CN102231521A - Power grid operation state identification method in distribution network self-healing control - Google Patents
Power grid operation state identification method in distribution network self-healing control Download PDFInfo
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Abstract
The invention discloses a power grid operation state identification method in distribution network self-healing control, comprising the steps of dividing operation states of a power grid according to power grid information and carrying out priority ordering, building an operation state assessing model at the same time, assessing the state of the present power grid operation state, obtaining a state identification result and outputting the result. In the invention, multidimensional power grid information is used, state features are utilized to identify the state of different operation states by using different identification models, the problem of defining the state boundary standard in the power grid operation state identification is solved, and the power grid operation state identification is favorably and efficiently realized. By combining with the history information and only aiming at a possible state, the assessing model is assessed, therefore, system resources are saved, fast state identification is easily realized, the assessing result is processed via regulations including the state grades, and the reliability and the safety of later self-healing control measures are enhanced.
Description
Technical field:
The present invention relates to power system operation control technology field, be specifically related to the operation of power networks state identification method in a kind of power distribution network self-healing control.
Background technology:
The development of intelligent power distribution net has proposed requirement to realizing power distribution network self-healing control.On the one hand, realize that power distribution network self-healing control is the necessary condition that improves the safe and reliable level of power distribution network, the bitter lesson of domestic and international great power grid accident shows, builds the self-cure type power distribution network and helps the fast quick-recovery of distribution network failure and effectively reduce causality loss; On the other hand, the bulky complex of the construction of intelligent power distribution net and power distribution network provides desirability for power distribution network self-healing control: ACT (equipment, channel, agreement) provides guarantee for real-time Data Transmission; Various information systems realize sharing in many ways of data by unified data standard and information platform (by interface mode or integration mode); Electrical network parameter is extremely complete, upgrades in time and unification, provides distribution network to optimize all data of operating analysis.
Carry out self-healing control, can effectively improve the power distribution network power supply reliability, realize optimizing operation.The self-healing control system can take control measure to remove a hidden danger after scenting a hidden danger, and avoids fault to take place; In case break down, carry out fault location rapidly, and isolated fault automatically, recover to perfect block supply; Possess certain natural calamity early warning and reply disposal ability; Under normal operating condition, possesses multiple-objection optimization calibration capability etc.Obviously, the top priority that self-healing control realizes is accurate identification power distribution network running status, determines that current power distribution network is whether normal or optimize operation, is to face risk, still breaks down, and takes corresponding measure in view of the above again, realizes self-healing control.
Deficiencies such as current power distribution network running status identification technique, existence are classified simply, Consideration is unilateral, the state estimation model is single, practicality is lower, and identification speed is slow.
Summary of the invention:
At the deficiencies in the prior art, the object of the present invention is to provide the operation of power networks state identification method in a kind of power distribution network self-healing control, utilize assessment models to assess, saved system resource, be easy to realize the fast state identification, and by rule processing assessment results such as state classifications, the reliability and security of self-healing control measure after having strengthened.
Operation of power networks state identification method in a kind of power distribution network self-healing control provided by the invention, its improvements are:
(1) gathers power distribution network operation information and monitoring;
(2) divide the row major level ordering of going forward side by side of operation of power networks state according to the information of described step (1);
(3) the operation of power networks state of dividing according to described step (2) is set up operation of power networks state estimation model;
(4) the previous moment operation of power networks information that provides according to described step (1) is divided into corresponding described operation of power networks state estimation model to the current state identification and with described current state identification result;
(5) carry out state estimation;
(6) according to the state estimation result of described step (5),, obtain the highest state identification result of priority in conjunction with the prioritization of described step (2);
(7) output state identification result.
The operation of power networks state identification method of first preferred version provided by the invention, its improvements are, described operation of power networks state is divided into normal condition, optimization state, returns to form, risk status and the state of emergency, and the height order of sign priority of status, the wherein said state of emergency is highest.
