CN105226707A - A kind of methodology based on Shapley value wind-electricity integration system fixed cost of power transmission - Google Patents

Abstract

The invention discloses a kind of methodology based on Shapley value wind-electricity integration system fixed cost of power transmission, the method has certain randomness based on wind power output, adopt the scene of Monte-Carlo Simulation wind power output, but the introducing of a large amount of scene can increase computation burden, for alleviating computation burden and keeping certain calculating credibility, adopt scene "flop-out" method to reduce wind power output scene, generate an approximate scene subset of former scene collection; Under guaranteed range constraint, adopt the method based on Shapley value to calculate the contributory value of transmission system fixed cost under wind-electricity integration environment.The present invention be under wind-electricity integration environment sharing of transmission system fixed cost provide effective method.

Description

A kind of methodology based on Shapley value wind-electricity integration system fixed cost of power transmission

Technical field

The present invention relates to a kind of methodology based on Shapley value wind-electricity integration system fixed cost of power transmission, be specifically related to a kind of transmission fixed cost allocation method based on the transmission system of Shapley value under wind-electricity integration environment, belong to cost sharing field.

Background technology

The dual-pressure of energy security and environmental protection makes renewable energy power generation receive much concern.Wind power generation is technology maturation, possesses the renewable power supply of scale exploit condition, and worldwide obtain extensive use, installed capacity presents the situation that grows continuously and fast.

By wind speed stochastic volatility and intermittently to affect, wind-powered electricity generation belongs to typical randomness power supply.And the characteristic feature of electric power system to be any instant all must ensure power supply and demand balance, otherwise system will be difficult to keep stable operation.Due between wind power and wind speed in cubic relationship, the minor variations of wind speed all will cause the obvious change of wind power, in addition the rapid increase of wind energy turbine set scale, the power that wind energy turbine set injects electrical network points of common connection (PointofCommonCoupling, PCC) will present larger fluctuation.

In order to ensure the safety and stability economical operation of wind-electricity integration system, need the Allocation of transmission system fixed cost solving number of different types, as transmission line investment cost share, transmission line transmitting jam expenses, electric power transmission network power transmission loss cost allocation etc.These expenses with 1,000,000, ten million, even calculate with hundred million usually.Rational transmission fixed cost allocation strategy, has great importance for improving the production of electric energy, transmission and service efficiency.

Transmission system fixed cost has can not the characteristic of decoupling zero, namely there is not relation one to one between the generation of fixed cost and concrete load (or generating).People can not explicitly point out, and which load (or generating) should be responsible for which partial fixing cost.This mainly because, electric power networks is monopolistic, all loads and generator must use same electric power networks simultaneously, and reciprocation complicated between them creates fixed cost jointly, distinguish actual reciprocation responsibility and usually cannot accomplish in reality.Therefore, the Allocation of transmission system fixed cost is a difficulties that must solve.

At present, in the transmission system operation in countries in the world, usually carry out apportioned fixed cost according to the ratio of load (or generating) size.But, the shortcoming of pro rata distribution method clearly, not only easily cause the alternative subsidy between load, violate the market principle of economical fairness, and the more important thing is, it can not provide correct economic incentives signal, promotes the optimization aim that load (or generating) reduces fixed cost to reach at the reasonable layout of the whole network, saves social resources.

Summary of the invention

Technical problem to be solved by this invention is: provide a kind of methodology based on Shapley value wind-electricity integration system fixed cost of power transmission, consider the impact of wind-electricity integration environment on transmission system transmission fixed cost allocation, make cost sharing result meet fairness, stability, financial settlement balance.

The present invention is for solving the problems of the technologies described above by the following technical solutions:

Based on a methodology for Shapley value wind-electricity integration system fixed cost of power transmission, comprise the steps:

Step 1, utilize Monte Carlo model to simulate wind power output scene to obtain wind power output scene collection, and generate the wind power output data of each time period according to the time period of presetting;

Step 2, utilize scene "flop-out" method to reduce the wind power output scene collection that step 1 obtains, obtain the approximate scene subset of this scene collection;

Step 3, obtain the basic condition of each user in wind-electricity integration system, comprising: load season, working system, time-of-use tariffs Time segments division, peak valley ordinary telegram valency ratio, the quality of power supply and power consumption;

Step 4, the basic condition of each user to be normalized, to obtain the standardized index of each user;

Step 5, step 2 is reduced after contextual data and the standardized index data of each user that obtain of the step 4 Shapley value of carrying out under guaranteed range constraint calculate, obtain the Shapley value that each user is corresponding, Shapley value corresponding for each user is multiplied by fixed cost of power transmission, obtains each user and answer allocated cost.

Preferably, utilize scene "flop-out" method to integrate the detailed process of reducing to the wind power output scene that step 1 obtains described in step 2 to be: the probability that known wind power output scene concentrates all scene numbers to occur as n and each scene i is as p _i, calculate scene and concentrate the distance between arbitrary scene and all scenes to obtain the distance matrix C of n*n, the arbitrary element c in C _ijrepresent the distance between scene i and scene j, be multiplied by the matrix B that C obtains n*n after the probabilistic that each scene occurs being become the matrix of 1*n, the arbitrary element b in matrix B _ij=p _i* c _ij, the scene of corresponding for least member value in B probability is deleted, i=1 ..., n, j=1 ..., n, is added to the probability deleting scene on the probability of the scene nearest with this scene distance, and repeats said process, till tapering to the scene number needing to retain.

Preferably, described in step 4, standardized index comprises: straight purchase of electricity index, power quality index and tou power price index.

Preferably, the computing formula of described tou power price index is: wherein, D _kfor the tou power price index of a kth user, m is total number of users, and l is the typical number of days divided for each user, T _afor the number of days that typical case day a is corresponding, α _a: 1: β _afor peak, flat, the paddy electricity price ratio of typical case day a, t _{ka, f}, t _{ka, p}, t _{ka, g}be respectively user k at the peak of typical case day a, flat, paddy utilizes hourage.

Preferably, described in step 5, the computing formula of Shapley value is: ${\mathrm{\φ}}_k=\frac{1}{m!}\underset{S:k\∈s\∈M}{\Σ}(s-1)!(m-s)!\{c\left(S\right)-c(S-\{k\left\}\right)\},$ Wherein, φ _kfor the Shapley value of a kth user, m is total number of users, and S is the alliance of user, and s is the number of user in user coalitions, the marginal contribution value that c (S)-c (S-{k}) is user k, and M is the set of all users.

The present invention adopts above technical scheme compared with prior art, has following technique effect:

1, contemplated by the invention the impact of randomness power supply on transmission system transmission fixed cost allocation, under wind-electricity integration environment, transmission system transmission fixed cost allocation provides effective method.

2, the present invention adopts the visual angle of Shapley value to share the fixed cost of transmission system under wind-electricity integration environment, all users (user of fixed cost) employ whole electrical network jointly, electrical network fixed cost is that all user's actings in conjunction produce, reciprocation complicated between them creates fixed cost jointly, distinguish actual reciprocation responsibility and usually be difficult to accomplish in reality.But from the angle of cooperative game, between user, constitute actual cooperative relationship.Adopt sharing of transmission system fixed cost under Shapley value method invention wind-electricity integration environment, there is justice, rational advantage.

3, the present invention adopts Shapley value to share the Transmission Cost of wind-electricity integration, embodies the principle by division of responsibiltiy well, is considered as justice by cooperative parties; In addition, Shapley value share the Economic Stimulus signal that result can provide positive usually, make participant while making great efforts to reduce self contributory value, decrease the common cost of whole Major Leagues.

Accompanying drawing explanation

Fig. 1 is the overall flow figure of the methodology that the present invention is based on Shapley value wind-electricity integration system fixed cost of power transmission.

Fig. 2 is the reduction flow chart of wind power output contextual data of the present invention.

Fig. 3 is wind power output scene random data figure in the embodiment of the present invention.

Fig. 4 is the design sketch of wind power output scene random data after reduction in the embodiment of the present invention.

Fig. 5 is the comparison diagram of each user to 3 kinds of methods (postage stamp method, Shapely value, AR-Shapely value) transmission fixed cost allocation ratio.

