CN110135631A

CN110135631A - Electrical integrated energy system dispatching method based on information gap decision theory

Info

Publication number: CN110135631A
Application number: CN201910347244.XA
Authority: CN
Inventors: 马丽叶; 陆肖宇
Original assignee: Yanshan University
Current assignee: Shenmu Meitian Green Carbon Management Co ltd
Priority date: 2019-04-26
Filing date: 2019-04-26
Publication date: 2019-08-16
Anticipated expiration: 2039-04-26
Also published as: CN110135631B

Abstract

The invention discloses the electrical integrated energy system dispatching method based on information gap decision theory, content includes: to establish information gap decision-theoretic model；Optimum Economic benefit moving model after establishing wind-powered electricity generation-pump-storage generator joint；Consider that wind power output is uncertain, establishes the wind based on information gap decision theory and store Unit erriger scheduling model；Establish the electrical integrated energy system scheduling model of deterministic type；Consider the uncertainty of load, establishes the electrical integrated energy system scheduling model based on information gap decision theory；Model is solved in conjunction with bacterial community chemotaxis algorithm；Solving result is sent to energy scheduling center, energy scheduling center is scheduled energy resource system according to solving result.Scheduling strategy proposed by the present invention can efficiently reduce intermittence and fluctuation, the raising wind electricity digestion amount and the electrical integrated energy system economic benefit of increase of wind-powered electricity generation, and different scheduling strategies is provided for the policymaker of different risk partialities.

Description

Electrical integrated energy system dispatching method based on information gap decision theory

Technical field

The present invention relates to energy field more particularly to a kind of electrical integrated energy systems based on information gap decision theory Dispatching method.

Background technique

Since conventional fossil fuel is non-renewable, the utilization rate for improving renewable energy becomes critical issue, and improves electricity The key of Force system renewable energy high proportion permeability is the operational flexibility for increasing energy-consuming and surveying, and is thus proposed " comprehensive This concept of energy resource system ".Electric-gas integrated energy system is the most important thing, electric system and natural gas in integrated energy system System is two energy resource systems runed independently of each other.But since gas turbine has rapid starting/stopping characteristic and quick load adjustment Characteristic causes gas consumption worldwide to increase rapidly.The year two thousand thirty is expected, fuel gas generation amount increases by 230%, phase The installation quantity for the gas turbine answered will quickly increase, and further deepen the degree of coupling of electric system and natural gas system.With Therebetween degree of coupling be continuously improved, economy will interact with reliability, therefore tradition is based on single energy resource system Independent analytical methods be not suitable for electric power-natural gas energy resource system of close coupling, there is an urgent need to from electric-gas comprehensive energy system System angle is set out, and the coordination optimization method of operation of meter and the two operation constraint is sought.

Electric-gas integrated energy system traditionally relies solely on gas turbine as double net coupling channels, energy stream It moves as single direction；Electricity turns the appearance of gas (power-to-gas, P2G) device so that the energy flow of the double nets of electricity, gas becomes double To the double net systems couplings of reinforcing, the two coupling passes through gas turbine (as G2P equipment) and the realization of P2G system.Gas turbine by Natural gas network gas supply, is both the load of gas net and the power supply of power grid；P2G equipment is both the load and gas net of power grid Gas source.P2G technology may be implemented energy from electric system to hydrogen, natural gas system conversion and realize the indirect big rule of electric energy Mould stores for a long time, has expanded the thinking of new energy consumption.The methane of P2G synthesis is similar to the property of common natural gas, thus It can inject in natural-gas transfer pipeline and storage network, the uncertainty for reducing natural gas load demand gives conduit running bring Risk reduces the use of fossil energy, helps to realize multi-energy system and mutually merges.

There are many uncertain factors, such as load fluctuation, generation of electricity by new energy to contribute when electric-gas integrated energy system is run Fluctuation etc..These factors influence the normal table operation of system.Wind-force is intermittent energy source, wind power output have fluctuation and with Machine is incorporated into the power networks and brings new challenge to system call.Therefore, electrical integrated energy system scheduling strategy is being formulated When, it is necessary to consider the uncertainty of wind power output and load.

In recent years, as more and more large and medium-sized wind power plant puts into operation in succession in China, energy storage device has become wind The crucial matching component of force generating system.Wherein, energy storage is drawn water as a kind of mode for storing electric energy, by establishing the storage that draws water It is also the world using most common physics energy storage mode that energy power station, which has become most mature,.And hydroenergy storage station is a kind of energy storage appearance The effects of measuring biggish equipment, capable of playing peak load shifting, system reserve, the technical application in power grid are very extensive.And it takes out Water storage station has the characteristics that capacity greatly and adjusting is quick, can not only improve well in conjunction with changeable wind power plant of contributing The economy and stability of the access Operation of Electric Systems containing large-scale wind power, and renewable energy can be made full use of.

Processing wind power output and the method for negative rules mainly have stochastic programming and robust optimization etc. at present.But with Machine planning, robust Optimal methods have some limitations, stochastic programming need uncertain parameter exact probability be distributed or Need to generate a large amount of scenes, calculation amount is larger, and the feasible solution that robust Optimal methods acquire is overly conservative, and economy is bad.Information Gap decision theory (Information gap decision theory, IGDT) is a kind of probabilistic new method of processing, This method can preferably describe uncertain information, while different scheduling plans can be provided for the policymaker of different risk partialities Slightly, the problem of overcoming computationally intensive and conservative decision provides new approaches for processing uncertain factor.IGDT exists at present The Unit Combination optimization of electric system, idle and voltage optimization etc. also have certain application.But in electrical comprehensive energy Using less, research IGDT having uncertain factor in processing economic load dispatching in the application of this aspect systematic economy scheduling aspect Significance.

In summary, it is necessary to electrical integrated energy system dispatching method of the invention based on information gap decision theory, first To wind-powered electricity generation and pump-storage generator combined optimization, guarantee that wind stores Unit erriger maximum economic benefit, then combine fired power generating unit and day Right gas network establishes electrical integrated energy system scheduling model.Both it increased the online power of wind-powered electricity generation, reduced its grid-connected wave Dynamic property and intermittence, and increase the economic benefit of electrical integrated energy system while wind power output and load has been effectively treated Uncertainty is steady much before coordinating the operation of whole system relatively.

Summary of the invention

It is an object of that present invention to provide a kind of electrical integrated energy system dispatching method based on information gap decision theory, This method has the characteristics that easy, Consideration comprehensively and practicability is high.To achieve the above object, the present invention be by with What lower technical solution was realized, content includes the following steps:

Step 1 establishes information gap decision theory (IGDT) model；

Step 2 establishes the Optimum Economic benefit moving model after wind-powered electricity generation-pump-storage generator joint；

Step 3, according to the Optimum Economic benefit after information gap decision-theoretic model and wind-powered electricity generation-pump-storage generator joint Moving model considers that wind power output is uncertain, establishes the wind based on information gap decision theory and stores Unit erriger scheduling model, Detailed process is as follows:

Firstly, establishing the uncertain collection model of wind power output:

In formula: P_w(t, k) is output of wind electric field predicted value；For output of wind electric field actual value；α_wTo fluctuate width Degree, value are directly related with prediction error.

When not considering uncertainty, i.e. α_wWhen=0, it is deterministic type scheduling model that above-mentioned wind, which stores Unit erriger scheduling model, Economic benefit at this time, referred to as basic benefit can be calculated, F is denoted as₀。

Then, it according to the uncertain collection model of wind power output, establishes the wind based on information gap decision theory and stores Unit erriger Scheduling model is specifically expressed as follows:

Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Objective function are as follows: max α_w；

Constraint condition are as follows:And the step Institute's Prescribed Properties of Optimum Economic benefit moving model in 2 after wind-powered electricity generation-pump-storage generator joint.

Wherein, F₀For basic benefit；α_wFor fluctuating range；F is wind-powered electricity generation online economic benefit；For robust Model economy Benefit straggling parameter；For output of wind electric field actual value；U(α_w, P_w(t, k) is the uncertain collection of wind power output；

Establish the IGDT scheduling opportunity model that chance is sought under strategy:

Objective function are as follows: min α_w；

Wherein, α_wFor fluctuating range；For opportunity model economic benefit straggling parameter；For output of wind electric field Actual value；U(α_w, P_w(t, k) is the uncertain collection of wind power output；

Step 4 establishes the electrical integrated energy system scheduling model of deterministic type；

Step 5, according to information gap decision-theoretic model and the electrical integrated energy system scheduling model of deterministic type, consider negative The uncertainty of lotus establishes the electrical integrated energy system scheduling model based on information gap decision theory, and detailed process is as follows:

Firstly, establishing the uncertain collection model of workload demand:

In formula: U (α_L, P_{L, t}) it is the uncertain collection of workload demand；P_{L, t}For the predicted value of load；For the actual value of load； α_LFor fluctuating range, value is directly related with prediction error.

When not considering uncertainty, i.e. α_L, when=0, above-mentioned electrical integrated energy system scheduling model is deterministic type scheduling Model can calculate scheduling cost at this time, referred to as basic cost, be denoted as C₀。

Then, according to the uncertain collection model of workload demand, the electrical comprehensive energy based on information gap decision theory is established System call model, specific as follows:

Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Objective function are as follows: max α_L；

Constraint condition are as follows:And it is determined in the step 4 Institute's Prescribed Properties of the electrical integrated energy system scheduling model of type.

Wherein, α_LFor fluctuating range, C is the total operating cost of electrical integrated energy system,It is scheduled to for robust Model This straggling parameter；

Objective function are as follows: min α_L；

Wherein,Cost straggling parameter is dispatched for opportunity model；

Step 6 is solved in conjunction with model of the bacterial community chemotaxis algorithm to the step 3 and step 5, is obtained related Parameter, the parameter specifically include: the wind based on information gap decision theory stores two kinds of models of Unit erriger scheduling model Wind power output does not know radius α_w, economic benefit F and wind store Unit erriger and contribute situation, the electricity based on information gap decision theory The load of two kinds of models of gas integrated energy system scheduling model does not know radius α_L, cost C and generating set contribute situation；

The parameter that the step 6 solution obtains is sent to energy scheduling center, energy scheduling Central Radical by step 7 Energy resource system is scheduled according to the parameter.

Preferably, in the step 1, information gap decision-theoretic model is established, detailed process is as follows:

IGDT is a kind of Mathematics Optimization Method for the model containing uncertain parameter, and the model optimized using IGDT is as follows:

In formula: X is uncertain parameter；D is decision variable；B (X, d) is objective function；H (X, d), G (X, d) be equation and Inequality constraints.

Uncertain parameter X can be described as follows around the fluctuation of predicted value X:

In formula:Indicate the predicted value of uncertain parameter, α indicates the fluctuating range of uncertain parameter, α >=0； Indicate that the range of uncertain parameter X deviation predicted value is no more than

In uncertain environment, conservative policymaker, usually will not be really in order to guarantee the realization of a certain lowest desired target The unfavorable disturbance for determining parameter maximizes, and the policymaker to advance rashly is more to pursue uncertain possible extra returns.

The robust Model of IGDT is expressed as follows:

The opportunity model of IGDT is expressed as follows:

In formula: B_oIt is taken for XThe target function value of up-to-date style (1)；B_cFor the expected cost of robust Model；B_jFor opportunity model Expected cost；β_cFor the deviation factors of robust Model, expected cost is represented higher than B_oExtent of deviation；β_jFor opportunity model Deviation factors represent expected cost lower than B_oExtent of deviation；

For the function that given d, maxB (X, d) and minB (X, d) are about X, if the two can be obvious with the variation of X Property it is determining, then they embody form and can intuitively be indicated.

Formula (3) is robust Model (robustness model, RM), it indicates d pairs of decision value acquired under the model In Arbitrary PerturbationExpected cost can be guaranteed not higher than B_c。

Formula (4) is opportunity model (opportuneness model, OM), it indicates the decision for acquiring under the model Value d at least has oneSo that expected cost is not higher than B_o。

Preferably, the Optimum Economic benefit operation mould in the step 2, after establishing wind-powered electricity generation-pump-storage generator joint Type, detailed process is as follows:

Wind-powered electricity generation-water-storage Unit erriger Optimum Economic benefit objective function are as follows:

maxF (8)

In formula: F is wind-powered electricity generation online economic benefit；P_ws(t, k) is that t hours kth time period wind stores the grid-connected power of Unit erriger； P_p(t, k) is draw water power of the pump-storage generator in t hours kth time periods；C (t, k) is the online of t hours kth time periods Electricity price；C_i(t, k) is the electricity price of drawing water of t hours kth time periods；T is a cycle i.e. 24 hour；Number of segment when K is interior per hour That is 4 periods.

The constraint condition of wind storage Unit erriger Optimum Economic benefit:

(1) equality constraint:

X_t+Y_t=1 (13)

P_ws(t, k)=P_ws(t, k+1) (15)

In formula:Respectively wind stores Unit erriger kth under the state of drawing water and generating state, when k takes 1,2,3,4 The grid-connected power of section；X_tExpression unit was generating state, X at t hours when=1_tUnit was the shape that draws water at t hours when=0 State；Y_tExpression unit was generating state, Y at t hours when=0_tUnit was state of drawing water at t hours when=1；P_w(t, k) is T hours kth time period Wind turbines prediction powers；P_w.tFor the total prediction power of t hours Wind turbines；P_g(t, k) is to draw water Generated output of the accumulation of energy unit in t hours kth time periods；η_pFor the efficiency of drawing water of pump-storage generator；

Formula (15) indicates that wind stores Unit erriger and meets the grid-connected power relative smooth of joint that wind stores Unit erriger.

(2) inequality constraints condition:

1. the grid-connected power that wind stores Unit erriger constrains under the state of drawing water and generating state:

In formula:Indicate unit in t hours kth time period Wind turbines prediction power minimum values； Indicate unit in t hours kth time period Wind turbines prediction power maximum values；P_min(t, k), P_max(t, k) is t hours kth The minimum value and maximum value of the period wind storage grid-connected power of Unit erriger.

2. pump-storage generator power constraint under the state of drawing water and generating state:

0≤P_g(t, k)≤P_g.max(t, k) (18)

0≤P_p(t, k)≤P_p.max(t, k) (19)

In formula: P_p.max(t, k) and P_g.max(t, k) is respectively draw water power and the generated output upper limit.

3. under Power Market, for grid-connected wind-powered electricity generation-water-storage combining operation mode, in addition to reduce to being Outside the influence of system, the gene-ration revenue problem for considering itself is also needed, influence of the wind-electricity integration to grid stability is considered, sets wind Electricity-grid-connected the power constraint of water-storage Unit erriger:

P_min(t, k)≤P_ws(t, k)≤P_max(t, k) (20)

In formula: P_min(t, k), P_max(t, k) be t hour kth time period wind store the minimum value of the grid-connected power of Unit erriger with Maximum value.

4. wind storage Unit erriger draws water, power and Fa Shen power are constrained each other:

In formula: η_gFor the generating efficiency of pump-storage generator.

5. the grid-connected constraint of Wind turbines prediction power:

P_d.min(t, k)≤P_w(t, k)≤P_d.max(t, k) (22)

Work as X_tP_w(t, k) >=P_d.maxWhen (t, k), indicate are as follows:

X_tP_w(t, k)=P_d.max(t, k) (23)

In formula: P_d.min(t, k), P_d.max(t, k) is the minimum value and most of kth time period Wind turbines installed capacity in t hours Big value.

6. pump-storage generator start-stop time constrains:

Research of the invention is average using the hour prediction power of wind-powered electricity generation prediction power and a cycle in a certain hour The comparison of value determines the start-stop time of pump-storage generator, i.e., start-stop time draws water/generating state with pump-storage generator Variation and change, the start-stop time of pump-storage generator is constrained, is indicated are as follows:

In formula: M is the start-stop time of pump-storage generator；For the number for the state of drawing water；For of generating state Number.

Preferably, in the step 4, the electrical integrated energy system scheduling model of deterministic type is established, was implemented Journey is as follows:

1) objective function:

Target is that the total operating cost C of electrical integrated energy system is minimum, including fired power generating unit cost of electricity-generating, wind store joint Unit runs cost of electricity-generating and gas source power output cost.Therefore, objective function is shown below:

In formula: t is scheduling slot；T is to dispatch total period；Ω_GC、Ω_NThe respectively set of coal unit, gas source；P_{GC, i, t} For i-th of coal unit the t period active power output；a_i, b_i, c_iFor the cost of electricity-generating coefficient of i-th of coal unit；g_iIt is i-th The natural gas purchase cost coefficient of a gas source；F_{N, i, t}For i-th of gas source the t period output gas flow amount；K_cCombination machine is stored for wind The cost of electricity-generating coefficient of group, P_{Ws, t}The grid-connected power of Unit erriger is stored for t hours wind.

2) constraint condition:

The constraint condition of electrical integrated energy system Optimized Operation, comprising: electric power networks constraint, natural gas network constraint with And the coupling constraint of the two network.

(1) electric power networks constrain:

Electric power networks constraint uses conventional constraint, including the constraint of power-balance constraint, balance nodes phase angle, generating set, It include coal unit and Gas Generator Set units limits, node voltage constraint, line power constraint and generating set Climing constant, Using Cartesian form, it is expressed as follows:

P_{G, i, t}+P_{Ws, t}-P_{P2G, i, t}-P_{L, i, t}-P_{I, t}=0 (29)

Q_{G, i, t}-Q_L,_{I, t}-Q_{I, t}=0 (30)

tanθ_bal.t-f_{Bal, t}/e_{Bal, t}=0 (31)

P_{G, i, min}≤P_{G, i, t}≤P_{G, i, max} (32)

Q_{G, i, min}≤Q_{G, i, t}≤Q_{G, i, max} (33)

V² _{I, min}≤e_{I, t} ²+f_{I, t} ²≤V² _{I, max} (34)

0≤P_{Ij, t} ²+Q_{Ij, t} ²≤S² _{Ij, max} (35)

P_{G, i, t}-P_{G, i, t-1}≤R_{U, i} (36)

P_{G, j, t-1}-P_{G, i, t}≤R_{D, i} (37)

In formula: P_{I, t}、Q_{I, t}The respectively active and reactive power of t moment node i；P_{G, i, t}For having for t moment generating set i Function power output；Q_{G, i, t}For the idle power output of t moment generating set i；P_{L, i, t}For the burden with power of t moment node i；Q_{L, i, t}For t moment The load or burden without work of node i；P_{P2G, i, t}Electricity turns the active power output of device of air i when for t；θ_{Bal, t}For t moment balance nodes voltage phase angle； e_{Bal, t}、f_{Bal, t}The respectively real and imaginary parts of t moment balance nodes voltage；P_{G, i, max}、P_{G, i, min}And Q_{G, i, max}、Q_{G, i, min}Respectively For the active power output bound and idle power output bound of generating set i；e_{I, t}、f_{I, t}The respectively real part of t moment node i voltage And imaginary part；V_{I, max}、V_{I, min}Respectively node i voltage magnitude bound；P_{Ij, t}、Q_{Ij, t}Respectively active, the nothing of t moment route ij Function power；S_{Ij, max}For the upper limit of route ij apparent energy；R_{U, i}、R_{D, i}The upper limit that respectively generating set i climbs above and below.

(2) natural gas network constraint:

Natural gas network, which specifically includes that, provides the gas source point of natural gas, by the pipeline and use of natural gas transportation to load side The pressurizing point of the pressure loss in supplement energy transport.The multi-period dynamic process of present invention research, it is also necessary to which consideration has The air accumulator and pipe of store function deposit (linepack).

1. gas source point:

Gas source point injects natural gas to natural gas network, and the bound constraint representation of each gas source point supply flow is as follows:

Q_{N, j},_min≤Q_{N, j, t}≤Q_{N, j, max} (38)

In formula: Q_{N, j, t}For the natural gas supply flow of t moment gas source point j；Q_{N, j, max}、Q_{N, j, min}Respectively gas source point j's Natural gas supply flow upper and lower limit.

2. pipeline:

Natural gas line flow equation is related with pipe ends pressure and many physical characteristics of pipeline, has no general shape Formula, the gas flow under particular condition are usually described with nonlinear equation.Gas pipeline is insulated for ideal, considers that natural gas is double To flowing,

Its flow equation may be expressed as:

In formula:Indicate that t moment flows through the average flow rate of pipeline ij, wherein Qⁱⁿ _{Ij, t}、Q^out _{Ij, t} Respectively the head end natural gas filling inbound traffics of t moment pipeline ij and end natural gas output flow；C_ijFor with pipeline ij efficiency, temperature The related constant such as degree, length, internal diameter, compressibility factor；p_{I, t}、p_{J, t}Respectively t moment first and last node i, the pressure value of j.

Natural gas line flow equation (39) is only applicable to the network of high pressure turbulent flow, and node pressure value has bound constraint, It is expressed as follows:

p_{J, min}≤p_{J, t}≤p_{J, max} (40)

P in formula_{J, min}、p_{J, max}Respectively node j pressure value upper and lower limit.

3. pipe is deposited:

Due to the compressibility of natural gas, pipeline head end natural gas filling inbound traffics often with end natural gas output flow not Together, the gas discharge of first and last end difference just briefly stores in the duct, and referred to as pipe is deposited.Guan Cunke buffers natural gas network The fluctuation of gas load is the key factor for guaranteeing natural gas and reliably supplying.The average pressure and pipeline of Guan Cunyu pipe ends are joined Number is directly proportional, considers multi-period dynamic process, may be expressed as:

In formula: L_{In, t}Pipe for t moment pipeline ij is deposited；M_ijFor with pipeline ij length, radius, temperature and gas density, pressure The related constant such as the contracting factor；Indicate the average pressure of t moment pipeline ij.

4. air accumulator:

Load is reliably supplied in the storage of natural gas in natural gas network and network security stable operation is most important.? When biggish fluctuation occurs for natural gas network failure or gas load, it is natural that air accumulator can replace gas source point to provide to network Gas ensures that natural gas load is in liberal supply.Natural gas network air accumulator is limited in storage capacity and natural gas injection, output The limitation of flow, considers multi-period dynamic process, and constraint may be expressed as:

In formula: S_{S, j, t}For the memory capacity of t moment air accumulator j；The respectively natural gas of t moment air accumulator j Inject flow and output flow；S_{S, j, max}、S_{S, j, min}The respectively upper and lower limit of air accumulator j memory capacity； The respectively upper limit of air accumulator j natural gas filling inbound traffics and output flow.

5. compressor:

The pressure loss of the natural gas network as caused by frictional resistance, natural gas for reliable transmission natural gas and compensation A certain number of pressurizing points are needed to configure in network.The most important part of pressurizing point is the compressor for increasing gas pressure.It is false If the energy of compressor consumption derives from the natural gas by compressor, the load of natural gas network can be regarded as.Compressor The gas discharge of consumption is related with the flow and compression ratio that flow through compressor, can be expressed as follows:

In formula: Q_{Com, k, t}For the gas discharge of t moment compressor k consumption；H_{Com, k, t}For the energy of t moment compressor k consumption Amount；β_kFor the energy conversion factor of compressor k；B_kFor constant related with compressor k efficiency, temperature, heating value of natural gas； f_{Com, k, t}The gas discharge of compressor k is flowed through for t moment；Z_kIt is related with compressor k compressibility factor and heating value of natural gas normal Number；R_{K, max}、R_{K, min}The respectively upper and lower limit of compressor k compression ratio.

6. flow equilibrium:

Similar to the node power balance in electric power networks, each section in natural gas network can be obtained according to flow conservation law The flux balance equations of point indicate are as follows:

In formula: i ∈ j indicates all nodes being connected with node j；Q_{P2G, j, t}For t moment electricity turn gas j be converted to it is natural Throughput；Q_{GT, j, t}For the gas discharge of t moment gas turbine j consumption；Q_{Com, j, t}For the natural gas of t moment compressor j consumption Flow；Q_{L, j, t}For the natural gas load of t moment node j.

(3) coupling constraint of electric system and natural gas system:

Electrical integrated energy system is coupled to form by electric power networks and natural gas network, and meter of the present invention and electricity turn gas and combustion Two kinds of coupled modes of gas-turbine.The present invention turns the energy conversion efficiency and heating value of natural gas of gas and gas turbine by electricity, establishes Its linear model:

1. electricity turns gas:

In formula:Turn the transfer efficiency of gas j for electricity；H_gFor heating value of natural gas, 39MJ/m is taken³。

2. gas turbine:

In formula:For the transfer efficiency of gas turbine j.

Preferably, in the step 6, solution procedure is carried out to the step 3 using bacterial community chemotaxis algorithm are as follows:

(1) when not considering uncertainty, i.e. α_wWhen=0, with predicted value P_w(t, k) replaces uncertain parameterIt is excellent Change and solve deterministic models, i.e. formula (5)-(24), obtains objective function optimal value F₀, it is set to a reference value；

(2) cost deviation factors are setDetermine two kinds of model expectation target valuesWith

(3) robust Model and opportunity model are calculated separately using bacterial community chemotaxis algorithm, obtains the wind of two kinds of models Electricity, which is contributed, does not know radius α_w, economic benefit F and wind store the parameter of Unit erriger power output situation.

Preferably, it in the step 6, is solved using model of the bacterial community chemotaxis algorithm to the step 5 Step are as follows:

(1) when not considering uncertainty, i.e. α_LWhen=0, with predicted value P_{L, t}Instead of uncertain parameterOptimization Solution is true Qualitative model, i.e. formula (28)-(50) obtain objective function optimal value C₀, it is set to a reference value；

(2) cost deviation factors are setDetermine the acceptable two kinds of models expectation target value of policymakerWith

(3) robust Model and opportunity model are calculated separately using bacterial community chemotaxis algorithm, obtains the negative of two kinds of models Lotus does not know radius α_L, cost C and generating set power output situation parameter.

Due to the adoption of the above technical scheme, compared with prior art, it has the advantages that

Scheduling strategy proposed by the present invention is more simple and convenient compared with prior art, practicability is high, and can be more effective Ground reduces intermittence and fluctuation, the raising wind electricity digestion amount and the electrical integrated energy system economic benefit of increase of wind-powered electricity generation, and IGDT scheduling model can preferably describe uncertain information, while can provide for the policymaker of different risk partialities different Scheduling strategy, the problem of overcoming computationally intensive and conservative decision, provide new approaches for processing uncertain factor.This hair The use bacterial community chemotaxis algorithm of bright proposition keeps solution procedure low optimization accuracy high and fast convergence rate model solution.

Detailed description of the invention

Fig. 1 is the method for the present invention system construction drawing；And

Fig. 2 is the overview flow chart of the method for the present invention.

Specific embodiment

The method of the present invention is in the case where considering that there are the new energy such as randomness, intermittent wind-powered electricity generation to access grid condition on a large scale A kind of electrical integrated energy system dispatching method based on information gap decision theory of proposition, method content include following step It is rapid:

Step 1 establishes information gap decision theory (IGDT) model；

Step 3, according to the Optimum Economic benefit after information gap decision-theoretic model and wind-powered electricity generation-pump-storage generator joint Moving model considers that wind power output is uncertain, establishes the wind based on information gap decision theory and stores Unit erriger scheduling model；

Step 5, according to information gap decision-theoretic model and the electrical integrated energy system scheduling model of deterministic type, consider negative The uncertainty of lotus establishes the electrical integrated energy system scheduling model based on information gap decision theory；

Step 6 is solved in conjunction with model of the bacterial community chemotaxis algorithm to step 3 and step 5；

Step 6 is solved the uncertain radius for obtaining two kinds of scheduling models, cost and generating set power output situation by step 7, Scheduling decision person sends uncertain radius, cost and generating set power output situation to energy scheduling center, energy according to regulation goal Energy resource system is adjusted according to actual schedule target and uncertain radius, cost and generating set power output situation source control centre Degree, so that energy scheduling result meets regulation goal.

Below with reference to Fig. 1 and Fig. 2, the electrical comprehensive energy system based on information gap decision theory that the present invention will be described in detail System dispatching method, specific step is as follows by the present invention:

Step 1, information gap decision theory (IGDT) model is established；

IGDT is a kind of Mathematics Optimization Method for the model containing uncertain parameter, and effect is to meet goal-selling Under the premise of, studying possibility caused by uncertain parameter influences.According to the quality of goal-selling, influence can be divided into passive and product The aspect of pole two, corresponding model are known as robust (that is: risk avertion) model and chance (that is: risk is speculated) model.They divide Do not corresponded to two kinds of value orientation completely contradicted that policymaker is taken when in face of risk: robust Model thinks uncertain ginseng Several presence will it is expected to have a negative impact to target；Opportunity model then thinks that uncertain parameter will be sent out towards advantageous direction Exhibition, and then facilitate the realization of target.

The model optimized using IGDT is as follows:

In IGDT theory, uncertain parameter X can be described as follows around the fluctuation of predicted value X:

The robust Model of IGDT is expressed as follows:

The opportunity model of IGDT is expressed as follows:

For the function that given d, maxB (X, d) and minB (X, d) are about X, if the two can be dominant with the variation of X Ground determines, then they embody form and can intuitively be indicated.

Step 2, the Optimum Economic benefit moving model after establishing wind-powered electricity generation-pump-storage generator joint；

(2-1) wind power generating set predicts force modeling:

Wind speed is the stochastic variable of Follow Weibull Distribution, and the power characteristic of Wind turbines is generally manufactured by blower Quotient provides, and can also be obtained by actual measurement.In calculating, the generated output P of separate unit wind turbine_IFIt approximate can use and divide with wind speed relationship v Section function representation are as follows:

In formula: v_r, P_WrRespectively indicate rated wind speed, the rated power for being blower in t hours kth time periods；v_inFor incision Wind speed；v_outFor cut-out wind speed.

Total generated output P of Wind turbines_w(t, k) is indicated are as follows:

P_w(t, k)=efN_w(t, k) P_IF(t, k) (6)

0≤P_IF(t, k)≤P_WR(t, k) (7)

In formula: P_IF(t, k), P_w(t, k) is respectively t hours kth time period separate unit blowers and total Wind turbines power generation function Rate (MW)；E, f are respectively the transmission efficiency and generating efficiency (%) of blower；N_W(t, k) is in t hours kth time period wind power plants The blower number of units of normal operation；P_WR(t, k) is the rated power (MW) of t hours kth time period separate unit blowers.

The coordination mode of (2-2) Wind turbines and pump-storage generator:

The present invention establishes wind and stores Unit erriger after coordinating Wind turbines and pump-storage generator, it is specific that wind stores Unit erriger Coordination mode is as follows: Optimum Economic benefit moving model after wind-powered electricity generation-pump-storage generator joint was prediction with 24 hours one day Period divides four periods again per hour, totally 96 coordination periods, and sets interior wind-powered electricity generation prediction power when a certain small and be more than or equal to When wind-powered electricity generation prediction power average value, then the hour is defined as the state of drawing water, and four periods under this state are water-storage machine Drawing water for group or was drawn water for zero period at the period, and the zero period unit that draws water still works, but the power that draws water is zero.Interior wind-powered electricity generation when a certain small When prediction power is less than wind-powered electricity generation prediction power average value, then the hour is defined as generating state, when under this state four Section is the power generation period or zero period of power generation of pump-storage generator, and zero period unit of power generation still works, but generated output is zero, should The power generation of state apparatus for lower wind is less, releases water from reservoir generate electricity at this time.

(2-3) wind-powered electricity generation-water-storage Unit erriger Optimum Economic benefit objective function:

After Wind turbines and pump-storage generator joint, wind storage Unit erriger is regarded as an entirety, i.e. water-storage The power that draws water of unit is only provided by Wind turbines, using performance number and corresponding unit quantity at product come the wind in expression system The online economy and pump-storage generator of electric field are drawn water cost.Unit erriger online power and water-storage machine are stored by optimization wind / the generated output that draws water of group farthest utilizes wind energy.

The mathematical model that wind stores the scheduling of Unit erriger Optimum Economic benefit is as follows:

maxF (8)

The constraint condition of (2-4) wind storage Unit erriger Optimum Economic benefit:

(2.4.1) equality constraint:

X_t+Y_t=1 (13)

P_ws(t, k)=P_ws(t, k+1) (15)

In formula: P_ws(t, k) is that t hours kth time period wind stores the grid-connected power of Unit erriger；P_p(t, k) is water-storage machine Draw water power of the group in t hours kth time periods；Respectively wind stores Unit erriger under the state of drawing water and generating state The grid-connected power of kth (k takes 1,2,3,4) period；X_tExpression unit was generating state, X at t hours when=1_tUnit exists when=0 T hours are state of drawing water；Y_tExpression unit was generating state, Y at t hours when=0_tUnit was pumping at t hours when=1 Water state；P_w(t, k) is t hours kth time period Wind turbines prediction powers；P_w.tFor the total pre- measurement of power of t hours Wind turbines Rate；P_g(t, k) is generated output of the pump-storage generator in t hours kth time periods；η_pFor the efficiency of drawing water of pump-storage generator；

(2.4.2) inequality constraints condition:

0≤P_g(t, k)≤P_g.max(t, k) (18)

0≤P_p(t, k)≤P_p.max(t, k) (19)

In formula: P_p.max(t, k) and P_g.max(t, k) is respectively draw water power and the generated output upper limit；P_p(t, k) is the storage that draws water Draw water power of the energy unit in t hours kth time periods；P_g(t, k) is power generation of the pump-storage generator in t hours kth time periods Power.

P_min(t, k)≤P_ws(t, k)≤P_max(t, k) (20)

In formula: P_min(t, k), P_max(t, k) be t hour kth time period wind store the minimum value of the grid-connected power of Unit erriger with Maximum value；P_ws(t, k) is that t hours kth time period wind stores the grid-connected power of Unit erriger.

4. wind storage Unit erriger draws water, power and generated output are constrained each other:

In formula: η_gFor the generating efficiency of pump-storage generator.

5. the grid-connected constraint of Wind turbines prediction power:

P_d.min(t, k)≤P_w(t, k)≤P_d.max(t, k) (22)

Work as X_tP_w(t, k) >=P_d.maxWhen (t, k), it is expressed as,

X_tP_w(t, k)=P_d.max(t, k) (23)

In formula: P_d.min(t, k), P_d.max(t, k) is the minimum value and most of kth time period Wind turbines installed capacity in t hours Big value；P_w(t, k) is t hours kth time period Wind turbines prediction powers.

6. pump-storage generator start-stop time constrains:

Research of the invention is average using the hour prediction power of wind-powered electricity generation prediction power and a cycle in a certain hour The start-stop time of value compared to determine pump-storage generator.I.e. start-stop time draws water/generating state with pump-storage generator Variation and change, the start-stop time of pump-storage generator is constrained, is indicated are as follows:

Step 3, consider that wind power output is uncertain, establish the wind based on information gap decision theory and store Unit erriger scheduling Model；

Under Uncertain environments, wind power output has serious uncertainty in practice.Using IGDT foundation meter and not Deterministic scheduling model.

(3-1) uncertain collection model:

The uncertain collection model of wind power output is as follows:

(3-2) IGDT scheduling model:

Consider that uncertain is that the IGDT that the too conservative scheduling decision person of decision intention formulates under Risk Avoiding Strategy is dispatched Model can seek the IGDT scheduling model under strategy for the partially congenial scheduling decision person making machine of decision intention.It is expected meeting Corresponding uncertain, economic benefit and unit output plan are studied in the case of economic benefit deviation.In order to describe conveniently, this Maximum uncertainty level and chance that Risk Avoiding Strategy acquires are sought the minimum uncertainty level that strategy acquires by invention It is referred to as uncertainty.

3.2.1 Risk Avoiding Strategy:

The purpose of strategy is to seek corresponding uncertainty, value in the case where decision economic benefit is no more than desired value Bigger, the ability avoided risk is bigger, but corresponding economic benefit is lower.Scheduling decision person is using less economic benefit as cost The ability avoided risk is obtained, the robustness of IGDT is embodied.Robust Model economic benefit straggling parameter is arranged in the present invention WithIndicate the expected cost of policymaker.Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Wherein, α_wFor fluctuating range；F is wind-powered electricity generation online economic benefit；For robust Model economic benefit straggling parameter；For output of wind electric field actual value；U(α_w, P_w(t, k) is the uncertain collection of wind power output；F₀For basic benefit.

3.2.2 chance seeks strategy:

Chance seeks strategy and seeks the minimum uncertainty for enabling economic benefit increased, and value is bigger, the wind faced Danger is bigger, and corresponding economic benefit is bigger.Scheduling decision person seeks to increase the chance of economic benefit in bigger risk, embodies The opportunistic of IGDT.Similarly, opportunity model economic benefit straggling parameter is arranged in the present inventionIt has a chance or opportunity and seeks under strategy IGDT dispatches opportunity model, indicates are as follows:

Wherein, α_wFor fluctuating range；F is wind-powered electricity generation online economic benefit；For opportunity model economic benefit straggling parameter；For output of wind electric field actual value；U(α_w, P_w(t, k) is the uncertain collection of wind power output；F₀For basic benefit.

Step 4, the electrical integrated energy system scheduling model of deterministic type is established；

Electric energy system includes electric system side and natural gas system side, and is with gas turbine unit and P2G device Coupling element forms the closure type of flow of the two-way conversion of electric energy.

(4-1) objective function:

In formula: C is the total operating cost of electrical integrated energy system；T is scheduling slot；T is to dispatch total period；Ω_GC、 Ω_NThe respectively set of coal unit, gas source；P_{GC, i, t}For i-th of coal unit the t period active power output；a_i, b_i, c_iFor The cost of electricity-generating coefficient of i-th of coal unit；g_iFor the natural gas purchase cost coefficient of i-th of gas source；F_{N, i, t}For i-th of gas source In the output gas flow amount of t period；K_cThe cost of electricity-generating coefficient of Unit erriger, P are stored for wind_{Ws, t}Unit erriger is stored simultaneously for t hours wind Net power.

(4-2) constraint condition:

The constraint condition of electrical integrated energy system Optimized Operation include electric power networks constraint, natural gas network constraint and The coupling constraint of the two network.

The constraint of (4.2.1) electric power networks:

Electric power networks constraint uses conventional constraint, including power-balance constraint, balance nodes phase angle constrain, generating set is Coal unit and Gas Generator Set units limits, node voltage constraint, line power constraint and generating set Climing constant, using straight Angular coordinate form, is expressed as follows:

P_{G, i, t}+P_{Ws, t}-P_{P2G, i, t}-P_{L, i, t}-P_{I, t}=0 (29)

Q_{G, i, t}-Q_{L, i, t}-Q_{I, t}=0 (30)

tanθ_{Bal, t}-f_{Bal, t}/e_{Bal, t}=0 (31)

P_{G, i, min}≤P_{G, i, t}≤P_{G, i, max} (32)

Q_{G, i, min}≤Q_{G, i, t}≤Q_{G, i, max} (33)

V² _{I, min}≤e_{I, t} ²+f_{I, t} ²≤V² _{I, max} (34)

0≤P_{Ij, t} ²+Q_{Ij, t} ²≤S² _{Ij, max} (35)

P_{G, i, t}-P_{G, i, t-1}≤R_{U, i} (36)

P_{G, i, t-1}-P_{G, i, t}≤R_{D, i} (37)

In formula: P_{I, t}、Q_{I, t}The respectively active and reactive power of t moment node i；P_{G, i, t}For having for t moment generating set i Function power output；P_{G, i, t-1}For the active power output of t-1 moment generating set i；Q_{G, i, t}For the idle power output of t moment generating set i；P_{L, i, t} For the burden with power of t moment node i；Q_{L, i, t}For the load or burden without work of t moment node i；P_{P2G, i, t}Electricity turns having for device of air i when for t Function power output；θ_{Bal, t}For t moment balance nodes voltage phase angle；e_{Bal, t}、f_{Bal, t}Respectively the real part of t moment balance nodes voltage and Imaginary part；P_{G, i, max}、P_{G, i, min}And Q_{G, i, max}、Q_{G, i, min}Respectively above and below the active power output bound of generating set i and idle power output Limit；e_{I, t}、f_{I, t}The respectively real and imaginary parts of t moment node i voltage；V_{I, max}、V_{I, min}Respectively above and below node i voltage magnitude Limit；P_{Ij, t}、Q_{Ij, t}The respectively active and reactive power of t moment route ij；S_{Ij, max}For the upper limit of route ij apparent energy；R_{U, i}、 R_{D, i}The upper limit that respectively generating set i climbs above and below.

(4.2.2) natural gas network constraint:

Natural gas network mainly includes providing the gas source point of natural gas, by the pipeline of natural gas transportation to load side and is used for Supplement the pressurizing point of the pressure loss in energy transport.The multi-period dynamic process of present invention research, it is also necessary to which consideration, which has, deposits The air accumulator and pipe for storing up function deposit (linepack).

1. gas source point:

Q_{N, j, min}≤Q_{N, j, t}≤Q_{N, j, max} (38)

2. pipeline:

Its flow equation may be expressed as:

In formula:Indicate that t moment flows through the average flow rate of pipeline ij, wherein Qⁱⁿ _{Ij, t}、Q^out _{Ij, t} Respectively the head end natural gas filling inbound traffics of t moment pipeline ij and end natural gas output flow；C_ijFor constant, C_ijSpecific number It is worth related with pipeline ij efficiency, temperature, length, internal diameter, compressibility factor etc.；p_{I, t}、p_{J, t}Respectively t moment first and last node i, j Pressure value.

p_{J, min}≤p_{J, t}≤p_{J, max} (40)

3. pipe is deposited:

In formula: L_{Ij, t}Pipe for t moment pipeline ij is deposited；L_{Ij, t-1}Pipe for t-1 moment pipeline ij is deposited；M_ijFor constant, M_ijTool Body numerical value and pipeline ij length, radius, temperature and gas density, compressibility factor etc. are related；Indicate t The average pressure of moment pipeline ij.

4. air accumulator:

In formula: S_{S, j, t}For the memory capacity of t moment air accumulator j；S_{S, j, t-1}For the memory capacity of t-1 moment air accumulator j；Respectively the natural gas filling inbound traffics of t moment air accumulator j and output flow；S_{S, j, max}、S_{S, j, min}Respectively gas storage The upper and lower limit of tank j memory capacity；Respectively air accumulator j natural gas filling inbound traffics and output flow is upper Limit.

5. compressor:

In formula: Q_{Com, k, t}For the gas discharge of t moment compressor k consumption；H_{Com, k, t}For the energy of t moment compressor k consumption Amount；β_kFor the energy conversion factor of compressor k；B_kFor constant related with compressor k efficiency, temperature, heating value of natural gas； f_{Com, k, t}The gas discharge of compressor k is flowed through for t moment；Z_kIt is related with compressor k compressibility factor and heating value of natural gas normal Number；R_{K, max}、R_{K, min}The respectively upper and lower limit of compressor k compression ratio；p_{I, t}、p_{J, t}Respectively t moment first and last node i, the pressure of j Value.

6. flow equilibrium:

Similar to the node power balance in electric power networks, each section in natural gas network can be obtained according to flow conservation law The flux balance equations of point:

In formula: i ∈ j indicates all nodes being connected with node j；Q_{N, j, t}For the natural gas supply stream of t moment gas source point j Amount；Q_{P2G, j, t}Turn the gas discharge that gas j is converted to for t moment electricity；Q_{GT, j, t}For the natural gas of t moment gas turbine j consumption Flow；Q_{Com, j, t}For the gas discharge of t moment compressor j consumption；Q_{L, j, t}For the natural gas load of t moment node j；Qⁱⁿ _{Ij, t}、 Q^out _{Ij, t}Respectively the head end natural gas filling inbound traffics of t moment pipeline ij and end natural gas output flow；Point Not Wei t moment air accumulator j natural gas filling inbound traffics and output flow；

The coupling constraint of (4.2.3) electric system and natural gas system:

Electrical integrated energy system is coupled to form by electric power networks and natural gas network, and meter of the present invention and electricity turn gas and combustion Two kinds of coupled modes of gas-turbine.The present invention turns the energy conversion efficiency and heating value of natural gas of gas and gas turbine by electricity, establishes Its linear model, is embodied as:

1. electricity turns gas:

In formula: Q_{P2G, j, t}Turn the gas discharge that gas j is converted to for t moment electricity；Turn the conversion effect of gas j for electricity Rate；P_{P2G, j, t}Electricity turns the active power output of device of air j when for t；H_gFor heating value of natural gas, 39MJ/m is taken³。

2. gas turbine:

In formula:For the transfer efficiency of gas turbine j；Q_{GT, j, t}For the gas discharge of t moment gas turbine j consumption； P_{GT, j, t}For the active power output of t moment gas turbine j.

Step 5, consider the uncertainty of load, establish the electrical integrated energy system tune based on information gap decision theory Spend model；

In deterministic type scheduling model, it is believed that the prediction of workload demand is accurately that Generation Side and load side are according to prediction Coordinated operation.But under new Uncertain environments, workload demand has serious uncertainty in practice.

(5-1) uncertain collection model:

The uncertain collection model of workload demand is as follows:

In formula: P_{L, t}For the predicted value of load；For the actual value of load；α_LFor fluctuating range, value and prediction error It is directly related.

When not considering uncertainty, i.e. α_LWhen=0, step 4 scheduling model is deterministic type scheduling model, can be calculated at this time Scheduling cost, referred to as basic cost is denoted as C₀。

(5-2) IGDT scheduling model:

Consider that uncertain is that the IGDT that the too conservative scheduling decision person of decision intention formulates under Risk Avoiding Strategy is dispatched Model can seek the IGDT scheduling model under strategy for the partially congenial scheduling decision person making machine of decision intention.It is expected meeting Corresponding uncertain, scheduling cost and unit output plan are studied in the case of costvariation.

5.2.1 Risk Avoiding Strategy:

The purpose of strategy is to seek corresponding uncertainty in the case where cost of decision making is no more than desired value, and value is got over Greatly, the ability avoided risk is bigger, but corresponding scheduling cost is bigger.Scheduling decision person is obtained using more dispatching cost as cost The ability that must be avoided risk embodies the robustness of IGDT.Robust Model scheduling cost straggling parameter is arranged in the present inventionWithIndicate expected cost.Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Wherein, α_LFor fluctuating range, C is the total operating cost of electrical integrated energy system,It is scheduled to for robust Model This straggling parameter；For the actual value of load；C₀For basic cost.

5.2.2 chance seeks strategy:

Chance seeks strategy and seeks to make to be scheduled to the minimum uncertainty that instinct decreases, and value is bigger, the wind faced Danger is bigger, and corresponding cost is smaller.Scheduling decision person seeks to reduce the chance of cost in bigger risk, embodies the machine of IGDT Meeting property.Similarly, opportunity model scheduling cost straggling parameter is arranged in the present inventionHave a chance or opportunity the IGDT scheduling sought under strategy Opportunity model:

Wherein, α_LFor fluctuating range, C is the total operating cost of electrical integrated energy system,For opportunity model scheduling Costvariation parameter；For the actual value of load；C₀For basic cost.

Step 6, it is solved in conjunction with model of the bacterial community chemotaxis algorithm to step 3 and step 5, obtains related ginseng Number；

6-1 bacterial community chemotaxis algorithm:

Bacterial community chemotaxis (bacterial colony chemotaxis, BCC) algorithm is the prior art, as one Optimization method of the kind based on biobehavioral realizes that thought and other group's optimization methods have relatively big difference.It is excellent in other groups In change, individual is detached from the search that completely random can only be carried out when surrounding group influence, and the single bacterium in BCC algorithm also has one Fixed optimizing ability；The moving direction of each bacterium chemotactic and time be all according to probability distribution value, therefore BCC algorithm have it is prominent Broken part is most worth the performance of limitation.

6-2 combines existing bacterial community chemotaxis algorithm to store Unit erriger scheduling model to the wind in step 3 based on IGDT Solution procedure are as follows:

(6.2.1) uses predicted value P_w(t, k) replaces uncertain parameterOptimization Solution deterministic models, i.e. formula (5)-(24) obtain objective function optimal value F₀, it is set to a reference value；

(6.2.2) artificially formulates cost deviation factorsDetermine two kinds of model expectation target valuesWith

(6.2.3) calculates separately robust Model and opportunity model using bacterial community chemotaxis algorithm, obtains two kinds of models Wind power output do not know radius α_w, economic benefit F and wind store the parameter of Unit erriger power output situation.

6-3 combination bacterial community chemotaxis algorithm is to the electrical integrated energy system economic load dispatching in step 5 based on IGDT Model solution step are as follows:

(6.3.1) uses predicted value P_{L, t}Instead of uncertain parameterOptimization Solution deterministic models, i.e. formula (28)-(50), Obtain objective function optimal value C₀, it is set to a reference value；

(6.3.2) artificially formulates cost deviation factorsDetermine the acceptable two kinds of models expectation of policymaker Target valueWith

(6.3.3) calculates separately robust Model and opportunity model using bacterial community chemotaxis algorithm, obtains two kinds of models Load do not know radius α_L, cost C and generating set power output situation parameter.

Step 7, step 6 is solved into obtained parameter and is sent to energy scheduling center, energy scheduling center is according to parameter pair Energy resource system is scheduled.

(7-1) solves the wind based on information gap decision theory using bacterial community chemotaxis algorithm and stores Unit erriger scheduling Model, the wind power output for obtaining robust Model and opportunity model respectively do not know radius α_w, economic benefit F and wind store Unit erriger Contribute P_{Ws, t}.Wind power output radius α is not known into_w, economic benefit F and wind stores Unit erriger and contributes P_{Ws, t}It is applied to electrical synthesis In energy resource system scheduling system.

(7-2) solves the electrical integrated energy system based on information gap decision theory using bacterial community chemotaxis algorithm Scheduling model, the load for respectively obtaining robust Model and opportunity model do not know radius α_L, cost C and generating set power output P_{G, i, t}.Load radius α is not known into_L, cost C and generating set power output P_{G, i, t}It is also applied to electrical integrated energy system scheduling In system.

Electrical integrated energy system control centre makes different scheduling strategies according to different risk partialities, guarantees electrical Steady, the economic operation of integrated energy system.

Finally, it should be noted that above each embodiment is only used to illustrate the technical scheme of the present invention, rather than its limitations； Although the present invention is described in detail referring to the foregoing embodiments, those skilled in the art should understand that: its according to Can so modify to technical solution documented by previous embodiment, or part of or all technical features are carried out etc. With replacement；And these modifications or substitutions, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution Range.

Claims

1. a kind of electrical integrated energy system dispatching method based on information gap decision theory, it is characterised in that: the method Content includes the following steps:

Step 1 establishes information gap decision-theoretic model；

Step 3 is run according to the Optimum Economic benefit after information gap decision-theoretic model and wind-powered electricity generation-pump-storage generator joint Model considers that wind power output is uncertain, establishes the wind based on information gap decision theory and stores Unit erriger scheduling model, specifically Process is as follows:

Firstly, establishing the uncertain collection model of wind power output:

In formula: P_w(t, k) is output of wind electric field predicted value；For output of wind electric field actual value；α_wFor fluctuating range, Value is directly related with prediction error；U(α_w,P_w(t, k) is the uncertain collection of wind power output；

When not considering uncertainty, i.e. α_wWhen=0, it is deterministic type scheduling model that above-mentioned wind, which stores Unit erriger scheduling model, can be calculated Economic benefit at this time, referred to as basic benefit out, are denoted as F₀；

Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Objective function are as follows: max α_w；

Constraint condition are as follows:And in the step 2 Institute's Prescribed Properties of Optimum Economic benefit moving model after wind-powered electricity generation-pump-storage generator joint；

Wherein, F₀For basic benefit；α_wFor fluctuating range；For robust Model economic benefit straggling parameter；For wind Electric field power output actual value；U(α_w,P_w(t, k) is the uncertain collection of wind power output；

Objective function are as follows: min α_w；

Wherein, α_wFor fluctuating range；For opportunity model economic benefit straggling parameter；For output of wind electric field reality Value；U(α_w,P_w(t, k) is the uncertain collection of wind power output；

Step 5, according to information gap decision-theoretic model and the electrical integrated energy system scheduling model of deterministic type, consider load Uncertainty establishes the electrical integrated energy system scheduling model based on information gap decision theory, and detailed process is as follows:

Firstly, establishing the uncertain collection model of workload demand:

In formula: U (α_L,P_L,t) it is the uncertain collection of workload demand；P_L,tFor the predicted value of load；For the actual value of load；α_LFor Fluctuating range, value are directly related with prediction error；

When not considering uncertainty, i.e. α_LWhen=0, above-mentioned electrical integrated energy system scheduling model is deterministic type scheduling model, can Scheduling cost at this time, referred to as basic cost are calculated, C is denoted as₀；

Then, according to the uncertain collection model of workload demand, the electrical integrated energy system based on information gap decision theory is established Scheduling model, specific as follows:

Establish the IGDT scheduling robust Model under Risk Avoiding Strategy:

Objective function are as follows: max α_L；

Constraint condition are as follows:And deterministic type electricity in the step 4 Institute's Prescribed Properties of gas integrated energy system scheduling model；

Wherein, α_LFor fluctuating range,Cost straggling parameter is dispatched for robust Model；

Objective function are as follows: min α_L；

Wherein,Cost straggling parameter is dispatched for opportunity model；

Step 6 is solved in conjunction with model of the bacterial community chemotaxis algorithm to the step 3 and step 5, obtains related ginseng Number, the parameter specifically include: the wind based on information gap decision theory stores the wind of two kinds of models of Unit erriger scheduling model Electricity, which is contributed, does not know radius α_w, economic benefit F and wind store Unit erriger and contribute situation, based on the electrical of information gap decision theory The load of two kinds of models of integrated energy system scheduling model does not know radius α_L, cost C and generating set contribute situation；

The parameter that the step 6 solution obtains is sent to energy scheduling center by step 7, and energy scheduling center is according to institute Parameter is stated to be scheduled energy resource system.

2. a kind of electrical integrated energy system dispatching method based on information gap decision theory according to claim 1, It is characterized by: establishing information gap decision-theoretic model, detailed process is as follows in the step 1:

In formula: X is uncertain parameter；D is decision variable；B (X, d) is objective function；H (X, d), G (X, d) are equation and differ Formula constraint；

In formula:Indicate the predicted value of uncertain parameter, α indicates the fluctuating range of uncertain parameter, α >=0；It indicates The range that uncertain parameter X deviates predicted value is no more than

In uncertain environment, conservative policymaker is in order to guarantee the realization of a certain lowest desired target, usually by uncertain ginseng Several unfavorable disturbances maximizes, and the policymaker to advance rashly is more to pursue uncertain possible extra returns；

The robust Model of IGDT is expressed as follows:

The opportunity model of IGDT is expressed as follows:

In formula: B_oIt is taken for XThe target function value of up-to-date style (1)；B_cFor the expected cost of robust Model；B_jFor the pre- of opportunity model Period cost；β_cFor the deviation factors of robust Model, expected cost is represented higher than B_oExtent of deviation；β_jFor the deviation of opportunity model The factor represents expected cost lower than B_oExtent of deviation；

For the function that given d, maxB (X, d) and minB (X, d) are about X, if the two can by explicitly with the variation of X It determines, then they embody form and can intuitively be indicated；

Formula (3) is robust Model, it indicates the decision value d acquired under the model for Arbitrary PerturbationIt can Guarantee that expected cost is not higher than B_c；

Formula (4) is opportunity model, it indicates the decision value d for acquiring under the model, at least there is oneMake It obtains expected cost and is not higher than B_o。

3. the electrical integrated energy system dispatching method according to claim 1 based on information gap decision theory, special Sign is: in the step 2, the Optimum Economic benefit moving model after wind-powered electricity generation-pump-storage generator is combined is established, it is specific Process is as follows:

maxF(8)

In formula: F is wind-powered electricity generation online economic benefit；P_ws(t, k) is that t hours kth time period wind stores the grid-connected power of Unit erriger；P_p (t, k) is draw water power of the pump-storage generator in t hours kth time periods；C (t, k) is the online electricity of t hours kth time periods Valence；C_i(t, k) is the electricity price of drawing water of t hours kth time periods；T is a cycle i.e. 24 hour；Number of segment 4 when K is interior per hour A period；

The constraint condition of wind storage Unit erriger Optimum Economic benefit:

(1) equality constraint:

X_t+Y_t=1 (13)

P_ws(t, k)=P_ws(t,k+1) (15)

In formula: P_ws(t, k) is that t hours kth time period wind stores the grid-connected power of Unit erriger；P_p(t, k) is that pump-storage generator exists The power that draws water of t hours kth time periods；Respectively wind stores Unit erriger kth under the state of drawing water and generating state, K takes the grid-connected power of 1,2,3,4 periods；X_tExpression unit was generating state, X at t hours when=1_tUnit is small in t when=0 When to draw water state；Y_tExpression unit was generating state, Y at t hours when=0_tUnit was the shape that draws water at t hours when=1 State；P_w(t, k) is t hours kth time period Wind turbines prediction powers；P_w.tFor the total prediction power of t hours Wind turbines；P_g (t, k) is generated output of the pump-storage generator in t hours kth time periods；η_pFor the efficiency of drawing water of pump-storage generator；

Formula (15) indicates that wind stores Unit erriger and meets the grid-connected power relative smooth of joint that wind stores Unit erriger；

(2) inequality constraints condition:

In formula:Indicate unit in t hours kth time period Wind turbines prediction power minimum values；It indicates Unit was in t hours kth time period Wind turbines prediction power maximum values；P_min(t,k)、P_max(t, k) is t hours kth time periods The minimum value and maximum value of the wind storage grid-connected power of Unit erriger；

0≤P_g(t,k)≤P_g.max(t,k) (18)

0≤P_p(t,k)≤P_p.max(t,k) (19)

In formula: P_p.max(t, k) and P_g.max(t, k) is respectively draw water power and the generated output upper limit；

3. under Power Market, for grid-connected wind-powered electricity generation-water-storage combining operation mode, in addition to reduce to system Outside influencing, the gene-ration revenue problem for considering itself is also needed, influence of the wind-electricity integration to grid stability is considered, sets wind-powered electricity generation-pumping The grid-connected power constraint of water accumulation of energy Unit erriger:

P_min(t,k)≤P_ws(t,k)≤P_max(t,k) (20)

In formula: P_min(t,k)、P_max(t, k) is that t hours kth time period wind stores the minimum value and maximum of the grid-connected power of Unit erriger Value；

In formula: η_gFor the generating efficiency of pump-storage generator；

5. the grid-connected constraint of Wind turbines prediction power:

P_d.min(t,k)≤P_w(t,k)≤P_d.max(t,k) (22)

Work as X_tP_w(t,k)≥P_d.maxWhen (t, k), indicate are as follows:

X_tP_w(t, k)=P_d.max(t,k) (23)

In formula: P_d.min(t,k)、P_d.max(t, k) is the minimum value and maximum value of kth time period Wind turbines installed capacity in t hours；

6. pump-storage generator start-stop time constrains:

Research of the invention is the hour prediction power average value using wind-powered electricity generation prediction power and a cycle in a certain hour Compare to determine the start-stop time of pump-storage generator, i.e., start-stop time with pump-storage generator draws water/change of generating state Change and change, the start-stop time of pump-storage generator is constrained, is indicated are as follows:

In formula: M is the start-stop time of pump-storage generator；For the number for the state of drawing water；For the number of generating state.

4. the electrical integrated energy system dispatching method according to claim 1 based on information gap decision theory, special Sign is: in the step 4, the electrical integrated energy system scheduling model of deterministic type is established, the specific implementation process is as follows:

1) objective function:

Target is that the total operating cost C of electrical integrated energy system is minimum, including fired power generating unit cost of electricity-generating, wind store Unit erriger Run cost of electricity-generating and gas source power output cost；Therefore, objective function is shown below:

In formula: t is scheduling slot；T is to dispatch total period；Ω_GC、Ω_NThe respectively set of coal unit, gas source；P_GC,i,tIt is Active power output of the i coal unit in the t period；a_i, b_i, c_iFor the cost of electricity-generating coefficient of i-th of coal unit；g_iFor i-th of gas The natural gas purchase cost coefficient in source；F_N,i,tFor i-th of gas source the t period output gas flow amount；K_cUnit erriger is stored for wind Cost of electricity-generating coefficient, P_ws,tThe grid-connected power of Unit erriger is stored for t hours wind；

2) constraint condition:

The constraint condition of electrical integrated energy system Optimized Operation, comprising: electric power networks constraint, natural gas network constraint and two The coupling constraint of person's network；

(1) electric power networks constrain:

Electric power networks constraint uses conventional constraint, including the constraint of power-balance constraint, balance nodes phase angle, generating set, that is, wraps Coal unit and Gas Generator Set units limits, node voltage constraint, line power constraint and generating set Climing constant are included, is used Cartesian form is expressed as follows:

P_G,i,t+P_ws,t-P_P2G,i,t-P_L,i,t-P_i,t=0 (29)

Q_G,i,t-Q_L,i,t-Q_i, t=0 (30)

tanθ_bal,t-f_bal,t/e_bal,t=0 (31)

P_G,i,min≤P_G,i,t≤P_G,i,max (32)

Q_G,i,min≤Q_G,i,t≤Q_G,i,max (33)

V² _i,min≤e_i,t²+f_i,t²≤V² _i,max (34)

0≤P_ij,t ²+Q_ij,t ²≤S² _ij,max (35)

P_G,i,t-P_G,i,t-1≤R_U,i (36)

P_G,i,t-1-P_G,i,t≤R_D,i (37)

In formula: P_i,t、Q_i,tThe respectively active and reactive power of t moment node i；P_G,i,tFor t moment generating set i it is active go out Power；Q_G,i,tFor the idle power output of t moment generating set i；P_L,i,tFor the burden with power of t moment node i；Q_L,i,tFor t moment node The load or burden without work of i；P_P2G,i,tElectricity turns the active power output of device of air i when for t；θ_bal,tFor t moment balance nodes voltage phase angle； e_bal,t、f_bal,tThe respectively real and imaginary parts of t moment balance nodes voltage；P_G,i,max、P_G,i,minAnd Q_G,i,max、Q_G,i,minRespectively For the active power output bound and idle power output bound of generating set i；e_i,t、f_i,tThe respectively real part of t moment node i voltage And imaginary part；V_i,max、V_i,minRespectively node i voltage magnitude bound；P_ij,t、Q_ij,tRespectively active, the nothing of t moment route ij Function power；S_ij,maxFor the upper limit of route ij apparent energy；R_U,i、R_D,iThe upper limit that respectively generating set i climbs above and below；

(2) natural gas network constraint:

Natural gas network, which specifically includes that, provides the gas source point of natural gas, by the pipeline of natural gas transportation to load side and is used to mend Fill the pressurizing point of the pressure loss in energy transport；The multi-period dynamic process of present invention research, it is also necessary to which consideration has storage The air accumulator and pipe of function are deposited；

1. gas source point:

Q_N,j,min≤Q_N,j,t≤Q_N,j,max (38)

In formula: Q_N,j,tFor the natural gas supply flow of t moment gas source point j；Q_N,j,max、Q_N,j,minThe respectively natural gas of gas source point j Supply flow upper and lower limit；

2. pipeline:

Natural gas line flow equation is related with pipe ends pressure and many physical characteristics of pipeline, has no general form, special Gas flow under shape of pledging love usually is described with nonlinear equation, is insulated gas pipeline for ideal, is considered natural gas bidirectional flow It is dynamic,

Its flow equation may be expressed as:

In formula:Indicate that t moment flows through the average flow rate of pipeline ij, wherein Qⁱⁿ _ij,t、Q^out _ij,tRespectively For the head end natural gas filling inbound traffics and end natural gas output flow of t moment pipeline ij；C_ijFor with pipeline ij efficiency, temperature, The related constant such as length, internal diameter, compressibility factor；p_i,t、p_j,tRespectively t moment first and last node i, the pressure value of j；

Natural gas line flow equation (39) is only applicable to the network of high pressure turbulent flow, and node pressure value has bound constraint, indicates It is as follows:

p_j,min≤p_j,t≤p_j,max (40)

P in formula_j,min、p_j,maxRespectively node j pressure value upper and lower limit；

3. pipe is deposited:

Due to the compressibility of natural gas, pipeline head end natural gas filling inbound traffics are often different from end natural gas output flow, The gas discharge of first and last end difference just briefly stores in the duct, and referred to as pipe is deposited, and Guan Cunke buffers natural gas network gas The fluctuation of load is the key factor for guaranteeing natural gas and reliably supplying, the average pressure and pipe parameter of Guan Cunyu pipe ends It is directly proportional, consider multi-period dynamic process, may be expressed as:

In formula: L_ij,tPipe for t moment pipeline ij is deposited；M_ijFor with pipeline ij length, radius, temperature and gas density, compression because The related constant such as son；Indicate the average pressure of t moment pipeline ij；

4. air accumulator:

Load is reliably supplied in the storage of natural gas in natural gas network and network security stable operation is most important, natural When biggish fluctuation occurs for gas network failure or gas load, air accumulator can replace gas source point to provide natural gas to network, protect It is in liberal supply to hinder natural gas load, natural gas network air accumulator is limited in storage capacity and natural gas injection, output flow Limitation, consider multi-period dynamic process, constraint may be expressed as:

In formula: S_S,j,tFor the memory capacity of t moment air accumulator j；The natural gas of respectively t moment air accumulator j injects Flow and output flow；S_S,j,max、S_S,j,minThe respectively upper and lower limit of air accumulator j memory capacity；Point Not Wei air accumulator j natural gas filling inbound traffics and output flow the upper limit；

5. compressor:

The pressure loss of the natural gas network as caused by frictional resistance, natural gas network for reliable transmission natural gas and compensation In need to configure a certain number of pressurizing points, the most important part of pressurizing point is the compressor for increasing gas pressure, it is assumed that pressure The energy of contracting machine consumption derives from the natural gas by compressor, can be regarded as the load of natural gas network, compressor consumption Gas discharge it is related with the flow and compression ratio for flowing through compressor, can be expressed as follows:

In formula: Q_com,k,tFor the gas discharge of t moment compressor k consumption；H_com,k,tFor the energy of t moment compressor k consumption； β_kFor the energy conversion factor of compressor k；B_kFor constant related with compressor k efficiency, temperature, heating value of natural gas；f_com,k,tFor T moment flows through the gas discharge of compressor k；Z_kFor constant related with compressor k compressibility factor and heating value of natural gas； R_k,max、R_k,minThe respectively upper and lower limit of compressor k compression ratio；

6. flow equilibrium:

Similar to the node power balance in electric power networks, each node in natural gas network can be obtained according to flow conservation law Flux balance equations indicate are as follows:

In formula: i ∈ j indicates all nodes being connected with node j；Q_P2G,j,tTurn the natural gas flow that gas j is converted to for t moment electricity Amount；Q_GT,j,tFor the gas discharge of t moment gas turbine j consumption；Q_com,j,tFor the natural gas flow of t moment compressor j consumption Amount；Q_L,j,tFor the natural gas load of t moment node j；Qⁱⁿ _ij,t、Q^out _ij,tThe head end natural gas of respectively t moment pipeline ij injects Flow and end natural gas output flow；Respectively the natural gas filling inbound traffics of t moment air accumulator j and output Flow；Q_N,j,tFor the natural gas supply flow of t moment gas source point j；

(3) coupling constraint of electric system and natural gas system:

Electrical integrated energy system is coupled to form by electric power networks and natural gas network, and meter of the present invention and electricity turn gas and combustion gas wheel Two kinds of coupled modes of machine, the present invention are turned the energy conversion efficiency and heating value of natural gas of gas and gas turbine by electricity, establish its line Property model:

1. electricity turns gas:

In formula:Turn the transfer efficiency of gas j for electricity；H_gFor heating value of natural gas, 39MJ/m is taken³；

2. gas turbine:

In formula:For the transfer efficiency of gas turbine j.

5. the electrical integrated energy system dispatching method according to claim 1 based on information gap decision theory, special Sign is: in the step 6, carrying out solution procedure to the step 3 using bacterial community chemotaxis algorithm are as follows:

(1) when not considering uncertainty, i.e. α_wWhen=0, with predicted value P_w(t, k) replaces uncertain parameterOptimization is asked Deterministic models, i.e. formula (5)-(24) are solved, objective function optimal value F is obtained₀, F₀Referred to as basic benefit；

(3) robust Model and opportunity model are calculated separately using bacterial community chemotaxis algorithm, the wind-powered electricity generation for obtaining two kinds of models goes out Power does not know radius α_w, economic benefit F and wind store the parameter of Unit erriger power output situation.

6. the electrical integrated energy system dispatching method according to claim 5 based on information gap decision theory, special Sign is: in the step 6, carrying out solution procedure using model of the bacterial community chemotaxis algorithm to the step 5 are as follows:

(1) when not considering uncertainty, i.e. α_LWhen=0, with predicted value P_L,tInstead of uncertain parameterOptimization Solution certainty Model, i.e. formula (28)-(50) obtain objective function optimal value C₀, C₀For basic cost；

(3) robust Model and opportunity model are calculated separately using bacterial community chemotaxis algorithm, obtains the load of two kinds of models not Determine radius α_L, cost C and generating set power output situation parameter.