CN110378523B - Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving - Google Patents
Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving Download PDFInfo
- Publication number
- CN110378523B CN110378523B CN201910598878.2A CN201910598878A CN110378523B CN 110378523 B CN110378523 B CN 110378523B CN 201910598878 A CN201910598878 A CN 201910598878A CN 110378523 B CN110378523 B CN 110378523B
- Authority
- CN
- China
- Prior art keywords
- unit
- power
- energy storage
- thermal power
- thermal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000004146 energy storage Methods 0.000 claims abstract description 71
- 238000010438 heat treatment Methods 0.000 claims abstract description 49
- 238000010248 power generation Methods 0.000 claims abstract description 26
- 230000008901 benefit Effects 0.000 claims abstract description 14
- 230000005611 electricity Effects 0.000 claims abstract description 12
- 238000012423 maintenance Methods 0.000 claims abstract description 7
- 238000005338 heat storage Methods 0.000 claims description 26
- 239000003245 coal Substances 0.000 claims description 13
- 238000009825 accumulation Methods 0.000 claims description 12
- 230000009194 climbing Effects 0.000 claims description 11
- 238000005192 partition Methods 0.000 claims description 9
- 238000005457 optimization Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 4
- 238000009833 condensation Methods 0.000 claims description 4
- 230000005494 condensation Effects 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 3
- 239000000446 fuel Substances 0.000 claims description 3
- 230000000452 restraining effect Effects 0.000 claims description 3
- 238000010977 unit operation Methods 0.000 claims description 3
- 238000005265 energy consumption Methods 0.000 abstract description 3
- 239000002245 particle Substances 0.000 description 5
- 230000000875 corresponding effect Effects 0.000 description 4
- 230000009467 reduction Effects 0.000 description 3
- 238000004134 energy conservation Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005485 electric heating Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
A capacity allocation method for thermoelectric and wind power combined participation in power grid peak shaving belongs to the technical field of power grid peak shaving promotion energy consumption of thermoelectric units, and particularly relates to a capacity allocation method for thermoelectric and wind power combined participation in power grid peak shaving. The invention provides a capacity allocation method for a combined participation of thermoelectric and wind power in power grid peak shaving. The invention comprises the following steps: setting the optimized objective function asWherein R is electricity selling benefits (including wind generating sets and thermal power generating sets) and heat supply benefits; c is the running cost of the wind turbine generator, the thermal power generating unit and the energy storage heating unit; t=1, 2, …,24, corresponding to 24 times of day-ahead schedule;the method comprises the steps of surfing the Internet for wind power;the method comprises the steps of (1) surfing electricity price for a thermal power generating unit;the heat supply price is supplied to the energy storage heating unit;andthe power generation power of the wind power plant and the thermal power generating unit respectively;a heating load allocated to the energy storage heating unit; c (C) c 、C w 、C x The system is the maintenance cost of a thermal power unit, a wind power unit and an energy storage heating unit.
Description
Technical Field
The invention belongs to the technical field of power grid peak regulation promotion energy consumption of thermoelectric units, and particularly relates to a capacity allocation method for thermoelectric wind power combined participation in power grid peak regulation.
Background
Thermal power generation is still the main force army in the power industry of China at present, under the pressure of taking carbon emission reduction as a target and taking energy conservation and emission reduction as a large situation, the power generation structure mainly taking thermal power needs to be changed urgently, and novel clean energy sources are developed greatly.
Wind power is used as a renewable, pollution-free and high-universality energy source, and is a preferred target for developing clean energy sources.
The domestic heat energy consumption is mainly provided by a coal-fired boiler, and a large amount of pollutants are generated while a large amount of primary energy is consumed, so that the environment is seriously polluted. The heat storage equipment can be used for absorbing the abandoned wind resources to a greater extent, so that the construction of some flexible thermal power resources and heat storage heating units on a large-scale wind power base is considered to be used for wind power peak shaving.
