CN113705964B - Method and device for formulating pre-disaster plan for toughness recovery of power distribution network - Google Patents

Method and device for formulating pre-disaster plan for toughness recovery of power distribution network Download PDF

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CN113705964B
CN113705964B CN202110807250.6A CN202110807250A CN113705964B CN 113705964 B CN113705964 B CN 113705964B CN 202110807250 A CN202110807250 A CN 202110807250A CN 113705964 B CN113705964 B CN 113705964B
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崔正达
刁冠勋
陈颖
管必萍
余浩斌
戴人杰
卫思明
李博达
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Tsinghua University
State Grid Shanghai Electric Power Co Ltd
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State Grid Shanghai Electric Power Co Ltd
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Abstract

The invention provides a method and a device for planning a pre-disaster plan for toughness recovery of a power distribution network, which are used for preparing contracts for energy recovery by using public traffic resources during the toughness recovery of the power distribution network, wherein the method comprises the following steps: establishing a toughness recovery contract model of the power distribution network; establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery; determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network; under the topology of the topology reconstruction model, optimizing the constraint model according to the confidence parameters and preset disaster information to obtain a pre-disaster planning result of the toughness recovery of the power distribution network. The public traffic resource is reasonably utilized in the toughness recovery of the power distribution network so as to improve the toughness recovery capability of the power distribution network; and a reasonable contract model is formulated and a pre-disaster plan result is obtained by solving, so that a basis is provided for the overall decision of the toughness improvement of the power distribution network.

Description

Method and device for formulating pre-disaster plan for toughness recovery of power distribution network
Technical Field
The invention relates to the technical field of toughness recovery of a power distribution network, in particular to a method and a device for planning a pre-disaster plan for toughness recovery of the power distribution network.
Background
The toughness of the power system refers to the capability of changing the state of the power grid to reduce fault loss and recover the normal power supply level as soon as possible under the extreme conditions of serious disasters, man-made attacks and the like. The power distribution network needs to make advanced deployment and prevention aiming at disasters, and disaster uncertainty is reasonably considered to make pre-disaster deployment decisions.
Toughness research focuses on extreme natural disasters, and the influence caused by future disasters is difficult to obtain through historical data in the class of small-probability events, so that a probability model cannot be simply adopted to measure disaster results. In traditional toughness recovery of a power distribution network, the power distribution network uses self resources (maintenance personnel, emergency power supply equipment and the like) of a power grid company to recover, and the power grid has poor and insufficient self recovery capacity, so that normal operation work of the power distribution network is influenced, and toughness recovery of the power distribution network is influenced.
Disclosure of Invention
The invention provides a method and a device for planning a pre-disaster plan for toughness recovery of a power distribution network, which are used for solving the defect of poor toughness recovery capability of the power distribution network in the prior art, and realizing the improvement of the toughness recovery capability of the power distribution network by reasonably calling public traffic resources.
The invention provides a method for preparing a pre-disaster plan for toughness recovery of a power distribution network, which is used for preparing contracts for energy recovery by using public traffic resources during toughness recovery of the power distribution network, and comprises the following steps:
Establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part;
establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery;
determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network;
and under the structure of the topology reconstruction model, carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
According to the method for planning the pre-disaster plan for the toughness recovery of the power distribution network, which is provided by the invention, a contract model for the toughness recovery of the power distribution network is established, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part, and the method specifically comprises the following steps: the objective function of the contract model is:
where x represents a decision variable of the contract model,decision vector, x, representing a contract model k Representing the purchase amount of the ith resource in the decision variable, cost k (x k ) Represents the purchase cost of the kth resource, p s Representing the probability of occurrence of the corresponding fault scene s, z s Representing auxiliary variables, alpha representing confidence parameters, ζ representing disaster damage threshold;
the objective function of the pre-disaster acquisition resource cost part is as follows:
wherein x is k Representing the purchase amount of the kth resource in the decision variable;
the objective function of the predicted post-disaster damage part is as follows:
where pi (x, s) represents the disaster loss in scene s.
According to the method for planning the pre-disaster plan for the toughness recovery of the power distribution network, which is provided by the invention, a contract model for the toughness recovery of the power distribution network is established, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part, and the method specifically comprises the following steps:
definition pi (x, ζ) represents disaster damage of the distribution network, whereinRepresenting pre-disaster contract decision vectors, ζ represents a random variable vector, and for each x, t (x,) is a cumulative distribution function of disaster damage pi (x, ζ):
ψ(x,ζ)＝P{ξ|π(x,ξ)<ζ}
given the confidence parameter α∈ (0, 1), the Risk Value (VaR, value-at-Risk) α -VaR for α is defined as follows:
ζ α (x)＝min{ζ|ψ(x,ζ)}≥α}
the above equation represents the minimum disaster damage in the scene where the damage occurs most severely with the probability of (1- α);
given the confidence parameter α∈ (0, 1), the conditional Risk value of α (CVaR, conditional Value-at-Risk) α -CVaR is defined as follows:
φ α (x)＝E[ζ|ζ>ζ α (x)]
The above formula represents the expectation of disaster damage exceeding alpha-VaR, the mid-term of the above formulaThe expected probability distribution is the probability distribution ψ obtained by readjusting the probability that ψ (x, ζ) exceeds the α portion α (x,ζ)：
And carrying out discrete sampling on the condition risk value to obtain occurrence probability of each scene, and approximating probability distribution to obtain an expression of an objective function of the predicted post-disaster loss part.
