CN116029114A - Comprehensive energy base optimal configuration method based on annual time sequence production simulation - Google Patents
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Abstract
The invention relates to a comprehensive energy base optimal configuration method based on annual time sequence production simulation, which comprises the following steps: step 1, building a unit output and unit state model, wherein the model comprises a wind power system output model, a photovoltaic system output model, a thermal power unit running state model and an energy storage system charge and discharge model; step 2, establishing a system economy optimization target, and calculating the whole life cycle cost including investment cost and operation and maintenance cost into annual average capacity cost; setting output constraint conditions, including system reliability constraint, output channel power constraint, thermal power unit output constraint, thermal power unit climbing constraint, energy storage system capacity constraint and energy storage system charging and discharging power constraint; and 4, solving and calculating. The invention can provide support for determining the installation scale of each power supply type in the integrated energy base project, and can solve the capacity configuration problem of each power supply type in the integrated energy base which is transmitted in a bundling way.
Description
Technical Field
The invention belongs to the technical field of power generation, and particularly relates to a comprehensive energy base optimal configuration method based on annual time sequence production simulation.
Background
The large-scale comprehensive energy base is developed on the power base, combines the local resource condition and the energy characteristic, adopts multi-energy varieties such as wind energy, solar energy, water energy, coal and the like to generate power to supplement each other according to local conditions, moderately increases a certain proportion of energy storage, and comprehensively plans, designs, builds and operates various power sources.
The method is a core scientific problem of integrated base project planning and design, and is used for defining the optimal configuration target of a large-scale comprehensive energy base and reasonably proportioning the loading capacity and the conveying capacity of thermal power, wind power, photovoltaic and energy storage. The optimization configuration target of the large-scale comprehensive energy base has two aspects, namely, the energy complementary optimization target built in the large-scale comprehensive energy base project is on the one hand, and the optimized power output target outside the large-scale comprehensive energy base project is on the other hand, and corresponds to project economic benefit and reliable and stable operation requirements of an electric power system respectively, so that the multi-aspect optimization operation requirements of normal operation states, abnormal states, power grids and the like are met. Therefore, the optimization of multiple constraints and different targets is the core content of the optimization configuration of the large-scale comprehensive energy base, and the multi-parameter unification of the new energy development quantity, the reliable and stable support of the power grid and the project economy is achieved together.
The large-scale comprehensive energy base is optimally configured, so that the complementary characteristics of all energy sources in the base are met, the power requirement of a load side is met, and the economic performance of a project and the reliability of a power system are respectively met. The current method for optimizing and configuring the large-scale comprehensive energy base mainly comprises the steps of collecting wind-light historical operation data of a target area, and obtaining power grid demand power generation amount at each moment in a historical period to obtain a new energy output curve and a load demand curve. Based on the wind power, complementation, thermal power and energy storage power generation capacity configuration calculation, a comprehensive energy base output curve under different configuration proportions is obtained, and a group of wind, light and fire storage capacity configuration proportions with the lowest cost are determined by taking the lowest cost as a principle.
The existing large-scale comprehensive energy base optimizing configuration method mostly adopts the history operation data of the new energy unit actually measured in the target area to optimize, and under the condition of insufficient basic data, the specific area is difficult to plan. In addition, the existing large-scale comprehensive energy base optimizing configuration method mainly aims at wind and light abandoning, total cost minimization and the like, does not comprehensively consider the optimizing configuration of an operation level, and has larger deviation between a configuration result and a time operation state.
Disclosure of Invention
The invention aims to provide a comprehensive energy base optimizing configuration method based on annual time sequence production simulation, which is characterized in that on the basis of analyzing the operation and characteristics of different power forms, output models of various power types are built, the system operation is simulated and optimized by adopting an annual time sequence production simulation method through analysis of wind-light resource distribution characteristics and historical data of a target area, basic conditions of a thermal power unit, performance parameters of an energy storage system and the like, and capacity optimizing configuration results of wind power, a photovoltaic system, a thermal power unit, the energy storage system and the like are obtained, so that the capacity configuration problem of all power types in an integrated comprehensive energy base which is transmitted in a bundling mode is solved.
