CN108767854A - Power purchase scheme optimization method, apparatus and electronic equipment - Google Patents
Power purchase scheme optimization method, apparatus and electronic equipment Download PDFInfo
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- CN108767854A CN108767854A CN201810641137.3A CN201810641137A CN108767854A CN 108767854 A CN108767854 A CN 108767854A CN 201810641137 A CN201810641137 A CN 201810641137A CN 108767854 A CN108767854 A CN 108767854A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/62—The condition being non-electrical, e.g. temperature
- H02J2310/64—The condition being economic, e.g. tariff based load management
-
- 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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
Abstract
The present invention provides a kind of power purchase scheme optimization method, apparatus and electronic equipments, are related to power management techniques field, and power purchase scheme optimization method includes：Object function is established, keeps the weighted value of power purchase total cost in the object function and Trading risk value minimum, wherein the power purchase total cost includes：Preset time outsourcing electricity charge use, preset time power purchase expense and spot market power purchase expense；Establish power purchase constraints model；It is based on the object function according to the power purchase constraints model, it is calculated by particle cluster algorithm, obtain power purchase data, solves the technical issues of market that current power purchase strategy existing in the prior art mainly considers is excessively single, can not adapt to the continuous variation and development of Vehicles Collected from Market environment.
Description
Technical field
The present invention relates to power management techniques fields, more particularly, to a kind of power purchase scheme optimization method, apparatus and electricity
Sub- equipment.
Background technology
Electricity market includes two kinds of meanings of broad sense and narrow sense, the electricity market of broad sense refer to power generation, transmission, using and
The summation of sale relationship；The electricity market of narrow sense refers to emulative electricity market, is that electrical energy production person and user pass through association
Quotient, the modes such as bid are traded with regard to electric energy and its Related product, are set price the mechanism with quantity by market competition.
Under Power Market, it is that provincial power network economic benefit is real that Trading risk is controlled while reducing power purchase expense
Existing is basic.Monthly electricity purchasing plan has accounted for 80% or more of transaction total amount.Therefore, the research of monthly electricity purchasing plan passes through power grid
The realization of battalion's target is of great significance.
But the market that power purchase strategy mainly considers at present is excessively single, can not adapt to the continuous change of Vehicles Collected from Market environment
Change and develops.
Invention content
In view of this, the purpose of the present invention is to provide a kind of power purchase scheme optimization method, apparatus and electronic equipment, with
It is excessively single to solve the market that current power purchase strategy existing in the prior art mainly considers, Vehicles Collected from Market environment can not be adapted to
The technical issues of constantly variation is with development.
In a first aspect, an embodiment of the present invention provides a kind of power purchase scheme optimization methods, including：Object function is established, is made
The weighted value of power purchase total cost in the object function and Trading risk value is minimum, wherein the power purchase total cost includes：In advance
If time outsourcing electricity charge use, preset time power purchase expense and spot market power purchase expense；
Establish power purchase constraints model；
It is based on the object function according to the power purchase constraints model, is calculated, is obtained by particle cluster algorithm
Power purchase data.
With reference to first aspect, an embodiment of the present invention provides the first possible embodiments of first aspect, wherein institute
It states and establishes object function, make the weighted value minimum of the power purchase total cost and Trading risk value in the object function, specifically include：
According to power purchase quantity, preset time outsourcing outside the default implementation number of days of power purchase, predeterminable area power purchase price, predeterminable area
Electricity is calculated, and preset time outsourcing electricity charge use is obtained；
It is calculated, is obtained in predeterminable area with preset time purchase of electricity according to preset time power purchase price in predeterminable area
Preset time power purchase expense；
It is calculated according to spot market electricity price desired value, spot market purchase of electricity desired value, obtains spot market power purchase
Expense；
According to Risk rated ratio coefficient, the historical data of Conditional Lyapunov ExponentP CVaR, sample data and power purchase penalty values into
Row calculates, and obtains Trading risk value；
Establish object function, so that the preset time outsourcing electricity charge is used, preset time power purchase expense in the predeterminable area,
The weighted value of the spot market power purchase expense and the Trading risk value is minimum.
With reference to first aspect, an embodiment of the present invention provides second of possible embodiments of first aspect, wherein institute
State the difference that power purchase penalty values are practical power purchase expense and desired power purchase expense.
With reference to first aspect, an embodiment of the present invention provides the third possible embodiments of first aspect, wherein institute
It states and establishes power purchase constraints model, specifically include：
Multiple constraints equatioies are established according to the quantity of electricity coupled wave equation of electric quantity balancing, power purchase；
According to peak regulation value-at-risk, thermoelectricity generated energy and its upper limit and lower limit, thermoelectricity power generation work(under peak load and paddy lotus state
Rate and its upper limit and lower limit, predeterminable area outsourcing electric unit power, power purchase marketing contact line transmission capacity, establish multiple constraint items
Part inequality；
According to the multiple constraints equation and the multiple constraints inequality, power purchase constraints mould is established
Type.
