CN108537393B - Opportunity constraint planning-based cross section optimization method for wind power plant outgoing transmission line - Google Patents
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Abstract
The invention relates to a wind power plant outgoing transmission line section optimization method based on opportunity constraint planning. The method comprises the steps of considering randomness of temperature and wind speed, aiming at the maximum social benefit expected value, including wind power income sent by a wind power plant sending project year, wind abandon punishment cost, power transmission line investment cost, line power transmission loss cost and line operation and maintenance cost, establishing an opportunity constraint planning model for wind power sending lead section selection based on transmission constraint and wind abandon constraint of confidence level, and realizing wind power plant sending line section optimization.
Description
Technical Field
The invention relates to power transmission line section optimization, in particular to a wind power plant outgoing power transmission line section optimization method based on opportunity constraint planning.
Background
The wind power resource is generally far away from the load center, and a matched remote transmission line needs to be constructed to transmit electric energy to the load center. For safe operation of the grid, the maximum transmission capacity of the transmission line is typically the maximum constant allowed transmission capacity calculated under the most severe environmental conditions, such as extremely high temperatures and extremely low wind speeds. Because actual meteorological conditions are often not calculated and the meteorological conditions are severe, the transmission capacity constraint of the existing power transmission line is relatively conservative, the upper limit of the transmittable power is reduced, and the economic operation of the power system is not facilitated. In order to improve the transmission capacity, the actual engineering generally selects a larger cross-sectional area of the conducting wire, so that the engineering investment is increased, the utilization efficiency of a transmission line is reduced, and the economical efficiency of the transmission engineering is not facilitated, especially for a long-distance transmission line.
The existing research basically relates to the optimization of the wind power delivery capacity, the type selection of a section and the transmission capability of a power transmission project are not further optimized, and the optimal sectional area of a lead is selected by adopting an opportunity constraint planning model based on the randomness of wind speed and temperature, so that the cost of an over-conservative decision scheme is reduced, and the maximization of social benefit is realized.
Disclosure of Invention
The invention aims to provide a wind power plant outgoing power transmission line section optimization method based on opportunity constraint planning, which considers the randomness of temperature and wind speed meteorological factors and maximizes social benefits of a wind power plant and an outgoing project thereof to establish a wind power plant outgoing power transmission line section optimization model based on opportunity constraint planning, thereby providing an effective method for line selection of a wind power plant outgoing line section.
In order to achieve the purpose, the technical scheme of the invention is as follows: a method for optimizing the cross section of a wind power plant outgoing transmission line based on opportunity constraint planning considers the randomness of temperature and wind speed, takes the maximum social benefit expectation value as a target, comprises the income of wind power sent out by a wind power plant in an engineering year, the penalty cost of wind abandonment, the investment cost of the transmission line, the loss cost of line transmission and the operation and maintenance cost of the line, establishes an opportunity constraint planning model for wind power sending out wire cross section selection based on the transmission constraint and the wind abandonment constraint of a confidence level, and realizes the optimization of the cross section of the wind power plant outgoing line.
In an embodiment of the present invention, the method specifically includes the following steps:
step S1: acquiring historical meteorological data around a power transmission line sent by a wind power plant, and researching the distribution rule of the meteorological data through the historical data;
step S2: sampling environmental temperature and wind speed in historical meteorological data by utilizing a Latin hypercube sampling method: according to the ambient temperature taAnd the distribution rule of the wind speed V, sampling the environment temperature and the wind speed by a Latin hypercube sampling method, extracting N samples, namely N scenes, wherein the s-th scene is expressed as X(s) ═ ta(s), v(s), s ═ 1,2, …, N, probability of s-th scene is p(s);