According to the method for planning the pre-disaster planning for the toughness recovery of the power distribution network, which is provided by the invention, a topology reconstruction model of a power distribution network fault scene set is established according to preset disaster information, wherein the topology reconstruction model is used for representing the post-disaster topology structure of the toughness recovery reconstruction of the power distribution network, and specifically comprises the following steps:
determining fault scene information to be predicted and corresponding occurrence probability;
obtaining a fault scene set according to the fault scene information and the occurrence probability;
and establishing the topology reconstruction model according to the fault scene set and a preset rule.
According to the method for planning the pre-disaster plan for the toughness recovery of the power distribution network, which is provided by the invention, under the structure of a topology reconstruction model, the contract model is optimized according to the confidence parameter and preset disaster information to obtain a pre-disaster plan result for the toughness recovery of the power distribution network, and the method specifically comprises the following steps:
Initializing each fault scene in the fault scene set to obtain decision variables of each fault scene;
at least one round of iteration is respectively carried out on each fault scene, the contract model of each fault scene is respectively optimized in each round of iteration, and expected decision variables are obtained according to the probability of occurrence of the fault sceneIs>And applying in each iteration an update of the multiplier +.>Wherein->Zeta being the VaR value s Corresponding multiplier(s)>As decision variable x s The penalty factor rho is used for controlling the updating amplitude of the decision variable of each iteration;
decision variables for each fault scenarioIs->And stopping iteration when the deviation of the (E) is smaller than the threshold value epsilon, and obtaining an optimal decision variable x and an optimal disaster loss threshold value zeta.
According to the method for planning the pre-disaster plan for toughness recovery of the power distribution network, which is provided by the invention, the Cost function Cost of decision variables in the objective function of the pre-disaster acquisition resource Cost part is adopted k (x k ) Setting as a quadratic function; under the structure of the topology reconstruction model, optimizing the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result of the toughness recovery of the power distribution network, wherein the pre-disaster planning result comprises the following steps:
The optimal decision variable x and the optimal disaster loss threshold zeta s And inputting the confidence parameter alpha into a contract model target parameter to obtain a pre-disaster planning result for toughness recovery of the power distribution network.
The invention also provides a device for preparing a pre-disaster plan for toughness recovery of the power distribution network, which is used for preparing contracts for energy recovery by using public traffic resources during the toughness recovery of the power distribution network, and comprises the following steps:
the system comprises a contract model modeling unit, a power distribution network toughness recovery contract model, a power distribution network toughness recovery control unit and a power distribution network toughness recovery control unit, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part;
the topology reconstruction model modeling unit is used for establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a post-disaster power distribution network toughness recovery reconstructed topology structure;
the power distribution network risk determination system comprises a confidence parameter determination unit, a power distribution network risk determination unit and a power distribution network risk determination unit, wherein the confidence parameter determination unit is used for determining a confidence parameter, and the confidence parameter is used for characterizing power distribution network risk preference;
and the optimization unit is used for carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information under the structure of the topology reconstruction model to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
According to the pre-disaster planning device for toughness recovery of the power distribution network, provided by the invention, the topology reconstruction model modeling unit specifically comprises:
the prediction parameter determining unit is used for determining fault scene information to be predicted and corresponding occurrence probability;
the fault scene generating unit is used for obtaining a fault scene set according to the fault scene information and the occurrence probability;
and the reconstruction unit is used for establishing the topology reconstruction model according to the fault scene set and a preset rule.
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 steps of any of the method for planning the pre-disaster planning of the toughness recovery of the power distribution network when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the pre-disaster planning method for toughness restoration of a power distribution network as described in any one of the above.
According to the method and the device for simulating and predicting the pre-disaster fault scene of the power distribution network, the public transportation resource is reasonably invoked, so that the toughness recovery capability of the power distribution network is improved; in addition, in the contract model of external resource scheduling, the uncertainty of disasters is fully considered by presetting different disaster information, and meanwhile, the bearing capacity of different power grid companies on disaster loss risks is reflected by different confidence parameters, so that a more reasonable and accurate contract model is established, and a basis is provided for the overall decision of the improvement of the toughness of the power distribution network.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a simulation prediction method for a pre-disaster fault scene of a power distribution network;
FIG. 2 is a graph showing the experimental simulation effect of the experiment of example 1 by applying the method provided by the invention;
FIG. 3 is a schematic diagram of a node distribution structure of example 2 using the method provided by the present invention;
FIG. 4 is a graph showing the experimental simulation effect of the experiment of example 2 performed by the method provided by the invention;
FIG. 5 is a schematic structural diagram of a device for simulating and predicting a pre-disaster fault scene of a power distribution network;
fig. 6 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the embodiment of the invention, in order to improve the toughness recovery capability of the power distribution network, electrified public traffic resources are utilized to help the power distribution network to carry out toughness recovery, and the decision form of the power distribution network needs to be changed. In traditional toughness recovery of a power distribution network, the power distribution network uses self resources (maintenance personnel, emergency power supply equipment and the like) of a power grid company to recover, and has complete allocation rights to the resources. If the social resources such as electrified public transportation are expected to be utilized, coordination needs to be carried out in advance, certain resource allocation rights are given to the power distribution network, the running state is adjusted in advance, and disasters are prevented. In a preferred embodiment, the power supply of a portion of the electric buses in urban traffic may be invoked for toughness restoration of the distribution network. Therefore, a scheduling use contract between the power distribution network and the external scheduling resource needs to be analyzed in advance so as to provide basis for toughness recovery decision of the power distribution network.
