CN113839415A - Optimized scheduling method for multi-type flexible power supply - Google Patents

Optimized scheduling method for multi-type flexible power supply Download PDF

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CN113839415A
CN113839415A CN202110992668.9A CN202110992668A CN113839415A CN 113839415 A CN113839415 A CN 113839415A CN 202110992668 A CN202110992668 A CN 202110992668A CN 113839415 A CN113839415 A CN 113839415A
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power
wind
output
capacity
generating unit
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CN113839415B (en
Inventor
周强
张彦琪
吴悦
马志程
吕清泉
王定美
韩旭杉
马彦宏
李津
高鹏飞
张金平
张健美
张珍珍
张睿骁
甄文喜
陈柏旭
赵龙
丁坤
沈琛云
刘丽娟
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Jiuquan Power Supply Co Of State Grid Gansu Electric Power Co
Linxia Power Supply Company State Grid Gansu Electric Power Co
STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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Jiuquan Power Supply Co Of State Grid Gansu Electric Power Co
Linxia Power Supply Company State Grid Gansu Electric Power Co
STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H02J3/472—For selectively connecting the AC sources in a particular order, e.g. sequential, alternating or subsets of sources
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/10—The dispersed energy generation being of fossil origin, e.g. diesel generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/10—Photovoltaic [PV]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/50—Hydropower in dwellings
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention relates to an optimized scheduling method of a multi-type flexible power supply, which uses the following source-network coordination scheduling strategy: arranging the minimum output capacity of a thermal power generating unit, the wind power photoelectric generator set, the runoff water power generator set and the storage capacity hydroelectric generator set to be loaded; judging the load source condition at the current moment; when the power is less than the load, the output is increased according to the sequence of the reservoir capacity hydroelectric generating set, the thermal power generating set and the gas generating set; if the source is still less than the charge, arranging external power purchase; when the power is larger than the load, the output is reduced according to the sequence of the thermal power generating unit, the reservoir capacity hydroelectric generating unit and the gas generating unit; if the power is still larger than the load, the output is continuously reduced according to the sequence of the wind power, the photoelectricity and the runoff hydroelectric generating set. Based on the space-time complementary characteristics of various types of power supplies, the wind, light, fire and water combustion power generation sequence is coordinated through a source-network coordination scheduling strategy, wind abandon and light abandon can be effectively reduced, wind and light cluster absorption is improved, the wind power photoelectric absorption capability and the operation benefit of the system under the source-network synergistic effect are more advantageous, and the power system can operate more efficiently and stably.

Description

Optimized scheduling method for multi-type flexible power supply
Technical Field
The invention relates to the technical field of new energy optimization scheduling, in particular to an optimization scheduling method for multiple types of flexible power supplies.
Background
The wind power, the photovoltaic power generation and other renewable energy sources are different from the traditional fossil energy sources, and the output of the renewable energy sources has strong randomness. With the rapid development of wind power generators and photovoltaic generators, large-scale wind power and photovoltaic electric field centralized grid connection add a plurality of uncertain factors to the economic dispatching of a power system.
Regarding large-scale wind power and photoelectric centralized grid connection, related researches at home and abroad are concentrated on the influences of the wind power and the photoelectric centralized grid connection on the voltage and the frequency of a local grid of a grid-connected point and the impact on the power flow of the grid-connected point, and researches on the aspects of reactive voltage control, active control and prediction and forecast of the grid-connected point are also carried out, so that the research on a source grid coordination control technology for considering the improvement of the wind-solar-power cluster high-efficiency absorption of various flexible power supplies is not related too much.
Disclosure of Invention
The invention aims to provide an optimized scheduling method of multiple types of flexible power supplies so as to improve the consumption of large-scale wind, light and electricity and reduce the operation cost of a system.
