CN118117571A - Digital double-agent power grid power tracking and adjusting method, system, equipment and medium - Google Patents
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Abstract
A digital double-agent power grid power tracking and adjusting method, a system, equipment and a medium belong to the technical field of power grid power adjustment, and the method comprises the steps of establishing a digital twin-based distributed power tracking model according to a communication network among different modulation and control resources, setting constraint conditions for the digital twin-based distributed power tracking model, and establishing an objective function; and carrying out algorithm design on the distributed power supply tracking model based on digital twinning by using a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus. The invention adopts the digital twin based on the equipment level to monitor the power tracking signal from physical to computer aided design, can quickly obtain the optimal scheduling scheme for real-time power tracking, combines the distributed power tracking method with a communication network, can improve the calculation efficiency, protects the privacy of the supervision resources, and is more suitable for the communication between the supervision resources.
Description
Technical Field
The invention belongs to the technical field of power regulation of a power grid, and particularly relates to a digital double-agent power grid power tracking and regulating method, a system, equipment and a medium.
Background
With the development of new energy, more and more supervision resources participate in power tracking. The conventional power tracking model only considers one centralized controller and gives the optimal algorithm for the independent system operators. With the increase of adjustment resources, the calculation cost of dynamic power tracking optimization also increases greatly. This means that it is difficult to obtain a high quality scheduling scheme with the conventional centralized controller-based power tracking method. Today, with advances in electronics and software, digital twin agents can be considered as digital counterparts to the optimization, control and monitoring processes of real-world power grids. Meanwhile, a distributed power tracking framework is provided to reduce the calculation cost and accelerate the optimization speed. Digital twinning is a good tool for integrating reality and virtualization, and it can manage intelligence more effectively. Currently, there have been some studies to combine the grid with digital twinning technology.
Power tracking of the grid is a nonlinear, multi-constraint and time series problem. For these application scenarios, a centralized-based power tracking method, such as a data planning method or a heuristic algorithm, is generally adopted to obtain a high-quality scheduling scheme. With the decentralization of the power grid and the expansion of the adjustment resources, the traditional method has difficulty in quickly obtaining a global optimal scheme within a preset time.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a digital double-agent power grid power tracking and adjusting method, a system, equipment and a medium, which can quickly obtain an optimal scheduling scheme for real-time power tracking.
In order to achieve the above purpose, the present invention has the following technical scheme:
in a first aspect, a digital dual-proxy power grid power tracking adjustment method is provided, including:
Establishing a distributed power supply tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions for the distributed power supply tracking model based on digital twin, and establishing an objective function;
And carrying out algorithm design on the distributed power supply tracking model based on digital twinning by using a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
In the step of establishing the distributed power supply tracking model based on digital twinning according to the communication network among different modulation resources, the modulation resources comprise modulation resources, one modulation resource is selected as a consensus leader for optimization, and the other modulation resource is selected as a consensus follower.
As a preferable solution, in the step of setting constraint conditions for the distributed power supply tracking model based on digital twin, the constraint conditions include adjustment direction constraint, power balance constraint, power generation capacity constraint and power generation slope constraint, and specific meanings and expressions of the constraint conditions are as follows:
Adjusting direction constraint:
The adjustment direction of the resource power command is the same as the adjustment direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
the summation of the power adjustment input commands received by all the power tracking model adjustment resources is equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
The power tracking model adjusts the power adjustment command obtained by the resource not to exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
As a preferred embodiment, in the step of creating an objective function, an expression of the objective function is as follows:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
In the step of carrying out algorithm design on the distributed power tracking model based on digital twinning through the device-level digital twinning agent algorithm based on distributed consensus control, as a preferred scheme, an adjusting resource is taken as a node or an agent, the expression of a communication network is G= (V, E, W), a node set V= { V 1,V2,…,Vn } is a set of the adjusting resource or a digital agent, and the setting of edges is carried outRepresenting the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
As a preferred scheme, the step of carrying out algorithm design on the distributed power tracking model based on digital twin through the device-level digital twin proxy algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus is represented by the following operations according to the proposed communication network and matrix based on the device-level digital twin proxy algorithm of distributed consensus control:
Payment compensation consensus:
The update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
Modifying the regulated resource that is not subject to the power constraint to a feasible region of the solution while focusing on the feasible range of the compensation payment, the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
In a second aspect, a digital dual agent power grid power tracking regulation system is provided, comprising:
The power tracking model setting module is used for establishing a distributed power tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions for the distributed power tracking model based on digital twin and establishing an objective function;
The distributed consensus control calculation module is used for carrying out algorithm design on the distributed power supply tracking model based on digital twinning through a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
As a preferable scheme, when the power tracking model setting module establishes a distributed power tracking model based on digital twin according to a communication network among different modulation resources, the modulation resources comprise modulation resources, one modulation resource is selected as a consensus leader for optimization, and the other modulation resource is selected as a consensus follower.
