CN116526544A - New energy power generation system flexible resource planning method, system and equipment - Google Patents
New energy power generation system flexible resource planning method, system and equipment Download PDFInfo
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- 238000010248 power generation Methods 0.000 title claims abstract description 58
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000003860 storage Methods 0.000 claims abstract description 132
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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
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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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
- 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]
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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
- 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
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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
- 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
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- 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
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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Abstract
According to the method, a possible operation scene and occurrence probability of each operation scene of a new energy power generation system in a future period are acquired, and a constructed system flexibility resource planning model taking the minimum expected cost of flexibility resources as an objective function is solved according to the acquired operation scene and occurrence probability of each operation scene, so that an optimal system flexibility resource planning scheme is obtained. The invention considers the running characteristic and the cluster effect of the distributed variable-speed pumped storage unit, not only effectively improves the running flexibility and the economy of the system, but also realizes the high-efficiency consumption of high-proportion renewable energy sources.
Description
Technical Field
The invention belongs to the technical field of power system planning, and particularly relates to a method, a system and equipment for planning flexible resources of a new energy power generation system.
Background
The construction of a novel power system taking new energy as a main body is an important measure for constructing a clean, low-carbon, safe and efficient energy system. Compared with the traditional thermal power generation, the new energy power generation has the advantages of large reserve, less pollution and the like. However, wind and light output is generally affected by geography and climate, and the output has randomness and fluctuation. In the early stage, thermal power generation is generally configured to stabilize fluctuation of new energy output such as wind, light and the like, and in the background of high-proportion renewable energy access, the configuration has weak regulation capability and poor flexibility in the operation process of a power system.
Pumped storage is an energy storage technology which is mature, large in capacity, low in electricity cost and slow in equipment depreciation, and is also a key for guaranteeing the safety of a power grid and promoting new energy consumption. The electric power resource planning of the pumped storage is researched, the flexibility requirements of new energy output, load fluctuation and the like can be better met, and the method has important significance in constructing a novel electric power system taking new energy as a main body.
The early constant-speed pumped storage power station is mainly used for coping with the dead water period of the basin. Compared with constant-speed pumped storage, the variable-speed pumped storage is not limited to rated rotation speed operation, so that the variable-speed pumped storage is more flexible, quick, efficient and reliable, and becomes a new direction and research hotspot in the field of global pumped storage. However, there is currently little research on flexible resource planning for variable speed pumped storage.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a method, a system and equipment for planning flexible resources of a new energy power generation system, which can effectively improve the flexibility of the system and realize the efficient consumption of high-proportion renewable energy.
In order to achieve the above object, the technical scheme of the present invention is as follows:
the flexible resource planning method of the new energy power generation system sequentially comprises the following steps:
step A, obtaining possible operation scenes of a new energy power generation system in a future period of time and occurrence probability of each operation scene;
and B, solving the constructed system flexibility resource planning model taking the minimum expected cost of the flexibility resource as an objective function according to the acquired operation scene and the occurrence probability thereof to obtain an optimal system flexibility resource planning scheme, wherein the system flexibility resource planning scheme comprises capacity and operation state data of distributed variable-speed pumped storage.
The objective function of the system flexible resource planning model is as follows:
in the above, C inv Investment cost g for distributed variable-speed pumping and accumulating unit and reservoir inv For annual investment conversion factor ρ s For the probability of occurrence of the s-th running scenario,N s to run scene number, C ope C, maintaining the running cost of the distributed variable-speed pumping and accumulating unit and the reservoir bes,s 、C coal,s 、C SS,s 、C w,s 、C pv,s The method is characterized in that the method comprises the following steps of respectively generating inadaptation cost, battery degradation cost, thermal power fuel cost, thermal power start-stop cost, wind discarding cost and light discarding cost for response of a demand side in an s-th operation scene.
