CN102738835A - Wind-fire-water co-scheduling method on basis of multi-agent system - Google Patents
Wind-fire-water co-scheduling method on basis of multi-agent system Download PDFInfo
- Publication number
- CN102738835A CN102738835A CN2012102470553A CN201210247055A CN102738835A CN 102738835 A CN102738835 A CN 102738835A CN 2012102470553 A CN2012102470553 A CN 2012102470553A CN 201210247055 A CN201210247055 A CN 201210247055A CN 102738835 A CN102738835 A CN 102738835A
- Authority
- CN
- China
- Prior art keywords
- power system
- electric power
- agent
- wind
- unit
- 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.)
- Granted
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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Landscapes
- Wind Motors (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention relates to a power scheduling operation method, in particular to a wind-fire-water co-scheduling method on the basis of a multi-agent system. The method solves the problem that a conventional power scheduling operation method cannot meet the requirement on the large-scale wind power grid-connected operation. The wind-fire-water co-scheduling method on the basis of the multi-agent system is implemented by adopting the following steps of: 1, constructing a wind-fire-water co-scheduling model on the basis of the multi-agent in a scheduling Agent; 2, acquiring predicted data of a load demand in a power system by a load Agent in the power system; 3, sending acquired basic data and real-time data into the wind-fire-water co-scheduling model on the basis of the multi-agent by each thermal power Agent; and 4, issuing and executing a scheduling command by each thermal power Agent and a hydroelectric Agent. The wind-fire-water co-scheduling method is suitable for large-scale wind power grid-connected operation scheduling.
Description
Technical field
The present invention relates to the power scheduling operation method, specifically is a kind of " wind-fire-water " coordinated dispatching method based on multiple agent.
Background technology
Wind energy is a kind of contain abundant and clean regenerative resource.Along with the more and more maturation of wind generating technology, wind power generation also more and more receives the attention of the Chinese government.By 2011, China's wind-powered electricity generation accumulative total installed capacity broke through 6544.15 ten thousand kilowatts, surpasses the U.S. first, leaps to the first in the world.
The power supply architecture of China is main with thermoelectricity and water power mainly.The restriction of conditions such as fired power generating unit receives that boiler, steam turbine minimum technology are exerted oneself, the adjusting range of fired power generating unit is less, and equipment such as boiler, steam turbine receives the restriction of alternate stress, and it is slower to regulate the speed.Thermoelectric exerting oneself in the heat supply phase of unit is obstructed, and the peak of system becomes littler, and the difficulty of peak regulation becomes bigger.Pollutant that gives off during thermal power unit operation such as nitrogen oxide, oxysulfide also can cause environmental pollution.Hydropower Unit has adjusting range big, regulate the speed fast, operating cost advantage low, low in the pollution of the environment.
Wind power generation has intermittence, fluctuation, randomicity characteristics.Along with the increase of wind-powered electricity generation installation scale, being incorporated into the power networks steadily, safely of wind-powered electricity generation becomes the key issue of being badly in need of solution, and conventional electric power management and running method can't satisfy the demand that large-scale wind power is incorporated into the power networks.Because being incorporated into the power networks, large-scale wind power needs the spinning reserve capacity in the rational management electric power system; In order to bear the peak regulation task of wind-powered electricity generation; But because the anti-peak regulation characteristic of wind-powered electricity generation unit output; Increased the difficulty of peak regulation, conventional electric power management and running method is difficult to solve the fluctuation of the active power and the frequency of electrical network, when serious even can threaten the safety of whole electric power system.
Therefore, be badly in need of a kind of new dispatching method of invention, this method can take into full account in the electric power system power producing characteristics of various power supplys and dispatch, and makes power system security, economy, environmental protection operation.
Summary of the invention
The present invention provides a kind of " wind-fire-water " coordinated dispatching method based on multiple agent in order to solve the problem that conventional electric power management and running method can't satisfy the demand that large-scale wind power is incorporated into the power networks.
The present invention adopts following technical scheme to realize: based on " wind-fire-water " coordinated dispatching method of multiple agent, this method is to adopt following steps to realize: 1) in scheduling Agent, make up " wind-fire-water " the cooperative scheduling model based on multiple agent; 2) by the prediction data of workload demand in the collection of the load Agent in the electric power system electric power system, the prediction data with the workload demand that collects is sent to the scheduling Agent in the electric power system simultaneously; After scheduling Agent received the prediction data of workload demand, each thermoelectricity Agent in electric power system, water power Agent, wind-powered electricity generation Agent sent the request of image data; After each thermoelectricity Agent receives the request of image data, gather the master data and the real time data of each fired power generating unit in the electric power system; After each water power Agent receives the request of image data, gather the master data and the real time data of each Hydropower Unit in the electric power system; After each wind-powered electricity generation Agent receives the request of image data, gather the real time data and the prediction data of each wind-powered electricity generation unit in the electric power system; 3) by each thermoelectricity Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each water power Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each wind-powered electricity generation Agent real time data that collects and prediction data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; " wind-fire-water " cooperative scheduling model based on multiple agent decomposes the data that receive, and utilizes the MOPSO algorithm to solve exerting oneself of the exerting oneself of each fired power generating unit in the electric power system, each Hydropower Unit respectively; 4) will find the solution the exerting oneself of each fired power generating unit that obtains by scheduling Agent and be sent to each thermoelectricity Agent in the electric power system; To find the solution the exerting oneself of each Hydropower Unit that obtains by scheduling Agent and be sent to the water power Agent in the electric power system; Each thermoelectricity Agent, water power Agent issue and the operation dispatching order according to exerting oneself of receiving.
Said step 1) may further comprise the steps: the frame model that 1.1) makes up " wind-fire-water " cooperative scheduling model; Said frame model comprises several thermoelectricitys Agent, several water power Agent, several wind-powered electricity generations Agent, thermoelectricity Management Agent, water power Management Agent, wind-powered electricity generation Management Agent, scheduling Agent and load Agent; Wherein, each thermoelectricity Agent connects scheduling Agent through the thermoelectricity Management Agent; Each water power Agent connects scheduling Agent through the water power Management Agent; Each wind-powered electricity generation Agent connects scheduling Agent through the wind-powered electricity generation Management Agent; Load Agent connects scheduling Agent; 1.2) structure " wind-fire-water " cooperative scheduling Model Optimization target function; The optimization aim of said optimization aim function comprises: the power-balance problem of electric power system; The economy problems of power system operation; The emission pollution problem of each fired power generating unit in the electric power system; 1.3) confirm the spinning reserve of each fired power generating unit in the electric power system; 1.4) make up the constraints of " wind-fire-water " cooperative scheduling model; Said constraints comprises: the constraint of the positive and negative spinning reserve of electric power system; The constraint of exerting oneself of each fired power generating unit, the constraint of regulations speed in the electric power system; The constraint of the constraint of the constraint of exerting oneself of each Hydropower Unit, regulations speed, storage capacity, the constraint of letdown flow in the electric power system; The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit in the electric power system.