As a preferable scheme, when the power tracking model setting module sets constraint conditions for the distributed power tracking model based on digital twin, the constraint conditions comprise adjustment direction constraint, power balance constraint, power generation capacity constraint and power generation slope constraint, and the specific meaning and expression of each constraint condition are as follows:
Adjusting direction constraint:
The adjustment direction of the resource power command is the same as the adjustment direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
the summation of the power adjustment input commands received by all the power tracking model adjustment resources is equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
The power tracking model adjusts the power adjustment command obtained by the resource not to exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
As a preferred scheme, the power tracking model setting module sets up an objective function according to the following expression:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
As a preferable scheme, the distributed consensus control calculation module uses the regulated resource as a node or proxy when carrying out algorithm design on the distributed power tracking model based on digital twin through a device digital twin proxy algorithm based on distributed consensus control, the expression of the communication network is G= (V, E, W), the node set V= { V 1,V2,…,Vn } is a set of regulated resources or a digital proxy, and the setting of the edgeRepresenting the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
As a preferred solution, the distributed consensus control calculation module represents the device-level digital twin proxy algorithm based on distributed consensus control according to the proposed communication network and matrix by:
Payment compensation consensus:
The update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
Modifying the regulated resource that is not subject to the power constraint to a feasible region of the solution while focusing on the feasible range of the compensation payment, the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the digital dual-agent power grid power tracking adjustment method when executing the computer program.
In a fourth aspect, a computer readable storage medium is provided, where a computer program is stored, where the computer program when executed by a processor implements the digital dual agent grid power tracking adjustment method.
Compared with the prior art, the first aspect of the invention has at least the following beneficial effects:
The digital double-agent power grid power tracking adjustment method of the invention can rapidly obtain the optimal scheduling scheme for real-time power tracking by monitoring the power tracking signal from physics to computer aided design by better adopting digital twin based on equipment level. The invention combines the distributed power tracking method with the communication network by utilizing a distributed power tracking model (DT-DPT) based on digital twinning and a device digital twinning agent Algorithm (Distributed Consensus Control-based Algorithm, DCCA) based on distributed consensus control, thereby improving the calculation efficiency and protecting the privacy of the supervision resources. The distributed consensus method can perform rapid calculation, and the consensus algorithm based on the communication network is more suitable for the communication between the supervision resources. Therefore, the invention adopts the consensus control algorithm, and can quickly obtain the high-performance power tracking scheme with digital double agents.
Furthermore, the invention provides a power tracking model based on a digital twin agent, which designs the life cycle of power tracking from aspects of disturbance acquisition, controller strategy optimization, resource response adjustment, dynamic control performance visualization and the like.
Furthermore, the mathematical model provided by the invention cooperates with the digital twin agency, the power tracking of compensation payment is carried out by adopting a distributed method, and the influence of load disturbance on the dynamic Control Performance Standard (CPS) of the power grid can be rapidly evaluated.
