CN104268693A - Power grid dispatching determining method and system - Google Patents

Abstract

The invention discloses a power grid dispatching determining method and system and relates to a power grid dispatching simulation method and system. Currently, power grid faults are frequently influenced by outside environments, and under extreme weather conditions, people can only wait for happening or developing of faults or accidents passively and cannot conduct prognosis and prevention on dispatching risks initiatively. A power grid structure and topological information are obtained from a power grid SCADA/EMS system, spare power automatic switching information is automatically generated, a repair schedule is combined, and the state information of a spare power automatic switching device is adjusted; combination with weather information can be achieved, the change of equipment outage probability is calculated, the load shedding amount is calculated specific to a threshold-crossing device and a power outage device, and early warning is given specific to large risk changes. According to the technical scheme, a dispatcher can find various risks in the operation process of a power grid in time.

Description

A kind of method and system of decision of power system dispatching

Technical field

The invention belongs to dispatching of power netwoks simulation calculation field, particularly a kind of method and system of decision of power system dispatching.

Background technology

Electric network fault usually affects by outside environmental elements, extreme weather usually causes increasing of electric network fault, how to carry out the decision of power system dispatching under extreme weather conditions, carry out relevant prediction scheme in advance, reduce loss of outage is the target that power supply enterprise at different levels lays siege to always.

Current dispatching of power netwoks person can only rely on dispatch automated system acquisition power grid measurement and topology information to judge operation of power networks state, it is discrete for catching due to automated system the information come, it is the measurement information based on collection point, yardman cannot obtain the external action information such as more relevant weather, can not Efficient Evaluation weather on the impact of electric network fault, under extreme weather conditions, the generation or the development that wait pending fault or accident that can only be passive, various information cannot be relied on, initiatively anticipation and prevention is in advance carried out to schedule risk, objectively need a kind of method and system meeting decision of power system dispatching.

Summary of the invention

The present invention mainly solves yardman initiatively cannot carry out anticipation in advance under extreme weather conditions technical matters to power grid risk, and for this reason, the present invention takes following technical scheme.

A method for decision of power system dispatching, is characterized in that comprising the following steps:

1) electric network composition and topology information is obtained from electrical network SCADA/EMS system;

2) according to electric network composition data, automatically prepared auto restart information is generated;

3) bonding apparatus turnaround plan, adjustment prepared auto restart status information;

4) regularly obtain dissimilar weather information, probability calculation is carried out to element, provides element stoppage in transit probable value;

5) carry out simulation to element to cut-off, calculate consequence, provide out-of-limit equipment and power failure equipments;

6) according to sensitivity, cutting load amount is converted to for out-of-limit equipment;

7) carry out power failure Risk Calculation and reliability index calculating, calculating comprises: load summate probability, expected loss of load, expected loss of energy, voltage limit risk and element overload risk;

8) compare risk indicator change, when larger change occurs risk class, provide early warning.

A system for decision of power system dispatching, is characterized in that comprising with lower unit:

Real-time data interface unit: obtain power grid measurement and structural information from electrical network SCADA/EMS;

Prepared auto restart generation unit: according to power network topology, generates prepared auto restart information;

Prepared auto restart confirmation unit: bonding apparatus turnaround plan, adjustment prepared auto restart state;

Weather information acquiring unit: read weather information; Probability calculation is carried out to element, provides element probable value; Weather information, as Typhoon Information, lightning information etc.;

Electrical network analysis unit: carry out simulation to element and cut-off, calculates consequence, provides out-of-limit equipment and power failure equipments;

Consequences analysis unit: according to sensitivity, cutting load amount is converted to out-of-limit equipment;

Indicator calculating unit: carry out power failure Risk Calculation and reliability index calculating, calculating comprises: load summate probability, expected loss of load, expected loss of energy, voltage limit risk and element overload risk;

Prewarning unit: compare risk indicator change, when larger change occurs risk class, provides early warning.

Beneficial effect: the technical program is according to electric network model and topology information in electrical network SCADA/EMS, in conjunction with service information, weather information, the power grid risk change that real-time analysis causes because of weather reason, timely early warning is carried out to larger risk, yardman is had and a kind ofly can find and identify the effective technology means that power grid risk changes.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention.