Said step 2) in, the master data of each fired power generating unit comprises: the minimax of each fired power generating unit exert oneself, the make progress emissions data of downward regulations speed, operating cost data, pollutant; The real time data of each fired power generating unit comprises: each fired power generating unit go out force data in real time; The master data of each Hydropower Unit comprises: the minimax of each Hydropower Unit exert oneself, make progress downward regulations speed, minimax storage capacity, minimax letdown flow, operating cost data; The real time data of each Hydropower Unit comprises: each Hydropower Unit go out force data in real time; The real time data of each wind-powered electricity generation unit comprises: the data of the quality of power supply of each wind energy turbine set; The prediction data of each wind-powered electricity generation unit comprises: the prediction data of each wind energy turbine set; The prediction data of workload demand comprises: to the prediction data of load active power demand.
In the said step 3), the MOPSO algorithm may further comprise the steps: 3.1) initialization population, and the scale M of definite population and total iterations N; 3.2) calculate the pairing object vector of each particle in the population, and upgrade the optimal solution pbest of each particle; During to iterations iterations≤n, the noninferior solution in the population is joined in the outside document, and safeguard outside document; To iterations iterations>during n, judge that whether fitness1 is less than ε; If greater than ε, think then that this is separated and be not noninferior solution; If less than ε, judge then whether fitness2 and fitness3 that this is separated arrange separating in the outside document; If domination is then directly separated this outside document of adding and is deleted ridden separating in the document; If this is separated by outside document domination, then this is separated and is not added outside document; If this separate with document in separate mutually and do not arrange, then this is separated the outside document of direct adding; 3.3) safeguard outside document, and from outside document, choose one and separate as globally optimal solution gbest; 3.4) upgrade each particle's velocity and position; 3.5) judge that whether iterations iterations is less than N; If iterations iterations is less than N, iterations iterations+1 then, and jump into step 3.2) circulation; If iterations iterations is greater than N, then loop ends; 3.6) from outside document, choose globally optimal solution gbest, and return globally optimal solution gbest.
Said step 1.2) in, the power-balance problem of electric power system obtains through following formula:
In the formula (1),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
is the active power of workload demand in the electric power system;
is the station service power consumption rate of transmission losses in the electric power system and each power plant;
The economy problems of power system operation obtains through following formula:
In the formula (2),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
The emission pollution problem of each fired power generating unit obtains through following formula in the electric power system:
（3）；
In the formula (3),
is the summation that discharges pollutants of each fired power generating unit in the electric power system.
Through type (2) and formula (3) can make the multiple electricity of unit that operating cost is lower in the electric power system, pollutant emission is less, and the unit that operating cost is higher, pollutant emission is more generates electricity less; Guarantee the requirement of the economy and the feature of environmental protection of power system operation thus.
Said step 1.3) in, definite principle of the spinning reserve of each fired power generating unit is following in the electric power system:
If fired power generating unit is coal group of motors and the annual peak regulation of participating in, to single-machine capacity 300MW and above newly-built unit, will rotate up subsequent use confirming as about 20%, will be rotated down and subsequent usely confirm as 25%; Production time unit early to single-machine capacity 200MW-600MW will rotate up subsequent use confirming as about 15%, will be rotated down subsequent use confirming as about 20%; To single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%;
If fired power generating unit is a thermoelectric unit and at heating period, to single-machine capacity 135MW and following unit, will exert oneself is obstructed confirms as 10%, will rotate up and subsequent usely confirm as 5%, will be rotated down and subsequent usely confirm as 10%; To single-machine capacity 200MW and above unit, will exert oneself is obstructed confirms as 15%-20%, will rotate up subsequent usely to confirm as 10%, will be rotated down subsequent usely to confirm as 10%; If fired power generating unit is a thermoelectric unit and at non-heating period, to single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%; To the unit of single-machine capacity 200MW-300MW, will rotate up and subsequent usely confirm as 15%, will be rotated down and subsequent usely confirm as 20%.
Said step 1.4) in, the constraint of the positive and negative spinning reserve of electric power system obtains through following formula:
In the formula (4),
for each Hydropower Unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
for each fired power generating unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
predicted value for loading in the electric power system;
is the prediction data of each wind-powered electricity generation unit in the electric power system;
value for loading in the t electric power system constantly;
is the data of each wind-powered electricity generation unit in the t electric power system constantly;
The constraint of exerting oneself of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (5),
is exerting oneself of i the Hydropower Unit t moment;
is that i Hydropower Unit t minimum is constantly exerted oneself;
is i Hydropower Unit t EIAJ constantly;
The constraint of the regulations speed of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (6),
is the downward regulations speed of each Hydropower Unit in the electric power system;
is the upwards regulations speed of each Hydropower Unit in the electric power system;
The constraint of the letdown flow of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (7),
is a Hydropower Unit t letdown flow constantly;
is a Hydropower Unit t minimum letdown flow constantly;
is a Hydropower Unit t maximum letdown flow constantly;
The constraint of the storage capacity of each Hydropower Unit obtains through following formula in the electric power system:
（8）；
In the formula (8),
is a Hydropower Unit t storage capacity constantly;
is a Hydropower Unit t minimum storage capacity constantly;
is a Hydropower Unit t maximum storage capacity constantly;
The constraint of exerting oneself of each fired power generating unit obtains through following formula in the electric power system:
In the formula (9),
is exerting oneself of i fired power generating unit;
is that the minimum of i fired power generating unit is exerted oneself;
is i unit EIAJ;
The constraint of the regulations speed of each fired power generating unit obtains through following formula in the electric power system:
In the formula (10),
is the downward regulations speed of each fired power generating unit in the electric power system;
is the upwards regulations speed of each fired power generating unit in the electric power system;
The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit comprises following condition in the electric power system:
Voltage deviation: control wind-powered electricity generation unit be incorporated into the power networks point voltage for its rated voltage-3%-7%;
Frequency departure: the normal frequency deviation allowable value of electric power system is ± 0.2Hz, when the capacity of electric power system hour, the normal frequency deviation allowable value is loosened to ± 0.5Hz;
Voltage unbalance degree limit value: when electric power system normally moved, the negative sequence voltage degree of unbalance was no more than 2%, was no more than 4% in short-term;
Tri-phase unbalance factor: the expression formula of tri-phase unbalance factor is following:
In the formula (11);
is the positive sequence component root mean square value of three-phase voltage, and its unit is volt;
is the negative sequence component root mean square value of three-phase voltage, and its unit is volt;
is the zero-sequence component root mean square value of three-phase voltage, and its position is volt;
Flickering: the flickering interference value of the points of common connection that the wind-powered electricity generation unit is inserted satisfies the national standard requirement;
Harmonic wave: the harmonic wave injection current of the points of common connection at wind-powered electricity generation unit place satisfies the national standard requirement.