The invention provides a comprehensive energy base optimal configuration method based on annual time sequence production simulation, which comprises the following steps:
step 1, building a unit output and unit state model, wherein the model comprises a wind power system output model, a photovoltaic system output model, a thermal power unit running state model and an energy storage system charge and discharge model;
the method for establishing the wind power system output model comprises the following steps:
before the output of the wind power generation system is calculated, correcting the wind speed of input wind speed data to the wind speed at the height of a hub of a fan, and simulating the property of the wind speed vertically distributed in flat terrain by a power function method, wherein the basic form is as follows:
in the method, in the process of the invention, v mounting height H for wind turbine WT Wind speed at; v r For reference height H r Lower measured wind speed; ζ is the coefficient of wind speed energy law, the properties of altitude, time, season, topography, wind speed, temperature, thermodynamic and mechanical mixing parametersChanging the reference value under the flat terrain to be 1/7;
calculating the output of the wind power generation system, wherein factors for determining the output of the wind power generation system comprise a power curve of the wind turbine, wind speed distribution of the position where the wind turbine is installed and the installation height of the wind turbine;
the model of the output power of the wind power generation system is shown in a formula (2), and the annual wind power output curve is obtained through calculation;
wherein P is N Is rated installed capacity; v c 、v N 、v f The cut-in wind speed, the rated wind speed and the cut-out wind speed of the wind turbine are respectively;
adding a reduction coefficient to correct the overall power output of the wind power generation system, wherein the total power output by the wind power plant is shown in a formula (3);
P WT ＝P WT ′×f 1 ×f 2 ×f 3 ×f 4 ×f 5 (3)
wherein P is WT The total power output by the wind farm; f (f) 1 The coefficient is reduced for wake; f (f) 2 For control and turbulence reduction coefficients; f (f) 3 The power curve guarantee rate reduction coefficient of the wind turbine generator system; f (f) 4 The power consumption, line loss and other reduction coefficients are used for the field; f (f) 5 In order to consider the interaction between large wind farms, the surrounding wind farms influence the reduction coefficient;
the building method of the photovoltaic system output model comprises the following steps:
calculating solar radiation absorbed by the photovoltaic panel on any inclined surface;
assuming that light Fu Banmian is placed in the south, only solar radiation on any inclined plane is calculated, and the calculation formula of the solar radiation on the inclined plane at different moments is shown as formula (4):
R β ＝S×[sin(h+θ)/sinh]+D (4)
wherein R is β Is the total solar radiation amount on the inclined plane; s is waterSolar direct radiation on a plane; d is the scattered radiation quantity; θ is the inclination of the inclined surface; h is the solar altitude, which changes continuously with time, and the solar altitude at different moments is confirmed by using each parameter, and the calculation method is as shown in formula (5):
in the method, in the process of the invention,
is the local latitude; sigma is solar declination; omega is the solar time angle;
the calculation formulas of the solar declination and the solar hour angle are shown as formula (6) and formula (7):
sinσ＝0.39795cos[0.98563(N-173)] (6)
ω＝15×(ST-12) (7)
wherein N is the product days arranged according to the sequence of days; ST is true solar energy, and 24 hours is taken as a period;
i=0, v=v in defining the open battery state OC The method comprises the steps of carrying out a first treatment on the surface of the Maximum power point, v=v m ，I＝I m The calculation formulas are shown as formula (8), formula (9) and formula (10):
short-circuit current I SC Open circuit voltage V OC Maximum power point current I m Maximum power point voltage V m As the amount of solar radiation or the temperature changes, the correction method is as shown in formula (11):
wherein I is SC ′、V OC ′、I m ′、V m ' is a correction value under different circumstances; t, T 0 Photovoltaic panel temperature and standard cell temperature (25 ℃ C.). G. G 0 For solar radiation and standard solar radiation; a. b and c are correlation coefficients;
the output power of the photovoltaic system with the loss factor is shown as a formula (12);
P PV ＝n×N 1 ×N 2 ×V×I×f c ×f 0 (12)
wherein P is PV The total power output by the photovoltaic system; n is the number of low-voltage cabinets of the photovoltaic system; n (N) 1 The number of the photovoltaic cells connected in series; n (N) 2 The number of strings of photovoltaic cells in each low-voltage cabinet is counted; f (f) c Introducing a factor for connection loss; f (f) 0 Introducing factors for other losses;
the method for establishing the running state model of the thermal power generating unit comprises the following steps:
the peak regulating capacity of the thermal power generating unit under the normal running condition is as shown in formula (13):
wherein P is i,min The minimum operation output of the ith thermal power unit at the time t is P i,t Represents the active power of the ith thermal power unit at the moment t, U i,t Represents the start-stop state of the ith thermal power generating unit at the moment t, U i,t =0 indicates shutdown of the thermal power generating unit, U i,t =1 indicates that the thermal power generating unit is in start-up operation;
the method for establishing the charge and discharge model of the energy storage system comprises the following steps:
during the operation of the system, the operation state of the energy storage system is divided into a charging state, a discharging state and an electric quantity static state;
the condition that the battery pack is in a charged state is shown in a formula (14);
the change of the electric quantity of the battery pack in a charged state is shown in a formula (15);
the condition that the battery pack is in a discharge state is shown in a formula (16);
the change of the electric quantity of the battery pack in a discharging state is shown in a formula (17);
the power generation amount of the system is equal to the power consumption amount of the load, as shown in a formula (18);
(W WT (t)+W PV (t)+W T (t))×η inv -E L (t)＝0 (18)
the energy supply of the system is insufficient, and the battery pack stops discharging as shown in a formula (19);
the system is in an overcharged state, and the battery pack stops charging as shown in a formula (20);
the battery pack is in a static state as shown in formula (21);
E B (t)＝E B (t-1) (21)
in which W is WT (t) the generated energy and the electric quantity value of the wind power generation system at the moment t; w (W) PV (t) the generated energy and the electric quantity value of the photovoltaic system at the moment t; w (W) T (t) is the generated energy and the electric quantity value of the thermal power system at the moment t; e (E) L (t) is the load electricity consumption at the moment t, and the electricity value; η (eta) inv Inversion efficiency; η (eta) Bc Charging efficiency of the battery; η (eta) Dc Is the discharge efficiency of the storage battery;
