CN109245093A - A kind of supply of cooling, heating and electrical powers distributed busbar protection collaboration Optimization Scheduling - Google Patents
A kind of supply of cooling, heating and electrical powers distributed busbar protection collaboration Optimization Scheduling Download PDFInfo
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 16
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- H—ELECTRICITY
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- 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
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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
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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
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- H—ELECTRICITY
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- 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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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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Abstract
The present invention relates to a kind of supply of cooling, heating and electrical powers distributed busbar protections to cooperate with Optimization Scheduling, comprising the following steps: step 1: being established according to supply of cooling, heating and electrical powers distributed busbar protection each section equipment operation characteristic and considers economic benefit planning operation model；Step 2: comprehensively considering Environmental costs and economic operation cost, will discharge pollutants is indicated with environmental carrying capacity with ECONOMICAL APPROACH TO, constructs global optimization scheduling model for the moving model combination constraint condition of supply of cooling, heating and electrical powers distributed busbar protection each section equipment；Step 3: solve to global optimization scheduling model and then obtain supply of cooling, heating and electrical powers distributed busbar protection each section equipment optimal scheduling strategy based on the adaptive particle swarm optimization algorithm of bee colony Optimizing operator using what is improved and optimizated.Compared with prior art, the advantages that present invention has accurate offer operation plan, is easy to engineers and technicians' use, and the algorithm speed of service is fast, and precision is high, and global optimization ability is strong.
Description
Technical field
The present invention relates to a kind of Optimization Schedulings, cooperate with more particularly, to a kind of supply of cooling, heating and electrical powers distributed busbar protection excellent
Change dispatching method.
Background technique
Lack of energy and environmental protection become the theme of current social, and China supports energetically and encourages exploitation, utilizes cleaning
The energy.For realize renewable energy large-scale application, and solve the problems, such as resource spatially be unevenly distributed weighing apparatus, many scholars
Propose the technologies such as micro-capacitance sensor, smart grid.But with distributed energy diversification, the magnanimity of distributed apparatus, the energy point
The wide area of cloth, micro-capacitance sensor technology and intelligent power grid technology are no longer satisfied practical application.In consideration of it, a kind of flexibly integrated more
Kind energy-provision way, the distributed busbar protection with relative independentability have become a hot topic of research.
Distributed busbar protection system structure is complicated, and energy-provision way is various, and main energy-provision way includes wind energy, water energy, the sun
Energy, natural gas, hydrogen etc.；In distributed busbar protection, energy flow is not only electric energy, further includes thermal energy, chemical energy etc..Have
It is current multifunctional system research hotspot and difficult point about multiple-energy-source microgrid modeling control, planning operation.The more collection of main research at present
In in distributed CCHP system, refrigeration and heating equipment are relatively simple, and the collaboration optimizing research based on cool and thermal power is
There is certain achievement, but not deep enough for distributed busbar protection systematic research.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of supplies of cooling, heating and electrical powers point
Cloth energy source station cooperates with Optimization Scheduling.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of supply of cooling, heating and electrical powers distributed busbar protection collaboration Optimization Scheduling, comprising the following steps:
Step 1: establishing the moving model that each equipment of supply of cooling, heating and electrical powers distributed busbar protection considers economic planning factor；
Step 2: establishing the global optimization scheduling model combined including constraint condition；
Step 3: improving bee colony and optimize PSO Algorithm Optimized model, obtain the optimal power output of each equipment；
Step 4: verification algorithm feasibility and high efficiency after the optimal power output operation reserve of actual motion equipment.
Preferably, the moving model in the step 1 includes: gas internal-combustion engine generating set model, wind-driven generator
Group model, photovoltaic power generation unit model, electric energy storage device model, cold/hot water machine of lithium bromide group model, centrifugal cold
Model and air source heat pump model.
Preferably, the global optimization scheduling model in the step 2 includes:
Distributed busbar protection overall operation cost minimization, formula are as follows:
min Csum=Cpurel+Cpurgas+Cenv；
In formula, t, T, i, N are natural number, CsumFor distributed busbar protection overall operation cost, CpurelFor power purchase expense,
CpurgasTo purchase natural gas expense, CenvFor Environmental costs, Cgrid,tFor electricity price, PSELL_tFor electricity, CgasFor natural gas unit heat
Costly lattice,Amount of natural gas, V are consumed for gas internal-combustion engineMT_(t)iAmount of natural gas is consumed for gas turbine,And ENOx,k(PiIt (t)) be respectively cooling heating and power generation system in t moment specific power is P
When i-th of generating equipment CO2,SO2,NOxDischarge amount,WithRespectively CO2,SO2,NOxUnit environment at
This, unit is, for heat equivalent coefficient of performance ρ=Qh/SEERC, wherein SEERCFor equivalent electric quantity consumption, QhWork as heat supply
Amount.