In order to solve the above problems, the optimized scheduling method for multiple types of flexible power supplies according to the present invention uses the following source-network coordinated scheduling strategy:
sequentially arranging the minimum output capacity of the thermal power generating unit, the wind power photoelectric generator set, the runoff water current generator set and the storage capacity water generator set with loads;
calculating and judging the load source condition at the current moment;
when the output of all the units is smaller than the current load, the output is increased according to the sequence of a reservoir capacity hydroelectric generating unit, a reservoir capacity thermal generating unit and a reservoir capacity gas generating unit; if the current load is still less than the current load, arranging external power purchase;
when the output of all the units is greater than the current load, reducing the output according to the sequence of the thermal power unit, the storage capacity hydroelectric unit and the gas unit; and if the load is still larger than the current load, continuously reducing the output according to the sequence of the wind power generator, the photoelectric generator and the runoff water generator.
Preferably, before the arrangement of the minimum output capacity of the thermal power generating unit, the method further comprises the following steps: and carrying out segmentation processing on the capacity of the started thermal power generating unit, and dividing the capacity into a minimum output capacity and an adjustable output capacity.
Preferably, the method further comprises the following steps:
constructing an objective function of an optimized scheduling model by taking the minimum running cost as a target based on the source-network coordinated scheduling strategy;
solving the optimized scheduling model by combining the objective function and a preset constraint condition, acquiring a parameter of optimized scheduling, and using the parameter for scheduling control; the parameters of the optimized scheduling comprise the output condition of each controllable unit, the transmission power of the tie line and the economic cost after the optimized scheduling.
Preferably, the formula of the objective function is as follows:
Figure BDA0003232954030000021
wherein, of represents the operation cost of the system in the scheduling period, Cg，tIndicating normal operation of the thermal engine g at time tCost, ct,tPr,tIndicating the cost of normal operation of the gas-fired motor r at time t, VOLL LSi,tRepresenting the cost of electricity purchase that may be made from outside for system stability,
Figure BDA0003232954030000022
and
Figure BDA0003232954030000023
and (4) the penalty cost of wind abandon and light abandon is represented, wherein VOLW and VOLV are coefficients of wind abandon and light abandon penalty, and the normal operation cost of the hydraulic motor in the system is ignored.
Preferably, the preset constraint conditions include an operation cost constraint condition of the thermal power generator, a power balance constraint condition of the power system, a rotation positive and negative reserve capacity constraint condition, an operation constraint condition of the thermal power generator, an operation constraint condition of the hydroelectric generating set, an operation constraint condition of the gas power generator, a switch constraint condition of the conventional generating set, and upper and lower limit constraint conditions of wind power and photovoltaic power generation output.
Compared with the prior art, the invention has the following advantages:
according to the wind-solar-power integrated power generation system, based on the time-space complementary characteristics of wind, light, water, fire and gas multi-type power sources, the power generation sequence of wind power, photovoltaic power generation, thermal power, hydroelectric power and gas power generation is coordinated through a source-grid coordinated scheduling strategy, large-scale wind power and photovoltaic power generation can be effectively connected to the grid, wind and light abandonment is reduced, wind-solar-power cluster consumption is promoted, economic benefit maximization is taken as an optimization target, the wind power photoelectric consumption capability and the operation benefit of the system under the source-grid synergistic effect are more advantageous, and the power system can be operated more efficiently and stably.
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The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of a source-network coordinated scheduling policy according to an embodiment of the present invention.
Fig. 2 is a flowchart of an optimized scheduling method according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of piecewise linearization of a secondary cost curve of a thermal power generator according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a main parameter model of the hydroelectric generator according to the embodiment of the present invention.
Fig. 5 is a schematic diagram of a 24bus model of the power system according to the embodiment of the present invention.
Fig. 6 shows the 24-hour grid connection amount of the wind generating set provided by the embodiment of the invention.
Fig. 7 shows the 24-hour grid connection amount of the photovoltaic generator set provided by the embodiment of the invention.
Fig. 8 shows a 24-hour grid connection amount of the thermal power generating unit according to the embodiment of the present invention.
Fig. 9 shows a 24-hour grid connection amount of the gas-electric generating set provided by the embodiment of the invention.
Fig. 10 shows a 24-hour grid connection amount of the hydroelectric generating set provided by the embodiment of the invention.