The electrified public transportation resource is a social resource, and in the embodiment of the invention, the power grid company needs to purchase power supply service for a social main body (public transport company and distributed power supply), so that the electricity utilization safety when disasters occur is ensured. The social body can receive certain economic compensation, reduce partial service and dispatch the rest electric energy resources to the power grid to support the recovery of the power distribution network.
As shown in fig. 1, an embodiment of the present invention provides a method for predicting a disaster-pre-disaster fault scenario of a power distribution network, configured to formulate a contract for energy recovery by using public transportation resources when toughness of the power distribution network is recovered, where the method includes:
step 110: establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part;
in the embodiment of the invention, in the contract, the power grid needs to purchase power supply service for the social main body under the condition that accurate disaster fault information cannot be known, so that disaster uncertainty must be considered in the contract model. In addition, different power grid companies have different bearing capacities on disaster loss risks, and because toughness and economy are often a pair of contradictions, certain economy is sometimes sacrificed to improve toughness, and the opposite is sometimes required, so that a contract model needs to consider power grid company risk preference in pre-disaster contract formulation. Therefore, in the step, the pre-disaster purchased resource cost part corresponds to the budget of the pre-disaster power grid company for purchasing external electric energy resources; the predicted post-disaster damage part corresponds to post-disaster power distribution network damage prediction, and the uncertainty of disasters and the risk preference of power grid companies are fully considered.
Step 120: establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery;
in the embodiment of the invention, in the toughness recovery scene of the power distribution network, the power distribution network is often subjected to larger impact and possibly generates multiple faults, and in order to reduce disaster loss, the power distribution network is required to be subjected to topology reconstruction, so that a key load power supply path is ensured.
In this step, the building of the topology reconstruction model specifically includes:
establishing a power distribution network fault probability model;
generating a power distribution network fault scene set according to preset disaster information and a preset total number of generated scenes based on the power distribution network fault probability model;
and performing topology reconstruction in the power distribution network fault scene set to construct a fault topology reconstruction model.
In the embodiment of the invention, the power distribution network is of a topological structure and comprises a plurality of power transmission lines.
Inputting preset disaster information into the power distribution network fault probability model, wherein the preset disaster information comprises disaster duration time;
carrying out one-time fault scene random simulation generation on each power transmission line in the power distribution network according to the duration time of the disaster to obtain a fault scene;
And repeating the simulation generation process to obtain the fault scenes of the total number of the preset generation scenes, and forming the power distribution network fault scene set.
The topology reconstruction model established in the step is to maximize the difference value between the self charge recovery quantity of the power distribution network and the charge quantity of the external power supply.
In the embodiment of the invention, a reasonable power distribution network topology reconstruction model is the basis of toughness recovery of the power distribution network. The reconstruction model after the faults of the power distribution network is more studied, but the reconstruction model of the external public transportation power resource elements is not considered in the prior art, so that the embodiment of the invention establishes a power distribution network topology reconstruction model considering the public transportation power resource elements.
In the embodiment of the invention, the fault topology reconstruction model preferably uses the power from the main network to perform autonomous recovery, does not use external power supply resources such as a distributed power supply as much as possible, and uses the external power supply resources unless the power of the main network cannot be recovered, so that the objective function of the fault topology reconstruction model is as follows:
wherein,representing the charge recovery quantity at point t of the ith node in the distribution network, < >>Indicating the output of the external power supply resource t time of the ith node, omega i Representing the load importance of the ith node, gamma represents a penalty factor greater than 0, Indicating the output of the ith node at the moment t，/>Representing a collection of nodes in a distribution network connecting a main network, in which distribution network typically only 1 node is connected to the main network, and therefore typically +.> And (3) representing all node sets in the power distribution network, and T representing disaster duration time in a fault scene.
(1) The factor gamma is introduced, which means that when the output of the external power supply resource is increased, the overall power distribution network can recover more load, but the increase of the overall objective function is not as good as that of the direct use of the main network power, so that the output of the external power supply resource can be reduced as much as possible when the optimization problem of fault topology reconstruction is solved.
(2) It can be seen that when the node in the power distribution network is not the node connected with the main network, the processing of the node is the output of the external power supply resource. (3) The equation indicates that no external power supply resource is used at the node connected to the main network.
The similarity of different power distribution network fault scenes is measured and is a precondition for carrying out fault scene clustering. Clustering is carried out on disaster scenes of the power distribution network, wherein the similarity of the fault scenes takes the fault loss of each node of the power distribution network as a basis, and the losses of each node caused by the similar fault scenes are similar. The starting point is from the perspective of fault influence, and the scene similarity can be reflected to a certain extent. However, in the failure scenario of the distribution network, there is a disadvantage in clustering only from the point of failure loss. When the power distribution network recovers, different topology reconstruction results can be generated according to fault conditions, the topology structure influences power supply paths of a power source and a load, and the power distribution network is divided into islanding when the faults are serious, so that the specific recovery decision is greatly affected by the topology structure. Different topology reconstruction results may lead to similar fault losses, which may lead to intrinsically different power distribution network toughness recovery decisions.