Furthermore, the DCCA algorithm provided by the invention can be cooperated with the regulation and control resources, so that the rapid regulation and control performance of the renewable energy sources is effectively utilized, the control performance standard of the DT-DPT model is improved, the communication speed is improved, and the privacy of the regulation and control resources is protected.
It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 (a) is a schematic diagram of a ring network of 10 types of communication network structures for adjusting resources of a DT-DPT system according to an embodiment of the present invention.
Fig. 1 (b) is a schematic diagram of a local connection network of 10 communication network structures for adjusting resources of the DT-DPT system according to an embodiment of the present invention.
FIG. 1 (c) is a schematic diagram of a fully connected network of 10 communication network structures for adjusting resources of a DT-DPT system according to an embodiment of the present invention.
Fig. 2 (a) is a graph showing the DCAA convergence of DT-DPT system in different communication networks when Δp C = -80MW according to the embodiment of the present invention.
Fig. 2 (b) is a graph showing the convergence of DCAA in different communication networks of DT-DPT system when Δp C =120 MW according to the embodiment of the present invention.
Fig. 3 (a) is a graph of power tracking for DCAA and PROP under random power disturbances, as proposed by an embodiment of the present invention.
FIG. 3 (b) is a graph of regulated resource output based on DCAA under random power perturbation in an embodiment of the present invention.
Fig. 3 (c) is a graph showing dynamic power deviation of DCAA and PROP under random power disturbance according to an embodiment of the present invention.
FIG. 3 (d) is a graph of dynamic CPS for DCAA and PROP under random power disturbance as proposed by an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.
Example 1
Compared with the traditional centralized power tracking method, such as a mathematical programming method or a heuristic algorithm, the optimal solution of the power grid can be obtained more quickly based on the distributed algorithm. Aiming at a distributed optimization strategy of power grid power tracking, there are a leader and a distributed method based on two basic types of leaders. Whereas for leader-based algorithms, the usual approach is collaborative consensus technology. By adopting the consensus algorithm, the economic dispatching scheme can be obtained rapidly by selecting the leader of the dispatching resource and achieving the increment cost. A distributed consensus method based fast computation, a communication network based consensus algorithm would be more suitable for supervising the communication between resources. Therefore, the invention adopts a consensus control algorithm to quickly obtain a high-performance power tracking scheme with digital double agents.
The digital double-agent power grid power tracking and adjusting method provided by the embodiment of the invention comprises the following steps:
S1, establishing a distributed power supply tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions on the distributed power supply tracking model based on digital twin, and establishing an objective function;
S2, carrying out algorithm design on the distributed power supply tracking model based on digital twinning through a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
Furthermore, the embodiment of the invention is based on a digital twin distributed power supply tracking model, in the physical control process, load disturbance is applied to a power grid, then frequency and link power are measured, the next step of real-time power tracking acquisition is realized, a controller receives signals and optimally distributes power commands to adjustment resources according to a device-level digital twin agent algorithm based on distributed consensus control, and finally dynamic control performance is evaluated. The regulation resources comprise various regulation resources, such as fire coal, hydrogen, liquefied Natural Gas (LNG), wind power generation (WF) and Photovoltaic (PV), and one regulation resource is selected as a consensus leader to optimize and the other regulation resource is selected as a consensus follower.
In one possible implementation, to better simulate the link between physical reality and simulation models, a distributed power tracking model based on digital twinning should take into account some constraints. When constraints are set on a digital twinning-based distributed power tracking model, these constraints are dynamically changing due to the fast tuning nature of the grid. In the power tracking process, the constraint mainly comprises an adjustment direction constraint, a power balance constraint, a power generation capacity constraint and a power generation slope constraint.
Adjusting direction constraint:
In order to fully utilize the regulated resource, the regulating direction of the resource power command is the same as the regulating direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
In order to confirm that the optimal solution meets the requirement of the power grid rule, the accumulation of the power adjustment input commands received by all the power tracking model adjustment resources should be exactly equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
In order to ensure that the regulated resource has good regulation performance and safe environment, the power regulation command obtained by the power tracking model regulated resource should not exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
for new energy regulating resources, the regulation of these resources can change rapidly, as the new energy regulating resources are controlled by the electrical switches. For the traditional regulation resource, the generation of the slope constraint is considered, and the expression is as follows:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
In one possible implementation, one possible optimization objective is to reduce the overall compensation of the tuning resources for a single system operator, based on the minimum value of the frequency mileage-based compensation for the DT-DPT tuning resources. The adjustment compensation amount can be calculated from the integrated price coefficient and the adjustment power deviation. Wherein the integrated payment coefficient depends on the ramp performance and the time delay of the regulated resource.
Step S1 in the step of establishing an objective function, the expression of the objective function is as follows:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
In one possible implementation, step S2 is implemented by using a device-level digital twin proxy algorithm based on distributed consensus control to perform algorithm design on the distributed power tracking model based on digital twin, and since DT-DPT is used to balance power disturbance, DCCA can quickly obtain a power scheme. Taking the regulating resource as a node or proxy, the expression of the communication network is G= (G, E, W), the node set V= { V 1,V2,…,Vn } is a set of regulating resources or a digital proxy, and the setting of edges Representing the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
in one possible implementation, step S2 is based on a device-level digital twin proxy algorithm of distributed consensus control, which can be represented by the following operations, according to the proposed communication network and matrix:
Payment compensation consensus:
in making the compensation payment calculation, the update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
First, the update of the optimal leader may be determined by tracking the increase or decrease of power. A high performance regulated resource R i is selected as the best leader. Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
In order to ensure that the obtained optimal solution does not violate the power capacity, the adjustment resources which do not obey the power constraint are modified to a feasible region of the solution, and meanwhile, the feasible range of compensation payment is paid attention to, and the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; the iteration termination condition is that the power error is less than limit value P e [ t ] and less than or equal to epsilon or when the current iteration exceeds the maximum iteration number N i and less than or equal to t. And then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
Example 2
In simulation tests, the embodiment of the invention designs a DT-DPT system with 10 adjustment resources, and verifies the performance of the method. For setting DCCA parameters, the termination parameter is set to be an optimal process e of 0.001mw,3 types of network connection topologies, as shown in fig. 1 (a) to 1 (c), the 4 th adjustment resource is set to be an optimal pilot, the power tracking error coefficient is set to be 0.1, and the maximum optimal iteration N i is set to be 500. In fig. 1 (a) to 1 (c), embodiments of the present invention will use three topology type networks to illustrate the performance of the proposed DCCA.
The effect of different connection agents on DCCA convergence is analyzed using the proposed three topology networks. The networking comprises annular networking, local connection networking and full connection networking. These three networks help optimize DCCA in two power (Δp C＝-80MW andΔPC =120 MW) command scenarios. As can be seen from fig. 2 (a) and fig. 2 (b), the local connection network proposed in the embodiment of the present invention can quickly balance the power error, which means that the local network auxiliary DCCA has the highest optimal performance compared with the other two connection modes. The optimization speed is about 1 time faster than that of the full communication network and about 2 times faster than that of the annular network. As shown in fig. 2 (a) and fig. 2 (b), the method of the present invention can obtain a high quality solution in 18 steps, while the full communication network needs 35 iterations, and the ring network proposed by the present invention needs 55 iterations. Meanwhile, the DCCA based on the local communication network can only achieve high convergence in 15 iterations, the full communication network is based on the full communication network to obtain the optimal value in about 30 steps, and the annular network is based on about 45 iterations. This suggests that the local connection approach helps to relieve the communication pressure of the digital proxy and improve the convergence performance of DCCA.
To further verify the superiority of the proposed method, a random load disturbance was constructed, as shown in fig. 3 (a), performed on the DT-DPT system. Dynamic adjustment performance was verified using DCCA based on a local connectivity network and a scale-based method, with CPS and power bias as examples. First, the real-time power tracking of the two algorithms is shown in fig. 3 (a), from which it can be seen that DCCA according to the embodiment of the present invention can obtain tracking power lower than the pro. In addition, the method of the invention can effectively reduce the power deviation of the DT-DPT system under random load disturbance, as shown in fig. 3 (c), which is probably due to the fact that the DCCA has higher coordination ability and real-time regulation and control performance for the regulation and control resources, as shown in fig. 3 (b), while the proportion-based method lacks an optimal mechanism for compensating payment or dynamic regulation and control performance. Finally, as shown in fig. 3 (d), it can be seen from fig. 3 (d) that the method proposed by the embodiment of the present invention helps to reduce the reduction of CPS, so that it can be seen that the DCCA proposed by the embodiment of the present invention can obtain a power scheme with higher adjustment performance than the conventional pro.
The present invention verifies the performance of the proposed distributed power tracking method in a simulation system with 10 tuning resources. Meanwhile, the invention designs the communication network, and realizes the real signal exchange. The distributed power tracking method provided by the invention is combined with the communication network, so that the calculation efficiency can be improved, and the privacy of the supervision resources can be protected. The distributed consensus method can perform rapid calculation, and the consensus algorithm based on the communication network is more suitable for the communication between the supervision resources. Therefore, the invention adopts a consensus control algorithm to quickly obtain a high-performance power tracking scheme with digital double agents.
Example 3
Another embodiment of the present invention also proposes a digital dual-agent power grid power tracking regulation system, including:
The power tracking model setting module is used for establishing a distributed power tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions for the distributed power tracking model based on digital twin and establishing an objective function;
The distributed consensus control calculation module is used for carrying out algorithm design on the distributed power supply tracking model based on digital twinning through a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
In one possible implementation, the power tracking model setting module selects one regulation resource as a consensus leader for optimization and another regulation resource as a consensus follower when establishing a digital twin-based distributed power tracking model according to a communication network between different regulation resources.
In one possible implementation manner, when the power tracking model setting module sets constraint conditions on the distributed power tracking model based on digital twin, the constraint conditions include adjustment direction constraint, power balance constraint, power generation capacity constraint and power generation slope constraint, and specific meanings and expressions of the constraint conditions are as follows:
Adjusting direction constraint:
The adjustment direction of the resource power command is the same as the adjustment direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
the summation of the power adjustment input commands received by all the power tracking model adjustment resources is equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
The power tracking model adjusts the power adjustment command obtained by the resource not to exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
Further, when the power tracking model setting module establishes the objective function, the expression of the objective function is as follows:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
In one possible implementation manner, when the distributed consensus control calculation module performs algorithm design on the digital twin-based distributed power supply tracking model through a device digital twin proxy algorithm based on distributed consensus control, an adjustment resource is used as a node or proxy, an expression of a communication network is θ= (V, E, W), a node set v= { V 1,V2,…,Vn } is a set of regulation resources or a digital proxy, and an edge is setRepresenting the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
In one possible implementation, the distributed consensus control calculation module represents the device-level digital twin proxy algorithm based on distributed consensus control according to the proposed communication network and matrix by:
Payment compensation consensus:
The update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
Modifying the regulated resource that is not subject to the power constraint to a feasible region of the solution while focusing on the feasible range of the compensation payment, the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
Example 4
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the digital double-agent power grid power tracking and adjusting method when executing the computer program.
Example 5
Another embodiment of the present invention further proposes a computer readable storage medium storing a computer program, which when executed by a processor implements the digital dual agent grid power tracking adjustment method.
The computer program comprises computer program code which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable storage medium may include: any entity or device, medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunications signals, software distribution media, and the like capable of carrying the computer program code. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals. For convenience of description, the foregoing disclosure shows only those parts relevant to the embodiments of the present invention, and specific technical details are not disclosed, but reference is made to the method parts of the embodiments of the present invention. The computer readable storage medium is non-transitory and can be stored in a storage device formed by various electronic devices, and can implement the execution procedure described in the method according to the embodiment of the present invention.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flowchart and/or block of the flowchart illustrations and/or block diagrams, and combinations of flowcharts and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (14)
1. A digital dual-agent power grid power tracking adjustment method, comprising:
Establishing a distributed power supply tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions for the distributed power supply tracking model based on digital twin, and establishing an objective function;
And carrying out algorithm design on the distributed power supply tracking model based on digital twinning by using a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
2. The method according to claim 1, wherein in the step of establishing a distributed power supply tracking model based on digital twin according to a communication network between different modulation resources, the modulation resources include modulation resources, one modulation resource is selected as a consensus leader for optimization, and the other modulation resource is selected as a consensus follower.
3. The method for tracking and adjusting the power of the digital dual-proxy power grid according to claim 1, wherein in the step of setting constraint conditions for the distributed power tracking model based on digital twin, the constraint conditions include adjustment direction constraint, power balance constraint, power generation capacity constraint and power generation slope constraint, and specific meanings and expressions of the constraint conditions are as follows:
Adjusting direction constraint:
The adjustment direction of the resource power command is the same as the adjustment direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
the summation of the power adjustment input commands received by all the power tracking model adjustment resources is equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
The power tracking model adjusts the power adjustment command obtained by the resource not to exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
4. A digital dual agent power grid power tracking adjustment method according to claim 3, characterized in that in the step of establishing an objective function, the expression of the objective function is as follows:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
5. The method for tracking and adjusting power of digital dual-proxy power grid according to claim 4, wherein in the step of performing algorithm design on the digital twin-based distributed power supply tracking model through a device-level digital twin proxy algorithm based on distributed consensus control, an adjustment resource is used as a node or proxy, an expression of a communication network is g= (V, E, W), a node set v= { V 1,V2,…,Vn } is a set of regulation resources or a digital proxy, and an edge is setRepresenting the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
6. The method for power tracking and adjusting of a digital dual-proxy power grid according to claim 5, wherein the steps of performing algorithm design on the digital twin-based distributed power tracking model through a distributed consensus control-based device-level digital twin-proxy algorithm, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus are performed, and the method is represented by the following operations according to the proposed communication network and matrix based on the distributed consensus control-based device-level digital twin-proxy algorithm:
Payment compensation consensus:
The update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
Modifying the regulated resource that is not subject to the power constraint to a feasible region of the solution while focusing on the feasible range of the compensation payment, the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
7. A digital dual-agent power grid power tracking regulation system, comprising:
The power tracking model setting module is used for establishing a distributed power tracking model based on digital twin according to a communication network among different modulation and control resources, setting constraint conditions for the distributed power tracking model based on digital twin and establishing an objective function;
The distributed consensus control calculation module is used for carrying out algorithm design on the distributed power supply tracking model based on digital twinning through a device-level digital twinning agent algorithm based on distributed consensus control, and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
8. The digital dual-proxy power grid power tracking adjustment system of claim 7, wherein the power tracking model setting module selects one of the regulated resources as a consensus leader for optimization and another of the regulated resources as a consensus follower when establishing a digital twinning-based distributed power tracking model based on a communication network between different regulated resources.
9. The digital dual-proxy power grid power tracking adjustment system of claim 7, wherein the power tracking model setting module sets constraint conditions for the digital twin-based distributed power tracking model, the constraint conditions comprise adjustment direction constraint, power balance constraint, power generation capacity constraint and power generation slope constraint, and specific meanings and expressions of the constraint conditions are as follows:
Adjusting direction constraint:
The adjustment direction of the resource power command is the same as the adjustment direction of the total power command, and the expression is as follows:
In the method, in the process of the invention, The adjustment command is distributed to the ith power tracking model adjustment resource in the kth control interval, and DeltaP C (k) is the total adjustment command from the power grid to the power tracking model;
Power balance constraint:
the summation of the power adjustment input commands received by all the power tracking model adjustment resources is equivalent to the total power adjustment commands sent by the power grid, and the expression is as follows:
Power generation capacity constraint:
The power tracking model adjusts the power adjustment command obtained by the resource not to exceed the corresponding capacity, and the expression is as follows:
In the method, in the process of the invention, And/>Representing the minimum and maximum values of the ith regulated resource in the kth time control interval;
Power generation ramp constraint:
In the method, in the process of the invention, Represents the output power command received by the ith power tracking model adjustment resource at the kth control interval, deltaT represents the adjustment time of the control interval,/>The maximum ramp rate of the resource is adjusted for the ith power tracking model.
10. The digital dual-agent power grid power tracking adjustment system of claim 9, wherein the power tracking model setting module, when establishing an objective function, has an expression of:
Wherein R i represents compensation payment of the ith regulated resource, C i represents comprehensive payment coefficient, and lambda is price coefficient of mileage deviation; m i (k) represents the power tracking mileage at the kth time control interval; And/> Respectively representing the rate performance score and the time delay of the ith regulation resource; w 1 and w 2 represent the weights corresponding to the rate performance score and the time delay of the ith regulated resource, wherein w 1+w2 =1,/>Adjusting the average slope of the resource for the ith,/>Representing the adjustment delay of the ith adjustment resource.
11. The digital dual-proxy power grid power tracking and regulating system according to claim 10, wherein the distributed consensus control calculation module takes regulating resources as nodes or proxies when carrying out algorithm design on the digital twin-based distributed power tracking model through a device-level digital twin proxy algorithm based on distributed consensus control, the expression of a communication network is g= (V, E, W), the node set v= { V 1,V2,…,Vn } is a set of regulated resources or a digital proxy, and the setting of edges is that Representing the relationship between two nodes, and the weighted adjacency matrix w= [ W ij]∈Rn×n represents the connection weight of the corresponding edge;
based on the communication network, a laplace matrix l= [ L ij]∈Rn×n is established, and the obtained information is as follows:
The next row is a random matrix d= [ D ij]∈Rn×n, determined by the laplace matrix, expressed as follows:
12. The digital dual-agent grid power tracking adjustment system according to claim 11, characterized in that the distributed consensus control calculation module represents a device-level digital twin-agent algorithm based on distributed consensus control according to the proposed communication network and matrix by:
Payment compensation consensus:
The update of the payment compensation is given by a row random matrix, expressed as follows:
wherein d ij represents aggregation from another j node to the ith node, R j [ t ] represents compensation payment corresponding to the jth adjustment resource in the t optimal iteration;
Updating of the optimal leader:
Based on the rights balance, the optimal leader should track the rights responsibilities for the iteration and current rights increment as follows:
In the method, in the process of the invention, The compensation payment corresponding to the optimal lead at the t optimal iteration is represented, mu represents a power tracking error coefficient, P e [ t ] represents the power tracking error at the t optimal iteration, and DeltaP C (k) represents the total power tracking value of the k time control interval;
modification of the power scheme:
Modifying the regulated resource that is not subject to the power constraint to a feasible region of the solution while focusing on the feasible range of the compensation payment, the expression is as follows:
consensus optimization process:
For the proposed leading salary calculation and consensus calculation, reducing the power tracking error to be close to zero after iterative optimization; when the iteration termination condition is reached, the iteration is terminated; and then solving to obtain a corresponding optimal power scheme according to the proposed compensation payment consensus.
13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized by: the processor, when executing the computer program, implements a digital dual-agent power grid power tracking adjustment method as claimed in any one of claims 1 to 6.
14. A computer-readable storage medium storing a computer program, characterized in that: the computer program, when executed by a processor, implements a digital dual agent grid power tracking adjustment method as claimed in any one of claims 1 to 6.
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