Fig. 11 is a result of multi-type flexible power supply joint optimization scheduling in case 1 according to an embodiment of the present invention.
Fig. 12 is a model provided by an embodiment of the present invention, which considers only wind, solar, and thermal power generation, i.e., case 2.
Fig. 13 is a result of multi-type flexible power supply joint optimization scheduling in case 2 according to an embodiment of the present invention.
Detailed Description
Referring to fig. 1, an embodiment of the present invention provides an optimized scheduling method for multiple types of flexible power supplies, where the optimized scheduling method uses the following source-network coordinated scheduling policy (the source-network coordinated scheduling policy refers to setting switching conditions and loading order of each type of unit according to a certain operation scheduling logic on the premise of ensuring safe and stable operation of a system):
and S100, sequentially arranging the minimum output capacity of the thermal power generating unit, the wind power photoelectric unit, the runoff water power generating unit and the storage capacity water power generating unit to be loaded.
Specifically, the capacity of the thermal power generating unit which is started up is segmented in advance and divided into a minimum output capacity and an adjustable output capacity. Based on the wind-solar power generation prediction of the hour level, setting a unit loading sequence: the minimum capacity is arranged to be loaded first. And carrying out multi-state processing on the photovoltaic and wind turbine generator, and preferentially arranging the photovoltaic and wind turbine generator to be loaded. And finally, arranging the runoff hydroelectric generating set and the reservoir capacity hydroelectric generating set to be loaded according to the hydrological conditions.
And step S101, calculating and judging the load source condition at the current moment.
Step S102, when the output of all the units is smaller than the current load (source < load), namely the current state needs to climb, the output is increased according to the sequence of a reservoir capacity hydroelectric generating unit, a thermal power generating unit and a gas generating unit; and if the current load is still less than the current load, arranging external power purchase.
Step S103, when the output of all the units is greater than the current load (source load), namely the slope is required to be reduced in the current state, the output is reduced according to the sequence of a thermal power unit, a storage capacity hydroelectric unit and a gas unit; if the load is still larger than the current load, the output is continuously reduced according to the sequence of the wind power generator, the photoelectric generator and the radial flow water generator, and the phenomena of wind abandoning, light abandoning and water abandoning occur.
Referring to fig. 2, on the basis of the source-network coordinated scheduling policy, the optimal scheduling method of the present invention further includes the following steps:
and S200, constructing an objective function of an optimized scheduling model by taking the minimum running cost as a target based on a source-network coordinated scheduling strategy.
Figure BDA0003232954030000041
Wherein, of represents the operation cost of the system in the scheduling period, Cg,tRepresenting the cost of the thermal engine g in normal operation at time t, cr,tPr,tIndicating the cost of normal operation of the gas-fired motor r at time t, VOLL LSi,tRepresenting the cost of electricity purchase that may be made from outside for system stability,
Figure BDA0003232954030000042
and
Figure BDA0003232954030000043
and (4) the penalty cost of wind abandon and light abandon is represented, wherein VOLW and VOLV are coefficients of wind abandon and light abandon penalty, and the normal operation cost of the hydraulic motor in the system is ignored.
Step S201, constraint conditions are constructed in advance.
The constructed constraint conditions comprise an operation cost constraint condition of the thermal power generator, a power balance constraint condition of the power system, a rotation positive and negative reserve capacity constraint condition, an operation constraint condition of the thermal power generator, an operation constraint condition of the hydroelectric power generator, an operation constraint condition of the gas power generator, a switch constraint condition of the conventional generator and upper and lower limit constraint conditions of wind power and photovoltaic power generation output.
And S202, solving the optimized scheduling model by combining the objective function in the step S200 and the constraint condition preset in the step S201, and obtaining parameters of optimized scheduling.
In step S203, the parameters acquired in step S202 are used for scheduling control.
The parameters of the optimized scheduling comprise the output condition of each controllable unit, the transmission power of the tie line and the economic cost after the optimized scheduling, and the output condition of the wind power grid-connection, the photovoltaic grid-connection, the thermal generator set, the hydroelectric generator set and the gas generator set, the transmission power of the tie line and the like in each time period are regulated and controlled according to the parameters.