Considering the overall resource distribution condition and power distribution of China, the wind power and thermal power supply can be jointly planned in areas rich in wind energy resources and coal resources in order to fully exert the characteristics of wind power and thermal power. From the resource distribution point of view, the coal resource distribution is not much different from the wind power resource distribution. Therefore, the pollution of the thermal power resources can be compensated by utilizing the cleanliness of the wind power resources and the convenience of the heat storage heating equipment, and the uncertainty, the volatility and the anti-peak shaving characteristics of the wind power unit are compensated by utilizing the stability of the thermal power unit and the economy of the heat storage heating unit. The method utilizes local resources to the maximum extent, optimizes the power supply composition, and simultaneously makes contribution to environmental protection industry.
In a multi-power hybrid power generation system, various power supplies are mutually restricted and correlated, and the capacity ratio is optimized. The wind power generation, the thermal power generation and the energy storage and heating are also interrelated, under the framework of the electric heating comprehensive energy system, the proportioning relationship of various power supplies can be realized, the power supply proportioning is more reasonable under the condition of meeting the constraint of power supply and heat supply, and the maximization of the energy conservation and emission reduction benefits is realized.
Disclosure of Invention
The invention aims at the problems and provides a capacity allocation method for the combined participation of thermoelectric power and wind power in power grid peak shaving.
In order to achieve the above purpose, the invention adopts the following technical scheme that the invention comprises the following steps:
setting the optimized objective function as
Wherein R is electricity selling benefits (including wind generating sets and thermal power generating sets) and heat supply benefits; c is the running cost of the wind turbine generator, the thermal power generating unit and the energy storage heating unit; t=1, 2, …,24, corresponding to 24 times of day-ahead schedule;is wind powerThe online electricity price; />The method comprises the steps of (1) surfing electricity price for a thermal power generating unit; />The heat supply price is supplied to the energy storage heating unit; />And->The power generation power of the wind power plant and the thermal power generating unit respectively; />A heating load allocated to the energy storage heating unit; c (C) c 、C w 、C x The system is the maintenance cost of a thermal power unit, a wind power unit and an energy storage heating unit. F (F) t Is the running cost of the energy storage heating unit and the thermal power unit system.
The operation cost of the energy storage heating unit and the thermal power unit system can be expressed as follows:
wherein a is i 、b i 、c i The operation cost coefficient of the heat storage-thermoelectric unit is; c (C) V Is a unit operation parameter;the heat supply power is supplied to the thermal power generating unit; s is S t For the heat storage and release power of the heat storage device at time t (heat release time S t Negative).
Wherein the maintenance cost C of the thermal power unit, the wind power unit and the energy storage heating unit c 、C w 、C x The expression is as follows:
C c ＝C cd +C cv
C w ＝C wd +C wv
C x ＝C xd +C xv
wherein C is cd 、C wd 、C xd Respectively reducing the cost of the thermal power generation unit, the wind power generation unit and the energy storage unit; c (C) cv 、C wv 、C xv The variable costs of the thermal power generation, wind power generation and energy storage units are respectively.
As a preferable scheme, the variable cost of the thermal power and energy storage unit is as follows:
in the thermal power generating unit, the variable cost C cv Mainly comprises coal purchasing cost and energy storage unit variable cost C xv The method mainly comprises the step of coal purchasing cost for charging a heat accumulating boiler; variable cost C of wind turbine generator system wv Can be considered as 0; v i The method is characterized in that v is a state variable of the thermal power generating unit participating in wind power peak regulation x The energy storage unit participates in the wind power peak regulation state variable, when v x When the energy storage unit is in the range of (1), the energy storage unit is used as a wind power peak regulation power supply, and when v x When the energy storage unit is=0, the energy storage unit is not used as a wind power peak shaving power supply. Gamma is the price of fire coal; u (u) it The method is characterized in that the method is a state variable of the thermal power generating unit at moment, the starting state is 1, and the stopping state is 0; u (u) xt The method is characterized in that the method is a state variable of the energy storage unit at the time t, the starting state is 1, and the stopping state is 0; SU (SU) i The method comprises the following steps of (1) burning coal consumption for starting a thermal power unit; YU (Ye) x The fuel consumption for charging the energy storage unit; p (P) t And c is the output of the unit at the time t.
