CN109066695A - Two-stage linearization electrical optimal energy flow calculation method - Google Patents
Two-stage linearization electrical optimal energy flow calculation method Download PDFInfo
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected 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
- 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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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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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Abstract
The invention discloses a two-stage linearization electrical optimal energy flow calculation method, which comprises the following steps: step 100, establishing an electric-gas optimal energy flow model; step 200, performing first-stage linear processing and solving an electric-gas optimal energy flow model; and 300, performing second-stage linearization processing and solving the electricity-gas optimal energy flow model, wherein the method gives consideration to the precision and the computational complexity of the electricity-gas optimal energy flow model on the premise of ensuring the safe operation of the electricity-gas interconnected comprehensive energy system, realizes the comprehensive utilization of energy between the electric power system and the natural gas system while minimizing the total operation cost of the electricity-gas interconnected comprehensive energy system, and solves the established electricity-gas optimal energy flow model by adopting a two-stage linearization method, and the result of the first-stage optimization model provides a high-quality linearization expansion point for the second-stage linearization, so that the linearization precision is ensured, the model accuracy and the computational complexity are balanced, and the method has high practical value.
Description
Technical field
The present embodiments relate to the electrical optimal energy streams of technical field of energy utilization more particularly to a kind of linearisation of two stages
Calculation method.
Background technique
With becoming increasingly conspicuous for environmental problem, the generating set using fossil energies such as fire coal, fuel oils as fuel is difficult to fit
Answer the demand of modern power systems cleaning, low-carbon.Compared with other non-renewable energy, gas economic environmental protection, rich reserves.Combustion gas
Power generation has outstanding advantages of efficient, low-carbon, fast response time.In recent years, jet dynamic control is greatly developed, installation
Capacity persistently rises, and electric system and the coupling of natural gas system are therefore further close, in this context, with electric system and day
The integrated energy system that right gas system interconnection is integrated, Mutually fusion is constituted becomes important carrier and the future of comprehensive utilization of energy
The development trend of energy resource system.How to cooperate with optimization electric system and natural gas system is that integrated energy system realization is provided multiple forms of energy to complement each other
Key, and electric-gas interconnection integrated energy system it is optimal can flow point analysis (hereinafter referred to as: electric-gas it is optimal can flow point analysis) be desirable
Consider most basic problem and such issues that Research foundation.
Currently, having carried out many researchs about the optimal energy flow point analysis of electric-gas.For power system modeling, partially grind
Study carefully and electric system is described using AC Ioad flow model, non-linear AC Ioad flow model brings huge challenge to optimization analysis.It is existing
There is most of research to model using tractable linear DC tide model, but DC flow model can not count and electric power network loss,
In fact, power consumption has great influence to optimum results and scheduling scheme, natural gas system is modeled, existing research exists
Mostly simplify the combustion gas loss even ignored and generated by compressor, mould is lost using the compressor of exact non-linear in a small amount of research
Type, it is nonlinear for leading to the Optimized model established, it is difficult to Efficient Solution.Therefore, electric system and natural how is considered comprehensively
The accuracy and computation complexity of gas system modelling are the key that optimal can flow of electric-gas efficiently calculates.
Summary of the invention
In order to overcome the shortcomings of that prior art, the present invention provide a kind of electrical optimal energy flux computation of two stages linearisation
Method takes into account the precision of the optimal energy flow model of electric-gas under the premise of guaranteeing electric-gas interconnection integrated energy system safe operation
And computation complexity realizes electric system and natural gas while minimizing electric-gas interconnection integrated energy system total operating cost
The comprehensive utilization of the energy between system can effectively solve the problem of background technique proposes.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of electrical optimal energy flux computation method of two stages linearisation, which comprises the steps of:
Step 100 establishes the optimal energy flow model of electric-gas；
Step 200 carries out first stage linearization process and solves the optimal energy flow model of electric-gas；
Step 300 carries out second stage linearization process and solves the optimal energy flow model of electric-gas.
Further, the step 100 includes:
Step 101 establishes Operation of Electric Systems constraint；
Step 102 establishes natural gas system operation constraint；
Step 103, Optimized model constraint condition establish the optimal energy flow model of electric-gas.