The invention establishes an optimized scheduling model as a Mixed Integer Linear Programming (MILP) problem. And solving by adopting a CPLEX solver.
The specific contents of the constraint conditions constructed in advance in step S201 are as follows.
(1) Operating cost constraint condition of thermal power engine
Constructing a piecewise linearization function of the operating cost of the thermal power generating unit; and constructing an operation cost constraint condition of the thermal power machine. In order to make the whole model be a mixed integer linearization Model (MILP), the thermal engine cost function is piecewise linearized. As shown in fig. 3. Minimum power P of thermal power generating unitminWith maximum power PmaxIs divided into n equal parts, and each equal part is expressed by a formula
Figure BDA0003232954030000051
The linearization cost of the thermal power engine is expressed by the following formula:
Figure BDA0003232954030000052
(2) power system power balance constraint
Figure BDA0003232954030000053
Therein, sigmag，tPg，tThe output value of the g th thermal engine in the t period is represented; sigmar,tPr,tExpressing the output value, sigma of the No. r gas motor in the t time periodh，tPh，tThe output value of the h-th hydroelectric generating set in the t time period is represented; sigmaw,tPw,tAnd Σv,tPv,tRepresenting the grid connection quantity of the wind power and the photovoltaic generator set; dtIs the base load demand of the system for period t.
(3) Constraint condition of rotating positive and negative spare capacity
Figure BDA0003232954030000061
Figure BDA0003232954030000062
Wherein, U'GIs the power generation state of a conventional generator set at the moment t, wherein the current is U'GWhen being 0, the regular motor is in a closed state, U'GIs 1 to indicate that the conventional motor is in a starting state, G indicates the number of conventional motor groups, P'G,max、P′G,minThe maximum output and the minimum output of the conventional unit at the time t are obtained. RL,up、RL,downIndicating the positive and negative rotation standby needed by the system when the wind-solar-electricity is not accessed. R'WV,up、R′WV,downThe wind and solar power fluctuation is respectively used as backup for the up-down rotation required by wind and solar power fluctuation.
(4) Thermal power generating unit operation constraint condition
Including the ramp of thermal power generating unit, the upper and lower limit constraint conditions of output power
Figure BDA0003232954030000063
Wherein j represents the number of the unit, X (t, j) represents the operation state of the jth unit in the t period (0 represents that the unit is stopped, and 1 represents that the unit is operating). Meanwhile, the power p of the thermal power generating unitT(t, j) uphill gradient rate of unit
Figure BDA0003232954030000064
And down-grade rate
Figure BDA0003232954030000065
The limit of (a) is set to be,
Figure BDA0003232954030000066
Figure BDA0003232954030000067
(5) hydro-power generating unit operation constraint
Including constraints on operation of hydroelectric machine, hydroelectric conversion, constraints on daily flow of hydroelectric power figure 4 is a model parameter for hydroelectric power generation where x is the total water storage (m) in the reservoir3)；
Figure BDA0003232954030000068
Is the maximum running volume (m) of the reservoir3)；
Figure BDA0003232954030000069
Is the minimum running volume (m) of the reservoir3) (ii) a q is the displacement (m) of the turbine of the unit3S); s is station overflow flow (m)3In s). Hydroelectric machines follow the constraints of hydroelectric conversion capacity:
Ph＝k·η·hg·q
in the formula PhObtained in the process of converting hydraulic potential energy into electric energyPower (MW); k is equal to the gravitational constant multiplied by the specific gravity of water and is 0.00981[ MW/(m)3/s)/m]。
In order to ensure normal and stable operation of the upstream and downstream of the hydropower station, the daily flow limit constraint of the hydropower station needs to be set,
Figure BDA0003232954030000071
the upper limit and the lower limit of the output power of the hydroelectric generating set are restricted as follows:
Figure BDA0003232954030000072
(6) gas motor operation constraint condition
And setting the daily gas control quantity as an operation constraint of the gas motor.
