CN109740899A - A kind of multi-user multi-stage optimization dispatching method considering active distribution network - Google Patents
A kind of multi-user multi-stage optimization dispatching method considering active distribution network Download PDFInfo
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Abstract
The invention discloses a kind of multi-user multi-stage optimization dispatching methods for considering active distribution network.Traditional cluster building Optimization Scheduling mainly considers that own characteristic optimizes, and Optimized Operation scheme has ignored the influence of active distribution network, limits the optimal of cluster building energy supply economy.The technical solution adopted by the present invention are as follows: consider the hot dynamic model of the building of multiple heating zones, active distribution network model in building active distribution network；And then the multi-user multi-stage optimization scheduling model for considering active distribution network safe operation constraint is constructed, the multi-user Optimized Operation scheme for meeting active distribution network safe operation constraint is obtained by solving.The present invention considers influence of the active distribution network safe operation constraint to multi-user Optimized Operation scheme, and more economical reliable energy supply scheduling scheme can be provided for multi-user.
Description
Technical field
The invention belongs to user side integrated energy system running optimizatin technical field more particularly to a kind of consideration active distribution
The multi-user multi-stage optimization dispatching method of net safe operation constraint.
Background technique
Distribution network in regional complex energy resource system (ICES) is most important to the optimization operation of whole system, can such as lead to
Cross the power supply capacity that network reconfiguration increases system；Using on-load regulator transformer (On-loadTapChanger, OLTC), simultaneously
Join compensation device, regulating system reactive power distribution simultaneously improves node voltage.In this respect, have numerous scholars and carried out and deeply grind
Study carefully, effectively improves the safety and economy of power distribution network operation.Cluster building are as active distribution network
One in (ActiveDistributionNetwork, ADN) it is main with can load, to its inside with can be carried out Optimized Operation
User be can effectively reduce with energy cost.However, the quick increasing of cluster building (such as summer cooling) power load under special screne
Length may touch the safe operation restrained boundary of active distribution network, how under the premise of ensureing active distribution network security constraint,
Cluster building system energy economy is promoted, is the difficulties of urgent need to resolve.
Domestic scholars and research institution have carried out certain exploration to the field: there is research to consider the thermal inertia of building building,
Carry out secondary distribution running Optimization.Have and has researched and proposed a kind of optimal mixed current calculating side ICES for considering power distribution network reconfiguration
Method improves the power supply capacity of distribution network, and reduce the operating cost of ICES by reconstructed network topology.There is research base
In cogeneration units (combinedheatandpower, CHP) hotspot stress tunable characteristic, a kind of ICES dual-layer optimization mould is proposed
Type reduces and uses energy cost, improves energy consumption efficiency.A kind of ICES layering energy management frame has been researched and proposed, has been realized
Optimized Operation and coordinated control to different energy sources system, energy link and demand response resource.ICES is researched and analysed
Middle source, net, lotus interaction coupled relation, and construct its be layered value models.
The studies above provides many methods for reference to the running optimizatin of ICES, but its mentioned method is isolated mostly
Relevance between cluster building and active distribution network, there are certain queries the reasonability of cluster building Optimized Operation scheme.
Especially in actual operation, influence of the active distribution network safe operation constraint to cluster building energization schemes, and actively match
The realization whether power grid regulating power facilitates cluster building optimal scheduling scheme, which is not yet received, to be fully considered.Traditional cluster building
Space Optimization Scheduling mainly considers that own characteristic optimizes, and Optimized Operation scheme has ignored the influence of active distribution network,
Limit the optimal of cluster building energy supply economy.
Summary of the invention
The technical problem to be solved by the present invention is to overcome the problems of the above-mentioned prior art, a kind of consideration active is provided
The multi-user multi-stage optimization dispatching method of power distribution network safe operation constraint considers active distribution network safe operation constraint pair
The influence of multi-user Optimized Operation scheme provides more economical reliable energy supply scheduling scheme for multi-user.
For this purpose, the present invention adopts the following technical scheme that: a kind of multi-user multi-stage optimization considering active distribution network
Dispatching method comprising:
The mathematical modulo of the hot dynamic model of the building of multiple heating zones, active distribution network is considered in building active distribution network
Type；Building considers the multi-user multi-stage optimization scheduling model of active distribution network safe operation constraint, is expired by solving
The multi-user Optimized Operation scheme of sufficient active distribution network safe operation constraint.
Supplement as above-mentioned technical proposal, the building process of the hot dynamic model of building for considering multiple heating zones
It is as follows:
Building region RC network model is made of thermal resistance R and thermal capacitance C, they are respectively provided with the energy of transmission heat with savings heat
Power；There are two types of type, wall body node and room air node, node is connected with each other node each by thermal resistance, and is connect through thermal capacitance
Ground；One heating/refrigerated area corresponds to one group of RC network model, and building model is then by the region clustering of multiple like configurations
It forms；For the sake of simplicity, it is consistent to assume construction for the heating zone in every building, therefore in control method of the same race and same light
According under parameter, the HVAC system power of each heating zone is consistent in building group, and based on this, passes through building HVAC system
System, adjustment equipment supply air temperature and air-supply mass flow, reach central controlled purpose；
The hot dynamic mathematical models of single heating zone are as follows:
In formula:For the wall heat capacity between node i and node j；For all nodes adjacent with the wall；TjFor
Temperature at node j；Wall temperature between node i and j；Thermal resistance between node i and j；ri,jIn this wall
0 is taken in not sunkissed situation, otherwise takes 1；αi,jWithWall heat absorption rate respectively between node i and node j and
Surface area；The intensity of illumination of direction is corresponded to for the wall；
In formula:For i-th of heating zone thermal capacitance；For room temperature to be asked；For all sections adjacent with No. i-th room
Point；For i-th of heating zone air-supply quality flow；cpFor room air specific heat capacity；For indoor supply air temperature；πi,j?