Further, in the step 101, specific operation constraint includes:
(1)、
(2)、
(3)、
(4)、-Pmax,ij≤Pij≤Pmax,ij；
(5)、
(6)、
Wherein, (1) is the constraint of electric system active balance；It (2) is the active equation of branch；It (3) is branch loss equation；
(4), (5) and (6) are respectively the bound constraint of branch power, conventional electric power generation unit and jet dynamic control；
(1) symbol description in-(6): PCON,i、PNGU,iAnd PL,iConventional electric generators respectively at electric system node i, combustion
The active power of gas generating set and load；Pij、Pij,loss、Pmax,ij、xij、gijAnd bijRespectively (head end i, the end branch i-j
J) active power, active loss, the upper limit of the power, reactance, conductance and susceptance on；Vi、Vj、θiAnd θjRespectively node i and j
Voltage magnitude and phase angle； WithThe conventional electric generators at node i, jet dynamic control go out respectively
The bound of power；ΩiIndicate the node set connecting with node i.
Further, in the step 102, specific operation constraint includes:
(7)
(8)
(9)FNGU,m=CNGU,m-iPNGU,i/GHV；
(10)
(11)
(12)
(13)
(14)
(15)
Wherein, (7) are the constraints of node air balance equation；It (8) is pipeline flow equation；It (9) is jet dynamic control mould
Type, for describing the relationship between jet dynamic control generated energy and air consumption；(10) be compressor consumption gas quantity；(11)
It (12) is respectively the step-up ratio of compressor and the traffic constraints for flowing through compressor；(13), (14) and (15) are respectively that gas source goes out
The bound of power, pipeline flow and node pressure constrains；
(7) symbol description in-(15): FS,m、FD,mAnd FNGU,mAt respectively natural gas system node m gas source power output,
The air consumption of gas load and jet dynamic control；PNGU,iAnd CNGU,m-iRespectively jet dynamic control generated energy (access power train
System node i) and jet dynamic control energy conversion factor；GHV is fixed high heating value；Fmn、And CmnRespectively pipeline m-n
(head end m, the throughput of end n), the maximum airflow of permission and pipeline constant；FC,k、τC,k、rC,k、βC,k、BC,kAnd ZC,kRespectively flow through the throughput and its upper limit value, compressor of compressor k
Air consumption, compressor step-up ratio, the upper offline value of step-up ratio, the pressure and compressor energy turn of suction port of compressor and outlet
Change coefficient and compressor constant；WithThe bound of gas source power output at respectively node m；WithRespectively
The pressure bound of node m；ΩmFor the node set being connect with node m；ΩC,mFor the compressor node collection being connect with node m
It closes.
Further, the step 103 specifically:
Optimization aim is to minimize electric-gas to interconnect integrated energy system total operating cost, the hair including conventional electric power generation unit
The purchase gas cost of electric cost and gas source, formula are as follows:
(16)
In formula: c1,i、c2,i、c3,iThe respectively consumption coefficient of conventional electric power generation unit i；cS,mFor the purchase gas price lattice of gas source m；
ΩCONAnd ΩSRespectively conventional electric power generation unit set and gas source set；
The constraint condition of Optimized model are as follows: Operation of Electric Systems constrains (1)-(6)；Natural gas system operation constraint (7)-
(15)。
Further, the step 200 specifically:
Linearization process is carried out to pipeline equation using Taylor series, ignores secondary or more item, obtains:
(17)
In formula: linearisation point (πm,0,πn,0) choose node pressure lower limit value；
The first stage linearisation optimal energy flow model of electric-gas is established, grid loss P is ignoredij,lossWith the gas consumption of compressor
Measure τC,k, it is as follows to establish the optimal energy flow model of lossless electric-gas:
(18)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6)；Natural gas system operation constraint (7), (9),
(11)-(15), (17)；
Solve the optimal energy flow model of electric-gas established in the above process.