The constraint conditions of the objective function comprise constant-speed pumped storage operation constraint, constant-speed pumped storage capacity constraint, distributed variable-speed pumped storage operation constraint and distributed variable-speed pumped storage capacity constraint;
the constant-speed pumped storage operation constraint is as follows:
x sp,i,t,s +x sg,i,t,s ≤1
P sp,i,t,s ＝x sp,i,t,s p 0
p sg,min x sg,i,t,s ≤P sg,i,t,s ≤p sg,max x sg,i,t,s
in the above, x sp,i,t,s 、x sg,i,t,s Respectively the pumping and generating states of the ith constant-speed pumping energy storage unit in the t period under the s-th operation scene, P sp,i,t,s 、P sg,i,t,s Pumping and generating power of the ith constant-speed pumped storage unit in the t period under the s-th operation scene respectively, p 0 、p sg,min 、p sg,max The rated pumping power, the minimum generating power and the maximum generating power of a single constant-speed pumping energy storage unit are respectively;
the storage capacity constraint of the constant-speed pumped storage is as follows:
V UR0,min ≤V UR0,t,s ≤V UR0,max
V LR0,min ≤V LR0,t,s ≤V LR0,max
in the above, V UR0,t,s 、V LR0,t,s C is the water storage capacity of the upper reservoir and the lower reservoir existing in the t period under the s-th operation scene g 、c p Respectively the power-flow conversion coefficients of pumping and generating of the pumping energy storage unit, n is the number of the constant-speed pumping energy storage units, deltat is the duration of each period of time, and V UR0,min 、V UR0,max Respectively the minimum water storage capacity and the maximum water storage capacity of the existing upper reservoir, V LR0,min 、V LR0,max The water storage capacity is the minimum and maximum of the existing lower reservoir respectively;
the distributed variable-speed pumped storage operation constraint is as follows:
x vp,j,t,s +x vg,j,t,s ≤1
in the above, w 1 、w 2 As a converted linear variable, x vp,j,t,s 、x vg,j,t,s Pumping and generating states of the jth distributed variable-speed pumped storage unit in the(s) th operation scene in the t period respectively are C, C L 、C U The loading capacity, the minimum loading capacity and the maximum loading capacity of a single distributed variable-speed pumped storage unit, P vp,j,t,s 、P vg,j,t,s Pumping and generating power of the jth distributed variable-speed pumping energy storage unit in the t period under the s-th operation scene respectively, and ρ vp , 1 、ρ vp , 2 The ratio coefficient between the lower pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit and the ratio coefficient between the upper pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit are respectively, p vg , 1 、ρ vg , 2 The ratio coefficients of the lower limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit and the upper limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit are respectively;
the storage capacity constraint of the distributed variable-speed pumped storage is as follows:
V UR1,j,t+1,s ＝V UR1,j,t,s -c g P vg,j,t,s Δt+c p P vp,j,t,s Δt
V LR1，j，t+1，s ＝V LR1，j，t，s +c g P vg，j，t，s Δt-c p P vp，j，t，s Δt
V UR1,min ≤V UR1,j,t,s ≤V UR1,max
V LR1,min ≤V LR1,j,t,s ≤V LR1,max
in the above, V UR1,j,t,s 、V LR1,j,t,s The water storage amounts of the upper reservoir and the lower reservoir respectively newly built at the t period under the s-th operation scene are V UR1,min 、V UR1,max Respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir, V LR1,min 、V LR1,max The water storage capacity is respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir.
The constraint conditions of the objective function also comprise battery energy storage operation constraint and thermal power unit constraint;
the battery energy storage operation constraint is as follows:
SOC min ≤SOC BES,t,s ≤SOC max
0≤P ch,t,s ≤P ch,max
0≤P dis,t,s ≤P dis,max
in the above, SOC BES,t,s For the state of charge of the battery energy storage at the t period under the s-th operation scene, P ch,t,s 、P dis,t,s Respectively charging and discharging power, eta of battery energy storage at t time intervals under the s-th operation scene ch 、η dis Charging and discharging efficiency and SOC of battery energy storage respectively min 、SOC max Respectively the lower and upper limits of the charge state of the battery energy storage, E R For battery energy storage capacity, P ch,max 、P dis,max Maximum charge and discharge power of the battery energy storage respectively;
the thermal power generating unit is constrained as follows:
P c，min，i x c，i，t，s ≤P c，i，t，s ≤P c，max，i x c，i，t，s
P c，i，t+1，s ≤P c，i，t，s +r u，i ·Δt·x c，i，t，s +P c，max，i (1-x c，i，t，s )
P c，it，s ≤P c，i，t+1，s +r d，i ·Δt·x c，i，t+l，s +P c，max，i (1-x c，i，t+1，s )
in the above, P c，i，t，s The power generation power of the ith thermal power unit in the t period under the s-th operation scene, P c，min，i 、P c，max，i Respectively the minimum and maximum output and x of the ith thermal power unit c，i，t，s Is the start-stop state variable of the ith thermal power unit in the t period under the s-th operation scene, r u，i 、r d，i The maximum ascending and descending climbing rates of the ith thermal power generating unit are respectively.
The constraint condition of the objective function further comprises a demand side response constraint, wherein the demand side response constraint is:
L e，t，s ＝L ebase，t，s +L ein，t，s
0≤L ein，t，s ≤L ein，max，t，s
in the above, L e，t，s 、L ebase，t，s Respectively the total load and the non-schedulable regular load of the t period under the s-th operation scene, L ein，t，s 、L ein，max，t，s Respectively the system elastic load and the maximum value thereof in the s-th operation scene at the T time period, wherein T is the total time period and D ein，s Is the total amount of elastic load in the s-th operation scene.