The operation of power networks state identification method of second preferred version provided by the invention, its improvements are that described step (3) operation of power networks state estimation model is m (Φ, f, g, h, t), Φ wherein, f, g, h, t are respectively the direct indicator set Φ (φ of state estimation
1, φ
2... φ
8), derive quantitative function set f (Φ, t), derive qualitative function/index set g (Φ, t), state estimation auxiliary function/index set h (Φ, t) and time t; φ wherein
1-φ
8Be set at following information respectively:
Overhead line structures, lead nominal cross and various device the put into operation time limit, failure logging, maintenance record and device parameter information;
Voltage, electric current, active power, reactive power, leakage current, frequency, merit angle, phase angle, waveform, harmonic wave, wire tension/stress, device temperature and facility parameter information;
Dispatching of power netwoks instruction, video, equipment state, equipment actions/operations, power system operating mode, power supply is exerted oneself and maintenance scheduling information;
Meteorological condition, hydrogeology and filthy information in the history of running environment, monitoring in real time and the information of forecasting;
Electrical network knowledge and expertise information;
The command information of higher level and dispatcher's issue;
The character of each power supply, insert that electric pressure, on-position, operational mode, maximum and minimum are exerted oneself and currently go out force information;
With
Other carries out history and real time data information, history and the real-time decision information of the system such as power distribution automation, the automation of transformation substations of state estimation necessity, the second protection information of adjusting.
The operation of power networks state identification method of the 3rd preferred version provided by the invention, its improvements are that the method that the described result that described current information is handled of described step (4) is divided into corresponding described operation of power networks state estimation model comprises:
1) electrical network previous moment state identification the unknown as a result, risk of selection state estimation model, state of emergency assessment models, the assessment models that returns to form and optimization state estimation model carry out the current state identification, if all be not, then are normal condition;
2) the electrical network previous moment is a normal condition, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If variation has taken place the current time operational mode, then be the optimization state;
3) the electrical network previous moment is a risk status, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form;
4) the electrical network previous moment is the state of emergency, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form;
5) the electrical network previous moment is for returning to form, and risk of selection state estimation model, state of emergency assessment models and the assessment models that returns to form are carried out the current state identification, if all be not, then is normal condition;
6) the electrical network previous state is the optimization state, selects to optimize the state estimation model and carries out the current state identification, if not, then be normal condition.
The operation of power networks state identification method of the 4th preferred version provided by the invention, its improvements are that the method that described step (5) is assessed comprises:
1. normal condition is made as m
1(Φ
1, f
1, g
1, h
1, t
1), work as m
1Meet the definition of described normal condition, then the operation of power networks state is normal condition M
1=1, otherwise electrical network is in abnormal condition M
1=0;
2. risk status is made as m
2(Φ
2, f
2, g
2, h
2, t
2), work as m
2Meet the definition of described risk status, then the operation of power networks state is risk status M
2=1, otherwise electrical network is in non-risk status M
2=0;
3. the state of emergency is made as m
3(Φ
3, f
3, g
3, h
3, t
3), work as m
3Meet the definition of the described state of emergency, then the operation of power networks state is state of emergency M
3=1, otherwise electrical network is in non-emergent state M
3=0;
4. will return to form and be made as m
4(Φ
4, f
4, g
4, h
4, t
4), work as m
4Meet the described definition that returns to form, then the operation of power networks state is the M that returns to form
4=1, otherwise electrical network is in the non-M of returning to form
4=0;
5. the optimization state is made as m
5(Φ
5, f
5, g
5, h
5, t
5), work as m
5Meet the definition of described optimization state, then the operation of power networks state is optimization state M
5=1, otherwise electrical network is in unoptimizable state M
5=0.
The operation of power networks state identification method of the 5th preferred version provided by the invention, its improvements are that the method that described step (6) obtains the highest state identification result of priority comprises:
When I) assessing out 1 operation of power networks state, described state is current operation of power networks state;
When II) assessing out 2 and above operation of power networks state, the state that priority is the highest is as current operation of power networks state.