Preferably, the constraint condition in the step 2 includes:
Energy balance constraint, formula are as follows:
In formula,T period all gas internal-combustion engine power supply volumes are represented,Represent t period all light
Lie prostrate generated energy, Pdis_tT period energy-storage battery discharge capacity is represented,T period all wind-driven generator power supply volumes are represented,
PSELL_tThe t period is represented from power grid purchase of electricity,Represent t period all centrifugal cold power consumption, PNEED_tRepresent t
Period user power utilization demand, Pch_tRepresent t period energy-storage battery charge volume, PLOSS_tRepresent t period system power consumption, QNEED_t
Represent the thermic load of t period, QHP,R_tThe heat pump heat supply amount of t period is represented,Represent t period lithium bromide absorption type cooling and heating
Water dispenser group heating load, Qloss_tRepresent t period heat dissipation capacity, C when operating normallyNEED_tRepresent t period refrigeration duty, QEC,J_tRepresent t
Period centrifugal cold refrigerating capacity,Represent t period cold/hot water machine of lithium bromide group refrigerating capacity, Closs_tRepresent t
Period operates normally dissipation amount.
The generated output of gas internal-combustion engine constrains, and formula is as follows:
In formula,T moment gas internal-combustion engine generated output is represented,Represent t-1 moment combustion gas internal combustion
Machine generated output,Maximum power generation is represented,Represent minimum generated output, UGEIt represents in combustion gas
The upward creep speed of combustion engine, DGEThe downward creep speed of gas internal-combustion engine is represented, Δ t is transformation period,
Lithium cold Hot water units semen donors and the constraint of heating load bound, formula are as follows:
In formula,Minimum and maximum is for calorific value when respectively representing lithium cold Hot water units heat supply,Minimum and maximum cooling supply value when respectively representing lithium cold Hot water units refrigeration, Point
Lithium cold Hot water units t moment heating capacity and refrigerating capacity are not represented,
Centrifugal cold t period refrigerating capacity bound constraint, formula are as follows:
QEC,min≤QEC,J_t≤QEC,max；
In formula, QEC,J_tFor centrifugal cold t period refrigerating capacity, QEC,minFor centrifugal cold refrigerating capacity minimum value, QEC,max
For centrifugal cold refrigerating capacity maximum value,
The constraint of air source heat pump t period heating load bound, formula are as follows:
QHP,min≤QHP,R_t≤QHP,max；
In formula, QHP,R_tFor air source heat pump t period heating load, QHP,R_minIt is minimum for air source heat pump t period heating load
Value, QHP,R_maxFor air source heat pump t period heating load maximum value,
The bound constraint of the discharge power and charge power of electric energy storage device, formula are as follows:
In formula, γES,chFor electric energy storage device maximum charge multiplying power；γES,disFor electric energy storage device maximum discharge-rate；
PES,ch_tFor electric energy storage device period t charge power；PES,ch_tFor electric energy storage device period t discharge power；SESFor
Electric energy storage device rated capacity.
Preferably, the improvement bee colony optimization particle swarm algorithm in the step 3 includes introducing self-adaptive weight sum search
Operator improves and optimizates.
Preferably, the formula of the adaptive weighting are as follows:
In formula, f indicates current particle target function value, fmean, fminRespectively indicate current particle average target functional value and
Smallest particles target function value, ωminFor weight minimum value, ωmaxFor weight maximum value, ω is weight,
The formula of the searching operators are as follows:
zid=xid+φid(xid-xkd)+ψid(pbest-xid)；
In formula, xidFor i-th of food source, xkdFor k-th of food source, k ∈ n, k ≠ i, zidFor searching operators, φidFor [-
1,1] random number between, ψidFor the random number between [0,1.5], pbestFor local optimum.
Preferably, the step 3 specifically includes the following steps:
Step 31: global optimization scheduling model is set fitness function by global optimization scheduling model parameter initialization；
Step 32: given optimized variable size, velocity original value, maximum number of iterations and running precision, at the beginning of obtaining multiple groups
Beginning population selects optimal initial individuals population and obtains the optimal initial value of supply of cooling, heating and electrical powers distributed busbar protection each section equipment
And the overall operation value at cost from which further followed that.
Step 33: candidate solution being searched for around the optimal initial individuals population according to artificial bee colony operator, compares candidate solution
It will most if the overall operation cost that candidate solution obtains is less than the overall operation cost that optimal initial value obtains with optimal initial value
Excellent initial value replaces with candidate solution；If it is not, optimal initial value is constant；
Step 34: determining whether global optimum's variable in each replacement process meets given running precision or maximum and change
Generation number, if meeting given running precision or reaching maximum number of iterations, the supply of cooling, heating and electrical powers distribution after exporting final optimization pass
The optimal value of formula energy source station each section equipment and the overall operation value at cost from which further followed that；
Step 35: if not reaching Rule of judgment, by updating weight coefficient and population velocity location formula, repeating
Step 32~34.
Compared with prior art, the invention has the following advantages that
(1) this Optimization Scheduling not only promotes " peak load shifting " of external power grid compared to conventional scheduling method, but also
Alleviate network load pressure, improves the on-site elimination ability of region new energy, realize clean and effective truly.
(2) it establishes comprising the distribution including wind-light storage, cooling heating and power generation system, centrifugal cold and air source heat pump
Energy source station model, objective function considers system operation cost and Environmental costs, and Environmental costs are discharged by trilogy supply gas
It is associated with Environmental costs, single-object problem is converted by multi-objective optimization question, more comprehensively establishes optimization fortune
Row model.