And B, solving the constructed system flexible resource planning model by adopting an uncertainty optimization method based on scene generation.
In the step A, the possible operation scenes and the occurrence probability of each operation scene of the new energy power generation system in a future period are generated by a Monte Carlo method based on the historical data of the system, wherein the historical data comprise environment data, system electric load data and operation state data of each energy conversion unit, and each energy conversion unit comprises a wind driven generator, a photovoltaic power generation device, a constant-speed pumped storage device and a distributed variable-speed pumped storage device.
In the step B, the system flexible resource planning scheme also comprises constant-speed pumped storage, battery storage, running state data of the thermal power unit and demand side response data.
The new energy power generation system flexible resource planning system comprises an operation scene and occurrence probability acquisition module, a planning model construction module and a planning model solving module;
the operation scene and occurrence probability acquisition module is used for acquiring possible operation scenes and occurrence probability of each operation scene of the new energy power generation system in a future period of time;
the planning model construction module is used for constructing a system flexibility resource planning model taking the minimum flexibility resource expected cost as an objective function;
and the planning model solving module is used for solving the system flexible resource planning model according to the acquired operation scene and the occurrence probability thereof to obtain an optimal system flexible resource planning scheme.
The flexible resource planning equipment of the new energy power generation system comprises a processor and a memory;
the memory is used for storing computer program codes and transmitting the computer program codes to the processor;
the processor is configured to execute the new energy power generation system flexible resource planning method of any one of claims 1-8 according to instructions in the computer program code.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method for planning the flexible resources of the new energy power generation system, the possible operation scenes and the occurrence probability of each operation scene of the new energy power generation system in a period of time in the future are firstly obtained, the constructed system flexible resource planning model taking the minimum expected cost of flexible resources as an objective function is solved according to the obtained operation scenes and the occurrence probability thereof, the optimal system flexible resource planning scheme is obtained, the planning model establishes operation constraint and reservoir capacity constraint models of a fixed-speed pumped storage unit based on the operation characteristic difference of the fixed-speed pumped storage unit and the variable-speed pumped storage unit, the models are converted into mixed integer linear planning problems taking the minimum expected cost as an objective through bilinear-linear constraint relaxation of the variable-speed pumped storage unit, the optimal planning scheme is obtained through solving, on one hand, the operation flexibility and the economical efficiency of the system are effectively improved, on the other hand, the realization of the model embodies the cluster effect of distributed variable-speed pumped storage, the power is flexibly adjusted according to the load change, the possible matching between the source loads is avoided, the frequent start-stop unit is avoided, and the high-efficiency energy can be efficiently consumed.
2. The flexible resource planning method of the new energy power generation system also considers the running states and the demand side response of other flexible resources such as battery energy storage, thermal power units and the like in a planning model, so that pumped storage can be better coordinated with the other flexible resources and the demand side to jointly ensure safe and reliable running of the system, and the system running flexibility and economy are further improved, and meanwhile high-proportion fluctuation wind-light new energy is effectively consumed.
Drawings
Fig. 1 is a schematic diagram of a new energy power generation system in embodiment 1.
Fig. 2 is a graph of pump power for the fixed and variable speed pumped-storage unit of example 1.
Fig. 3 is a graph of turbine power for the fixed and variable speed pumped-storage unit of example 1.
Fig. 4 is a battery state of charge curve for the fixed and variable speed pumped-hydro energy storage unit of example 1.
Fig. 5 is a graph showing the output curve of the thermal power generating unit in example 1.
Fig. 6 is a frame diagram of a flexible resource planning system of the new energy power generation system provided in embodiment 2.
Fig. 7 is a frame diagram of a new energy power generation system flexible resource planning apparatus provided in embodiment 3.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and the accompanying drawings.
The invention mainly considers the operation characteristics and the clustering effect of the distributed variable-speed pumped storage unit. Because the installed capacity of each distributed variable-speed pumping and accumulating unit in planned configuration is different, the running range of the distributed variable-speed pumping and accumulating unit is also different. When the randomness of the output of the wind and light new energy and the fluctuation of the load are absorbed, the distributed variable-speed pumped storage has a certain degree of clustering effect, namely the distributed variable-speed pumped storage can be matched with the start-stop linkage through the sequence coordination among all units so as to ensure that the fluctuation renewable energy and the load are matched as much as possible.