Embodiment

Be described below in detail embodiments of the present invention, the example of described execution mode is shown in the drawings, and wherein same or similar label represents same or similar element or has element that is identical or similar functions from start to finish.Being exemplary below by the execution mode be described with reference to the drawings, only for explaining the present invention, and can not limitation of the present invention being interpreted as.

As shown in Figure 1, the methodology that the present invention is based on Shapley value wind-electricity integration system fixed cost of power transmission mainly comprises following three steps:

The first step, simulation wind power output scene, and scene reduction is carried out to these scenes.The randomness of wind power output scene determines the introducing of a large amount of scene, can increase computation burden like this.In order to calculate simple and keep certain credibility, we adopt scene "flop-out" method to reduce scene.

Scene method is a kind of important method of simulation operation states of electric power system, can effectively process operating chance phenomenon, and the present invention adopts Monte Carlo simulation to produce scene, also can adopt existing historical data simulated scenario in actual applications.If electric power system be a scene s in a possibility running status time series of T period, the set that the scene likely occurred by system is formed is called scene collection S.Although scenario simulation solves stochastic problems, but the introducing of a large amount of scene adds the burden of calculating, for alleviating computation burden and keeping certain credibility, scene "flop-out" method can be adopted to reduce scene, generate an approximate scene subset of former scene collection, make scene collection and former scene collection probability metrics after reduction the shortest.The present invention adopts synchronous back substitution "flop-out" method (simultaneousbackwardreduction) to carry out scene reduction, and its flow process as shown in Figure 2.

As shown in Figure 3, for the wind power output scene graph obtained by Monte-Carlo Simulation, dot-dash curve represents scene 1, dashed curve represents scene 2, dotted line curve represents scene 3, block curve represent scene 4, dotted line have the curve of circles mark represent the curve that scene 5, dotted line have diamond to mark represent scene 6, dotted line have six curves connecting shapes mark represent the curve that scene 7, solid line have square to mark represent scene 8, dotted line have the curve of downward triangular marker to represent the curve that scene 9, dotted line have square to mark represents scene 10.

As shown in Figure 4, be the wind power output scene obtained by scene "flop-out" method, dot-dash curve represents scene 1, dashed curve represents scene 2, dotted line curve represents scene 3.

Second step, the exploitation of transmission system transmission fixed cost allocation method and game theory analysis thereof under wind-electricity integration environment.According to the function feature of the fixed cost-electricity of transmission system under wind-electricity integration environment, set up the characteristic function model of Shapley value.Adopt cooperative game method to analyze adaptability condition that Shapley value is applied to transmission fixed cost allocation under wind-electricity integration environment, and share fairness, stability, the financial settlement balance of result, and Shapley value is positioned at the condition of core.

3rd step, the practical analysis of transmission system transmission fixed cost allocation under wind-electricity integration environment, utilize the particularity of transmission system transmission fixed cost allocation problem under wind-electricity integration environment, alliance as little in brief characteristic function value, reduce alliance's number very many times methodology amount of calculation.

In recent years, the new forms of energy such as wind-powered electricity generation, photovoltaic obtain and develop fast, and it accesses electrical network in a centralized or distributed manner, but due to wind-powered electricity generation, the randomness of photovoltaic equal energy source, fluctuation, intermittence, a large amount of accesses can bring pressure to system safety stable operation.For safeguards system safe and stable operation, often need conventional power unit coordinate and increase reserve capacity, add system operation cost.In embodiments of the invention, wind power output is directly related with wind speed size, and in one day, wind speed often presents randomness, intermittent feature, and the uncertainty of wind speed is that the prediction of wind power output brings difficulty.But as in longer time scale as the moon, season, year are analyzed wind speed, can find out that wind speed presents again seasonal feature, fixing month wind speed mean variation little, present certain periodicity, suitably adjust reserve capacity scheme according to the seasonal feature of wind speed in different months or season and can be conducive to dissolving of wind-powered electricity generation.

Autoregressive moving-average model (autoregressivemovingaveragemodel is extensively adopted in wind speed simulation, ARMA), this model can embody the sequential feature of wind speed, p rank autoregression q rank moving average model ARMA (p, q) model.Arma modeling is applicable to stationary time series, and the present invention does not discuss to the stationarity of wind speed, and the method adopting time series models to come Simulation and Prediction wind speed and wind power generation pushes away wind series to standardization series model is also counter.According to autoregression, moving average and white noise sequence parameter, stochastic simulation can be adopted to generate n wind speed scene, and the probability of each scene is 1/n.

The data that embodiment adopts are as shown in table 1.For simplicity, this embodiment directly gives 5 electric energy quality grade: A, B, C, D, E, and corresponding power quality index is 5,4,3,2,1.First, we will carry out dimensionless normalized to data, obtain table 2.

The each user's basic condition of table 1

The standardized index of each user of table 2

User's name	Straight purchase of electricity index	Power quality index	Tou power price index
				User A	0.4223	0.1818	0.5192
User B	0.4114	0.0909	0.2762
				User C	0.0845	0.2727	0.1440
User D	0.0819	0.4545	0.0606

Charolais cattle (Shapley) methodology: traditional postage stamp method uses a kind of comparatively general method at present.This method, when calculating transfer fee, shares out equally the fixed cost of whole power transmission network by the size of reality transhipment power.This method only considered power consumption single index of user, and the transshipment charge contributory value of each user is determined by last Shapley value.The transshipment charge contributory value of user i is C _i=C × z _i, wherein C is total fixed cost, z _ifor the amortization ratio of user i.

The Shapley value of contributrion margin and Game with Coalitions: at least one user of random choose is combined into alliance from user, for member k arbitrary in any alliance, its contributrion margin is c (S)-c (S-{k}), Game with Coalitions has the definition of multiple solution, comprises core (core), nucleon (nucleolus), stable set (stableset), bargaining set (bargainingset), core (kernel) and Charolais cattle (Shapleyvalue) etc.

The definition of the Charolais cattle another solution of Game with Coalitions that to be Shapley propose in nineteen fifty-three, due to the relative simplicity that any Game with Coalitions all exists Shapley value solution and calculates, be widely used till now from proposition, therefore the present invention is also using the solution of Shapley value as Game with Coalitions always.The Split Factor of i-th user is

Wherein, i represents i-th user participating in fixed cost cost allocation; N represents the total number of users participating in transmission fixed cost allocation; S represents the number of user in alliance S; C (S) represents the income of alliance S; C (S-{k}) represents the income removing k in alliance S; C (S)-c (S-{k}) represents because user k coalizes the fixed cost that S shares to alliance.

The object of composition alliance S obtains minimum alliance apportioning cost c (S), can pass through to separate following linear programming:

$c\left(S\right)=\underset{\mathrm{\ω}}{\min }\underset{e=1}{\overset{E}{\Σ}}{\mathrm{\ω}}_e{x}_e\left(S\right)$

wherein, E is total number of standardized index, x _ebe e and refer to target value, ω _eit is the parameter of e index.

Then ask its Shapley value, obtain its optimal distribution ratio z=(z ₁..., z _n) ∈ R, wherein, z _irepresent the ratio of the fixed cost that user i shares, i=1 ..., n.

Table 3 has AR constraints Xia Ge alliance characteristic function

The Shapley value of the Game with Coalitions under table 4 has AR to retrain

User's name	User A	User B	User C	User D
					Shapley value	0.3820	0.3213	0.1346	0.1621

Table 5 is without AR constraints Xia Ge alliance characteristic function

Table 6 retrains the Shapley value of Xia Ge alliance without AR

User's name	User A	User B	User C	User D
					Shapley value	0.3411	0.2318	0.1853	0.2418

Table 3, table 4 are respectively the Shapley value that guaranteed region (AR) retrains Xia Ge alliance characteristic function and Game with Coalitions, and table 5, table 6 are respectively the Shapley value that unsecured region (AR) retrains Xia Ge alliance characteristic function and each alliance.4 respectively can to find table from this, guaranteed range constraint to share result more fair, more stable.

As shown in Figure 5, for the comparison diagram of the amortization ratio that the inventive method and traditional postage stamp method, AR-Shapley value obtain, The inventive process provides positive Economic Stimulus signal as seen from the figure, make participant while making great efforts to reduce self contributory value, decrease the common cost of whole Major Leagues.

Above embodiment is only and technological thought of the present invention is described, can not limit protection scope of the present invention with this, and every technological thought proposed according to the present invention, any change that technical scheme basis is done, all falls within scope.

Claims (5)

1., based on a methodology for Shapley value wind-electricity integration system fixed cost of power transmission, it is characterized in that: comprise the steps:

Step 1, utilize Monte Carlo model to simulate wind power output scene to obtain wind power output scene collection, and generate the wind power output data of each time period according to the time period of presetting;

Step 2, utilize scene "flop-out" method to reduce the wind power output scene collection that step 1 obtains, obtain the approximate scene subset of this scene collection;

Step 3, obtain the basic condition of each user in wind-electricity integration system, comprising: load season, working system, time-of-use tariffs Time segments division, peak valley ordinary telegram valency ratio, the quality of power supply and power consumption;

Step 4, the basic condition of each user to be normalized, to obtain the standardized index of each user;

Step 5, step 2 is reduced after contextual data and the standardized index data of each user that obtain of the step 4 Shapley value of carrying out under guaranteed range constraint calculate, obtain the Shapley value that each user is corresponding, Shapley value corresponding for each user is multiplied by fixed cost of power transmission, obtains each user and answer allocated cost.

2. as claimed in claim 1 based on the methodology of Shapley value wind-electricity integration system fixed cost of power transmission, it is characterized in that: utilize scene "flop-out" method to integrate the detailed process of reducing to the wind power output scene that step 1 obtains described in step 2 to be: the probability that known wind power output scene concentrates all scene numbers to occur as n and each scene i is as p _i, calculate scene and concentrate the distance between arbitrary scene and all scenes to obtain the distance matrix C of n*n, the arbitrary element c in C _ijrepresent the distance between scene i and scene j, be multiplied by the matrix B that C obtains n*n after the probabilistic that each scene occurs being become the matrix of 1*n, the arbitrary element b in matrix B _ij=p _i* c _ij, the scene of corresponding for least member value in B probability is deleted, i=1 ..., n, j=1 ..., n, is added to the probability deleting scene on the probability of the scene nearest with this scene distance, and repeats said process, till tapering to the scene number needing to retain.

3. as claimed in claim 1 based on the methodology of Shapley value wind-electricity integration system fixed cost of power transmission, it is characterized in that: described in step 4, standardized index comprises: straight purchase of electricity index, power quality index and tou power price index.

4., as claimed in claim 3 based on the methodology of Shapley value wind-electricity integration system fixed cost of power transmission, it is characterized in that: the computing formula of described tou power price index is: $D_k=\underset{a=1}{\overset{l}{\Σ}}{T}_a({\mathrm{\α}}_a{t}_{ka,f}+t_{ka,p}+{\mathrm{\β}}_a{t}_{ka,g}),k=1,...,m,$ Wherein, D _kfor the tou power price index of a kth user, m is total number of users, and l is the typical number of days divided for each user, T _afor the number of days that typical case day a is corresponding, α _a: 1: β _afor peak, flat, the paddy electricity price ratio of typical case day a, t _{ka, f}, t _{ka, p}, t _{ka, g}be respectively user k at the peak of typical case day a, flat, paddy utilizes hourage.

5., as claimed in claim 1 based on the methodology of Shapley value wind-electricity integration system fixed cost of power transmission, it is characterized in that: described in step 5, the computing formula of Shapley value is: ${\mathrm{\φ}}_k=\frac{1}{m!}\underset{S:k\∈s\∈M}{\Σ}(s-1)!(m-s)!\{c\left(S\right)-c(S-\{k\left\}\right)\},$ Wherein, φ _kfor the Shapley value of a kth user, m is total number of users, and S is the alliance of user, and s is the number of user in user coalitions, the marginal contribution value that c (S)-c (S-{k}) is user k, and M is the set of all users.