CN102054234B - Method for checking reserve capacity of power system based on random optimal power flow - Google Patents

Method for checking reserve capacity of power system based on random optimal power flow Download PDF

Info

Publication number
CN102054234B
CN102054234B CN2011100003735A CN201110000373A CN102054234B CN 102054234 B CN102054234 B CN 102054234B CN 2011100003735 A CN2011100003735 A CN 2011100003735A CN 201110000373 A CN201110000373 A CN 201110000373A CN 102054234 B CN102054234 B CN 102054234B
Authority
CN
China
Prior art keywords
random
fault
constraint
optimal load
margin capacity
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CN2011100003735A
Other languages
Chinese (zh)
Other versions
CN102054234A (en
Inventor
雍太有
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
WUXI AISUOSI ELECTRONIC TECHNOLOGY Co Ltd
Original Assignee
WUXI AISUOSI ELECTRONIC TECHNOLOGY Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by WUXI AISUOSI ELECTRONIC TECHNOLOGY Co Ltd filed Critical WUXI AISUOSI ELECTRONIC TECHNOLOGY Co Ltd
Priority to CN2011100003735A priority Critical patent/CN102054234B/en
Publication of CN102054234A publication Critical patent/CN102054234A/en
Application granted granted Critical
Publication of CN102054234B publication Critical patent/CN102054234B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention relates to a method for checking reserve capacity of a power system based on random optimal flow. In the invention, non-linear power flow constraint is linearized and a continuous random variable is discretized to form a two-stage random optimization problem facilitating solution. Fault analysis is performed on the system, and a fault type imposing relatively large influence on system operation is selected so as to lessen the random variable space of the system and reduce the problem solving difficulty. The method provided by the invention can help a system operation manner reasonably plan the generated output and system reserve of the system under the condition of large amount of new energy generation. The system reserve in the operation plan and the system reserve out of the plan are distinguished, and a proper parameter is designed to ensure that the system reserve in the plan is scheduled preferentially. In the method, the feasibility of post-fault power transmission is considered when calculating the post-fault re-scheduling. The re-scheduling conditions of all combinations are analyzed, a reliability index of the system is provided for the system operation and planners, the information of additional system reserve is obtained, and the reliability of system operation is improved.