With reference to first aspect, an embodiment of the present invention provides the 4th kind of possible embodiments of first aspect, wherein institute
It states and the object function is based on according to the power purchase constraints model, calculated by particle cluster algorithm, obtain power purchase number
According to specifically including：
A inputs the object function and the preset data in the power purchase constraints model, and initializes particle rapidity
With position；
B is based on the object function according to the preset data and calculates power purchase total cost and Trading risk value, obtains particle
Fitness value；
C, is updated the particle rapidity and position according to the particle fitness value and iteration；
D judges whether the value of the particle rapidity and position meets power purchase constraint according to the power purchase constraints model
Condition；If not, thening follow the steps b to step d；If so, executing step e；
Multiple particle fitness values are compared, obtain comparing result by e；
F determines intended particle fitness value according to the comparing result from multiple particle fitness values；
G determines intended particle speed and position according to the intended particle fitness value；
H obtains power purchase data according to the intended particle speed and position.
With reference to first aspect, an embodiment of the present invention provides the 5th kind of possible embodiments of first aspect, wherein institute
It states and power purchase data is obtained according to the intended particle speed and position, further include before：
g1：Judge whether the intended particle speed reaches the iteration upper limit with position, or judges the intended particle speed
Whether it is more than default accuracy value with the precision of position；If all no, b is thened follow the steps to step g1；If it is therein at least
One is to then follow the steps h.
With reference to first aspect, an embodiment of the present invention provides the 6th kind of possible embodiments of first aspect, wherein institute
Stating preset data includes：Preset time power load demand, peak load power, paddy lotus power, shows preset time prediction load curve
Goods market price forecasts value, spot-market price prediction standard be poor, thermoelectricity Generation Bidding in Electricity Market, peak load and paddy lotus state in predeterminable area
Peak regulation gets at least one of limit value, preset time outsourcing electricity price lattice, interconnection transmission capacity, Risk rated ratio coefficient.
Second aspect, the embodiment of the present invention also provide a kind of power purchase scheme optimization device, including：
Function establishes module, for establishing object function, makes power purchase total cost and Trading risk in the object function
The weighted value of value is minimum, wherein the power purchase total cost includes：Preset time in preset time outsourcing electricity charge use, predeterminable area
Power purchase expense and spot market power purchase expense；
Model building module, for establishing power purchase constraints model；
Computing module passes through particle cluster algorithm for being based on the object function according to the power purchase constraints model
It is calculated, obtains power purchase data.
The third aspect, the embodiment of the present invention also provide a kind of electronic equipment, including memory, processor, the memory
In be stored with the computer program that can be run on the processor, the processor realized when executing the computer program with
And the step of method as described in relation to the first aspect.
Fourth aspect, the embodiment of the present invention also provide a kind of meter for the non-volatile program code that can perform with processor
Calculation machine readable medium, said program code make the method for the processor execution as described in relation to the first aspect.
Technical solution provided in an embodiment of the present invention brings following advantageous effect：Power purchase side provided in an embodiment of the present invention
In case optimization method, device and electronic equipment, power purchase scheme optimization method includes：First, object function is established, target letter is made
The weighted value of power purchase total cost in number and Trading risk value is minimum, wherein power purchase total cost includes：The preset time outsourcing electricity charge
With, preset time power purchase expense and spot market power purchase expense, furthermore, power purchase constraints model is established, then, according to purchase
Electric constraints model is based on object function, is calculated to obtain power purchase data by particle cluster algorithm, pre- by calculating
If time outsourcing electricity charge use, preset time power purchase expense, spot market power purchase expense and Trading risk value etc., particle is recycled
Group's algorithm calculates power purchase data, realizes and considers the preset times such as spot market environment, monthly and intersect shadow with spot market
Power purchase strategy under ringing, to adapt to the variation of Vehicles Collected from Market environment, so as under the environment of spot market, consider stock and the moon
The relationship for spending market, establishes provincial power network monthly electricity purchasing stochastic model, obtained monthly electricity purchasing plan and moon quantity division side
Case, realize the monthly market of stock, inside the province to the optimization of inter-provincial monthly electricity purchasing plan and corresponding quantity division scheme etc., moreover,
The weighted value minimum for making the power purchase total cost and Trading risk value in object function by the object function of foundation, can reach
While power purchase cost minimization target, Trading risk minimum is realized as far as possible and wind-powered electricity generation is received and maximized, makes monthly electricity purchasing
Optimum results fining, operability are stronger, mainly consider to solving current power purchase strategy existing in the prior art
Market is excessively single, can not adapt to the technical issues of continuous variation of Vehicles Collected from Market environment is with development.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that understand through the implementation of the invention.The purpose of the present invention and other advantages are in specification and attached drawing
Specifically noted structure is realized and is obtained.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate
Appended attached drawing, is described in detail below.