(3) optimal operation model is solved using the APSO algorithm for introducing bee colony operator, bee colony operator draws
Enter to improve exploring ability, so that algorithm jumps out local optimum when solving complex nonlinear optimization problem, improves algorithm performance；
Adaptive weighting introduce, can with the relationship between dynamic regulation example target function value and example average target functional value so that
Particle searching process is not easy to fall into Local Minimum.Algorithm of the invention effectively improves algorithm later period convergence hardly possible, is easily trapped into office
The optimal problem in portion, compared with traditional PS O algorithm, with better local optimum and global optimization ability.
Detailed description of the invention
Fig. 1 is applicating flow chart of the invention；
Fig. 2 is distributed busbar protection structural schematic diagram in the present invention；
Fig. 3 is garden summer typical day electric load and refrigeration duty in example；
Fig. 4 is garden winter typical day electric load and thermic load in example；
Fig. 5 is garden cold energy optimizing scheduling result under the typical day of summer in example；
Fig. 6 is garden electric energy optimizing scheduling result under the typical day of summer in example；
Fig. 7 is garden thermal energy optimizing scheduling result under typical day in winter in example；
Fig. 8 is garden electric energy optimizing scheduling result under typical day in winter in example；
Fig. 9 is idiographic flow schematic diagram of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is a part of the embodiments of the present invention, rather than whole embodiments.Based on this hair
Embodiment in bright, those of ordinary skill in the art's every other reality obtained without making creative work
Example is applied, all should belong to the scope of protection of the invention.
Embodiment
As shown in Fig. 2, distributed busbar protection system integrates refrigeration, heat supply, power generation.Electric load is by gas internal-combustion engine
Gas Engine, abbreviation GE and power grid Grid power supply；Refrigeration duty is by flue gas type cold/hot water machine of lithium bromide group Lithium
Bromide Cold or Heat Water Unit with Type of Flue Gas Absorption, abbreviation LB offer,
Insufficient section is supplemented by centrifugal refrigerating machines Electric Chillier, abbreviation EC；Thermic load is by flue gas type lithium bromide absorption
Formula water chiller-heater unit provides, and insufficient section is supplemented by net for air-source heat pump units (Heat Pump, abbreviation HP)；Simultaneously in the system,
Comprising wind energy Wind Turbine, abbreviation WT, solar energy Photovoltaic Concentrator System, abbreviation PV etc. are clear
The clean energy, and increase energy storage device Energy Storage Equipment, abbreviation ES, the system energy is various informative, to divide
The economical operation of cloth energy source station needs to consider the output distribution of each supply unit in distributed busbar protection system, and distribution
Electric energy between formula energy source station and external power grid interacts, and under the premise of meeting hot and cold, electric load the demand in region, improves energy
Source system performance driving economy and the feature of environmental protection.
As shown in figure 9, a kind of supply of cooling, heating and electrical powers distributed busbar protection cooperates with Optimization Scheduling, distributed busbar protection is main
Equipment has combined supply system, centrifugal cold, air source heat pump and wind-light storage comprising following steps:
Step 1: being established according to supply of cooling, heating and electrical powers distributed busbar protection each section equipment operation characteristic and consider economic benefit rule
It draws, establishes the moving model that each equipment of supply of cooling, heating and electrical powers distributed busbar protection considers economic planning factor；
Step 2: comprehensively considering Environmental costs and economic operation cost, will discharge pollutants and environmental carrying capacity economics
Method indicates, for supply of cooling, heating and electrical powers distributed busbar protection each section equipment moving model combination constraint condition construct it is whole
Optimal Operation Model establishes the global optimization scheduling model combined including constraint condition；
Step 3: using improving and optimizating based on the adaptive particle swarm optimization algorithm of bee colony Optimizing operator to global optimization
Scheduling model solve and then obtains supply of cooling, heating and electrical powers distributed busbar protection each section equipment optimal scheduling strategy, improves bee colony
Optimize PSO Algorithm Optimized model, obtain the optimal power output of each equipment, wherein step 3 it is further comprising the steps of:
Step 31: global optimization scheduling model is set fitness function by global optimization scheduling model parameter initialization；
Step 32: given optimized variable size, velocity original value, maximum number of iterations and running precision, at the beginning of obtaining multiple groups
Beginning population selects optimal initial individuals population and obtains the optimal initial value of supply of cooling, heating and electrical powers distributed busbar protection each section equipment
And the overall operation value at cost from which further followed that.
Step 33: candidate solution being searched for around the optimal initial individuals population according to artificial bee colony operator, compares candidate solution
It will most if the overall operation cost that candidate solution obtains is less than the overall operation cost that optimal initial value obtains with optimal initial value
Excellent initial value replaces with candidate solution；If it is not, optimal initial value is constant；
Step 34: determining whether global optimum's variable in each replacement process meets given running precision or maximum and change
Generation number, if meeting given running precision or reaching maximum number of iterations, the supply of cooling, heating and electrical powers distribution after exporting final optimization pass
The optimal value of formula energy source station each section equipment and the overall operation value at cost from which further followed that；
Step 35: if not reaching Rule of judgment, by updating weight coefficient and population velocity location formula, repeating
Step 32~34.