Figure BDA0003232954030000073
The gas power station also needs output constraint and climbing constraint
Figure BDA0003232954030000074
Figure BDA0003232954030000075
(7) Switch constraint condition of conventional unit
Figure BDA0003232954030000076
Figure BDA0003232954030000077
Wherein, Y (t, j) and Z (t, j) are the start-up state and the stop state of the jth unit at the time period t, for Y (t, j), 0 represents not in the start-up state, and 1 represents being started; for Z (t, j), 0 indicates not in shutdown state, 1 indicates shutdown; s represents a startup and shutdown time period; s represents the time step for the minimum startup or shutdown. Further, the unit startup and shutdown running state logic constraint of three key state variables X, Y and Z of the unit is as follows:
Figure BDA0003232954030000081
(8) wind power and photovoltaic power generation output upper and lower limit constraint conditions
Wind power and photoelectric power connected to power grid are less than or equal to electric quantity actually generated by wind motor and photoelectric motor
Figure BDA0003232954030000082
Figure BDA0003232954030000083
Simulation experiment analysis:
as shown in FIG. 5, the tested multi-type flexible power system network is composed of a modified IEEE RTS-24-bus power system. The system consists of various types of flexible power supplies such as wind power, photovoltaic power, hydroelectric power, thermal power and the like. A Hexi wind power base and a Dunhuang photovoltaic base of Gansu province are selected as research objects. Wherein, 3 wind power plants are arranged on No. 8, No. 19 and No. 20 lines, and the capacities are respectively 250MW, 200MW and 300 MW. And 3 photovoltaic electric fields are arranged on No. 13, No. 15 and No. 22 wires, and the capacities are respectively 300MW, 300MW and 250 MW. The hydropower station is on a line No. 16 and a line No. 23, and the capacity is 155MW and 300 MW. Taking 1 day as a scheduling cycle and 1h as 1 scheduling period. The operation parameters of the hydropower station are shown in appendix A, and the salt pan gorges and the eight pan gorges in the appendix A are selected as the set for the operation of the hydropower machine participating in adjustment. The other parameters η u ═ η d ═ 5%, η e ═ 8%, and ω u ═ ω d ═ 25%.
Taking data of a certain typical day in winter as an example, fig. 6-11 show coordination optimization scheduling results of wind, water, gas, fire and various types of flexible power supplies, and the model realizes full consumption of wind, electricity and light. In fact, the objective function is the minimum value of the solving cost, and the light and wind abandoning punishment cost is added, so that the wind power and the photovoltaic power are preferentially merged into the power grid. It can be seen from the figure that, in the time period of sufficient wind and light resources, the output of other flexible power supplies is reduced, and a space is made for the power system to absorb wind power and photovoltaic power. The hydropower station and the gas turbine set increase the output in the peak period (18: 00-22: 00) of the system load, reduce the power generation in the valley period of the load, and achieve the purposes of stabilizing the fluctuation of the wind power and the photoelectric grid connection and reducing the load peak-valley difference by utilizing the flexible adjusting capability. The addition of water, electricity and gas electricity ensures that the load of the thermal power generating unit is as stable as possible under the condition of meeting the system load requirement, and reduces the frequent opening and closing of the thermal power generating unit.
A multi-type power supply coordination optimization model is taken as a situation 1, and a model only considering wind power photoelectricity and thermal power generation is taken as a situation 2. Fig. 12 is a model of the power system in case 2, and fig. 13 shows scheduling results of various power sources in case 2. Two different scene results were compared. In case 1, complete absorption of wind power and photovoltaic power generation can be achieved, and in case 2, the wind abandoning rate and the light abandoning rate reach 5.13%. This demonstrates that relying solely on complementary characteristics between wind power and photovoltaic power generation does not enable large-scale wind power and photovoltaic power generation to be completely absorbed by the grid. The standby capacity needs to be increased in a form of hybrid access of various power supplies, and the fluctuation of new energy when the new energy is accessed into a power grid is smoothed. In terms of cost, since the cost of calculating the access of hydropower to the power grid is neglected in case 1, and the phenomenon of wind and light abandonment occurs in case 2, the economic cost of case 1 is much lower than that of case 2. The total cost of all units in case 1 is reduced by 25.16% compared to the cost of case 2. If this reduced cost is converted to thermal power plant combustion standard coal and released SO2And CO2And when the gas is equal, the coordinated optimization scheduling method considering the multi-type power supply has considerable economic and environmental benefits.
