CN115189395A - Double-layer optimal configuration method of wind, light, water and fire energy storage multi-energy complementary delivery system - Google Patents
Double-layer optimal configuration method of wind, light, water and fire energy storage multi-energy complementary delivery system Download PDFInfo
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Abstract
The invention relates to the technical field of power generation and delivery, in particular to a double-layer optimal configuration method of a wind, light, water and fire storage multi-energy complementary delivery system, which comprises the following steps: acquiring historical weather data in the multi-energy complementary outgoing power generation system; establishing output models of a photovoltaic generator set, a wind turbine generator set and a hydroelectric generator set according to the historical weather data; establishing a double-layer optimization model of the multi-energy complementary delivery power generation system based on predicted values of output models of the photovoltaic generator set, the wind turbine generator set and the hydroelectric generator set; and calculating and outputting the system installed capacity and the optimal result of the unit output at each moment by adopting a planning operation integrated configuration method through the double-layer optimization model. The method adopts a double-layer optimization model to integrally configure planning operation, effectively reduces the phenomena of wind and light abandonment, and improves the economy of the system.
Description
Technical Field
The invention relates to the technical field of power generation and delivery, in particular to a double-layer optimal configuration method of a wind, light, water and fire energy storage multi-energy complementary delivery system.
Background
With the rapid development of society and economy in China, the demand of electric energy is more and more large. Due to the problems of consumption of a large amount of fossil energy and environmental pollution caused by the traditional electric energy production, green renewable energy sources such as water energy, wind energy, solar energy and the like are actively developed all over the world. Wind power and photovoltaic power generation have volatility, intermittence and randomness, peak-valley difference of equivalent load of a power system can be increased by large-scale grid connection of the wind power and photovoltaic power generation, and the safe and stable operation of the power system is threatened. The energy storage, thermal power and hydroelectric generating set is flexible in starting and stopping, and electric energy fluctuation caused by wind and light uncertainty can be rapidly adjusted, so that the flexibility of the system is effectively improved, and the consumption of renewable energy is promoted. Meanwhile, the total amount of wind, light and water energy resources in China is huge and is mainly distributed in the three north area, but the wind, light and water energy resources are reversely distributed with a load center and do not have the capacity of absorbing large-scale new energy locally, so that the phenomena of wind abandonment and light abandonment are serious.
Aiming at the problems of uncertainty of wind power generation and photovoltaic power generation, low new energy consumption rate and the like, the optimal configuration method of the wind, light, water and fire energy storage multi-energy complementary delivery power generation system is considered, the phenomena of wind abandoning and light abandoning can be effectively reduced, the safe and stable operation of the system is ensured, and the system operation economy is improved. Most of the existing external transmission researches consider 'wind-fire' bundling, 'wind-solar' bundling and 'wind-solar storage' bundling, and little consideration is given to new energy resources and output characteristics of a transmitting end and load characteristics of a receiving end power grid, so in order to promote the consumption of new energy resources of the transmitting end and improve the power supply quality of the receiving end, a method for optimally configuring an external transmission power generation system considering wind-solar-water-fire storage multi-energy complementation is needed to be researched.
Disclosure of Invention
The purpose of the invention is as follows: in order to solve the planning operation problem related to the power generation and delivery of the multi-energy complementary power supply, the invention provides a double-layer optimization configuration method of a wind, light, water and fire storage multi-energy complementary delivery system.
The technical scheme is as follows: in order to realize the purpose, the invention adopts the technical scheme that:
a double-layer optimal configuration method of a wind, light, water and fire energy storage multi-energy complementary delivery system comprises the following steps:
step 1: acquiring annual illumination radiation intensity, ambient temperature, wind speed and water flow data in a multi-energy complementary outgoing power generation system, and establishing output models of a photovoltaic generator set, a wind turbine generator set and a hydroelectric generator set;
step 2: establishing a double-layer optimization model of a multi-energy complementary outgoing power generation system: the upper-layer optimization model plans the installed capacity of the wind, light, water and fire storage with the aim of minimizing the total cost of the power generation system, and the lower-layer optimization model optimizes the output of the unit at each moment to obtain the fuel cost of the thermal power unit and the wind and light abandoning cost of the complementary power generation system and returns the cost to the upper-layer model to participate in the target cost calculation;
and step 3: the upper-layer optimization model adopts a particle swarm algorithm to solve the system installed capacity as the input of the lower-layer optimization model, and the lower-layer optimization model specifies the unit output scheduling priority: and wind, light and water storage fire, solving the sum of the fuel cost and the wind and light abandoning cost of the thermal power generating unit under the installed capacity configuration, returning the sum to an upper layer model, and obtaining the optimal result of the installed capacity of the system and the output of the unit at each moment by taking the minimum total cost of the multi-energy complementary outgoing power generation system as a target in an upper layer optimization model.