In the embodiment of the invention, the fault scene set is obtained according to the preset fault scene information and occurrence probability, the topology reconstruction structure of the fault scene set is obtained according to the established topology reconstruction model, the follow-up contract model calculation under the determined topology reconstruction structure of the fault scene is carried out after the topology reconstruction structure is determined, the plan result is obtained, the repeated calculation of the corresponding topology structure in the fault scene of the power distribution network in the contract model optimization solving process is avoided, the calculated amount in the contract model calculating process is reduced, and the solving speed is improved.
Step 130: determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network;
in the embodiment of the invention, the confidence parameter reflects the risk preference of the power grid company, when the confidence parameter value is smaller, the risk preference of the power grid company is lower, the consideration and research of most of fault scenes in the fault scene set are needed, and when the confidence parameter value is larger, the risk preference of the power grid company is higher, the consideration and research of the smaller part of fault scenes in the fault scene set are needed.
Step 140: and under the structure of the topology reconstruction model, carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
In the embodiment of the invention, in the toughness recovery of the power distribution network, the relation between the toughness and the economy is required to be balanced, and in the pre-disaster decision, the relation is expressed on the trade-off between the pre-disaster resource preparation cost and the post-disaster loss. If the power grid has extremely high requirements on toughness, the power grid is willing to pay very high pre-disaster preparation cost to cope with almost all possible disaster scenes; if the grid is properly relaxed in terms of toughness, and it is desired to cope with disasters in a more economical manner, resource preparation before the disaster may not cope with the most extreme disaster scenarios. In order to adapt to power grid risk preference under different conditions, the embodiment of the invention establishes a pre-disaster contract making scheme comprehensively considering pre-disaster preparation cost and disaster loss risk.
In step 110, the objective function of the contract model is:
where x represents a decision variable of the contract model,decision vector, x, representing a contract model k Representing the purchase amount of the ith resource in the decision variable, cost k (x k ) Represents the purchase cost of the kth resource, p s Representing the probability of occurrence of the corresponding fault scene s, z s Represents the auxiliary variable, α represents the confidence parameter, ζ represents the disaster damage threshold.
The objective function of the contract model is the minimum sum of the pre-disaster cost and the disaster risk as seen by the formula (4), the formula (4) is a two-stage random optimization model, the first stage is a pre-disaster resource purchasing decision, the second stage is based on the pre-disaster decision, disaster recovery is carried out under the disaster scene s, and finally the power distribution network risk index decision is obtained.
The objective function of the pre-disaster acquisition resource cost part is as follows:
wherein x represents the purchase amount of the kth resource in the decision variable, and (5) represents the pre-disaster purchase resource cost.
Because the formula (5) is a pre-disaster decision part, in the embodiment of the invention, the pre-disaster decision content is the purchased power supply quantity of a power grid company to a main body with power supply resources in the society, namely, the power supply quantity is contracted with the relevant main body in advance before disaster, and after the power distribution network suffers from disaster, the main body in the society, which is contracted with the contract, should provide the contract power supply quantity for dispatching to the power distribution network. After the electrified traffic participates in the recovery of the power distribution network, the power grid company lacks the scheduling right for social resources, and the power supply to the power grid can influence the operation of public transportation service, so that the contract is formulated before the disaster, the working state in the disaster is coordinated in advance, and the corresponding power supply resources are reserved.
Based on the above conditions, in the embodiment of the invention, the contract model decision variable x comprises the total amount of power supplied by the power grid to the distributed power source of the social subject and the electric bus purchase. And during disaster scheduling, the electric quantity scheduled by the power distribution network cannot exceed the total power supply amount of pre-disaster decision, so that a constraint condition (6) is formed.
The objective function of the predicted post-disaster damage part is as follows:
Where pi (x, s) represents the disaster loss in scene s.
In the embodiment of the present invention, the determining process of the predicted post-disaster damage portion, that is, the determining process of the formula (7), specifically includes:
definition pi (x, ζ) represents disaster damage of the distribution network, whereinRepresenting pre-disaster contract decision vectors, ζ represents a random variable vector, and for each x, t (x,) is a cumulative distribution function of disaster damage pi (x, ζ):
ψ(x,ζ)＝P{ξ|π(x,ξ)<ζ} (10)
given the confidence parameter α∈ (0, 1), the Risk Value (VaR, value-at-Risk) α -VaR for α is defined as follows:
ζ α (x)＝min{ζ|ψ(x,ζ)}≥α} (11)
(11) The formula represents the minimum disaster damage in the scene where the damage occurs most severely with a probability of (1-alpha);
given the confidence parameter α∈ (0, 1), the conditional Risk value of α (CVaR, conditional Value-at-Risk) α -CVaR is defined as follows:
φ α (x)＝E[ζ|ζ>ζ α (x)] (12)
(12) The formula represents the expectation of disaster damage exceeding alpha-VaR, and the expected probability distribution in the formula (12) is the probability distribution psi obtained by readjusting the probability of psi (x, ζ) exceeding alpha part α (x,ζ)：
And carrying out discrete sampling on the condition risk value to obtain occurrence probability of each scene, and approximating probability distribution to obtain an expression of an objective function of the predicted post-disaster loss part.