In order to solve the problem of large-scale wind power photoelectric centralized grid-connected consumption, the invention provides an optimized scheduling method for promoting wind power photoelectric consumption by considering cooperation of multiple types of flexible power supplies, and simulation examples show that: the scheduling method can reduce the abandon amount of wind power and photovoltaic power generation, increase the grid-connected amount of the wind power and photovoltaic power generation, and reduce the operation cost of the thermal power generating unit while ensuring the system load and the standby requirement. In addition, complementary difference of wind energy and solar energy in time and space is utilized to smooth fluctuation of wind energy and solar energy power generation in a combined area, influence of random fluctuation of wind power generation and photovoltaic power generation on a power grid is relieved, and the method has important significance for improving safe and stable operation of the power grid.
The technical solution provided by the present invention is described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.

Claims (5)

1. An optimized scheduling method for multi-type flexible power supplies is characterized in that the following source-network coordinated scheduling strategy is used:
sequentially arranging the minimum output capacity of the thermal power generating unit, the wind power photoelectric generator set, the runoff water current generator set and the storage capacity water generator set with loads;
calculating and judging the load source condition at the current moment;
when the output of all the units is smaller than the current load, the output is increased according to the sequence of a reservoir capacity hydroelectric generating unit, a reservoir capacity thermal generating unit and a reservoir capacity gas generating unit; if the current load is still less than the current load, arranging external power purchase;
when the output of all the units is greater than the current load, reducing the output according to the sequence of the thermal power unit, the storage capacity hydroelectric unit and the gas unit; and if the load is still larger than the current load, continuously reducing the output according to the sequence of the wind power generator, the photoelectric generator and the runoff water generator.
2. The optimal scheduling method of claim 1, further comprising, before scheduling the minimum capacity of thermal power plants to export: and carrying out segmentation processing on the capacity of the started thermal power generating unit, and dividing the capacity into a minimum output capacity and an adjustable output capacity.
3. The optimized scheduling method of claim 1, further comprising:
constructing an objective function of an optimized scheduling model by taking the minimum running cost as a target based on the source-network coordinated scheduling strategy;
solving the optimized scheduling model by combining the objective function and a preset constraint condition, acquiring a parameter of optimized scheduling, and using the parameter for scheduling control; the parameters of the optimized scheduling comprise the output condition of each controllable unit, the transmission power of the tie line and the economic cost after the optimized scheduling.
4. The optimal scheduling method of claim 3 wherein the objective function is formulated as follows:
Figure RE-FDA0003316652250000011
wherein, of represents the operation cost of the system in the scheduling period, Cg,tRepresenting the cost of the thermal engine g in normal operation at time t, cr,tPr,tIndicating the cost of normal operation of the gas-fired motor r at time t, VOLL LSi,tRepresenting the cost of electricity purchase that may be made from outside for system stability,
Figure RE-FDA0003316652250000021
and
Figure RE-FDA0003316652250000022
and (4) the penalty cost of wind abandon and light abandon is represented, wherein VOLW and VOLV are coefficients of wind abandon and light abandon penalty, and the normal operation cost of the hydraulic motor in the system is ignored.
5. The optimal scheduling method according to claim 3, wherein the preset constraint conditions comprise an operation cost constraint condition of a thermal power generator, a power balance constraint condition of a power system, a rotation positive/negative reserve capacity constraint condition, an operation constraint condition of a thermal power generating unit, an operation constraint condition of a hydroelectric generating unit, an operation constraint condition of a gas power generator, a switch constraint condition of a conventional generating unit and upper and lower limit constraint conditions of wind power and photovoltaic power generation output.
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