Said step 3.2) in, object vector obtains through following formula:
In the formula (12),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
for the active power of workload demand in the electric power system,
is the station service power consumption rate of each power plant for the transmission losses in the electric power system;
In the formula (13),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
In the formula (14),
is the summation of the pollutant emission of each fired power generating unit in the electric power system.
Said step 3.4) in, upgrade each particle's velocity and position and obtain through following formula:
In formula (15)-(17), w is the inertia weight of particle rapidity; Iterations is an iterations; N is total iterations;
and
is the random number of [0,1]; Pbest is the locally optimal solution of particle; Gbest is the globally optimal solution of particle.
Compare with conventional electric power management and running method, " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention has the following advantages: one, taken into full account the power producing characteristics of various generating sets in the electric power system: Hydropower Unit exert oneself adjusting range big, regulate the speed fast; Fired power generating unit is because of the restriction of conditions such as receiving that boiler, steam turbine minimum technology are exerted oneself, and the adjusting range of exerting oneself of fired power generating unit is little, regulations speed is slow; Thermoelectric unit is influenced by heat supply exerting oneself of heat supply phase; Wind power generation has intermittence, fluctuation and randomness.Two, problems such as economy, minimizing pollutant emission have been taken into full account.Therefore this method not only can guarantee to utilize to greatest extent wind energy resources, and can realize the energy-saving and emission-reduction scheduling.
" wind-fire-water " coordinated dispatching method based on multiple agent of the present invention is based on brand-new scheduling principle; Realized the exerting oneself of the exerting oneself of electric power system apoplexy group of motors, fired power generating unit, exerting oneself of Hydropower Unit are carried out Collaborative Control; Effectively reduced the large-scale wind power impact of back of being incorporated into the power networks thus to electric power system; Avoid fluctuation and the variation of frequency of the active power of electric power system, guaranteed the safety of electric power system." wind-fire-water " coordinated dispatching method based on multiple agent of the present invention is from the angle of power scheduling; Not only guaranteed the power-balance of electric power system; But also considered the economy of power system operation and the pollutant emission problem of thermal power plant, it is very significant that this problem at the current environment and the energy receives under the background that people pay close attention to day by day.
The present invention efficiently solves the problem that conventional electric power management and running method can't satisfy the demand that large-scale wind power is incorporated into the power networks, and is applicable to large-scale wind-electricity integration traffic control.
Description of drawings
Fig. 1 is the step sketch map based on multiple agent " wind-fire-water " coordinated dispatching method of the present invention.
Fig. 2 is the structural representation of the frame model of " wind-fire-water " cooperative scheduling model among the present invention.
Fig. 3 is the automated system implementation framework sketch map based on multiple agent " wind-fire-water " coordinated dispatching method of the present invention.
Fig. 4 is the system control strategy illustraton of model based on multiple agent " wind-fire-water " coordinated dispatching method of the present invention.
Fig. 5 is the schematic flow sheet based on multiple agent " wind-fire-water " coordinated dispatching method of the present invention.
Fig. 6 is the schematic flow sheet of the MOPSO algorithm among the present invention.
Fig. 7 is the schematic flow sheet of the renewal pbest of the MOPSO algorithm among the present invention.
Fig. 8 is the schematic flow sheet of the renewal gbest of the MOPSO algorithm among the present invention.
Fig. 9 is the schematic flow sheet of the outside document of maintenance of the MOPSO algorithm among the present invention.
Figure 10 is the emulation experiment curve synoptic diagram based on multiple agent " wind-fire-water " coordinated dispatching method of the present invention.
Figure 11 adopts the coal consumption curve contrast sketch map based on fired power generating unit before and after " wind-fire-water " coordinated dispatching method of multiple agent of the present invention.
Embodiment
Based on " wind-fire-water " coordinated dispatching method of multiple agent, this method is to adopt following steps to realize:
1) in scheduling Agent, makes up " wind-fire-water " cooperative scheduling model based on multiple agent;
2) by the prediction data of workload demand in the collection of the load Agent in the electric power system electric power system, the prediction data with the workload demand that collects is sent to the scheduling Agent in the electric power system simultaneously; After scheduling Agent received the prediction data of workload demand, each thermoelectricity Agent in electric power system, water power Agent, wind-powered electricity generation Agent sent the request of image data;
After each thermoelectricity Agent receives the request of image data, gather the master data and the real time data of each fired power generating unit in the electric power system; After each water power Agent receives the request of image data, gather the master data and the real time data of each Hydropower Unit in the electric power system; After each wind-powered electricity generation Agent receives the request of image data, gather the real time data and the prediction data of each wind-powered electricity generation unit in the electric power system;
3) by each thermoelectricity Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each water power Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each wind-powered electricity generation Agent real time data that collects and prediction data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent;
" wind-fire-water " cooperative scheduling model based on multiple agent decomposes the data that receive, and utilizes the MOPSO algorithm to solve exerting oneself of the exerting oneself of each fired power generating unit in the electric power system, each Hydropower Unit respectively;
4) will find the solution the exerting oneself of each fired power generating unit that obtains by scheduling Agent and be sent to each thermoelectricity Agent in the electric power system; To find the solution the exerting oneself of each Hydropower Unit that obtains by scheduling Agent and be sent to the water power Agent in the electric power system; Each thermoelectricity Agent, water power Agent issue and the operation dispatching order according to exerting oneself of receiving.
Said step 1) may further comprise the steps:
1.1) make up the frame model of " wind-fire-water " cooperative scheduling model; Said frame model comprises several thermoelectricitys Agent, several water power Agent, several wind-powered electricity generations Agent, thermoelectricity Management Agent, water power Management Agent, wind-powered electricity generation Management Agent, scheduling Agent and load Agent; Wherein, each thermoelectricity Agent connects scheduling Agent through the thermoelectricity Management Agent; Each water power Agent connects scheduling Agent through the water power Management Agent; Each wind-powered electricity generation Agent connects scheduling Agent through the wind-powered electricity generation Management Agent; Load Agent connects scheduling Agent;
1.2) structure " wind-fire-water " cooperative scheduling Model Optimization target function; The optimization aim of said optimization aim function comprises: the power-balance problem of electric power system; The economy problems of power system operation; The emission pollution problem of each fired power generating unit in the electric power system;
1.3) confirm the spinning reserve of each fired power generating unit in the electric power system;
1.4) make up the constraints of " wind-fire-water " cooperative scheduling model; Said constraints comprises: the constraint of the positive and negative spinning reserve of electric power system; The constraint of exerting oneself of each fired power generating unit, the constraint of regulations speed in the electric power system; The constraint of the constraint of the constraint of exerting oneself of each Hydropower Unit, regulations speed, storage capacity, the constraint of letdown flow in the electric power system; The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit in the electric power system.