Description

Based on the electric system margin capacity check method of optimal load flow at random
Technical field
The present invention relates to a kind ofly, belong to electric system economic security operation planning field based on the electric system margin capacity check method of optimal load flow at random.
Background technology
Along with the development and the energy conservation and environment protection of intelligent grid, the service requirement safety of electric system, economy, reliable.And a large amount of generations of electricity by new energy (wind-powered electricity generation, solar electrical energy generation) are incorporated into the power networks, the development of electric automobile, and the energy-conservation participation of loading, the development of electricity market, the uncertain factor of Operation of Electric Systems is in continuous increase.The operational plan that relies on traditional analytical method and decision-making means to be obtained can't be satisfied reliability of system operation and economy requirement probably.And the present method that lacks probabilistic sacurity dispatching of tackling Operation of Electric Systems both at home and abroad.The further investigation Operation of Electric Systems is uncertain, and the systematic analytic method that generation of electricity by new energy and intelligent grid development are satisfied in exploitation is absolutely necessary.
The optimal load flow technology is widely used in confirming of electric energy operation plan and operation reserve capacity.The optimal load flow that has a security constraint can be simulated and the electric energy and the back scheduling plan of definite taking into account system powering-off state, but does not consider the randomness of fault usually, does not also consider the scheduling of subsequent use capacity after the fault.The optimal load flow method is that traditional electric energy operation plan and margin capacity plan are confirmed replenishing of method at random; Consider a kind of method of finding the solution electric energy scheduling and system reserve plan of proposing after the electric system uncertainty just, considered equipment stoppage in transit, load prediction deviation, intermittent generate electricity or the like.Its target be make total electric energy operation plan and alternative plan expense and uncertainty event takes place after the expectation value of the expense of dispatching minimum.
Optimal load flow is considered the uncertain and system load flow constraint of electric system at random.Corresponding to practical power systems at random optimal load flow be a large-scale nonlinear random optimization problem.Usually utilizing linearization and discretize to come problem simplified finds the solution.Research shows that the characteristic that makes full use of Operation of Electric Systems can be pointedly be used to solve some problems of Operation of Electric Systems with optimal load flow at random.
Summary of the invention
The present invention proposes and use the abundant property that optimal load flow nucleus correcting system is at random checked has the margin capacity under a large amount of generation of electricity by new energy situation, provide a kind of based on the electric system margin capacity check method of optimal load flow at random.Its purpose is to combine the practice of conventional formulation system's generation schedule and alternative plan; Further utilize optimal load flow method at random, whether resolution system has the uncertain problem that enough margin capacities are dealt with system's operations such as system's generation of electricity by new energy is intermittent, the flowability of electric automobile load, the energy-conservation response randomness of load.
According to technical scheme provided by the invention; Whether Operation of Electric Systems and planning personnel can examine calculated margin capacity can satisfy the system reliability requirement, and mobile loads such as the generation of electricity by new energy of research program or electric automobile are to the influence of system's operational reliability.Specific as follows:
1), forms network associate matrix, impedance matrix, and further generate non-linear power flow equation according to power system network information;
2) according to the objective function of given system's operating point, normal network topology, formulation, carry out conventional optimal load flow and calculate, be met the optimal load flow of system's operation constraint; Said conventional optimal load flow is meant the tide optimization method of considering to confirm to satisfy under the systematic parameter electric power system tide constraint;
3) at optimal load flow Xie Chu non-linear power flow equation is carried out linearization, generate the linearization power flow equation;
4) obtain the system failure situation of user's appointment or carry out the N-1 fault scanning automatically, according to fault the influence index of system is selected index and surmount fault type to threshold value; Said N-1 fault is meant at one time to have only one to break down in N the equipment.
5) obtain the uncertain parameters that system moves; The predicted value and the issue parameter that comprise predicted value that line fault and probability of happening thereof, generator failure and probability of happening thereof, generation of electricity by new energy are exerted oneself and distribution parameter, power load, and according to the satisfaction of selecting in advance to the random variable of continuous type discretize;
6) the discrete and random variable is made up; Set up the stochastic variable space: establishing independent random variables has: L line fault, G genset fault, D load value; W generation of electricity by new energy exerted oneself; According to N-1 rule hypothesis, L+G+1 network topology combination and D * W input combination are arranged so, complete stochastic variable space just comprises (L+G+1) * D * W kind combination;
7) obtain the predetermined margin capacity plan of system, and preferential right power priority scheduling when allowing the system failure is given in plan to margin capacity;