Further, based on the annual illumination radiation intensity, the ambient temperature, the wind speed and the water flow data in the region multi-energy complementary outgoing power generation system obtained in the step 1, an output model of the photovoltaic generator set, the wind turbine set and the hydroelectric generator set is established;
further, the wind turbine generator output model is as follows:
in the formula: p is wd,f (t) is a predicted value of the output of the wind turbine generator at the moment t; p WD The installed capacity of the wind turbine generator is set; v (t) is the wind speed at the moment t; v. of in The cut-in wind speed of the fan is obtained; v. of rate The rated wind speed of the fan; v. of out The cut-out wind speed of the fan.
The photovoltaic generator set output model is as follows:
P pv,f (t)＝P PV G(t)[1+k pv (T p (t)-T nom )]/G nom
in the formula: p pv,f (t) is a predicted value of the output of the photovoltaic generator set at the t moment; p is PV The installed capacity of the photovoltaic generator set is obtained; g (t) is the illumination intensity at the moment t; k is a radical of pv The power temperature coefficient of the photovoltaic is taken as-0.35%/DEG C; t is p (t) is the photovoltaic cell surface temperature at time t; t is nom Taking the temperature of the battery at 25 ℃ under standard conditions; g nom Taking 1kW/m as the radiation intensity under the standard condition 2 。
The hydroelectric generating set output model is as follows:
P hd,f (t)＝9.81η hd Q(t)H
in the formula: p hd,f (t) is a predicted value of the output of the hydroelectric generating set at the moment t; eta hd For water and electricityThe station efficiency is equal to the product of the efficiency of the water turbine, the efficiency of the generator and the transmission efficiency of the unit; q (t) is the water flow at the moment t; h is the water head of the water turbine, namely the water head difference between the upstream water and the downstream water.
Further, establishing a double-layer optimization model of the multi-energy complementary outgoing power generation system:
(1) The objective function of the upper layer optimization model is as follows:
minF＝min(C IN +C OM +f)
in the formula: f is the total cost of the multi-energy complementary transmission power generation system; c IN 、C OM The total investment cost and the total operation and maintenance cost of the unit are calculated; f is a return value of the optimization result of the lower layer model; c INg 、C OMg Investment cost per unit volume and operation and maintenance cost per unit volume of the g-type unit; p g The capacity of the machine assembling machine is g; gamma is the showing rate, and 0.07 is taken; r is g The service life of the g-shaped machine set is prolonged.
(2) The constraint conditions of the upper-layer optimization model are as follows:
0≤P g ≤P gmax
in the formula: p gmax Is the upper limit of the capacity of the assembling machine of the g-type machine.
(3) The objective function of the lower optimization model is:
in the formula: t is the unit output scheduling period; p is th (t)、P wd (t)、P pv (t) the thermal power generating unit, the wind power generating unit and the photovoltaic generating unit output at t moment; f th Fuel cost for thermal power; p wd,f (t)、P pv,f (t) wind turbine generator, lightOutput predicted value at t moment of the photovoltaic generator set; and alpha and beta are wind and light abandoning punishment coefficients, and 0.1 yuan/(kWh) is taken.
(4) The constraint conditions of the lower layer optimization model are as follows:
(a) And power balance constraint:
P wd (t)+P pv (t)+P hd (t)+P th (t)+P dis (t)-P ch (t)＝L(t)
in the formula: p hd (t) the output of the hydroelectric generating set at the moment t; p dis (t)、P ch (t) is the discharge power and the charge power of the energy storage unit at the moment t; and L (t) is the outgoing power of the extra-high voltage direct current line at the time t.
(b) Output restraint of the wind turbine generator:
0≤P wd (t)≤P wd,f (t)
(c) Output restraint of the photovoltaic generator set:
0≤P pv (t)≤P pv,f (t)
(d) Output restraint of the hydroelectric generating set:
0≤P hd (t)≤P hd,f (t)
(e) Output restraint of the thermal power generating unit:
TH min P TH ≤P th (t)≤TH max P TH
in the formula: TH (TH) min 、TH max The minimum output coefficient and the maximum output coefficient of the thermal power generating unit are obtained; p TH The installed capacity of the thermal power generating unit.
(f) And (3) charge and discharge restraint of the energy storage battery:
0≤P dis (t)≤P LiB
0≤P ch (t)≤P LiB
P dis (t)P ch (t)＝0
in the formula: p LiB And the installed capacity of the energy storage machine is obtained.