As another preferred aspect, the present power balance constraint:
wherein N is the set n=g of thermal power generating units in the region c +G b +G e ；Wind power which is connected with the grid at the moment t in the system is obtained;the system is electrically loaded at time t.
Heating constraint:
where k=1, 2, …, M is the total number of heating zones;the total heat load required to be born by the k-th partition thermal power plant at the moment t; />The heat accumulation amount at the time t of the k-th partition heat accumulation device; />Respectively the collection of the suction type and back pressure type units of the kth partition
Unit constraint
Upper and lower limit constraint of active output of a unit:
in the method, in the process of the invention,the minimum and maximum active output of the unit i under the condensed gas working condition are respectively; c m,i C for unit i m A value; c v,i C for unit i v A value; k (K) i Is constant.
Upper and lower limit constraint of unit heat output:
in the method, in the process of the invention,the maximum heat output limit for the unit i is determined by the heat exchanger capacity.
Unit climbing rate constraint:
wherein P is up,i 、P down,i And (5) respectively restraining the upward and downward climbing rates of the unit i. The output change of the general thermal power generating unit is realized by changing the state of a boiler, so that the climbing speed constraint corresponding to the electric and thermal output of the unit is converted into the electric power constraint under the pure condensation condition before steam extraction.
When c v ＝0、c m When=0, the unit is a pure condensing unit, and the constraint is unchanged.
When c v ＝0、c m Not equal to 0, the back pressure thermoelectric unit is defined as follows:
thermal storage device operation constraints
Heat storage device heat storage/release capacity constraint:
wherein P is h,k,cmax 、P h,k,fmax The maximum heat accumulation and release power of the heat accumulation device are respectively.
Capacity constraint of the thermal storage device:
wherein S is h,k,max Is the heat storage capacity of the heat storage device.
The invention has the beneficial effects that.
The invention solves the problem that the deep frequency modulation and peak shaving of the power grid are difficult after large-scale grid connection of wind power. And meanwhile, the most economical power supply capacity ratio is finished through the investment and the operation cost of each unit.
The invention optimizes the capacity ratio of various power supplies in the power grid system based on the operation characteristics and constraint conditions of various power supplies and heat sources in the power grid system and with the aim of minimizing the cost of the wind power, thermal power and energy storage combined planning system.
The invention establishes operation constraint conditions of the power grid system based on the power and heat demand constraint in the power grid system, the conventional unit utilization constraint and the energy storage device system constraint.
The invention establishes an economic benefit expression of the power grid system based on electricity selling benefits, heat supply benefits and related cost coefficients in the power grid system.
According to the method, the running constraint conditions are combined, particle swarm algorithm solving is carried out based on the benefit expression, and the economical capacity ratio of the wind power, thermal power and energy storage combined system is calculated.
According to the invention, under the frame of the comprehensive energy system, the power generation and heating cost is minimized through the proportioning relation of the capacities of the wind power, the thermal power and the energy storage unit.
Drawings
The invention is further described below with reference to the drawings and the detailed description. The scope of the present invention is not limited to the following description.
Figure-capacity configuration flow chart of particle swarm algorithm based on crowd searching
Combined planning flow chart of wind power and thermal power energy storage unit in figure II
Detailed Description
As shown in the figure, the power structure proportion of wind power and thermal power combined planning is required to ensure technical operability and also meet the maximization of benefits. The method is characterized in that the method comprises the steps of establishing a function expression taking the minimum cost as an optimization target from the aspect of economy for stably operating the power system, and solving the function expression by a particle swarm algorithm to calculate the optimal capacity ratio.
The invention comprises the following steps:
setting the optimized objective function as
Wherein R is electricity selling benefits (including wind generating sets and thermal power generating sets) and heat supply benefits; c is the running cost of the wind turbine generator, the thermal power generating unit and the energy storage heating unit; t=1, 2, …,24, corresponding to 24 times of day-ahead schedule;the method comprises the steps of surfing the Internet for wind power; />The method comprises the steps of (1) surfing electricity price for a thermal power generating unit; />The heat supply price is supplied to the energy storage heating unit; />And->The power generation power of the wind power plant and the thermal power generating unit respectively; />A heating load allocated to the energy storage heating unit; c (C) c 、C w 、C x The system is the maintenance cost of a thermal power unit, a wind power unit and an energy storage heating unit. F (F) t For energy-storage heating unitsAnd the running cost of the thermal power generating unit system.