Description of the drawings
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described, it should be apparent that, in being described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, other drawings may also be obtained based on these drawings.
Fig. 1 shows the flow chart for the power purchase scheme optimization method that the embodiment of the present invention one is provided；
Fig. 2 shows the flow charts for the power purchase scheme optimization method that the embodiment of the present invention two is provided；
Fig. 3 shows another flow chart for the power purchase scheme optimization method that the embodiment of the present invention two is provided；
Fig. 4 shows a kind of structural schematic diagram for power purchase scheme optimization device that the embodiment of the present invention three is provided；
Fig. 5 shows the structural schematic diagram for a kind of electronic equipment that the embodiment of the present invention four is provided.
Icon：3- power purchase scheme optimization devices；31- functions establish module；32- model building modules；33- computing modules；
4- electronic equipments；41- memories；42- processors；43- buses；44- communication interfaces.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Lower obtained every other embodiment, shall fall within the protection scope of the present invention.
Currently, the market that power purchase strategy mainly considers is excessively single, can not adapt to the continuous variation of Vehicles Collected from Market environment with
Development is based on this, and a kind of power purchase scheme optimization method, apparatus provided in an embodiment of the present invention and electronic equipment can solve
The market that current power purchase strategy existing in the prior art mainly considers is excessively single, can not adapt to the continuous of Vehicles Collected from Market environment
The technical issues of variation is with development.
For ease of understanding the present embodiment, first to a kind of power purchase scheme optimization side disclosed in the embodiment of the present invention
Method, device and electronic equipment describe in detail.
Embodiment one：
A kind of power purchase scheme optimization method provided in an embodiment of the present invention, as shown in Figure 1, this method includes：
S11：Object function is established, the weighted value minimum of the power purchase total cost and Trading risk value in object function is made,
In, power purchase total cost includes：Preset time outsourcing electricity charge use, preset time power purchase expense and spot market power purchase expense.
In practical applications, build with inside the province it is monthly, from stock with the total power purchase expense and Trading risk of outer power purchase weight most
The small object function for target.
S12：Establish power purchase constraints model.
Specifically, according to multiple constraints equatioies and multiple constraints inequality, power purchase constraints model is established.
Wherein, structure equality constraint includes each outer power purchase quantity of electricity coupled wave equation and electric quantity balancing equation, and inequality constraints includes peak
Lotus and the peak regulation chance constraint under paddy lotus state, the constraint of thermoelectricity electricity bound, the constraint of thermal power output bound, outsourcing electric unit
Power constraint, the inter-provincial interconnection transmission capacity constraint in outer power purchase market.
S13：It is based on object function according to power purchase constraints model, is calculated by particle cluster algorithm, obtains power purchase
Data.
It is finally obtained most with the optimal power purchase scheme of PSO Algorithm as the preferred embodiment of the present embodiment
The power purchase data of good power purchase scheme.
For the prior art, under Power Market, control Trading risk is while reducing power purchase expense
Provincial power network economic benefit is realized basic.Monthly electricity purchasing plan has accounted for 80% or more of transaction total amount.Therefore, monthly electricity purchasing
The research of plan is of great significance to the realization of power grid operations objective.In addition, pilot is just gradually carried out in spot market in China
Work, the market risk is larger, and going out the larger wind-powered electricity generation of fluctuation, also positive fast development, the reverse property of resource and power load distributing more make
It is more frequent to obtain area's transaction transprovincially.Therefore, the intension of current power purchase decision is more abundant, and optimization aim is also from economic benefit
It is main to be transformed into safety, economic and environmental benefit coordination.What power purchase strategy was mainly studied at present is that the power purchase of single market is asked
Topic, the rarely seen monthly electricity purchasing strategy for considering spot market, can not adapt to the needs of current in stock market development.
By considering under the background of spot market, preset times and the power purchase plan under the cross influence of spot market such as monthly
Slightly, to adapt to the variation of Vehicles Collected from Market environment.Specifically, power purchase scheme optimization method provided in this embodiment may be one kind
Meter and spot market risk the monthly electricity purchasing method of provincial power network containing wind-powered electricity generation, by this method can under the environment of spot market,
Consider stock and monthly market relationship, establish provincial power network monthly electricity purchasing stochastic model, obtained monthly electricity purchasing plan with
Month quantity division scheme, realize the monthly market of stock, inside the province to inter-provincial monthly electricity purchasing plan and corresponding quantity division scheme etc.