(g) And (3) energy storage battery charge state constraint:
E＝CTη ch P LiB
S(t+1)＝S(t)(1-θ)+P ch (t)η ch -P dis (t)/η dis
0≤S(t)≤0.9E
in the formula: e is the energy storage capacity of the energy storage unit; the CT is the time required by charging the energy storage unit; theta, eta ch 、η dis The self-discharge rate, the charging efficiency and the discharging efficiency of the energy storage unit are obtained; and S (t) is the energy storage capacity of the energy storage unit at the moment t.
Further, a planning operation integrated configuration method adopting double-layer optimization is adopted: the upper-layer optimization model takes the minimum total cost of the multi-energy complementary transmission power generation system as a target function, adopts a particle swarm algorithm to plan the installed capacity of the system, and is used as the input of the lower-layer optimization model; the lower optimization model specifies the unit output scheduling priority: wind, light and water storage and fire, optimizing the running power of the thermal power generating unit at each moment, obtaining the fuel cost of the thermal power generating unit and the wind and light abandoning cost of the complementary power generation system on the basis, and returning the optimization result to the upper model to participate in the calculation of the target cost.
Further, the lower layer optimization model specifies the unit output scheduling priority: wind, light, water and fire storage. The method comprises the following specific steps:
s1: reading the illumination radiation intensity, the environment temperature, the wind speed and the water flow data, and calculating the maximum output value of each unit;
s2: and judging whether the output power of the wind and light set reaches the maximum value or not, wherein the output power is higher than the transmission power of the extra-high voltage line. If yes, executing S3; if not, S4 is performed.
S3: and when the output of the wind and light set is maximum, if the charging power of the energy storage device reaches the maximum, judging whether the system output power is higher than the transmission power of the extra-high voltage line. If so, the wind and light machine set carries out wind and light abandoning punishment according to the maximum output ratio; if not, the wind and light set output is the maximum value, and the maximum value is more than that of the energy storage device of the extra-high voltage line part for charging. S7 is performed.
S4: and when the output of the wind and light set is judged to be the maximum, if the discharge power of the energy storage device reaches the maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged. If so, the wind and light set output is the maximum value, the output is less than the discharge of the energy storage device of the extra-high voltage line part, and S7 is executed; if not, S5 is performed.
S5: and when the output of the wind and light unit is maximum and the discharge power of the energy storage device is maximum, if the output of the hydroelectric generating set is maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged. If so, the wind and light set output is the maximum value, the energy storage device discharge power is the maximum value, and the wind and light set output is greater than that of a part of the water and electricity set of the extra-high voltage line, and S7 is executed; if not, the output of the wind, solar and water generating set is the maximum value, the discharge power of the energy storage device is the maximum value, and the output is more than that of the thermal power generating set of the extra-high voltage line part, and S6 is executed.
S6: and judging whether the output of the thermal power generating unit is greater than the maximum output limit. If yes, the target function f is endowed with a maximum value and S9 is executed; if not, S7 is executed.
S7: the value of the objective function f is calculated and S8 is performed.
S8: and judging whether the energy storage capacity exceeds the limit. If yes, the target function f is endowed with a maximum value and S9 is executed; if not, S9 is performed.
S9: the value of the objective function f is returned to the upper optimization model.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the wind power generation system and the photovoltaic power generation system adopt a wind, light, water and fire storage multi-energy complementary power generation mode, utilize the time and space complementarity of the wind power generation unit and the photovoltaic power generation unit and the characteristics of flexible starting and rapid adjustment of the energy storage device, the thermal power generation unit and the hydroelectric power generation unit, effectively relieve the phenomena of large output power fluctuation, serious wind and light abandonment and the like of the wind power generation and the photovoltaic power generation caused by randomness and intermittence, solve the problems of low power supply reliability, difficult peak regulation and frequency modulation and the like caused when new energy is connected into a power grid, improve the renewable energy consumption rate of the system, ensure the safe and stable operation of the system and simultaneously improve the operation economy of the system.
2. Different from the capacity planning method of the machine assembly machine in the prior art, the step 4 in the invention considers the influence of the operation optimization result on the machine assembly capacity planning result, and introduces the operation optimization module into the planning by adopting a planning operation integrated configuration method. The upper layer model plans the installed capacity of the multi-energy complementary outgoing power generation system by taking the minimum total system cost as a target and is used as the constraint of the lower layer model, the lower layer model optimizes the output characteristics at all times by specifying the output scheduling priority of the unit, simultaneously returns the planning result of the operation cost value influencing the upper layer model, iteratively solves the optimal results of the installed capacity of the system and the output of the unit at all times, achieves the optimization of planning and operation at the same time, solves the problems of resource waste and the like possibly existing in the conventional planning method, and accordingly maximizes the total economic benefit of the power generation system.