The operation cost of the energy storage heating unit and the thermal power unit system can be expressed as follows:
wherein a is i 、b i 、c i The operation cost coefficient of the heat storage-thermoelectric unit is; c (C) V Is a unit operation parameter;the heat supply power is supplied to the thermal power generating unit; s is S t For the heat storage and release power of the heat storage device at time t (heat release time S t Negative).
Wherein the maintenance cost C of the thermal power unit, the wind power unit and the energy storage heating unit c 、C w 、C x The expression is as follows:
C c ＝C cd +C cv
C w ＝C wd +C wv
C x ＝C xd +C xv
wherein C is cd 、C wd 、C xd Respectively reducing the cost of the thermal power generation unit, the wind power generation unit and the energy storage unit; c (C) cv 、C wv 、C xv The variable costs of the thermal power generation, wind power generation and energy storage units are respectively.
The change cost of the thermal power and energy storage unit is as follows:
in the thermal power generating unit, the variable cost C cv Mainly comprises coal purchasing cost and energy storage unit variable cost C xv Mainly is a storageCoal purchasing cost of charging the heat boiler; variable cost C of wind turbine generator system wv Can be considered as 0; v i The method is characterized in that v is a state variable of the thermal power generating unit participating in wind power peak regulation x The energy storage unit participates in the wind power peak regulation state variable, when v x When the energy storage unit is in the range of (1), the energy storage unit is used as a wind power peak regulation power supply, and when v x When the energy storage unit is=0, the energy storage unit is not used as a wind power peak shaving power supply. Gamma is the price of fire coal; u (u) it The method is characterized in that the method is a state variable of the thermal power generating unit at moment, the starting state is 1, and the stopping state is 0; u (u) xt The method is characterized in that the method is a state variable of the energy storage unit at the time t, the starting state is 1, and the stopping state is 0; SU (SU) i The method comprises the following steps of (1) burning coal consumption for starting a thermal power unit; YU (Ye) x The fuel consumption for charging the energy storage unit; p (P) t c The output of the machine set at the time t is obtained.
In order to ensure that the wind-fire storage combined planning system can safely and stably supply heat and supply heat, the related technical parameters of the system are required to be restrained.
The power balance constraint of the invention:
wherein N is the set n=g of thermal power generating units in the region c +G b +G e ；Wind power which is connected with the grid at the moment t in the system is obtained;the system is electrically loaded at time t.
Heating constraint:
where k=1, 2, …, M is the total number of heating zones;the total heat load required to be born by the k-th partition thermal power plant at the moment t; />The heat accumulation amount at the time t of the k-th partition heat accumulation device; />Respectively the collection of the suction type and back pressure type units of the kth partition
Unit constraint
Upper and lower limit constraint of active output of a unit:
in the method, in the process of the invention,the minimum and maximum active output of the unit i under the condensed gas working condition are respectively; c m,i C for unit i m A value; c v,i C for unit i v A value; k (K) i Is constant.
Upper and lower limit constraint of unit heat output:
in the method, in the process of the invention,the maximum heat output limit for the unit i is determined by the heat exchanger capacity.
Unit climbing rate constraint:
wherein P is up,i 、P down,i And (5) respectively restraining the upward and downward climbing rates of the unit i. In generalThe output change of the thermal power generating unit is realized by changing the state of the boiler, so that the climbing rate constraint corresponding to the electric and thermal output of the unit is converted into the electric power constraint under the pure condensation condition before steam extraction.
When c v ＝0、c m When=0, the unit is a pure condensing unit, and the constraint is unchanged.
When c v ＝0、c m Not equal to 0, the back pressure thermoelectric unit is defined as follows:
thermal storage device operation constraints
Heat storage device heat storage/release capacity constraint:
wherein P is h,k,cmax 、P h,k,fmax The maximum heat accumulation and release power of the heat accumulation device are respectively.