Optimization, while reaching power purchase cost minimization target, realize as far as possible Trading risk minimum and wind-powered electricity generation receive it is maximum
Change, keeps the fining of monthly electricity purchasing optimum results, operability stronger.
Embodiment two：
A kind of power purchase scheme optimization method provided in an embodiment of the present invention, as shown in Fig. 2, this method includes：
S21：According to power purchase quantity, preset time outside the default implementation number of days of power purchase, predeterminable area power purchase price, predeterminable area
Outer purchase of electricity is calculated, and preset time outsourcing electricity charge use is obtained.
The present embodiment is one monthly with the preset time of power purchase, and the predeterminable area of power purchase is to be said for provincial region
Bright, therefore, the preset time outsourcing electricity charge are with the be outside one's consideration calculation formula of power purchase expense of front-month：
Wherein, FoutIt is used for the monthly outsourcing electricity charge, D is that Transaction algorithm implements moon number of days, Pout,iTo save power purchase price, N from i
Quantity is saved for sale of electricity；Wout,tFor monthly outer purchase of electricity the t days divide day electricity.
S22：It is calculated with preset time purchase of electricity according to preset time power purchase price in predeterminable area, obtains preset areas
Preset time power purchase expense in domain.
It should be noted that preset time power purchase expense is that the calculation formula of power purchase expense inside the province is in predeterminable area：
Wherein, FinFor power purchase expense inside the province, PcFor thermoelectricity monthly electricity purchasing price inside the province；K is load condition serial number, when k takes
Peak, flat, paddy three state are corresponded to when 1,2,3 respectively；Whct.kFor the thermoelectricity moon purchase of electricity t days k periods decomposition electricity；Pr.t.k.m
For the t days period spot markets k electricity price desired values；Wr.t.k.mIt it is the t days k periods of thermoelectricity in spot market purchase of electricity desired value.
S23：It is calculated according to spot market electricity price desired value, spot market purchase of electricity desired value, obtains spot market
Power purchase expense.
S24：It is lost according to Risk rated ratio coefficient, the historical data of Conditional Lyapunov ExponentP CVaR, sample data and power purchase
Value is calculated, and Trading risk value is obtained.
In the present embodiment, power purchase penalty values are the difference of practical power purchase expense and desired power purchase expense.Preferably as one
Scheme, using the form simulation electricity price and wind-powered electricity generation historical data of random sampling, the approximate calculation Trading risk in a manner of numerical integration,
Formula is as follows：
Wherein, FβFor the Trading risk under confidence level β, and Zk.t.n=[f (x, yk.t.n)-αt.k]+, wherein m be for
Calculate the historical data number of CVaR；N is the serial number of sample data；f(X,yk.t.n) be power purchase lose, i.e., practical power purchase expense and
It is expected that the difference of power purchase expense.
S25：Object function is established, makes preset time outsourcing electricity charge use, preset time power purchase expense, stock in predeterminable area
Market power purchase expense and the weighted value of Trading risk value are minimum.
As a preferred embodiment, plan as a whole spot market in monthly market, with monthly, total with outer power purchase from stock inside the province
Power purchase expense weights minimum target with Trading risk, and formula is specific as follows：
F=min (Fout+Fin+λFβ)
Wherein, FoutIt is used for the monthly outsourcing electricity charge, FinFor power purchase expense inside the province, it is expected by the power purchase expense of the moon inside the province and stock
Power purchase expense forms；FβFor the Trading risk under confidence level β；λ is Risk rated ratio coefficient.
S26：Multiple constraints equatioies are established according to the quantity of electricity coupled wave equation of electric quantity balancing, power purchase.
For the equation of electric quantity balancing, Ke Yiwei：
Wload.t.k=Whc.t.k+Wout.t.k+Wfct.k
Wherein, Wload.t.kFor the t days k period power loads；Wout.t.kIt is the monthly electricity of outer power purchase in the t days k periods
Decompose electricity.
It should be noted that for each outer power purchase quantity of electricity coupled wave equation, Ke Yiwei：
S27：According to peak regulation value-at-risk, thermoelectricity generated energy and its upper limit and lower limit, thermoelectricity hair under peak load and paddy lotus state
Electrical power and its upper limit and lower limit, predeterminable area outsourcing electric unit power, power purchase marketing contact line transmission capacity, establish it is multiple about
Beam conditional inquality.
For the inequality of the peak regulation chance constraint under peak load and paddy lotus state, Ke Yiwei：
Wherein, Pr{ } is probability operator；N1、N2Respectively wind-powered electricity generation and thermoelectricity generate electricity unit inside the province；Pd.t.max、Pd.t.minRespectively
For the t days maximum, minimum loads；Ph.i、Pf.iRespectively i-th of thermal power generation unit, wind-power electricity generation specific power random value；
Pout.iIt contributes for i-th of outer power purchase；α1、α2Respectively peak regulation risk level value under peak load and Gu He states.
For the inequality of thermoelectricity electricity bound constraint, Ke Yiwei：
Wh.max≤Wh≤Wh.min
Wherein, WhFor thermoelectricity gross generation；Wh.max、Wh.minRespectively thermoelectricity maximum, minimum generated energy.
It should be noted that the inequality of thermal power output bound constraint beam, Ke Yiwei：
Ph.max≤Ph≤Ph.min
Wherein, PhFor the total generated output of thermoelectricity；Ph.max、Ph.minRespectively thermoelectricity maximum, minimum generated output.
The inequality of outsourcing electric unit power constraint, Ke Yiwei：
0≤Pout.i.k≤Pout.i.k.max
Wherein, Pout.i.kFor from i power purchase kth time period power outside the province；Pout.i.k.maxFor its maximum output.
The outer inter-provincial interconnection transmission capacity in power purchase market constrains inequality, Ke Yiwei：
Pl.min≤Pl≤Pl.max
Wherein, PlFor the transmitted power of inter-provincial interconnection l；Pl.max、Pl.minRespectively inter-provincial interconnection l transmitted powers are most
Greatly, minimum value.
S28：According to multiple constraints equatioies and multiple constraints inequality, power purchase constraints model is established.
S29：Object function and the preset data in power purchase constraints model are inputted, and initializes particle rapidity and position
It sets.
In this step, preset data includes：Preset time power load demand, preset time prediction load curve, peak load
Power, paddy lotus power, spot-market price predicted value, spot-market price prediction standard be poor, thermoelectricity is sent a telegram in predeterminable area
Valence, peak load and paddy lotus state peak regulation are got in limit value, preset time outsourcing electricity price lattice, interconnection transmission capacity, Risk rated ratio coefficient
At least one.
In practical applications, the monthly power load demand of the whole province can be inputted, monthly prediction load curve, system peak load,
Paddy lotus power；Spot market usually, peak when, price predicted value when paddy, spot-market price prediction standard is poor；Wind-powered electricity generation is monthly inside the province
Power quantity predicting value at times, for thermoelectricity by electricity power group's quotation, quote situations, peak load and Gu He state peak regulations get over limit value α inside the province1、
α2；Outer power purchase is contributed in peak, flat, paddy period, outsourcing electricity price lattice price；Inter-provincial interconnection transmission capacity；Conditional Lyapunov ExponentP
Confidence level；The data such as Risk rated ratio coefficient.And population is initialized, each particle of random initializtion.
S30：It is based on object function according to preset data and calculates power purchase total cost and Trading risk value, obtains particle fitness
Value.
In step S30 to step S37, the process with the optimal power purchase scheme of PSO Algorithm is carried out.Specifically,
Power purchase total cost and risk are calculated first, power purchase expense and Trading risk value are calculated according to step S21 to step S25, as grain
Sub- fitness value.
S31：Particle rapidity and position are updated according to particle fitness value and iteration.
During power purchase scheme optimal with PSO Algorithm, to particle speed by way of update and iteration
Degree and position optimize.
S32：Judge whether the value of particle rapidity and position meets power purchase constraints according to power purchase constraints model.Such as
Fruit is no, thens follow the steps S30 to step S32.If so, executing step S33.
Preferably, determine whether to meet every constraints, specifically, according to step S26 to step S28 list it is each about
Whether beam condition, calculating meet constraint：As met, then continue step S33；It is such as unsatisfactory for, then returns to step S30 extremely
Step S32.
S33：Multiple particles fitness value is compared, comparing result is obtained.
S34：According to comparing result, intended particle fitness value is determined from multiple particles fitness value.
In step S33 to step S34, the newer process of individual optimal and globally optimal solution is carried out, specifically, to each
Its fitness value is compared by particle with its history adaptive optimal control angle value, if more preferably, most as history
It is excellent.
S35：Intended particle speed and position are determined according to intended particle fitness value.
S36：Judge whether intended particle speed and position reach the iteration upper limit, or judges intended particle speed and position
Whether precision is more than default accuracy value.If all no, S30 is thened follow the steps to step S36.If therein at least one
It is to then follow the steps S37.
Further, determining whether reach the iteration upper limit or precision meets the requirements, if reaching termination condition, i.e.,
The optimal solution or maximum iteration of enough accuracy, then hold after the step S37 that continues；Otherwise, S30 is returned to step to step
S36。
S37：Power purchase data are obtained according to intended particle speed and position.