step 2, establishing a system economy optimization target, and calculating the whole life cycle cost including investment cost and operation and maintenance cost into annual average capacity cost, wherein the method specifically comprises the following steps of:
the economic evaluation of the life cycle of the system comprehensively considers the investment cost and the operation and maintenance cost of the wind power system, the photovoltaic system, the thermal power unit and the energy storage system;
the annual average power generation cost calculating method is as shown in the formula (22):
C＝(C acap (PV+Wind+Bat+Thermal)+C amain (PV+Wind+Bat+Thermal))/P out (22)
wherein: c (C) acap Initial investment for each part; p (P) out Output power of the system in whole year; c (C) amain For annual operation and maintenance cost, the operation and maintenance cost of the thermal power unit comprises the operation and maintenance cost of the unit and the coal consumption cost of thermal power operation, and the calculation method is as shown in formula (23):
A(P T )＝S coal (a(P T ) 2 +bP T +c) (23)
wherein A (P T ) Representing the coal consumption cost of the thermal power unit; p (P) T Representing the actual output power of the thermal power generating unit; s is S coal The price of the standard coal purchased by the thermal power plant is represented by the unit: the meta/t, a, b and c represent coal consumption characteristic parameters of the thermal power unit;
step 3, setting output constraint conditions, including system reliability constraint, output channel power constraint, thermal power unit output constraint, thermal power unit climbing constraint, energy storage system capacity constraint and energy storage system charge and discharge power constraint;
the system reliability constraint adopts annual load electricity shortage rate as a constraint index of the system reliability, as shown in a formula (24);
where T is the number of hours of Time data entered, time (P available (t)<P needed (t)) load off-time refers to the time when the system fails to meet the load power demand when the battery in the system is depleted and the other power sources are undercharged;
the outgoing channel power constraint is as shown in equation (25):
P total ≤P tomax (25)
wherein: p (P) tomax The power upper limit value of the outgoing channel;
the output constraint of the thermal power generating unit is shown as a formula (26);
P Tmin ≤P T ≤P Tmax (26)
wherein P is Tmax 、P Tmin The maximum and minimum output values of the thermal power generating unit are respectively obtained. The method comprises the steps of carrying out a first treatment on the surface of the
The climbing constraint of the thermal power generating unit is shown as a formula (27);
-△P Td ≤P T -P T (t- 1)≤△P Tu (27)
wherein DeltaP d 、△P u The maximum downward and upward climbing rates of the thermal power generating unit are respectively;
the energy storage system capacity constraint is as shown in formula (28);
E Bmin ≤E B ≤E Bmax (28)
wherein E is Bmax 、E Bmin The upper and lower limits of the capacity of the energy storage system are respectively set;
the charge and discharge power constraint of the energy storage system is shown as a formula (29);
-△P Bd ≤P B -P B (t- 1)≤△P Bu (29)
wherein DeltaP Bd 、△P Bu The charging and discharging power of the energy storage system and the charging power of the energy storage system are respectively;
step 4, solving and calculating: the method comprises the steps of connecting each wind power output model, each photovoltaic output model, each thermal power unit running state model and each energy storage system charging and discharging model in series based on an annual time sequence production simulation method to obtain a comprehensive energy base optimizing configuration model based on the annual time sequence production simulation method; the wind power output model and the photovoltaic output model input parameters are annual time-by-time wind speed data, direct radiation data, scattered radiation data and temperature data, the thermal power unit running state model and the energy storage system charge-discharge model input parameters are upper and lower limits at different moments and power change constraint, load data adopts time-by-time load data of different seasons on a demand side, the time-by-time load data of different seasons are expanded according to seasons, complete annual load data is obtained, iterative calculation is carried out on the model, and the solution of an optimal configuration model is realized.
By means of the scheme, the comprehensive energy base optimizing configuration method based on annual time sequence production simulation is used for constructing output models of various power supply types on the basis of analyzing operation and characteristics of different power supply forms, dependence on wind power and photovoltaic actual measurement operation data can be avoided through model calculation, and the difficulty in acquiring the data is reduced. The capacity optimization configuration results of the wind power system, the photovoltaic system, the thermal power system, the energy storage system and the like are obtained through analysis and optimization of wind-solar resource distribution characteristics of a target area, basic conditions of the thermal power unit, performance parameters of the energy storage system and the like, a certain support can be provided for determining the installation scale of each power supply type of the comprehensive energy base project, and the capacity configuration problem of each power supply type in the integrated comprehensive energy base which is bundled and sent out is solved.
The foregoing description is only an overview of the present invention, and is intended to provide a better understanding of the present invention, as it is embodied in the following description, with reference to the preferred embodiments of the present invention and the accompanying drawings.
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FIG. 1 is a flow chart of the method for optimizing and configuring the comprehensive energy base based on the annual time sequence production simulation.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
Referring to fig. 1, the embodiment provides a comprehensive energy base optimizing configuration method based on annual time sequence production simulation, which can calculate and obtain capacity configuration results of all power supply types in the integrated comprehensive energy base which is bundled and sent.
The optimal configuration of the comprehensive energy base project mainly depends on the resource conditions of wind power and photovoltaic in a target area, the adjustment capability of a thermal power unit and an energy storage system is fully utilized, the installed capacities of the wind power, the photovoltaic installation, the motor unit and the energy storage system are optimally matched, and the wind power and photovoltaic absorption utilization level is improved to the greatest extent. And determining the installed capacity, the thermal power and energy storage regulation operation mode and the output curve of each power supply form according to the intrinsic conditions of the source region and the load requirements of the receiving region.