8) form the two-stage optimal load flow model at random with linear restriction, to be that generator is meritorious exert oneself and margin capacity a stage decision variable, and the variable of two-stage comprises busbar voltage and merit angle, and generator reactive is exerted oneself, and generator is proofreaied and correct and controlled; The constraint of one stage comprises the scope of generator output and margin capacity; The constraint of two-stage comprises bus trend balance equation, and branch road or transmission profile constraints are proofreaied and correct the control constraint, busbar voltage range constraint, generator reactive constraint;
9) parameter of the linear restriction of each combination in the corresponding stochastic variable of the generation space comprises linearization trend constraint condition, the unit operation restrictive condition;
10) utilize random optimization software DECIS to linear second-order at random optimal power flow problems find the solution;
11) separating of all combinations detected, the statistics scheduling exceeds the probability and the expectation value of margin capacity, the reliability index of output system under given unit output and alternative plan and the combination of subsequent use deficiency.
Wherein, step 3 is that non-linear power flow equation is carried out the power flow equation linearization at the Xie Chu of a conventional optimal load flow, converts non-linear constrain to linear restriction.
Step 5 said according to the satisfaction of selecting in advance to the random variable of continuous type discretize, utilize discrete random variable approximate continuity type stochastic variable.
Step 6 utilizes combined method to handle the stochastic variable in the Operation of Electric Systems simultaneously: network failure, generator failure, load variations and the generation of electricity by new energy variation of exerting oneself.
Step 7 said to margin capacity plan give preferential right power and be meant and give the priority scheduling rank the generated output that comes by margin capacity conversion, make margin capacity after fault, preferentially be used for participating in scheduling.
The identification of the calculating of the said reliability index of step 11 and the combination of subsequent use deficiency is meant according to the constraint among the optimal load flow result at random crosses the border computing system reliability of operation index.
Advantage of the present invention is: this method is carried out preferential service rating to schedulable generating capacity outside the plan in the system and is distributed; Make and calculatedly when the system failure subsequent usely can preferentially participate in dispatching again; Then the abundant property of nucleus correcting system margin capacity is calculated in stochastic variable combinations all in the system.The present invention is according to the uncertainty of Operation of Electric Systems; Comprise generation of electricity by new energy and the flowability of intermittence and novel electric vehicle load; The economy and the reliability of taking into account system operation simultaneously; Plan or systems organization to operation carry out verification, and help system operations staff rationally dispatches when generating electricity in the face of a large amount of new forms of energy Home Networks and plans, improves reliability of system operation and economic benefit.
Description of drawings
Fig. 1 is the process flow diagram of this method.
Fig. 2 is a continuous distribution load discretize synoptic diagram.
Embodiment
Describe the present invention below in conjunction with accompanying drawing.The present invention adopts following technical scheme to realize particularly, and as shown in Figure 1, concrete steps are following:
1) reads check method and study the ground system data, the margin capacity plan of generator output plan and system's operation.
2) distribute based on given system's generation schedule, normal operational network topological sum system loading, form conventional optimal power flow problems commonly used in the present Power System Analysis.
Conventional optimal power flow problems is become with the constraint system of equations by objective function.The objective function of conventional optimal load flow and equation of constraint should be consistent with equation of constraint with the objective function of optimal load flow at random.For example the objective function of optimal load flow is the generating total expenses at random, and the objective function of so conventional optimal load flow also should be the generating total expenses.Equation of constraint comprises power flow equation, circuit or transmission section transmission constraint, generator operation constraint etc.Its median generatrix trend balance equation is described suc as formula (1), and the circuit trend is described suc as formula (2).
f ( V , δ ) - W g P g Q g + W d P d Q d = 0 - - - ( 1 )
g(V，δ)≤g max (2)
The variable V is here represented busbar voltage, and δ representes busbar voltage merit angle, f (V, δ) meritorious and idle input, the W of all branch roads on the expression bus gThe annexation of expression bus and generator, W dThe annexation of expression bus and load point, P gExpression the meritorious of generator exerted oneself Q gExpression the idle of generator exerted oneself P dThe meritorious requirement of expression load, Q dThe idle requirement of expression load, g (V, the δ) trend of expression circuit or transmission section, g MaxThe extreme value of the trend of expression circuit or transmission section.
Conventional optimal load flow like this is the optimization problem that contains non-linear constrain.The second-order optimum problem that has linearization trend constraint and other linear restrictions through continuous solving finds the system optimal trend when given generator output to separate; The meritorious imbalance that elimination causes because of system loss; And obtain the system's operating point that satisfies the normal operation of system, comprise generator output, load distribution, busbar voltage and merit angle.
But about related content in conventional optimal load flow model list of references 1 and the document 2.
3) at optimal load flow Xie Chu linearization is carried out in non-linear trend constraint, obtained the Jacobian matrix of power flow equation, data are provided for forming linear trend equation of constraint.
Suppose to be (V at busbar voltage and the merit angle of optimal load flow Xie Chu 0, δ 0), so f (V, δ) and g (V, Jacobian matrix δ) is formula (3), F in (4) and G are at (V 0, δ 0) value:
F = ( ∂ f ( V , δ ) ∂ V , ∂ f ( V , δ ) ∂ δ ) - - - ( 3 )
G = ( ∂ g ( V , δ ) ∂ V , ∂ g ( V , δ ) ∂ δ ) - - - ( 4 )
So linear trend equation of constraint just becomes formula (5) and (6).
f ( V 0 , δ 0 ) + F ΔV Δδ - W g P g Q g + W d P d Q d = 0 - - - ( 5 )
g ( V 0 , δ 0 ) + G ΔV Δδ ≤ g max - - - ( 6 )
About but related content in linearization list of references 1 and the document 2 is carried out in non-linear trend constraint.
4) obtain the given failure condition of user, or system is carried out the N-1 fault scanning, the failure condition of the influence and the user-defined index of system being selected considered according to fault.
Calculating fault can be through calculating the performance index PI of trend after the fault to the influence of system like formula (7).
PI = Σ l = 1 L β l ( P l P l max ) 2 - - - ( 7 )
Here L representes to transmit the quantity of branch road, β lThe weight of expression branch road l, P lMeritorious trend on the expression branch road l,
Figure GDA0000081352280000046
The meritorious trend limit on the expression branch road l.To each calculation of fault performance index, can sort to the influence of system like this, select to influence big fault according to user-defined standard and get into the calculating of optimal load flow at random fault.
5) obtain system's operation stochastic variable, and to continuous random variable, the for example variation of generation of electricity by new energy and load is carried out discretize according to customer requirements.
In the stochastic variable of system's operation, line fault is arranged, generator failure etc., these can be represented with 0 or 1 state.They can be represented with discrete random variable.In the stochastic variable of system's operation, also have load variations, the variation of generator output (wind-powered electricity generation, solar electrical energy generation etc.), they are continuous random variables, value is distributed on the interval.For example, suppose that it is as shown in Figure 2 that load distributes, load is distributed in L 1And L 5Between, the d that its distribution function is (L).Can be divided into 4 interval L to load so 1-L 2, L 2-L 3, L 3-L 4, L 4-L 5, each is interval with a typical value L A, L R, L C, L DRepresent that their probability is respectively
Figure GDA0000081352280000047
Like this, successional stochastic variable just is similar to discrete random variable.If require higher precision, can dwindle interval scope, increase interval quantity.
But about continuous random variable being carried out related content in discretize list of references 1 and the document 2.
6), form stochastic variable space with mutually independent random variables combination to the making up of all discrete and random variablees.
For the combination of stochastic variable, need make up according to the correlativity of stochastic variable, guarantee to form the variable space with separate element.Suppose that independent random variables has: L line fault; G genset fault, D load value, W generation of electricity by new energy exerted oneself; Suppose that load variations, unit output change and the system architecture variation is separate; According to N-1 rule hypothesis, L+G+1 network topology combination and D * W input combination are arranged so, complete stochastic variable space just comprises (L+G+1) * D * W kind combination.
7) obtain the dispatched scope of system reserve capacity plan and the non-margin capacity of the system failure, distribute the priority level of participating in proofreading and correct control, give the right of priority that calculated margin capacity can be scheduled.
The priority level of proofreading and correct control is to realize through setting different weights.For example, when objective function was generation cost, the generating price that can give the conversion of margin capacity was 0.
8) mathematical model of formation two-stage linear random optimization problem comprises unit operation constraint, the subsequent use constraint of capacity, system load flow constraint etc.
According to nonlinear equation linearization and continuous random variable discretize, optimal load flow has become a two-stage linear random optimal problem at random.Wherein mainly be in power flow equation, to introduce the control of fault post-equalization, bus trend balance equation becomes:
f ( V 0 , δ 0 ) + F ΔV Δδ - W g P g + P c Q g + Q c + W d P d - P S Q d - Q S = 0 - - - ( 8 )
Here P cThe correction control that the expression unit can be participated in after system condition changes comprises the generating capacity that the margin capacity conversion comes, Q cThe corresponding P of expression unit cThe idle variation of exerting oneself, P sThe expression system must subtract load, Q sThe corresponding reaction component that subtracts load of expression.P dThe meritorious requirement of expression load has distribution character here, Q dBe corresponding P dThe reactive load requirement, P gBeing that generator is meritorious exerts oneself, and intermittent in this way generating then is the generated output of stochastic distribution, Q gBe that generator reactive is exerted oneself, F is the Jacobian matrix of corresponding each system architecture, W gIt is the relational matrix of corresponding unit fault.
Simultaneously, unit participates in proofreading and correct the ability (P of control c) be to receive system reserve capacity plan (R g) restriction.Unit is proofreaied and correct control also can produce expense, and this expense expectation value also is the two-stage part of the objective function of optimal problem at random as producing cost.
9) a stage decision variable and constraint and the two-stage decision variable and the constraint of appointment two-stage linear random optimization problem.Corresponding each line fault forms Jacobian and revises matrix, and generates the linear restriction coefficient and the border of each combination in the corresponding stochastic variable space.
In optimal load flow at random, a stage decision variable is the meritorious P that exerts oneself of generator gWith margin capacity R g, the variable of two-stage comprises busbar voltage and merit angle Δ V, Δ δ, the generator reactive Q that exerts oneself g, generator is proofreaied and correct control P cThe constraint of one stage comprises the scope of generator output and margin capacity.The constraint of two-stage comprises bus trend balance equation, and branch road or transmission profile constraints are proofreaied and correct the control constraint, busbar voltage range constraint, generator reactive constraint etc.