Said step 2) in, the master data of each fired power generating unit comprises: the minimax of each fired power generating unit exert oneself, the make progress emissions data of downward regulations speed, operating cost data, pollutant; The real time data of each fired power generating unit comprises: each fired power generating unit go out force data in real time; The master data of each Hydropower Unit comprises: the minimax of each Hydropower Unit exert oneself, make progress downward regulations speed, minimax storage capacity, minimax letdown flow, operating cost data; The real time data of each Hydropower Unit comprises: each Hydropower Unit go out force data in real time; The real time data of each wind-powered electricity generation unit comprises: the data of the quality of power supply of each wind energy turbine set; The prediction data of each wind-powered electricity generation unit comprises: the prediction data of each wind energy turbine set; The prediction data of workload demand comprises: to the prediction data of load active power demand.
In the said step 3), the MOPSO algorithm may further comprise the steps:
3.1) the initialization population, and the scale M of definite population and total iterations N;
3.2) calculate the pairing object vector of each particle in the population, and upgrade the optimal solution pbest of each particle;
During to iterations iterations≤n, the noninferior solution in the population is joined in the outside document, and safeguard outside document;
To iterations iterations>during n, judge that whether fitness1 is less than ε; If greater than ε, think then that this is separated and be not noninferior solution; If less than ε, judge then whether fitness2 and fitness3 that this is separated arrange separating in the outside document; If domination is then directly separated this outside document of adding and is deleted ridden separating in the document; If this is separated by outside document domination, then this is separated and is not added outside document; If this separate with document in separate mutually and do not arrange, then this is separated the outside document of direct adding;
3.3) safeguard outside document, and from outside document, choose one and separate as globally optimal solution gbest;
3.4) upgrade each particle's velocity and position;
3.5) judge that whether iterations iterations is less than N; If iterations iterations is less than N, iterations iterations+1 then, and jump into step 3.2) circulation; If iterations iterations is greater than N, then loop ends;
3.6) from outside document, choose globally optimal solution gbest, and return globally optimal solution gbest.
Said step 1.2) in, the power-balance problem of electric power system obtains through following formula:
In the formula (1),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
is the active power of workload demand in the electric power system;
is the station service power consumption rate of transmission losses in the electric power system and each power plant;
The economy problems of power system operation obtains through following formula:
In the formula (2),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
The emission pollution problem of each fired power generating unit obtains through following formula in the electric power system:
In the formula (3),
is the summation that discharges pollutants of each fired power generating unit in the electric power system.
Through type (2) and formula (3) can make the multiple electricity of unit that operating cost is lower in the electric power system, pollutant emission is less, and the unit that operating cost is higher, pollutant emission is more generates electricity less; Guarantee the requirement of the economy and the feature of environmental protection of power system operation thus.
Said step 1.3) in, definite principle of the spinning reserve of each fired power generating unit is following in the electric power system:
If fired power generating unit is coal group of motors and the annual peak regulation of participating in, to single-machine capacity 300MW and above newly-built unit, will rotate up subsequent use confirming as about 20%, will be rotated down and subsequent usely confirm as 25%; Production time unit early to single-machine capacity 200MW-600MW will rotate up subsequent use confirming as about 15%, will be rotated down subsequent use confirming as about 20%; To single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%;
If fired power generating unit is a thermoelectric unit and at heating period, to single-machine capacity 135MW and following unit, will exert oneself is obstructed confirms as 10%, will rotate up and subsequent usely confirm as 5%, will be rotated down and subsequent usely confirm as 10%; To single-machine capacity 200MW and above unit, will exert oneself is obstructed confirms as 15%-20%, will rotate up subsequent usely to confirm as 10%, will be rotated down subsequent usely to confirm as 10%; If fired power generating unit is a thermoelectric unit and at non-heating period, to single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%; To the unit of single-machine capacity 200MW-300MW, will rotate up and subsequent usely confirm as 15%, will be rotated down and subsequent usely confirm as 20%.
Said step 1.4) in, the constraint of the positive and negative spinning reserve of electric power system obtains through following formula:
In the formula (4),
for each Hydropower Unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
for each fired power generating unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
predicted value for loading in the electric power system;
is the prediction data of each wind-powered electricity generation unit in the electric power system;
value for loading in the t electric power system constantly;
is the data of each wind-powered electricity generation unit in the t electric power system constantly;
The constraint of exerting oneself of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (5),
is exerting oneself of i the Hydropower Unit t moment;
is that i Hydropower Unit t minimum is constantly exerted oneself;
is i Hydropower Unit t EIAJ constantly;
The constraint of the regulations speed of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (6),
is the downward regulations speed of each Hydropower Unit in the electric power system;
is the upwards regulations speed of each Hydropower Unit in the electric power system;
The constraint of the letdown flow of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (7),
is a Hydropower Unit t letdown flow constantly;
is a Hydropower Unit t minimum letdown flow constantly;
is a Hydropower Unit t maximum letdown flow constantly;
The constraint of the storage capacity of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (8),
is a Hydropower Unit t storage capacity constantly;
is a Hydropower Unit t minimum storage capacity constantly;
is a Hydropower Unit t maximum storage capacity constantly;
The constraint of exerting oneself of each fired power generating unit obtains through following formula in the electric power system:
In the formula (9),
is exerting oneself of i fired power generating unit;
is that the minimum of i fired power generating unit is exerted oneself;
is i unit EIAJ;
The constraint of the regulations speed of each fired power generating unit obtains through following formula in the electric power system:
（10）；
In the formula (10),
is the downward regulations speed of each fired power generating unit in the electric power system;
is the upwards regulations speed of each fired power generating unit in the electric power system;
The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit comprises following condition in the electric power system:
Voltage deviation: control wind-powered electricity generation unit be incorporated into the power networks point voltage for its rated voltage-3%-7%;
Frequency departure: the normal frequency deviation allowable value of electric power system is ± 0.2Hz, when the capacity of electric power system hour, the normal frequency deviation allowable value is loosened to ± 0.5Hz;
Voltage unbalance degree limit value: when electric power system normally moved, the negative sequence voltage degree of unbalance was no more than 2%, was no more than 4% in short-term;
Tri-phase unbalance factor: the expression formula of tri-phase unbalance factor is following:
In the formula (11);
is the positive sequence component root mean square value of three-phase voltage, and its unit is volt;
is the negative sequence component root mean square value of three-phase voltage, and its unit is volt;
is the zero-sequence component root mean square value of three-phase voltage, and its position is volt;
Flickering: the flickering interference value of the points of common connection that the wind-powered electricity generation unit is inserted satisfies the national standard requirement;
Harmonic wave: the harmonic wave injection current of the points of common connection at wind-powered electricity generation unit place satisfies the national standard requirement.
Said step 3.2) in, object vector obtains through following formula:
In the formula (12),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
for the active power of workload demand in the electric power system,
is the station service power consumption rate of each power plant for the transmission losses in the electric power system;
In the formula (13),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
In the formula (14),
is the summation of the pollutant emission of each fired power generating unit in the electric power system.
Said step 3.4) in, upgrade each particle's velocity and position and obtain through following formula:
（16）；
（17）；
In formula (15)-(17), w is the inertia weight of particle rapidity; Iterations is an iterations; N is total iterations;
and
is the random number of [0,1]; Pbest is the locally optimal solution of particle; Gbest is the globally optimal solution of particle.
During practical implementation; Frame model for making up shown in Figure 2 based on " wind-fire-water " cooperative scheduling of multiple agent; Adopt the dispatching patcher model of this structure of Fig. 2 to have following advantage: 1) to have good distributed characteristics, meet large-scale wind power and insert distributed characteristics behind the electrical network.2) adopt this structure well to solve total activation Agent with the communication issue between each Agent of power plant.The constructed model of this method has added district management Agent between total activation Agent and the end Agent of each factory; Can reduce the communication bandwidth of total activation Agent like this, prevent that the end Agent of each factory from communicating by letter with total activation Agent and cause the communication blocking of total activation Agent.Shown in Figure 3 is the implementation framework of the automated system of " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention.Wherein the end Agent of factory (wind energy turbine set Agent, the Agent of thermal power plant and hydroelectric station Agent) is through the needed data of acquisition system collection scheduling Agent; Communication language (ACL language) through Agent sends in the dispatching patcher model; Agent calls these data and utilizes the MOPSO algorithm to find the solution by scheduling; Find the solution and finish the back and solving result is sent to the end Agent of each factory, issue and the operation dispatching order by them by scheduling Agent.Shown in Figure 4 is the model of the system control strategy of " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention.Wherein, Scheduling Agent exerts oneself according to the prediction of active power and the wind-powered electricity generation of the forecast demand of load Agent and water power, exerting oneself in real time of thermoelectricity calculate △ PW; Dispatch Agent simultaneously and let the energy output △ PG and the △ PH of thermoelectricity Agent, water power Agent adjustment self, make according to the constraints of each thermoelectricity, Hydropower Unit | △ PW+ △ PG+ △ PH| → 0; Shown in Figure 5 is the flow process of " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention.Wherein, the 1st step of flow process is to judge whether scheduling Agent receives the t+1 data (being prediction data) constantly that load Agent sends at t constantly, if the information of receiving then continue, otherwise scheduling Agent is in wait state.The 2nd step was that scheduling Agent receives after the workload demand data, sent the request of image data to the end Agent of each factory; The 3rd step was the end Agent of each factory, received the data that collection scheduling Agent needs after the request that scheduling Agent sends and sent to scheduling Agent; The 4th step was that scheduling Agent receives after prediction data and the master data, utilized the MOPSO algorithm to find the solution; The 5th step: the result that finding the solution of step 4 obtained sends to the end Agent of each factory, is responsible for issuing with operation dispatching by them and orders.Shown in Figure 6 is the flow process of MOPSO algorithm.Shown in Figure 7 for upgrading the flow process of pbest.Shown in Figure 8 for upgrading the flow process of globally optimal solution gbest.Shown in Figure 9 for safeguarding the flow process of outside document.Installed capacity and the local data of loading of choosing thermoelectricity, water power and the wind-powered electricity generation in Xinzhou, two cities, Shuozhou for the present invention shown in Figure 10, the emulation experiment of carrying out.Can find out that from result of experiment " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention can be realized smoothly being incorporated into the power networks of wind-powered electricity generation through thermoelectricity and exerting oneself of Hydropower Unit in the collaborative electric power system.Shown in Figure 11 is based on " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention, and considers the comparison of coal consumption curve and the net coal consumption rate curve of each fired power generating unit of the operational mode of not considering economy, environmental protection of fired power generating unit of the operational mode of electric power system economy, environmental protection.Can draw through Figure 11; After adopting " wind-fire-water " coordinated dispatching method based on multiple agent of the present invention; The net coal consumption rate of fired power generating unit is starkly lower than the net coal consumption rate of only considering meritorious balance in the electric power system, explains that the inventive method can make electric power system reach the requirement of economy, environmental protection operation.
Claims (9)
1. " wind-fire-water " coordinated dispatching method based on multiple agent is characterized in that: this method is to adopt following steps to realize:
1) in scheduling Agent, makes up " wind-fire-water " cooperative scheduling model based on multiple agent;
2) by the prediction data of workload demand in the collection of the load Agent in the electric power system electric power system, the prediction data with the workload demand that collects is sent to the scheduling Agent in the electric power system simultaneously; After scheduling Agent received the prediction data of workload demand, each thermoelectricity Agent in electric power system, water power Agent, wind-powered electricity generation Agent sent the request of image data;
After each thermoelectricity Agent receives the request of image data, gather the master data and the real time data of each fired power generating unit in the electric power system; After each water power Agent receives the request of image data, gather the master data and the real time data of each Hydropower Unit in the electric power system; After each wind-powered electricity generation Agent receives the request of image data, gather the real time data and the prediction data of each wind-powered electricity generation unit in the electric power system;
3) by each thermoelectricity Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each water power Agent master data that collects and real time data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent; By each wind-powered electricity generation Agent real time data that collects and prediction data are sent in " wind-fire-water " the cooperative scheduling model based on multiple agent;
" wind-fire-water " cooperative scheduling model based on multiple agent decomposes the data that receive, and utilizes the MOPSO algorithm to solve exerting oneself of the exerting oneself of each fired power generating unit in the electric power system, each Hydropower Unit respectively;
4) will find the solution the exerting oneself of each fired power generating unit that obtains by scheduling Agent and be sent to each thermoelectricity Agent in the electric power system; To find the solution the exerting oneself of each Hydropower Unit that obtains by scheduling Agent and be sent to the water power Agent in the electric power system; Each thermoelectricity Agent, water power Agent issue and the operation dispatching order according to exerting oneself of receiving.
2. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 1 is characterized in that:
Said step 1) may further comprise the steps:
1.1) make up the frame model of " wind-fire-water " cooperative scheduling model; Said frame model comprises several thermoelectricitys Agent, several water power Agent, several wind-powered electricity generations Agent, thermoelectricity Management Agent, water power Management Agent, wind-powered electricity generation Management Agent, scheduling Agent and load Agent; Wherein, each thermoelectricity Agent connects scheduling Agent through the thermoelectricity Management Agent; Each water power Agent connects scheduling Agent through the water power Management Agent; Each wind-powered electricity generation Agent connects scheduling Agent through the wind-powered electricity generation Management Agent; Load Agent connects scheduling Agent;
1.2) structure " wind-fire-water " cooperative scheduling Model Optimization target function; The optimization aim of said optimization aim function comprises: the power-balance problem of electric power system; The economy problems of power system operation; The emission pollution problem of each fired power generating unit in the electric power system;
1.3) confirm the spinning reserve of each fired power generating unit in the electric power system;
1.4) make up the constraints of " wind-fire-water " cooperative scheduling model; Said constraints comprises: the constraint of the positive and negative spinning reserve of electric power system; The constraint of exerting oneself of each fired power generating unit, the constraint of regulations speed in the electric power system; The constraint of the constraint of the constraint of exerting oneself of each Hydropower Unit, regulations speed, storage capacity, the constraint of letdown flow in the electric power system; The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit in the electric power system.
3. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 1 is characterized in that:
Said step 2) in, the master data of each fired power generating unit comprises: the minimax of each fired power generating unit exert oneself, the make progress emissions data of downward regulations speed, operating cost data, pollutant; The real time data of each fired power generating unit comprises: each fired power generating unit go out force data in real time; The master data of each Hydropower Unit comprises: the minimax of each Hydropower Unit exert oneself, make progress downward regulations speed, minimax storage capacity, minimax letdown flow, operating cost data; The real time data of each Hydropower Unit comprises: each Hydropower Unit go out force data in real time; The real time data of each wind-powered electricity generation unit comprises: the data of the quality of power supply of each wind energy turbine set; The prediction data of each wind-powered electricity generation unit comprises: the prediction data of each wind energy turbine set; The prediction data of workload demand comprises: to the prediction data of load active power demand.
4. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 1 is characterized in that:
In the said step 3), the MOPSO algorithm may further comprise the steps:
3.1) the initialization population, and the scale M of definite population and total iterations N;
3.2) calculate the pairing object vector of each particle in the population, and upgrade the optimal solution pbest of each particle;
During to iterations iterations≤n, the noninferior solution in the population is joined in the outside document, and safeguard outside document;
To iterations iterations>during n, judge that whether fitness1 is less than ε; If greater than ε, think then that this is separated and be not noninferior solution; If less than ε, judge then whether fitness2 and fitness3 that this is separated arrange separating in the outside document; If domination is then directly separated this outside document of adding and is deleted ridden separating in the document; If this is separated by outside document domination, then this is separated and is not added outside document; If this separate with document in separate mutually and do not arrange, then this is separated the outside document of direct adding;
3.3) safeguard outside document, and from outside document, choose one and separate as globally optimal solution gbest;
3.4) upgrade each particle's velocity and position;
3.5) judge that whether iterations iterations is less than N; If iterations iterations is less than N, iterations iterations+1 then, and jump into step 3.2) circulation; If iterations iterations is greater than N, then loop ends;
3.6) from outside document, choose globally optimal solution gbest, and return globally optimal solution gbest.
5. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 2 is characterized in that:
Said step 1.2) in, the power-balance problem of electric power system obtains through following formula:
In the formula (1),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
is the active power of workload demand in the electric power system;
is the station service power consumption rate of transmission losses in the electric power system and each power plant;
The economy problems of power system operation obtains through following formula:
（2）；
In the formula (2),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
The emission pollution problem of each fired power generating unit obtains through following formula in the electric power system:
In the formula (3),
is the summation that discharges pollutants of each fired power generating unit in the electric power system;
Through type (2) and formula (3) can make the multiple electricity of unit that operating cost is lower in the electric power system, pollutant emission is less, and the unit that operating cost is higher, pollutant emission is more generates electricity less; Guarantee the requirement of the economy and the feature of environmental protection of power system operation thus.
6. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 2 is characterized in that:
Said step 1.3) in, definite principle of the spinning reserve of each fired power generating unit is following in the electric power system:
If fired power generating unit is coal group of motors and the annual peak regulation of participating in, to single-machine capacity 300MW and above newly-built unit, will rotate up subsequent use confirming as about 20%, will be rotated down and subsequent usely confirm as 25%; Production time unit early to single-machine capacity 200MW-600MW will rotate up subsequent use confirming as about 15%, will be rotated down subsequent use confirming as about 20%; To single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%;
If fired power generating unit is a thermoelectric unit and at heating period, to single-machine capacity 135MW and following unit, will exert oneself is obstructed confirms as 10%, will rotate up and subsequent usely confirm as 5%, will be rotated down and subsequent usely confirm as 10%; To single-machine capacity 200MW and above unit, will exert oneself is obstructed confirms as 15%-20%, will rotate up subsequent usely to confirm as 10%, will be rotated down subsequent usely to confirm as 10%; If fired power generating unit is a thermoelectric unit and at non-heating period, to single-machine capacity 135MW and following unit, will rotate up and subsequent usely confirm as 10%, will be rotated down and subsequent usely confirm as 15%; To the unit of single-machine capacity 200MW-300MW, will rotate up and subsequent usely confirm as 15%, will be rotated down and subsequent usely confirm as 20%.
7. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 2 is characterized in that:
Said step 1.4) in, the constraint of the positive and negative spinning reserve of electric power system obtains through following formula:
In the formula (4),
for each Hydropower Unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
for each fired power generating unit in the t electric power system constantly upwards, be rotated down subsequent use capacity summation;
predicted value for loading in the electric power system;
is the prediction data of each wind-powered electricity generation unit in the electric power system;
value for loading in the t electric power system constantly;
is the data of each wind-powered electricity generation unit in the t electric power system constantly;
The constraint of exerting oneself of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (5),
is exerting oneself of i the Hydropower Unit t moment;
is that i Hydropower Unit t minimum is constantly exerted oneself;
is i Hydropower Unit t EIAJ constantly;
The constraint of the regulations speed of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (6),
is the downward regulations speed of each Hydropower Unit in the electric power system;
is the upwards regulations speed of each Hydropower Unit in the electric power system;
The constraint of the letdown flow of each Hydropower Unit obtains through following formula in the electric power system:
In the formula (7),
is a Hydropower Unit t letdown flow constantly;
is a Hydropower Unit t minimum letdown flow constantly;
is a Hydropower Unit t maximum letdown flow constantly;
The constraint of the storage capacity of each Hydropower Unit obtains through following formula in the electric power system:
（8）；
In the formula (8),
is a Hydropower Unit t storage capacity constantly;
is a Hydropower Unit t minimum storage capacity constantly;
is a Hydropower Unit t maximum storage capacity constantly;
The constraint of exerting oneself of each fired power generating unit obtains through following formula in the electric power system:
In the formula (9),
is exerting oneself of i fired power generating unit;
is that the minimum of i fired power generating unit is exerted oneself;
is i unit EIAJ;
The constraint of the regulations speed of each fired power generating unit obtains through following formula in the electric power system:
（10）；
In the formula (10),
is the downward regulations speed of each fired power generating unit in the electric power system;
is the upwards regulations speed of each fired power generating unit in the electric power system;
The constraint of the wind-powered electricity generation quality of power supply of each wind-powered electricity generation unit comprises following condition in the electric power system:
Voltage deviation: control wind-powered electricity generation unit be incorporated into the power networks point voltage for its rated voltage-3%-7%;
Frequency departure: the normal frequency deviation allowable value of electric power system is ± 0.2Hz, when the capacity of electric power system hour, the normal frequency deviation allowable value is loosened to ± 0.5Hz;
Voltage unbalance degree limit value: when electric power system normally moved, the negative sequence voltage degree of unbalance was no more than 2%, was no more than 4% in short-term;
Tri-phase unbalance factor: the expression formula of tri-phase unbalance factor is following:
（11）；
In the formula (11);
is the positive sequence component root mean square value of three-phase voltage, and its unit is volt;
is the negative sequence component root mean square value of three-phase voltage, and its unit is volt;
is the zero-sequence component root mean square value of three-phase voltage, and its position is volt;
Flickering: the flickering interference value of the points of common connection that the wind-powered electricity generation unit is inserted satisfies the national standard requirement;
Harmonic wave: the harmonic wave injection current of the points of common connection at wind-powered electricity generation unit place satisfies the national standard requirement.
8. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 4 is characterized in that:
Said step 3.2) in, object vector obtains through following formula:
In the formula (12),
is the summation of exerting oneself of each wind-powered electricity generation unit in the electric power system;
is the summation of exerting oneself of each fired power generating unit in the electric power system;
is the summation of exerting oneself of each Hydropower Unit in the electric power system;
for the active power of workload demand in the electric power system,
is the station service power consumption rate of each power plant for the transmission losses in the electric power system;
In the formula (13),
is the operating cost of each Hydropower Unit in the electric power system;
is the operating cost of each fired power generating unit in the electric power system;
In the formula (14),
is the summation of the pollutant emission of each fired power generating unit in the electric power system.
9. " wind-fire-water " coordinated dispatching method based on multiple agent according to claim 4 is characterized in that:
Said step 3.4) in, upgrade each particle's velocity and position and obtain through following formula:
In formula (15)-(17), w is the inertia weight of particle rapidity; Iterations is an iterations; N is total iterations;
and
is the random number of [0,1]; Pbest is the locally optimal solution of particle; Gbest is the globally optimal solution of particle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210247055.3A CN102738835B (en) | 2012-07-17 | 2012-07-17 | Wind-fire-water co-scheduling method on basis of multi-agent system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210247055.3A CN102738835B (en) | 2012-07-17 | 2012-07-17 | Wind-fire-water co-scheduling method on basis of multi-agent system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102738835A true CN102738835A (en) | 2012-10-17 |
| CN102738835B CN102738835B (en) | 2014-08-20 |
Family
ID=46993849
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210247055.3A Active CN102738835B (en) | 2012-07-17 | 2012-07-17 | Wind-fire-water co-scheduling method on basis of multi-agent system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102738835B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103151803A (en) * | 2013-03-14 | 2013-06-12 | 吉林省电力有限公司电力科学研究院 | Method for optimizing wind power system-contained unit and backup configuration |
| CN103208813A (en) * | 2013-01-21 | 2013-07-17 | 云南电网公司电网规划研究中心 | Power system daily peak regulation capability assessment method for accurately calculating wind power influence |
| CN103427444A (en) * | 2013-05-16 | 2013-12-04 | 新疆大学 | Control method for reducing wind power grid-connected scheduling plan error |
| CN103490449A (en) * | 2013-10-10 | 2014-01-01 | 华北电力大学 | Method for optimizing operation simulation of multi-energy combined power generation system |
| CN103887814A (en) * | 2014-02-13 | 2014-06-25 | 国家电网公司 | Thermal power unit emergency control method for blower group offline fault |
| CN104424510A (en) * | 2013-09-06 | 2015-03-18 | 华北电力大学（保定） | Power transmission grid frame recovering method based on plurality of intelligent bodies and cluster simulation of thermal power generating unit |
| CN105048516A (en) * | 2015-08-18 | 2015-11-11 | 四川大学 | Wind-light-water-fire multi-source complementary optimization scheduling method |
| CN106130079A (en) * | 2016-07-08 | 2016-11-16 | 华北电力大学 | A kind of edema due to wind pathogen fire short-term joint optimal operation method |
| CN107479523A (en) * | 2017-09-28 | 2017-12-15 | 齐鲁工业大学 | Multiple agent based on QPSO manufactures process optimization method and apparatus |
| CN108678815A (en) * | 2018-05-07 | 2018-10-19 | 国网黑龙江省电力有限公司电力科学研究院 | The minimum technology output measurement device and method of extraction condensing type Turbo-generator Set |
| CN113515831A (en) * | 2021-07-30 | 2021-10-19 | 广东电网有限责任公司 | Energy scheduling method and device, electronic equipment and storage medium |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107730029B (en) * | 2017-09-22 | 2019-09-06 | 齐鲁工业大学 | Manufacturing process optimization method and apparatus based on quantum-behaved particle swarm optimization |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10020965A1 (en) * | 2000-04-28 | 2001-10-31 | Umweltkontor Ingenieurgmbh | Power generation involves accumulating and transmitting power generator-specific characteristics for distributed power generation plants e.g. wind power plants using standard interface |
| JP2002354679A (en) * | 2001-05-29 | 2002-12-06 | Kyocera Corp | Power conversion device, and power supply system using it |
| CN102097828A (en) * | 2010-12-30 | 2011-06-15 | 中国电力科学研究院 | Wind power optimal scheduling method based on power forecast |
| CN102170129A (en) * | 2011-04-22 | 2011-08-31 | 武汉大学 | Low-carbon dispatching method and device for electric power system based on large-scale wind power grid connection |
-
2012
- 2012-07-17 CN CN201210247055.3A patent/CN102738835B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10020965A1 (en) * | 2000-04-28 | 2001-10-31 | Umweltkontor Ingenieurgmbh | Power generation involves accumulating and transmitting power generator-specific characteristics for distributed power generation plants e.g. wind power plants using standard interface |
| JP2002354679A (en) * | 2001-05-29 | 2002-12-06 | Kyocera Corp | Power conversion device, and power supply system using it |
| CN102097828A (en) * | 2010-12-30 | 2011-06-15 | 中国电力科学研究院 | Wind power optimal scheduling method based on power forecast |
| CN102170129A (en) * | 2011-04-22 | 2011-08-31 | 武汉大学 | Low-carbon dispatching method and device for electric power system based on large-scale wind power grid connection |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103208813A (en) * | 2013-01-21 | 2013-07-17 | 云南电网公司电网规划研究中心 | Power system daily peak regulation capability assessment method for accurately calculating wind power influence |
| CN103208813B (en) * | 2013-01-21 | 2015-03-25 | 云南电网公司电网规划研究中心 | Power system daily peak regulation capability assessment method for accurately calculating wind power influence |
| CN103151803A (en) * | 2013-03-14 | 2013-06-12 | 吉林省电力有限公司电力科学研究院 | Method for optimizing wind power system-contained unit and backup configuration |
| CN103427444A (en) * | 2013-05-16 | 2013-12-04 | 新疆大学 | Control method for reducing wind power grid-connected scheduling plan error |
| CN103427444B (en) * | 2013-05-16 | 2015-07-08 | 新疆大学 | Control method for reducing wind power grid-connected scheduling plan error |
| CN104424510B (en) * | 2013-09-06 | 2018-10-09 | 华北电力大学（保定） | The transmission of electricity rack restoration methods emulated based on multiple agent and fired power generating unit cluster |
| CN104424510A (en) * | 2013-09-06 | 2015-03-18 | 华北电力大学（保定） | Power transmission grid frame recovering method based on plurality of intelligent bodies and cluster simulation of thermal power generating unit |
| CN103490449A (en) * | 2013-10-10 | 2014-01-01 | 华北电力大学 | Method for optimizing operation simulation of multi-energy combined power generation system |
| CN103887814A (en) * | 2014-02-13 | 2014-06-25 | 国家电网公司 | Thermal power unit emergency control method for blower group offline fault |
| CN103887814B (en) * | 2014-02-13 | 2015-12-02 | 国家电网公司 | A kind of urgent regulate and control method of fired power generating unit of tackling blower fan group off-grid fault |
| CN105048516A (en) * | 2015-08-18 | 2015-11-11 | 四川大学 | Wind-light-water-fire multi-source complementary optimization scheduling method |
| CN106130079A (en) * | 2016-07-08 | 2016-11-16 | 华北电力大学 | A kind of edema due to wind pathogen fire short-term joint optimal operation method |
| CN106130079B (en) * | 2016-07-08 | 2018-11-09 | 华北电力大学 | A kind of short-term joint optimal operation method of geomantic omen fire |
| CN107479523A (en) * | 2017-09-28 | 2017-12-15 | 齐鲁工业大学 | Multiple agent based on QPSO manufactures process optimization method and apparatus |
| CN108678815A (en) * | 2018-05-07 | 2018-10-19 | 国网黑龙江省电力有限公司电力科学研究院 | The minimum technology output measurement device and method of extraction condensing type Turbo-generator Set |
| CN108678815B (en) * | 2018-05-07 | 2020-11-10 | 国网黑龙江省电力有限公司电力科学研究院 | Minimum technical output determination device and method for extraction condensing steam turbine generator unit |
| CN113515831A (en) * | 2021-07-30 | 2021-10-19 | 广东电网有限责任公司 | Energy scheduling method and device, electronic equipment and storage medium |
| CN113515831B (en) * | 2021-07-30 | 2023-07-18 | 广东电网有限责任公司 | Energy scheduling method and device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102738835B (en) | 2014-08-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102738835B (en) | Wind-fire-water co-scheduling method on basis of multi-agent system | |
| CN102710013B (en) | Park energy-network energy optimizing management system based on microgrids and implementing method thereof | |
| CN103825279B (en) | Based on the micro-grid system Voltage Stability Control method of robust control | |
| CN105470982B (en) | The intelligent micro-grid generated power control system and control method of a kind of energy storage containing medium | |
| CN102842904B (en) | Micro-grid collaborative frequency control method based on power shortage prediction and distribution | |
| CN102611118B (en) | Method for comprehensively controlling reactive voltage of wind farm with imported prediction method | |
| CN103441520B (en) | Micro-grid distribution type new energy storage system | |
| CN103001223B (en) | Off-grid type microgrid frequency adjusting method based on control of energy-storing current converter | |
| CN104795846A (en) | Optimized operation method of pumped-storage power station and wind power combined system | |
| CN102355057A (en) | Computer monitoring method for microgrid system | |
| CN104184171A (en) | Wind power plant layer active power control system and method | |
| CN108767876A (en) | A kind of active frequency response model forecast Control Algorithm towards bulk power grid | |
| CN104953622B (en) | A kind of distributed power source accesses monitoring system | |
| CN109992818A (en) | The Unit Combination model and method for solving of large-scale wind power participation primary frequency modulation | |
| Iov et al. | Advanced power converter for universal and flexible power management in future electricity network | |
| CN106300323A (en) | Distributed power source electrical network | |
| CN206211536U (en) | Distributed power source power network | |
| CN209488190U (en) | Multi-purpose station electric system | |
| CN113612259B (en) | Comprehensive energy station coordination control secondary system and method | |
| CN107332249A (en) | Consider the fuzzy optimal trend method of the multiple target dynamic random of power system containing wind-powered electricity generation of transmission ＆ distribution collaboration | |
| CN107196348A (en) | It is a kind of to consider the soft straight generation schedule preparation method a few days ago of multiterminal | |
| CN112068502A (en) | Distributed energy multi-machine remote centralized control management system | |
| Sun et al. | Research on Coordinated and Optimized Operation of Electric-Thermal Energy System with Concentrated Solar Power Plant | |
| Wen et al. | Retrospect and prospect of wind power participating in power system frequency regulation | |
| CN205051360U (en) | Power transmission network structure that contains distributed generator |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C53 | Correction of patent of invention or patent application | ||
| CB02 | Change of applicant information |
Address after: 030013 No. 36 South Street, red ditch, Shanxi, Taiyuan Applicant after: Engineering College of Shanxi University Applicant after: Electric Power Research Institute of State Grid Shanxi Power Supply Company Address before: 030013 No. 36 South Street, red ditch, Shanxi, Taiyuan Applicant before: Engineering College of Shanxi University Applicant before: Electric Power Research Institute of Shanxi Electric Power Company |
|
| ASS | Succession or assignment of patent right |
Owner name: STATE GRID CORPORATION OF CHINA ELECTRIC POWER RES Free format text: FORMER OWNER: ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANXI POWER SUPPLY COMPANY Effective date: 20140708 Owner name: SHANXI UNIVERISTY Free format text: FORMER OWNER: TAIYUAN INSTITUTE OF ELECTRICAL ENGINEERING Effective date: 20140708 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| COR | Change of bibliographic data |
Free format text: CORRECT: ADDRESS; FROM: 030013 TAIYUAN, SHAANXI PROVINCE TO: 030006 TAIYUAN, SHAANXI PROVINCE |
|
| TA01 | Transfer of patent application right |
Effective date of registration: 20140708 Address after: 030006 No. 90, Hollywood Road, Taiyuan, Shanxi Applicant after: Shanxi Univeristy Applicant after: State Grid Corporation of China Applicant after: Electric Power Research Institute of State Grid Shanxi Power Supply Company Address before: 030013 No. 36 South Street, red ditch, Shanxi, Taiyuan Applicant before: Engineering College of Shanxi University Applicant before: Electric Power Research Institute of State Grid Shanxi Power Supply Company |
|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |