CN106779165A - Power system environment dispatching method based on urban air-quality Predicting Technique - Google Patents
Power system environment dispatching method based on urban air-quality Predicting Technique Download PDFInfo
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Abstract
The invention discloses a kind of power system environment dispatching method based on urban air-quality Predicting Technique, including step one：History meteorological data, Historical Pollution source emission data and the history air quality information of target cities are obtained from weather environment database, the following air quality of target cities is predicted using artificial neural network algorithm is obtained Air Quality Forecast value；Step 2：Judge whether Air Quality Forecast value has correlation with history meteorological data, if so, obtaining the atmospheric environment saturation of target cities；Otherwise, return to step one；Step 3：Set up power system environment scheduling model；Step 4：Under the conditions of default constraints and the atmospheric environment saturation for meeting target cities, power system environment scheduling model is solved, obtain the optimum value of the active power output of each unit, and then obtain power system environment scheduling scheme.Under this scheduling method, system gross contamination thing discharge capacity is significantly reduced, and financial cost is balanced with Environmental costs.
Description
Technical field
The invention belongs to power scheduling field, more particularly to a kind of power system based on urban air-quality Predicting Technique
Environment dispatching method.
Background technology
The environmental situation of China is serious at present, and the problem of environmental pollution with haze as representative has had a strong impact on people's
Daily life, endangers the health of people.The problem caused by such a long-term excess emissions, has only enterprising from source
Row is administered, and reduces discharge or even zero-emission.Used as coal-fired rich and influential family, annual discharge amount of pollution is considerable, " low-carbon (LC) for power system
Emission reduction, energy-conserving and environment-protective " is undoubtedly the key challenge that power system future development will face.
With social progress, the raising of people's living standard, Ecological Civilization Construction is more subject to government and the common people
Concern.Increasing spatiotemporal, trans-regional linkage is generated between environmental factor and electric power system dispatching.On the one hand,
Pollutant in air is diffused with air flow, it will change the pollutant index between different zones, so as to power train
System pollutant emission forms hard constraints, influences original scheduling result；On the other hand, environmental factor will produce shadow to energy resource structure
Ring, regenerative resource is more taken seriously, and the ratio of the power supply such as wind-powered electricity generation, photovoltaic, cogeneration of heat and power will constantly increase, such new energy
Power supply is sensitive to environmental factor, and the change of weather will cause its fluctuation seriously, and the safety and stability to power network is a no small punching
Hit.Under the requirement of energy-saving and emission-reduction, under environmental factor and the continuous more close background of power system, traditional power scheduling
The need for pattern does not adapt to sustainable development and Ecological Civilization Construction, therefore, research is a set of to take into account " economical ", " section
Comprehensive all kinds of the new of key element such as energy environmental protection ", science, efficient power system environment scheduling mode, with highly important reason
By meaning and researching value.
Power system energy-saving distribution reduces energy loss and reduces environmental pollution to a certain extent；External some hairs
Power system up to country has been set up opening the electricity market of user side, generating, distribution, retailer and with can join per family
With marketing, two-way mutual electric power system dispatching can be carried out.Both at home and abroad for grinding that electric power system dispatching problem is carried out
Study carefully and have been achieved for a large amount of achievements.But these researchs inherent connection not between mining environment factor and electric power system dispatching
System, a portion scheduling mode only focuses on the control of financial cost and ignores the importance of energy-saving and emission-reduction；Another part is adjusted
Degree mode is conceived to the control of energy-conservation and carbon emission, but ignores SO2、NOx, the important pollutant such as dust brings to atmospheric environment
Negative effect；The researchs launched for environment scheduling few in number are then limited only to algorithm aspect, fail to implement to reality,
Electric power system dispatching could not be combined with real atmosphere environment.
Existing electric power system dispatching does not set up environmental factor and electric power system dispatching on the various dimensions such as time, space
Inner link, it is impossible to ask for accurate power system environment scheduling model, it is impossible to obtain each unit active power output it is optimal
Value, therefore, existing power system environment scheduling scheme does not consider environmental factor with electric power system dispatching in time and sky
Between inner link on various dimensions so that power system expends that energy is more and discharge amount of pollution is big, the negative shadow caused to environment
Ring big.
The content of the invention
The invention discloses a kind of power system environment dispatching method based on urban air-quality Predicting Technique.The present invention
It is artificial urban air-quality is predicted using neural network algorithm with reference to real time meteorological data, carried out to prediction data
After relevance verification, prediction data is converted into urban atmospheric pollution saturation using numerical method, in this, as power system
More crucial environmental constraint in environment scheduling.With electric power system dispatching be combined so as to set up environmental factor by the present invention
A kind of new environment scheduling method, this environment scheduling can effectively reduce power system pollutant emission, be that energy-saving and emission-reduction are done
Go out positive contribution.
To achieve the above object, concrete scheme of the invention is as follows：
A kind of power system environment dispatching method based on urban air-quality Predicting Technique, including：
Step one：History meteorological data, the Historical Pollution source emission number of target cities are obtained from weather environment database
According to history air quality information, the following air quality of target cities is predicted using artificial neural network algorithm, obtain
To Air Quality Forecast value；
Step 2：Judge whether Air Quality Forecast value has correlation with history meteorological data, if so, using numerical method
The atmospheric environment saturation of target cities is obtained to the treatment of Air Quality Forecast value；Otherwise, return to step one；
Step 3：Set up power system environment scheduling model；Wherein, power system environment scheduling model is electric to ask for target
The minimum value of the total operating cost of Force system, the total operating cost of target power system is equal to the operating cost of each unit and all kinds of
The punishment cost sum of pollutant emission；The operating cost of unit and the punishment cost of pollutant emission are unit active power output
Function；
Step 4：Under the conditions of default constraints and the atmospheric environment saturation for meeting target cities, electric power is solved
System environments scheduling model, obtains the optimum value of the active power output of each unit, and then obtains power system environment scheduling scheme.
Mining environment factor of the present invention and inner link of the electric power system dispatching on the various dimensions such as time, space, set up
The a set of power system environment scheduling model based on urban air-quality Predicting Technique, urban air-quality real time information is melted
Enter among electric power system dispatching, power system is scheduled according to urban atmosphere annelism, reach the mesh of energy-saving and emission-reduction
And improved with this go from bad to worse ambient air quality, reduce the negative effect that is brought to environment of disposal of pollutants.
It is to the process that future city air quality is predicted using artificial neural network algorithm in step one：
Using history meteorological data as characterization factor, selection meets the history air quality information of selected history meteorological data
Used as training sample, discharge of pollutant sources data are the input factor, delivery air quality predictions.
The change for finding pollutant by the analysis to pollutant monitoring data has stronger non-linear spy
Property, it is accurately predicted, just must be using the forecasting procedure that can catch non-linear change tendencies.Artificial neuron
Network, as a computer model with nonlinear ability, is the very effective instrument for processing this problem.
The present invention is modeled prediction to urban air-quality using artificial neural network algorithm.Present invention combination real time meteorological data,
It is artificial urban air-quality is predicted using neural network algorithm, so that predicting the outcome, it is higher to have with sample data
Correlation, while error is smaller compared with congenic method, it is more accurate to predict the outcome.
In step 2, project pollution far stronger+(air matter is drafted in the atmospheric environment saturation=planning region of target cities
Amount secondary standard mean annual concentration-locality atmosphere pollution background value-the point concerned mean annual concentration predicted value) plan in * planning regions
Determine project pollution far stronger/the point concerned mean annual concentration predicted value；Wherein, project pollution far stronger, air quality are drafted in planning region
Secondary standard mean annual concentration and local atmosphere pollution background value are given data, and the point concerned mean annual concentration predicted value is by step
A rapid prediction is obtained.
The point concerned is the atmosphere environment supervision website in target cities.
Urban air-quality is predicted the outcome and is converted into atmospheric environment capacity by the present invention using numerical method, in this, as electric power
To the environmental constraints of unit output in system environments scheduling, environmental factor is cleverly combined with electric power system dispatching.
In step 2, by calculating the coefficient correlation of Air Quality Forecast value and history meteorological data, air matter is obtained
Measure the correlation of predicted value and history meteorological data.Concentration prediction value is converted into atmospheric environment saturation to electricity with numerical method
Force system is dispatched into row constraint, finally gives accurate power system environment scheduling scheme.
In step 4, presetting constraints includes active units limits, power-balance constraint and environmental constraints.
The present invention solves electric power under the conditions of presetting constraints and meeting the atmospheric environment saturation of target cities
System environments scheduling model, obtains the optimum value of the active power output of each unit, and then obtains power system environment scheduling scheme, most
Power system is reached eventually expends the purpose that energy and discharge amount of pollution are reduced.
Wherein, active power output is constrained to：The active power output of any unit is held at a preset range in power system
Within.
Power-balance constraint is：The power that the power that generators in power systems sends is consumed with load and network loss keeps phase
Deng.
Environmental constraint also includes：The total blowdown flow rate of target power system is no more than atmospheric environment saturation, and every
Maximum blowdown flow rate of the blowdown share of unit no more than preset standard regulation.
Meteorological data in the step one includes wind speed, wind direction and temperature.
Meteorological data can also include humidity and sunshine information in step one.
Air quality information in the step one includes air quality index, PM2.5 concentration values, SO2Concentration value and NOx
Concentration value.
Air quality information in step one also includes dust concentration value, TSP concentration value, inhalable particles
Thing concentration value (PM10) and ozone concentration value.
Beneficial effects of the present invention：
(1) urban air-quality is predicted using artificial neural network algorithm, predict the outcome has with sample data
Correlation higher, while error is smaller compared with congenic method, it is more accurate to predict the outcome.
(2) urban air-quality is predicted the outcome using numerical method and is converted into atmospheric environment capacity, in this, as power train
To the environmental constraints of unit output in system environment scheduling, environmental factor is cleverly combined with electric power system dispatching.
(3) present invention go deep into mining environment factor and electric power system dispatching on the various dimensions such as time, space in connection
System, is considering that power system is Eco-power simultaneously, focuses on the overall blowdown cost of control system, under environment scheduling, system
Total pollutant discharge amount is significantly reduced, and is conducive to improving atmospheric environment situation severe at present from source, has taken into account electric power
The economy and environmental protection characteristic of system.
Brief description of the drawings
Fig. 1 is the power system environment dispatching method flow chart based on urban air-quality Predicting Technique of the invention.
Specific embodiment
The present invention will be further described with embodiment below in conjunction with the accompanying drawings：
It is to tackle the ambient air quality problem for going from bad to worse, performance power system is in " energy-saving and emission-reduction, preventing and treating haze "
Effect, the present invention is studied meter and the power system optimal dispatch problem of environmental factor, based on environmental factor and electric power
The inner link of system, urban air-quality real time information is dissolved among electric power system dispatching, uses neural network algorithm
Urban pollutant concentration is predicted, concentration prediction value is converted into atmospheric environment saturation to power system with numerical method
Dispatch into row constraint.Under this scheduling method, the total pollutant discharge amount of system is significantly reduced, financial cost and Environmental costs
Balanced.
Fig. 1 is the power system environment dispatching method flow chart based on urban air-quality Predicting Technique of the invention.Such as
The power system environment dispatching method based on urban air-quality Predicting Technique shown in Fig. 1, comprises the following steps：
Step one：History meteorological data, the Historical Pollution source emission number of target cities are obtained from weather environment database
According to history air quality information, the following air quality of target cities is predicted using artificial neural network algorithm, obtain
To Air Quality Forecast value.
In step one, air quality information includes：Air quality index (AQI), PM2.5 concentration values, SO2Concentration value and
NOxConcentration value；Meteorological data includes：Wind direction, wind speed and temperature.
Target cities air quality is predicted, it is necessary to using history meteorological data.The present invention is by wind direction, wind speed, gas
The data such as temperature are used as characterization factor, and the discharge of pollutant sources and monitoring station that selected meteorological condition is met in selection meteorogical phenomena database are small
When Monitoring Data as training sample, discharge of pollutant sources data are the input factor, the Monitoring Data conduct that monitoring site is monitored
The output factor.
The change for finding pollutant by the analysis to pollutant monitoring data has stronger non-linear spy
Property, it is accurately predicted, just must be using the forecasting procedure that can catch non-linear change tendencies.Artificial neuron
Network, as a computer model with nonlinear ability, is the very effective instrument for processing this problem.
The present invention is modeled prediction to urban air-quality using BP neural network algorithm.
There are many models in artificial neural network, wherein error back propagation (BP) neutral net is that application is the widest at present
One of general network model, is a kind of effectively algorithm.
Neural network model firstly the need of sample is provided, includes the input factor and the corresponding phase before training in sample
The output factor is hoped, weights and threshold value should be constantly adjusted in training process, to cause that the error function of neutral net reaches minimum.BP
The guiding theory of neutral net is to decline most fast direction (i.e. negative gradient along performance function to the amendment of network weight and threshold value
Direction) carry out.Its training process is made up of two parts：Information forward-propagating and error back propagation.BP neural network model by
A series of " layers " composition that many simple processing units are constituted, including input layer, hidden layer (can be one or more layers) and
Output layer.For input signal, implicit node is first traveled to forward, by after activation primitive, then the output of implicit node
Information Communication finally provides output result to output node.Network operation process includes forward-propagating and backpropagation two parts,
During forward-propagating, input signal passes through excitation function from input layer, successively to hidden layer, output Es-region propagations；If cannot
Desired output, then be transferred to backpropagation, error signal is returned along original connecting path, by changing each layer neuron
Weights so that error signal is minimum, so as to terminate the learning process of network.The continuous iteration of above procedure, finally causes that signal is missed
Difference is reached in allowed band.
Neutral net is trained using the meteorological data collected, the output error of output layer to it is implicit once and input layer
Carry out backpropagation, and weights to each interlayer are constantly corrected, and systematic variance is reached minimum, now trained god
It is that can be used for the prediction of urban air-quality through network.
Step 2：Judge whether Air Quality Forecast value has correlation with history meteorological data, if so, using numerical method
The atmospheric environment saturation of target cities is obtained to the treatment of Air Quality Forecast value；Otherwise, return to step one.
In step 2, by calculating the coefficient correlation of Air Quality Forecast value and history meteorological data, air matter is obtained
Measure the correlation of predicted value and history meteorological data.
Whether inspection predicted value has correlation with meteorological data, is more than as a example by 0.7 by coefficient correlation
Coefficient correlation predicts the outcome with meteorological data more than 0.7 explanation has correlation, and meteorological data selection is reasonable, prediction
Result precision is high；Coefficient correlation predicts the outcome weak with meteorological data correlation less than 0.7 explanation, should now reselect meteorology
Data.
Requirement with reality to the accuracy that predicts the outcome, coefficient correlation can also select other numerical value.
In step 2, urban air-quality information prediction data are processed using numerical method, obtain urban atmosphere
Carrying capacity.For target cities, in order to realize to the pollutant emission constraint in city, it is necessary to precompute whole
The atmospheric environment capacity in city.The atmospheric environment capacity that we are usually previously mentioned in Environmental Impact Assessment generally refers to narrow sense
On atmospheric environment capacity, mainly in the atmospheric environment capacity of indivedual pollutant factors, typically all conventional big compression ring
Border contaminant transport model index, such as SO2、NO2, flue dust (PM10) etc..
The atmospheric environment capacity of the target cities asked by equation below：
In formula：Emax：Atmospheric environment capacity, Co：Air quality secondary standard mean annual concentration (mg/m3)、Cs：Local air
Pollutant background value (mg/m3)、Ccon：The point concerned mean annual concentration predicted value (mg/m3)、Qpre：It is dirty to draft project in planning region
Dye source strength.Wherein, project pollution far stronger, air quality secondary standard mean annual concentration and local atmosphere pollution are drafted in planning region
Thing background value is given data, and the point concerned mean annual concentration predicted value is obtained by step one prediction.
The target cities atmospheric environment capacities E that solution is obtainedmaxThe pollutant emission of system is about among being dispatched as environment
Beam.
Step 3：Set up power system environment scheduling model；Wherein, power system environment scheduling model is electric to ask for target
The minimum value of the total operating cost of Force system, the total operating cost of target power system is equal to the operating cost of each unit and all kinds of
The punishment cost sum of pollutant emission；The operating cost of unit and the punishment cost of pollutant emission are unit active power output
Function.
In step 3, the total operating cost of target power system shows as the operating cost of each unit and all kinds of pollutions
The punishment cost of thing discharge.The operating cost of fired power generating unit is commonly described as the quadratic function of unit active power output.
Object function is the optimization of system synthesis sheet：
In formula, FCIt is the operating cost of fired power generating unit, FEIt is the punishment cost of fired power generating unit pollutant emission；N is unit platform
Number, is positive integer；PiIt is the active power output of unit i；ai,bi,ciFuel cost curve letter respectively in the unit i unit interval
Several coefficients, ai,bi,ciIt is constant；PeIt is the punishment cost price of pollutant emission；EPiIt is the pollutant emission of unit i
Amount.
System predominant emissions SO2、NOxDischarge capacity can be expressed as the function of unit output.Such as the NO of unitxDischarge
Function is represented by the quadratic function and exponential function sum of active power output, to SO2Discharge has similar description, can be right as needed
Emissions object is selected.The discharge function E of unit iPiIt is expressed as：
α in formulai、βi、γi、ξi、λiIt is the discharge function coefficients of unit i, αi、βi、γi、ξi、λiIt is constant.
Environment scheduling is carried out to power system will follow following constraints：
(1) active power output constraint
Pi,min≤Pi≤Pi,max, i=1,2 ..., N
Within the scope of the active power output of any unit should all be maintained at one normally in system, P in formulai,min、Pi,maxPoint
Not Wei each unit active power output bound；PiIt is the active power output of unit i, N is unit number of units, is positive integer.
(2) power-balance constraint
In power system, the power that the power that generator sends is consumed with load and network loss should keep equal.