Capacity constraint of the thermal storage device:
wherein S is h,k,max Is the heat storage capacity of the heat storage device.
And before the capacity of each energy storage unit is optimized through an algorithm, the electricity selling income and the electricity generation cost are verified. And after verifying that the conditions are met, combining constraint conditions and an objective function, and adopting a particle swarm optimization algorithm based on crowd searching to obtain the capacity configuration with the minimum wind power, thermal power and energy storage joint planning cost.
The model is an optimization and improvement of a unit combination model, and an optimal solution of a wind power, thermal power and energy storage combined power transmission and loading machine structure is sought by introducing an objective function with the generation cost C as a minimum value. The group combination problem can be solved by means of a particle swarm algorithm based on crowd searching, and the group combination problem is falseThe optimization result of the state variable of the wind power peak regulation by taking part in the thermal power is set asThe optimal result of real-time output of the thermal power generating unit is +.>The start-stop state variable is optimized to be +.>The real-time output of the wind power plant is +.>Then, the predetermined installed capacity P can be obtained w The optimal cooperation thermal power generating unit and the energy storage heating unit of the wind farm have the following capacities:
according to the peak regulation relation among the wind turbine generator, the thermal power unit and the heat storage and heating unit, power planning among the wind turbine generator, the thermal power unit and the heat storage and heating unit is performed.
The power and thermal demand constraints of the present invention include power balance constraints and heating constraints.
The conventional unit utilization constraint comprises upper and lower limit constraint of active output of the unit, upper and lower limit constraint of hot output of the unit and climbing rate constraint of the unit.
The energy storage device system constraints of the present invention include thermal storage device operational constraints and thermal storage device capacity constraints.
It should be understood that the foregoing detailed description of the present invention is provided for illustration only and is not limited to the technical solutions described in the embodiments of the present invention, and those skilled in the art should understand that the present invention may be modified or substituted for the same technical effects; as long as the use requirement is met, the invention is within the protection scope of the invention.
Claims (1)
1. The capacity configuration method for the combined participation of thermoelectric and wind power in the peak shaving of the power grid is characterized by comprising the following steps of:
setting the optimized objective function as
Wherein R is electricity selling benefit and heat supply benefit; c is the running cost of the wind turbine generator, the thermal power generating unit and the energy storage heating unit; t=1, 2, …,24, corresponding to 24 times of day-ahead schedule;the method comprises the steps of surfing the Internet for wind power; />The method comprises the steps of (1) surfing electricity price for a thermal power generating unit; />The heat supply price is supplied to the energy storage heating unit; />And->The power generation power of the wind power plant and the thermal power generating unit respectively; />A heating load allocated to the energy storage heating unit; c (C) c 、C w 、C x The maintenance cost of the thermal power unit, the wind power unit and the energy storage heating unit is reduced; f (F) t The method is the operation cost of an energy storage heating unit and a thermal power unit system;
the operation cost of the energy storage heating unit and the thermal power unit system is expressed as:
wherein a is i 、b i 、c i The operation cost coefficient of the heat storage-thermoelectric unit is; c (C) V Is a unit operation parameter;the heat supply power is supplied to the thermal power generating unit; s is S t Is the heat storage and release power of the heat storage device at the moment t, wherein S is the heat release time t Is negative;
wherein the maintenance cost C of the thermal power unit, the wind power unit and the energy storage heating unit c 、C w 、C x The expression is as follows:
C c ＝C cd +C cv
C w ＝C wd +C wv
C x ＝C xd +C xv
wherein C is cd 、C wd 、C xd Respectively reducing the cost of the thermal power generation unit, the wind power generation unit and the energy storage unit; c (C) cv 、C wv 、C xv The variable cost of the thermal power generation unit, the wind power generation unit and the energy storage unit are respectively;
the change cost of the thermal power and energy storage unit is as follows:
in the thermal power generating unit, the variable cost C cv For the purchase cost of fire coal, the energy storage unit changes the cost C xv Coal purchasing cost for charging the heat accumulating boiler; variable cost C of wind turbine generator system wv Is 0; v i Is fire ofState variable v of motor group participating in wind power peak regulation x The energy storage unit participates in the wind power peak regulation state variable, when v x When the energy storage unit is in the range of (1), the energy storage unit is a wind power peak regulation power supply, and when v x When the energy storage unit is not in a wind power peak shaving power supply; gamma is the price of fire coal; u (u) it The method is characterized in that the method is a state variable of the thermal power generating unit at moment, the starting state is 1, and the stopping state is 0; u (u) xt The method is characterized in that the method is a state variable of the energy storage unit at the time t, the starting state is 1, and the stopping state is 0; SU (SU) i The method comprises the following steps of (1) burning coal consumption for starting a thermal power unit; YU (Ye) x The fuel consumption for charging the energy storage unit; p (P) t c The output of the unit at the time t is given;
power balance constraint:
wherein N is the set n=g of regional thermal power units c +G b +G e ；Wind power which is connected with the grid at the moment t in the system is obtained; />The system is electrically loaded at the moment t;
heating constraint:
where k=1, 2, …, M is the total number of heating zones;the total heat load required to be born by the k-th partition thermal power plant at the moment t; />The heat accumulation amount at the time t of the k-th partition heat accumulation device; />Respectively the collection of the suction type and back pressure type units of the kth partition
Unit constraint
Upper and lower limit constraint of active output of a unit:
in the method, in the process of the invention,the minimum and maximum active output of the unit i under the condensed gas working condition are respectively; c m,i C for unit i m A value; c v,i C for unit i v A value; k (K) i Is a constant;
upper and lower limit constraint of unit heat output:
in the method, in the process of the invention,the maximum limit of the heat output of the unit i is set;
unit climbing rate constraint:
wherein P is up,i 、P down,i Respectively restraining upward and downward climbing rates of the unit i; converting climbing rate constraint corresponding to electric and thermal output of the unit into electric power constraint under a pure condensation working condition before steam extraction;
when c v ＝0、c m When the temperature is=0, the unit is a pure condensation unit, and the constraint is unchanged;
when c v ＝0、c m Not equal to 0, the back pressure thermoelectric unit is defined as follows:
thermal storage device operation constraints
Heat storage device heat storage/release capacity constraint:
wherein P is h,k,cmax 、P h,k,fmax The maximum heat accumulation and release power of the heat accumulation device are respectively;
capacity constraint of the thermal storage device:
wherein S is h,k,max Is the heat storage capacity of the heat storage device;
according to the optimization result of the real-time output of the thermal power unit, the optimization result of the start-stop state variable and the real-time output of the wind power plant, respectively obtaining the preset installed capacity as P w The optimal cooperation thermal power generating unit and the energy storage heating unit of the wind farm have the capacity:
in the method, in the process of the invention,for optimal cooperation thermal power generating unit of wind farm +.>Capacity for energy-storage heating units, in particular->Optimizing result for wind power peak regulation state variable of thermal power participation +.>The method is an optimization result of real-time output of the thermal power generating unit;
wherein, the start-stop state variable optimization result is thatThe real-time output of the wind power plant is +.>
Carrying out power planning among the wind power generation unit, the thermal power generation unit and the heat storage heating unit according to peak regulation relations among the wind power generation unit, the thermal power generation unit and the heat storage heating unit;
the power and thermal demand constraints include power balance constraints and heating constraints;
the conventional unit utilization constraint comprises an upper limit constraint and a lower limit constraint of active output of the unit, an upper limit constraint and a lower limit constraint of hot output of the unit and a climbing rate constraint of the unit;
the energy storage device system constraints include a thermal storage device operating constraint and a thermal storage device capacity constraint.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910598878.2A CN110378523B (en) | 2019-07-04 | 2019-07-04 | Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910598878.2A CN110378523B (en) | 2019-07-04 | 2019-07-04 | Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110378523A CN110378523A (en) | 2019-10-25 |
| CN110378523B true CN110378523B (en) | 2024-01-26 |
Family
ID=68251971