The operation of power networks state identification method of more preferably scheme provided by the invention, its improvements are, described normal condition, be meant that electrical network moves by predefined operational mode, all users except that scheduled outage are kept continued power, every, various operating index are all at preset range, according to this state operation, can not cause or come power grid risk with low probability band;
Described risk status, be meant under the operational mode of setting in advance, under the later service conditions of current operation of power networks conditioned disjunction current point in time, a certain or the multinomial operating index of electrical network has exceeded maybe will exceed preset range, have big possibility to cause the operation of power networks target component to worsen, take place certain or multiple power grid accident; Though or risk do not appear in electrical network, foregone conclusion spare, service conditions occur, the operation of power networks state of the control measure that need employ prevention;
The described state of emergency is meant that electrical network one place or many places have taken place or is continuing to take place certain or multiple power grid accident, does not take to protect control measure as yet; Though or taked protection, control measure, accident still continue, operation of power networks still at the state that worsens, caused or just caused user's power failure, electric power facility damage, quality of power supply severe overweight, electrical network unstability; Though or electrical network do not break down, and foregone conclusion spare, service conditions occur, need take the operation of power networks state of urgent protection, control measure;
Described returning to form, be meant with state of living in behind the power grid accident with for avoiding operation of power networks state after certain accident takes some electric grid operatings to change to be called to restPose that electrical network is returned to the process of normal condition residing state and is called and returns to form from restPosing;
Described optimization state is meant that electrical network is according to the equal running status in allowed band of the operation of the determined operational mode of optimization aim, every operating index.
Compared with the prior art, beneficial effect of the present invention is:
On the basis of taking all factors into consideration the power distribution network various information, form a plurality of direct or indirect indexs, set up corresponding state estimation model respectively at each state.In the state recognition,, adopt rules such as all kinds of state estimation models and state classification, state mutual exclusion, carry out the operation of power networks state estimation according to real-time grid information.
This method adopts the multidimensional electric network information, utilize each state characteristic to adopt different identification models to carry out state identification to different running statuses, solve state boundary standard problem identificatioin in the operation of power networks state identification, helped the efficient realization of operation of power networks state identification.
This method only at possible state, utilizes assessment models to assess in conjunction with historical information, saved system resource, be easy to realize the fast state identification, and handle assessment result, the reliability and security of self-healing control measure after having strengthened by rules such as state classifications.
The present invention carries out secondary evaluation to the running status of electrical network, has strengthened the accuracy of system.
Description of drawings
Operation of power networks state identification method flow diagram during the power distribution network self-healing that Fig. 1 proposes for the present invention is controlled.
Embodiment
Below in conjunction with accompanying drawing the specific embodiment of the present invention is described in further detail.
Present embodiment is to operation of power networks state identification method step as shown in Figure 1, and is specific as follows:
(1) gathers power distribution network operation information and monitoring;
(2) divide the row major level ordering of going forward side by side of operation of power networks state according to the information of step (1);
With the operation of power networks state be divided into normal condition, optimization state, return to form, risk status, the state of emergency, and characterize the height order of priority of status, the wherein said state of emergency be the superlative degree.
Normal condition, be meant that electrical network moves by predefined operational mode, all users except that scheduled outage are kept continued power, every, various operating index are all at preset range, according to the operation of this state, can not cause or come power grid risk with low probability band;
Risk status, be meant under the operational mode of setting in advance, under the later service conditions of current operation of power networks conditioned disjunction current point in time, a certain or the multinomial operating index of electrical network has exceeded maybe will exceed preset range, have big possibility to cause the operation of power networks target component to worsen, take place certain or multiple power grid accident; Though or risk do not appear in electrical network, foregone conclusion spare, service conditions occur, the operation of power networks state of the control measure that need employ prevention;
The state of emergency is meant that electrical network one place or many places have taken place or is continuing to take place certain or multiple power grid accident, does not take to protect control measure as yet; Though or taked protection, control measure, accident still continue, operation of power networks still at the state that worsens, caused or just caused user's power failure, electric power facility damage, quality of power supply severe overweight, electrical network unstability; Though or electrical network do not break down, and foregone conclusion spare, service conditions occur, need take the operation of power networks state of urgent protection, control measure;
Return to form, be meant with state of living in behind the power grid accident with for avoiding operation of power networks state after certain accident takes some electric grid operatings to change to be called to restPose that electrical network is returned to the process of normal condition residing state and is called and returns to form from restPosing;
The optimization state is meant that electrical network is according to the equal running status in allowed band of the operation of the determined operational mode of optimization aim, every operating index.
(3), set up operation of power networks state estimation model according to described step (2);
The state estimation model comprises the incidence relation in one or more direct indicators, one or more derivation quantitative function, the qualitative function/index of one or more derivation, one or more state auxiliary characteristics etc. and these indexs/function application, the state estimation model is m (Φ, f, g, h, t), Φ, f, g, h, t are respectively the direct indicator set Φ (φ of state estimation
1, φ
2... φ
8), derive quantitative function set f (Φ, t), derive qualitative function/index set g (Φ, t), state estimation auxiliary function/index set h (Φ, t) and time t.
The normal condition assessment models is designated as m
1(Φ
1, f
1, g
1, h
1, t), the risk status assessment models is designated as m
2(Φ
2, f
2, g
2, h
2, t), state of emergency assessment models is designated as m
3(Φ
3, f
3, g
3, h
3, t), the assessment models that returns to form is designated as m
4(Φ
4, f
4, g
4, h
4, t), optimize the state estimation model and be designated as m
5(Φ
5, f
5, g
5, h
5, t).Wherein:
A) overhead line structures, lead nominal cross and various device the are put into operation time limit, failure logging, maintenance record and device parameter information is made as φ
1
B) voltage, electric current, active power, reactive power, leakage current, frequency, merit angle, phase angle, waveform, harmonic wave, wire tension/stress, device temperature and facility parameter information are made as φ
2
C) with dispatching of power netwoks instruction, video, equipment state, equipment actions/operations, power system operating mode, power supply is exerted oneself and maintenance scheduling information is made as φ
3
D) meteorological condition, hydrogeology and filthy information in the history of running environment, monitoring in real time and the information of forecasting are made as φ
4
E) electrical network knowledge and expertise information are made as φ
5
F) command information with higher level and dispatcher's issue is made as φ
6
G) with the character of each power supply (comprising wind-powered electricity generation, photoelectricity, water power, thermoelectricity, combustion gas, rubbish, thermoelectric joint operation), insert that electric pressure, on-position, operational mode, maximum and minimum are exerted oneself and currently go out force information and be made as φ
7
H) other is carried out the power distribution automation of state estimation necessity, history and real time data information, history and the real-time decision information of electric substation automation system, the second protection information of adjusting is made as φ
8
(4) the previous moment operation of power networks information that provides according to described step (1) is divided into corresponding described operation of power networks state estimation model to the current state identification and with described current state identification result;
According to state mutual exclusion rule and state genetic sequence rule, carry out the selection of current state assessment models.
Alleged state mutual exclusion rule is meant the uniqueness of electric network state promptly can not have two kinds and above state simultaneously.5 kinds of states according to claim 1, normal condition and optimization state can exist simultaneously, inapplicable mutual exclusion rule.Risk status, the state of emergency, return to form and normal condition/optimization state between be suitable for mutual exclusion rule.According to the state mutual exclusion rule, if the possible running status of current electrical network has the N kind, comprise state 1, state 2 ..., N state-1, N state, by the state estimation model judge electrical network be not in state 1, state 2 ..., N state-1, then need not the N state assessment models and carry out state estimation, can determine that current operation of power networks state is a N state.
Alleged state genetic sequence rule, the state of being meant has certain precedence, and some states only occur in after certain state, and certain or some states perhaps only takes place after state.According to state genetic sequence rule, under known electrical network previous moment state identification result's situation,, only need carry out the assessment of some state, and not need to move all state estimation models for current electrical network.
The unknown as a result of electrical network previous moment state identification, risk of selection state estimation model, state of emergency assessment models, the assessment models that returns to form and optimization state estimation model carry out the current state identification, if all be not, then are normal condition; If wherein one or more are arranged for being, then according to state genetic sequence rule, select priority high be current state.
The electrical network previous moment is a normal condition, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If variation has taken place the current time operational mode, then be the optimization state; If wherein one or more are arranged for being, then according to state genetic sequence rule, select priority high be current state.
The electrical network previous moment is a risk status, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form; If wherein one or more are arranged for being, then according to state genetic sequence rule, select priority high be current state.
The electrical network previous moment is the state of emergency, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form; If wherein one or more are arranged for being, then according to state genetic sequence rule, select priority high be current state.
The electrical network previous moment is for returning to form, and risk of selection state estimation model, state of emergency assessment models and the assessment models that returns to form are carried out the current state identification, if all be not, then is normal condition; If wherein one or more are arranged for being, then according to state genetic sequence rule, select priority high be current state.
The electrical network previous state is the optimization state, selects to optimize the state estimation model and carries out the current state identification, if not, then be normal condition.
(5) according to described step (4), utilize a plurality of state estimation models, can carry out state estimation simultaneously:
1. normal condition is made as m
1(Φ
1, f
1, g
1, h
1, t
1), work as m
1Meet the definition of described normal condition, then the operation of power networks state is normal condition M
1=1, otherwise electrical network is in abnormal condition M
1=0;
2. risk status is made as m
2(Φ
2, f
2, g
2, h
2, t
2), work as m
2Meet the definition of described risk status, then the operation of power networks state is risk status M
2=1, otherwise electrical network is in non-risk status M
2=0;
3. the state of emergency is made as m
3(Φ
3, f
3, g
3, h
3, t
3), work as m
3Meet the definition of the described state of emergency, then the operation of power networks state is state of emergency M
3=1, otherwise electrical network is in non-emergent state M
3=0;
4. will return to form and be made as m
4(Φ
4, f
4, g
4, h
4, t
4), work as m
4Meet the described definition that returns to form, then the operation of power networks state is the M that returns to form
4=1, otherwise electrical network is in the non-M of returning to form
4=0;
5. the optimization state is made as m
5(Φ
5, f
5, g
5, h
5, t
5), work as m
5Meet the definition of described optimization state, then the operation of power networks state is optimization state M
5=1, otherwise electrical network is in unoptimizable state M
5=0.
Wherein, the evaluation time of each state at interval can be inconsistent.
The state of emergency:, need carry out the assessment of the state of emergency in real time at electrical network.
Risk status:, can carry out the assessment of risk status with relatively long time interval circulation (not necessarily real-time) at electrical network.
Return to form: at electrical network, the assessment that can return to form aperiodically.Only when the condition that may return to form occurs, be in a state of emergency or during risk status the assessment that returns to form as electrical network.
Optimization state:, can be optimized the assessment of state aperiodically at electrical network.Only when the condition that may optimize state occurs, when being in normal condition or optimizing state, be optimized the assessment of state as electrical network.
Normal condition:, can not carry out the assessment of normal condition, and, determine normal condition according to the described state mutual exclusion rule of step (3) at electrical network.
(6) according to the state estimation result of described step (5),, obtain the unique state identification result in conjunction with the prioritization of described step (2);
When I) assessing out 1 operation of power networks state, described state is current operation of power networks state;
When II) assessing out 2 and above operation of power networks state, the state that rank is high is as current operation of power networks state.
For example:
According to state of emergency assessment models, assess out electrical network and be in a state of emergency, be i.e. M
3=1, because the state of emergency is superior to other states, no matter whether other state flag bits are 1, judge that then current operation of power networks state is the state of emergency so.
According to state of emergency assessment models, assess out electrical network and be in non-emergent state, i.e. M
3=0, according to the risk status assessment models, assess out electrical network and be in risk status, be i.e. M
2=1, because risk status rank in all non-emergent states is the highest, no matter whether other state flag bits are 1, judge that then current operation of power networks state is a risk status so.
According to state of emergency assessment models and risk status assessment models, assess out electrical network and be in non-emergent non-risk status, i.e. M
3=0 and M
2=0, according to the assessment models that returns to form, assess out electrical network and be in and return to form, be i.e. M
4=1, because the rank that returns to form in all non-emergent non-risk status is the highest, no matter whether other state flag bits are 1, judge that then current operation of power networks state is for returning to form so.
According to state of emergency assessment models, risk status assessment models and the assessment models that returns to form, assess out electrical network and be in non-the returning to form of non-emergent non-risk, i.e. M
3=0, M
2=0 and M
4=0, according to optimizing the state estimation model, assess out electrical network and be in optimization state, i.e. M
5=1, be higher than normal condition owing to optimize Status Level so, no matter whether the normal condition flag bit is 1, judges that then current operation of power networks state is the optimization state.
If M
3=0, M
2=0, M
4=0 and M
5=0, judge that then current operation of power networks state is a normal condition.
(7) output state identification result.
Should be noted that at last: only illustrate that in conjunction with the foregoing description technical scheme of the present invention is not intended to limit.Those of ordinary skill in the field are to be understood that: those skilled in the art can make amendment or are equal to replacement the specific embodiment of the present invention, but these modifications or change are all among the claim protection range that application is awaited the reply.
Claims (7)
1. the operation of power networks state identification method during a power distribution network self-healing is controlled is characterized in that:
(1) gathers power distribution network operation information and monitoring;
(2) divide the row major level ordering of going forward side by side of operation of power networks state according to the information of described step (1);
(3) the operation of power networks state of dividing according to described step (2) is set up operation of power networks state estimation model;
(4) the previous moment operation of power networks information that provides according to described step (1) is divided into corresponding described operation of power networks state estimation model to the current state identification and with described current state identification result;
(5) carry out state estimation;
(6) according to the state estimation result of described step (5),, obtain the highest state identification result of priority in conjunction with the prioritization of described step (2);
(7) output state identification result.
2. operation of power networks state identification method as claimed in claim 1, it is characterized in that, described operation of power networks state is divided into normal condition, optimization state, returns to form, risk status and the state of emergency, and characterizes the height order of priority of status, and the wherein said state of emergency be the superlative degree.
3. operation of power networks state identification method as claimed in claim 1 is characterized in that, described step (3) operation of power networks state estimation model be m (Φ, f, g, h, t), Φ wherein, f, g, h, t are respectively the direct indicator set Φ (φ of state estimation
1, φ
2... φ
8), derive quantitative function set f (Φ, t), derive qualitative function/index set g (Φ, t), state estimation auxiliary function/index set h (Φ, t) and time t; φ wherein
1-φ
8Be set at following information respectively:
Overhead line structures, lead nominal cross and various device the put into operation time limit, failure logging, maintenance record and device parameter information;
Voltage, electric current, active power, reactive power, leakage current, frequency, merit angle, phase angle, waveform, harmonic wave, wire tension/stress, device temperature and facility parameter information;
Dispatching of power netwoks instruction, video, equipment state, equipment actions/operations, power system operating mode, power supply is exerted oneself and maintenance scheduling information;
Meteorological condition, hydrogeology and filthy information in the history of running environment, monitoring in real time and the information of forecasting;
Electrical network knowledge and expertise information;
The command information of higher level and dispatcher's issue;
The character of each power supply, insert that electric pressure, on-position, operational mode, maximum and minimum are exerted oneself and currently go out force information; With
Other carries out history and real time data information, history and the real-time decision information of the system such as power distribution automation, the automation of transformation substations of state estimation necessity, the second protection information of adjusting.