Further, the step 300 specifically includes:
Step 301, the linearisation point for updating pipeline flow equation (17), obtain node pressure with first stage model solution
Substitution；
Step 302 linearizes grid loss equation (3) using Taylor series, ignores secondary or more item, obtains:
(19)
In formula: linearisation point (θi,0,θj,0) choose the node phase angle that first stage Optimized model solves；
Step 303 linearizes compressor air consumption equation (10) using Taylor series, ignores secondary or more item；
(20)
In formula: linearisation pointWhat selection first stage Optimized model solved flows through compressor
Flow value, outlet and inlet pressure；
Step 304 establishes the second stage linearisation optimal energy flow model of electric-gas, meter and the gentle network loss consumption of power grid, electric-gas
Optimal energy flow model, formula are as follows:
(21)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6), (19)；Natural gas system operation constraint (7),
(9), (11)-(15), (17), (20)；
Step 305 linearizes the optimal energy flow model of electric-gas using the second stage established in CPLEX solution procedure 304,
Export the solving result of Optimized model.
Compared with prior art, the beneficial effects of the present invention are:
The present invention takes into account that electric-gas is optimal to flow mould under the premise of guaranteeing electric-gas interconnection integrated energy system safe operation
The precision and computation complexity of type realize electric system while minimizing electric-gas interconnection integrated energy system total operating cost
The comprehensive utilization of the energy between natural gas system retains the easy to handle advantage of DC flow model in power system modeling level,
Meter and grid loss simultaneously model level in natural gas system, handle gas net nonlinear model using linearization technique, and guarantee
Linearization accuracy.To the optimal energy flow model of the electric-gas established, solved using two stages linearization technique, the first stage
The result of Optimized model provides the linearisation breaking up point of high quality for second stage linearisation, to guarantee the essence of linearisation
Degree.The two stages linearisation optimal energy flow model of electric-gas established is the Optimized model of full linear constraint, can efficiently be asked
Solution.The balanced model of mentioned method is accurate and computation complexity, has a very high practical value.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention without any creative labor, may be used also for those of ordinary skill in the art
To obtain other attached drawings according to these attached drawings.
Fig. 1 is workflow 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 embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, the present invention provides a kind of two stages to linearize electrical optimal energy flux computation method, including walk as follows
It is rapid:
Step 100 establishes the optimal energy flow model of electric-gas；
Step 200 carries out first stage linearization process and solves the optimal energy flow model of electric-gas；
Step 300 carries out second stage linearization process and solves the optimal energy flow model of electric-gas.
Specifically, the step 100 includes:
Step 101 establishes Operation of Electric Systems constraint；
Step 102 establishes natural gas system operation constraint；
Step 103, Optimized model constraint condition establish the optimal energy flow model of electric-gas.
Specifically, in the step 101, specific operation constraint includes:
(1)、
(2)、
(3)、
(4)、-Pmax,ij≤Pij≤Pmax,ij；
(5)、
(6)、
Wherein, (1) is the constraint of electric system active balance；It (2) is the active equation of branch；It (3) is branch loss equation；
(4), (5) and (6) are respectively the bound constraint of branch power, conventional electric power generation unit and jet dynamic control；
(1) symbol description in-(6): PCON,i、PNGU,iAnd PL,iConventional electric generators respectively at electric system node i, combustion
The active power of gas generating set and load；Pij、Pij,loss、Pmax,ij、xij、gijAnd bijRespectively (head end i, the end branch i-j
J) active power, active loss, the upper limit of the power, reactance, conductance and susceptance on；Vi、Vj、θiAnd θjRespectively node i and j
Voltage magnitude and phase angle； WithThe conventional electric generators at node i, jet dynamic control go out respectively
The bound of power；ΩiIndicate the node set connecting with node i.
Specifically, in the step 102, specific operation constraint includes:
(7)
(8)
(9)FNGU,m=CNGU,m-iPNGU,i/GHV；
(10)
(11)
(12)
(13)
(14)
(15)
Wherein, (7) are the constraints of node air balance equation；It (8) is pipeline flow equation；It (9) is jet dynamic control mould
Type, for describing the relationship between jet dynamic control generated energy and air consumption；(10) be compressor consumption gas quantity；(11)
It (12) is respectively the step-up ratio of compressor and the traffic constraints for flowing through compressor；(13), (14) and (15) are respectively that gas source goes out
The bound of power, pipeline flow and node pressure constrains；
(7) symbol description in-(15): FS,m、FD,mAnd FNGU,mAt respectively natural gas system node m gas source power output,
The air consumption of gas load and jet dynamic control；PNGU,iAnd CNGU,m-iRespectively jet dynamic control generated energy (access power train
System node i) and jet dynamic control energy conversion factor；GHV is fixed high heating value；Fmn、And CmnRespectively pipeline m-n
(head end m, the throughput of end n), the maximum airflow of permission and pipeline constant；FC,k、τC,k、rC,k、βC,k、BC,kAnd ZC,kRespectively flow through the throughput and its upper limit value, compressor of compressor k
Air consumption, compressor step-up ratio, the upper offline value of step-up ratio, the pressure and compressor energy turn of suction port of compressor and outlet
Change coefficient and compressor constant；WithThe bound of gas source power output at respectively node m；WithRespectively
The pressure bound of node m；ΩmFor the node set being connect with node m；ΩC,mFor the compressor node collection being connect with node m
It closes.
Specifically, the step 103 specifically:
Optimization aim is to minimize electric-gas to interconnect integrated energy system total operating cost, the hair including conventional electric power generation unit
The purchase gas cost of electric cost and gas source, formula are as follows:
(16)
In formula: c1,i、c2,i、c3,iThe respectively consumption coefficient of conventional electric power generation unit i；cS,mFor the purchase gas price lattice of gas source m；
ΩCONAnd ΩSRespectively conventional electric power generation unit set and gas source set；
The constraint condition of Optimized model are as follows: Operation of Electric Systems constrains (1)-(6)；Natural gas system operation constraint (7)-
(15)。
Specifically, the step 200 specifically:
Linearization process is carried out to pipeline equation using Taylor series, ignores secondary or more item, obtains:
(17)
In formula: linearisation point (πm,0,πn,0) choose node pressure lower limit value；
The first stage linearisation optimal energy flow model of electric-gas is established, grid loss P is ignoredij,lossWith the gas consumption of compressor
Measure τC,k, it is as follows to establish the optimal energy flow model of lossless electric-gas:
(18)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6)；Natural gas system operation constraint (7), (9),
(11)-(15), (17)；
Solve the optimal energy flow model of electric-gas established in the above process.
Specifically, the step 300 specifically includes:
Step 301, the linearisation point for updating pipeline flow equation (17), obtain node pressure with first stage model solution
Substitution；
Step 302 linearizes grid loss equation (3) using Taylor series, ignores secondary or more item, obtains:
(19)
In formula: linearisation point (θi,0,θj,0) choose the node phase angle that first stage Optimized model solves；
Step 303 linearizes compressor air consumption equation (10) using Taylor series, ignores secondary or more item；
(20)
In formula: linearisation pointWhat selection first stage Optimized model solved flows through compressor
Flow value, outlet and inlet pressure；
Step 304 establishes the second stage linearisation optimal energy flow model of electric-gas, meter and the gentle network loss consumption of power grid, electric-gas
Optimal energy flow model, formula are as follows:
(21)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6), (19)；Natural gas system operation constraint (7),
(9), (11)-(15), (17), (20)；
Step 305 linearizes the optimal energy flow model of electric-gas using the second stage established in CPLEX solution procedure 304,
Export the solving result of Optimized model.
The above, the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although referring to before
Stating embodiment, invention is explained in detail, those skilled in the art should understand that: it still can be to preceding
Technical solution documented by each embodiment is stated to modify or equivalent replacement of some of the technical features；And these
It modifies or replaces, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (7)
1. a kind of two stages linearize electrical optimal energy flux computation method, which comprises the steps of:
Step 100 establishes the optimal energy flow model of electric-gas；
Step 200 carries out first stage linearization process and solves the optimal energy flow model of electric-gas；
Step 300 carries out second stage linearization process and solves the optimal energy flow model of electric-gas.
2. a kind of two stages according to claim 1 linearize electrical optimal energy flux computation method, which is characterized in that described
Step 100 includes:
Step 101 establishes Operation of Electric Systems constraint；
Step 102 establishes natural gas system operation constraint；
Step 103, Optimized model constraint condition establish the optimal energy flow model of electric-gas.
3. a kind of two stages according to claim 2 linearize electrical optimal energy flux computation method, which is characterized in that described
In step 101, specific operation constraint includes:
(1)、
(2)、
(3)、
(4)、-Pmax,ij≤Pij≤Pmax,ij；
(5)、
(6)、
Wherein, (1) is the constraint of electric system active balance；It (2) is the active equation of branch；It (3) is branch loss equation；(4),
(5) and (6) be respectively branch power, conventional electric power generation unit and jet dynamic control bound constraint；
(1) symbol description in-(6): PCON,i、PNGU,iAnd PL,iConventional electric generators respectively at electric system node i, combustion gas hair
The active power of motor group and load；Pij、Pij,loss、Pmax,ij、xij、gijAnd bijRespectively branch i-j is (on head end i, end j)
Active power, active loss, the upper limit of the power, reactance, conductance and susceptance；Vi、Vj、θiAnd θjThe respectively voltage of node i and j
Amplitude and phase angle； WithThe conventional electric generators at node i, jet dynamic control are contributed respectively
Bound；ΩiIndicate the node set connecting with node i.
4. a kind of two stages according to claim 3 linearize electrical optimal energy flux computation method, which is characterized in that described
In step 102, specific operation constraint includes:
(7)
(8)
(9)FNGU,m=CNGU,m-iPNGU,i/GHV；
(10)
(11)
(12)
(13)
(14)
(15)
Wherein, (7) are the constraints of node air balance equation；It (8) is pipeline flow equation；(9) it is gas electricity generator group model, uses
To describe the relationship between jet dynamic control generated energy and air consumption；(10) be compressor consumption gas quantity；(11) and
It (12) is respectively the step-up ratio of compressor and the traffic constraints for flowing through compressor；(13), (14) and (15) be respectively gas source power output,
The constraint of the bound of pipeline flow and node pressure；
(7) symbol description in-(15): FS,m、FD,mAnd FNGU,mGas source power output at respectively natural gas system node m, gas load
With the air consumption of jet dynamic control；PNGU,iAnd CNGU,m-iRespectively jet dynamic control generated energy (access electric system node i)
With jet dynamic control energy conversion factor；GHV is fixed high heating value；Fmn、And CmnRespectively (head end m, the end pipeline m-n
N) maximum airflow and pipeline constant of throughput, permission；FC,k、τC,k、rC,k、
βC, k、BC,kAnd ZC,kRespectively flow through compressor k throughput and its upper limit value, the air consumption of compressor, compressor step-up ratio,
Upper offline value, the pressure and compressor energy conversion factor and compressor constant of suction port of compressor and outlet of step-up ratio；WithThe bound of gas source power output at respectively node m；WithThe respectively pressure bound of node m；
ΩmFor the node set being connect with node m；ΩC,mFor the compressor node set being connect with node m.
5. a kind of two stages according to claim 4 linearize electrical optimal energy flux computation method, which is characterized in that described
Step 103 specifically:
Optimization aim be minimize electric-gas interconnect integrated energy system total operating cost, the power generation including conventional electric power generation unit at
The purchase gas cost of this and gas source, formula are as follows:
(16)
In formula: c1,i、c2,i、c3,iThe respectively consumption coefficient of conventional electric power generation unit i；cS,mFor the purchase gas price lattice of gas source m；ΩCONWith
ΩSRespectively conventional electric power generation unit set and gas source set；
The constraint condition of Optimized model are as follows: Operation of Electric Systems constrains (1)-(6)；Natural gas system operation constraint (7)-(15).
6. a kind of two stages according to claim 4 linearize electrical optimal energy flux computation method, which is characterized in that described
Step 200 specifically:
Linearization process is carried out to pipeline equation using Taylor series, ignores secondary or more item, obtains:
(17)
In formula: linearisation point (πm,0,πn,0) choose node pressure lower limit value；
The first stage linearisation optimal energy flow model of electric-gas is established, grid loss P is ignoredij,lossWith the air consumption τ of compressorC,k,
It is as follows to establish the optimal energy flow model of lossless electric-gas:
(18)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6)；Natural gas system operation constraint (7), (9), (11)-
(15), (17)；
Solve the optimal energy flow model of electric-gas established in the above process.
7. a kind of two stages according to claim 6 linearize electrical optimal energy flux computation method, which is characterized in that described
Step 300 specifically includes:
Step 301, the linearisation point for updating pipeline flow equation (17), obtain node pressure with first stage model solution and replace
Generation；
Step 302 linearizes grid loss equation (3) using Taylor series, ignores secondary or more item, obtains:
(19)
In formula: linearisation point (θi,0,θj,0) choose the node phase angle that first stage Optimized model solves；
Step 303 linearizes compressor air consumption equation (10) using Taylor series, ignores secondary or more item；
(20)
In formula: linearisation pointChoose the stream for flowing through compressor that first stage Optimized model solves
Magnitude, outlet and inlet pressure；
Step 304 establishes the second stage linearisation optimal energy flow model of electric-gas, and meter and the gentle network loss consumption of power grid, electric-gas are optimal
Energy flow model, formula are as follows:
(21)
Constraint condition: Operation of Electric Systems constrains (1)-(2), (4)-(6), (19)；Natural gas system operation constraint (7), (9),
(11)-(15), (17), (20)；
Step 305 linearizes the optimal energy flow model of electric-gas, output using the second stage established in CPLEX solution procedure 304
The solving result of Optimized model.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109902854A (en) * | 2019-01-11 | 2019-06-18 | 重庆大学 | Electric-gas interacted system optimal load flow full linear model based on deep learning method |
| CN110377973A (en) * | 2019-06-28 | 2019-10-25 | 西安交通大学 | A kind of construction method of normal linearity integrated energy system model |
| CN113627021A (en) * | 2021-08-11 | 2021-11-09 | 东南大学 | Electrical interconnection system optimal energy flow calculation method based on sequence convex programming |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106096777A (en) * | 2016-06-12 | 2016-11-09 | 清华大学 | A kind of Optimization Scheduling of electrical couplings multipotency streaming system |
| CN106960282A (en) * | 2017-03-27 | 2017-07-18 | 武汉大学 | A kind of coordinated operation method of pneumoelectric comprehensive energy distribution network systems |
| CN107368927A (en) * | 2017-08-01 | 2017-11-21 | 重庆大学 | Electrical energy flow point cloth collaboration optimized calculation method based on target cascade analysis |
| CN107370170A (en) * | 2017-06-23 | 2017-11-21 | 浙江大学 | A kind of energy storage system capacity collocation method for considering capacity price of electricity and load prediction error |
| CN107947245A (en) * | 2017-11-20 | 2018-04-20 | 重庆大学 | Consider the equivalent optimal load flow model building method of natural gas system constraint |
-
2018
- 2018-09-29 CN CN201811150193.3A patent/CN109066695A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106096777A (en) * | 2016-06-12 | 2016-11-09 | 清华大学 | A kind of Optimization Scheduling of electrical couplings multipotency streaming system |
| CN106960282A (en) * | 2017-03-27 | 2017-07-18 | 武汉大学 | A kind of coordinated operation method of pneumoelectric comprehensive energy distribution network systems |
| CN107370170A (en) * | 2017-06-23 | 2017-11-21 | 浙江大学 | A kind of energy storage system capacity collocation method for considering capacity price of electricity and load prediction error |
| CN107368927A (en) * | 2017-08-01 | 2017-11-21 | 重庆大学 | Electrical energy flow point cloth collaboration optimized calculation method based on target cascade analysis |
| CN107947245A (en) * | 2017-11-20 | 2018-04-20 | 重庆大学 | Consider the equivalent optimal load flow model building method of natural gas system constraint |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109902854A (en) * | 2019-01-11 | 2019-06-18 | 重庆大学 | Electric-gas interacted system optimal load flow full linear model based on deep learning method |
| CN109902854B (en) * | 2019-01-11 | 2020-11-27 | 重庆大学 | Method for constructing optimal power flow full-linear model of electric-gas interconnection system |
| CN110377973A (en) * | 2019-06-28 | 2019-10-25 | 西安交通大学 | A kind of construction method of normal linearity integrated energy system model |
| CN110377973B (en) * | 2019-06-28 | 2021-08-13 | 西安交通大学 | Construction method of standard linear comprehensive energy system model |
| CN113627021A (en) * | 2021-08-11 | 2021-11-09 | 东南大学 | Electrical interconnection system optimal energy flow calculation method based on sequence convex programming |
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