3. Different from the prior art that the output of the unit is constrained by the load demand predicted value, the method is suitable for the technical field of power generation and power transmission, and the power balance constraint in the lower-layer optimization model in the step 3 is that the output of the power source is constrained by the power of the power transmission and power transmission at each moment. The output transmission power is the result of optimizing an extra-high voltage direct current output operation curve designed by existing students according to the load demand of a receiving-end power grid and the output characteristic of new energy at a sending end. By adopting the outgoing transmission power as a constraint value, the problems of increased receiving end peak regulation pressure and the like in the existing outgoing power generation technology are solved to a certain extent, and the technical effects of improving the new energy consumption rate and preventing the waste of unit installation can be achieved.
Description of the drawings:
FIG. 1 is a flow chart of an optimal configuration method of the present invention;
FIG. 2 is a diagram of a two-layer optimization model according to the present invention;
FIG. 3 is a flow chart of a solution of a two-layer optimization model according to the present invention;
fig. 4 is an operation curve of the extra-high voltage dc line according to the present invention;
FIG. 5 is a wind, light and water force characteristic curve of the present invention;
FIG. 6 shows the output of the unit for 24h in a typical day in summer.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
The present invention will be described in detail with reference to fig. 1 to 6.
As shown in fig. 1, the invention provides a double-layer optimal configuration method of a wind, light, water, fire and energy storage multi-energy complementary delivery system, which comprises the following steps:
step 1: and acquiring the data of the illumination radiation intensity, the environmental temperature, the wind speed and the water flow rate in the multi-energy complementary outgoing power generation system from a related meteorological data website. And establishing output models of the photovoltaic generator set, the wind turbine generator set and the hydroelectric generator set according to the obtained data.
(1) The wind turbine generator output model is as follows:
in the formula: p wd,f (t) is a predicted value of the output of the wind turbine generator at the moment t; p is WD The installed capacity of the wind turbine generator is set; v (t) is the wind speed at the moment t; v. of in Setting the cut-in wind speed of the fan to be 4m/s; v. of rate Setting the rated wind speed of a fan to be 12m/s; v. of out The cut-out wind speed for the fan was set at 25m/s.
(2) The photovoltaic generator set output model is as follows:
P pv,f (t)＝P PV G(t)[1+k pv (T p (t)-T nom )]/G nom
in the formula: p is pv,f (t) is a predicted value of the output of the photovoltaic generator set at the t moment; p PV The installed capacity of the photovoltaic generator set is obtained; g (t) is the illumination intensity at the moment t; k is a radical of formula pv Taking the power temperature coefficient of photovoltaic to be-0.35%/DEG C; t is p (t) is the photovoltaic cell surface temperature at time t; t is nom Taking the temperature of the battery at 25 ℃ under standard conditions; g nom Taking 1kW/m as the radiation intensity under the standard condition 2 。
The calculation formula of the surface temperature of the photovoltaic cell is as follows:
T p (t)＝T a (t)+K G G
in the formula: t is a (t) is ambient temperature at time t; k G As the temperature rise coefficient, take 0.032 deg.C/(m) 2 ·W -1 )。
(3) The output model of the hydroelectric generating set is as follows:
P hd,f (t)＝9.81η hd Q(t)H
in the formula: p hd,f (t) is a predicted value of the output of the hydroelectric generating set at the t moment; eta hd The hydropower station efficiency is equal to the product of the efficiency of a water turbine, the efficiency of a generator and the transmission efficiency of a unit; q (t) is the water flow at the moment t; h is the water head of the water turbine, namely the water head difference between the upstream water and the downstream water.
And 2, step: establishing a double-layer optimization model of the multi-energy complementary delivery power generation system: the upper-layer optimization model plans the installed capacity of the wind, light, water and fire storage with the aim of minimizing the total cost of the power generation system, and the lower-layer optimization model optimizes the unit to output power at all times to obtain the fuel cost of the thermal power unit, the wind abandoning cost and the light abandoning cost of the complementary power generation system and returns the costs to the upper-layer model to participate in the target cost calculation.
The structure of the two-layer optimization model is shown in FIG. 2.
(1) The objective function of the upper layer optimization model is as follows:
minF＝min(C IN +C OM +f)
in the formula: f isThe total cost of the multi-energy complementary outgoing power generation system; c IN 、C OM The total investment cost and the total operation and maintenance cost of the unit are calculated; f is a return value of the optimization result of the lower model; c INg 、C OMg Investment cost per unit volume and operation and maintenance cost per unit volume of the g-type unit are saved; p is g The capacity of the machine assembling machine is g; gamma is the showing rate, and 0.07 is taken; r is a radical of hydrogen g The service life of the g-shaped machine set is prolonged.
(2) The constraint conditions of the upper-layer optimization model are as follows:
0≤P g ≤P gmax
in the formula: p is gmax Is the upper limit of the capacity of the assembling machine of the g-type machine.
(3) The objective function of the lower optimization model is:
in the formula: t is the unit output scheduling period; p is th (t)、P wd (t)、P pv (t) the thermal power generating unit, the wind power generating unit and the photovoltaic generating unit output at t moment; f th Fuel cost for thermal power; p wd,f (t)、P pv,f (t) output predicted values of the wind turbine generator set and the photovoltaic generator set at t moment; and alpha and beta are wind abandon and light abandon penalty coefficients, and 0.1 yuan/(kWh).
(4) The constraint conditions of the lower layer optimization model are as follows:
(a) And power balance constraint:
P wd (t)+P pv (t)+P hd (t)+P th (t)+P dis (t)-P ch (t)＝L(t)
in the formula: p hd (t) the output of the hydroelectric generating set at the moment t; p dis (t)、P ch (t) is the discharge power and the charge power of the energy storage unit at the moment t; and L (t) is the outgoing power of the extra-high voltage direct current line at the time t.
(b) Output restraint of the wind turbine generator:
0≤P wd (t)≤P wd,f (t)
(c) Photovoltaic generator set output constraint:
0≤P pv (t)≤P pv,f (t)
(d) Output restraint of the hydroelectric generating set:
0≤P hd (t)≤P hd,f (t)
(e) Output restraint of the thermal power generating unit:
TH min P TH ≤P th (t)≤TH max P TH
in the formula: TH min 、TH max The minimum output coefficient and the maximum output coefficient of the thermal power generating unit are obtained; p TH The installed capacity of the thermal power generating unit.
(f) And (3) charge and discharge restraint of the energy storage battery:
0≤P dis (t)≤P LiB
0≤P ch (t)≤P LiB
P dis (t)P ch (t)＝0
in the formula: p LiB The installed capacity of the energy storage machine is obtained.
(g) And (3) energy storage battery charge state constraint:
E＝CTη ch P LiB
S(t+1)＝S(t)(1-θ)+P ch (t)η ch -P dis (t)/η dis
0≤S(t)≤0.9E
in the formula: e is the energy storage capacity of the energy storage unit; the CT is the time required by charging the energy storage unit; theta, eta ch 、η dis The self-discharge rate, the charging efficiency and the discharging efficiency of the energy storage unit are obtained; and S (t) is the energy storage capacity of the energy storage unit at the moment t.
And step 3: the upper-layer optimization model adopts a particle swarm algorithm to solve the system installed capacity as the input of the lower-layer optimization model, and the lower-layer optimization model specifies the unit output scheduling priority: and wind, light and water storage fire, solving the sum of the fuel cost and the wind and light abandoning cost of the thermal power generating unit under the installed capacity configuration, returning the sum to an upper layer model, and obtaining the optimal result of the installed capacity of the system and the output of the unit at each moment by taking the minimum total cost of the multi-energy complementary outgoing power generation system as a target in an upper layer optimization model. A flow chart for solving the two-layer model is shown in fig. 3.
Wherein, the lower optimization model stipulates the unit output scheduling priority: wind, light, water and fire storage.
The method comprises the following specific steps:
the method comprises the following steps: reading the illumination radiation intensity, the environment temperature, the wind speed and the water flow data, and calculating the maximum output value of each unit;
step two: and judging whether the output power of the wind and light set reaches the maximum value or not, wherein the output power is higher than the transmission power of the extra-high voltage line. If yes, executing the step three; if not, executing step four.
Step three: and when the output of the wind and light set is maximum, if the charging power of the energy storage device reaches the maximum, judging whether the system output power is higher than the transmission power of the extra-high voltage line. If so, the wind-solar unit performs wind abandoning and light abandoning punishment according to the maximum output ratio; if not, the wind and light set output is the maximum value, and the maximum value is more than that of the energy storage device of the extra-high voltage line part for charging. Step seven is executed.
Step four: and when the output of the wind and light set is judged to be the maximum, if the discharge power of the energy storage device reaches the maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged. If so, the wind and light set output is the maximum value, the output is less than the discharge of the energy storage device of the extra-high voltage line part, and the seventh step is executed; if not, step five is executed.
Step five: and when the output of the wind and light unit is maximum and the discharge power of the energy storage device is maximum, if the output of the hydroelectric generating set is maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged. If so, the output of the wind and light unit is the maximum value, the discharge power of the energy storage device is the maximum value, and the output is more than that of the partial hydroelectric generating set of the extra-high voltage line, and the seventh step is executed; if not, the output of the wind, solar and water generating set is the maximum value, the discharge power of the energy storage device is the maximum value, the output is more than that of the thermal power generating set of the extra-high voltage line part, and the step six is executed.
Step six: and judging whether the output of the thermal power generating unit is greater than the maximum output limit. If yes, the objective function f is endowed with a maximum value and the step nine is executed; if not, step seven is performed.
Step seven: the value of the objective function f is calculated and step eight is performed.
Step eight: and judging whether the energy storage capacity exceeds the limit. If yes, the target function f is endowed with a maximum value and the step nine is executed; if not, step nine is performed.
Step nine: the value of the objective function f is returned to the upper optimization model.
Based on the above consideration, the optimal configuration method of the wind, light, water, fire and energy storage multi-energy complementary power generation system is explained in detail by taking a certain typical day in summer in the Tibet region as an example. The following examples are only for illustrating the technical solution of the present invention more clearly, and do not limit the scope of the present invention.
The Tibetan medicine has the advantages that the average altitude is more than 4000 meters in the southwest part of the Qinghai-Tibet plateau at Tibet, the Tibetan medicine has rich clean energy resources including water energy, solar energy, wind energy and the like, and the Tibetan medicine has higher development and utilization values. The Tibetan region has rich wind resources and solar resources, the development cost of wind energy is low, and the wind energy and the solar resources are easy to obtain, but the wind energy and the photovoltaic power generation are difficult to control due to the characteristics of randomness and intermittence of wind speed and illumination radiation, and the wind energy and the solar resources are mainly reflected as follows: in the daytime, the sunshine time in the Tibet is long, the radiation range is wide, the wind power is weak, at night, the solar radiation is weak, the wind power is gradually increased, and the power supply quality and the stability of a power grid can be influenced by independent power generation of wind energy and solar energy. The energy storage, thermal power and hydroelectric generating set is flexible to start and stop and rapid to adjust, the advantages of renewable energy sources can be fully exerted by adopting a wind, light, water, fire and energy storage multi-energy complementary power generation mode, and the consumption rate of the renewable energy sources and the power supply reliability of a power grid are improved.
The device parameters of the wind, light, water and fire generator set are shown in the table 1.
TABLE 1 Generator set parameters
The energy storage cell parameters are shown in table 2.
TABLE 2 energy storage Battery parameters
The fuel consumption parameters of the thermal power generating unit are shown in table 3.
TABLE 3 thermal power generating unit fuel consumption parameters
The operation curve of the extra-high voltage direct current line is designed by the scholars according to the output characteristics of the renewable energy sources in the sending terminal area and the load response characteristics in the receiving terminal area and is shown in fig. 4. The wind, light and water output characteristic curve obtained according to data of a certain typical sunlight radiation intensity, an ambient temperature, a wind speed and a water flow rate in summer in the Tibet region is shown in FIG. 5.
The optimal planning is carried out according to the double-layer optimal configuration method, the configuration result of the optimal installed capacity of the unit in the Tibet region is shown in the table 4, and the output situation of the unit of 24 hours on a certain typical day in summer is shown in the figure 6.
TABLE 4 optimal installed capacity configuration results
When only the multi-energy complementary system is considered for power generation and delivery, in order to minimize the wind and light abandoning rate of the system, the principle of preferentially using clean energy is adopted. Charging the energy storage device for the part exceeding the sending power of the extra-high voltage direct current line, and considering the punishment of partial wind and light abandonment when the charging power reaches the maximum; the part of the insufficient extra-high voltage direct current line outgoing power is discharged by the energy storage device, and the part of the insufficient extra-high voltage direct current line outgoing power is discharged by the hydroelectric generating set and the thermal generating set sequentially after the discharging power reaches the maximum.
As can be seen from fig. 6, the photovoltaic generator set has no output in the early morning and the late afternoon, the output is preferably from the wind turbine generator set, and the insufficient portion is provided by the energy storage device, the hydroelectric generator set and the thermal power generator set. And when the energy storage capacity is insufficient at the moment of low wind speed and light intensity in the daytime, the output is provided by a thermal power generating unit and a hydroelectric generating unit. The output condition at each moment is strictly carried out according to the output scheduling priority-wind, light and water storage fire specified by the inner layer optimization model, and the output characteristics of wind power and photovoltaic power generation meet the change conditions of wind speed and illumination intensity. Therefore, the optimal configuration method of the external power generation system considering wind, light, water, fire and energy storage complementation, provided by the invention, can effectively reduce the phenomena of wind and light abandonment and environmental pollution, and improve the economic benefit of the power generation system.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A double-layer optimal configuration method of a wind, light, water and fire energy storage multi-energy complementary delivery system is characterized in that: the method comprises the following steps:
step 1: acquiring historical weather data in the multi-energy complementary outgoing power generation system;
step 2: establishing output models of the photovoltaic generator set, the wind turbine generator set and the hydroelectric generator set according to the historical weather data;
and step 3: establishing a double-layer optimization model of the multi-energy complementary transmission power generation system based on the predicted values of the output models of the photovoltaic generator set, the wind turbine generator set and the hydroelectric generator set;
and 4, step 4: and calculating and outputting the system installed capacity and the optimal result of the unit output at each moment by adopting a planning operation integrated configuration method through the double-layer optimization model.
2. The double-layer optimal configuration method for the wind, light, water, fire and energy storage multi-energy complementary delivery system according to claim 1, wherein the step 2 specifically comprises: establishing output models of a photovoltaic generator set, a wind turbine generator set and a hydroelectric generator set according to the acquired annual illumination radiation intensity, environmental temperature, wind speed and water flow data in the multi-energy complementary external power generation system;
the wind turbine generator output model is as follows:
in the formula: p wd,f (t) is a predicted value of the output of the wind turbine generator at the moment t; p WD The installed capacity of the wind turbine generator is set; v (t) is the wind speed at the moment t; v. of in The cut-in wind speed of the fan is obtained; v. of rate The rated wind speed of the fan; v. of out Cutting out the wind speed of the fan;
the photovoltaic generator set output model is as follows:
P pv,f (t)＝P PV G(t)[1+k pv (T p (t)-T nom )]/G nom
in the formula: p pv,f (t) is a predicted value of the output of the photovoltaic generator set at the t moment; p PV The installed capacity of the photovoltaic generator set is obtained; g (t) is the illumination intensity at the moment t; k is a radical of pv Is the power temperature coefficient of the photovoltaic; t is p (t) is the photovoltaic cell surface temperature at time t; t is nom Is the cell temperature under standard conditions; g nom Is the radiation intensity under standard conditions;
the hydroelectric generating set output model is as follows:
P hd,f (t)＝9.81η hd Q(t)H
in the formula: p hd,f (t) is a predicted value of the output of the hydroelectric generating set at the t moment; eta hd The hydropower station efficiency is equal to the product of the efficiency of a water turbine, the efficiency of a generator and the transmission efficiency of a unit; q (t) is the water flow at the moment t; h is the water head of the water turbine, namely the water head difference between the upstream water and the downstream water.
3. The double-layer optimization configuration method of the wind, light, water, fire and energy storage multi-energy complementary delivery system according to claim 1, wherein the double-layer optimization model of the multi-energy complementary delivery power generation system in the step 3 comprises an upper layer optimization model and a lower layer optimization model, the upper layer optimization model plans the unit installed capacity with the minimum total cost of the power generation system as a target and is used as an input of the lower layer optimization model, and the lower layer optimization model schedules the priority by specifying the unit output: wind, light and water storage, optimizing the output power of the unit at each moment, and returning the operation cost to the upper layer for iterative solution.
4. The double-layer optimal configuration method of the wind, light, water, fire and energy storage multi-energy complementary delivery system according to claim 3,
the objective function of the upper layer optimization model is as follows:
min F＝min(C IN +C OM +f)
in the formula: f is the total cost of the multi-energy complementary transmission power generation system; c IN 、C OM The total investment cost and the total operation and maintenance cost of the unit are calculated; f is a return value of the optimization result of the lower model; c INg 、C OMg Investment cost per unit volume and operation and maintenance cost per unit volume of the g-type unit; p g The capacity of the machine assembling machine is g; gamma is the discount rate; r is a radical of hydrogen g The service life of the G-shaped machine set is prolonged;
the constraint conditions of the upper-layer optimization model are as follows:
0≤P g ≤P gmax
in the formula: p gmax The upper limit of the capacity of the machine assembling machine of the g type;
the objective function of the lower optimization model is:
in the formula: t is the unit output scheduling period; p th (t)、P wd (t)、P pv (t) the thermal power generating unit, the wind power generating unit and the photovoltaic generating unit output at t moment; f th Fuel cost for thermal power; p wd,f (t)、P pv,f (t) predicted values of output of the wind turbine generator set and the photovoltaic generator set at t moment; alpha and beta are wind abandon and light abandon punishment coefficients;
the constraint conditions of the lower layer optimization model are as follows:
and power balance constraint:
P wd (t)+P pv (t)+P hd (t)+P th (t)+P dis (t)-P ch (t)＝L(t)
in the formula: p hd (t) the output of the hydroelectric generating set at the moment t; p dis (t)、P ch (t) is the discharge power and the charge power of the energy storage unit at the moment t; l (t) is the outgoing power of the extra-high voltage direct current line at the time t;
output constraint of the wind turbine generator:
0≤P wd (t)≤P wd,f (t)
output restraint of the photovoltaic generator set:
0≤P pv (t)≤P pv,f (t)
output restraint of the hydroelectric generating set:
0≤P hd (t)≤P hd,f (t)
output restraint of the thermal power generating unit:
TH min P TH ≤P th (t)≤TH max P TH
in the formula: TH min 、TH max The minimum output coefficient and the maximum output coefficient of the thermal power generating unit are obtained; p TH The installed capacity of the thermal power generating unit is obtained;
and (3) charge and discharge restraint of the energy storage battery:
0≤P dis (t)≤P LiB
0≤P ch (t)≤P LiB
P dis (t)P ch (t)＝0
in the formula: p LiB Installing capacity for the energy storage unit;
and (3) energy storage battery charge state constraint:
E＝CTη ch P LiB
S(t+1)＝S(t)(1-θ)+P ch (t)η ch -P dis (t)/η dis
0≤S(t)≤0.9E
in the formula: e is the energy storage capacity of the energy storage unit; the CT is the time required by charging the energy storage unit; theta, eta ch 、η dis The energy storage unit has self-discharge rate, charge efficiency and discharge efficiency; and S (t) is the energy storage capacity of the energy storage unit at the moment t.
5. The double-layer optimization configuration method of the wind, light, water, fire and energy storage multi-energy complementary delivery system according to claim 1, characterized in that the step 4 adopts a double-layer optimization planning operation integrated configuration method, an upper layer optimization model adopts a particle swarm optimization algorithm to plan the installed capacity of the system with the minimum total cost of the multi-energy complementary delivery power generation system as an objective function, and the upper layer optimization model is used as the input of a lower layer optimization model; the lower-layer optimization model specifies that the output scheduling priority of the unit is wind, light and water storage fire, the running power of the unit at each moment is optimized, the fuel cost of the thermal power unit and the wind and light abandoning cost of the power generation system are obtained on the basis, the optimization result is returned to the upper-layer model to participate in the calculation of the target cost, and the optimization results are complemented in the upper-layer optimization model in a multi-energy mode.
6. The double-layer optimization configuration method of the wind, light, water, fire and energy storage multi-energy complementary delivery system according to claim 5, wherein the lower-layer optimization model specifies unit output scheduling priorities: the wind-solar water storage fire comprises the following specific steps:
s1: reading the illumination radiation intensity, the environment temperature, the wind speed and the water flow data, and calculating the maximum output value of each unit;
s2: judging whether the output power of the wind and light set is higher than the transmission power of the extra-high voltage line when the output power of the wind and light set reaches the maximum value, and if so, executing S3; if not, executing S4;
s3: when the output of the wind and light set is maximum, if the charging power of the energy storage device reaches the maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged, and if so, the wind and light set carries out wind and light abandoning punishment according to the maximum output ratio; if not, the wind and light set output is the maximum value, and is more than the energy storage device of the extra-high voltage line part for charging, and S7 is executed;
s4: when the output of the wind and light set is judged to be maximum, if the discharge power of the energy storage device reaches the maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged; if so, the wind and light set output is the maximum value, the output is less than the discharge of the energy storage device of the extra-high voltage line part, and S7 is executed; if not, executing S5;
s5: when the output of the wind and light unit is maximum and the discharge power of the energy storage device is maximum, if the output of the hydroelectric generating unit is maximum, whether the system output power is higher than the transmission power of the extra-high voltage line or not is judged, if so, the output of the wind and light unit is the maximum, the discharge power of the energy storage device is the maximum, and the output of a part of the hydroelectric generating unit is higher than that of the extra-high voltage line, and S7 is executed; if not, the output of the wind, solar and water generating set is the maximum value, the discharge power of the energy storage device is the maximum value, and the output is more than that of the thermal power generating set of the extra-high voltage line part, and S6 is executed;
s6: judging whether the output of the thermal power generating unit is greater than the maximum output limit, if so, giving a maximum value to the target function f and executing the ninth step; if not, executing S7;
s7: calculating the value of the objective function f and executing S8;
s8: judging whether the energy storage capacity exceeds the limit, if so, giving a maximum value to the target function f and executing the ninth step; if not, executing S9;
s9: the value of the objective function f is returned to the upper optimization model.
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| CN117913921A (en) * | 2024-03-19 | 2024-04-19 | 长春工业大学 | Time sequence power transmission expansion planning method considering wind-solar grid connection |
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| CN117913921A (en) * | 2024-03-19 | 2024-04-19 | 长春工业大学 | Time sequence power transmission expansion planning method considering wind-solar grid connection |
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