When the output of new energy is higher than the load demand, the pump is different from the fixed speed unit, pumping water according to rated power can be conducted, and certain deviation is caused between the combined output of a plurality of fixed speed units and redundant wind and light power, particularly when the output of new energy or load fluctuates, the fixed speed pump can be forced to stop one unit, so that the unit is frequently started and stopped, and the economical efficiency of the system is deteriorated. The multiple speed change units can flexibly coordinate pumping power by changing the rotating speed so as to consume redundant wind and light energy sources, and the economical and reliable operation of the system is ensured.
In order to economically and efficiently consume high-proportion fluctuation wind-solar new energy, the planning and operation process of the combined optimization system is realized, namely, the capacity planning and operation of distributed variable-speed pumped storage are optimized simultaneously, and the operation of constant-speed pumped storage, battery energy storage, thermal power units and demand side response is also optimized simultaneously. Through coordination of the various flexible resources, particularly coordination of distributed variable-speed pumped storage, various power regulation characteristics can be exerted to the greatest extent, fluctuation new energy is consumed to the greatest extent and most economically, and feasibility of a planning scheme is finally ensured.
Example 1:
the embodiment aims at the new energy power generation system shown in fig. 1, the system comprises a wind driven generator, a photovoltaic power generation device, battery energy storage, constant-speed pumped storage, distributed variable-speed pumped storage and 2 thermal power units, wherein the installed capacity scale of the variable-speed pumped storage unit is 0-100MW, the rated power of the two thermal power units is 180MW and 250MW respectively, the rated capacity of the battery energy storage is 100MW, the charging and discharging efficiency is 0.9, the total amount of elastic load responded on the demand side is 30% of the total amount of daily base load, and the basic concept is that: the electric energy generated by the wind driven generator and the photovoltaic power generation device is directly supplied to surrounding loads; the flexible resources such as pumped storage, battery storage, demand response and the like bear the functions of balancing power and stabilizing new energy fluctuation; when the output of the new energy fluctuates, the system power shortage is supplemented by the thermal power unit, the pumped storage and the battery storage, otherwise, the abundant wind-solar power generation is stored in the pumped storage and the battery storage; meanwhile, the demand side response adjusts the electricity demand through actively adjusting the elastic load, so that the system flexibility is improved, and the safe and reliable operation of the system is ensured together with flexible resources.
The flexible resource planning method of the new energy power generation system sequentially comprises the following steps:
1. generating and acquiring possible operation scenes and occurrence probability of each operation scene of the system in a future period of time through a Monte Carlo method based on historical data of a new energy power generation system, wherein the historical data comprise environment data, system electric load data and operation state data of each energy conversion unit, and each energy conversion unit comprises a wind driven generator, a photovoltaic power generation device, constant-speed pumped storage and distributed variable-speed pumped storage.
2. According to the acquired operation scene and occurrence probability thereof, a system flexibility resource planning model is solved and constructed by adopting an uncertainty optimization method based on scene generation, and an optimal system flexibility resource planning scheme is obtained, wherein the system flexibility resource planning scheme comprises capacity and operation state data of distributed variable-speed pumped storage, constant-speed pumped storage, battery energy storage, operation state data of a thermal power generating unit and demand side response data, and an objective function of the system flexibility resource planning model is as follows:
in the above, item C inv The investment cost of the distributed variable speed pumping and accumulating unit and the reservoir is calculated by adding the cost of system operation and maintenance and the cost of other flexible resource operation to the cost of investment g inv For annual investment conversion factors related to the rate of discount, the planning year, ρ s For the probability of occurrence of the s-th running scenario,N s to run scene number, C ope C, maintaining the running cost of the distributed variable-speed pumping and accumulating unit and the reservoir bes,s 、C coal,s 、C SS,s 、C w,s 、C pv,s The method is characterized in that the method comprises the following steps of respectively generating inadaptation cost, battery degradation cost, thermal power fuel cost, thermal power start-stop cost, wind discarding cost and light discarding cost for response of a demand side in an s-th operation scene.
The constraint conditions of the objective function comprise constant-speed pumped storage operation constraint, constant-speed pumped storage capacity constraint, distributed variable-speed pumped storage operation constraint, distributed variable-speed pumped storage capacity constraint, battery energy storage operation constraint, thermal power generating unit constraint and demand side response constraint;
the motor rotating speed of the constant-speed pumping and accumulating unit can not be adjusted when the water pump works and can only work at rated rotating speed and power, so the following constant-speed pumping and accumulating operation constraint is established:
x sp,i,t,s +x sg,i,t,s ≤1
P sp,i,t,s ＝x sp,i,t,s p 0
p sg,min x sg,i,t,s ≤P sg,i,t,s ≤p sg,max x sg,i,t,s
in the above, x sp,i,t,s 、x sg,i,t,s Respectively the pumping and generating states of the ith constant-speed pumping energy storage unit in the t period under the s-th operation scene, P sp,i,t,s 、P sg,i,t,s Pumping and generating power of the ith constant-speed pumped storage unit in the t period under the s-th operation scene respectively, p 0 、p sg,min 、p sg,max Rated pumping power of single constant-speed pumping energy storage unitMinimum generated power, maximum generated power.
The constant-speed pumped storage is used as the existing flexible resource, a plurality of constant-speed pumped storage sets are considered to share the same existing reservoir, other reservoirs and power stations for constant-speed pumping and storage are not needed to be newly built, and the following reservoir capacity constraint of the constant-speed pumped storage is established:
V UR0,min ≤V UR0,t,s ≤V UR0,max
V LR0,min ≤V LR0,t,s ≤V LR0,max
in the above, V UR0,t,s 、V LR0,t,s C is the water storage capacity of the upper reservoir and the lower reservoir existing in the t period under the s-th operation scene g 、c p Respectively the power-flow conversion coefficients of pumping and generating of the pumping energy storage unit, n is the number of the constant-speed pumping energy storage units, deltat is the duration of each period of time, and V UR0,min 、V UR0,max Respectively the minimum water storage capacity and the maximum water storage capacity of the existing upper reservoir, V LR0,min 、V LR0,max The water storage capacity is respectively the minimum water storage capacity and the maximum water storage capacity of the existing lower reservoir.
Compared with a constant-speed pumping and accumulating unit, the variable-speed pumping and accumulating unit can change the rotating speed to search the optimal operation condition, so that the power can be adjusted, and the distributed variable-speed pumping and accumulating operation constraint is as follows:
x vp,j,t,s +x vg,j,t,s ≤1
p vp,min x vp,j,t,s ≤P vp,j,t,s ≤p vp,max x vp,j,t,s
p vg,min x vg,j,t,s ≤P vg,j,t,s ≤p vg,max x vg,j,t,s
in the above, x vp,j,t,s 、x vg,j,t,s Respectively pumping and generating states of the jth distributed variable-speed pumped storage unit in the t period under the s-th operation scene, and P vp,j,t,s 、P vg,j,t,s Pumping and generating power of the jth distributed variable-speed pumping energy storage unit in the t period under the s-th operation scene respectively, p vp,min 、p vp,max Minimum and maximum pumping power, p, of a single distributed variable-speed pumping energy storage unit respectively vg,min 、p vg,max The minimum and maximum power generation power of a single distributed variable-speed pumped storage unit are respectively;
due to p in the constraint equation vp,min 、p vp,max 、p vg,min 、p vg,max Generally related to installed capacity, related to x vp,j,t,s 、x vg,j,t,s The nonlinear constraint is formed after multiplication, so the bilinear constraint is converted to the following linear constraint based on the mccomick envelope:
in the above, w 1 、w 2 C, C as a converted linear variable L 、C U The installed capacity, the minimum installed capacity and the maximum installed capacity of the single distributed variable-speed pumped storage unit are respectively, and p vp,1 、ρ vp,2 The ratio coefficient between the lower pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit and the ratio coefficient between the upper pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit are respectively, p vg,1 、ρ vg,2 The ratio coefficients of the lower limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit and the upper limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit are respectively.
The distributed variable-speed pumped storage can reasonably utilize local hydrologic conditions to match with the existing flexible resources to consume the fluctuation new energy. Therefore, each newly-built distributed variable-speed pumping and accumulating unit is considered to be newly built with a small reservoir, and the following reservoir capacity constraint of the distributed variable-speed pumping and accumulating unit is constructed:
V UR1，j，t+1，s ＝V UR1，j，t，s -c g P vg，j，t，s Δt+c p P vp，j，t，s Δt
V LR1，j，t+1，s ＝V LR1，j，t，s +c g P vg，j，t，s Δt-c p P vp，j，t，s Δt
V UR1，min ≤V UR1，j，t，s ≤V UR1，max
V LR1，min ≤V LR1，j，t，s ≤V LR1，max
in the above, V UR1，j，t，s 、V LR1，j，t，s The water storage amounts of the upper reservoir and the lower reservoir respectively newly built at the t period under the s-th operation scene are V UR1，min 、V UR1，max Respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir, V LR1，min 、V LR1，max The water storage capacity is respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir.