In the embodiment of the invention, to consider the power grid Risk preference, a conditional Risk value (CVaR, conditional Value-at-Risk) is introduced. CVaR focuses on the tail risk of loss and is widely applied to investment risk avoidance. The extreme scenario concerned in the toughness recovery problem is also a low-probability high-loss scenario, and corresponds to the tail risk of the CVaR, so that the CVaR is a suitable risk assessment index in toughness recovery.
As can be seen from the expression (7), the CVaR defined in the expression (12) is based on the case where the cumulative probability distribution is a continuous function, but in practical application, there is often a case where an accurate probability distribution function cannot be obtained, and at this time, the probability of occurrence of different scenes can be obtained by using a sampling method, and the probability distribution is approximated. In response to the need for modification of CVaR, the equation (14) is introduced as an approximation to this failure scenario:
wherein [ pi (x, ζ) - ζ] + Represents max {0, pi (x, ζ) - ζ }, p r (xi) tableShow belongs to scene setProbability of xi occurrence in (a).
In particular to a scene-based optimization problem, when the CVaR is minimized, the formula (11) can be substituted into a contract model optimization problem, and the optimization problem of the CVaR can be converted into the form of the formula (7) according to grid risk assessment and uncertainty after disaster. Since equation (14) is approximately obtained by sampling equation (12), the result of equation (7), which is equivalent to equation (14), can be regarded as a CVaR value defined by equation (12).
In the embodiment of the invention, under the condition that the confidence parameter alpha and the occurrence probability of the fault scene are given, the objective function of the predicted post-disaster damage part is converted into the following formula to be optimized:
wherein pi (x, s) represents disaster loss in scene s, ω i Representing the importance of the load of the ith node in the distribution network,represents the load loss amount of the i-th node, x k Representing the purchase amount of the kth resource in the decision variable,/->Output size indicating purchase resource of ith node,/->Indicating the discharge capacity of the ith node to purchase the resource, < >>Representing a set of power supply nodes in a distribution network,>representing a collection of nodes in a distribution network having purchased resource contributions.
In the embodiment of the present invention, step 140 is a process of solving the reduction model on the basis of determining the topology reconstruction structure and the confidence parameter of the power distribution network, and specifically includes:
initializing each fault scene in the fault scene set to obtain decision variables of each fault scene; and carrying out initialization calculation on each scene once to obtain a decision variable of each scene when one scene is considered independently.
At least one round of iteration is respectively carried out on each fault scene, sub-problems in each fault scene, namely, contract models, are respectively optimized in each round of iteration, and expected decision variables are obtained according to probability processing of occurrence of the fault scenesIs>And applying a fixed penalty factor ρ to update the multiplier in each round of iterations>Wherein->Zeta being the VaR value s Corresponding multiplier(s) >As decision variable x s The penalty factor rho is used for controlling the updating amplitude of the decision variable of each iteration;
in particular, the method comprises the steps of,determining desired decision variables based on probability of occurrenceIs>
In the objective function of the sub-problem of each iteration, respectivelyAnd->Applying a linear penalty proportional to the multiplier,>and upper-wheel VaR value->A quadratic penalty term for the deviation of (2) and a scene decision +.>Decision making with upper round expectations->A quadratic penalty term for the deviation. These penalty terms will cause the VaR values and decision variables for each scene to converge towards the final result.
Decision variables for each fault scenarioIs->And stopping iteration when the deviation of the (c) is smaller than the threshold epsilon, and obtaining an optimal decision variable x, an optimal disaster loss threshold zeta and related CVaR and VaR values.
In the embodiment of the invention, the Cost function Cost of the decision variable in the objective function of the pre-disaster acquisition resource Cost part k (x k ) Setting as a quadratic function; processing the contract model of the power distribution network according to the confidence parameter to obtain a pre-disaster planning result of toughness recovery of the power distribution network, wherein the pre-disaster planning result comprises the following steps:
and inputting the optimal decision variable x, the optimal disaster loss threshold zeta and the confidence parameter alpha into the contract model target parameter to obtain a pre-disaster planning result for the toughness recovery of the power distribution network.
The method disclosed by the embodiment of the invention is subjected to a related simulation experiment by combining a specific example.
Calculation example 1: the Cost function of the distributed power supply in the external power supply in this example is set to Cost (x) =0.001 x 2 +2x, cost function of electric bus is set to Cost (x) =0.0001 x 2 +3x, during the iterative computation of the contract model, the penalty factor ρ is set to 20.
In the example, the following results were obtained by taking the confidence parameters α as 0.3,0.5,0.7,0.8,0.9, respectively.
TABLE 1 Pre-disaster decision costs, CVaR, vaR values under different confidence parameters
In this example, the pre-disaster decision cost, CVaR, vaR values obtained under different confidence parameters are shown in table 1, and the trend of the change is shown in fig. 2. As can be seen in fig. 2, as the confidence parameter rises, the CVaR, vaR values rise continuously, the VaR is always smaller than the CVaR, and as the confidence parameter rises, the difference between the two becomes smaller, this result meets the definition of the two, i.e. the CVaR is the desire to exceed the losses of the VaR. The pre-disaster decision cost is less in change, the whole trend is upward along with the confidence parameter, and when the confidence parameter is changed, the pre-disaster decision change caused by the power grid paying attention to the tail risk is reflected.
