A comprehensive power outage planning method

Abstract

The present invention relates to a comprehensive power outage plan scheduling method, including obtaining a power outage plan for at least one alternative outage line; using the node voltage phase angle added at the first node of the alternative outage line as a state variable, constructing a mixed integer quadratic programming model with all linear constraints; constructing an objective function according to the power outage plan target; optimizing the model, and iterating safety verification. It can effectively realize the optimization adjustment of the power outage plan and provide results that meet N‑1 safety constraints and other expected fault constraints. In the case of limited power outage windows and large power outage demands, it can provide strong support for the arrangement of power grid operation modes.

Description

Technical Field

[0001] The invention relates to the technical field of power system blackout decision-making, and in particular to a comprehensive blackout plan scheduling method. Background Art

[0002] With the development of science and technology and the progress of society, people's requirements for power and power quality are also increasing day by day. Therefore, power grid blackout plans for the purpose of daily maintenance and overhaul of power grids have emerged to prevent large-scale power outages caused by power grid accidents and reduce the inconvenience caused by power grid failures to people's daily lives.

[0003] The power outage arrangement of power transmission and transformation equipment is a complex optimization problem, which requires balancing the goals of power supply adequacy, safety, and economic cost, and also requires comprehensive consideration of different requirements such as the coordination, mutual exclusivity, and time window of the power outage arrangement.

[0004] The existing actual maintenance outage plan strategy relies on the decision maker's experience and subjective judgment, and is only suitable for maintenance decision arrangements for a single power outage event. It is difficult to achieve the optimal decision for maintenance decision arrangements for multiple power outage events. In addition, the optimization model lacks comprehensive consideration of the power grid side, the user side, and the maintenance side, resulting in the maintenance plan being unable to guarantee indicators such as the minimum power outage amount for users and the highest user satisfaction. In addition, the formulation process of the power outage plan is cumbersome and cannot achieve the global optimum. It is urgent to propose an automatic outage plan scheduling method based on artificial intelligence and multi-objective constraints to solve the power grid maintenance plan decision problem for multiple power outage events. Summary of the invention

[0005] In order to overcome the above technical problems, the present invention provides a comprehensive power outage plan scheduling method, which can iteratively supplement the expected fault set according to the safety verification results, add section constraints in the optimization model, and realize the optimized scheduling of power outage plans.

[0006] To achieve the above object, the technical solution of the present invention is as follows:

[0007] A comprehensive power outage planning method, comprising:

[0008] Obtain at least one alternative outage plan for the outage equipment;

[0009] The node voltage phase angle added at the first node of the candidate outage equipment is used as a state variable, and a mixed integer quadratic programming model with all linear constraints is constructed;

[0010] Construct an objective function based on the outage plan objectives;

[0011] Optimize the model and iteratively update the safety check of the expected fault set.

[0012] Preferably, the construction constraint conditions are all linear mixed integer quadratic programming models, including:

[0013] Adjust unit output;

[0014] P G,min ≤P G,d ≤P G,max

[0015] Among them, P G,min , P G,max P is the lower and upper limits of the unit output regulation; G,d is the unit output vector;

[0016] All nodes j need to satisfy the power balance equation;

[0017]

[0018] Among them, P j,d represents the injected power of node j; P l,d and P k,d Respectively represent the power of branch l and branch k; F j represents the branch set with node j as the first node; T j represents the set of branches with node j as the end node; N bus is the number of system nodes.

[0019] Preferably, the mixed integer quadratic programming model in which all the construction constraints are linear also includes:

[0020] Virtual nodes are introduced to construct a branch disconnection linear constraint model to construct a node power balance equation, thereby constructing a full linear constraint outage plan optimization model;

[0021] The branch i connected between busbars m and n is connected with u i,d represents the branch disconnection situation, and the corresponding constraint condition is

[0022] -u i,d P i,max ≤P i,d ≤u i,d P i,max

[0023] (1-u i,d )M≤δ m,d -δ m′,d ≤(1+u i,d )M

[0024] P i,d =(δ m′,d -δ si,d ) / x i ; i∈Ψ

[0025] Among them, P i,max represents the transmission power limit of the branch; M is a large number; ψ represents the set of branches with maintenance plans; δ m,d ,δ m',d They represent the node voltage phase angles of node m and virtual node m′ respectively; δ si,d represents the phase angle of the sending end of branch i; x i represents the reactance value of branch i;

[0026] The active power flowing through each operating branch should be within the thermal stability limit;

[0027] |P l,d |≤P l,max

[0028] The branch power equation is:

[0029]

[0030] Among them, δ sl,d ,δ rl,d Respectively represent the voltage phase angles of the sending and receiving nodes of branch l; x l Represents the reactance value of branch l.

[0031] If necessary, add fault section constraints based on experience or safety check scan results:

[0032] |LODF h,k,d P k,d +P h,d |≤P h,max (h,k)∈Ψ d

[0033] Among them, ψ d Represents the critical fault section set; LODF h,k,d is the equipment outage transfer factor.

[0034] Preferably, the constructing the objective function comprises:

[0035] Use y i,d 、z i,d They represent the state change of the equipment from shutdown to operation or from operation to shutdown respectively. The objective function to minimize the state change of the equipment is constructed as follows:

[0036]

[0037] The objective function to minimize the power generation cost is constructed as follows:

[0038]

[0039] Where: α represents the impact weight of the deviation from the original plan; ui,d is the running status of device i on day d, u i,d =1 means running, u i,d =0 means exit; u i,d,0 Indicates the initial planned value of the equipment outage status; N is the number of substation equipment to be scheduled for outage; N G is the number of units; D is the number of days in the research period; P G,k,d is the power generation of unit k on day d, f i is the power generation cost function of unit k, i=1,…,N; d=1,…,D;

[0040] Related work has minimum downtime requirements for equipment downtime:

[0041]

[0042] u i,d -u i,d-1 =y i,d -z i,d

[0043]

[0044] Among them, D i,min represents the minimum maintenance time of equipment i; let u i,0 =1, i=1,…,N, it is assumed that there is no equipment outage from the previous cycle that continues to this cycle.

[0045] The beneficial effects of the present invention are:

[0046] This application proposes a comprehensive power outage scheduling method, which constructs a mixed integer quadratic programming model for power outage scheduling, iteratively supplements the expected fault set according to the safety verification results, adds section constraints in the optimization model, and realizes the optimization scheduling of the power outage plan. It can effectively realize the optimization adjustment of the power outage plan and provide results that meet N-1 safety constraints and other expected fault constraints. When the power outage window is limited and the power outage demand is large, it can provide strong support for the arrangement of power grid operation mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 A schematic diagram of a branch circuit breaking model of a comprehensive power outage plan arrangement method of the present invention;

[0049] Figure 2 A schematic diagram of a power outage plan optimization process of a comprehensive power outage plan scheduling method of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] In some of the processes described in the specification and claims of the present invention and the above-mentioned drawings, multiple operations appearing in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as S1, S2, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel.

[0052] The embodiment of the present invention provides a method for scheduling a comprehensive power outage plan. Figure 1 , which shows a schematic diagram of a power outage plan optimization process of an embodiment of a comprehensive power outage plan scheduling method of the present invention, a comprehensive power outage plan scheduling method, comprising:

[0053] Obtain at least one alternative outage plan for the outage equipment;

[0054] The node voltage phase angle added at the first node of the candidate outage equipment is used as a state variable, and a mixed integer quadratic programming model with all linear constraints is constructed;

[0055] Construct an objective function based on the outage plan objectives;

[0056] Optimize the model and iteratively update the safety check of the expected fault set.

[0057] Preferably, the construction constraint conditions are all linear mixed integer quadratic programming models, including:

[0058] Adjust unit output;

[0059] P G,min ≤P G,d ≤P G,max

[0060] Among them, P G,min , P G,max P is the lower and upper limits of the unit output regulation; G,d is the unit output vector;

[0061] All nodes j need to satisfy the power balance equation;

[0062]

[0063] Among them, P j,d represents the injected power of node j; P l,d and P k,d Respectively represent the power of branch l and branch k; F j represents the branch set with node j as the first node; T j represents the set of branches with node j as the end node; N bus is the number of system nodes.

[0064] The power outage arrangement of power transmission and transformation equipment is a complex optimization problem, which needs to balance the goals of power supply adequacy, safety and economic cost, and also needs to comprehensively consider the coordination, mutual exclusion, time window and other requirements of the power outage arrangement. In addition, the power outage arrangement will cause different changes to the grid structure in different time periods, further increasing the difficulty of setting safety constraints.

[0065] In terms of constraints, the constraints include not only system safety operation constraints and maintenance management constraints, but also coordination constraints between maintenance projects, such as simultaneous maintenance constraints, mutually exclusive maintenance constraints, maintenance resource constraints, maintenance time constraints, maintenance risk constraints, etc. In terms of safe operation of the power grid, the equipment status and system flow in the maintenance plan model are coupled with each other, the safety constraints are complex, and the combination of maintenance status and N-1 status to be considered further increases the scale of the problem.

[0066] Preferably, the mixed integer quadratic programming model in which all the construction constraints are linear also includes:

[0067] Virtual nodes are introduced to construct a branch disconnection linear constraint model to construct a node power balance equation, thereby constructing a full linear constraint outage plan optimization model;

[0068] The branch i connected between busbars m and n is connected with u i,d represents the branch disconnection situation, and the corresponding constraint condition is

[0069] -u i,d P i,max ≤P i,d ≤u i,d P i,max

[0070] (1-u i,d )M≤δ m,d -δ m′,d ≤(1+u i,d )M

[0071] P i,d =(δ m′,d -δsi,d ) / x i ; i∈Ψ

[0072] Among them, P i,max represents the transmission power limit of the branch; M is a large number; ψ represents the set of branches with maintenance plans; δ m,d ,δ m',d They represent the node voltage phase angles of node m and virtual node m′ respectively; δ si,d represents the phase angle of the sending end of branch i; x i represents the reactance value of branch i;

[0073] The active power flowing through each operating branch should be within the thermal stability limit;

[0074] |P l,d |≤P l,max

[0075] The branch power equation is:

[0076]

[0077] Among them, δ sl,d ,δ rl,d Respectively represent the voltage phase angles of the sending and receiving nodes of branch l; x l Represents the reactance value of branch l.

[0078] If necessary, add fault section constraints based on experience or safety check scan results:

[0079] |LODF h,k,d P k,d +P h,d |≤P h,max (h,k)∈Ψ d

[0080] Among them, ψ d Represents the critical fault section set; LODF h,k,d is the equipment outage transfer factor.

[0081] Preferably, the constructing the objective function comprises:

[0082] Use y i,d 、z i,d They represent the state change of the equipment from shutdown to operation or from operation to shutdown respectively. The objective function to minimize the state change of the equipment is constructed as follows:

[0083]

[0084] The objective function to minimize the power generation cost is constructed as follows:

[0085]

[0086] Where: α represents the impact weight of the deviation from the original plan; u i,d is the running status of device i on day d, u i,d =1 means running, u i,d =0 means exit; u i,d,0 Indicates the initial planned value of the equipment outage status; N is the number of substation equipment to be scheduled for outage; N G is the number of units; D is the number of days in the research period; P G,k,d is the power generation of unit k on day d, f i is the power generation cost function of unit k, i=1,…,N; d=1,…,D;

[0087] Related work has minimum downtime requirements for equipment downtime:

[0088]

[0089] u i,d -u i,d-1 =y i,d -z i,d

[0090]

[0091] Among them, D i,min represents the minimum maintenance time of equipment i; let u i,0 =1, i=1,…,N, it is assumed that there is no equipment outage from the previous cycle that continues to this cycle.

[0092] As those skilled in the art will know, the outage of power transmission and transformation equipment will cause changes in the topology of the power grid, resulting in the redistribution of power flows in other equipment, affecting the reliability of the entire network. In an embodiment of the present invention, a reliability-based power transmission maintenance planning model is established with the goal of minimizing load reduction. Further considering the risk balance of each maintenance period, an optimized maintenance model for the transmission system based on equal risk theory is established, and a maintenance plan with equal risk is proposed. The problem of transmission line maintenance planning is studied with the goal of minimizing the risk increase, and a transmission line maintenance planning model is proposed. Taking the maximum system load supply capacity as the optimization goal, the impact of line maintenance on system reliability is mainly considered, and the economic goal is used as the objective function. A random fuzzy dual uncertainty mathematical model containing complex network constraints in the transmission line maintenance planning problem is established.

[0093] Maintenance plan optimization is essentially a multi-objective, multi-constrained nonlinear mixed integer programming problem. Single-objective optimization problems cannot meet the actual needs of decision makers for diversified optimization objectives. Considering the two objectives of minimizing the deviation between maintenance time and due maintenance time and reasonable workload distribution, a maintenance optimization model is established. Taking the minimum transmission maintenance cost and the maximum available transmission capacity as the optimization objectives, a transmission maintenance optimization model is constructed, and the model is solved using Lagrangian relaxation planning technology. In the maintenance strategy optimization modeling, the system peak-shaving capacity and wind power output uncertainty are considered. Taking the weighted sum of the power system production cost, maintenance cost and equivalent peak-shaving capacity shortage as the optimization objective, an integrated maintenance optimization model for the power generation and transmission system is established, and a suitable maintenance plan is formulated. Taking the maintenance cost and expected power shortage as the minimum objective, a multi-objective optimization model for the transmission network maintenance plan is established, and an improved multi-objective particle swarm algorithm based on a niche is proposed to solve it, and the maintenance cost and reliability objectives of the maintenance plan are comprehensively coordinated. The same optimization goal is established, and an interactive multi-objective decision-making solution method is proposed. The multi-objective optimization model is decomposed into multiple single-objective decision models for interactive solution, which is convenient for practical operation and application. The optimization goal is to minimize the comprehensive risk cost composed of equipment failure risk and power grid operation risk, hoping to obtain the optimal technical and economic comprehensive state maintenance decision-making plan. In actual engineering, under the premise of meeting the N-1 criterion, it is necessary to try to meet the power outage window reported by the operation and maintenance unit, while avoiding unnecessary repeated power outages and avoiding multiple changes in equipment status to reduce operational risks. It is also a goal that needs to be considered.

[0094] This application proposes a comprehensive power outage scheduling method, which constructs a mixed integer quadratic programming model for power outage scheduling, iteratively supplements the expected fault set according to the safety verification results, adds section constraints in the optimization model, and realizes the optimization scheduling of the power outage plan. It can effectively realize the optimization adjustment of the power outage plan and provide results that meet N-1 safety constraints and other expected fault constraints. When the power outage window is limited and the power outage demand is large, it can provide strong support for the arrangement of power grid operation mode.

[0095] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for scheduling a comprehensive power outage, characterized in that: include: Obtain at least one alternative outage plan for the outage equipment; The node voltage phase angle added at the first node of the candidate outage equipment is used as a state variable, and a mixed integer quadratic programming model with all linear constraints is constructed; Construct an objective function based on the outage plan objectives; Optimize the model and iteratively update the safety check of the expected fault set; The mixed integer quadratic programming model in which all the construction constraints are linear includes: Adjust unit output; P G,min ≤P G,d ≤P G,max Among them, P G,min , P G,max P is the lower and upper limits of the unit output regulation; G,d is the unit output vector; All nodes j need to satisfy the power balance equation; Among them, P j,d represents the injected power of node j; P l,d and P k,d Represent the power of branch l and branch k respectively; F j represents the branch set with node j as the first node; T j represents the set of branches with node j as the end node; N bus is the number of system nodes; The mixed integer quadratic programming model in which all the construction constraints are linear also includes: Virtual nodes are introduced to construct a branch disconnection linear constraint model to construct a node power balance equation, thereby constructing a full linear constraint outage plan optimization model; The branch i connected between busbars m and n is connected with u i,d represents the branch disconnection situation, and the corresponding constraint condition is -u i,d Q i,max ≤P i,d ≤u i,d Q i,max (1-u i,d )M≤δ m,d -δ m′,d ≤(1+u i,d )M P i,d =(δ m′,d -d si,d ) / x i ;i∈Ψ Among them, P i,max represents the transmission power limit of the branch; M is a number; ψ represents the set of branches with maintenance plans; δ m,d ,δ m',d Respectively represent the node voltage phase angles of node m and virtual node m'; δ si,d represents the phase angle of the sending end of branch i; x i represents the reactance value of branch i; The active power flowing through each operating branch should be within the thermal stability limit; |P l,d |≤P l,max The branch power equation is: Among them, δ sl,d , δ rl,d Respectively represent the voltage phase angles of the sending and receiving nodes of branch l; x l It represents the reactance value of branch l; It is necessary to add fault section constraints based on experience or safety check scan results: |LODF h,k,d P k,d +P h,d |≤P h,max (h,k)∈Ψ d Among them, ψ d Represents the critical fault section set; LODF h,k,d is the equipment outage transfer factor.

2. A method for scheduling a comprehensive power outage according to claim 1, characterized in that: The constructing of the objective function comprises: Use y i,d 、z i,d They represent the state change of the equipment from shutdown to operation or from operation to shutdown respectively. The objective function to minimize the state change of the equipment is constructed as follows: The objective function to minimize the power generation cost is constructed as follows: Where: α represents the impact weight of the deviation from the original plan; u i,d is the running status of device i on day d, u i,d =1 means running, u i,d =0 means exit; u i,d,0 Indicates the initial planned value of the equipment outage status; N is the number of substation equipment to be scheduled for outage and transportation; N G is the number of units; D is the number of days in the research period; P G,k,d is the power generation of unit k on day d, f i is the power generation cost function of unit k, i=1,…,N; d=1,…,D; Related work has minimum downtime requirements for equipment downtime: you i,d -u i,d-1 =y i,d -z i,d Among them, D i,min represents the minimum maintenance time of equipment i; let u i,0 =1, i=1,…,N, it is assumed that there is no equipment outage from the previous cycle that continues to this cycle.

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