0 is taken in the case that this room is windowless, otherwise takes 1；For window transmissivity；Room window surface product thus；With
Respectively the forms correspond to the intensity of illumination of direction and the inner heat source in the room；For the thermal resistance of i-th of heating zone forms；
Formula (1) is considered as the equality constraint of wall between i and j node, and formula (2) is considered as the hot Dynamic Equation constraint in No. i-th room,
Two formulas are further changed to following state equation:
In formula: g (x, u) and d (t) is the non-linear partial of i-th of heating zone state equation；X is i-th of heating zone
State variable refers to each node temperature in network；U is the control variable of system, refers to air-supply mass flow and supply air temperature；
D (t) and y is respectively system disturbance amount and output quantity；By taking certain heating zone as an example, system state variables are shown in control variable
Formula (4) and (5):
The matrix B of matrix A and determining system output quantity is shown in formula (6) and (7)
B=[1 000 0] (7)
In formula, CrFor heating zone equivalence thermal capacitance；
Non-linear partial g (x, u) and disturbance term d (t) in system are shown in formula (8) and (9):
In formula, x1It indicates the state variable of i-th of heating zone, refers to heating zone room temperature；
Subsequently, based on the single heating zone mathematical model of above-mentioned (1)~(9), obtained by polymerization containing multiple systems
The hot dynamic model of the entire building of thermal region is shown in formula (10):
In formula: b is the number of heating zone in building, b={ 1,2 ... L }.
Supplement as above-mentioned technical proposal carries out the thermic load of heating zones all in building according to formula (10) tired
Add, to obtain the hot dynamic load of entire building；The power consumption models for then obtaining building HVAC are as follows:
HVAC system always consumes energy in building is defined as:
In formula:For t moment HVAC system electric power consumption, calculation method is as follows:
In formula:For the heating system electric power consumption in t moment building HVAC system；For t moment supply air system electricity
Power consumption, calculation method are shown in formula (13)~(14):
In formula:For the air-supply mass flow in t moment HVAC system；For t moment HVAC system heating when blow
Temperature；For the actual temperature of the t moment in the heating zone i；cp,airFor air specific heat capacity；COP is Energy Efficiency Ratio；ηfan、
ηmotorBlower, coefficient of electrical machinery respectively in blowing device；ΔPtotFor the pressure difference in blowing device, calculation formula is as follows:
In formula: PstaticFor static pressure difference；ρ is atmospheric density；V is wind speed；
Building total energy consumption is defined as:
In formula: PBtFor t moment building power, calculation method is as follows:
In formula: PotFor the use power of other electrical equipments in t moment resident's building.
The mathematical model building process of supplement as above-mentioned technical proposal, the active distribution network is as follows:
1) the Branch Power Flow model without OLTC
In the single line topological structure of radial power grid, VmAnd VnThe respectively complex voltage of node m and n；ImnFor route
The electric current of mn；rmn+jxmnFor the impedance of route mn；Pmn+jQmnApparent energy for route mn in the side node m；Pin,nAnd Qin,nPoint
Not Wei node n injection active power and reactive power；Active power relevant to the route, reactive power and current amplitude table
It is shown as:
In formula: vmAnd lmnRespectively square of the quadratic sum route mn current amplitude of node m voltage magnitude；K:n → k is indicated
The child node of node n；vnIndicate square of node n voltage magnitude；PnkIndicate the injection active power of node k；QnkIndicate node k
Injection reactive power；
2) the Branch Power Flow model containing OLTC
In topological structure comprising OLTC branch, the adjustable no-load voltage ratio k of OLTC in route mnmnModel it is as follows:
kmn=k0+KmnΔkmn (22)
In formula: k0With Δ kmnOLTC standard no-load voltage ratio and adjusting step-length in respectively branch mn；Kmn、WithRespectively
The gear of OLTC and its adjustable upper and lower limit in branch mn；Dummy node t is introduced, route mt modeling is as follows:
Ptn=Pmt-lmtrmt (26)
Qtn=Qmt-lmtxmt (27)
In formula: PmtWith QmtThe active and reactive power of respectively node m to dummy node t；PtnWith QtnRespectively virtual section
The active and reactive power of point t to node n；rmt+jxmtIt is mono- on high-tension side OLTC for conversion in route mt impedance and the route
The sum of bit length impedance, wherein rmtFor resistance, xmtFor reactance；lmtFor node m to the length of dummy node t；
Dummy node t is introduced, route tn modeling is as follows:
In formula: vtIndicate square of node t voltage magnitude；ltnFor node n to the length of dummy node t；PtnWith QtnRespectively
For the active and reactive power of dummy node t to node n.
Supplement as above-mentioned technical proposal considers the multi-user multi-stage optimization of active distribution network safe operation constraint
The building process of scheduling model is as follows:
Consider the control strategy of following four kinds of HVAC:
1. only controlling the air-supply mass flow in HVAC HVAC systemAbbreviation M control；
2. only controlling the supply air temperature in HVAC HVAC systemAbbreviation T control；
3. jointly controlling the mass flow in HVAC HVAC systemWith supply air temperatureAbbreviation C control；
4., by introducing multi-user load coefficient item, realizing load coefficient control, abbreviation B2G control on the basis of C control
System；
Stage 1: scheme optimization stage
1) objective function
Under different HVAC control modes, while considering the acceptable temperature regulating range of user in building, building intelligence
Housing economy Optimal Operation Model；The main target of multi-user economic optimization scheduling is to guarantee user temperature comfort level
On the basis of, minimize multi-user HVAC system operating cost；Therefore its objective function consists of two parts: first is that it is economical at
This；Second is that user's bring due to Thermal comfort is not satisfied punishes that wherein economic cost refers to multi-user HVAC system
Electric cost；Therefore, the objective function of M control, T control and the economic optimization scheduling model under C control are as follows:
In formula: first item is multi-user HVAC system electric cost,For each period HVAC system electricity consumption；
ΩTFor this area's Spot Price；Section 2 is the penalty function item for influencing user temperature comfort level and setting,Withε tIt is slack variable,
It respectively indicates heating zone and violates the ability that user sets comfort level upper and lower limit, it is feasible with ensure to optimize to add slack variable
Property；κ is penalty factor, is selected according to different user's sensibility, and penalty factor is considered as user to the sensitive journey of temperature pleasant degree
Degree, i.e. user's sensitivity coefficient, unit be 0.1 $/DEG C；
Multi-user Optimized Operation objective function under B2G control introduces building on the basis of tri- kinds of control modes of T, M, C
Space cluster load coefficient item, expression formula are shown in formula (33), and same up-to-date style (33) passes through normalized, denominator λ and μ respectively with its
The mathematic(al) representation of molecule is identical, and the constant value to acquire under C control；α and β respectively indicates building side weight coefficient and network
Side weight coefficient.
2) constraint condition
In intelligent building economic optimization scheduling model in the first stage, constraint condition consists of two parts: first is that being based on
Two kinds of equation of heat balances of wall and room air under building difference heating zone construct Indoor Temperature from the angle of the conservation of energy
Degree and the equality constraint between heats power and external environment parameters；Second is that HVAC system control parameter and resident set in building
Determine the inequality constraints of temperature pleasant degree；
Stage 2: scheme checking stage
1) objective function
If the multi-user Optimized Operation scheme that the stage 1 obtains meets active distribution network safe operation constraint, export most
Whole multi-user Optimized Operation scheme；It, will be minimum with OLTC action frequency if being unsatisfactory for active distribution network safe operation constraint
Optimization aim, by optimal control, so that multi-user Optimized Operation scheme meets active distribution network safe operation constraint, and defeated
Final scheduling scheme out；Therefore, the objective function in stage 2 is that OLTC action frequency is minimum in entire dispatching cycle:
2) constraint condition
The constraint condition in stage 2 consists of two parts: first is that conventional electrical distribution net system restriction；Second is that after system addition OLTC
The new constraint of construction.
Supplement as above-mentioned technical proposal is optimized excellent to the multi-user multistage based on MIXED INTEGER second order cone
Change scheduling model to be solved.
The device have the advantages that as follows: can be examined based on present invention cluster building energy supply scheduling scheme obtained
Safety and the regulating power for considering active distribution network, more reasonable scheduling scheme is provided for cluster building.
Detailed description of the invention
Fig. 1 is the equivalent RC network illustraton of model that the present invention considers multiple heating zones inside building；
Fig. 2 is the Branch Power Flow illustraton of model of the invention without OLTC；
Fig. 3 is the Branch Power Flow model of the invention containing OLTC；
Fig. 4 is intensity of illumination and outdoor temperature figure of the present invention；
Fig. 5 is building inner heat source of the present invention and electric load curve graph；
Fig. 6 is cluster power purchase price graph in building of the present invention；
Fig. 7 is active distribution network (ADN) example schematic diagram of integrated intelligent building in the present invention；
Fig. 8 is 32 total load figure of active distribution network (ADN) node under four kinds of control modes in the present invention；
Fig. 9 is the OLTC gear variation diagram of the lower four kinds of control modes of medium to high permeable rate of the present invention；
Figure 10 is the OLTC gear variation diagram of the lower four kinds of control modes of middle-low permeability of the present invention；
Figure 11 is that (Figure 11 a is 8 voltage of node point for not considering OLTC network-control to 8 voltage distribution graph of interior joint of the present invention
Butut, Figure 11 b are 8 voltage distribution graph of node for considering OLTC network-control)；
Figure 12 is application technology frame diagram of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
Embodiment
The technical solution used in the present invention are as follows: the building heat dynamic of multiple heating zones is considered in building active distribution network
Model, active distribution network model；And then construct the multi-user multi-stage optimization tune for considering active distribution network safe operation constraint
Model is spent, obtains the multi-user Optimized Operation scheme for meeting active distribution network safe operation constraint by solving.The present invention examines
Influence of the active distribution network safe operation constraint to multi-user Optimized Operation scheme is considered, can provide for multi-user and more pass through
The reliable energy supply scheduling scheme of Ji.
Step 1 establishes the hot dynamic model of building for considering multiple heating zones
Fig. 1 describes the equivalent RC network model for considering multiple heating zones inside building, as shown in Figure 1: building region
RC network model is made of thermal resistance (R) and thermal capacitance (C), they are respectively provided with the ability of transmission heat with savings heat.There are two types of nodes
Type, wall body node and room air node.Node is connected with each other each by thermal resistance, and is grounded through thermal capacitance.One heating/system
Cold-zone domain corresponds to one group of RC network model, and building model is formed by the region clustering of multiple like configurations.Simply to rise
See, it is consistent that construction is assumed in the heating zone in every building, therefore under control method of the same race and identical illumination parameter, building
The Heating of each heating zone in group, Ventilation and Air Conditioning (HVAC) system power is one
It causes.And based on this, by building HVAC system, adjustment equipment supply air temperature and air-supply mass flow, reach concentration control
The purpose of system.
The hot dynamic mathematical models of single heating zone are as follows:
In formula:For the wall heat capacity between node i and node j；For all nodes adjacent with the wall；TjFor
Temperature at node j；Wall temperature between node i and j；Thermal resistance between node i and j；ri,jIn this wall
0 is taken in not sunkissed situation, otherwise takes 1；αi,jWithWall heat absorption rate respectively between node i and node j and
Surface area；The intensity of illumination of direction is corresponded to for the wall.
In formula:For i-th of heating zone thermal capacitance；Ti rFor room temperature to be asked；For all sections adjacent with No. i-th room
Point；For i-th of heating zone air-supply quality flow；cpFor room air specific heat capacity；For indoor supply air temperature；πi,j?
0 is taken in the case that this room is windowless, otherwise takes 1；For window transmissivity；Room window surface product thus；With
Respectively the forms correspond to the intensity of illumination of direction and the inner heat source in the room；For the thermal resistance of i-th of heating zone forms.
Formula (1) can be considered that the equality constraint of wall between i and j node, formula (2) can be considered the hot Dynamic Equation in No. i-th room
Constraint, two formulas can further be changed to following state equation:
In formula: g (x, u) and d (t) is the non-linear partial of i-th of heating zone state equation；X is i-th of heating zone
State variable refers to each node temperature in network；U is the control variable of system, refers to air-supply mass flow and supply air temperature；
D (t) and y is respectively system disturbance amount and output quantity；By taking certain heating zone as an example, system state variables are shown in control variable
Formula (4) and (5):
The matrix B of matrix A and determining system output quantity is shown in formula (6) and (7)
B=[1 000 0] (7)
In formula, CrFor heating zone equivalence thermal capacitance.
Non-linear partial g (x, u) and disturbance term d (t) in system are shown in formula 8) and (9):
In formula, x1It indicates the state variable of i-th of heating zone, refers to heating zone room temperature.
It is available containing more by polymerization subsequently, based on the single heating zone mathematical model of above-mentioned (1)~(9)
The hot dynamic model of the entire building of a heating zone is shown in formula (10):
In formula: b (b={ 1,2 ... L }) is the number of heating zone in building.Can will be owned in building according to formula (10)
The thermic load of heating zone adds up, to obtain the hot dynamic load of entire building.The function of building HVAC then can be obtained
Rate consumption models are as follows:
HVAC system always consumes energy in building is defined as:
In formula:For t moment HVAC system electric power consumption, calculation method is as follows:
In formula:For the heating system electric power consumption in t moment building HVAC system；For t moment supply air system electricity
Power consumption.Its calculation method is shown in formula (13)~(14):
In formula:For the air-supply mass flow in t moment HVAC system；For t moment HVAC system heating when blow
Temperature；For the actual temperature of the t moment in the heating zone i；cp,airFor air specific heat capacity；COP is Energy Efficiency Ratio；ηfan、
ηmotorBlower, coefficient of electrical machinery respectively in blowing device；ΔPtotFor the pressure difference in blowing device, calculation formula is as follows:
In formula: PstaticFor static pressure difference；ρ is atmospheric density；V is wind speed.
Building total energy consumption is defined as:
In formula:For t moment building power, calculation method is as follows:
In formula:For the use power of other electrical equipments such as light, household electrical appliance in t moment resident's building.
2) active distribution network system mathematic model
(1) the Branch Power Flow model without OLTC
The single line topological structure of radial power grid is shown in Fig. 2.
In Fig. 2: VmAnd VnThe respectively complex voltage of node m and n；ImnFor the electric current of route mn；rmn+jxmnFor route mn's
Impedance；Pmn+jQmnApparent energy for route mn in the side node m；Pin,nAnd Qin,nRespectively the injection active power of node n and
Reactive power.Active power relevant to the route, reactive power and current amplitude may be expressed as:
In formula: vmAnd lmnRespectively square of the quadratic sum route mn current amplitude of node m voltage magnitude；K:n → k is indicated
The child node of node n；vnIndicate square of node n voltage magnitude；PnkIndicate the injection active power of node k；QnkIndicate node k
Injection reactive power.
(2) the Branch Power Flow model containing OLTC
OLTC be Reactive-power control equipment important in power grid include OLTC branch topological structure be shown in Fig. 3.
K in Fig. 3mnFor the adjustable no-load voltage ratio of OLTC in route mn, model is as follows:
kmn=k0+KmnΔkmn (22)
In formula: k0With Δ kmnOLTC standard no-load voltage ratio and adjusting step-length in respectively branch mn；Kmn、WithRespectively
The gear of OLTC and its adjustable upper and lower limit in branch mn.Dummy node t is introduced, route mt can model as follows:
Ptn=Pmt-lmtrmt (26)
Qtn=Qmt-lmtxmt (27)
In formula: PmtWith QmtThe active and reactive power of respectively node m to dummy node t；PtnWith QtnRespectively virtual section
The active and reactive power of point t to node n；rmt+jxmtIt is mono- on high-tension side OLTC for conversion in route mt impedance and the route
The sum of bit length impedance, wherein rmtFor resistance, xmtFor reactance；lmtFor node m to the length of dummy node t.
Dummy node t is introduced, route tn can model as follows:
In formula: vtIndicate square of node t voltage magnitude；ltnFor node n to the length of dummy node t；PtnWith QtnRespectively
For the active and reactive power of dummy node t to node n.
3) it establishes and considers that the multi-user multi-stage optimization scheduling model of active distribution network safe operation constraint will consider such as
The control strategy of lower four kinds of HVAC:
1. only controlling the air-supply mass flow in HVAC HVAC systemAbbreviation M control；
2. only controlling the supply air temperature in HVAC HVAC systemAbbreviation T control；
3. jointly controlling the mass flow in HVAC HVAC systemWith supply air temperatureAbbreviation C control.
4., by introducing multi-user load coefficient item, realizing load coefficient control, abbreviation B2G on the basis of C control
(Building-to-Grid) it controls.
Stage 1: scheme optimization stage
(1) objective function
Under different HVAC control modes, while considering the acceptable temperature regulating range of user in building, building intelligence
Housing economy Optimal Operation Model.The main target of multi-user economic optimization scheduling is to guarantee user temperature comfort level
On the basis of, minimize multi-user HVAC system operating cost.Therefore its objective function consists of two parts: first is that it is economical at
This；Second is that user's bring due to Thermal comfort is not satisfied is punished.Wherein economic cost refers to multi-user HVAC system
Electric cost.Therefore, the objective function of M control, T control and the economic optimization scheduling model under C control are as follows:
In formula: first item is multi-user HVAC system electric cost,For each period HVAC system electricity consumption；
ΩTFor this area's Spot Price.Section 2 is the penalty function item for influencing user temperature comfort level and setting,Withε tIt is slack variable,
It respectively refers to that the ability that user sets comfort level upper and lower limit can be violated for heating zone, adds slack variable to ensure to optimize
Feasibility；κ is penalty factor, can be selected according to different user's sensibility.Penalty factor can be considered as to user to temperature pleasant
The sensitivity of degree, i.e. user's sensitivity coefficient, unit be 0.1 $/DEG C.
Multi-user Optimized Operation objective function under B2G control introduces on the basis of tri- kinds of control modes of T, M, C
Multi-user load coefficient item, expression formula are shown in formula (33).Same up-to-date style (33) passes through normalized, denominator λ and μ respectively with
The mathematic(al) representation of its molecule is identical, and the constant value to acquire under C control；α and β is respectively referred to for building side weight coefficient and net
Network side weight coefficient.
(2) constraint condition
In intelligent building economic optimization scheduling model in the first stage, constraint condition consists of two parts: first is that being based on
Two kinds of equation of heat balances of wall and room air under building difference heating zone construct Indoor Temperature from the angle of the conservation of energy
Degree and the equality constraint between heats power and external environment parameters；Second is that HVAC system control parameter and resident set in building
Determine the inequality constraints of temperature pleasant degree.
1. construction wall thermal balance constrains
By taking No. 1 heating zone as an example, formula (1) and (2) are expanded into formula (34) and (35).In view of building heat dissipate with
Temperature change category slow dynamics process, the building equation of heat balance that can further express the differential equation carry out differencing processing, with
Realize the simple and effective solution to Housing economy optimization problem.Thermal balance constraint is as follows:
2. heating zone thermal balance constrains
In addition to building thermal balance, also need consider various kinds of equipment itself constraint, including each plant capacity upper and lower limit constraint,
The comfort level deviation constraint that the rate of change of supply air temperature and air-supply mass flow, building resident can allow for.
3. mass flow of blowing and supply air temperature constrain
In formula: utRefer to this moment air-supply mass flow and supply air temperature；With δuFor the rate of change bound of u；
WithuFor the rate of change bound of u.
4. user's room temperature comfort level tolerance constrains
In formula:For heating zone temperature；WithTThe upper and lower limit of comfort temperature respectively in heating zone；Withε tFor
Slack variable respectively refers to violate the ability that user sets comfort level bound due to penalty factor for heating zone, excellent to ensure
The feasibility of change.
5. load coefficient constrains
In formula: LF refers to load coefficient；PavgAnd P∞Respectively the average load of system and peak value are negative whithin a period of time
Lotus.
Stage 2: scheme checking stage
(1) objective function
If the multi-user Optimized Operation scheme that the stage 1 obtains meets active distribution network safe operation constraint, export most
Whole multi-user Optimized Operation scheme；It, will be minimum with OLTC action frequency if being unsatisfactory for active distribution network safe operation constraint
Optimization aim, by optimal control, so that multi-user Optimized Operation scheme meets active distribution network safe operation constraint, and defeated
Final scheduling scheme out.Therefore, the objective function in stage 2 is that OLTC action frequency is minimum in entire dispatching cycle:
(2) constraint condition
The constraint condition in stage 2 consists of two parts: first is that conventional electrical distribution net system restriction；Second is that after system addition OLTC
The new constraint of construction.
1. distribution power flow constrains (branch without OLTC)
Formula (18)~(21) are shown in distribution power flow constraint.
2. operational safety constrains
Vmin≤Vi≤Vmax (40)
In formula: ViFor node voltage amplitude；For route ij electric current；Subscript m in and max respectively indicate minimum value and maximum
Value.
3. radial operation constraint
Nloop=Nbr-Ne-bus+1 (42)
In formula: NloopFor the quantity of looped network；NbrFor sum (including block switch and the contact of operable switch in power distribution network
Switch)；Ne-busFor power distribution network number of nodes.
4. the operation of the branch containing OLTC constrains
Formula (19)~(31) are shown in system operation constraint containing OLTC.
Above-mentioned Optimized model is solved based on the optimization of MIXED INTEGER second order cone.
Application examples
Consider that the economic optimization for carrying out one day is dispatched, discontinuity surface when 1min takes one, HVAC system control strategy
Time step is 15 minutes.Building construction is set as only civil construction, every layer of four heating zone, each long 8m, wide 8m, layer
High 3m, totally five layers；And multi-user is formed by 5 similar buildings, and use identical control method.Building relevant parameter is shown in Table
1, multi-user inside HVAC system relevant parameter is shown in Table 2.A certain typical day in northern China winter is chosen, intensity of solar radiation is bent
Line and outdoor temperature are shown in Fig. 4 in view of the angular relationship of direct sunlight direction and external window of building, part exterior window back sun and glass
The factors such as the shading coefficient of glass, it is 0.4 that approximation, which takes wall heat absorption coefficient α, and window transmissivityτ is 0.9.Building inner heat source fever master
The two parts that be generated heat by equipment and human body form.A certain typical case's day list building routine electricity consumption (without heating electricity consumption) curve and
Building inner heat source curve is shown in Fig. 5, and this is foundation, and considers the stochastic behaviour of residential electricity consumption, is distributed, is estimated by random normal
Calculate multi-user inner heat source and conventional electricity consumption situation.The multi-user power purchase price that this example uses is shown in Fig. 6.
1 architectural modulus information of table
| Parameter | Value |
| Wall heat resistance Rwall | 0.06K/W |
| The wall heat resistance R of side containing windowwall(win) | 0.08K/W |
| Window thermal resistance Rwin | 0.02K/W |
| Wall heat capacity Cwall | 7.9e+5J/k |
| The wall heat capacity C of side containing windowwall(win) | 2.6e+7J/k |
| Room thermal capacitance Cr | 2.5e+5J/k |
2 HVAC system parameter of table
The active distribution network test example situation of integrated intelligent building is as follows are as follows: in the base of 33 node standard distributed net systems
On plinth, control equipment of the OLTC as network side is added, is configured between 1,2 node, so that the voltage mark at node 2
It is worth and is adjusted in positive and negative 10% range；OLTC equipment has 32 taps, and each tap-c hange control amount is 0.00625p.u..
Building load is accessed into power distribution network, each heating zone is equipped with HVAC terminal control system to maintain in building
Users'comfort, every building has 20 heating zones and similar temperature requirements, and considers the stochastic behaviour of residential electricity consumption, adopts
The electric load data being distributed with random normal.In high permeability, connect respectively in active distribution network node 3,10,18,32
Enter 18,5,15,25 building；In the case where low-permeability, connect respectively in active distribution network node 3,10,18,32
Enter 8,5,12,10 building.Example signal is illustrated in Fig. 7.
Fig. 8 is described under high permeability scene, and the active distribution network of integrated intelligent building is in four kinds of control mode lower nodes
The change curve of 32 total loads.Therefrom as it can be seen that the total load of C control mode lower node 32 exists compared with T control, M control mode
Floor level is kept in whole day scheduling process, it is seen that the power consumption of HVAC is lower under the control mode；And B2G control mode
Under, it is higher that the total load of node 32 in night scheduling instance compares other control modes, to keep higher load coefficient water
It is flat.
Table 3 and Fig. 9 give the simulation result of high permeability next stage 2.If the Optimized Operation result of 1 multi-user of stage
It is unsatisfactory for active distribution network safe operation constraint, then calls the system optimizing control in stage 2, passes through the pressure regulation tap to OLTC
It is adjusted, so that security constraint is satisfied, specific calculated result is shown in Table 3 and Fig. 9.Table 3 the result shows that: four kinds of control modes
Under the obtained Optimized Operation scheme of multi-user of stage 1, the constraint of active distribution network voltage is not satisfied.For this reason, it may be necessary to adjust
With the OLTC control algolithm in stage 2, so that final scheme can satisfy security constraint.In addition, comparing other control modes, B2G
Obtained 1 scheduling scheme of stage is controlled due to introducing load coefficient, so that the quality of voltage of active distribution network and network loss situation
It is superior to other control programs.Fig. 9 the result shows that: compare other control modes, the obtained OLTC of stage 2 under B2G control
Pressure regulation action frequency is minimum, and gained network-controlled scheme is most economical.In whole day scheduling, it is only necessary to adjust OLTC 3 times
Reach the voltage constraint of 0.9p.u..Therefore, B2G control mode, can be from economy and safety due to considering load coefficient
Two dimensions guarantee the efficient operation of active distribution network.
3 high permeability next stage of table, 1 simulation result
Table 4 and Figure 10 give the simulation result of low-permeability next stage 2.Table 4 the result shows that: under four kinds of control modes
The Optimized Operation scheme for the multi-user that stage 1 obtains also is not satisfied the constraint of active distribution network voltage, but is better than high permeability
Situation.For this reason, it may be necessary to the OLTC control algolithm in stage 2 be called, so that scheme can satisfy security constraint.Compare other controlling parties
Formula, the multi-user Optimized Operation scheme in the stage 1 obtained under B2G control is due to introducing load coefficient, so that active distribution
The quality of voltage and network loss situation of net are superior to other control programs.Figure 10 the result shows that: compare other control modes, B2G control
The obtained OLTC pressure regulation action frequency of stage 2 under system is minimum, and gained network-controlled scheme is most economical.In whole day scheduling,
It only needs to adjust OLTC 2 times, that is, can reach the voltage constraint of 0.9p.u..Therefore, B2G control mode is more excellent, this point and height
Its situation of permeability is consistent.
4 low-permeability next stage of table, 2 simulation result
Voltage's distribiuting the result is shown in Figure 11 of the active distribution network electrical node 8 when considering and not considering OLTC control in the stage 2,
It is therefrom visible: not consider that the multi-user Optimized Operation scheme of OLTC control is unsatisfactory for the voltage constraint of active distribution network；And
Stage 2 by optimizing control to OLTC, improves the voltage's distribiuting of active distribution network, so that final scheduling scheme energy
Enough meet the operation constraint of active distribution network.
In conclusion the present invention proposes a kind of multi-user multi-stage optimization of consideration active distribution network safe operation constraint
Dispatching method, method application framework are as shown in figure 12.The building heat that multiple heating zones are considered in active distribution network is constructed first
Dynamic model, active distribution network model；And then it constructs and considers that the multi-user multistage of active distribution network safe operation constraint is excellent
Change scheduling model, obtains the multi-user Optimized Operation scheme for meeting active distribution network safe operation constraint by solving.This hair
The bright influence for considering active distribution network safe operation constraint to multi-user Optimized Operation scheme, can provide more for multi-user
Add the energy supply scheduling scheme of economic and reliable, conclusion is as follows:
1) the operation regulation of more cluster building is cooperateed with into consideration with active distribution network, better regulating effect can be obtained, made
User's operating cost it is lower, system safety in operation is higher.
2) HVAC is the participation main body of multi-user Optimized Operation, and the present invention carries out tetra- class control mode of M, T, C and B2G
It is found after comparison, B2G control strategy can take into account the safety of the economy and active distribution network system of building operation, gained control
Effect is more excellent.
Embodiments of the present invention above described embodiment only expresses, can not be therefore understands that for patent of invention range
Limitation, also not structure of the invention is made any form of restriction.It should be pointed out that for the common skill of this field
For art personnel, without departing from the inventive concept of the premise, several changes and improvements can also be made, these belong to this hair
Bright protection scope.
Claims (6)
1. a kind of multi-user multi-stage optimization dispatching method for considering active distribution network characterized by comprising
The mathematical model of the hot dynamic model of the building of multiple heating zones, active distribution network is considered in building active distribution network；Structure
The multi-user multi-stage optimization scheduling model for considering active distribution network safe operation constraint is built, is met actively by solving to obtain
The multi-user Optimized Operation scheme of power distribution network safe operation constraint.
2. multi-user multi-stage optimization dispatching method according to claim 1, which is characterized in that described to consider multiple systems
The building process of the hot dynamic model of the building of thermal region is as follows:
Building region RC network model is made of thermal resistance R and thermal capacitance C, they are respectively provided with the ability of transmission heat with savings heat；Section
There are two types of type, wall body node and room air node, node is connected with each other point each by thermal resistance, and is grounded through thermal capacitance；One
A heating/refrigerated area corresponds to one group of RC network model, and building model is formed by the region clustering of multiple like configurations；
For the sake of simplicity, the heating zone in every building assumes that construction is consistent, therefore in control method of the same race and same light according to ginseng
Under several, the HVAC system power of each heating zone is consistent in building group, and based on this, by building HVAC system, adjusts
Equipment supply air temperature and air-supply mass flow are saved, central controlled purpose is reached；
The hot dynamic mathematical models of single heating zone are as follows:
In formula:For the wall heat capacity between node i and node j；For all nodes adjacent with the wall；TjFor node j
The temperature at place；Wall temperature between node i and j；Thermal resistance between node i and j；ri,jIn this wall not by sun
Light takes 0 in the case where irradiating, and otherwise takes 1；αi,jWithWall heat absorption rate and surface area respectively between node i and node j；The intensity of illumination of direction is corresponded to for the wall；
In formula:For i-th of heating zone thermal capacitance；For room temperature to be asked；For all nodes adjacent with No. i-th room；For i-th of heating zone air-supply quality flow；cpFor room air specific heat capacity；For indoor supply air temperature；πi,jHerein
0 is taken in the case that room is windowless, otherwise takes 1；For window transmissivity；Room window surface product thus；WithPoint
Not Wei the forms correspond to the intensity of illumination of direction and the inner heat source in the room；For the thermal resistance of i-th of heating zone forms；
Formula (1) is considered as the equality constraint of wall between i and j node, and formula (2) is considered as the hot Dynamic Equation constraint in No. i-th room, two formulas
Further it is changed to following state equation:
In formula: g (x, u) and d (t) is the non-linear partial of i-th of heating zone state equation；X is i-th of heating zone state
Variable refers to each node temperature in network；U is the control variable of system, refers to air-supply mass flow and supply air temperature；d(t)
And y is respectively system disturbance amount and output quantity；By taking certain heating zone as an example, system state variables and control variable are shown in formula
(4) and (5):
The matrix B of matrix A and determining system output quantity is shown in formula (6) and (7)
B=[1 000 0] (7)
In formula, CrFor heating zone equivalence thermal capacitance；
Non-linear partial g (x, u) and disturbance term d (t) in system are shown in formula (8) and (9):
In formula, x1It indicates the state variable of i-th of heating zone, refers to heating zone room temperature；
Subsequently, based on the single heating zone mathematical model of above-mentioned (1)~(9), obtained by polymerization containing multiple heating areas
The hot dynamic model of the entire building in domain is shown in formula (10):
In formula: b is the number of heating zone in building, b={ 1,2 ... L }.
3. multi-user multi-stage optimization dispatching method according to claim 2, which is characterized in that according to formula (10) by building
The thermic load of all heating zones adds up in space, to obtain the hot dynamic load of entire building；Then obtain building
The power consumption models of HVAC are as follows:
HVAC system always consumes energy in building is defined as:
In formula:For t moment HVAC system electric power consumption, calculation method is as follows:
In formula:For the heating system electric power consumption in t moment building HVAC system；For t moment supply air system electrical power
Consumption, calculation method are shown in formula (13)~(14):
In formula:For the air-supply mass flow in t moment HVAC system；For t moment HVAC system heating when air-supply temperature
Degree；For the actual temperature of the t moment in the heating zone i；cp,airFor air specific heat capacity；COP is Energy Efficiency Ratio；ηfan、ηmotor
Blower, coefficient of electrical machinery respectively in blowing device；ΔPtotFor the pressure difference in blowing device, calculation formula is as follows:
In formula: PstaticFor static pressure difference；ρ is atmospheric density；V is wind speed；
Building total energy consumption is defined as:
In formula: PBtFor t moment building power, calculation method is as follows:
In formula: PotFor the use power of other electrical equipments in t moment resident's building.
4. multi-user multi-stage optimization dispatching method according to claim 3, which is characterized in that the active distribution network
Mathematical model building process it is as follows:
1) the Branch Power Flow model without OLTC
In the single line topological structure of radial power grid, VmAnd VnThe respectively complex voltage of node m and n；ImnFor the electricity of route mn
Stream；rmn+jxmnFor the impedance of route mn；Pmn+jQmnApparent energy for route mn in the side node m；Pin,nAnd Qin,nRespectively save
The injection active power and reactive power of point n；Active power relevant to the route, reactive power and current amplitude indicate are as follows:
In formula: vmAnd lmnRespectively square of the quadratic sum route mn current amplitude of node m voltage magnitude；K:n → k indicates node
The child node of n；vnIndicate square of node n voltage magnitude；PnkIndicate the injection active power of node k；QnkIndicate the note of node k
Enter reactive power；
2) the Branch Power Flow model containing OLTC
In topological structure comprising OLTC branch, the adjustable no-load voltage ratio k of OLTC in route mnmnModel it is as follows:
kmn=k0+KmnΔkmn (22)
In formula: k0With Δ kmnOLTC standard no-load voltage ratio and adjusting step-length in respectively branch mn；Kmn、WithRespectively branch
The gear of OLTC and its adjustable upper and lower limit in mn；Dummy node t is introduced, route mt modeling is as follows:
Ptn=Pmt-lmtrmt (26)
Qtn=Qmt-lmtxmt (27)
In formula: PmtWith QmtThe active and reactive power of respectively node m to dummy node t；PtnWith QtnRespectively dummy node t
To the active and reactive power of node n；rmt+jxmtIt is long on high-tension side OLTC unit with conversion on the route for route mt impedance
The sum of impedance is spent, wherein rmtFor resistance, xmtFor reactance；lmtFor node m to the length of dummy node t；
Dummy node t is introduced, route tn modeling is as follows:
In formula: vtIndicate square of node t voltage magnitude；ltnFor node n to the length of dummy node t；PtnWith QtnIt is respectively empty
The active and reactive power of quasi- node t to node n.
5. multi-user multi-stage optimization dispatching method according to claim 4, which is characterized in that consider active distribution network
The building process for being safely operated the multi-user multi-stage optimization scheduling model of constraint is as follows:
Consider the control strategy of following four kinds of HVAC:
1. only controlling the air-supply mass flow in HVAC HVAC systemAbbreviation M control；
2. only controlling the supply air temperature in HVAC HVAC systemAbbreviation T control；
3. jointly controlling the mass flow in HVAC HVAC systemWith supply air temperatureAbbreviation C control；
4., by introducing multi-user load coefficient item, realizing load coefficient control, abbreviation B2G control on the basis of C control；
Stage 1: scheme optimization stage
1) objective function
Under different HVAC control modes, while considering the acceptable temperature regulating range of user in building, constructs intelligent building
Economic optimization scheduling model；The main target of multi-user economic optimization scheduling is on the basis for guaranteeing user temperature comfort level
On, minimize multi-user HVAC system operating cost；Therefore its objective function consists of two parts: first is that economic cost；Two
Be user due to Thermal comfort is not satisfied bring punish, wherein economic cost refer to the electricity consumption of multi-user HVAC system at
This；Therefore, the objective function of M control, T control and the economic optimization scheduling model under C control are as follows:
In formula: first item is multi-user HVAC system electric cost,For each period HVAC system electricity consumption；ΩTFor
This area's Spot Price；Section 2 is the penalty function item for influencing user temperature comfort level and setting,Withε tIt is slack variable, respectively
It indicates that the ability that user sets comfort level upper and lower limit is violated in heating zone, adds slack variable to ensure the feasibility optimized；κ
It for penalty factor, is selected according to different user's sensibility, to the sensitivity of temperature pleasant degree, i.e., penalty factor is considered as user
User's sensitivity coefficient, unit be 0.1 $/DEG C；
Multi-user Optimized Operation objective function under B2G control introduces building collection on the basis of tri- kinds of control modes of T, M, C
Group's load coefficient item, expression formula is shown in formula (33), and same up-to-date style (33) passes through normalized, denominator λ and μ respectively with its molecule
Mathematic(al) representation it is identical, and be the constant value that acquires under C control；α and β respectively indicates building side weight coefficient and network side is weighed
Weight coefficient；
2) constraint condition
In intelligent building economic optimization scheduling model in the first stage, constraint condition consists of two parts: first is that being based on building
Two kinds of equation of heat balances of wall and room air under different heating zones, from the angle of the conservation of energy, construct room temperature with
Equality constraint between heats power and external environment parameters；Second is that HVAC system control parameter and resident set temperature in building
Spend the inequality constraints of comfort level；
Stage 2: scheme checking stage
1) objective function
If the multi-user Optimized Operation scheme that the stage 1 obtains meets active distribution network safe operation constraint, final building is exported
Space cluster Optimized Operation scheme；It, will be with the minimum optimization of OLTC action frequency if being unsatisfactory for active distribution network safe operation constraint
Target so that multi-user Optimized Operation scheme meets active distribution network safe operation constraint, and is exported most by optimal control
Whole scheduling scheme；Therefore, the objective function in stage 2 is that OLTC action frequency is minimum in entire dispatching cycle:
2) constraint condition
The constraint condition in stage 2 consists of two parts: first is that conventional electrical distribution net system restriction；Second is that being constructed after system addition OLTC
New constraint.
6. multi-user multi-stage optimization dispatching method according to claim 5, which is characterized in that be based on MIXED INTEGER two
Rank cone optimization solves the multi-user multi-stage optimization scheduling model.
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