P in formulaD、PLThe respectively load and network loss of system；PiIt is the active power output of unit i, N is unit number of units, is just whole
Number.Load can be obtained before implementation is dispatched by prediction, be in practice a stochastic variable, can be considered fixed in the range of each scheduling slot
Value；The exact value of via net loss can again be tried to achieve after solving system power flow equation, but generally using easy Kron's nets
Damage formula and calculate approximation：
BinIt is i-th row the n-th row component of loss factor matrix B, wherein, i rows are corresponding with unit i.
(3) environmental constraints：
Pollutant emission is constrained
For the overall pollutant discharge amount of control system, reduce power system and discharge the influence brought to atmospheric environment,
It is preferable solution within city atmospheric environment capacity by the total exhaust emission constraint of system.
EPi≤Eli, i=1,2,3 .., N
The total blowdown flow rate of system should be less than the atmospheric environment saturation of goal systems, while every blowdown share of unit
National standard should be followed, the maximum blowdown flow rate of standard regulation is must not exceed.
Step 4：Under the conditions of default constraints and the atmospheric environment saturation for meeting target cities, electric power is solved
System environments scheduling model, obtains the optimum value of the active power output of each unit, and then obtains power system environment scheduling scheme.
The present invention gos deep into mining environment factor and inner link of the electric power system dispatching on the various dimensions such as time, space,
Considering that power system is Eco-power simultaneously, focusing on the overall blowdown cost of control system, under environment scheduling, system is total
Pollutant discharge amount is significantly reduced, and is conducive to improving atmospheric environment situation severe at present from source, has taken into account power system
Economy and environmental protection characteristic.
Although above-mentioned be described with reference to accompanying drawing to specific embodiment of the invention, not to present invention protection model
The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not
Need the various modifications made by paying creative work or deformation still within protection scope of the present invention.
Claims (10)
1. a kind of power system environment dispatching method based on urban air-quality Predicting Technique, it is characterised in that including：
Step one：Obtained from weather environment database the history meteorological data of target cities, Historical Pollution source emission data and
History air quality information, is predicted using artificial neural network algorithm to the following air quality of target cities, obtains sky
Gas quality predictions；
Step 2：Judge whether Air Quality Forecast value has correlation with history meteorological data, if so, using numerical method to sky
The treatment of gas quality predictions obtains the atmospheric environment saturation of target cities；Otherwise, return to step one；
Step 3：Set up power system environment scheduling model；Wherein, power system environment scheduling model is to ask for target power system
The minimum value of the total operating cost of system, the total operating cost of target power system is equal to the operating cost of each unit and all kinds of pollutions
The punishment cost sum of thing discharge；The operating cost of unit and the punishment cost of pollutant emission are the letter of unit active power output
Number；
Step 4：Under the conditions of default constraints and the atmospheric environment saturation for meeting target cities, power system is solved
Environment scheduling model, obtains the optimum value of the active power output of each unit, and then obtains power system environment scheduling scheme.
2. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, is to the process that future city air quality is predicted using artificial neural network algorithm in step one：
Using history meteorological data as characterization factor, selection meets the history air quality information conduct of selected history meteorological data
Training sample, discharge of pollutant sources data are the input factor, delivery air quality predictions.
3. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, in step 2, project pollution far stronger+(air is drafted in the atmospheric environment saturation=planning region of target cities
Mass secondary standard mean annual concentration-locality atmosphere pollution background value-the point concerned mean annual concentration predicted value) in * planning regions
Draft project pollution far stronger/the point concerned mean annual concentration predicted value；Wherein, project pollution far stronger, air matter are drafted in planning region
Amount secondary standard mean annual concentration and local atmosphere pollution background value are given data, the point concerned mean annual concentration predicted value by
Step one prediction is obtained.
4. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, in step 4, presetting constraints includes active units limits and power-balance constraint.
5. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 4, its
It is characterised by, active power output is constrained to：The active power output of any unit is held within a preset range in power system.
6. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 4, its
It is characterised by, power-balance constraint is：The power that the power that generators in power systems sends is consumed with load and network loss keeps
It is equal.
7. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, default constraints also includes：The blowdown share of every unit of target power system is advised no more than preset standard
Fixed maximum blowdown flow rate.
8. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, the meteorological data in the step one includes wind speed, wind direction and temperature.
9. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, the air quality information in the step one includes air quality index, PM2.5 concentration values, SO2Concentration value and NOx
Concentration value.
10. a kind of power system environment dispatching method based on urban air-quality Predicting Technique as claimed in claim 1, its
It is characterised by, in step 2, by calculating the coefficient correlation of Air Quality Forecast value and history meteorological data, obtains air matter
Measure the correlation of predicted value and history meteorological data.
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