CN107069783B - Heat storage electric boiler merges energy-storage system optimal control method - Google Patents

Heat storage electric boiler merges energy-storage system optimal control method Download PDF

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Publication number
CN107069783B
CN107069783B CN201710031302.9A CN201710031302A CN107069783B CN 107069783 B CN107069783 B CN 107069783B CN 201710031302 A CN201710031302 A CN 201710031302A CN 107069783 B CN107069783 B CN 107069783B
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abandonment
electric boiler
particle
heat storage
energy
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CN107069783A (en
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李国庆
王鹤
庄冠群
田春光
李建林
吕项羽
周宏伟
李德鑫
常学飞
王佳穎
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Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
Northeast Electric Power University
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Northeast Dianli University
Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects

Abstract

A kind of heat storage electric boiler fusion energy-storage system optimal control method, belongs to power system and automation technology.The purpose of the present invention is by when one heat storage electric boiler of design merge the model of energy-storage system and realize that the heat storage electric boiler for the optimum control for merging energy-storage system to heat storage electric boiler merges energy-storage system optimal control method.Step of the invention is: establishing the mathematical model of heat storage electric boiler fusion energy-storage system optimal control, obtains the wind power prediction information of wind power plant, and then obtains abandonment power prediction information, the abandonment power that the mathematical model obtained using step 1 and step 2 are obtained;Consider the constraint condition that step 1 is mentioned, hybrid system is optimized using particle swarm algorithm.The present invention can be integrated in the system of heat storage electric boiler fusion energy storage hybrid system control centre, realize the optimal control to whole system, take into account consumption abandonment maximization and electrode boiler adjusts number adjusting and minimizes, realize the operation of hybrid system economic stability.

Description

Heat storage electric boiler merges energy-storage system optimal control method
Technical field
The invention belongs to power system and automation technologies.
Background technique
China's Wind Power Generation Industry is quickly grown, and installed capacity of wind-driven power occupies first place in the world, but wind-powered electricity generation abandonment outstanding problem at present, especially It is that power grid " three Norths " area, Flexible Power Grid based on thermoelectricity are poor.During heating in winter, northern area thermoelectricity unit " electricity determining by heat " operation, it is large-scale " abandonment " that the downward peak modulation capacity deficiency of unit further results in the night dip period.How Consumption wind-powered electricity generation has become one of the critical issue for restricting the development of China's wind-power electricity generation.For the wind electricity digestion for solving the problems, such as China, Country has put into effect a series of measures, clearly proposes to attempt to promote abandonment electric heating, promotes conversion of the electric load to thermic load. In addition, consumption abandonment electric power is assisted also to receive extensive attention using energy storage technology.
Existing literature to heat storage electric boiler improve wind power plant wind-powered electricity generation on-site elimination economy and scheduling controlling technology into More in-depth study is gone, it was demonstrated that utilize the application prospect of heat storage electric boiler technology consumption abandonment.Also there is document proposition Hybrid system is constituted using energy storage fusion heat storage electric boiler, is that target carries out simulation analysis using the Income Maximum of system, demonstrate,proves The economic feasibility of hybrid system is illustrated.But heat storage electric boiler tracking abandonment changed power is not accounted in existing literature Regulating power problem.The electrode of currently used heat storage electric boiler may be implemented power and continuously adjust, but it adjusts speed Degree and adjusting number are restricted by electrode mechanical part.Quickly, frequently power regulation will seriously damage heat storage electric boiler Service life.Energy storage mixed heat accumulation formula grill pan furnace system how is controlled, while maximizing its consumption wind-powered electricity generation, reduces its Machinery Ministry The mobile number of part extends service life of equipment in turn, becomes research hotspot at present.
Summary of the invention
The purpose of the present invention is merge the model of energy-storage system by one heat storage electric boiler of design to realize to accumulation of heat The heat storage electric boiler that formula electric boiler merges the optimum control of energy-storage system merges energy-storage system optimal control method.
Step of the invention is:
Step 1, the mathematical model for establishing heat storage electric boiler fusion energy-storage system optimal control:
Step 101: establish hybrid system consumption abandonment electricity index:
(1)
W s t FortThe abandonment electricity that period wind power plant is dissolved using heat storage electric boiler and electrochemical energy storage;
Step 102: it establishes heat storage electric boiler and adjusts number index:
(2)
TaptFor heat storage electric boiler the t period power gear;
Step 103: according to the difference of dimension between each objective function, subordinating degree function is constructed respectively to each target, It is translated into the satisfaction to optimum results, corresponding function are as follows:
(3)
(4)
To be up to value when target with abandonment consumption;To adjust the minimum target of number with boiler gear When value;To dissolve the acceptable flexible value of abandonment;The acceptable flexible value of number is adjusted for boiler gear; Abandonment total electricity is dissolved for hybrid system;Number is always adjusted for heat storage electric boiler;
Step 104: establish the evaluation function of heat storage electric boiler fusion each index of energy-storage system:
(5)
k1、k2For the weight coefficient of each section, and meetTo dissolve abandonment subordinating degree function;To adjust number subordinating degree function;
Step 105: above-mentioned various indexs being carried out using the constraint condition of heat storage electric boiler fusion energy-storage system optimization Limit constraint;
Step 2: obtaining the wind power prediction information of wind power plant, and then obtain abandonment power prediction information;
Step 3: the abandonment power that the mathematical model and step 2 obtained using step 1 is obtained;Consider what step 1 was mentioned Constraint condition optimizes hybrid system using particle swarm algorithm:
Step 301 initializes population, and the population is made of multiple particles, and the value of each particle is limiting model It is randomly generated in enclosing;
The objective function of step 1 mathematical model is imported algorithm by step 302, as the objective function of algorithm, steps for importing Abandonment power prediction information obtained in 2, as abandonment constraint qualification condition;
Step 303 starts iteration, calculates the comprehensive fitness degree of each particle in population, does not meet the grain of constraint condition Son is punished according to penalty function, takes the maximum particle of comprehensive fitness degree compared with current optimal particle, enable comprehensive fitness degree compared with Big particle is standard optimal particle;
After step 304 is iterated update to particle each in population according to following formula, return step 303;
(15)
(16)
K is the number of iterations;W is the inertia weight factor;For the random number between 0 ~ 1;For Studying factors (accelerated factor);It isThe speed of a particle at the kth iteration;It isA particle position at the kth iteration It sets;The optimal solution found for particle itself;The optimal solution found in group for particle;
When step 304 the number of iterations reaches maximum value, iteration terminates, when obtaining two objective satisfaction degree maximum of hybrid system Optimal control mode.
The present invention adjusts the minimum objective function of number with wind electricity digestion maximum and electrode boiler, considers abandonment constraint, function Rate Constraints of Equilibrium, equipment state constraint, the constraint of heat supply contract and boiler power constraint, realize and merge to heat storage electric boiler The optimum control of energy-storage system.It can be integrated in the system of heat storage electric boiler fusion energy storage hybrid system control centre, realize Optimal control to whole system, takes into account consumption abandonment maximization and electrode boiler adjusts number and adjusts minimum, realizes mixing Systematic economy stable operation.
Detailed description of the invention
Fig. 1 is process flow chart of the invention;
Fig. 2 is the abandonment power curve that this example uses;
Fig. 3 is the corresponding subordinating degree function of two targets;
Fig. 4 is heat storage electric boiler operation power gear after optimization;
Fig. 5 is heat-accumulator tank day part quantity of heat storage;
Fig. 6 is energy-storage battery day part operation power;
Fig. 7 is energy-storage battery day part reserve of electricity;
Fig. 8 is the control method consumption abandonment signal that this method proposes.
Specific embodiment
Step of the invention is:
Step 1, the mathematical model for establishing heat storage electric boiler fusion energy-storage system optimal control:
Step 101: establish hybrid system consumption abandonment electricity index:
(1)
W s t FortThe abandonment electricity that period wind power plant is dissolved using heat storage electric boiler and electrochemical energy storage.
Step 102: it establishes heat storage electric boiler and adjusts number index:
(2)
TaptFor heat storage electric boiler the t period power gear.Following Examples is by 30MW electrode boiler according to every 5MW mono- A power gear is divided into 7 gears from 0 to 30MW.
Step 103: according to the difference of dimension between each objective function, subordinating degree function is constructed respectively to each target, It is translated into the satisfaction to optimum results, it is intended under the premise of meeting institute's Prescribed Properties, so that comprehensive satisfaction reaches To maximum.Corresponding function are as follows:
(3)
(4)
To be up to value when target with abandonment consumption;To adjust the minimum target of number with boiler gear When value;To dissolve the acceptable flexible value of abandonment;The acceptable flexible value of number is adjusted for boiler gear; Abandonment total electricity is dissolved for hybrid system;Number is always adjusted for heat storage electric boiler.As shown in Figure 3.
Step 104: establish the evaluation function of heat storage electric boiler fusion each index of energy-storage system:
(5)
k1、k2For the weight coefficient of each section, and meetTo dissolve abandonment subordinating degree function;To adjust number subordinating degree function.
Step 105: above-mentioned various indexs being carried out using the constraint condition of heat storage electric boiler fusion energy-storage system optimization Limit constraint.Specifically include abandonment constraint, power-balance constraint, equipment state constraint, boiler power constraint and heat supply contract about Beam.
The constraint condition of the heat storage electric boiler fusion energy-storage system optimization are as follows:
The constraint condition for establishing heat storage electric boiler fusion energy-storage system optimization, specifically includes abandonment constraint, power-balance Constraint, equipment state constraint, boiler power constraint and the constraint of heat supply contract.
Wherein, abandonment constraint condition are as follows:
(6)
WhereinW qf t For t period abandonment electricity,W s t Dissolving abandonment electricity for system can be further represented as
(7)
W g t FortIt is used to heat electric boiler directly to the electricity of pipe network heat supply in period;W qi t FortPeriod is used to heat grill pan Furnace is the electricity of heat-accumulator tank heat accumulation;W ci t FortThe electricity of period electrochemical energy storage charging.
Power-balance constraint are as follows:
(8)
(9)
Q c t FortThe quantity of heat storage of period heat-accumulator tank;Q qi t FortThe heat that period boiler is stored in heat-accumulator tank;Q qo t FortPeriod stores The heat of hot tank release;W c t FortThe electricity of period electrochemical energy storage;W ci t FortPeriod electrochemical energy storage charge capacity;Wco tFort Period electrochemical energy storage discharge electricity amount.
Energy storage and heat accumulation equipment state constraint are as follows:
(10)
(11)
Q max For heat-accumulator tank maximum quantity of heat storage,Q min For heat-accumulator tank minimum quantity of heat storage;SOCmin、SOCmaxRespectively indicate charged shape The maxima and minima of state generally takes " 0.2 ", " 0.8 ".In following exampleQ max For 300GJ,Q min It is 0.
The constraint of heat supply contract are as follows:
(12)
tThe heat that moment provides to heat supply companyQ x t It can be further represented as
(13)
Q x.min For the minimum heating load of heat supply contract;For electric heating conversion coefficient coefficient, unit GJ/MWh; W co t Fort The electricity of period electrochemical energy storage electric discharge.In following exampleTake 3.597.
Electric boiler power constraint are as follows:
(14)
P h t FortPeriod electric boiler runs power, should be less than the maximum power of electric boilerP hmax .In following exampleP h t It takes 30MW。
Step 2: obtaining the wind power prediction information of wind power plant, and then obtain abandonment power prediction information;Wind power plant cluster Control system obtains 15 minutes grade active power output information of each wind power plant in wind power plant cluster by wind power prediction system, considers negative Lotus demand and schedule obtain 96 points of whole day of abandonment predictive information.
This example randomly selects one day abandonment electricity in wind factory heat supply mid-term and abandonment prediction electricity is replaced to carry out simulation analysis, As shown in Figure 2.
Step 3: the abandonment power that the mathematical model and step 2 obtained using step 1 is obtained;Consider what step 1 was mentioned Constraint condition optimizes hybrid system using particle swarm algorithm.
To system with wind electricity digestion maximum, boiler adjusts the minimum target of number and carries out single object optimization, obtains in monocular Hybrid system running boundary condition in the case of mark determines, value, and then determine heat accumulating type grill pan Evaluation function this example of furnace fusion each index of energy-storage system takes " 506.25,2,303.155,43 " respectively.
Step 301 initializes population, and the population is made of multiple particles, and the value of each particle is limiting model It is randomly generated in enclosing.
The objective function of step 1 mathematical model is imported algorithm by step 302, as the objective function of algorithm, in step 1 Algorithm is written in the constraint condition of consideration in the form of penalty function, when particle does not meet constraint condition in iterative process, by penalizing letter Number is punished;Abandonment power prediction information obtained in steps for importing 2, as abandonment constraint qualification condition.
Step 303 starts iteration, calculates the comprehensive fitness degree of each particle in population, does not meet the grain of constraint condition Son is punished according to penalty function, takes the maximum particle of comprehensive fitness degree compared with current optimal particle, enable comprehensive fitness degree compared with Big particle is standard optimal particle.
After step 304 is iterated update to particle each in population according to following formula, return step 303;
(15)
(16)
K is the number of iterations;W is the inertia weight factor;For the random number between 0 ~ 1;For Studying factors (accelerated factor), following Examples takes 2;It isThe speed of a particle at the kth iteration;It isA particle is in kth Position when secondary iteration;The optimal solution found for particle itself;The optimal solution found in group for particle.
When step 304 the number of iterations reaches maximum value, iteration terminates, when obtaining two objective satisfaction degree maximum of hybrid system Optimal control mode.Each equipment period power and state are as shown in figs. 4-7.Fig. 8 is that hybrid system dissolves wind-powered electricity generation signal Scheme, dash area is that system dissolves abandonment electricity in figure.
Fig. 4-Fig. 5 is respectively the power gear of electric boiler and the heat of heat-accumulator tank.Electric boiler according to setting 7 gears with The operation of track wind-powered electricity generation, whole day are adjusted electrode 26 times altogether, with boiler real-time tracking wind-powered electricity generation, are adjusted electrode position mode in real time and are compared, greatly Big reduce adjusts number, effectively extends the service life of equipment.A part of direct heating of heat that boiler generates, another part It is stored in heat-accumulator tank.This example, which sets unit time thermic load, cannot be below 60GJ to convert being electrical power being 16.68MWh.Work as boiler Underpower is to meet " the 31-41,43-56 " period in minimum thermic load such as Fig. 8, and heat-accumulator tank discharges heat, at this time heat-accumulator tank Interior quantity of heat storage decline;When boiler power can satisfy thermic load such as " the 1-10,56-65 " period, heat-accumulator tank heat accumulation, heat accumulation in tank Amount increases.
Fig. 6-Fig. 7 is respectively energy-storage battery operation power and energy-storage battery reserve of electricity.When boiler operatiopn power is higher than abandonment Power such as " 1,14,20 " period energy-storage battery power is less than 0, the deficiency of battery discharge supplement electricity under the premise of meeting SOC, Reserve of electricity decline;Such as " 4,6, the 10,21 " period when abandonment power is greater than boiler operatiopn power, energy storage power are greater than 0, meet Battery charges under the premise of SOC, and reserve of electricity rises.
Fig. 8 gives the coordinating and optimizing control method tracking abandonment using heat storage electric boiler proposed in this paper fusion energy storage The case where dissolving wind-powered electricity generation.After accessing hybrid system, dash area is that hybrid system dissolves the total 465.78MWh of abandonment, wind electricity digestion Ability and heat storage electric boiler traditional control method (22:00-05:00 is run, remaining time shuts down by heat-accumulator tank heat release heat supply) Compared to being obviously improved.

Claims (1)

1. a kind of heat storage electric boiler merges energy-storage system optimal control method, it is characterised in that:
Step 1, the mathematical model for establishing heat storage electric boiler fusion energy-storage system optimal control:
Step 101: establish hybrid system consumption abandonment electricity index:
Ws tThe abandonment electricity dissolved for t period wind power plant using heat storage electric boiler and electrochemical energy storage;
Step 102: it establishes heat storage electric boiler and adjusts number index:
TaptFor heat storage electric boiler the t period power gear;
Step 103: according to the difference of dimension between each objective function, subordinating degree function being constructed respectively to each target, by it It is converted into the satisfaction to optimum results, corresponding function are as follows:
KmaxTo be up to value when target with abandonment consumption;PminTo adjust value when the minimum target of number with boiler gear;δ1 To dissolve the acceptable flexible value of abandonment;δ2The acceptable flexible value of number is adjusted for boiler gear;F (k) disappears for hybrid system Receive abandonment total electricity;F (p) is that heat storage electric boiler always adjusts number;
Step 104: establish the evaluation function of heat storage electric boiler fusion each index of energy-storage system:
μmax=k1μ(k)+k2μ(p) (5)
k1、k2For the weight coefficient of each section, and meet k1+k2=1;μ (k) is consumption abandonment subordinating degree function;μ (p) is to adjust Number subordinating degree function;
Step 105: constraint is defined using the constraint condition of heat storage electric boiler fusion energy-storage system optimization;
Step 2: obtaining the wind power prediction information of wind power plant, and then obtain abandonment power prediction information;
Step 3: the abandonment power that the mathematical model and step 2 obtained using step 1 is obtained;Consider the constraint that step 1 is mentioned Condition optimizes hybrid system using particle swarm algorithm:
Step 301 initializes population, and the population is made of multiple particles, and the value of each particle is limiting in range It is randomly generated;
The objective function of step 1 mathematical model is imported algorithm by step 302, as the objective function of algorithm, in steps for importing 2 Obtained abandonment power prediction information, as abandonment constraint qualification condition;
Step 303 starts iteration, calculates the comprehensive fitness degree of each particle in population, do not meet the particle of constraint condition according to It is punished according to penalty function, takes the maximum particle of comprehensive fitness degree compared with current optimal particle, enable comprehensive fitness degree biggish Particle is standard optimal particle;
After step 304 is iterated update to particle each in population according to following formula, return step 303;
K is the number of iterations;W is the inertia weight factor;r1、r2For the random number between 0~1;c1、c2For Studying factors;It is The speed of i particle at the kth iteration;For i-th of particle position at the kth iteration;pbestIt is found for particle itself Optimal solution;gbestThe optimal solution found in group for particle;
When step 304 the number of iterations reaches maximum value, iteration terminates, when obtaining two objective satisfaction degree maximum of hybrid system most Excellent control mode.
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