Calculation example 2:
as shown in fig. 3, the distribution schematic of the nodes of the power distribution network in the simulation experiment is shown, the node 1 is connected with the main network of the power distribution network, the dotted line in the figure is a power distribution network tie line, in the power distribution network, the nodes 15 and 20 have electric bus charging stations, and the nodes 9, 18 and 29 have distributed power sources.
In this example, the confidence parameters α are 0.3,0.5,0.7,0.8,0.9, and the following pre-disaster decision results are calculated, and the specific pre-disaster decision results are shown in table 2.
TABLE 2 Pre-disaster decision under different confidence parameters
The trend is shown in fig. 4, wherein DG1, DG2 and DG3 represent the distributed power sources of grid nodes 9, 18 and 19, respectively.
As can be seen in fig. 4, as the confidence parameter rises, the decision of the grid changes somewhat: the electricity purchasing quantity of DG1 and DG3 is basically unchanged; the electricity purchasing quantity of DG2 is reduced, and the electricity purchasing quantity of the electric bus is increased. Generally, when the conservation degree of the power grid increases, in order to reduce the power supply loss of all fault scenarios, the total amount of resources should be increased as much as possible, and in this example, the purchase amount of DG2 decreases with the increase of the confidence parameter. This is because the confidence parameter of CVaR is not a direct measure of the degree of decision conservation, and this confidence parameter reflects the degree of concern for tail risk. Under extreme disaster conditions, the most serious faults can cause large-scale faults of the power distribution network, so that a plurality of nodes of the power distribution network lose power supply paths and cannot recover. In this case, even if there are sufficient power supply resources, the overall toughness of the power distribution network cannot be improved due to the lack of a power supply path. This is reflected when the confidence parameter of this example is higher, and when the electric wire netting is concerned with afterbody risk, select to purchase more electronic public transit power supply resource, and reduced DG 2's electric quantity purchase to under the limited circumstances of power supply route, promote distribution network toughness level as far as possible. Under the circumstance, the requirement of further improving the toughness level of the power distribution network cannot depend on preparing more pre-disaster resources, but needs to be combined with resources such as rush-repair and emergency power supply vehicles in disasters.
The following describes a pre-disaster planning device for toughness recovery of a power distribution network, where the pre-disaster planning device for toughness recovery of a power distribution network and the pre-disaster planning method for toughness recovery of a power distribution network described above can be correspondingly referred to each other, as shown in fig. 5, an embodiment of the present invention provides a pre-disaster planning device for toughness recovery of a power distribution network, which is used for making contracts for energy recovery by using public traffic resources during toughness recovery of a power distribution network, and the device includes:
a contract model modeling unit 510, configured to build a power distribution network toughness recovery contract model, where the contract model includes a pre-disaster acquisition resource cost portion and a predicted post-disaster loss portion.
In the embodiment of the invention, in the contract, the power grid needs to purchase power supply service for the social main body under the condition that accurate disaster fault information cannot be known, so that disaster uncertainty must be considered in the contract model. In addition, different power grid companies have different bearing capacities on disaster loss risks, and because toughness and economy are often a pair of contradictions, certain economy is sometimes sacrificed to improve toughness, and the opposite is sometimes required, so that a contract model needs to consider power grid company risk preference in pre-disaster contract formulation. Therefore, in this step, the pre-disaster resource purchasing cost portion corresponds to the budget of the pre-disaster power grid company for purchasing the external electric energy resource. The predicted post-disaster loss part corresponds to post-disaster power distribution network loss prediction, and the uncertainty of disasters and the risk preference of power grid companies are fully considered.
The topology reconstruction model modeling unit 520 is configured to establish a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, where the topology reconstruction model is used for characterizing a post-disaster power distribution network toughness recovery reconstructed topology structure.
In the embodiment of the invention, in the toughness recovery scene of the power distribution network, the power distribution network is often subjected to larger impact and possibly generates multiple faults, and in order to reduce disaster loss, the power distribution network is required to be subjected to topology reconstruction, so that a key load power supply path is ensured.
The confidence parameter determining unit 530 is configured to determine a confidence parameter, where the confidence parameter is used to characterize a risk preference of the power distribution network.
In the embodiment of the invention, the confidence parameter reflects the risk preference of the power grid company, when the confidence parameter value is smaller, the risk preference of the power grid company is lower, the consideration and research of most of fault scenes in the fault scene set are needed, and when the confidence parameter value is larger, the risk preference of the power grid company is higher, the consideration and research of the smaller part of fault scenes in the fault scene set are needed.
And the optimizing unit 540 is configured to perform optimization processing on the contract model according to the confidence parameter and preset disaster information under the structure of the topology reconstruction model, so as to obtain a pre-disaster planning result for toughness recovery of the power distribution network.