step S3: establishing an opportunity constraint planning-based wind power plant outgoing transmission line section optimization objective function: because the environmental temperature and the wind speed have randomness, the maximum current-carrying capacity of the lead is a random variable, the maximum transmission power and the social benefit of the lead are also random variables, the annual wind power income, the wind abandoning punishment cost, the investment cost of the power transmission line, the power transmission loss cost of the line and the operation and maintenance cost of the line are considered, and the social benefit expectation value is the maximum target, and the function is as follows:
f(Sline,X(s))＝pwQw-pqQq-Ct-Cploss-Cop
in the formula: e degree]Is a mathematical expectation; f (S)lineX (s)) is social benefit; cross section area S of wirelineIs an optimized variable; p is a radical ofwThe price of the wind power grid is the price of the wind power grid; p is a radical ofqPunishment coefficient for abandoned wind; qwThe annual wind power output electric quantity; qqThe wind power is abandoned for the year; qzThe total annual generated energy of wind power is obtained; ctInvesting for equal annual value of the transmission line; cplossAnnual transmission loss cost of a line is sent out for the wind power plant; copAnnual operation and maintenance cost of a line is sent out of the wind power plant;
step S4: establishing an opportunity constraint planning-based optimization constraint condition of the cross section of the wind power plant outgoing transmission line:
1) wind farm output constraint
0≤Pw,t≤Pw_max
Pc,t+Pq1,t＝Pw,t
2) Wire cross-sectional area constraint
Sline_min≤Sline≤Sline_max
3) Wind farm outbound line transmission power constraints
Pr{Pl,t≥Pc,t}≥α
4) Wind curtailment rate constraint of wind power
Pr{δwloss≤δN}≥β
In the formula: pw_maxThe upper limit of the output of the wind power plant is defined; pw,t、Pc,t、Pq1,tThe output of the wind power plant, the output of the wind power plant and the wind power abandoned wind power at the moment t are measured; sline_minAnd Sline_maxThe lower limit and the upper limit of the sectional area of the lead are respectively; pr{ ° is the probability that an event is true in { ° }; alpha, beta areA confidence level of a predetermined constraint; pl,tMaximum transmission power of the line at the time t; pw,tWind power output at the moment t; deltawlossThe wind abandoning rate of the wind power is obtained; deltaNThe wind abandon rate allowed by wind power is obtained;
step S5: and solving the model by utilizing a particle swarm optimization algorithm to obtain the optimal sectional area of the wind power plant outgoing transmission line.
In an embodiment of the present invention, the specific implementation steps of step S3 are as follows:
step S31: calculating the current-carrying capacity of the wire by using a mole root formula according to the environment temperature, and determining the maximum transmission power of the wire according to the current-carrying capacity of the wire; when the temperature rise of the lead is allowed to be the same, under a certain lead section, the maximum current-carrying capacity corresponding to different environmental temperatures and different wind speeds is different, and the conveyable capacity of the lead is different; the relationship between the maximum transmission power and the maximum current-carrying capacity of the wire is as follows:
in the formula: i istThe maximum current-carrying capacity of the lead corresponding to the ambient temperature in the period t; pl,tMaximum transmission power of the line at the time t; u is the line voltage grade;
a power factor for the line transmission power;
step S32: calculating the investment cost of the wind power plant outgoing transmission line according to a cost equal-year value method:
the equal-year value calculation formula of the transmission line investment is as follows:
in the formula: y is the investment per unit length of the unit area of the power transmission line; slineIs the sectional area of the wire; l is the length of the transmission conductor; n istA static investment recovery period for the transmission line; r is labelCurrent rate;
step S33: calculating annual transmission loss cost of wind power station outgoing transmission line:
Cploss＝p×Qploss
Qploss＝Qw×β×L
in the formula: p is the average electricity price; qplossPower consumption for annual line losses; beta is the loss rate of the line per unit length;
step S34: the calculation formula of the annual line operation and maintenance cost is as follows:
Cop＝α×L
in the formula: alpha is the operation and maintenance cost of a unit length of a line of one year.
Compared with the prior art, the invention has the following beneficial effects: the method considers that the environment temperature and the wind speed have randomness, the maximum current-carrying capacity of the lead is a random variable, and the maximum transmission power of the lead is also a random variable, so that the transmission capacity limit of the line and the wind abandon rate limit caused by the transmission capacity limit are restrained in a probability mode, a cross section optimization model of the sent line considering the maximization of the social benefit of the wind power plant transmission project is established, and the optimal cross section meeting the confidence level constraint is obtained on the basis of fully excavating the transmission potential of the lead.
Drawings
Fig. 1 is a diagram illustrating lead cross-section selection and social benefit intent with commensurate changes in confidence levels in an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is specifically explained below with reference to the accompanying drawings.
The invention relates to a method for optimizing the cross section of a wind power plant outgoing transmission line based on opportunity constraint planning, which considers the randomness of temperature and wind speed, takes the maximum social benefit expectation value as a target, and comprises wind power plant outgoing engineering year outgoing wind power income, wind abandonment punishment cost, transmission line investment cost, line transmission loss cost and line operation and maintenance cost, establishes an opportunity constraint planning model for wind power plant outgoing conductor cross section selection based on transmission constraint and wind abandonment constraint of a confidence level, and realizes the optimization of the wind power plant outgoing line cross section. The method comprises the following concrete implementation steps:
step S1: acquiring historical meteorological data around a power transmission line sent by a wind power plant, and researching the distribution rule of the meteorological data through the historical data;
step S2: sampling environmental temperature and wind speed in historical meteorological data by utilizing a Latin hypercube sampling method: according to the ambient temperature taAnd the distribution rule of the wind speed V, sampling the environment temperature and the wind speed by a Latin hypercube sampling method, extracting N samples, namely N scenes, wherein the s-th scene is expressed as X(s) ═ ta(s), v(s), s ═ 1,2, …, N, probability of s-th scene is p(s);
step S3: establishing an opportunity constraint planning-based wind power plant outgoing transmission line section optimization objective function: because the environmental temperature and the wind speed have randomness, the maximum current-carrying capacity of the lead is a random variable, the maximum transmission power and the social benefit of the lead are also random variables, the annual wind power income, the wind abandoning punishment cost, the investment cost of the power transmission line, the power transmission loss cost of the line and the operation and maintenance cost of the line are considered, and the social benefit expectation value is the maximum target, and the function is as follows:
f(Sline,X(s))＝pwQw-pqQq-Ct-Cploss-Cop
in the formula: e degree]Is a mathematical expectation; f (S)lineX (s)) is social benefit; cross section area S of wirelineIs an optimized variable; p is a radical ofwThe price of the wind power grid is the price of the wind power grid; p is a radical ofqPunishment coefficient for abandoned wind; qwThe annual wind power output electric quantity; qqThe wind power is abandoned for the year; qzThe total annual generated energy of wind power is obtained; ctInvesting for equal annual value of the transmission line; cplossAnnual transmission loss cost of a line is sent out for the wind power plant; copAnnual operation and maintenance cost of a line is sent out of the wind power plant;
step S4: establishing an opportunity constraint planning-based optimization constraint condition of the cross section of the wind power plant outgoing transmission line:
the optimal constraint conditions of the cross section of the wind power plant outgoing transmission line based on opportunity constraint planning comprise wind power plant output constraint, wire sectional area constraint, wind power plant outgoing line transmission power constraint and wind power plant wind curtailment rate constraint. Because the ambient temperature and the wind speed have randomness, the maximum current-carrying capacity of the wire is a random variable, and the maximum transmission power of the wire is also a random variable. Opportunistic constraint planning is mainly directed to the case where the constraint conditions contain random variables and the decision must be made before the realization of the random variables is observed. Considering that the decision made may not satisfy the constraint condition when the adverse condition occurs, a principle is adopted: i.e. to allow the decision to be made to a degree that the constraint is not satisfied, but the decision should be such that the probability that the constraint is satisfied is not less than a certain confidence level. Therefore, aiming at the transmission power constraint and the wind curtailment constraint related to the transmission capacity, the invention expresses the transmission capacity limit and the wind curtailment rate constraint of the line in a probabilistic way, and avoids the situation that the section selection of the wire is too conservative to reduce the economy of the project. The constraints are specifically as follows:
1) wind farm output constraint
0≤Pw,t≤Pw_max
Pc,t+Pq1,t＝Pw,t
2) Wire cross-sectional area constraint
Sline_min≤Sline≤Sline_max
3) Wind farm outbound line transmission power constraints
Pr{Pl,t≥Pc,t}≥α
4) Wind curtailment rate constraint of wind power
Pr{δwloss≤δN}≥β
In the formula: pw_maxThe upper limit of the output of the wind power plant is defined; pw,t、Pc,t、Pq1,tThe output of the wind power plant, the output of the wind power plant and the wind power abandoned wind power at the moment t are measured; sline_minAnd Sline_maxThe lower limit and the upper limit of the sectional area of the lead are respectively; pr{ ° is the probability that an event is true in { ° }; alpha and beta are confidence levels of preset constraint conditions; pl,tMaximum transmission power of the line at the time t; pw,tWind power output at the moment t; deltawlossThe wind abandoning rate of the wind power is obtained; deltaNThe wind abandon rate allowed by wind power is obtained;
step S5: and solving the model by utilizing a particle swarm optimization algorithm to obtain the optimal sectional area of the wind power plant outgoing transmission line.
The specific implementation steps of step S3 are as follows:
step S31: calculating the current-carrying capacity of the wire by using a mole root formula according to the environment temperature, and determining the maximum transmission power of the wire according to the current-carrying capacity of the wire; when the temperature rise of the lead is allowed to be the same, under a certain lead section, the maximum current-carrying capacity corresponding to different environmental temperatures and different wind speeds is different, and the conveyable capacity of the lead is different; the relationship between the maximum transmission power and the maximum current-carrying capacity of the wire is as follows:
in the formula: i istThe maximum current-carrying capacity of the lead corresponding to the ambient temperature in the period t; pl,tMaximum transmission power of the line at the time t; u is the line voltage grade;
a power factor for the line transmission power;
step S32: calculating the investment cost of the wind power plant outgoing transmission line according to a cost equal-year value method:
the equal-year value calculation formula of the transmission line investment is as follows:
in the formula: y is the investment per unit length of the unit area of the power transmission line; slineIs the sectional area of the wire; l is the length of the transmission conductor; n istA static investment recovery period for the transmission line; r is the discount rate;
step S33: calculating annual transmission loss cost of wind power station outgoing transmission line:
Cploss＝p×Qploss
Qploss＝Qw×β×L
in the formula: p is the average electricity price; qplossPower consumption for annual line losses; beta is the loss rate of the line per unit length;
step S34: the calculation formula of the annual line operation and maintenance cost is as follows:
Cop＝α×L
in the formula: alpha is the operation and maintenance cost of a unit length of a line of one year.
The following are specific examples of the present invention.
Example (b): the total installed capacity of the wind power plant group is 891MW, and the wind power grid-connected electricity price pw0.6 yuan/(kW h), wind abandon penalty coefficient pqThe length L of the power transmission line is 63.5km, the investment I of the unit capacity and the unit length of the power transmission line is 100 ten thousand yuan/(MW 100km), and the investment recovery period of the power transmission line is 20 years; the operation and maintenance cost alpha of the unit length of the line is 5406 yuan/km, the loss rate beta of the unit length of the line is 0.05 percent, and the discount rate r is 8 percent; wind power allowable wind curtailment rate deltaNThe content was 5%.
As can be seen from fig. 1, as the confidence level in the constraints increases, the selected wire cross-section tends to increase, while the social benefit gradually decreases. The more conservative the transmission capacity estimation of the transmission line is, the larger the wire section required by the wind power delivery is, the more the investment cost is increased, and the social benefit is reduced.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.
Claims (2)
1. A method for optimizing the cross section of a wind power plant outgoing transmission line based on opportunity constraint planning is characterized in that randomness of temperature and wind speed is considered, a social benefit expected value is the maximum target, the method comprises wind power plant outgoing project year-out wind power income, wind abandoning punishment cost, transmission line investment cost, line transmission loss cost and line operation and maintenance cost, an opportunity constraint planning model for wind power plant outgoing conductor cross section selection is established based on transmission constraint and wind abandoning constraint of a confidence level, and optimization of the wind power plant outgoing line cross section is achieved; the method comprises the following concrete implementation steps:
step S1: acquiring historical meteorological data around a power transmission line sent by a wind power plant, and researching the distribution rule of the meteorological data through the historical data;
step S2: sampling environmental temperature and wind speed in historical meteorological data by utilizing a Latin hypercube sampling method: according to the ambient temperature taAnd the distribution rule of the wind speed V, sampling the environment temperature and the wind speed by a Latin hypercube sampling method, extracting N samples, namely N scenes, wherein the s-th scene is expressed as X(s) ═ ta(s), v(s), s ═ 1,2, …, N, probability of s-th scene is p(s);
step S3: establishing an opportunity constraint planning-based wind power plant outgoing transmission line section optimization objective function: because the environmental temperature and the wind speed have randomness, the maximum current-carrying capacity of the lead is a random variable, the maximum transmission power and the social benefit of the lead are also random variables, the annual wind power income, the wind abandoning punishment cost, the investment cost of the power transmission line, the power transmission loss cost of the line and the operation and maintenance cost of the line are considered, and the social benefit expectation value is the maximum target, and the function is as follows:
f(Sline,X(s))＝pwQw-pqQq-Ct-Cploss-Cop
in the formula: e degree]Is a mathematical expectation; f (S)lineX (s)) is social benefit; cross section of wireProduct SlineIs an optimized variable; p is a radical ofwThe price of the wind power grid is the price of the wind power grid; p is a radical ofqPunishment coefficient for abandoned wind; qwThe annual wind power output electric quantity; qqThe wind power is abandoned for the year; qzThe total annual generated energy of wind power is obtained; ctInvesting for equal annual value of the transmission line; cplossAnnual transmission loss cost of a line is sent out for the wind power plant; copAnnual operation and maintenance cost of a line is sent out of the wind power plant;
step S4: establishing an opportunity constraint planning-based optimization constraint condition of the cross section of the wind power plant outgoing transmission line:
1) wind farm output constraint
0≤Pw,t≤Pw_max
Pc,t+Pq1,t＝Pw,t
2) Wire cross-sectional area constraint
Sline_min≤Sline≤Sline_max
3) Wind farm outbound line transmission power constraints
Pr{Pl,t≥Pc,t}≥α
4) Wind curtailment rate constraint of wind power
Pr{δwloss≤δN}≥β
In the formula: pw_maxThe upper limit of the output of the wind power plant is defined; pw,t、Pc,t、Pq1,tThe output of the wind power plant, the output of the wind power plant and the wind power abandoned wind power at the moment t are measured; sline_minAnd Sline_maxThe lower limit and the upper limit of the sectional area of the lead are respectively; pr{ ° is the probability that an event is true in { ° }; alpha and beta are confidence levels of preset constraint conditions; pl,tMaximum transmission power of the line at the time t; pw,tWind power output at the moment t; deltawlossThe wind abandoning rate of the wind power is obtained; deltaNThe wind abandon rate allowed by wind power is obtained;
step S5: and solving the model by utilizing a particle swarm optimization algorithm to obtain the optimal sectional area of the wind power plant outgoing transmission line.
2. The method according to claim 1, wherein the step S3 is implemented as follows:
step S31: calculating the current-carrying capacity of the wire by using a mole root formula according to the environment temperature, and determining the maximum transmission power of the wire according to the current-carrying capacity of the wire; when the temperature rise of the lead is allowed to be the same, under a certain lead section, the maximum current-carrying capacity corresponding to different environmental temperatures and different wind speeds is different, and the conveyable capacity of the lead is different; the relationship between the maximum transmission power and the maximum current-carrying capacity of the wire is as follows:
in the formula: i istThe maximum current-carrying capacity of the lead corresponding to the ambient temperature in the period t; pl,tMaximum transmission power of the line at the time t; u is the line voltage grade;
a power factor for the line transmission power;
step S32: calculating the investment cost of the wind power plant outgoing transmission line according to a cost equal-year value method:
the equal-year value calculation formula of the transmission line investment is as follows:
in the formula: y is the investment per unit length of the unit area of the power transmission line; slineIs the sectional area of the wire; l is the length of the transmission conductor; n istA static investment recovery period for the transmission line; r is the discount rate;
step S33: calculating annual transmission loss cost of wind power station outgoing transmission line:
Cploss＝p×Qploss
Qploss＝Qw×β×L
in the formula: p is the average electricity price; qplossPower consumption for annual line losses; beta is the loss rate of the line per unit length;
step S34: the calculation formula of the annual line operation and maintenance cost is as follows:
Cop＝α×L
in the formula: alpha is the operation and maintenance cost of a unit length of a line of one year.
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| CN109449967B (en) * | 2018-09-20 | 2022-05-13 | 国网福建省电力有限公司 | Wind power plant group delivery site selection and volume fixing combined optimization method considering load randomness |
| CN109741110B (en) * | 2019-01-07 | 2022-07-01 | 福州大学 | Opportunity constraint planning-based wind-hydrogen system joint optimization modeling method |
| CN109888770A (en) * | 2019-01-24 | 2019-06-14 | 福州大学 | Wind energy turbine set installed capacity optimization method based on chance constrained programming and fluctuation cost |
| CN111079982B (en) * | 2019-11-25 | 2023-06-09 | 上海电气风电集团股份有限公司 | Planning method, system, medium and electronic equipment for cable path of wind power plant |
| CN116384049B (en) * | 2023-02-07 | 2023-09-19 | 国网甘肃省电力公司经济技术研究院 | Wind-solar power generation centralized outgoing channel capacity opportunity constraint optimization method |
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| 考虑热载荷能力的风火打捆外送线路导线截面优化;林章岁;《电气技术》;20180228;第43-48页 * |
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