CN116565872A - Alternating current power grid reliability rapid control method and device based on state similarity - Google Patents

Alternating current power grid reliability rapid control method and device based on state similarity Download PDF

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CN116565872A
CN116565872A CN202310082013.7A CN202310082013A CN116565872A CN 116565872 A CN116565872 A CN 116565872A CN 202310082013 A CN202310082013 A CN 202310082013A CN 116565872 A CN116565872 A CN 116565872A
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state
reliability
power
similarity
state similarity
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侯恺
刘泽宇
贾宏杰
朱乐为
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Tianjin University
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Tianjin University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/50—Controlling the sharing of the out-of-phase component
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract

The invention discloses a method and a device for rapidly controlling the reliability of an alternating current power grid based on state similarity, wherein the method comprises the following steps: based on the state similarity characteristics, converting an alternating current OPF model of the system state into a tide equation set, decoupling and iteratively solving; carrying out feasibility and optimality verification on the obtained tide square course group solution; if the verification is passed, calculating the optimal load reduction amount of the state by using the obtained solution, and if the verification is not passed, solving the optimal load reduction amount of the state by using a nonlinear optimization algorithm; and calculating the reliability index of the power system by integrating the optimal load reduction amount of each state, setting the risk level of the power system according to the reliability index, judging whether safety precaution is needed, counting the contribution of the system state to the reliability index, and taking measures for the power system state 1% in front of the rank. The device comprises: a processor and a memory. The invention greatly improves the reliability control efficiency of the alternating current power grid, and further meets the high timeliness requirement of reliability calculation in the alternating current power grid field.

Description

Alternating current power grid reliability rapid control method and device based on state similarity
Technical Field
The invention relates to the field of reliability control of power systems, in particular to a method and a device for rapidly controlling reliability of an alternating current power grid based on state similarity.
Background
In recent years, with the continuous expansion of the scale of the power system, new technologies such as renewable energy sources, electric vehicles, alternating current and direct current bring new uncertainty and risk to the safe and stable operation of the power system, and higher requirements are put on the reliability control of the power system.
There are two main types of reliability control [1] : monte Carlo Simulation (MCS) and State Enumeration (SE). In both methods, an Optimal Power Flow (OPF) calculation is required for a system state set, and the power flow distribution of the power system in each state is analyzed to obtain a system load reduction caused by a fault, so as to calculate a reliability index of the whole system. However, as the scale of the electric power system increases day by day, the number of system states increases exponentially, and the corresponding massive sub-OPF calculation brings heavy calculation burden to reliability evaluation, so that the traditional reliability control method is difficult to give the latest risk level of the system in time, and serious problems such as too late risk early warning and even missed early warning are easily caused, and huge socioeconomic loss is likely to be brought.
In order to improve reliability control efficiency, the most common approach is to reduce the number of system states. Document [2 ]]A state space reduction technique is proposed to reduce the number of samples, which can remove the system state without load loss in advance. Variance reduction techniques are also applied to accelerate the convergence speed of MCS methods, including: important sampling [3] Dual variable [4] And cross entropy method [5] . Document [6]A state enumeration reliability evaluation algorithm based on quick ordering is provided, which can quickly select a system according to probability descending orderAnd (5) a system state. Further, document [7]A rapid fault screening technology is provided, and the most serious fault state is searched according to probability and fault capacity. Furthermore, document [8]A state enumeration method (IISE) based on impact delta is provided, which can transfer part of the impact of a higher-order state to a corresponding lower-order state. However, the method is limited by the evaluation accuracy, the reduction degree of the state quantity of the method is limited, the reliability control still needs to process a system state set with huge scale, and the high requirement of the actual application on the efficiency is difficult to meet.
The method for improving the analysis and calculation speed of the single system state is also a method for improving the reliability control efficiency. Aiming at massive system state sets, if the OPF calculation speed of each system state can be accelerated, the reliability control efficiency can be greatly improved. Document [9] applies post-optimization analysis to the reliability control of a power generation and transmission system, and rapidly derives the optimal load reduction amount of the remaining states by using the base state. The literature [10] proposes to build a power transmission line state dictionary set by using a multi-parameter planning method, so as to rapidly calculate massive states generated by load fluctuation and generator faults, and avoid a large amount of optimization solving processes. However, the above studies are limited to power system direct current OPF calculation, and are difficult to adapt to alternating current OPF models.