In the embodiment of the invention, in the toughness recovery of the power distribution network, the relation between the toughness and the economy is required to be balanced, and in the pre-disaster decision, the relation is expressed on the trade-off between the pre-disaster resource preparation cost and the post-disaster loss. If the power grid has extremely high requirements on toughness, the power grid is willing to pay very high pre-disaster preparation cost to cope with almost all possible disaster scenes; if the grid is properly relaxed in terms of toughness, and it is desired to cope with disasters in a more economical manner, resource preparation before the disaster may not cope with the most extreme disaster scenarios. In order to adapt to power grid risk preference under different conditions, the embodiment of the invention establishes a pre-disaster contract making scheme comprehensively considering pre-disaster preparation cost and disaster loss risk.
In the embodiment of the present invention, the topology reconstruction model modeling unit 520 specifically includes:
the prediction parameter determining subunit is used for determining fault scene information to be predicted and corresponding occurrence probability;
the fault scene generation subunit is used for obtaining a fault scene set according to the fault scene information and the occurrence probability;
and the reconstruction subunit is used for establishing the topology reconstruction model according to the fault scene set and a preset rule.
In the embodiment of the present invention, the optimizing unit 540 specifically includes:
the initialization subunit is used for initializing each fault scene in the fault scene set to obtain decision variables of each fault scene;
the iteration subunit is used for respectively carrying out at least one round of iteration on each fault scene, respectively optimizing the contract model of each fault scene in each round of iteration, and processing according to the occurrence probability of the fault scene to obtain an expected decision variableIs>And applying in each iteration an update of the multiplier +.>Wherein->Zeta being the VaR value s Corresponding multiplier(s)>As decision variable x s The penalty factor rho is used for controlling the updating amplitude of the decision variable of each iteration;
the iteration stop judgment unit is used for judging the decision variables of each fault sceneIs->And stopping iteration when the deviation of the (E) is smaller than the threshold value epsilon, and obtaining an optimal decision variable x and an optimal disaster loss threshold value zeta.
An embodiment of the present invention provides an entity structure diagram of an electronic device, as shown in fig. 6, with reference to fig. 6, where the electronic device may include: processor 610, communication interface (Communications Interface) 620, memory 630, and communication bus 640, wherein processor 610, communication interface 620, and memory 630 communicate with each other via communication bus 640. The processor 610 may call logic instructions in the memory 630 to perform the method for planning a pre-disaster recovery plan for toughness recovery of a power distribution network provided by the present invention, the method comprising: establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part; establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery; determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network; and under the structure of the topology reconstruction model, carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
Further, the logic instructions in the memory 630 may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art or a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a computer program product, including a computer program stored on a non-transitory computer readable storage medium, the computer program including program instructions, which when executed by a computer, enable the computer to perform a method for preparing a pre-disaster recovery plan for toughness of a power distribution network provided by the above methods, the method including: establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part; establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery; determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network; and under the structure of the topology reconstruction model, carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
In yet another aspect, an embodiment of the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, is implemented to perform the foregoing method for planning a pre-disaster recovery scenario for toughness recovery of a power distribution network, where the method is provided by the foregoing steps: establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part; establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery; determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network; and under the structure of the topology reconstruction model, carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result for recovering the toughness of the power distribution network.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (9)

1. A method for preparing a pre-disaster plan for toughness recovery of a power distribution network, wherein the method is used for preparing a contract for energy recovery by using public traffic resources during toughness recovery of the power distribution network, and comprises the following steps:
establishing a power distribution network toughness recovery contract model, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part;
establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a reconstructed topology structure of the post-disaster power distribution network toughness recovery;
determining a confidence parameter, wherein the confidence parameter is used for representing the risk preference of the power distribution network;
under the structure of a topology reconstruction model, optimizing the contract model according to the confidence parameters and preset disaster information to obtain a pre-disaster planning result of the toughness recovery of the power distribution network;
the method for establishing the toughness recovery contract model of the power distribution network comprises a pre-disaster purchased resource cost part and a predicted post-disaster loss part, and specifically comprises the following steps: the objective function of the contract model is:
where x represents a decision variable of the contract model, Decision vector, x, representing a contract model k Representing the purchase amount of the ith resource in the decision variable, cost k (x k ) Represents the purchase cost of the kth resource, p s Representing the probability of occurrence of the corresponding fault scene s, z s Representing auxiliary variables, alpha representing confidence parameters, ζ representing disaster damage threshold;
the objective function of the pre-disaster acquisition resource cost part is as follows:
wherein x is k Representing the purchase amount of the kth resource in the decision variable;
the objective function of the predicted post-disaster damage part is as follows:
where pi (x, s) represents the disaster loss in scene s.
2. The method for preparing a pre-disaster plan for toughness recovery of a power distribution network according to claim 1, wherein the method for preparing a contract model for toughness recovery of a power distribution network comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part, and specifically comprises the following steps:
definition pi (x, ζ) represents disaster damage of the distribution network, whereinRepresenting pre-disaster contract decision vectors, ζ represents a random variable vector, and for each x, t (x,) is a cumulative distribution function of disaster damage pi (x, ζ):
ψ(x,ζ)＝P{ξ|π(x,ξ)<ζ}
given the confidence parameter α∈ (0, 1), the risk value α -VaR of α is defined as follows:
ζ α (x)＝min{ζ|ψ(x,ζ)}≥α}
the above equation represents the minimum disaster damage in the scene where the damage occurs most severely with the probability of (1- α);
Given the confidence parameter α∈ (0, 1), the conditional risk value α -CVaR defining α is as follows:
φ α (x)＝E[ζ|ζ>ζ α (x)]
the above equation represents the expectation of disaster damage exceeding a-VaR, where the expected probability distribution is the probability distribution ψ obtained by readjusting the probability that ψ (x, ζ) exceeds a portion α α (x,ζ)：
And carrying out discrete sampling on the condition risk value to obtain occurrence probability of each scene, and approximating probability distribution to obtain an expression of an objective function of the predicted post-disaster loss part.