Step 4: verification algorithm feasibility and high efficiency after the optimal power output operation reserve of actual motion equipment.
In the present embodiment, the moving model of each distributed unit being applied in step 1 is as follows:
1. gas internal-combustion engine generating set model
The present invention mainly studies the static characteristic of its output power and fuel input.Using the model can Simplified analysis,
And preferably show the relationship between power output and system:
Wherein,It represents internal combustion engine generator group and high-temperature flue gas heat is provided；Represent gas internal-combustion engine consumption
Amount of natural gas；θGE,i_tRepresent certain moment generated energy and high-temperature flue gas hotspot stress；ηGERepresent gas internal-combustion engine power generation coefficient.
2. wind-driven generator group model:
Wherein, PWT,N_tN typhoon power generator is represented in t period electrical power；vciTo cut wind speed；vcoTo cut out wind
Speed；vrateFor rated wind speed；λ1,λ2,λ3For fitting coefficient, the wind for obtaining, generally finding can be fitted by wind-force power curve
Speed is all the wind speed at 10m, it is understood that the wind speed of blower fan pylon height needs following update equation:
Vi=V2(Hi/H2)α；
Wherein, ViRepresent height HiWind speed, unit m/s；V2To need corrected altitude H2Wind speed, unit m/s；α
For power exponent, 1/7 is generally taken.
3. photovoltaic power generation model
Model is defeated at this time using simplified photovoltaic cell model when carrying out photovoltaic power generation prediction for the ease of simulation calculation
Power is only related with intensity of illumination and environment temperature out:
Wherein, PPV,M_tFor m group photovoltaic cell the t period electrical power；GAC,M_tIt is m group photovoltaic cell in the t period
Intensity of illumination；PSTCIt is m group photovoltaic cell in standard test condition (1000W/m2, 25 DEG C) under maximum electric power；
TAMD_tFor photovoltaic cell current operating temperature；NOCT is specified photovoltaic battery temperature, and m is natural number.
4. electric energy storage device model
Electric energy storage device plays important function in improving system power quality, energy station owner involved in the present embodiment
To consider the relationship between energy storage charge and discharge and current electric quantity using battery as energy storage device, not consider internal storage battery
Charge and discharge process:
Wherein, EES_tFor period t electricity energy storage device capacity；τ is electric energy storage self discharge efficiency；EES_(t-1)For t-1 period electricity
Energy storage device capacity；ηchFor electric energy storage device charge efficiency；ηdiscFor electric energy storage device discharging efficiency；Pch_tWhen for electric energy storage t
Section charge power；Pdisc_tFor electric energy storage t period discharge power.
5. cold/hot water machine of lithium bromide group model
Cold/hot water machine of lithium bromide group provides cooling and heating load for system, and output power and internal combustion engine export more than flue gas
Heat is directly proportional:
Wherein,For t period lithium cold Hot water units heating capacity；It is cold and hot for t period lithium bromide
Water dispenser group heats COP；To input high-temperature flue gas calorific value；For t period lithium cold Hot water units refrigerating capacity；For t period lithium cold Hot water units refrigeration COP.
6. centrifugal cold model
Electric refrigerating machine, refrigerating capacity are related with power consumption and energy efficiency coefficient:
QEC,J_t=PEC,J_tCOPEC,J_t；
Wherein, QEC,J_tIndicate the cold power that the centrifugal cold of J platform is provided in the t period；PEC,J_tIndicate that J platform is centrifugal
Cold the t period freeze consumption electrical power；COPEC,J_tIndicate that energy efficiency coefficient of the centrifugal cold of J platform in the t period, J are certainly
So number.
7. air source heat pump model
Heat pump cycle heating capacity:
QHP,R_t=PHP,R_tCOPHP,R_t；
Wherein, QHP,R_tRepresent R platform air source heat pump heating load within the t period；PHP,R_tRepresent R platform air-source heat
Pump power consumption within the t period；COPHP,R_tR platform air source heat pump is represented in t period energy efficiency coefficient.
In the present embodiment, in distributed busbar protection optimal operation model, economic optimization operation principal element has economic optimization
Operation principal element has operating cost and Environmental costs.Cost of equipment maintenance, equipment purchase cost, equipment are not considered in this model
Depreciable cost, main research power purchase expense, purchase natural gas expense and Environmental costs under collaboration optimization.Commercial power is fixed at present
Valence strategy mostly uses two electricity price systems, i.e., combines the corresponding basic electricity price of capacity electricity price corresponding with electricity consumption certainly
Determine electricity price, in winter and in summer power supply, by electricity price be arranged peak, paddy, flat third gear, consider distributed busbar protection purchase of electricity,
Electricity sales amount and purchase sale of electricity section, while considering to generate pollutant emission cost, distributed busbar protection global optimization by Gas Generator Set
Scheduling model includes:
Distributed busbar protection overall operation cost minimization, formula are as follows:
min Csum=Cpurel+Cpurgas+Cenv；
In formula, t, T, i, N are natural number, CsumFor distributed busbar protection overall operation cost, CpurelFor power purchase expense,
CpurgasTo purchase natural gas expense, CenvFor Environmental costs, Cgrid,tFor electricity price, PSELL_tFor electricity, CgasFor natural gas unit heat
Costly lattice,Amount of natural gas, V are consumed for gas internal-combustion engineMT_(t)iAmount of natural gas is consumed for gas turbine,And ENOx,k(PiIt (t)) be respectively cooling heating and power generation system in t moment specific power is P
When i-th of generating equipment CO2,SO2,NOxDischarge amount,WithRespectively CO2,SO2,NOxUnit environment at
This, unit is, for heat equivalent coefficient of performance ρ=Qh/SEERC, wherein SEERCFor equivalent electric quantity consumption, QhWork as heat supply
Amount.
Wherein, CpurelIt indicates the electricity purchased from power grid and the product of its electricity price, works as PSELL_t> 0 is represented at this time from electricity
Power purchase in net, at this time Cgrid,tUsing tou power price；Work as PSELL_tWhen < 0, system is represented at this time and is powered to power grid, at this time Cgrid,t
Using rate for incorporation into the power network, 0.67 yuan/KWh is taken in the present embodiment, Environmental costs mainly include environmental value and and discharge caused
Quantity is imposed a fine, pollutant emission mostlys come from combined supply system, wherein it is as follows that supply of cooling, heating and electrical powers gas discharges model:
In formula, Ej,k(PiIt (t)) is supply of cooling, heating and electrical powers gas emissions；Pi(t) exist for i-th of equipment of cooling heating and power generation system
T moment specific power, αi,βi,γ,λiModel parameter is discharged for gas.
Distributed busbar protection global optimization scheduling model includes day part gas internal-combustion engine power, air source heat pump heating function
Rate, energy-storage battery charge-discharge electric power, centrifugal cold refrigeration work consumption, fume hot-water type lithium bromide chiller refrigeration, heats power and
Power grid purchase of electricity；Under the premise of meeting each facility constraints and energy constraint, pass through electricity price rate, natural gas rate and pollution
Substance environment cost constraint realizes the cooperation between each equipment of different periods, and Reasonable Regulation And Control power purchase and purchase gas expense are used, real
The collaboration optimization of existing system operation cost and Environmental costs, as follows applied to the constraint condition in step 2:
In formula,T period all gas internal-combustion engine power supply volumes are represented,Represent t period all light
Lie prostrate generated energy, Pdis_tT period energy-storage battery discharge capacity is represented,T period all wind-driven generator power supply volumes are represented,
PSELL_tThe t period is represented from power grid purchase of electricity,Represent t period all centrifugal cold power consumption, PNEED_tRepresent t
Period user power utilization demand, Pch_tRepresent t period energy-storage battery charge volume, PLOSS_tRepresent t period system power consumption, QNEED_t
Represent the thermic load of t period, QHP,R_tThe heat pump heat supply amount of t period is represented,Represent t period lithium bromide absorption type cooling and heating
Water dispenser group heating load, Qloss_tRepresent t period heat dissipation capacity, C when operating normallyNEED_tRepresent t period refrigeration duty, QEC,J_tRepresent t
Period centrifugal cold refrigerating capacity,Represent t period cold/hot water machine of lithium bromide group refrigerating capacity, Closs_tRepresent t
Period operates normally dissipation amount.
The generated output of gas internal-combustion engine constrains, and the generated energy of gas internal-combustion engine is not to be exceeded its rated power, is simultaneously
Meet internal combustion engine with certain generating efficiency, the output power of internal combustion engine is no less than its 50 percent rated power, public
Formula is as follows:
In formula,T moment gas internal-combustion engine generated output is represented,Represent t-1 moment combustion gas internal combustion
Machine generated output,Maximum power generation is represented,Represent minimum generated output, UGEIt represents in combustion gas
The upward creep speed of combustion engine, DGEThe downward creep speed of gas internal-combustion engine is represented, Δ t is transformation period,
Lithium cold Hot water units semen donors and the constraint of heating load bound, formula are as follows:
In formula,Minimum and maximum is for calorific value when respectively representing lithium cold Hot water units heat supply,Minimum and maximum cooling supply value when respectively representing lithium cold Hot water units refrigeration, Point
Lithium cold Hot water units t moment heating capacity and refrigerating capacity are not represented,
Centrifugal cold t period refrigerating capacity bound constraint, formula are as follows:
QEC,min≤QEC,J_t≤QEC,max；
In formula, QEC,J_tFor centrifugal cold t period refrigerating capacity, QEC,minFor centrifugal cold refrigerating capacity minimum value, QEC,max
For centrifugal cold refrigerating capacity maximum value,
The constraint of air source heat pump t period heating load bound, formula are as follows:
QHP,min≤QHP,R_t≤QHP,max；
In formula, QHP,R_tFor air source heat pump t period heating load, QHP,R_minIt is minimum for air source heat pump t period heating load
Value, QHP,R_maxFor air source heat pump t period heating load maximum value,
The bound constraint of the discharge power and charge power of electric energy storage device, for electric energy storage device, externally
When electric discharge, the maximum discharge-rate that maximum discharge power is no more than its own capacity and allows similarly is filled in electric energy storage device
When electric, maximum charge power also cannot be beyond the maximum charge multiplying power of its own capacity permission, and formula is as follows:
In formula, γES,chFor electric energy storage device maximum charge multiplying power；γES,disFor electric energy storage device maximum discharge-rate；
PES,ch_tFor electric energy storage device period t charge power；PES,ch_tFor electric energy storage device period t discharge power；SESFor
Electric energy storage device rated capacity.
Using the APSO algorithm for mirroring artificial bee colony operator in step 3 of the present invention, algorithm is improved and optimizated,
It mainly include self-adaptive weight sum artificial bee colony searching operators, the formula of adaptive weighting are as follows:
In formula, f indicates current particle target function value, fmean, fminRespectively indicate current particle average target functional value and
Smallest particles target function value, ωminFor weight minimum value, ωmaxFor weight maximum value, ω is weight,
The formula of searching operators are as follows:
zid=xid+φid(xid-xkd)+ψid(pbest-xid)；
In formula, xidFor i-th of food source, xkdFor k-th of food source, k ∈ n, k ≠ i, zidFor searching operators, φidFor [-
1,1] random number between, ψidFor the random number between [0,1.5], pbestFor local optimum, Algorithm Convergence and weight are taken
Value is related.In APSO algorithm, when the target function value of particle deviates from particle average target functional value, at this time
Reduce inertia weight coefficient；When the target function value of particle is close to particle average target functional value, increase inertia weight at this time, reflects
Particle search ability is improved to sacrifice algorithm development ability as cost in artificial bee colony algorithm, introduces artificial bee colony algorithm search
Operator lays particular emphasis on raising exploring ability, so that algorithm jumps out local optimum when solving complex nonlinear optimization problem, improves and calculates
Method performance.
Optimize tune in distributed busbar protection applied to the artificial bee colony operator adaptive particle swarm optimization algorithm in step 3
The applicating flow chart of degree as shown in Figure 1, itself the following steps are included:
(1) model parameter initializes, and determines that variable to be optimized, variable bound, system restriction, electricity price and natural gas constrain,
Fitness function is set by the objective function of system；
(2) optimized variable size, velocity original value, maximum number of iterations and running precision are given；First in the pact of each equipment
One group of initial population is generated under the conditions of beam, by comparing the fitness size of every group of initial population, selects first time iteration most
Excellent individual calculates current optimal totle drilling cost；
(3) candidate solution is searched near the initial population according to artificial bee colony operator, compares candidate solution and is acquired with optimal solution
Initial solution is replaced with candidate solution if candidate solution show that totle drilling cost is smaller by totle drilling cost；If it is not, initial solution is constant；
(4) determine whether global optimum's variable meets given accuracy or the number of iterations, if meeting given accuracy or reaching repeatedly
Generation number, then it is optimum to export each optimized variable, optimized operation cost and Environmental costs；
(5) if not reaching Rule of judgment, formula is optimized by inertia coeffeicent and updates inertia coeffeicent, passes through particle group velocity
It spends location formula and updates variable size and variable change speed to be optimized, repeat step (2)-(4).
In the present embodiment, comparison tradition point is for the distributed busbar protection Optimized Operation side under form and under different control strategies
Method, for the present embodiment with the Practical Project case of East China garden, preset standard and device parameter are as shown in Table 1, 2 and 3
To rely on, construction is with the distributed busbar protection system for the supply of cooling, heating and electrical powers that wind-force, photovoltaic, natural gas are the basic energy, with summer
It is research object with winter typical day user side cold heat, electric load, summer and winter cold heat, electric load use garden user side
Truthful data, curve graph are as shown in Figures 3 and 4.
Summer refrigeration duty cooperate with optimum results as shown in figure 5, user's refrigeration duty demand as the diagram in figure 5 shows, summer is logical
It crosses fume hot-water type lithium bromide chiller and centrifugal cold two ways carrys out cooling supply, electricity price is relatively low while required when paddy when paddy
Refrigeration duty is smaller and pollutant emission limitation, paddy period freeze by centrifugal cold；The peak period preferentially uses bromination
Lithium unit refrigeration；Big in 8:00~17:00 period user side refrigeration duty demand, lithium bromide chiller refrigeration is no longer satisfied load
Demand is optimized by collaboration, and centrifugal cold is freezed simultaneously, the available satisfaction of workload demand.
Electrical load in summer cooperates with shown in optimum results Fig. 6, and broken line indicates custom power workload demand, summer customer charge
It is supplied by gas internal-combustion engine, energy storage device, wind turbine power generation and photovoltaic power generation, vacancy part is supplied from power grid, is meeting user side
Under the premise of electric load, extra electric energy can generate electricity by way of merging two or more grid systems, and paddy period user power utilization load is relatively low, using gas internal-combustion engine into
Row power supply, power output lower limit are 1600kW, and heat dissipates seriously, and Environmental costs greatly increase, when paddy electric load mainly by
Power grid power purchase meets with consumption wind-powered electricity generation；In 8:00~11:00 period, user's refrigeration duty and electrical load requirement are all bigger, this
When photovoltaic generation power and wind-power electricity generation power it is smaller, energy storage system discharges are still needed to from power grid for meeting customer charge demand
Purchase part electric energy is used to meet user's electrical load requirement；The period is whole because centrifugal cold simultaneously participates in refrigeration consumption electric energy
Body power supply is slightly larger than user's electrical load requirement.With temperature, the raising of sunlight irradiation degree and wind speed, after 11:00, electricity
Power supply is abundant, and extra electric energy generates electricity by way of merging two or more grid systems.
The supply of winter thermic load cooperates with optimum results as shown in fig. 7, winter passes through fume hot-water type lithium bromide chiller and sky
Air supply heat pump two ways heat supply preferentially uses lithium bromide chiller heat supply in 8:00~12:00 user's thermic load peak time,
User side thermal load demands are still unsatisfactory for, at this time using air source heat pump heat supply simultaneously；After 21:00, by air-source heat
Pump heat supply.
Winter electric load cooperates with optimum results as shown in figure 8, same summer, customer charge demand is by gas internal-combustion engine, storage
Energy equipment, blower and photovoltaic provide, and winter electric load usage amount is lower than summer, but because this area's winter temperature is low, sunlight spoke
Illumination is low, and wind speed is unstable and less than normal, and photovoltaic generation power and wind-power electricity generation power are far below summer, therefore rely primarily on combustion gas
Internal combustion engine supply of electrical energy, same to summer, paddy period user's side power load demand are mainly met by blower and power grid power purchase；8:
00~11:00 period energy-storage system starts electric discharge and meets user demand, and gas internal-combustion engine works in rated power state, due to heat
Heat pump heating also needs to consume a part of electric energy, and system power demand need to be met from power grid power purchase；After when 11, combustion engine, blower and
Photovoltaic power generation can satisfy user demand.
In order to verify the optimizing scheduling ability of ABC-APSO algorithm, the present embodiment with operating cost under traditional supplying mode and
Environmental costs the results are shown in Table 4 using PSO and CFW-PSO optimum results as reference, compared to tradition directly from power grid power purchase mode, warp
After crossing the optimization of distributed busbar protection systematic collaboration, system synthesis originally significantly decreases；In algorithm optimization result, because of bee colony
The outstanding local optimal searching effect of Optimizing operator, and then influence the performance of total optimization value, as can be seen from the results, ABC-APSO optimizing performance
Preferably, the lowest cost, while guaranteeing there is optimized operation cost compared under subenvironment cost reasons, can be with by result above
Find out, traffic control method according to the present invention, on the one hand makes full use of trough-electricity, the flat peak period reduces power purchase to the greatest extent, another
Aspect creates certain economic benefit by grid-connected sale of electricity under low pollution object conditions of discharge as far as possible, in addition, not only promoting
" peak load shifting " of external power grid alleviates power grid pressure, has also preferably dissolved region generation of electricity by new energy, realizes truly
Clean and effective.
1 pollutant emission model parameter of table
2 power industry polluted gas discharge standard of table
| CO2 | SO2 | NOx | |
| Environmental value ($/kg) | 0.018285 | 4.77 | 6.36 |
| Impose a fine amount of money ($/kg) | 0.00795 | 0.795 | 1.59 |
| Emission limit (kg) | 10000 | 500 | 40 |
3 distributed busbar protection system equipment parameter of table
4 distributed busbar protection aims of systems optimum results of table compare
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection scope subject to.
Claims (7)
1. a kind of supply of cooling, heating and electrical powers distributed busbar protection cooperates with Optimization Scheduling, which comprises the following steps:
Step 1: establishing the moving model that each equipment of supply of cooling, heating and electrical powers distributed busbar protection considers economic planning factor；
Step 2: establishing the global optimization scheduling model combined including constraint condition；
Step 3: improving bee colony and optimize PSO Algorithm Optimized model, obtain the optimal power output of each equipment；
Step 4: verification algorithm feasibility and high efficiency after the optimal power output operation reserve of actual motion equipment.
2. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 1 cooperates with Optimization Scheduling, feature exists
In the moving model in the step 1 includes: gas internal-combustion engine generating set model, wind-driven generator group model, photovoltaic hair
Motor group model, electric energy storage device model, cold/hot water machine of lithium bromide group model, centrifugal cold model and air-source heat
Pump model.
3. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 1 cooperates with Optimization Scheduling, feature exists
In the global optimization scheduling model in the step 2 includes:
Distributed busbar protection overall operation cost minimization, formula are as follows:
min Csum=Cpurel+Cpurgas+Cenv；
In formula, t, T, i, N are natural number, CsumFor distributed busbar protection overall operation cost, CpurelFor power purchase expense, Cpurgas
To purchase natural gas expense, CenvFor Environmental costs, Cgrid,tFor electricity price, PSELL_tFor electricity, CgasFor natural gas unit calorific value valence
Lattice,Amount of natural gas, V are consumed for gas internal-combustion engineMT_(t)iAmount of natural gas is consumed for gas turbine,WithRespectively cooling heating and power generation system is in t moment specific power
I-th of generating equipment CO when P2,SO2,NOxDischarge amount,WithRespectively CO2,SO2,NOxUnit environment
Cost, unit are, for heat equivalent coefficient of performance ρ=Qh/SEERC, wherein SEERCFor equivalent electric quantity consumption, QhFor heat supply
Equivalent.
4. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 1 cooperates with Optimization Scheduling, feature exists
In the constraint condition in the step 2 includes:
Energy balance constraint, formula are as follows:
In formula,T period all gas internal-combustion engine power supply volumes are represented,Represent t period all photovoltaic hairs
Electricity, Pdis_tT period energy-storage battery discharge capacity is represented,Represent t period all wind-driven generator power supply volumes, PSELL_t
The t period is represented from power grid purchase of electricity,Represent t period all centrifugal cold power consumption, PNEED_tRepresenting the t period uses
Family electricity demand, Pch_tRepresent t period energy-storage battery charge volume, PLOSS_tRepresent t period system power consumption, QNEED_tRepresent t
The thermic load of period, QHP,R_tThe heat pump heat supply amount of t period is represented,Represent t period cold/hot water machine of lithium bromide
Group heating load, Qloss_tRepresent t period heat dissipation capacity, C when operating normallyNEED_tRepresent t period refrigeration duty, QEC,J_tRepresent the t period from
Core type cold refrigerating capacity,Represent t period cold/hot water machine of lithium bromide group refrigerating capacity, Closs_tRepresent the t period just
Often operation dissipation amount,
The generated output of gas internal-combustion engine constrains, and formula is as follows:
In formula,T moment gas internal-combustion engine generated output is represented,Represent t-1 moment gas internal-combustion engine hair
Electrical power,Maximum power generation is represented,Represent minimum generated output, UGERepresent gas internal-combustion engine to
Upper creep speed, DGEThe downward creep speed of gas internal-combustion engine is represented, Δ t is transformation period,
Lithium cold Hot water units semen donors and the constraint of heating load bound, formula are as follows:
In formula,Minimum and maximum is for calorific value when respectively representing lithium cold Hot water units heat supply,Minimum and maximum cooling supply value when respectively representing lithium cold Hot water units refrigeration, Point
Lithium cold Hot water units t moment heating capacity and refrigerating capacity are not represented,
Centrifugal cold t period refrigerating capacity bound constraint, formula are as follows:
QEC,min≤QEC,J_t≤QEC,max；
In formula, QEC,J_tFor centrifugal cold t period refrigerating capacity, QEC,minFor centrifugal cold refrigerating capacity minimum value, QEC,maxFor from
Core type cold refrigerating capacity maximum value,
The constraint of air source heat pump t period heating load bound, formula are as follows:
QHP,min≤QHP,R_t≤QHP,max；
In formula, QHP,R_tFor air source heat pump t period heating load, QHP,R_minFor air source heat pump t period heating load minimum value,
QHP,R_maxFor air source heat pump t period heating load maximum value,
The bound constraint of the discharge power and charge power of electric energy storage device, formula are as follows:
In formula, γES,chFor electric energy storage device maximum charge multiplying power；γES,disFor electric energy storage device maximum discharge-rate；PES,ch_t
For electric energy storage device period t charge power；PES,ch_tFor electric energy storage device period t discharge power；SESFor electric energy storage
Equipment rated capacity.
5. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 1 cooperates with Optimization Scheduling, feature exists
In the improvement bee colony optimization particle swarm algorithm in the step 3 includes introducing self-adaptive weight sum searching operators to improve and optimizate.
6. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 5 cooperates with Optimization Scheduling, feature exists
In the formula of the adaptive weighting are as follows:
In formula, f indicates current particle target function value, fmean, fminRespectively indicate current particle average target functional value and minimum
Particle target function value, ωminFor weight minimum value, ωmaxFor weight maximum value, ω is weight,
The formula of the searching operators are as follows:
zid=xid+φid(xid-xkd)+ψid(pbest-xid)；
In formula, xidFor i-th of food source, xkdFor k-th of food source, k ∈ n, k ≠ i, zidFor searching operators, φidFor [- 1,1]
Between random number, ψidFor the random number between [0,1.5], pbestFor local optimum.
7. a kind of supply of cooling, heating and electrical powers distributed busbar protection according to claim 1 cooperates with Optimization Scheduling, feature exists
In, the step 3 specifically includes the following steps:
Step 31: global optimization scheduling model is set fitness function by global optimization scheduling model parameter initialization；
Step 32: given optimized variable size, velocity original value, maximum number of iterations and running precision obtain initial kind of multiple groups
Group, select optimal initial individuals population and obtain supply of cooling, heating and electrical powers distributed busbar protection each section equipment optimal initial value and into
The overall operation value at cost that one step obtains.
Step 33: candidate solution is searched for around the optimal initial individuals population according to artificial bee colony operator, compare candidate solution with most
Excellent initial value will be optimal first if the overall operation cost that candidate solution obtains is less than the overall operation cost that optimal initial value obtains
Initial value replaces with candidate solution；If it is not, optimal initial value is constant；
Step 34: determining whether global optimum's variable in each replacement process meets given running precision or greatest iteration time
Number, if meeting given running precision or reaching maximum number of iterations, the supply of cooling, heating and electrical powers distribution energy after exporting final optimization pass
The optimal value of source station each section equipment and the overall operation value at cost from which further followed that；
Step 35: if not reaching Rule of judgment, by updating weight coefficient and population velocity location formula, repeating step
32~34.
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