CN103904749A - Electric automobile orderly charging control method with wind power output fluctuation considered - Google Patents

Abstract

The invention discloses an electric automobile orderly charging control method with wind power output fluctuation considered. The method includes the following steps that (1) initialization is conducted on intraday power distribution network load information and intraday electricity price information; (2) wind power output information of a current period is read; (3) a charging station systematically judges whether a new electric automobile drives into the charging station or not; (4) according to expected parking time of electric automobiles in the charging station in the period, the maximum value tM of the parking time of all the vehicles is obtained, and the length T of optimization time of the time is calculated; (5) according to the constraint conditions and system information of a formula (please see the formula in the specification), the charging state xn of each electric automobile is determined, and orderly charging of the electric automobiles is achieved. The method is used for electric automobile orderly charging policy management after the electric automobiles and wind power are connected into a power grid at the same time, and the load peak-and-valley difference and user benefits are made to be optimal with load wind power output fluctuation stabilizing as the target, with electric automobile user charging expense, the peak-and-valley difference and the like as constraints and by the adoption of an optimization algorithm.

Description

A kind ofly consider the exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation

Technical field

The present invention relates to the orderly charge control method of a kind of electric automobile, specifically a kind ofly consider the exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation, belong to generation of electricity by new energy control technology field.

Background technology

The shortage of tradition fossil energy and consume the problem of environmental pollution causing excessively and make the focus that develops into of new forms of energy.Electric automobile attracts wide attention because of its zero discharge, advantage efficient, low noise, changes the full-fledged of electric facility and battery technology along with filling, and can estimate to have a large amount of electric automobiles access electrical networks.

After extensive electric automobile access electrical network, the economical efficiency that electric automobile causes is moved on power system planning the impact producing with it and be can not be ignored, if the charging load of electric automobile is not carried out to suitable control, will cause the increase of electrical network peak-valley difference, variation aggravation, grid loss to increase, affect the safe and stable operation of electrical network, the problem that meanwhile can bring utilization rate of equipment and installations to reduce, and for meeting the peak load demand increasing, must increase generate output, system cost of investment and operating cost also can increase thereupon.Therefore the electric automobile user behavior of charging is guided and control seems particularly important, need to be formulated the orderly charging strategy of charging electric vehicle behavior.

Nowadays, the grid-connected of regenerative resource is also one of study hotspot, wherein, wind energy resources is as one of the abundantest regenerative resource, and because the advantages such as regional limits is little, it is little to invest, cleanliness without any pollution cause extensive concern, China is also using Devoting Major Efforts To Developing wind generating technology as a fundamental state policy, but simultaneously, wind energy is also a kind of intermittent energy source, and its generating is subject to the various factors such as meteorological condition, and power output has discontinuous and uncertain feature.In addition, the power output of wind generator system also has very strong period of change, and this can produce periodic shock to electrical network.In the time that wind energy turbine set capacity reaches higher level, this impact meeting brings obvious impact to the stability of a system, even can cause system to lose stable.And generally speaking, domestic land wind-powered electricity generation generated output generally presents the feature that night is higher, daytime is lower, has anti-peak regulation characteristic.Therefore, wind-powered electricity generation access electrical network, its intrinsic and significant uncertainty and its anti-peak regulation characteristic are all brought huge challenge by the safety and stability economical operation of giving electrical network.

In future, wind-powered electricity generation unit, photovoltaic generating system distributed power supply and electric automobile will access electrical network on a large scale, and therefore, nowadays charging electric vehicle and regenerative resource cooperative scheduling are just becoming research emphasis both domestic and external.

Summary of the invention

Technical problem to be solved by this invention is to consider, on the fluctuation basis that wind-powered electricity generation is exerted oneself, to provide one can either safeguard electric automobile user interests, can stabilize again the orderly charge control method of electric automobile of wind-powered electricity generation and load fluctuation.

In order to solve the problems of the technologies described above, technical scheme of the present invention is:

Consider the exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation, comprise the following steps:

1) initialization power distribution network on same day load information and the same day electricity price information;

2) read the wind-powered electricity generation of current period and go out force information;

3) charging station system judges whether that new electric automobile sails charging station into, if had, reads the useful data information of all new access electric automobiles, if do not had, along the optimisation strategy of section between using for the moment;

4), according to the expected downtime of charging station electric automobile in this time period, obtain the maximum t of all stoppage of vehicle times _m, and calculate this suboptimization time span T,

for being less than or equal to the maximum integer of x;

5) exert oneself fluctuation effect optimum as target to stabilize wind-powered electricity generation, according to formula (1), constraints and system information, determine the charged state x of each electric automobile _n,j, realize the orderly charging of electric automobile:

$\min f=\frac{1}{J-1}\underset{j=1}{\overset{J}{\mathrm{\Σ}}}{(P_j-\stackrel{\‾}{P_a})}^2$ Formula (1)

Constraints: $B_{n,E}\≤\underset{j=t}{\overset{T+t-1}{\mathrm{\Σ}}}{x}_{n,j}{b}_n+B_{n,S}\≤0.95$

t _n,E≤T _n,E

$\underset{n=1}{\overset{n_j}{\mathrm{\Σ}}}{x}_{n,j}\≤N$

$\underset{j=t}{\overset{T+t-1}{\mathrm{\Σ}}}\underset{n=1}{\overset{n_j}{\mathrm{\Σ}}}{x}_{n,j}{\mathrm{Pp}}_j\mathrm{\Δt}\≤P_{\mathrm{total}}$

|P _max-P _min|<△P

Wherein: $\stackrel{\&OverBar;}{P_a}=\frac{1}{J}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{P}_j$

$P_j=\left\{\begin{array}{cc}{P}_{l.j}-P_{w,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P& j\&Element;[t,t+T-1]\\ P_{l,j}-P_{w,j}+P_{e,j}& j\&Element;[1,t-1]\end{array}\right.$

$\left\{\begin{array}{c}{P}_{\min }=\min (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\\ P_{\max }=\max (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\end{array}\right.$

In above-mentioned formula, segment value when t is current, x _n,jbe n electric automobile in the charging decision-making of j time period, x _n,j=1 is charging for electric automobile, x _n,j=0 is that electric automobile is uncharged; n _jbe j time period electric automobile sum to be charged; P is charging electric vehicle power; P _l,jbe j load in some time value; P _w,jbe that j time period wind-powered electricity generation goes out activity of force; P _e,jfor last time optimization finishes rear j period charging electric vehicle gross power; B _n,Sbe the SOC numerical value of n current period of electric automobile, within T time period, required final state-of-charge B when the battery charge state of the electric automobile being charged should at least reach charging beginning _n,E, in the situation that being full of, should stop charging simultaneously, for ensureing battery life, be within 0.95 o'clock, to think to be full of at state-of-charge; b _nfor an increasable battery SOC of period (being the state-of-charge of the battery) numerical value that charges; t _n,Eit is n charging electric vehicle end time; T _n,Efor the expection that this electric automobile user sets is charged the end time; N is charging pile quantity in charging station; p _jit is the electricity price of t time period; △ t is the time interval; T is the maximum of the expected downtime section of electric automobile in current slot; P _totalinitial value be set to: if the electricity price of each period is when minimum, the needed expense of electric automobile that all participations are optimized, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, P _totalprogressively increase 1%, until there is solution; P _maxand P _minsystem loading maximum and minimum value in finishing during this period of time since morning on the same day to the current optimization time period respectively; In conjunction with the peak valley difference of this period in seven days in the past, △ P initial value is decided to be this period peak-valley difference minimum value in these seven days, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, △ P progressively increases 1%, until there is solution.

In residential quarter, electric automobile is rested on normal charge in charging station by all used for electric vehicle selections per family, electric automobile park and the place of charging is fixed, b _nthink fixed value, △ t is 15min.

A kind of exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation of considering of the present invention, for the extensive grid-connected fluctuation causing of wind-powered electricity generation, by the orderly charging behavior of regulation and control electric automobile, level and smooth load fluctuation, access the orderly charging tactical management of electric automobile after electrical network for electric automobile and wind-powered electricity generation simultaneously, exert oneself fluctuation as target to stabilize load wind-powered electricity generation, the electric automobile user expense of charging, peak-valley differences etc. are constraint, adopt optimized algorithm, load peak-valley difference and user benefit have been taken into account simultaneously, system side and the doulbe-sides' victory of user's side are reached, peak-valley difference and user benefit optimum make to load.Compared with the orderly charge control method of existing electric automobile, adopt this method both to stabilize wind-powered electricity generation and load fluctuation, meet again user's charging electric vehicle interests demand.

Brief description of the drawings

Fig. 1 is the flow chart of the inventive method.

Fig. 2 is for adopting the inventive method front and back electrical network total load curve comparison figure.

Embodiment

Below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.

Taking a residential quarter as example, charging electric vehicle timesharing rolling optimization control method is proposed.Suppose the time to be divided into 96 time periods, the time is spaced apart 15min, according to historical routine data, can predict 96 conventional load data on the same day, and as shown in Figure 1, concrete optimal control method is as follows:

1) initialization power distribution network on same day load information and the same day electricity price information.

The present embodiment initialization power distribution network on same day load information is: this community has 780 resident families, and each household resident has an automobile, and wherein electric automobile has 100, and electric automobile permeability is 12.8%; Peak of power consumption period, average each household residential electricity consumption 4kW, resident's total load top is 3120kW; Electric automobile all uses lithium ion, and supposes its battery rated voltage 320V, rated capacity 100Ah, supposes that normal charge power is 7kW, and each electric automobile charges once every day.The same day, electricity price information adopted tou power price, and when charger assembled by several branch, electric price parameter arranges as shown in table 1.

Table 1 electric price parameter arranges table

2) read the wind-powered electricity generation of current period and go out force information.

The present embodiment supposition distribution scheduling center can be read in real time current period wind-powered electricity generation and be gone out force information.

3) charging station system judges whether that new electric automobile sails charging station into, if had, reads the useful data information of all new access electric automobiles.If no, along the optimisation strategy of using section between a period of time.

The present embodiment utilizes monte carlo method, produces at random multiple required charging electric vehicle data, and concrete data are as shown in table 2.

Table 2 charging electric vehicle data setting table

4), according to the expected downtime of charging station electric automobile in this time period, obtain the maximum t of all stoppage of vehicle times _m, and calculate this suboptimization time span T.

for being less than or equal to the maximum integer of x.

Get t _mfor 65min,

5) exert oneself fluctuation effect optimum as target to stabilize wind-powered electricity generation, according to formula (1), constraints and system information, determine the charged state x of each electric automobile _n,j, realize the orderly charging of electric automobile:

$\min f=\frac{1}{J-1}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{(P_j-\stackrel{\&OverBar;}{P_a})}^2$ Formula (1)

Constraints: $B_{n,E}\&le;\underset{j=t}{\overset{T+t-1}{\mathrm{\&Sigma;}}}{x}_{n,j}{b}_n+B_{n,S}\&le;0.95$

t _n,E≤T _n,E

$\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}\&le;N$

$\underset{j=t}{\overset{T+t-1}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}{\mathrm{Pp}}_j\mathrm{\&Delta;t}\&le;P_{\mathrm{total}}$

|P _max-P _min|<△P

Wherein: $\stackrel{\&OverBar;}{P_a}=\frac{1}{J}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{P}_j$

$P_j=\left\{\begin{array}{cc}{P}_{l.j}-P_{w,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P& j\&Element;[t,t+T-1]\\ P_{l,j}-P_{w,j}+P_{e,j}& j\&Element;[1,t-1]\end{array}\right.$

$\left\{\begin{array}{c}{P}_{\min }=\min (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\\ P_{\max }=\max (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\end{array}\right.$

In above-mentioned formula, segment value when t is current, x _n,jbe n electric automobile in the charging decision-making of j time period, x _n,j=1 is charging for electric automobile, x _n,j=0 is that electric automobile is uncharged; n _jbe j time period electric automobile sum to be charged; P is charging electric vehicle power; P _l,jbe j load in some time value; P _w,jbe that j time period wind-powered electricity generation goes out activity of force; P _e,jfor last time optimization finishes rear j period charging electric vehicle gross power; B _n,Sbe the SOC numerical value of n current period of electric automobile, within T time period, required final state-of-charge B when the battery charge state of the electric automobile being charged should at least reach charging beginning _n,E, in the situation that being full of, should stop charging simultaneously, for ensureing battery life, be within 0.95 o'clock, to think to be full of at state-of-charge; b _nfor the increasable battery SOC numerical value of period that charges; t _n,Eit is n charging electric vehicle end time; T _n,Efor the expection that this electric automobile user sets is charged the end time; N is charging pile quantity in charging station; p _jit is the electricity price of t time period; △ t is the time interval; T is the maximum of the expected downtime section of electric automobile in current slot; P _totalinitial value be set to: if the electricity price of each period is when minimum, the needed expense of electric automobile that all participations are optimized, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, P _totalprogressively increase 1%, until there is solution; P _maxand P _minsystem loading maximum and minimum value in finishing during this period of time since morning on the same day to the current optimization time period respectively; In conjunction with the peak valley difference of this period in seven days in the past, △ P initial value is decided to be this period peak-valley difference minimum value in these seven days, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, △ P progressively increases 1%, until there is solution.

Electrical network total load curve when equivalent load after stack wind-powered electricity generation as shown in Figure 2 and electric automobile access are charged in order, electric automobile shown in associative list 3 does not access and charges in two kinds of situations in order, system loading peak-valley difference and load variance contrast table can be found out, consider to cause load fluctuation aggravation problem after wind-powered electricity generation access, by optimizing charging electric vehicle behavior, after electric automobile access grid charging, charging load has suppressed load fluctuation, load variance reduces approximately 13.4%, meanwhile, load peak-valley difference also reduces approximately 22.9%; And the charging electric vehicle time mainly concentrates on tou power price and underestimates the period, therefore, the inventive method had both been stabilized wind-powered electricity generation and load fluctuation, had safeguarded again electric automobile user's interests.

Table 3 adopts the inventive method front and back system peak-valley difference and variance contrast table

Above-described embodiment does not limit the present invention in any way, and every employing is equal to replaces or technical scheme that the mode of equivalent transformation obtains all drops in protection scope of the present invention.

Claims (2)

1. consider the exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation, it is characterized in that comprising the steps:

1) initialization power distribution network on same day load information and the same day electricity price information;

2) read the wind-powered electricity generation of current period and go out force information;

3) charging station system judges whether that new electric automobile sails charging station into, if had, reads the useful data information of all new access electric automobiles, if do not had, along the optimisation strategy of section between using for the moment;

4), according to the expected downtime of charging station electric automobile in this time period, obtain the maximum t of all stoppage of vehicle times _m, and calculate this suboptimization time span T,

for being less than or equal to the maximum integer of x;

5) exert oneself fluctuation effect optimum as target to stabilize wind-powered electricity generation, according to formula (1), constraints and system information, determine the charged state x of each electric automobile _n,j, realize the orderly charging of electric automobile:

$\min f=\frac{1}{J-1}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{(P_j-\stackrel{\&OverBar;}{P_a})}^2$ Formula (1)

Constraints: $B_{n,E}\&le;\underset{j=t}{\overset{T+t-1}{\mathrm{\&Sigma;}}}{x}_{n,j}{b}_n+B_{n,S}\&le;0.95$

t _n,E≤T _n,E

$\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}\&le;N$

$\underset{j=t}{\overset{T+t-1}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}{\mathrm{Pp}}_j\mathrm{\&Delta;t}\&le;P_{\mathrm{total}}$

|P _max-P _min|<△P

Wherein: $\stackrel{\&OverBar;}{P_a}=\frac{1}{J}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{P}_j$

$P_j=\left\{\begin{array}{cc}{P}_{l.j}-P_{w,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P& j\&Element;[t,t+T-1]\\ P_{l,j}-P_{w,j}+P_{e,j}& j\&Element;[1,t-1]\end{array}\right.$

$\left\{\begin{array}{c}{P}_{\min }=\min (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\\ P_{\max }=\max (P_{l,j}-P_{w,j}+P_{e,j}+\underset{n=1}{\overset{n_j}{\mathrm{\&Sigma;}}}{x}_{n,j}P)\end{array}\right.$

In above-mentioned formula, segment value when t is current, x _n,jbe n electric automobile in the charging decision-making of j time period, x _n,j=1 is charging for electric automobile, x _n,j=0 is that electric automobile is uncharged; n _jbe j time period electric automobile sum to be charged; P is charging electric vehicle power; P _l,jbe j load in some time value; P _w,jbe that j time period wind-powered electricity generation goes out activity of force; P _e,jfor last time optimization finishes rear j period charging electric vehicle gross power; B _n,Sbe the SOC numerical value of n current period of electric automobile, within T time period, required final state-of-charge B when the battery charge state of the electric automobile being charged should at least reach charging beginning _n,E, in the situation that being full of, should stop charging simultaneously, for ensureing battery life, be within 0.95 o'clock, to think to be full of at state-of-charge; b _nfor the increasable battery SOC numerical value of period that charges; t _n,Eit is n charging electric vehicle end time; T _n,Efor the expection that this electric automobile user sets is charged the end time; N is charging pile quantity in charging station; p _jit is the electricity price of t time period; △ t is the time interval; T is the maximum of the expected downtime section of electric automobile in current slot; P _totalinitial value be set to: if the electricity price of each period is when minimum, the needed expense of electric automobile that all participations are optimized, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, P _totalprogressively increase 1%, until there is solution; P _maxand P _minsystem loading maximum and minimum value in finishing during this period of time since morning on the same day to the current optimization time period respectively; In conjunction with the peak valley difference of this period in seven days in the past, △ P initial value is decided to be this period peak-valley difference minimum value in these seven days, but this value is likely because the optimisation strategy that causes less than normal is without solution, if without solution, △ P progressively increases 1%, until there is solution.

2. according to a kind of exert oneself orderly charge control method of electric automobile of fluctuation of wind-powered electricity generation of considering claimed in claim 1, it is characterized in that, in residential quarter, electric automobile is rested on normal charge in charging station by all used for electric vehicle selections per family, electric automobile park and the place of charging is fixed, b _nbe fixed value, △ t is 15min.

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