10) utilize Optimization Software DECIS to the linear second-order section at random optimal power flow problems find the solution.Relevant but utilization DECIS is found the solution and stage related content in the optimal power flow problems list of references 3 at random.
11) scan separating that all make up at random in the optimal load flow at random, add up the scheduling situation of unplanned margin capacity, the reliability index of generation system under given generated output and capacity alternative plan.
Here the system reliability index of calculating has the expectation value of system Reduction of Students' Study Load lotus and the expectation value of system compensation regulate expenditure.The expectation value of system Reduction of Students' Study Load lotus is by satisfying the bus trend balance equation lotus (P that lightened the burden to all load buses s) and the probability of happening of corresponding combination calculate.The expectation value of system compensation control is that system is calculated in the expense of the correction control of each combination and the probability of happening of corresponding combination.
The susceptibility index that parameter changes is that the Lagrangian coefficient of corresponding equation of constraint is added up.When finding the solution at random optimal load flow, can produce the Lagrangian coefficient corresponding to equation of constraint simultaneously, corresponding generator changes and the influence of load variations to system's generation expense with the clear generator output of the Lagrangian coefficient table of the trend balance equation of load bus.
Scan all combinations, the combination of Reduction of Students' Study Load lotus is added up, so just can provide system and which type of fault can can't satisfy the system loading requirement, point out the situation that system reliability is weak in.
The present invention is analyzed as follows: the present invention with the continuous random variable discretize, forms the two-stage random optimization problem of finding the solution that is beneficial to non-linear trend constraint linearization.System is carried out fault analysis, select the fault type bigger, come reduction system stochastic variable space, reduce the difficulty of problem solving system's influence on system operation.Consider the intermittence of generation of electricity by new energy, under failure condition and generated output when uncertain, require enough system reserve capacities to guarantee reliability of system operation.The present invention can the help system method of operation generated output and the system reserve of planning system under a large amount of generation of electricity by new energy access situation reasonably; To the system reserve in the operational plan and unplanned in system reserve distinguish, the design proper parameters guarantee priority scheduling system reserve in the works, the availability of the margin capacity after the nucleus correcting system fault.The system transmissions obstruction that causes because of the system failure can limit some generator outputs, comprises the scheduling of margin capacity.This method is calculated the scheduling again after the fault, has considered the feasibility of transmitting electricity after the fault.Analyze the situation of scheduling again of all combinations, the reliability index of system is provided and obtains the subsequent use information of additional system, enhanced system reliability of operation to system's operation and staff planners.
To sum up, the present invention has following advantage.
1) the present invention passes through the linearization of non-linear trend constraint and the discretize of continuous random variable; Simplified the complicacy of optimal power flow problems at random; System is had under a large amount of probabilistic situation, checked the abundant property of the system reserve capacity of confirming according to usual manner.
2) the present invention checks all failure modes that need pay close attention to and the method for operation simultaneously simultaneously, and whether detection system is subsequent use all sidedly can satisfy scheduling again after the system failure.
3) the present invention considers the intermittence of generation of electricity by new energy, and the abundant property of system reserve capacity is checked.
4) the present invention considers the flowability of novel load (electric automobile), and the energy-conservation response of loading is checked the abundant property of system reserve capacity uncertainty.
4) the present invention utilizes ripe commercial Optimization Software bag that the linear random optimal problem is found the solution, and has guaranteed the rapidity of the extensibility to big system problem, robustness and the calculating of check method.
5) the present invention is system's generation schedule and the alternative plan computed reliability index that the operations staff formulates, and is provided at and reformulates generation schedule for the operational plan personnel under the situation of the method for operation of subsequent use deficiency and system reserve provides decision support.
6) the invention belongs to the core technology that the power system security economical operation is planned, also generation of electricity by new energy is incorporated into the power networks and novel load variations provides an important analytical approach to the influence that system moves in order to solve.
List of references 1. harmonies have very much PhD dissertation: " Study of Stochastic Optimal Power Flow ", University of Wisconsin-Madison, 2001.
The research report that the too promising American Electric Power of list of references 2. harmonies research institute accomplishes: " Stochastic Optimal Power Flow with Reserve Determination ", EPRI, PID1016227,2007.
The research report that the too promising American Electric Power of list of references 3. harmonies research institute accomplishes: " A Method to Determine Reserve Requirements for Large-Scale Renewable Integration:A Platform for Large-Scale Power Systems "; EPRI PID1017904,2009.