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910598878.2A Active CN110378523B (en) | 2019-07-04 | 2019-07-04 | Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110378523B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110867857B (en) * | 2019-11-29 | 2021-10-15 | 沈阳工业大学 | Optimization method of peak shaver set combination based on wind-storage combined system |
| CN111799778A (en) * | 2020-06-11 | 2020-10-20 | 国网山东省电力公司经济技术研究院 | Wind power-containing power system energy storage capacity optimization method considering peak shaving requirements |
| CN112613669B (en) * | 2020-12-23 | 2024-10-15 | 国网辽宁省电力有限公司经济技术研究院 | Method for predicting daily output of thermoelectric enterprise in concurrent environment of electric energy and peak shaving market |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106972532A (en) * | 2017-04-26 | 2017-07-21 | 华中科技大学 | A kind of wind-powered electricity generation Power tariff evaluation method compensated based on peak regulation assistant service |
| CN107508328A (en) * | 2017-04-08 | 2017-12-22 | 东北电力大学 | Consider the association system energy optimizing method of wind electricity digestion |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103236719A (en) * | 2013-04-17 | 2013-08-07 | 国家电网公司 | Wind power bundling control method after wind power and thermal power accessing to power grid |
-
2019
- 2019-07-04 CN CN201910598878.2A patent/CN110378523B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107508328A (en) * | 2017-04-08 | 2017-12-22 | 东北电力大学 | Consider the association system energy optimizing method of wind electricity digestion |
| CN106972532A (en) * | 2017-04-26 | 2017-07-21 | 华中科技大学 | A kind of wind-powered electricity generation Power tariff evaluation method compensated based on peak regulation assistant service |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110378523A (en) | 2019-10-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110826815B (en) | Regional comprehensive energy system operation optimization method considering comprehensive demand response | |
| CN113112087A (en) | Comprehensive energy system operation cost optimization method considering electric heating load demand response | |
| CN110378523B (en) | Capacity allocation method for thermoelectric and wind power combined participation power grid peak shaving | |
| CN112464477A (en) | Multi-energy coupling comprehensive energy operation simulation method considering demand response | |
| CN113193602B (en) | Power distribution network optimized operation system and method containing low-heating-value power generation and distributed power supply | |
| CN111027846B (en) | Electricity-hydrogen comprehensive energy system considering heat-hydrogen co-production and capacity configuration method thereof | |
| CN108808663B (en) | Industrial user heat demand response method based on multi-energy complementation | |
| CN110361969B (en) | Optimized operation method of cooling, heating and power comprehensive energy system | |
| CN109543889A (en) | A kind of regional complex energy resource system cooperates with optimizing operation method a few days ago | |
| CN106527142B (en) | A kind of cooling heating and power generation system coordinated scheduling method under active power distribution network environment | |
| CN111799772B (en) | Electric heating system optimal scheduling method considering depth peak shaving of unit | |
| CN113256045A (en) | Park comprehensive energy system day-ahead economic dispatching method considering wind and light uncertainty | |
| CN105958537A (en) | Energy conversion system facing energy Internet and optimal control method thereof | |
| CN107103431A (en) | A kind of lower power network of heat supply phase peak regulation constraint abandons landscape condition analysis method | |
| CN106712033A (en) | Wind curtailment absorption method in thermal power plant | |
| CN113313305A (en) | Non-cooperative game-based comprehensive energy system optimization scheduling method | |
| CN113240166A (en) | Day-ahead economic dispatching method of micro-energy network considering high-proportion new energy consumption | |
| CN112953364A (en) | Photothermal-wind power-photovoltaic combined system operation optimization model considering photothermal power station service life | |
| CN117350419A (en) | Park comprehensive energy system optimization operation method considering flexible load and carbon flow | |
| CN111030101B (en) | Clean energy consumption linkage regulation and control method and system based on diversified big data | |
| CN114362152B (en) | Multi-time scale scheduling method for comprehensive energy system | |
| Chen et al. | Optimal planning and operation of CCHP system considering renewable energy integration and seawater desalination | |
| CN110994698A (en) | Optimized operation method of solar photovoltaic-photothermal combined power generation system | |
| CN114021361A (en) | Multi-time scale optimal scheduling method and system for load of heat storage and power generation boiler | |
| CN114282828A (en) | Carbon circulation system and application thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |