CN107565605A - A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically - Google Patents
A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically Download PDFInfo
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- CN107565605A CN107565605A CN201710738249.6A CN201710738249A CN107565605A CN 107565605 A CN107565605 A CN 107565605A CN 201710738249 A CN201710738249 A CN 201710738249A CN 107565605 A CN107565605 A CN 107565605A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- 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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
Tend to the method for optimization automatically the invention discloses a kind of shop equipment based on micro-capacitance sensor.Specially：The minimum optimization aim of annual operating cost that shop equipment is formed with operation expense, purchases strategies, fuel cost and energy storage depreciable cost, consider cool and thermal power Constraints of Equilibrium, equipment operation constraint and energy storage device constraint, scheduling is optimized to micro-capacitance sensor, realize that the automatic trend of factory optimizes, its computational methods is as follows：Min CATC=COM+CES+CBW+CF.The beneficial effects of the invention are as follows：Realize various energy resources cooperative compensating, guiding user formulate reasonably with can scheme, improve the energy consumption efficiency of user side, reduce user with can cost, so as to increase economic efficiency and energy utilization rate.
Description
Technical field
The present invention relates to comprehensive energy and electricity needs response correlative technology field, refer in particular to a kind of based on micro-capacitance sensor
Shop equipment tends to the method for optimization automatically.
Background technology
Integrated energy system (integrated energy system, IES) is the energy resource system of intelligence of future generation so that
The energy production of energy resource system, transmission, storage and using having systematization, integrated and the operation and management that become more meticulous.It is comprehensive
Energy resource system is the important physical carrier of energy internet, is the key for realizing the technologies such as multi-energy complementation, cascaded utilization of energy.
Industrial park is the complicated energy resource system based on industrial load, comprising a variety of production capacities/use energy equipment, to power supply reliability requirement
Height, but the problems such as generally existing energy utilization rate is low, energy resource structure is unreasonable, peak valley electric power difference is big, environmental pollution.From China
The energy resource consumption situation of every profession and trade sees that industrial consumption energy occupies leading position in AND ENERGY RESOURCES CONSUMPTION IN CHINA, accounts for whole society's total energy consumption
70% or so, it is therefore necessary to energy management is carried out to factory, lifts the economic benefit and energy utilization rate of factory.
The content of the invention
The present invention is above-mentioned in order to overcome the shortcomings of to exist in the prior art, there is provided one kind is increased economic efficiency and the energy
The shop equipment based on micro-capacitance sensor of utilization rate tends to the method for optimization automatically.
To achieve these goals, the present invention uses following technical scheme：
A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically, and shop equipment is with operation expense, purchase
The minimum optimization aim of annual operating cost that electric cost, fuel cost and energy storage depreciable cost are formed, considers cold and hot electric equilibrium
Constraint, equipment operation constraint and energy storage device constraint, scheduling is optimized to micro-capacitance sensor, realizes the automatic trend optimization of factory,
Its computational methods is as follows：
MinCATC=COM+CES+CBW+CF。
This method is minimum with the annual operating cost of user under conditions of cool and thermal power Constraints of Equilibrium and plurality of devices constraint
Target, structure consider micro-capacitance sensor economic optimization scheduling model, realize the excellent scheduling that becomes certainly of factory.It is more that this method considers cool and thermal power
It can couple, realize various energy resources cooperative compensating, guiding user is formulated reasonably with energy scheme, and improve user side uses efficiency
Rate, reduce user with can cost, so as to increase economic efficiency and energy utilization rate.
Preferably, described shop equipment includes gas turbine, gas fired-boiler, photovoltaic unit, Absorption Refrigerator, heat
Pump, family air-conditioning, regenerative apparatus, battery energy storage and ice-chilling air conditioning system；The computational methods of the operation expense are as follows：
Wherein：Hop count when t is, T are unit Period Length,ξOMiFor equipment i unit capacities
Operation and maintenance cost；Represent power output of i-th of the equipment in period t.
Preferably, the computational methods of the purchases strategies are as follows：
Wherein：WithRespectively period t power purchase price and power purchase power；WithRespectively period t's sells
Electricity price lattice and sale of electricity power.
Preferably, the computational methods of the fuel cost are as follows：
Wherein：WithThe respectively gas consumption rate of i-th of gas turbine of period t and i-th of gas fired-boiler；For gas price.
Preferably, the energy storage depreciable cost refers to：With the intensification of depth of discharge, the discharge and recharge of battery energy storage can
Cycle-index is reduced, but cycle charge-discharge total amount is basically unchanged, if discharge and recharge total amount of the battery energy storage in life cycle management
Constant, the depreciable cost for obtaining battery energy storage accumulated discharge 1kWh is as follows：
Wherein：Cbat.repFor the replacement cost of energy storage, qlifetimeTotal amount is exported for the energy storage monomer life-cycle；
Then the depreciable cost of energy storage is：
Wherein：For i-th of battery energy storage period t discharge power.
Preferably, described cool and thermal power Constraints of Equilibrium includes electrical power Constraints of Equilibrium, heating power balance constraint and cold work(
Rate Constraints of Equilibrium；Described electrical power Constraints of Equilibrium include the constraint of ac bus total load, AC/DC changeover switch efficiency constraints, directly
Flow the constraint of bus total load and interconnection constraint and purchase sale of electricity state constraint, specific constraints are as follows：
(a) ac bus total load constrains：
Wherein：The electrical power exported for i-th of gas turbine in period t；For i-th of photovoltaic unit when
The electrical power of section t outputs；For period t AC load；For the electrical power of alternating current-direct current converter；For the total electrical power of family air-conditioning；It is total for i-th of ice-chilling air conditioning system of period t
Electrical power；The electrical power consumed for i-th of heat pump in period t；
(b) AC/DC changeover switch efficiency constraints：
Wherein：For period t dc bus total load；ηA/DFor the conversion efficiency of AC-to DC；ηD/AArrived for direct current
The conversion efficiency of exchange；
(c) dc bus total load constrains：
Wherein：For period t DC load；WithFor i-th of battery energy storage period t charging
Power and discharge power；
(d) interconnection constraint and purchase sale of electricity state constraint：
Wherein：WithRespectively to power network power purchase and the upper limit of the power of sale of electricity；WithRespectively at period t
In power purchase and the 0-1 state variables of sale of electricity,1 expression power purchase is taken,1 expression sale of electricity is taken, also define to purchase simultaneously
Sale of electricity.
Preferably, the constraints of the heating power balance constraint is as follows：
Wherein：For the thermal power of gas-turbine waste heat boiler output；It is defeated in period t for i-th of gas fired-boiler
The thermal power gone out；For thermal power of i-th of heat pump in period t；It is i-th of family air-conditioning in period t
Thermal power；WithFor i-th of regenerative apparatus period t accumulation of heat power and heating power；WithPoint
Not Wei shop equipment space thermic load and hot water load.
Preferably, the constraints of the cold power-balance constraint is as follows：
Wherein：The cooling power for being i-th of Absorption Refrigerator in period t；For i-th of family air-conditioning
Refrigeration work consumption in period t；For the refrigeration work consumption of i-th of ice-chilling air conditioning system of period t；For refrigeration duty.
Preferably, the constraints of the equipment operation constraint is as follows：
Wherein：WithInput-output powers of the equipment i in period t is represented respectively；WithRepresent respectively
Equipment i is in period t power output bound；WithRepresent equipment i in period t input power bound respectively.
Preferably, the energy storage device constraint needs to meet energy storage state constraint and charge and discharge energy power constraint, in order to protect
The continuity of scheduling is demonstrate,proved, before and after dispatching cycle, the energy storage capacity of energy storage device should be consistent；The constraint of the energy storage device constraint
Condition is as follows：
SL.i=ST.i
Wherein：WithThe minimum and maximum storage volume of energy storage device is represented respectively；SL.iAnd ST.iFor energy storage
Initial capacity and the capacity at the end of dispatching cycle；WithThe maximum charge and electric discharge work(of energy storage device are represented respectively
Rate；WithRepresent that energy storage device is in the 0-1 state variables for filling energy and exoergic in period t respectively,1 expression is taken to fill energy,
Take 1 expression exoergic, ensure that equipment can not charge and discharge energy simultaneously.
The beneficial effects of the invention are as follows：Various energy resources cooperative compensating is realized, guiding user, which formulates, reasonably uses energy scheme,
Improve the energy consumption efficiency of user side, reduce user with can cost, so as to increase economic efficiency and energy utilization rate.
Embodiment
With reference to embodiment, the present invention will be further described.
A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically, and shop equipment is with operation expense, purchase
The minimum optimization aim of annual operating cost that electric cost, fuel cost and energy storage depreciable cost are formed, considers cold and hot electric equilibrium
Constraint, equipment operation constraint and energy storage device constraint, scheduling is optimized to micro-capacitance sensor, realizes the automatic trend optimization of factory,
Its computational methods is as follows：
MinCATC=COM+CES+CBW+CF。
Wherein：Shop equipment includes gas turbine, gas fired-boiler, photovoltaic unit, Absorption Refrigerator, heat pump, family sky
Tune, regenerative apparatus, battery energy storage and ice-chilling air conditioning system.
1) computational methods of operation expense are as follows：
Wherein：Hop count when t is, T are unit Period Length,ξOM.iFor equipment i unit capacities
Operation and maintenance cost；Represent power output of i-th of the equipment in period t.
2) computational methods of purchases strategies are as follows：
Wherein：WithRespectively period t power purchase price and power purchase power；WithRespectively period t's sells
Electricity price lattice and sale of electricity power.
3) computational methods of fuel cost are as follows：
Wherein：WithThe respectively gas consumption rate of i-th of gas turbine of period t and i-th of gas fired-boiler；For gas price.
4) energy storage depreciable cost：
Energy storage depreciable cost refers to：With the intensification of depth of discharge, the discharge and recharge of battery energy storage, which is recycled number, to be reduced,
But cycle charge-discharge total amount is basically unchanged, if discharge and recharge constant total quantity of the battery energy storage in life cycle management, obtains battery
Energy storage accumulated discharge 1kWh depreciable cost is as follows：
Wherein：Cbat.repFor the replacement cost of energy storage, qlifetimeTotal amount is exported for the energy storage monomer life-cycle；
Then the depreciable cost of energy storage is：
Wherein：For i-th of battery energy storage period t discharge power.
In addition, cool and thermal power Constraints of Equilibrium includes electrical power Constraints of Equilibrium, heating power balance constraint and cold power-balance constraint；
Electrical power Constraints of Equilibrium includes the constraint of ac bus total load, AC/DC changeover switch efficiency constraints, dc bus total load constrain
Constrained with interconnection with purchasing sale of electricity state constraint.
(1) the specific constraints of electrical power Constraints of Equilibrium is as follows：
(a) ac bus total load constrains：
Wherein：The electrical power exported for i-th of gas turbine in period t；It is i-th of photovoltaic unit in the period
The electrical power of t outputs；For period t AC load；For the electrical power of alternating current-direct current converter；For the total electrical power of family air-conditioning；It is total for i-th of ice-chilling air conditioning system of period t
Electrical power；The electrical power consumed for i-th of heat pump in period t；(b) AC/DC changeover switch efficiency constraints：
Wherein：For period t dc bus total load；ηA/DFor the conversion efficiency of AC-to DC；ηD/AArrived for direct current
The conversion efficiency of exchange；
(c) dc bus total load constrains：
Wherein：For period t DC load；WithFor i-th of battery energy storage period t charging
Power and discharge power；
(d) interconnection constraint and purchase sale of electricity state constraint：
Wherein：WithRespectively to power network power purchase and the upper limit of the power of sale of electricity；WithRespectively period t
0-1 state variables in power purchase and sale of electricity,1 expression power purchase is taken,1 expression sale of electricity is taken, also define can not be simultaneously
Purchase sale of electricity.
(2) constraints of heating power balance constraint is as follows：
Wherein：For the thermal power of gas-turbine waste heat boiler output；It is i-th of gas fired-boiler in period t
The thermal power of output；For thermal power of i-th of heat pump in period t；It is i-th of family air-conditioning in period t
Thermal power；WithFor i-th of regenerative apparatus period t accumulation of heat power and heating power；With
Respectively the space thermic load of shop equipment and hot water load.(3) constraints of cold power-balance constraint is as follows：
Wherein：The cooling power for being i-th of Absorption Refrigerator in period t；For i-th of family air-conditioning
Refrigeration work consumption in period t；For the refrigeration work consumption of i-th of ice-chilling air conditioning system of period t；For refrigeration duty.
(4) constraints of equipment operation constraint is as follows：
Wherein：WithInput-output powers of the equipment i in period t is represented respectively；WithRepresent respectively
Equipment i is in period t power output bound；WithRepresent equipment i in period t input power bound respectively.
(5) energy storage device constrains：
Energy storage device constraint needs to meet energy storage state constraint and charge and discharge energy power constraint, in order to ensure the continuous of scheduling
Property, before and after dispatching cycle, the energy storage capacity of energy storage device should be consistent；The constraints of the energy storage device constraint is as follows：
SL.i=ST.i
Wherein：WithThe minimum and maximum storage volume of energy storage device is represented respectively；SL.iAnd ST.iFor energy storage
Initial capacity and the capacity at the end of dispatching cycle；WithThe maximum charge and electric discharge work(of energy storage device are represented respectively
Rate；WithRepresent that energy storage device is in the 0-1 state variables for filling energy and exoergic in period t respectively,1 expression is taken to fill energy,
Take 1 expression exoergic, ensure that equipment can not charge and discharge energy simultaneously.
This method is minimum with the annual operating cost of user under conditions of cool and thermal power Constraints of Equilibrium and plurality of devices constraint
Target, structure consider micro-capacitance sensor economic optimization scheduling model, realize the excellent scheduling that becomes certainly of factory.It is more that this method considers cool and thermal power
It can couple, realize various energy resources cooperative compensating, guiding user is formulated reasonably with energy scheme, and improve user side uses efficiency
Rate, reduce user with can cost, so as to increase economic efficiency and energy utilization rate.
Claims (10)
1. a kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically, it is characterized in that, shop equipment is with operation maintenance
The minimum optimization aim of annual operating cost that cost, purchases strategies, fuel cost and energy storage depreciable cost are formed, consider cold and hot
Electric equilibrium constraint, equipment operation constraint and energy storage device constraint, scheduling is optimized to micro-capacitance sensor, realizes the automatic trend of factory
Optimization, its computational methods are as follows：
Min CATC=COM+CES+CBW+CF。
2. a kind of shop equipment based on micro-capacitance sensor according to claim 1 tends to the method for optimization automatically, it is characterized in that,
Described shop equipment includes gas turbine, gas fired-boiler, photovoltaic unit, Absorption Refrigerator, heat pump, family air-conditioning, accumulation of heat
Device, battery energy storage and ice-chilling air conditioning system；The computational methods of the operation expense are as follows：
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3. a kind of shop equipment based on micro-capacitance sensor according to claim 2 tends to the method for optimization automatically, it is characterized in that,
The computational methods of the purchases strategies are as follows：
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Wherein：WithRespectively period t power purchase price and power purchase power；WithRespectively period t sale of electricity valency
Lattice and sale of electricity power.
4. a kind of shop equipment based on micro-capacitance sensor according to claim 2 tends to the method for optimization automatically, it is characterized in that,
The computational methods of the fuel cost are as follows：
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Wherein：WithThe respectively gas consumption rate of i-th of gas turbine of period t and i-th of gas fired-boiler；For
Gas price.
5. a kind of shop equipment based on micro-capacitance sensor according to claim 2 tends to the method for optimization automatically, it is characterized in that,
The energy storage depreciable cost refers to：With the intensification of depth of discharge, the discharge and recharge of battery energy storage, which is recycled number, to be reduced, but is followed
Ring discharge and recharge total amount is basically unchanged, if discharge and recharge constant total quantity of the battery energy storage in life cycle management, obtains battery energy storage
Accumulated discharge 1kWh depreciable cost is as follows：
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Wherein：Cbat.repFor the replacement cost of energy storage, qlifetimeTotal amount is exported for the energy storage monomer life-cycle；
Then the depreciable cost of energy storage is：
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Wherein：For i-th of battery energy storage period t discharge power.
6. a kind of shop equipment based on micro-capacitance sensor according to claim 2 tends to the method for optimization automatically, it is characterized in that,
Described cool and thermal power Constraints of Equilibrium includes electrical power Constraints of Equilibrium, heating power balance constraint and cold power-balance constraint；Described
Electrical power Constraints of Equilibrium includes the constraint of ac bus total load, AC/DC changeover switch efficiency constraints, dc bus total load constrain
Constrained with interconnection as follows with purchase sale of electricity state constraint, specific constraints：
(a) ac bus total load constrains：
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Wherein：The electrical power exported for i-th of gas turbine in period t；It is defeated in period t for i-th of photovoltaic unit
The electrical power gone out；For period t AC load；For the electrical power of alternating current-direct current converter；For the total electrical power of family air-conditioning；It is total for i-th of ice-chilling air conditioning system of period t
Electrical power；The electrical power consumed for i-th of heat pump in period t；
(b) AC/DC changeover switch efficiency constraints：
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<mi>t</mi>
</msubsup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msub>
<mi>&eta;</mi>
<mrow>
<mi>A</mi>
<mo>/</mo>
<mi>D</mi>
</mrow>
</msub>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>></mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>=</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>&eta;</mi>
<mrow>
<mi>D</mi>
<mo>/</mo>
<mi>A</mi>
</mrow>
</msub>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo><</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
Wherein：For period t dc bus total load；ηA/DFor the conversion efficiency of AC-to DC；ηD/AFor direct current to exchange
Conversion efficiency；
(c) dc bus total load constrains：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>P</mi>
<mrow>
<mi>P</mi>
<mi>V</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>C</mi>
<mo>-</mo>
<mi>l</mi>
<mi>o</mi>
<mi>a</mi>
<mi>c</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>S</mi>
<mo>.</mo>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>-</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>S</mi>
<mo>.</mo>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
Wherein：For period t DC load；WithFor i-th of battery energy storage period t charge power
With discharge power；
(d) interconnection constraint and purchase sale of electricity state constraint：
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>b</mi>
<mi>u</mi>
<mi>y</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>b</mi>
<mi>u</mi>
<mi>y</mi>
</mrow>
<mi>t</mi>
</msubsup>
<msubsup>
<mi>P</mi>
<mrow>
<mi>b</mi>
<mi>u</mi>
<mi>y</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
<mi>t</mi>
</msubsup>
<msubsup>
<mi>P</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>b</mi>
<mi>u</mi>
<mi>y</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<mn>1</mn>
</mrow>
Wherein：WithRespectively to power network power purchase and the upper limit of the power of sale of electricity；WithRespectively period t is in purchase
Electricity and the 0-1 state variables of sale of electricity,1 expression power purchase is taken,1 expression sale of electricity is taken, sale of electricity can not be purchased simultaneously by also defining.
7. a kind of shop equipment based on micro-capacitance sensor according to claim 6 tends to the method for optimization automatically, it is characterized in that,
The constraints of the heating power balance constraint is as follows：
<mrow>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>W</mi>
<mi>H</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>G</mi>
<mi>B</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>P</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>c</mi>
<mi>o</mi>
<mi>n</mi>
<mi>d</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>S</mi>
<mo>.</mo>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>-</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>S</mi>
<mo>.</mo>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&GreaterEqual;</mo>
<msubsup>
<mi>H</mi>
<mrow>
<mi>s</mi>
<mi>p</mi>
<mi>a</mi>
<mi>c</mi>
<mi>e</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>H</mi>
<mrow>
<mi>w</mi>
<mi>a</mi>
<mi>t</mi>
<mi>e</mi>
<mi>r</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
<mrow>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>W</mi>
<mi>H</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>G</mi>
<mi>B</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>P</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>S</mi>
<mo>.</mo>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>-</mo>
<munder>
<mi>&Sigma;</mi>
<mi>i</mi>
</munder>
<msubsup>
<mi>H</mi>
<mrow>
<mi>H</mi>
<mi>S</mi>
<mo>.</mo>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&GreaterEqual;</mo>
<msubsup>
<mi>H</mi>
<mrow>
<mi>w</mi>
<mi>a</mi>
<mi>t</mi>
<mi>e</mi>
<mi>r</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
Wherein：For the thermal power of gas-turbine waste heat boiler output；Exported for i-th of gas fired-boiler in period t
Thermal power；For thermal power of i-th of heat pump in period t；For hot merit of i-th of family air-conditioning in period t
Rate；WithFor i-th of regenerative apparatus period t accumulation of heat power and heating power；WithRespectively
The space thermic load of shop equipment and hot water load.
8. a kind of shop equipment based on micro-capacitance sensor according to claim 6 tends to the method for optimization automatically, it is characterized in that,
The constraints of the cold power-balance constraint is as follows：
<mrow>
<munder>
<mo>&Sigma;</mo>
<mi>i</mi>
</munder>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mi>H</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mo>&Sigma;</mo>
<mi>i</mi>
</munder>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>c</mi>
<mi>o</mi>
<mi>n</mi>
<mi>d</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<munder>
<mo>&Sigma;</mo>
<mi>i</mi>
</munder>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>i</mi>
<mi>c</mi>
<mi>e</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&GreaterEqual;</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>l</mi>
<mi>o</mi>
<mi>a</mi>
<mi>d</mi>
</mrow>
<mi>t</mi>
</msubsup>
</mrow>
Wherein：The cooling power for being i-th of Absorption Refrigerator in period t；For i-th of family air-conditioning when
Refrigeration work consumption in section t；For the refrigeration work consumption of i-th of ice-chilling air conditioning system of period t；For refrigeration duty.
9. a kind of shop equipment based on micro-capacitance sensor according to claim 1 tends to the method for optimization automatically, it is characterized in that,
The constraints of the equipment operation constraint is as follows：
<mrow>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>n</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>min</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>n</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>n</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
<mrow>
<msubsup>
<mi>w</mi>
<mrow>
<mi>o</mi>
<mi>u</mi>
<mi>t</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>min</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>o</mi>
<mi>u</mi>
<mi>t</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>o</mi>
<mi>u</mi>
<mi>t</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
Wherein：WithInput-output powers of the equipment i in period t is represented respectively；WithEquipment i is represented respectively
In period t power output bound；WithRepresent equipment i in period t input power bound respectively.
10. a kind of shop equipment based on micro-capacitance sensor according to claim 1 tends to the method for optimization, its feature automatically
It is that the energy storage device constraint needs to meet energy storage state constraint and charge and discharge energy power constraint, in order to ensure the continuity of scheduling,
Before and after dispatching cycle, the energy storage capacity of energy storage device should be consistent；The constraints of the energy storage device constraint is as follows：
<mrow>
<msubsup>
<mi>S</mi>
<mi>i</mi>
<mi>min</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>S</mi>
<mi>i</mi>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>S</mi>
<mi>i</mi>
<mi>max</mi>
</msubsup>
</mrow>
SL.i=ST.i
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<msubsup>
<mi>w</mi>
<mrow>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<msubsup>
<mi>w</mi>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>max</mi>
</msubsup>
</mrow>
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&gamma;</mi>
<mrow>
<mi>r</mi>
<mo>.</mo>
<mi>i</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>&le;</mo>
<mn>1</mn>
</mrow>
Wherein：WithThe minimum and maximum storage volume of energy storage device is represented respectively；SL.iAnd ST.iFor the first of energy storage
Beginning capacity and the capacity at the end of dispatching cycle；WithThe maximum charge and discharge power of energy storage device are represented respectively；WithRepresent that energy storage device is in the 0-1 state variables for filling energy and exoergic in period t respectively,1 expression is taken to fill energy,Take 1
Represent exoergic, ensure equipment can not simultaneously charge and discharge energy.
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| CN110783917A (en) * | 2019-11-05 | 2020-02-11 | 国网江苏省电力有限公司镇江供电分公司 | Configuration method of multi-energy hub containing new energy consumption |
| CN110648031A (en) * | 2019-11-28 | 2020-01-03 | 广东电网有限责任公司 | Energy router optimal operation scheduling method based on reverse order dynamic programming |
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Address after: 310052 Room 1708, Hanshi Building, 1786 Binsheng Road, Changhe Street, Binjiang District, Hangzhou City, Zhejiang Province Applicant after: Wanke Energy Technology Co., Ltd. Address before: 310000 Room 1708, Hanshi Building, 1786 Binsheng Road, Changhe Street, Binjiang District, Hangzhou City, Zhejiang Province Applicant before: Zhejiang Wanke Amperex Technology Limited |
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Application publication date: 20180109 |