Finally, the data of optimal power purchase scheme and quantity division scheme are obtained by step S21 to step S36.
As the another embodiment of the present embodiment, as shown in figure 3, a kind of power purchase scheme optimization method may be one
The monthly electricity purchasing method of provincial power network containing wind-powered electricity generation of kind meter and spot market risk, the specific steps of this method can be：First, it saves
Interior power purchase cost analysis can be carried out at the same time Trading risk analysis.Build later with inside the province it is monthly, from stock with total purchase of outer power purchase
The electricity charge object function that minimum target is weighted with Trading risk.Then constraints, including structure equality constraint, structure are built
Build inequality constraints, wherein structure equality constraint includes each outer power purchase quantity of electricity coupled wave equation and electric quantity balancing equation, is differed
Formula constraint includes peak load to be constrained with the peak regulation chance constraint under paddy lotus state, thermoelectricity electricity bound, thermal power output bound about
Beam, outsourcing electric unit power constraint, the inter-provincial interconnection transmission capacity constraint in outer power purchase market.Later, it proceeds by with particle
Group's algorithm solves the process of optimal power purchase scheme：First input data simultaneously initializes particle rapidity；Calculate power purchase total cost and risk；
Then, particle update is carried out；Determine whether to meet every constraints, if being unsatisfactory for, returns and re-start particle update, such as
Meet constraints then to carry out continuing following step；Then, update optimal solution is that individual is optimal and globally optimal solution updates, such as
Fruit be not optimal solution then return re-start particle update, best power purchase scheme is then obtained according to the optimal solution if it is optimal solution
With quantity division scheme.
Therefore, power purchase scheme optimization method considers the monthly cross influence with spot market, meter using spot market as background
And wind power output is uncertain, using the prediction of Conditional Value at Risk wind-powered electricity generation and spot market risk；By chance constraint reality
The out-of-limit risk control of existing peak-load regulating, establishes the monthly electricity purchasing stochastic model of the provincial power network containing wind-powered electricity generation under the environment of spot market,
The coordinated management of stock and monthly market is reached.
Embodiment three：
A kind of power purchase scheme optimization device provided in an embodiment of the present invention, as shown in figure 4, power purchase scheme optimization device 3 wraps
It includes：Function establishes module 31, model building module 32, computing module 33.
Specifically, function establishes module for establishing object function, make the power purchase total cost in object function and power purchase wind
The weighted value that is nearly worth is minimum, wherein power purchase total cost includes：Preset time is purchased in preset time outsourcing electricity charge use, predeterminable area
Electricity charge use and spot market power purchase expense.
As the preferred embodiment of the present embodiment, model building module is for establishing power purchase constraints model.
As the another embodiment of the present embodiment, computing module is used to be based on target according to power purchase constraints model
Function is calculated by particle cluster algorithm, obtains power purchase data.
Example IV：
A kind of electronic equipment provided in an embodiment of the present invention, as shown in figure 5, electronic equipment 4 includes memory 41, processor
42, the computer program that can be run on a processor is stored in memory, processor is realized above-mentioned when executing computer program
Embodiment one or apply example two offer method the step of.
Referring to Fig. 4, electronic equipment further includes：Bus 43 and communication interface 44, processor 42, communication interface 44 and memory
41 are connected by bus 43.Processor 42 is for executing the executable module stored in memory 41, such as computer program.
Wherein, memory 41 may include high-speed random access memory (RAM, Random Access Memory),
May further include nonvolatile memory (non-volatile memory), for example, at least a magnetic disk storage.By at least
One communication interface 44 (can be wired or wireless) realizes the communication between the system network element and at least one other network element
Connection can use internet, wide area network, local network, Metropolitan Area Network (MAN) etc..
Bus 43 can be isa bus, pci bus or eisa bus etc..It is total that bus can be divided into address bus, data
Line, controlling bus etc..For ease of indicating, only indicated with a four-headed arrow in Fig. 4, it is not intended that an only bus or one
The bus of type.
Wherein, memory 41 is for storing program, and processor 42 executes program after receiving and executing instruction, aforementioned
The method performed by device that the stream process that inventive embodiments any embodiment discloses defines can be applied in processor 42, or
Person is realized by processor 42.