The unit output and state model comprises a wind power output model, a photovoltaic output model, a thermal power unit running state model and an energy storage charging and discharging state model. After the economic optimization targets and the output constraint conditions of all power forms are set, the output model optimization variables are solved, and the comprehensive energy base project optimization configuration scheme is formed. The model input comprises wind power and photovoltaic resource conditions in the terminal sending area, load curves in the terminal receiving area in four seasons, different types of power supply cost, running cost and the like. The method comprises the following specific steps:
step S1, a unit output and unit state model is established, wherein the unit output and unit state model comprises a wind power system, a photovoltaic system time sequence output model, a thermal power unit running state model and an energy storage system running state model (an energy storage system charging and discharging model).
(1) Output model of wind power generation system
Before calculating the output of a wind power generation system, the wind speed of input wind speed data is corrected to the wind speed at the height of a hub of a fan, and the property of vertical distribution of the wind speed on flat terrains (such as fields, deserts, grasslands and the like) is simulated by a power function method, wherein the basic form is as follows:
wherein v is the installation height H of the wind turbine WT Wind speed at; v r For reference height H r Lower measured wind speed; zeta is the coefficient of wind speed energy law, and varies with the altitude, time, season, nature of terrain, wind speed, temperature, various thermodynamic and mechanical mixing parameters, and the like, and is generally 1/7 of the reference value under flat terrain. Then, the output of the wind power generation system is calculated, and three factors for determining the output of the wind power generation system are mainly: i.e. the power curve of the wind turbine, the wind speed distribution at the location where the wind turbine is installed, and the wind turbine installation height. The model of the output power of the wind power generation system is shown in the formula, and the annual wind power output curve can be obtained through calculation.
Wherein P is N Is rated installed capacity; v c 、v N 、v f The wind speed is the cut-in wind speed, the rated wind speed and the cut-out wind speed of the wind turbine respectively.
The power output of the whole wind power generation system is affected by multiple factors, so that a reduction coefficient is added for correction, and the total power output by the wind power plant is shown as a formula (3).
P WT ＝P WT ′×f 1 ×f 2 ×f 3 ×f 4 ×f 5 (3)
Wherein P is WT The total power output by the wind farm; f (f) 1 The coefficient is reduced for wake; f (f) 2 For control and turbulence reduction coefficients; f (f) 3 Is wind powerThe unit power curve guarantee rate reduces the coefficient; f (f) 4 The power consumption, line loss and other reduction coefficients are used for the field; f (f) 5 To account for interactions between large wind farms, the surrounding wind farms influence the reduction factor.
(2) Photovoltaic system (time sequence) output model
The output of the photovoltaic system is directly related to the solar energy received by the photovoltaic panels, and first the solar radiation absorbed by the photovoltaic panels on any inclined surface needs to be calculated.
Since the earth rotates around the equator as the axis, china is in the northern hemisphere, and solar radiation is received the most when the azimuth angle of the photovoltaic panel is in the positive south, the solar radiation on any inclined plane is only calculated on the assumption that light Fu Banmian is placed in the south, and the calculation formula of the solar radiation on the inclined plane at different moments is as follows:
R β ＝S×[sin(h+θ)/sinh]+D (4)
wherein R is β Is the total solar radiation amount on the inclined plane; s is the direct solar radiation quantity on the horizontal plane; d is the scattered radiation quantity; θ is the inclination of the inclined surface; h is the solar altitude, which changes continuously with time, and the solar altitude at different moments is confirmed by using each parameter, and the calculation method is as follows:
in the method, in the process of the invention,
is the local latitude; sigma is solar declination; ω is the solar time angle.
The calculation formulas of the solar declination and the solar hour angle are as follows:
sinσ＝0.39795cos[0.98563(N-173)] (6)
ω＝15×(ST-12) (7)
wherein N is the product days arranged according to the sequence of days; ST is true solar energy, and takes 24 hours as a period.
Photovoltaic panel power output is related to a number of factors, i=in the open cell state defined by this patent0，V＝V OC The method comprises the steps of carrying out a first treatment on the surface of the Maximum power point, v=v m ，I＝I m . The specific calculation formula is as follows:
the model requires input of short-circuit current I SC Open circuit voltage V OC Maximum power point current I m Maximum power point voltage V m These four parameters will change with the change of the solar radiation amount or temperature, and the correction method is as follows:
wherein I is SC ′、V OC ′、I m ′、V m ' is a correction value under different circumstances; t, T 0 Photovoltaic panel temperature and standard cell temperature (25 ℃ C.). G. G 0 For solar radiation and standard solar radiation (1000W/m 2); a. b and c are correlation coefficients (typical values take a=0.0025/. Degree.C., b=0.5, c= 0.00288/. Degree.C.)
The whole power output of the photovoltaic system is affected by multiple factors, and the output power of the photovoltaic system introducing the loss factor is shown in the formula.
P PV ＝n×N 1 ×N 2 ×V×I×f c ×f 0 (12)
Wherein P is PV The total power output by the photovoltaic system; n is the number of low-voltage cabinets of the photovoltaic system; n (N) 1 The number of the photovoltaic cells connected in series; n (N) 2 The number of strings of photovoltaic cells in each low-voltage cabinet is counted; f (f) c Introducing a factor for connection loss; f (f) 0 Factors are introduced for other losses.
(3) Thermal power generating unit running state model
The new energy consumption of the comprehensive energy system depends on the peak shaving space of the thermal power generating unit, and if the peak shaving space of the thermal power generating unit is larger, the new energy consumption is more. The peak shaving capacity of the thermal power generating unit under the conventional running condition is as follows:
wherein P is i,min The minimum operation output of the ith thermal power unit at the time t is P i,t Represents the active power of the ith thermal power unit at the moment t, U i,t Represents the start-stop state of the ith thermal power generating unit at the moment t, U i,t =0 indicates shutdown of the thermal power generating unit, U i,t =1 indicates that the thermal power generating unit is in start-up operation.
(4) Energy storage system charge-discharge model
In the comprehensive energy resource base project, wind power and photovoltaic output fluctuation is large, and because thermal power is limited by peak regulation capacity and unit climbing rate, the load requirement cannot be completely met, and the energy storage system can be used for supplementing and ensuring the supply and demand balance of electric power and improving the consumption proportion of new energy. During system operation, the operating state of the energy storage system is divided into a charged state, a discharged state and an electric quantity stationary state.
The conditions under which the battery pack is in a charged state are as follows.
The change in the charge of the battery pack is as follows.
The conditions under which the battery pack is in the discharge state are as follows.
The change in the amount of electricity of the battery pack in a discharged state is as follows.
(1) The system power generation amount is equal to the load power consumption amount as follows.
(W WT (t)+W PV (t)+W T (t))×η inv -E L (t)＝0 (18)
(2) The system is insufficiently powered and the battery pack stops discharging as shown below.
(3) The system is in an overcharged state and the battery pack stops charging as follows.
(4) The battery pack is in a stationary state as follows.
E B (t)＝E B (t-1) (21)
In which W is WT (t) the generated energy and the electric quantity value of the wind power generation system at the moment t; w (W) PV (t) the generated energy and the electric quantity value of the photovoltaic system at the moment t; w (W) T (t) is the generated energy and the electric quantity value of the thermal power system at the moment t; e (E) L (t) is the load electricity consumption at the moment t, and the electricity value; η (eta) inv Inversion efficiency; η (eta) Bc Charging efficiency of the battery; η (eta) Dc -discharge efficiency of the battery.
And S2, establishing a system economy optimization target, and calculating the total life cycle cost such as investment cost, operation and maintenance cost and the like as annual average capacity cost.
For the comprehensive energy resource base project, the annual average power generation cost mainly comprises three parts of initial investment cost, operation and maintenance cost in the operation period and thermal power fuel cost. In order to comprehensively consider the investment and the running economy of the whole life cycle of the comprehensive energy base project, the whole life cycle cost such as investment cost, operation maintenance cost and the like is calculated as annual average capacity cost. The economic evaluation of the life cycle of the system comprehensively considers the investment cost and the operation and maintenance cost of the wind power system, the photovoltaic system, the thermal power unit and the energy storage system. The annual average power generation cost calculation method comprises the following steps:
C＝(C acap (PV+Wind+Bat+Thermal)+C amain (PV+Wind+Bat+Thermal))/P out (22)
wherein: c (C) acap Initial investment for each part; p (P) out Output power of the system in whole year; c (C) amain For annual operation and maintenance cost, the operation and maintenance cost of the thermal power unit not only comprises the operation and maintenance cost of the unit, but also comprises the coal consumption cost of thermal power operation, and the calculation is performed by utilizing the coal consumption curve of the thermal power unit, wherein the calculation method comprises the following steps:
A(P T )＝S coal (a(P T ) 2 +bP T +c) (23)
wherein A (P T ) Representing the coal consumption cost of the thermal power unit; p (P) T Representing the actual output power of the thermal power generating unit; s is S coal The price (Yuan/t) of standard coal purchased by a thermal power plant is shown, and a, b and c show coal consumption characteristic parameters of a thermal power unit.
And S3, setting output constraint conditions, including system reliability, output channel power constraint, thermal power unit output constraint, thermal power unit climbing constraint, energy storage system capacity constraint, energy storage system charge and discharge power constraint and the like.
(1) The system reliability constraint adopts annual load power failure rate as a constraint index of the system reliability.
Where T-is the number of hours of Time data entered, time (P available (t)<P needed (t)) load off-time refers to the time when the system fails to meet the load power demand when the battery in the system is depleted and the other power sources are undercharged.
(2) Outgoing channel power constraint: p (P) total ≤P tomax (25)
Wherein: p (P) tomax Is the upper limit value of the power of the outgoing channel.
(3) Thermal power generating unit related constraint
Unit output constraint P Tmin ≤P T ≤P Tmax (26)
Wherein P is Tmax 、P Tmin The maximum and minimum output values of the thermal power generating unit are respectively obtained.
And (3) unit climbing constraint: syndrome of deficiency P (P) Td ≤P T -P T (t-1)≤△P Tu (27)
Wherein DeltaP d 、△P u The maximum downward and upward climbing rates of the thermal power generating unit are respectively.
(4) Energy storage system related constraints
Energy storage system capacity constraint E Bmin ≤E B ≤E Bmax (28)
Wherein E is Bmax 、E Bmin The upper and lower limits of the capacity of the energy storage system are respectively defined.