Fig. 2 is system construction drawing of the present invention

In Fig. 1 .S1 reads electric network composition and topology, and S2. generates prepared auto restart information, and S3. adjusts prepared auto restart status information, S4. computing element stoppage in transit probability, S5. calculates out-of-limit or outaged equipment, S6. computing element stoppage in transit cutting load amount, S7. calculate risk indicator, S8. carries out early warning to risk.

1. Real-time data interface unit, 2. prepared auto restart generation unit, 3. prepared auto restart confirmation unit, 4. weather information acquiring unit, 5. electrical network analysis unit, 6. consequences analysis unit, 7. indicator calculating unit, 8. prewarning unit in Fig. 2.

Embodiment

Below in conjunction with Figure of description, technical scheme of the present invention is described in further detail.

As shown in Figure 1, comprise the following steps:

S1, reading electric network composition and topological structure; First need from SCADA/EMS platform, obtain electrical network model and measurement, electric network composition herein comprises transformer station, station equipment (bus, mother/mother stock, main transformer), outer circuit of standing, generator.

Described electric network composition comprises the annexation of equipment room, and annexation is herein logic connecting relation, and topology is actual electrically communication relationship.

Described acquisition electric network model adopts CIM/XML mode, and power grid measurement adopts CIM/E file mode.

S2, generation prepared auto restart information, the whether accurate computational accuracy directly having influence on load loss amount of prepared auto restart information, needs to generate prepared auto restart facility information according to SCADA/EMS electric network composition information.

S3, adjustment prepared auto restart status information; The virtual condition of prepared auto restart equipment by the impact deviation to some extent of maintenance run, must may adjust prepared auto restart status information according to the method for operation of reality.

Element is stopped transport and is comprised forced outage, common-mode failure stoppage in transit, environment facies according to stoppage in transit, ageing failure stoppage in transit, the various stoppage in transit key element of half forced outage, needs to calculate total basis stoppage in transit probability.

Can comprise for power distribution network element: generator, circuit, transformer, isolating switch, capacity reactance device, disconnector and bus.In actual treatment, the probability of malfunction of line-breaker and disconnector counts circuit, and main transformer isolating switch and disconnector count main transformer, and bus connection switch will be set up alone.Load model is also included within system element model in addition.

Constant equipment failure rate cannot describe service condition and the impact of ambient weather change on equipment outage rate, mainly considers the factors such as thunderbolt, strong wind, external force, bird pest when actual probabilities calculates.Namely

Can adopt when calculating lightning strike probability: λ _thuderi=λ _aREAI* L _aREAI* M

M is weather element, and thunderstorm weather is 1, otherwise is 0, λ _aREAIfor the circuit lightning fault rate of thunder and lightning statistical regions, unit is secondary/(100km*1 Thunderstorm Day), L _aREAIfor being in the line length in this region, unit km.

Can calculate according to the following formula when the large wind-induced line outage rate of actual computation:

${\mathrm{\&lambda;}}_{\mathrm{wind}}=\left\{\begin{array}{c}0,\mathrm{\&omega;}\left(t\right)<{\mathrm{\&omega;}}_{\mathrm{cri}}\\ {\mathrm{\&lambda;}}_{\mathrm{base}}\&times;C_p\&times;(\frac{\mathrm{\&omega;}{\left(t\right)}^2}{{{\mathrm{\&omega;}}^2}_{\mathrm{cri}}}-1),\mathrm{\&omega;}\left(t\right)\&GreaterEqual;{\mathrm{\&omega;}}_{\mathrm{cri}}\end{array}\right.$

λ _windi＝λ _wind*L

L is the length of circuit in this climatic region, λ _basefor the crash rate in normal weather situation, wind speed, ω _crifor critical wind velocity; C _pfor scale parameter.ω _criobtained by statistical value, gale warning wind speed.Owing to lacking the statistics of message, ω _crifor 21m/s, scale parameter C _pget 3586.

Can following formula be adopted when actual computation external force:

λ _forcei＝λ _force*Lforce

L _forcefor circuit is in the length in outside destroy region, if circuit is not 0 in external force destroyed area value.λ _forcefor the line fault that external force causes.

Can following formula be adopted when actual computation bird pest:

λ _birdi＝λ _bird*L _bird

L _birdfor circuit is in the length in bird pest area, if circuit is not 0 in bird pest region value.λ _birdfor the line failure rate that bird pest causes, unit is secondary/(100km* day), and its value changes according to Monthly changes, can be calculated by following formula.

Can following formula be adopted when the reason of actual computation equipment own causes:

λ _devicei＝λ _device*Y _device*L _device

L _devicefor the length of circuit, λ _devicefor the line failure rate that equipment causes, unit is secondary/(100km* day), can be calculated by following formula.

Overall equipment component stoppage in transit probability is:

λi＝λ _thunderi+λ _windi+λ _devicei+λ _birdi+λ _forcei+λ _base

In formula, λ _basefor the basic outage rate of other transmission and distribution lines.

S4, computing element stoppage in transit probability; After probability calculation completes, need to calculate because element is stopped transport the out-of-limit or outaged equipment caused.

S5, calculate out-of-limit or stop equipment; Forecast failure collection technology is mainly adopted when calculating out-of-limit or outaged equipment, carry out fault set except N-1 fault, also need the situation considering multiple failure, the situation of multiple failure can be considered by Monte Carlo method, but the speed of Monte Carlo method cannot reach practical degree, therefore, also need to use analytical method to calculate, so we must obtain the fault set that can cover all dangerous points before calculating, and make our risk evaluation result be useful.

Multiple failure collection generates the main factor considering two aspects automatically, and one is carry out topological analysis to electrical network, and carries out subregion to electrical network, and one is the domain of influence considering fault.

S6, computing element stoppage in transit cutting load amount, calculate carrying out the main scan method of element stoppage in transit cutting load amount, for the fault of forecast failure collection, finds the 10kV load bus of dead electricity.For the 10kV bus of each dead electricity, find the user that it powers in distribution network model, judge that this user whether can dead electricity or degradation, cut-off each feeder line section, find affected user, judge that this user whether can dead electricity, provide risk class.

S7, risk indicator to be calculated, risk indicator shows effect of risk from each dimension, the electric network reliability index that main employing is relevant to load herein: LOLP (load summate probability), EDNS (expected loss of load), EENS (expected loss of energy), ROVV (voltage limit risk), ROLV (element overload risk), carries out abundant intensity and safety evaluation to the mains supply ability under various mode.

1) load summate probability LOLP, explanation be that the possibility that reduction plans occurs during assessing has much

$\mathrm{LOLP}=\underset{i=1}{\overset{\mathrm{NL}}{\mathrm{\&Sigma;}}}\left(\underset{s\&Element;\mathrm{Fi}}{\mathrm{\&Sigma;}}{p}_{\left(s\right)}\right)\frac{T_i}{T}---(4-1)$

Dual power supply user has a power failure LOLP (superfine, one-level, secondary often plant user power failure LOLP);

Dual power supply user demotes LOLP (superfine, one-level, secondary often plant user one degradation LOLP);

Single supply user has a power failure LOLP (user power failure LOLP often plants in interim responsible consumer, domestic consumer);

Comprehensive LOLP (dual power supply user degradation also can cause and have a power failure in short-term).

2) expected loss of load EDNS, explanation be during assessing cut down average load be much.

$\mathrm{EDNS}=\underset{i=1}{\overset{\mathrm{NL}}{\mathrm{\&Sigma;}}}\left(\underset{s\&Element;\mathrm{Fi}}{\mathrm{\&Sigma;}}P\left(s\right)C\left(s\right)\right)\frac{T_i}{T}---(4-2)$

Classification EDNS (dual power supply has a power failure or degradation, single supply);

Comprehensive EDNS (dual power supply user degradation also can cause and have a power failure in short-term).

3) expected loss of energy (expect lack delivery) EENS (unit is megawatt hour), explanation be assessment during due to the electricity of cutting load loss be much.

$\mathrm{EENS}=\underset{i=1}{\overset{\mathrm{NL}}{\mathrm{\&Sigma;}}}(\underset{s\&Element;F_i}{\mathrm{\&Sigma;}}P\left(s\right)\&CenterDot;C\left(s\right))\&CenterDot;T_i---(4-3)$

Classification EDNS (dual power supply has a power failure or degradation, single supply);

Comprehensive EDNS (dual power supply user degradation also can cause and have a power failure in short-term).

4) element overload risk ROLV, explanation be assessment during the risk of generating device or system overload have much.

${\mathrm{ROCV}}_{\mathrm{Ni}}=\underset{i=1}{\overset{\mathrm{NL}}{\mathrm{\&Sigma;}}}(\underset{s\&Element;L_i}{\mathrm{\&Sigma;}}P\left(s\right)\&CenterDot;{\left(\frac{\mathrm{\&Delta;I}\left(j\right)}{I\left(j\right)}\right)}^2)\frac{T_i}{T}---(4-4)$

${\mathrm{ROCV}}_s=\underset{i=1}{\overset{\mathrm{NL}}{\mathrm{\&Sigma;}}}(\underset{s\&Element;L_i}{\mathrm{\&Sigma;}}P\left(s\right)\&CenterDot;\left(\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left(\frac{\mathrm{\&Delta;I}\left(j\right)}{I\left(j\right)}\right)}^2\right))\frac{T_i}{T}---(4-5)$

5) the average power off time AIHC of user:

User during adding up in average power failure hourage;

Average power off time=the Σ of user (each power off time of each household)/total number of users

=Σ (each interruption duration × each customer interrupted number)/total number of users.

6) the average frequency of power cut AITC of user:

In scope of statistics low-voltage customer during adding up in average frequency of power cut;

Average frequency of power cut=the Σ of user (each customer interrupted number)/total number of users.

Described risk class mainly adopts the Pyatyi standard of defined in State Council 599 command, and star is higher, and risk is larger.

S8, early warning is carried out to risk; When risk class changes, need to carry out early warning.

Correspond, the system of decision of power system dispatching, as shown in Figure 2, at least comprise:

Real-time data interface unit 1: obtain power grid measurement and structural information from electrical network SCADA/EMS;

Prepared auto restart generation unit 2: according to power network topology, generates prepared auto restart information;

Prepared auto restart confirmation unit 3: bonding apparatus turnaround plan, adjustment prepared auto restart state;

Weather information acquiring unit 4: read weather information, as Typhoon Information, lightning information; Probability calculation is carried out to element, provides element probable value;

Electrical network analysis unit 5: carry out simulation to element and cut-off, calculates consequence, provides out-of-limit equipment and power failure equipments;

Consequences analysis unit 6: according to sensitivity, cutting load amount is converted to out-of-limit equipment;

Indicator calculating unit 7: carry out power failure Risk Calculation and reliability index calculating, calculating comprises: load summate probability, expected loss of load, expected loss of energy, voltage limit risk and element overload risk;

Prewarning unit 8: compare risk indicator change, when larger change occurs risk class, provides early warning.

Claims (2)

1. a method for decision of power system dispatching, is characterized in that comprising the following steps:

1) electric network composition and topology information is obtained from electrical network SCADA/EMS system;

2) according to electric network composition data, automatically prepared auto restart information is generated;

3) bonding apparatus turnaround plan, adjustment prepared auto restart status information;

4) regularly obtain dissimilar weather information, probability calculation is carried out to element, provides element stoppage in transit probable value;

5) carry out simulation to element to cut-off, calculate consequence, provide out-of-limit equipment and power failure equipments;

6) according to sensitivity, cutting load amount is converted to for out-of-limit equipment;

7) carry out power failure Risk Calculation and reliability index calculating, calculating comprises: load summate probability, expected loss of load, expected loss of energy, voltage limit risk and element overload risk;

8) compare risk indicator change, when larger change occurs risk class, provide early warning.

2. a system for decision of power system dispatching, is characterized in that comprising with lower unit:

Real-time data interface unit: obtain power grid measurement and structural information from electrical network SCADA/EMS;

Prepared auto restart generation unit: according to power network topology, generates prepared auto restart information;

Prepared auto restart confirmation unit: bonding apparatus turnaround plan, adjustment prepared auto restart state;

Weather information acquiring unit: read weather information, as Typhoon Information, lightning information; Probability calculation is carried out to element, provides element probable value;

Electrical network analysis unit: carry out simulation to element and cut-off, calculates consequence, provides out-of-limit equipment and power failure equipments;

Consequences analysis unit: according to sensitivity, cutting load amount is converted to out-of-limit equipment;

Indicator calculating unit: carry out power failure Risk Calculation and reliability index calculating, calculating comprises: load summate probability, expected loss of load, expected loss of energy, voltage limit risk and element overload risk;

Prewarning unit: compare risk indicator change, when larger change occurs risk class, provides early warning.