Reference to the literature
[1]W.Li,Risk Assessment of Power Systems:Models Methods and Applications.Hoboken,NJ,USA:Wiley,2014.
[2]C.Singh and J.Mitra,“Composite System Reliability Evaluation Using State Space Pruning,”IEEE Trans.Power Syst.,vol.12,no.1,pp.471-479,Feb.1997.
[3]Q.Chen and L.Mili,“Composite Power System Vulnerability Evaluation to Cascading Failures Using Importance Sampling and Antithetic Variates,”IEEE Trans.Power Syst.,vol.28,no.3,pp.2321-2330,Aug.2013.
[4]R.Billinton and A.Jonnavithula,“Composite System Adequacy Assessment Using Sequential Monte Carlo Simulation with Variance Reduction Techniques,”IET Proc.-Gener.Transm.Distrib.,vol.144,no.1,pp.1-6,Jan.1997.
[5]Y.Wang,V.Vittal,M.Abdi-Khorsand,and C.Singh,“Probabilistic Reliability Evaluation Including Adequacy and Dynamic Security Assessment,”IEEE Trans.Power Syst.,vol.35,no.1,pp.551-559,Jan.2020.
[6]H.Liu,Y.Sun,P.Wang,and L.Cheng,“A Novel States Selection Technique for Power System Reliability Evaluation,”Elect.Power Syst.Res.,vol.78,pp.1019-1027,2008.
[7]Y.Jia,P.Wang,X.Han,J.Tian,and C.Singh,“A Fast Contingency Screening Technique for Generation System Reliability Evaluation,”IEEE Trans.Power Syst.,vol.28,no.4,pp.4127-4133,Nov.2013.
[8]K.Hou,H.Jia,X.Li,X.Xu,Y.Mu,T.Jiang,and X.Yu,“Impact-increment Based Decoupled Reliability Assessment Approach for Composite Generation and Transmission Systems,”IET Gener.Transm.Distrib.,vol.12,no.3,pp.586-595,Feb.2018.
[9]A.Safdarian,M.Fotuhi-Firuzabad,F.Aminifar,and M.J.Ghorbany,“Composite Power System Adequacy Assessment Based on the Post Optimal Analysis,”Turk.J.Elec.Eng.Comput.Sci.,vol.21,no.1,pp.90-106,Jan.2013.
[10]P.Yong,N.Zhang,C.Kang,Q.Xia,and D.Lu,“MPLP-based Fast Power System Reliability Evaluation Using Transmission Line Status Dictionary,”IEEE Trans.Power Syst.,vol.34,no.2,pp.1630-1640,Mar.2019.
Disclosure of Invention
The invention provides a method and a device for rapidly controlling the reliability of an alternating current power grid based on state similarity, which accelerate the calculation speed of an alternating current OPF through the similarity among systems, convert nonlinear optimization problems into a nonlinear equation set based on the existing state similarity information, greatly improve the efficiency of the reliability control of the alternating current power grid, further meet the high timeliness requirement on the reliability calculation in the field of the alternating current power grid, and are described in detail below:
an ac power grid reliability rapid control method based on state similarity, the method comprising:
constructing an alternating current OPF model for each state in a power system state set, converting the alternating current OPF model into a power flow equation set based on state similarity characteristics, decoupling and iteratively solving the power flow equation set;
checking whether the obtained tide equation set solution is the optimal solution of the alternating current OPF model, comprising the following steps: feasibility verification and optimality verification;
for the system state passing the verification, calculating the optimal load reduction amount of the state by using the obtained equation set solution, and for the system state failing to pass the verification, solving the optimal load reduction amount of the state by using a nonlinear optimization algorithm;
and calculating the reliability index of the power system by integrating the optimal load reduction amount of each state, setting the risk level of the power system according to the reliability index, judging whether safety precaution is needed, counting the contribution of the power system state to the reliability index, and taking measures for the power system state 1% in front of the rank.
Wherein the state similarity feature comprises:
a branch circuit of the tidal current touch limit reaches a first phase angle, a first voltage, a first active power reduction, a first active power output and a first active power output of the generator of a variable lower limit;
a second phase angle reaching an upper limit of the variable, a second voltage, a second active reduction, a second reactive reduction, a second active output of the generator, and a second reactive output;
for the two power system states, if the state similarity characteristics of the two states are identical, indicating that the state similarity exists between the two states, and storing the state similarity characteristics at the moment into a state similarity database;
and converting the communication OPF model into an equation set based on the state similarity characteristics in the state similarity database.
Further, the decoupling and iterative solving of the tidal current equation set is as follows:
decoupling variables into two parts X α And X β ，X α Including phase angle and voltage variables, X β Including active power variable and reactive power variable, and accordingly power flowThe equation set is divided into two parts, and X is updated in an alternate iteration mode α And X β Until the maximum number of iterations N is reached max Or convergence accuracy tol, and the solution of the final tide equation set is [ X ] α ,X β ]；
Wherein the feasibility check is used to check whether the resulting solution satisfies the inequality constraint of the ac OPF model.
Further, the optimality check is: judging whether or not there isAnd->Such that:
wherein G is j (X) represents a jth constraint in the flow balance constraints; h k (X) represents the kth constraint in the inequality constraints of the touch limit.
Wherein the method comprises the following steps:
when the verification fails, calculating by adopting other state similar features in the state similarity library until the obtained solution passes the verification, or the state similarity library has no feature to be selected;
if all solutions obtained based on the existing features in the state similarity library cannot pass the verification, the state of the power system is proved to have a new state similarity feature, the optimal load reduction amount of the state of the power system is required to be solved through a nonlinear optimization algorithm, and the state similarity feature information of the state of the power system is added into a state similarity database.
An ac grid reliability fast control device based on state similarity, the device comprising: a processor and a memory, the memory having stored therein program instructions that cause the apparatus to perform any of the method steps described in the memory to be invoked by the processor.
The technical scheme provided by the invention has the beneficial effects that:
1. the invention realizes the rapid and accurate reliability control, which is crucial to the safe and reliable operation of the system, and along with the adjustment of the energy structure and the large-scale access of new energy into the power grid, the reliability control of the power system is more focused on the online short-time evaluation risk index;
2. the method can rapidly calculate the reliability index of the power system, and can monitor the operation risk level of the power system under the rapid change of the source load, so that the operation state of the system can be more intuitively known, and corresponding lifting measures can be formulated;
3. according to the method, the optimal power flow model of the alternating current power grid can be calculated based on the state similarity information, and an equation set solving algorithm based on the state similarity is adopted to replace an optimizing algorithm, so that the optimal power flow distribution of the system is obtained through rapid analysis.
Drawings
FIG. 1 is a flow chart of a method for quickly controlling the reliability of an AC power grid based on state similarity;
fig. 2 is a schematic structural diagram of a fast control device for reliability of an ac power grid based on state similarity;
FIG. 3 is a schematic diagram showing comparison of computational efficiency of various methods.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in further detail below.
Aiming at the problems existing in the background technology, the embodiment of the invention provides an alternating current power grid reliability control method based on state similarity, and an alternating current power flow equation set based on state similarity is established by combining the power flow characteristics of a power system, so that the reliability index of a computing system is obtained by quick solving, and a reliability quick control device suitable for an alternating current power system is further constructed.
Example 1
A method for controlling reliability of an ac power grid based on state similarity, see fig. 1, the method comprising the steps of:
101: generating a system state set according to real-time system operation data, load and renewable energy data;
wherein, the system state s is a combination of the element state z and the load and the renewable energy output level p, and the expression is as follows:
s＝[z p] (1)
z＝[z line z gen ] (2)
p＝[S d S gmin S gmax ] (3)
wherein z is line And z gen Is the state of the transmission line and the generator; s is S d The node load is; s is S gmin And S is gmax Is the upper and lower limits of the generator output, where the generator includes: conventional generators and distributed power sources such as wind power, photovoltaic and the like.
102: an alternating current OPF model is constructed according to the system state set and is used for analyzing and calculating the optimal load reduction amount of the power system under the fault, and the model is as follows:
min f LC ＝∑P LC (4)
the constraints are as follows:
G(X)＝[U]Y bus U * -S LC -C g S g +S d ＝0 (5)
F min ≤|Y ft U|≤F max (6)
U min ≤U≤U max (7)
S gmin ≤S g ≤S gmax (8)
0≤S LC ≤S d (9)
wherein f LC Is an objective function; s is S LC And P LC Complex power and active power of load reduction respectively; (5) Watch (watch)Showing a load flow balance constraint, wherein G (X) is the load flow balance constraint; u and S g Node voltage and generator output, respectively; u (U) * Represents the conjugation of U; y is Y bus Is a node admittance matrix; c (C) g Is a generator connection matrix; (6) displaying branch tidal current constraints; y is Y ft Is a branch admittance matrix; f (F) min And F max The lower limit and the upper limit of the branch tide are respectively; (7) represents a voltage constraint; v (V) min And V max Is the lower and upper limits of the voltage; (8) And (9) is a generator output constraint and a load shedding constraint.
103: establishing a tide equation set based on state similarity, and further rapidly calculating to obtain the optimal load reduction amount of the system state;
the optimal solutions for different system states when calculating the optimal load reduction amount often have the same optimization characteristics, a phenomenon which may be referred to as state similarity. The state similarity features include: and the branch circuit with the current limit reaches the phase angle, voltage, active reduction, reactive reduction, active output and reactive output of the generator at the lower limit of the variable, and reaches the phase angle, voltage, active reduction, reactive reduction, active output and reactive output of the generator at the upper limit of the variable. For two system states, the element state parameters, the load and the renewable energy output level are different, if the state similarity features of the two states are identical, the state similarity exists between the two system states, and the optimized feature information can be stored into a state similarity database as a state similarity feature.
The alternating OPF model of the system state can be converted into a system of equations based on the state similarity information in the state similarity database. For example, if the branch flow constraint (6) is bounded, the corresponding inequality constraint should be converted to an equality constraint. The variable in constraint (7), (8) or (9) is bounded, and the variable becomes a constant value. Thus, a system of state similarity based flow equations F (X) is derived:
wherein, the liquid crystal display device comprises a liquid crystal display device,and->Representing real and imaginary parts; v and θ are voltage magnitude and phase angle; p (P) LC And Q LC Active and reactive load reduction, respectively; p (P) g And Q g Active and reactive power for the generator; n is n b ,n g And n is l Node number, generator number and line number respectively; a, a l Is the number of touch lines; a, a 1 ,a 2 ,a 3 ,a 4 ,a 5 Is the number of touch-limited variables, a x ＝a 1 +a 2 +a 3 +a 4 +a 5 。
But due to (4 n) b +2n g -a x )>>(2n b +a l ) F (X) is a system of under-determined equations with an infinite number of solutions. In order to solve the equation set, the embodiment of the invention provides an alternate iteration solution for a state similarity trend equation set. First decoupling the variable into two parts X α And X β ，X α Including phase angle and voltage variables, X β The system comprises an active power variable and a reactive power variable, and further the equation set (10) is split into two parts:
wherein G is * Representing the rest of the flow balance equation; s is S b ＝S LC +C g S g 。
A part of a nonlinear equation set F α (X α )：
Wherein, the liquid crystal display device comprises a liquid crystal display device,and->Respectively carrying out forward and reverse touch branch tidal current constraint; a, a α ＝a 1 +a 2 . If equation (13) is an overdetermined system of equations, then the least squares method is used to solve the system of equations.
Another part is a linear equation set F β (X β )：
Wherein P is b ＝P LC +C g P g ；Q b ＝Q LC +C g Q g ；a 7 And a 8 Is the number of touch variables; a, a β ＝a 7 +a 8 。
Further alternate iterative updating of two solutions X α And X β ：
Wherein, the liquid crystal display device comprises a liquid crystal display device,representing the ith iteration X β Is a value of (2); />Representing the ith iteration X β Is a new value of (1); e represents an identity matrix;representing the ith iteration equation set F β For X β Is a jacobian matrix of (c).
In the same way as described above,
wherein, the liquid crystal display device comprises a liquid crystal display device,representing the ith iteration X α Is a value of (2); />Representing the ith iteration X α Is a new value of (1); />Representing the ith iteration equation set F α For X α Jacobian matrix of (a); g θ And G V Representing the derivatives of the flow balance equation G on V and theta; />And H V f Representing forward branch flow equation H f Derivatives of θ and V; />And->Representing the reverse branch flow equation H t Derivatives of θ and V.
Equations (17) and (19) are alternately iterated until a maximum number of iterations N is reached max Or the convergence accuracy tol is set,
i>N max (21)
ending the iteration to obtain a solution
104: checking whether the obtained solution X is an optimal solution of the ac OPF model, including: and (5) carrying out feasibility verification and optimality verification.
The feasibility check is to check whether the resulting solution satisfies the inequality constraint of the ac OPF model, i.e. equations (6), (7), (8), (9).
The optimality check is to judge whether or not there isAnd->Such that:
wherein G is j (X) represents a jth constraint in the flow balance constraints; h k (X) represents the kth constraint in the inequality constraints of the touch limit.
For the optimality check, the following conditions are employed to determine whether the resulting solution satisfies the optimality condition (23):
wherein H (X) represents an inequality constraint; rank represents the rank of the matrix.
If the verification is passed, the obtained solution is an optimal solution of the alternating current OPF model, and the optimal load reduction of the corresponding system state can be obtained through the optimal solution; otherwise, the verification is not passed, and the obtained solution is not the optimal solution of the alternating current OPF model.
Checking that the non-passing state does not accord with the state similarity feature requires calculation by adopting other features in the state similarity library until the obtained solution passes the checking, or the state similarity library has no feature to be selected. If all solutions obtained based on the existing features in the state similarity library cannot pass the verification, the system state is proved to have a new state similarity feature, the optimal load reduction of the state is required to be solved through an optimization algorithm, and the state similarity feature information of the state is added into a state similarity database.
105: and calculating the reliability index of the system according to the optimal load reduction amount of each state, setting the risk level of the system according to the reliability index, giving an operation dispatcher to judge whether safety pre-warning is needed, counting the contribution of each system state to the reliability index, and taking measures preferentially for the system state with the contribution of the reliability index being ranked as 1% of the top.
If the load state or the renewable energy source output state of a certain system has great contribution to the reliability index, operation schedulers need to arrange a scheduling plan in advance, and the schedulable flexible resources are utilized to increase the electric energy supply or reduce the electric load in advance, so that the safe and reliable power supply of the system is ensured.
If the fault state of a certain system element has a large contribution to the reliability index, the element is a weak link of the whole system, and an operation dispatcher should increase the maintenance monitoring force of the element, replace the ageing element in time and ensure the healthy operation of the element. If the element is a generator, a new generator set can be put into production, and the spare power generation capacity is improved. If the element is a line and the importance of load reduction is high, a new power supply line can be added, and the power supply redundancy is improved. If the common fault state of a plurality of system elements has great contribution to the reliability index, operation scheduling personnel should examine the system elements in time, and measures for improving the transmission capacity of the line and increasing the output capacity of the generator are adopted to reduce the load reduction amount of the state.
In addition, after each reliability evaluation control, the state similarity database obtained by the calculation is stored and used for the next reliability control.
Example 2
An ac power grid reliability rapid assessment device based on state similarity, see fig. 2, the device comprising: the system comprises a processor, a memory, an input interface, an output interface, a network adapter, a power module and a bus.
The memory stores program instructions and calculation data, and the processor calls the program instructions and calculation data in the memory to enable the steps of the alternating current power grid reliability rapid assessment method based on state similarity to be executed. The program instructions stored in the memory comprise a state rapid analysis module, a result verification module and an index calculation module. The state rapid analysis module is used for rapidly calculating and analyzing the optimal load reduction amount of the system state based on the state similarity information. The result checking module is used for checking the feasibility and the optimality of the obtained solution, thereby ensuring the accuracy of the method. The index calculation module calculates and obtains the reliability index of the system according to the optimal load reduction amount and the occurrence probability of each system state. The device may communicate with the power system via a wired or wireless network, or may be integrated into the power system.
The framework of the method proposed by the embodiment of the invention is shown in fig. 1, and the detailed description is as follows:
after the system operation data, load and renewable energy source data are input, a system state set is generated through a state enumeration method and a Monte Carlo simulation method so as to simulate each power system fault scene.
And then, constructing a tide optimization objective function and constraint based on the system state, and rapidly solving the optimal load reduction amount of the system state by using the state similarity information. Further judging whether the result meets feasibility and optimality, if so, obtaining a solution which is the optimal solution; if not, the state similarity database needs to be traversed continuously to find whether a solution which can pass the verification exists, if not, the state influence of the computing system is optimized, and the state related information is stored in the state similarity database.
Finally, all system states are analyzed, and a system reliability index is calculated based on the probability and load reduction of all states. Taking the expected value of insufficient power (EENS) as a reliability index, it can be calculated by the following formula:
wherein T is the system evaluation time; p(s) is the probability of state s; i(s) is the optimum load reduction amount for state s.
Example 3
The embodiment of the invention performs experimental tests on an IEEE-RTS79 system. The system comprises 24 nodes, 32 generator sets and 38 branches, and the peak loads are 2850MW respectively. The experiment is based onR2020b platform, computer equipped with double +.>Platinum 8180CPU (ES) 28×1.8GHz and 128GB RAM.
The state similarity method is combined with the Monte Carlo method, the influence increment method and the state enumeration method, and the calculation results are shown in table 1 and fig. 3:
TABLE 1 reliability evaluation results of RTS-79 systems
As shown in Table 1, the state similarity method is about 20 times faster than the conventional method, only a small portion of the system states are solved by the OPF optimization algorithm, and the rest of the states are rapidly solved by the state similarity equation set. In addition, the errors of the state similarity method are within 1%, and the accuracy of the calculated result is verified. Therefore, the rapid evaluation method based on the state similarity in the embodiment of the invention can greatly improve the reliability control efficiency of the alternating current power grid.
The embodiment of the invention does not limit the types of other devices except the types of the devices, so long as the devices can complete the functions.
Those skilled in the art will appreciate that the drawings are schematic representations of only one preferred embodiment, and that the above-described embodiment numbers are merely for illustration purposes and do not represent advantages or disadvantages of the embodiments.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.

Claims (7)

1. An alternating current power grid reliability rapid control method based on state similarity, which is characterized by comprising the following steps:
constructing an alternating current OPF model for each state in a power system state set, converting the alternating current OPF model into a power flow equation set based on state similarity characteristics, decoupling and iteratively solving the power flow equation set;
checking whether the obtained tide equation set solution is the optimal solution of the alternating current OPF model, comprising the following steps: feasibility verification and optimality verification;
for the system state passing the verification, calculating the optimal load reduction amount of the state by using the obtained equation set solution, and for the system state failing to pass the verification, solving the optimal load reduction amount of the state by using a nonlinear optimization algorithm;
and calculating the reliability index of the power system by integrating the optimal load reduction amount of each state, setting the risk level of the power system according to the reliability index, judging whether safety precaution is needed, counting the contribution of the power system state to the reliability index, and taking measures for the power system state 1% in front of the rank.
2. The method for quickly controlling reliability of an ac power grid based on state similarity according to claim 1, wherein said state similarity feature comprises:
a branch circuit of the tidal current touch limit reaches a first phase angle, a first voltage, a first active power reduction, a first active power output and a first active power output of the generator of a variable lower limit;
a second phase angle reaching an upper limit of the variable, a second voltage, a second active reduction, a second reactive reduction, a second active output of the generator, and a second reactive output;
for the two power system states, if the state similarity characteristics of the two states are identical, indicating that the state similarity exists between the two states, and storing the state similarity characteristics at the moment into a state similarity database;
and converting the communication OPF model into an equation set based on the state similarity characteristics in the state similarity database.
3. The method for rapidly controlling reliability of an ac power grid based on state similarity according to claim 1, wherein said decoupling and iteratively solving a system of tide equations is:
decoupling variables into two parts X α And X β ，X α Including phase angle and voltage variables, X β The method comprises active power variable and reactive power variable, and correspondingly, a tide equation set is split into two parts, and X is updated in an alternate iteration mode α And X β Until the maximum number of iterations N is reached max Or convergence accuracy tol, and the solution of the final tide equation set is [ X ] α ,X β ]。
4. The method for quickly controlling reliability of an ac power grid based on state similarity according to claim 1, wherein the feasibility check is used for checking whether the obtained solution satisfies the inequality constraint of the ac OPF model.
5. The method for quickly controlling reliability of an ac power grid based on state similarity according to claim 1, wherein the optimality check is:judging whether or not there isAnd->Such that:
wherein G is j (X) represents a jth constraint in the flow balance constraints; h k (X) represents the kth constraint in the inequality constraints of the touch limit.
6. A method for rapid control of ac grid reliability based on state similarity according to claim 1, characterized in that it comprises:
when the verification fails, calculating by adopting other state similar features in the state similarity library until the obtained solution passes the verification, or the state similarity library has no feature to be selected;
if all solutions obtained based on the existing features in the state similarity library cannot pass the verification, the state of the power system is proved to have a new state similarity feature, the optimal load reduction amount of the state of the power system is required to be solved through a nonlinear optimization algorithm, and the state similarity feature information of the state of the power system is added into a state similarity database.
7. An ac power grid reliability rapid control device based on state similarity, the device comprising: a processor and a memory, the memory having stored therein program instructions that invoke the program instructions stored in the memory to cause an apparatus to perform the method steps of any of claims 1-6.
CN202310082013.7A 2023-02-06 2023-02-06 Alternating current power grid reliability rapid control method and device based on state similarity Pending CN116565872A (en)

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