Energy storage system charge-discharge power constraint-delta P Bd ≤P B -P B (t-1)≤△P Bu (29)
Wherein DeltaP Bd 、△P Bu The charging and discharging power of the energy storage system and the charging power of the energy storage system are respectively.
And S4, solving and calculating, namely completing the series connection of all components based on the annual time sequence survival simulation method, and obtaining the comprehensive energy base optimal configuration model based on the annual time sequence production simulation method. The input parameters are annual time-by-time wind speed data, direct radiation data, scattered radiation data, temperature data, upper and lower limits at different moments, power change constraint, load data and the like, iterative calculation is carried out on the model, and the solution of the optimal configuration model is realized.
And (3) connecting each wind power output model, each photovoltaic output model, each thermal power unit running state model and each energy storage system charging and discharging model in series based on the annual time sequence production simulation method to obtain a comprehensive energy base optimizing configuration model based on the annual time sequence production simulation method. The input parameters of the wind power output model and the photovoltaic output model are time-by-time wind speed data, direct radiation data, scattered radiation data and temperature data of the whole year, and the input parameters of the running state model of the thermal power unit and the charge and discharge model of the energy storage system are upper and lower limits and power change constraint at different moments. The load data adopts time-by-time load data of different seasons on the demand side, and the time-by-time load data of different seasons is expanded in quarters to obtain complete annual load data. And (3) synthesizing an energy base optimal configuration model, and completing series connection based on a time sequence simulation method, wherein the optimal configuration model is a nonlinear mixed integer optimal model because of nonlinear functions such as an objective function, a constraint condition power function, a maximum value, a minimum value and the like. And carrying out iterative search on a feasible domain based on intelligent algorithms such as a particle swarm algorithm, a genetic algorithm and the like, so as to solve an optimal configuration model.
The following describes a point-to-point large-scale comprehensive energy base wind, light and fire storage bundling and conveying as an example.
Firstly, building a unit output and state model, wherein the wind power generation system output model is used for vertically distributing and correcting wind speed data and correcting the wind speed to be the wind speed at the height of a fan hub. And then calculating to obtain the output data of the unit wind power plant by using the power model of the wind power generation system. It is particularly noted here that the power output of the wind power generation system as a whole is affected by a plurality of factors, and therefore, a reduction coefficient is added to correct the output power of the wind power generation system. The method comprises the steps of building a photovoltaic system wind power plant output model, firstly correcting solar radiation on a horizontal plane into solar radiation on an inclined plane by using a solar time angle and solar declination, and then calculating typical output data of a unit photovoltaic power plant by using the photovoltaic output model. Similarly, the photovoltaic system has connection loss, line loss and the like in the process from power generation to grid connection to influence the whole output power, so that the loss factor is also added to correct the output power of the photovoltaic system. The running state models of the thermal power unit and the energy storage system are characterized by utilizing the difference value between new energy units and load demands of the thermal power unit at different moments, the output of the thermal power unit is limited by the peak regulation capacity of the thermal power unit, and the working state of the energy storage system is limited by the charge and discharge power of the energy storage system.
And secondly, establishing a system economy optimization target, and calculating the total life cycle cost such as investment cost, operation and maintenance cost and the like as annual average capacity cost. The economic evaluation of the life cycle of the system comprehensively considers the investment cost and the operation and maintenance cost of the wind power system, the photovoltaic system, the thermal power unit and the energy storage system, wherein the operation and maintenance cost of the thermal power comprises the coal consumption cost of the thermal power unit.
And thirdly, setting constraint conditions, including system reliability, output channel power constraint, constraint thermal power unit output constraint, thermal power unit climbing constraint, output channel power constraint, energy storage system capacity constraint, energy storage system charge and discharge power constraint and the like. And (3) constraining the time sequence operation of the comprehensive energy base optimal configuration model by utilizing the design of constraint conditions.
And fourthly, solving and calculating, wherein each wind power output model, each photovoltaic output model, each thermal power unit running state model and each energy storage system charging and discharging model are connected in series based on the annual time sequence production simulation method, and thus the comprehensive energy base optimizing configuration model based on the annual time sequence production simulation method is obtained. The input parameters of the wind power output model and the photovoltaic output model are time-by-time wind speed data, direct radiation data, scattered radiation data and temperature data of the whole year, and the input parameters of the running state model of the thermal power unit and the charge and discharge model of the energy storage system are upper and lower limits and power change constraint at different moments. The load data adopts time-by-time load data of different seasons on the demand side, and the time-by-time load data of different seasons is expanded in quarters to obtain complete annual load data. And (3) synthesizing an energy base optimal configuration model, and completing series connection based on a time sequence simulation method, wherein the optimal configuration model is a nonlinear mixed integer optimal model because of nonlinear functions such as an objective function, a constraint condition power function, a maximum value, a minimum value and the like. And carrying out iterative search on a feasible domain based on intelligent algorithms such as a particle swarm algorithm, a genetic algorithm and the like, so as to solve an optimal configuration model.
According to the comprehensive energy base optimal configuration method based on the annual time sequence production simulation, on the basis of analyzing the operation and characteristics of different power forms, the output models of various power types are built, dependence on wind power and photovoltaic actual measurement operation data can be avoided through model calculation, and the difficulty in acquiring the data is reduced. The capacity optimization configuration results of the wind power system, the photovoltaic system, the thermal power system, the energy storage system and the like are obtained through analysis and optimization of wind-solar resource distribution characteristics of a target area, basic conditions of the thermal power unit, performance parameters of the energy storage system and the like, a certain support can be provided for determining the installation scale of each power supply type of the comprehensive energy base project, and the capacity configuration problem of each power supply type in the integrated comprehensive energy base which is bundled and sent out is solved.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and it should be noted that it is possible for those skilled in the art to make several improvements and modifications without departing from the technical principle of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention.
Claims (1)
1. The comprehensive energy base optimal configuration method based on the annual time sequence production simulation is characterized by comprising the following steps of:
step 1, building a unit output and unit state model, wherein the model comprises a wind power system output model, a photovoltaic system output model, a thermal power unit running state model and an energy storage system charge and discharge model;
the method for establishing the wind power system output model comprises the following steps:
before the output of the wind power generation system is calculated, correcting the wind speed of input wind speed data to the wind speed at the height of a hub of a fan, and simulating the property of the wind speed vertically distributed in flat terrain by a power function method, wherein the basic form is as follows:
in the method, in the process of the invention, v mounting height H for wind turbine WT Wind speed at; v r For reference height H r Lower measured wind speed; zeta is the energy law coefficient of wind speed, changes with the change of altitude, time, season, property of topography, wind speed, temperature and thermodynamic and mechanical mixing parameters, and takes a reference value of 1/7 under flat topography;
calculating the output of the wind power generation system, wherein factors for determining the output of the wind power generation system comprise a power curve of the wind turbine, wind speed distribution of the position where the wind turbine is installed and the installation height of the wind turbine;
the model of the output power of the wind power generation system is shown in a formula (2), and the annual wind power output curve is obtained through calculation;
wherein P is N Is rated installed capacity; v c 、v N 、v f The cut-in wind speed, the rated wind speed and the cut-out wind speed of the wind turbine are respectively;
adding a reduction coefficient to correct the overall power output of the wind power generation system, wherein the total power output by the wind power plant is shown in a formula (3);
P WT ＝P WT ′×f 1 ×f 2 ×f 3 ×f 4 ×f 5 (3)
wherein P is WT The total power output by the wind farm; f (f) 1 The coefficient is reduced for wake; f (f) 2 For control and turbulence reduction coefficients; f (f) 3 The power curve guarantee rate reduction coefficient of the wind turbine generator system; f (f) 4 The power consumption, line loss and other reduction coefficients are used for the field; f (f) 5 In order to consider the interaction between large wind farms, the surrounding wind farms influence the reduction coefficient;
the building method of the photovoltaic system output model comprises the following steps:
calculating solar radiation absorbed by the photovoltaic panel on any inclined surface;
assuming that light Fu Banmian is placed in the south, only solar radiation on any inclined plane is calculated, and the calculation formula of the solar radiation on the inclined plane at different moments is shown as formula (4):
R β ＝S×[sin(h+θ)/sinh]+D (4)
wherein R is β Is the total solar radiation amount on the inclined plane; s is the direct solar radiation quantity on the horizontal plane; d is the scattered radiation quantity; θ is the inclination of the inclined surface; h is the solar altitude, which changes continuously with time, and the solar altitude at different moments is confirmed by using each parameter, and the calculation method is as shown in formula (5):
in the method, in the process of the invention,
is the local latitude; sigma is solar declination; omega is the solar time angle;
the calculation formulas of the solar declination and the solar hour angle are shown as formula (6) and formula (7):
sinσ＝0.39795cos[0.98563(N-173)] (6)
ω＝15×(ST-12) (7)
wherein N is the product days arranged according to the sequence of days; ST is true solar energy, and 24 hours is taken as a period;
i=0, v=v in defining the open battery state OC The method comprises the steps of carrying out a first treatment on the surface of the Maximum power point, v=v m ，I＝I m The calculation formulas are shown as formula (8), formula (9) and formula (10):
short-circuit current I SC Open circuit voltage V OC Maximum power point current I m Maximum power point voltage V m As the amount of solar radiation or the temperature changes, the correction method is as shown in formula (11):
wherein I is SC ′、V OC ′、I m ′、V m ' is a correction value under different circumstances; t, T 0 Photovoltaic panel temperature and standard cell temperature (25 ℃ C.). G. G 0 For solar radiation and standard solar radiation; a. b and c are correlation coefficients;
the output power of the photovoltaic system with the loss factor is shown as a formula (12);
PPV ＝n×N 1 ×N 2 ×V×I×f c ×f 0 (12)
wherein P is PV The total power output by the photovoltaic system; n is the number of low-voltage cabinets of the photovoltaic system; n (N) 1 The number of the photovoltaic cells connected in series; n (N) 2 The number of strings of photovoltaic cells in each low-voltage cabinet is counted; f (f) c Introducing a factor for connection loss; f (f) 0 Introducing factors for other losses;
the method for establishing the running state model of the thermal power generating unit comprises the following steps:
the peak regulating capacity of the thermal power generating unit under the normal running condition is as shown in formula (13):