Too fast a charge and discharge can degrade the performance of the battery energy storage system and shorten its life. The following operational constraints are therefore imposed on battery energy storage:
SOC min ≤SOC BES，t，s ≤SOC max
0≤P ch，t，s ≤P ch，max
0≤P dis，t，s ≤P dis，max
in the above, SOC BES，t，s For the state of charge of the battery energy storage at the t period under the s-th operation scene, P ch，t，s 、P dis，t，s Charging for respectively storing energy of batteries at t time intervals in s-th operation sceneDischarge power, eta ch 、η dis Charging and discharging efficiency and SOC of battery energy storage respectively min 、SOC max Respectively the lower and upper limits of the charge state of the battery energy storage, E R For battery energy storage capacity, P ch，max 、P dis，max Maximum charge and discharge power of the battery energy storage respectively;
the power generation power and the ascending and descending climbing rate of the thermal power generating unit are limited to a certain extent, namely the thermal power generating unit is constrained to be:
P c，min，i x c，i，t，s ≤P c，i，t，s ≤P c，max，i x c，i，t，s
P c，i，t+1，s ≤P c，i，t，s +r u，i ·Δt·x c，i，t，s +P c，max，i (1-x c，i，t，s )
P c，i，t，s ≤P c，i，t+1，s +r d，i ·Δt·x c，i，t+1，s +P c，max，i (1-x c，i，t+1，s )
in the above, P c，i，t，s The power generation power of the ith thermal power unit in the t period under the s-th operation scene, P c，min，i 、P c,max,i Respectively the minimum and maximum output and x of the ith thermal power unit c,i,t,s Is the start-stop state variable of the ith thermal power unit in the t period under the s-th operation scene, r u,i 、r d,i The maximum ascending and descending climbing rates of the ith thermal power generating unit are respectively.
The scheduling of the demand side response must be limited to a certain range, thus constructing the following demand side response constraints:
L e,t,s ＝L ebase,t,s +L ein,t,s
0≤L ein,t,s ≤L ein,max,t,s
in the above, L e,t,s 、L ebase,t,s Respectively isTotal load of t period under s-th operation scene, non-schedulable normal load, L ein,t,s 、L ein,max,t,s Respectively the system elastic load and the maximum value thereof in the s-th operation scene at the T time period, wherein T is the total time period and D ein,s Is the total amount of elastic load in the s-th operation scene.
The flexible resource planning scheme with a plurality of constant-speed pumped storage is taken as a comparison example, compared with the optimal system flexible resource planning scheme obtained by the embodiment, the result shows that,
the installed capacities of the fixed and variable speed pumped-storage units of this example and the comparative example were 234.37MW, and the expected total costs of this example and the comparative example were 4280.86 ×10, respectively 7 Yuan 4283.58 ×10 7 And (5) a meta.
In the optimal system flexibility resource planning scheme obtained by the embodiment, the power curves of the water pump of the fixed and variable speed pumped storage unit are shown in fig. 2, the power curves of the water turbine of the fixed and variable speed pumped storage unit are shown in fig. 3, the charge state curves of the battery of the fixed and variable speed pumped storage unit are shown in fig. 4, and the thermal power unit output of the fixed and variable speed pumped storage unit is shown in fig. 5.
As can be seen from fig. 2 and 3, the capacity planning of the distributed variable-speed pumped storage unit has large difference, and the power can be regulated in a constraint range during pumping, when the new energy or the fluctuation of the demand side is handled, the distributed variable-speed pumped storage unit quickly makes start-stop linkage through sequence coordination among the variable-speed units, so that a certain degree of clustering effect is shown, and the time periods of 5, 12, 18 and the like are shown more obviously in the figures. The capacity difference of the constant speed units is smaller, because of the constraint of the units, the water pumping working point of each constant speed unit during starting can only be positioned on one parallel line, so that the capacity difference of each unit is smaller in order to meet the requirement of system flexibility, the effect of the constant speed units is poorer when the same fluctuation is absorbed, and the economical efficiency of a planning scheme is also relatively poorer.
Example 2:
as shown in fig. 6, the flexible resource planning system of the new energy power generation system comprises an operation scene and occurrence probability acquisition module 1, a planning model solving module 2 and a planning model solving module 3;
the operation scene and occurrence probability acquisition module 1 is used for acquiring possible operation scenes of the new energy power generation system in a future period and occurrence probability of each operation scene;
the planning model solving module 2 is used for constructing a system flexibility resource planning model taking the minimum flexible resource expected cost as an objective function;
the planning model solving module 3 is used for solving the system flexible resource planning model according to the acquired operation scene and the occurrence probability thereof to obtain an optimal system flexible resource planning scheme.
Example 3:
as shown in fig. 7, the flexible resource planning device for the new energy power generation system comprises a processor 21 and a memory 22, wherein the memory 22 is used for storing computer program codes 23 and transmitting the computer program codes 23 to the processor 22, and the processor 22 is used for executing the flexible resource planning method for the new energy power generation system according to instructions in the computer program codes 23.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The solutions in the embodiments of the present application may be implemented in various computer languages, for example, object-oriented programming language Java, and an transliterated scripting language JavaScript, etc.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (9)
1. A flexible resource planning method for a new energy power generation system is characterized in that,
the planning method sequentially comprises the following steps:
step A, obtaining possible operation scenes of a new energy power generation system in a future period of time and occurrence probability of each operation scene;
and B, solving the constructed system flexibility resource planning model taking the minimum expected cost of the flexibility resource as an objective function according to the acquired operation scene and the occurrence probability thereof to obtain an optimal system flexibility resource planning scheme, wherein the system flexibility resource planning scheme comprises capacity and operation state data of distributed variable-speed pumped storage.
2. The flexible resource planning method of new energy power generation system according to claim 1, wherein,
the objective function of the system flexible resource planning model is as follows:
in the above, C inv Investment cost g for distributed variable-speed pumping and accumulating unit and reservoir inv For annual investment conversion factor ρ s For the probability of occurrence of the s-th running scenario,N s to run scene number, C ope C, maintaining the running cost of the distributed variable-speed pumping and accumulating unit and the reservoir bes,s 、C coal,s 、C SS,s 、C w,s 、C pv,s The method is characterized in that the method comprises the following steps of respectively generating inadaptation cost, battery degradation cost, thermal power fuel cost, thermal power start-stop cost, wind discarding cost and light discarding cost for response of a demand side in an s-th operation scene.
3. The flexible resource planning method of new energy power generation system according to claim 2, wherein,
the constraint conditions of the objective function comprise constant-speed pumped storage operation constraint, constant-speed pumped storage capacity constraint, distributed variable-speed pumped storage operation constraint and distributed variable-speed pumped storage capacity constraint;
the constant-speed pumped storage operation constraint is as follows:
x sp,i,t,s +x sg,i,t,s ≤1
P sp,i,t,s ＝x sp,i,t,s p 0
p sg,min x sg,i,t,s ≤P sg,i,t,s ≤p sg,max x sg,i,t,s
in the above, x sp,i,t,s 、x sg,i,t,s Respectively the pumping and generating states of the ith constant-speed pumping energy storage unit in the t period under the s-th operation scene, P sp,i,t,s 、P sg,i,t,s Pumping and generating power of the ith constant-speed pumped storage unit in the t period under the s-th operation scene respectively, p 0 、p sg,min 、p sg,max The rated pumping power, the minimum generating power and the maximum generating power of a single constant-speed pumping energy storage unit are respectively;
the storage capacity constraint of the constant-speed pumped storage is as follows:
V UR0,min ≤V UR0,t,s ≤V UR0,max
V LR0,min ≤V LR0,t,s ≤V LR0,max
in the above, V UR0,t,s 、V LR0,t,s C is the water storage capacity of the upper reservoir and the lower reservoir existing in the t period under the s-th operation scene g 、c p Respectively the power-flow conversion coefficients of pumping and generating of the pumping energy storage unit, n is the number of the constant-speed pumping energy storage units, deltat is the duration of each period of time, and V UR0,min 、V UR0,max Respectively the minimum water storage capacity and the maximum water storage capacity of the existing upper reservoir, V LR0,min 、V LR0,max The water storage capacity is the minimum and maximum of the existing lower reservoir respectively;
the distributed variable-speed pumped storage operation constraint is as follows:
x vp,j,t,s +x vg,j,t,s ≤1
in the above, w 1 、w 2 As a converted linear variable, x vp,j,t,s 、x vg,j,t,s Pumping and generating states of the jth distributed variable-speed pumped storage unit in the(s) th operation scene in the t period respectively are C, C L 、C U The loading capacity, the minimum loading capacity and the maximum loading capacity of a single distributed variable-speed pumped storage unit, P vp,j,t,s 、P vg,j,t,s Pumping and generating power of the jth distributed variable-speed pumping energy storage unit in the t period under the s-th operation scene respectively, and ρ vp，1 、ρ vp,2 The ratio coefficient between the lower pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit and the ratio coefficient between the upper pumping power limit and the installed capacity of the distributed variable-speed pumping energy storage unit are respectively, p vg,1 、ρ vg,2 The ratio coefficients of the lower limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit and the upper limit of the power generation power and the installed capacity of the distributed variable-speed pumped storage unit are respectively;
the storage capacity constraint of the distributed variable-speed pumped storage is as follows:
V UR1,j,t+1,s ＝V UR1,j,t,s -c g P vg,j,t,s Δt+c p P vp,j,t,s Δt
V LR1，j，t+1，s ＝V LR1，j，t，s +c g P vg，j，t，s Δt-c p P vp，j，t，s Δt
V UR1,min ≤V UR1,j,t,s ≤V UR1,max
V LR1,min ≤V LR1,j,t,s ≤V LR1,max
in the above, V UR1,j,t,s 、V LR1,j,t,s The water storage amounts of the upper reservoir and the lower reservoir respectively newly built at the t period under the s-th operation scene are V UR1,min 、V UR1,max Respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir, V LR1,min 、V LR1,max The water storage capacity is respectively the minimum water storage capacity and the maximum water storage capacity of the newly built upper reservoir.