4. operation of power networks state identification method as claimed in claim 1 is characterized in that, the method that the described result that described current information is handled of described step (4) is divided into corresponding described operation of power networks state estimation model comprises:
1) electrical network previous moment state identification the unknown as a result, risk of selection state estimation model, state of emergency assessment models, the assessment models that returns to form and optimization state estimation model carry out the current state identification, if all be not, then are normal condition;
2) the electrical network previous moment is a normal condition, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If variation has taken place the current time operational mode, then be the optimization state;
3) the electrical network previous moment is a risk status, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form;
4) the electrical network previous moment is the state of emergency, and risk of selection state estimation model and state of emergency assessment models are carried out the current state identification, if all be not, then is normal condition; If prepare to take the service restoration measure, for returning to form;
5) the electrical network previous moment is for returning to form, and risk of selection state estimation model, state of emergency assessment models and the assessment models that returns to form are carried out the current state identification, if all be not, then is normal condition;
6) the electrical network previous state is the optimization state, selects to optimize the state estimation model and carries out the current state identification, if not, then be normal condition.
5. operation of power networks state identification method as claimed in claim 1 is characterized in that, the method that described step (5) is assessed comprises:
1. normal condition is made as m
1(Φ
1, f
1, g
1, h
1, t
1), work as m
1Meet the definition of described normal condition, then the operation of power networks state is normal condition M
1=1, otherwise electrical network is in abnormal condition M
1=0;
2. risk status is made as m
2(Φ
2, f
2, g
2, h
2, t
2), work as m
2Meet the definition of described risk status, then the operation of power networks state is risk status M
2=1, otherwise electrical network is in non-risk status M
2=0;
3. the state of emergency is made as m
3(Φ
3, f
3, g
3, h
3, t
3), work as m
3Meet the definition of the described state of emergency, then the operation of power networks state is state of emergency M
3=1, otherwise electrical network is in non-emergent state M
3=0;
4. will return to form and be made as m
4(Φ
4, f
4, g
4, h
4, t
4), work as m
4Meet the described definition that returns to form, then the operation of power networks state is the M that returns to form
4=1, otherwise electrical network is in the non-M of returning to form
4=0;
5. the optimization state is made as m
5(Φ
5, f
5, g
5, h
5, t
5), work as m
5Meet the definition of described optimization state, then the operation of power networks state is optimization state M
5=1, otherwise electrical network is in unoptimizable state M
5=0.
6. operation of power networks state identification method as claimed in claim 1 is characterized in that, the method that described step (6) obtains the highest state identification result of priority comprises:
When I) assessing out 1 operation of power networks state, described state is current operation of power networks state;
When II) assessing out 2 and above operation of power networks state, the state that priority is the highest is as current operation of power networks state.
7. operation of power networks state identification method as claimed in claim 2, it is characterized in that, described normal condition, be meant that electrical network moves by predefined operational mode, all users except that scheduled outage are kept continued power, every, various operating index are all at preset range, according to this state operation, can not cause or come power grid risk with low probability band;
Described risk status, be meant under the operational mode of setting in advance, under the later service conditions of current operation of power networks conditioned disjunction current point in time, a certain or the multinomial operating index of electrical network has exceeded maybe will exceed preset range, have big possibility to cause the operation of power networks target component to worsen, take place certain or multiple power grid accident; Though or risk do not appear in electrical network, foregone conclusion spare, service conditions occur, the operation of power networks state of the control measure that need employ prevention;
The described state of emergency is meant that electrical network one place or many places have taken place or is continuing to take place certain or multiple power grid accident, does not take to protect control measure as yet; Though or taked protection, control measure, accident still continue, operation of power networks still at the state that worsens, caused or just caused user's power failure, electric power facility damage, quality of power supply severe overweight, electrical network unstability; Though or electrical network do not break down, and foregone conclusion spare, service conditions occur, need take the operation of power networks state of urgent protection, control measure;
Described returning to form, be meant with state of living in behind the power grid accident with for avoiding operation of power networks state after certain accident takes some electric grid operatings to change to be called to restPose that electrical network is returned to the process of normal condition residing state and is called and returns to form from restPosing;
Described optimization state is meant that electrical network is according to the equal running status in allowed band of the operation of the determined operational mode of optimization aim, every operating index.
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