment of the present invention, which differs from the first two embodiments in that:

[0134] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0135] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0136] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0137] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0138] Example 4, with reference to Figure 2 , which is the fourth embodiment of the present invention, provides a power cooperative operation system based on new energy, including a cooperative operation unit construction module, a first control module, a second control module and a correction module.

[0139] The collaborative operation unit construction module is used to obtain the real-time output data of the new energy access point and the demand data of the load node, and to construct the collaborative operation unit according to the grid topology information.

[0140] The first control module is used to evaluate the load regulation capability of each collaborative operation unit in combination with the new energy access situation, generate a first control instruction, and schedule the load with dispatchable characteristics in the load node to cope with fluctuations in new energy output.

[0141] The second control module is used to generate a second control instruction when the new energy load regulation capacity within the collaborative operation unit is insufficient, and call other collaborative operation units based on the cross-regional collaborative mechanism to achieve energy distribution among multiple regions.

[0142] The correction module is used to monitor the dispatching process in real time and dynamically correct the coordinated operation strategy based on the difference between renewable energy output and load demand, thereby improving the overall operating efficiency of the power system.

[0143] 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 the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for coordinated operation of electric power based on new energy, characterized by: include, Obtain real-time output data from new energy access points and demand data from load nodes, and build collaborative operation units based on grid topology information; Evaluate the load regulation capabilities of each collaborative operation unit based on the access status of new energy, generate a first control instruction, and dispatch the loads with dispatchable characteristics in the load nodes to cope with fluctuations in new energy output; When the new energy load regulation capacity within the coordinated operation unit is insufficient, a second control instruction is generated, and other coordinated operation units are called based on the cross-regional coordination mechanism to achieve energy distribution among multiple regions; The dispatching process is monitored in real time, and the coordinated operation strategy is dynamically modified based on the difference between renewable energy output and load demand to improve the overall operating efficiency of the power system.

2. The method for coordinated operation of electric power based on new energy sources according to claim 1, characterized in that: The real-time output data of the new energy access point and the demand data of the load node are obtained. include, Collect real-time output power, operating status information and geographic location information of new energy access points, as well as real-time power demand data, load type information and geographic location information of load nodes; Obtain grid topology information, including the connection relationship and electrical parameters between nodes; Based on the grid topology information, an electrical distance matrix is ​​constructed to identify the electrical coupling relationship between the new energy access points and the load nodes; Based on the electrical coupling relationship and the operating characteristics of each node, the new energy access point with a high electrical coupling degree and several load nodes are divided into a collaborative operation unit, wherein the collaborative operation unit includes at least one new energy access point and one or more load nodes; The nodes include new energy access points and load nodes.

3. The method for coordinated operation of electric power based on new energy as claimed in claim 2, characterized in that: The generating of the first control instruction includes: Based on the real-time output power of new energy access points, an output prediction model is constructed to predict the short-term output change trend of new energy; Obtain the current operating status and response capability parameters of the dispatchable loads in the load nodes within the collaborative operation unit, and evaluate the load regulation capability of the collaborative operation unit; Calculate the regulation margin of the coordinated operation unit based on the matching relationship between the predicted short-term output change trend of new energy and the load regulation capability; When the adjustment margin of the collaborative operation unit satisfies the deviation compensation between the predicted short-term output of renewable energy and the real-time electricity demand data of the load node, a first control instruction is generated, and a start-stop control, power increase or decrease, or peak-to-valley shifting instruction is issued to the load with dispatchable characteristics in the load node to realize the internal load adjustment of the collaborative operation unit and respond to the fluctuation of renewable energy output.

4. The method for coordinated operation of electric power based on new energy sources according to claim 3, characterized in that: The prediction of short-term output change trends of renewable energy sources includes building an output prediction model using a time series model based on the real-time output power, resource characteristic parameters, and historical output data of renewable energy access points to predict the output power change trends of renewable energy sources within a preset time window. The calculation of the regulation margin includes respectively calculating the upward power and downward power of the load with dispatchable characteristics in the load node within the cooperative operation unit, and determining the regulation margin at the current moment according to the short-term output change trend of the predicted new energy source at the new energy access point.

5. The method for coordinated operation of electric power based on new energy as claimed in claim 4, characterized in that: The insufficient load regulation capability includes judging the energy balance state of the current collaborative operation unit based on the predicted short-term output change trend of the new energy, the real-time output power and the currently executed load regulation; If the actual output of current renewable energy is lower than the total load demand, and the current regulation margin cannot cover the difference, or it is predicted that renewable energy will continue to fluctuate in the short term, exceeding the maximum load regulation range, or the load response is delayed or the unavailable ratio increases, resulting in the inability to execute the regulation command in a timely manner, it is deemed that the internal regulation capacity of the collaborative operation unit is insufficient.

6. The method for coordinated operation of electric power based on new energy sources according to claim 4, characterized in that: Generating the second control instruction includes sending a scheduling request to other coordinated operation units when insufficient load regulation capability is detected, wherein the scheduling request includes power gap, request time limit, acceptable support mode and support priority information; Determine other coordinated operation units to support based on the received dispatch request information and the current regulation margins of other coordinated operation units, the capacity constraints of the power grid transmission paths, the electrical distances, and the response capability parameters; Generate a second control instruction and issue it to other supporting collaborative operation units to achieve dynamic energy distribution and regulation among regions.

7. The method for coordinated operation of electric power based on new energy sources according to claim 4, characterized in that: The real-time monitoring includes real-time monitoring of the actual output of the new energy access point in the collaborative operation unit and the response result of the load node to the first control instruction or the second control instruction; Calculate the power imbalance of the current collaborative operation unit based on the difference between the predicted output and the actual output of the new energy access point, and the difference between the expected response and the actual execution of the dispatchable load in the collaborative operation unit; When the power imbalance exceeds the preset threshold, the current collaborative operation strategy is dynamically corrected, including adjusting the execution parameters of the control instructions and reallocating the regulation tasks between the collaborative operation units to improve the overall operation efficiency of the power system.

8. A power coordinated operation system based on new energy, applying the power coordinated operation method based on new energy as claimed in any one of claims 1 to 7, characterized in that: include: A collaborative operation unit construction module, a first control module, a second control module and a correction module; The collaborative operation unit construction module is used to obtain real-time output data of new energy access points and demand data of load nodes, and to construct collaborative operation units based on power grid topology information; The first control module is used to evaluate the load regulation capability of each collaborative operation unit in combination with the new energy access situation, generate a first control instruction, and dispatch the load with dispatchable characteristics in the load node to cope with the fluctuation of the new energy output; The second control module is used to generate a second control instruction when the new energy load regulation capacity within the coordinated operation unit is insufficient, and call other coordinated operation units based on the cross-region coordination mechanism to achieve energy distribution among multiple regions; The correction module is used to monitor the dispatching process in real time and dynamically correct the coordinated operation strategy according to the difference between the output of new energy and the load demand, so as to improve the overall operation efficiency of the power system.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the electric power coordinated operation method based on new energy are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for coordinated operation of electric power based on new energy sources according to any one of claims 1 to 7 are implemented.

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