3. The method for preparing a pre-disaster planning for toughness recovery of a power distribution network according to claim 2, wherein the topology reconstruction model is used for representing a post-disaster topology structure of the toughness recovery reconstruction of the power distribution network and is constructed according to preset disaster information, and specifically comprises the following steps:
determining fault scene information to be predicted and corresponding occurrence probability;
obtaining a fault scene set according to the fault scene information and the occurrence probability;
and establishing the topology reconstruction model according to the fault scene set and a preset rule.
4. The method for preparing a pre-disaster plan for toughness recovery of a power distribution network according to claim 3, wherein under the structure of a topology reconstruction model, optimizing the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster plan result for toughness recovery of the power distribution network, specifically comprising:
Initializing each fault scene in the fault scene set to obtain decision variables of each fault scene;
at least one round of iteration is respectively carried out on each fault scene, and each fault scene is respectively carried out in each round of iterationOptimizing the contract model, and processing according to the occurrence probability of the fault scene to obtain an expected decision variableIs>And applying a fixed penalty factor ρ to update the multiplier in each round of iterations>Wherein->Zeta being the VaR value s Corresponding multiplier(s)>As decision variable x s The penalty factor rho is used for controlling the updating amplitude of the decision variable of each iteration;
decision variables for each fault scenarioIs->And stopping iteration when the deviation of the (E) is smaller than the threshold value epsilon, and obtaining an optimal decision variable x and an optimal disaster loss threshold value zeta.
5. The method for planning a pre-disaster recovery plan for toughness recovery of power distribution network according to claim 4, wherein said pre-disaster acquisition resource Cost portion comprises a Cost function Cost of decision variables in an objective function k (x k ) Setting as a quadratic function; under the structure of the topology reconstruction model, optimizing the contract model according to the confidence parameter and preset disaster information to obtain a pre-disaster planning result of the toughness recovery of the power distribution network, wherein the pre-disaster planning result comprises the following steps:
And inputting the optimal decision variable x, the optimal disaster loss threshold zeta and the confidence parameter alpha into the contract model target parameter to obtain a pre-disaster planning result for the toughness recovery of the power distribution network.
6. A pre-disaster planning device for toughness recovery of a power distribution network, for making a contract for energy recovery using public transportation resources at the time of toughness recovery of the power distribution network, the device comprising:
the system comprises a contract model modeling unit, a power distribution network toughness recovery contract model, a power distribution network toughness recovery control unit and a power distribution network toughness recovery control unit, wherein the contract model comprises a pre-disaster acquisition resource cost part and a predicted post-disaster loss part;
the topology reconstruction model modeling unit is used for establishing a topology reconstruction model of a power distribution network fault scene set according to preset disaster information, wherein the topology reconstruction model is used for representing a post-disaster power distribution network toughness recovery reconstructed topology structure;
the power distribution network risk determination system comprises a confidence parameter determination unit, a power distribution network risk determination unit and a power distribution network risk determination unit, wherein the confidence parameter determination unit is used for determining a confidence parameter, and the confidence parameter is used for characterizing power distribution network risk preference;
the optimization unit is used for carrying out optimization processing on the contract model according to the confidence parameter and preset disaster information under the structure of the topology reconstruction model to obtain a pre-disaster planning result of the toughness recovery of the power distribution network;
The method for establishing the toughness recovery contract model of the power distribution network comprises a pre-disaster purchased resource cost part and a predicted post-disaster loss part, and specifically comprises the following steps: the objective function of the contract model is:
where x represents a decision variable of the contract model,decision vector, x, representing a contract model k Representing the purchase amount of the ith resource in the decision variable, cost k (x k ) Represents the purchase cost of the kth resource, p s Representing fault fieldsProbability of corresponding occurrence of scene s, z s Representing auxiliary variables, alpha representing confidence parameters, ζ representing disaster damage threshold;
the objective function of the pre-disaster acquisition resource cost part is as follows:
wherein x is k Representing the purchase amount of the kth resource in the decision variable;
the objective function of the predicted post-disaster damage part is as follows:
where pi (x, s) represents the disaster loss in scene s.
7. The power distribution network toughness recovery pre-disaster planning device according to claim 6, wherein the topology reconstruction model modeling unit specifically comprises:
the prediction parameter determining unit is used for determining fault scene information to be predicted and corresponding occurrence probability;
the fault scene generating unit is used for obtaining a fault scene set according to the fault scene information and the occurrence probability;
And the reconstruction unit is used for establishing the topology reconstruction model according to the fault scene set and a preset rule.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, performs the steps of the pre-disaster planning method for toughness restoration of a power distribution network according to any one of claims 1 to 5.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the pre-disaster planning method for toughness restoration of a power distribution network according to any one of claims 1 to 5.
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