4. The flexible resource planning method of new energy power generation system according to claim 3, wherein,
the constraint conditions of the objective function also comprise battery energy storage operation constraint and thermal power unit constraint;
the battery energy storage operation constraint is as follows:
SOC min ≤SOC BES,t,s ≤SOC max
0≤P ch,t,s ≤P ch,max
0≤P dis,t,s ≤P dis,max
in the above, SOC BES,t,s For the state of charge of the battery energy storage at the t period under the s-th operation scene, P ch,t,s 、P dis,t,s Respectively charging and discharging power, eta of battery energy storage at t time intervals under the s-th operation scene ch 、η dis Charging and discharging efficiency and SOC of battery energy storage respectively min 、SOC max Respectively the lower and upper limits of the charge state of the battery energy storage, E R For battery energy storage capacity, P ch,max 、P dis,max Maximum charge and discharge power of the battery energy storage respectively;
the thermal power generating unit is constrained as follows:
P c,min,i x c,i,t,s ≤P c,i.t.s ≤P c,max,i x c,i,t,s
P c，i，t+1，s ≤P c，i，t，s +r u，i ·Δt·x c，i，t，s +P c，max，i (1-P c，max，i (1-x c，i，t，s )
P c，i，t，s ≤P c，i，t+1，s +r d，i ·Δt·x c，i，t+1，s +P c，max，i (1-x c，i，t+1，s )
in the above, P c,i.t.s The power generation power of the ith thermal power unit in the t period under the s-th operation scene, P c,min,i 、P c,max,i Respectively the minimum and maximum output and x of the ith thermal power unit c,i,t,s Is the start-stop state variable of the ith thermal power unit in the t period under the s-th operation scene, r u,i 、r d,i The maximum ascending and descending climbing rates of the ith thermal power generating unit are respectively.
5. The flexible resource planning method of new energy power generation system according to claim 4, wherein,
the constraint condition of the objective function further comprises a demand side response constraint, wherein the demand side response constraint is:
L e,t,s ＝L ebase,t,s +L ein,t,s
0≤L ein,t,s ≤L ein,max,t,s
in the above, L e,t,s 、L ebase,t,s Respectively the total load and the non-schedulable regular load of the t period under the s-th operation scene, L ein,t,s 、L ein,max,t,s Respectively the system elastic load and the maximum value thereof in the s-th operation scene at the T time period, wherein T is the total time period and D ein,s Is the firstTotal amount of elastic load under s running scenarios.
6. The flexible resource planning method of new energy power generation system according to claim 1, wherein,
and B, solving the constructed system flexible resource planning model by adopting an uncertainty optimization method based on scene generation.
7. The flexible resource planning method of new energy power generation system according to claim 6, wherein,
in the step A, the possible operation scenes and the occurrence probability of each operation scene of the new energy power generation system in a future period are generated by a Monte Carlo method based on the historical data of the system, wherein the historical data comprise environment data, system electric load data and operation state data of each energy conversion unit, and each energy conversion unit comprises a wind driven generator, a photovoltaic power generation device, a constant-speed pumped storage device and a distributed variable-speed pumped storage device.
8. The flexible resource planning system of the new energy power generation system is characterized in that,
the system comprises an operation scene and occurrence probability acquisition module (1), a planning model construction module (2) and a planning model solving module (3);
the operation scene and occurrence probability acquisition module (1) is used for acquiring possible operation scenes of the new energy power generation system in a future period and occurrence probability of each operation scene;
the planning model construction module (2) is used for constructing a system flexibility resource planning model taking the minimum expected cost of flexibility resources as an objective function;
and the planning model solving module (3) is used for solving the system flexibility resource planning model according to the acquired operation scene and the occurrence probability thereof to obtain an optimal system flexibility resource planning scheme.
9. The flexible resource planning equipment of the new energy power generation system is characterized in that,
comprises a processor (21) and a memory (22);
-said memory (22) is adapted to store computer program code (23) and to transmit said computer program code (23) to said processor (21);
the processor (21) is configured to execute the new energy power generation system flexible resource planning method according to any of claims 1-7 according to instructions in the computer program code (23).
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