wherein P is i,min The minimum operation output of the ith thermal power unit at the time t is P i,t Represents the ithActive power of thermal power generating unit at t moment, U i,t Represents the start-stop state of the ith thermal power generating unit at the moment t, U i,t =0 indicates shutdown of the thermal power generating unit, U i,t =1 indicates that the thermal power generating unit is in start-up operation;
the method for establishing the charge and discharge model of the energy storage system comprises the following steps:
during the operation of the system, the operation state of the energy storage system is divided into a charging state, a discharging state and an electric quantity static state;
the condition that the battery pack is in a charged state is shown in a formula (14);
the change of the electric quantity of the battery pack in a charged state is shown in a formula (15);
the condition that the battery pack is in a discharge state is shown in a formula (16);
the change of the electric quantity of the battery pack in a discharging state is shown in a formula (17);
the power generation amount of the system is equal to the power consumption amount of the load, as shown in a formula (18);
(W WT (t)+W PV (t)+W T (t))×η inv -E L (t) =0 (18) system energy is insufficient, the battery pack stops discharging, as shown in formula (19);
the system is in an overcharged state, and the battery pack stops charging as shown in a formula (20);
the battery pack is in a static state as shown in formula (21);
E B (t)＝E B (t-1) (21)
in which W is WT (t) the generated energy and the electric quantity value of the wind power generation system at the moment t; w (W) PV (t) the generated energy and the electric quantity value of the photovoltaic system at the moment t; w (W) T (t) is the generated energy and the electric quantity value of the thermal power system at the moment t; e (E) L (t) is the load electricity consumption at the moment t, and the electricity value; η (eta) inv Inversion efficiency; η (eta) Bc Charging efficiency of the battery; η (eta) Dc Is the discharge efficiency of the storage battery;
step 2, establishing a system economy optimization target, and calculating the whole life cycle cost including investment cost and operation and maintenance cost into annual average capacity cost, wherein the method specifically comprises the following steps of:
the economic evaluation of the life cycle of the system comprehensively considers the investment cost and the operation and maintenance cost of the wind power system, the photovoltaic system, the thermal power unit and the energy storage system;
the annual average power generation cost calculating method is as shown in the formula (22):
C＝(C acap (PV+Wind+Bat+Thermal)+C amain (PV+Wind+Bat+Thermal))/P out (22)
wherein: c (C) acap Initial investment for each part; p (P) out Output power of the system in whole year; c (C) amain For annual operation and maintenance cost, the operation and maintenance cost of the thermal power unit comprises the operation and maintenance cost of the unit and the coal consumption cost of thermal power operation, and the calculation method is as shown in formula (23):
A(P T )＝S coal (a(P T ) 2 +bP T +c) (23)
wherein A (P T ) Representing the coal consumption cost of the thermal power unit; p (P) T Representing the actual output power of the thermal power generating unit; s is S coal The price of the standard coal purchased by the thermal power plant is represented by the unit: the meta/t, a, b and c represent coal consumption characteristic parameters of the thermal power unit;
step 3, setting output constraint conditions, including system reliability constraint, output channel power constraint, thermal power unit output constraint, thermal power unit climbing constraint, energy storage system capacity constraint and energy storage system charge and discharge power constraint;
the system reliability constraint adopts annual load electricity shortage rate as a constraint index of the system reliability, as shown in a formula (24);
where T is the number of hours of Time data entered, time (P available (t)<P needed (t)) load off-time refers to the time when the system fails to meet the load power demand when the battery in the system is depleted and the other power sources are undercharged;
the outgoing channel power constraint is as shown in equation (25):
P total ≤P tomax (25)
wherein: p (P) tomax The power upper limit value of the outgoing channel;
the output constraint of the thermal power generating unit is shown as a formula (26);
P Tmin ≤P T ≤P Tmax (26)
wherein P is Tmax 、P Tmin The maximum and minimum output values of the thermal power generating unit are respectively obtained. The method comprises the steps of carrying out a first treatment on the surface of the
The climbing constraint of the thermal power generating unit is shown as a formula (27);
-△P Td ≤P T -P T (t- 1)≤△P Tu (27)
wherein DeltaP d 、△P u The maximum downward and upward climbing rates of the thermal power generating unit are respectively;
the energy storage system capacity constraint is as shown in formula (28);
E Bmin ≤E B ≤E Bmax (28)
wherein E is Bmax 、E Bmin The upper and lower limits of the capacity of the energy storage system are respectively set;
the charge and discharge power constraint of the energy storage system is shown as a formula (29);
-△P Bd ≤P B -P B (t- 1)≤△P Bu (29) Wherein DeltaP Bd 、△P Bu The charging and discharging power of the energy storage system and the charging power of the energy storage system are respectively;
step 4, solving and calculating: the method comprises the steps of connecting each wind power output model, each photovoltaic output model, each thermal power unit running state model and each energy storage system charging and discharging model in series based on an annual time sequence production simulation method to obtain a comprehensive energy base optimizing configuration model based on the annual time sequence production simulation method; the wind power output model and the photovoltaic output model input parameters are annual time-by-time wind speed data, direct radiation data, scattered radiation data and temperature data, the thermal power unit running state model and the energy storage system charge-discharge model input parameters are upper and lower limits at different moments and power change constraint, load data adopts time-by-time load data of different seasons on a demand side, the time-by-time load data of different seasons are expanded according to seasons, complete annual load data is obtained, iterative calculation is carried out on the model, and the solution of an optimal configuration model is realized.
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