Claims (6)

1. based on the electric system margin capacity check method of optimal load flow at random, it is characterized in that may further comprise the steps:
1), forms network associate matrix, impedance matrix, and further generate non-linear power flow equation according to power system network information;
2) according to the objective function of given system's operating point, normal network topology, formulation, carry out conventional optimal load flow and calculate, be met the optimal load flow of system's operation constraint; Said conventional optimal load flow is meant the tide optimization method of considering to confirm to satisfy under the systematic parameter electric power system tide constraint;
3) at optimal load flow Xie Chu non-linear power flow equation is carried out linearization, generate the linearization power flow equation;
4) obtain the system failure situation of user's appointment or carry out the N-1 fault scanning automatically, according to fault the influence index of system is selected index and surmount fault type to threshold value; Said N-1 fault is meant at one time to have only one to break down in N the equipment;
5) obtain the uncertain parameters that system moves; The predicted value and the issue parameter that comprise predicted value that line fault and probability of happening thereof, generator failure and probability of happening thereof, generation of electricity by new energy are exerted oneself and distribution parameter, power load, and according to the satisfaction of selecting in advance to the random variable of continuous type discretize;
6) the discrete and random variable is made up; Set up the stochastic variable space: establishing independent random variables has: L line fault, G genset fault, D load value; W generation of electricity by new energy exerted oneself; According to N-1 rule hypothesis, L+G+1 network topology combination and D * W input combination are arranged so, complete stochastic variable space just comprises (L+G+1) * D * W kind combination;
7) obtain the predetermined margin capacity plan of system, and preferential right power priority scheduling when allowing the system failure is given in plan to margin capacity;
8) form the two-stage optimal load flow model at random with linear restriction, to be that generator is meritorious exert oneself and margin capacity a stage decision variable, and the variable of two-stage comprises busbar voltage and merit angle, and generator reactive is exerted oneself, and generator is proofreaied and correct and controlled; The constraint of one stage comprises the scope of generator output and margin capacity; The constraint of two-stage comprises bus trend balance equation, and branch road or transmission profile constraints are proofreaied and correct the control constraint, busbar voltage range constraint, generator reactive constraint;
9) parameter of the linear restriction of each combination in the corresponding stochastic variable of the generation space comprises linearization trend constraint condition, the unit operation restrictive condition;
10) utilize random optimization software DECIS to linear second-order at random optimal power flow problems find the solution;
11) separating of all combinations detected, the statistics scheduling exceeds the probability and the expectation value of margin capacity, the combination and the reliability index of the subsequent use deficiency of output system under given unit output and alternative plan.
2. said based on the electric system margin capacity check method of optimal load flow at random according to claim 1; It is characterized in that step 3 is that non-linear power flow equation is carried out the power flow equation linearization at the Xie Chu of a conventional optimal load flow, converts non-linear constrain to linear restriction.
3. said based on the electric system margin capacity check method of optimal load flow at random according to claim 1; It is characterized in that step 5 said according to the satisfaction of selecting in advance to the random variable of continuous type discretize, utilize discrete random variable approximate continuity type stochastic variable.
4. said based on the electric system margin capacity check method of optimal load flow at random according to claim 1; It is characterized in that step 6 utilizes combined method to handle the stochastic variable in the Operation of Electric Systems simultaneously: network failure; The variation of exerting oneself of generator failure, load variations and generation of electricity by new energy.
5. said based on the electric system margin capacity check method of optimal load flow at random according to claim 1; It is characterized in that step 7 said to margin capacity plan give preferential right power and be meant and give the priority scheduling rank the generated output that comes by margin capacity conversion, make margin capacity after fault, preferentially be used for participating in scheduling.
6. said based on the electric system margin capacity check method of optimal load flow at random according to claim 1, the identification of combination that it is characterized in that calculating and the subsequent use deficiency of the said reliability index of step 11 is meant according to the constraint among the optimal load flow result at random crosses the border computing system reliability of operation index.
CN2011100003735A 2011-01-04 2011-01-04 Method for checking reserve capacity of power system based on random optimal power flow Expired - Fee Related CN102054234B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2011100003735A CN102054234B (en) 2011-01-04 2011-01-04 Method for checking reserve capacity of power system based on random optimal power flow

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2011100003735A CN102054234B (en) 2011-01-04 2011-01-04 Method for checking reserve capacity of power system based on random optimal power flow

Publications (2)

Publication Number Publication Date
CN102054234A CN102054234A (en) 2011-05-11
CN102054234B true CN102054234B (en) 2012-07-04

Family

ID=43958526

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2011100003735A Expired - Fee Related CN102054234B (en) 2011-01-04 2011-01-04 Method for checking reserve capacity of power system based on random optimal power flow

Country Status (1)

Country Link
CN (1) CN102054234B (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104008434A (en) * 2014-06-06 2014-08-27 上海交通大学 Flexible constraint optimization method of electric power system
CN106408438B (en) * 2015-07-31 2019-10-15 中国电力科学研究院 Security and stability control strategy automatic Check method based on full dynamic simulation
CN106571624A (en) * 2015-10-12 2017-04-19 南京南瑞继保电气有限公司 Optimal power flow method considering power grid N-1 constraints
CN105281327B (en) * 2015-10-21 2019-02-12 国网内蒙古东部电力有限公司呼伦贝尔供电公司 Consider the large-scale distribution network optimal load flow calculation method of discrete and continuous decision variable
CN113065218B (en) * 2021-05-13 2024-02-13 南京工程学院 Electric power system reliability evaluation method, device and system considering LR attack

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101272052A (en) * 2008-05-16 2008-09-24 清华大学 Event coordination control method of advanced energy management system
CN101465547B (en) * 2009-01-12 2011-04-27 浙江大学 Optimum tide solvability identification method for electric power system

Also Published As

Publication number Publication date
CN102054234A (en) 2011-05-11

Similar Documents

Publication Publication Date Title
Van der Meer et al. Energy management system with PV power forecast to optimally charge EVs at the workplace
Liang et al. Analysis of factors affecting economic operation of electric vehicle charging station based on DEMATEL-ISM
Ghasemi-Marzbali Fast-charging station for electric vehicles, challenges and issues: A comprehensive review
Haupt et al. The influence of electric vehicle charging strategies on the sizing of electrical energy storage systems in charging hub microgrids
Conlon et al. Assessing new transmission and energy storage in achieving increasing renewable generation targets in a regional grid
Wiget et al. Probabilistic security constrained optimal power flow for a mixed HVAC and HVDC grid with stochastic infeed
Tan et al. The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory
He et al. Enhancing the power grid flexibility with battery energy storage transportation and transmission switching
Ding et al. Optimal dispatching strategy for user-side integrated energy system considering multiservice of energy storage
CN102054234B (en) Method for checking reserve capacity of power system based on random optimal power flow
Edmunds et al. Design of a DSO‐TSO balancing market coordination scheme for decentralised energy
CN112821397B (en) Source-load-storage coordinated low-carbon economic dispatching method and device
Yuan et al. Optimal scheduling for micro‐grid considering EV charging–swapping–storage integrated station
CN106447073A (en) Power purchase transaction method based on uncertainty factors and provincial load prediction
CN105427051A (en) Comprehensive evaluation method of power grid based on asset life cycle
Raouf Mohamed et al. Distributed battery energy storage systems operation framework for grid power levelling in the distribution networks
Wang et al. Optimizing probabilistic spinning reserve by an umbrella contingencies constrained unit commitment
Mirzaei et al. Network‐constrained rail transportation and power system scheduling with mobile battery energy storage under a multi‐objective two‐stage stochastic programming
Wang et al. A hybrid agent-based model predictive control scheme for smart community energy system with uncertain DGs and loads
Mohamed et al. Two‐phase BESS optimization methodology to enhance the distribution network power quality and mitigate violations
Cowan et al. Integrated technology roadmap development process: Creating smart grid roadmaps to meet regional technology planning needs in Oregon and the Pacific Northwest
Ye et al. Market-based hosting capacity maximization of renewable generation in power grids with energy storage integration
Antoniadou-Plytaria Optimal Energy Scheduling of Grid-Connected Microgrids with Battery Energy Storage
Neumann Computational and Near-Optimal Trade-Offs in Renewable Electricity System Modelling
Yamashita et al. Hierarchical Control Structure for Optimising Building Microgrid Self-consumption

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20120704

Termination date: 20180104