Further, processor 42 may be a kind of IC chip, the processing capacity with signal.It was realizing
Each step of Cheng Zhong, the above method can pass through the integrated logic circuit of the hardware in processor 42 or the instruction of software form
It completes.Above-mentioned processor 42 can be general processor, including central processing unit (Central Processing Unit, letter
Claim CPU), network processing unit (Network Processor, abbreviation NP) etc..It can also be digital signal processor (Digital
Signal Processing, abbreviation DSP), application-specific integrated circuit (Application Specific Integrated
Circuit, abbreviation ASIC), ready-made programmable gate array (Field-Programmable Gate Array, abbreviation FPGA) or
Person other programmable logic device, discrete gate or transistor logic, discrete hardware components.It may be implemented or execute sheet
Disclosed each method, step and logic diagram in inventive embodiments.General processor can be microprocessor or the processing
Device can also be any conventional processor etc..The step of method in conjunction with disclosed in the embodiment of the present invention, can be embodied directly in
Hardware decoding processor executes completion, or in decoding processor hardware and software module combination execute completion.Software mould
Block can be located at random access memory, flash memory, read-only memory, programmable read only memory or electrically erasable programmable storage
In the storage medium of this fields such as device, register maturation.The storage medium is located at memory 41, and processor 42 reads memory 41
In information, in conjunction with its hardware complete the above method the step of.
Embodiment five：
It is provided in an embodiment of the present invention it is a kind of with processor can perform non-volatile program code it is computer-readable
The step of medium, program code makes processor execute above-described embodiment one or applies the method for the offer of example two.
Unless specifically stated otherwise, the opposite step of the component and step that otherwise illustrate in these embodiments, digital table
It is not limit the scope of the invention up to formula and numerical value.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description
It with the specific work process of device, can refer to corresponding processes in the foregoing method embodiment, details are not described herein.
In all examples being illustrated and described herein, any occurrence should be construed as merely illustrative, without
It is as limitation, therefore, other examples of exemplary embodiment can have different values.
It should be noted that：Similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent attached drawing in a attached drawing.
Flow chart and block diagram in attached drawing show the system, method and computer journey of multiple embodiments according to the present invention
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part for a part for one module, section or code of table, the module, section or code includes one or more uses
The executable instruction of the logic function as defined in realization.It should also be noted that in some implementations as replacements, being marked in box
The function of note can also occur in a different order than that indicated in the drawings.For example, two continuous boxes can essentially base
Originally it is performed in parallel, they can also be executed in the opposite order sometimes, this is depended on the functions involved.It is also noted that
It is the combination of each box in block diagram and or flow chart and the box in block diagram and or flow chart, can uses and execute rule
The dedicated hardware based system of fixed function or action is realized, or can use the group of specialized hardware and computer instruction
It closes to realize.
The computer-readable medium of the non-volatile program code provided in an embodiment of the present invention that can perform with processor,
The power purchase scheme optimization method, apparatus and electronic equipment technical characteristic having the same provided with above-described embodiment, so
Identical technical problem can be solved, identical technique effect is reached.
In addition, in the description of the embodiment of the present invention unless specifically defined or limited otherwise, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
Can also be electrical connection to be mechanical connection；It can be directly connected, can also indirectly connected through an intermediary, Ke Yishi
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood at this with concrete condition
Concrete meaning in invention.
In the description of the present invention, it should be noted that term "center", "upper", "lower", "left", "right", "vertical",
The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely to
Convenient for the description present invention and simplify description, do not indicate or imply the indicated device or element must have a particular orientation,
With specific azimuth configuration and operation, therefore it is not considered as limiting the invention.
The computer program product for the carry out power purchase scheme optimization method that the embodiment of the present invention is provided, including store place
The computer readable storage medium of the executable non-volatile program code of device is managed, the instruction that said program code includes can be used for
The method described in previous methods embodiment is executed, specific implementation can be found in embodiment of the method, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed systems, devices and methods, it can be with
It realizes by another way.The apparatus embodiments described above are merely exemplary, for example, the division of the unit,
Only a kind of division of logic function, formula that in actual implementation, there may be another division manner, in another example, multiple units or component can
To combine or be desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or beg for
The mutual coupling, direct-coupling or communication connection of opinion can be by some communication interfaces, device or unit it is indirect
Coupling or communication connection can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer read/write memory medium.Based on this understanding, technical scheme of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be expressed in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.
Finally it should be noted that：Embodiment described above, only specific implementation mode of the invention, to illustrate the present invention
Technical solution, rather than its limitations, scope of protection of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hair
It is bright to be described in detail, it will be understood by those of ordinary skill in the art that：Any one skilled in the art
In the technical scope disclosed by the present invention, it can still modify to the technical solution recorded in previous embodiment or can be light
It is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make
The essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover the protection in the present invention
Within the scope of.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of power purchase scheme optimization method, which is characterized in that including：
Object function is established, makes the weighted value minimum of the power purchase total cost and Trading risk value in the object function, wherein institute
Stating power purchase total cost includes：Preset time outsourcing electricity charge use, preset time power purchase expense and spot market power purchase expense；
Establish power purchase constraints model；
It is based on the object function according to the power purchase constraints model, is calculated by particle cluster algorithm, obtains power purchase
Data.
2. power purchase scheme optimization method according to claim 1, which is characterized in that it is described to establish object function, make described
Power purchase total cost and the weighted value of Trading risk value in object function is minimum, specifically includes：
Implement number of days, predeterminable area power purchase price, power purchase quantity outside predeterminable area, purchase of electricity outside preset time according to power purchase is default
It is calculated, obtains preset time outsourcing electricity charge use；
It is calculated with preset time purchase of electricity according to preset time power purchase price in predeterminable area, obtains presetting in predeterminable area
Time power purchase expense；
It is calculated according to spot market electricity price desired value, spot market purchase of electricity desired value, obtains spot market power purchase expense；
It is counted according to Risk rated ratio coefficient, the historical data of Conditional Lyapunov ExponentP CVaR, sample data and power purchase penalty values
It calculates, obtains Trading risk value；
Object function is established, so that the preset time outsourcing electricity charge is used, is preset time power purchase expense in the predeterminable area, described
Spot market power purchase expense and the weighted value of the Trading risk value are minimum.
3. power purchase scheme optimization method according to claim 2, which is characterized in that the power purchase penalty values are practical power purchase
The difference of expense and desired power purchase expense.
4. power purchase scheme optimization method according to claim 1, which is characterized in that described to establish power purchase constraints mould
Type specifically includes：
Multiple constraints equatioies are established according to the quantity of electricity coupled wave equation of electric quantity balancing, power purchase；
According under peak load and paddy lotus state peak regulation value-at-risk, thermoelectricity generated energy and its upper limit and lower limit, thermoelectricity generated output and
Its upper limit and lower limit, predeterminable area outsourcing electric unit power, power purchase marketing contact line transmission capacity, establish multiple constraintss not
Equation；
According to the multiple constraints equation and the multiple constraints inequality, power purchase constraints model is established.
5. power purchase scheme optimization method according to claim 1, which is characterized in that described according to the power purchase constraints
Model is based on the object function, is calculated by particle cluster algorithm, obtains power purchase data, specifically include：
A inputs the object function and the preset data in the power purchase constraints model, and initializes particle rapidity and position
It sets；
B is based on the object function according to the preset data and calculates power purchase total cost and Trading risk value, obtains particle adaptation
Angle value；
C, is updated the particle rapidity and position according to the particle fitness value and iteration；
D judges whether the value of the particle rapidity and position meets power purchase constraints according to the power purchase constraints model；
If not, thening follow the steps b to step d；If so, executing step e；
Multiple particle fitness values are compared, obtain comparing result by e；
F determines intended particle fitness value according to the comparing result from multiple particle fitness values；
G determines intended particle speed and position according to the intended particle fitness value；
H obtains power purchase data according to the intended particle speed and position.
6. power purchase scheme optimization method according to claim 5, which is characterized in that described according to the intended particle speed
Power purchase data are obtained with position, further include before：
g1：Judge whether the intended particle speed reaches the iteration upper limit with position, or judges the intended particle speed and position
Whether the precision set is more than default accuracy value；If all no, b is thened follow the steps to step g1；If therein at least one
It is to then follow the steps h.
7. power purchase scheme optimization method according to claim 5, which is characterized in that the preset data includes：When default
Between power load demand, preset time prediction load curve, peak load power, paddy lotus power, spot-market price predicted value, stock
Thermoelectricity Generation Bidding in Electricity Market, peak load and paddy lotus state peak regulation get over limit value, outside preset time in market price forecasts standard deviation, predeterminable area
At least one of power purchase price, interconnection transmission capacity, Risk rated ratio coefficient.
8. a kind of power purchase scheme optimization device, which is characterized in that including：
Function establishes module, for establishing object function, makes the power purchase total cost in the object function and Trading risk value
Weighted value is minimum, wherein the power purchase total cost includes：Preset time power purchase in preset time outsourcing electricity charge use, predeterminable area
Expense and spot market power purchase expense；
Model building module, for establishing power purchase constraints model；
Computing module is carried out for being based on the object function according to the power purchase constraints model by particle cluster algorithm
It calculates, obtains power purchase data.
9. a kind of electronic equipment, including memory, processor, be stored in the memory to run on the processor
Computer program, which is characterized in that the processor realizes that the claims 1 to 7 are any when executing the computer program
Described in method the step of.
10. a kind of computer-readable medium for the non-volatile program code that can perform with processor, which is characterized in that described
Program code makes the processor execute described any the method for claim 1 to 7.
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