CN114004646B - Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game - Google Patents
Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game Download PDFInfo
- Publication number
- CN114004646B CN114004646B CN202111279600.2A CN202111279600A CN114004646B CN 114004646 B CN114004646 B CN 114004646B CN 202111279600 A CN202111279600 A CN 202111279600A CN 114004646 B CN114004646 B CN 114004646B
- Authority
- CN
- China
- Prior art keywords
- power
- electric energy
- distribution network
- transaction
- price
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 230000005540 biological transmission Effects 0.000 claims abstract description 19
- 238000004364 calculation method Methods 0.000 claims abstract description 17
- 230000005611 electricity Effects 0.000 claims description 33
- 238000004146 energy storage Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 11
- 238000005206 flow analysis Methods 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 3
- 230000009467 reduction Effects 0.000 abstract description 5
- 238000004458 analytical method Methods 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 28
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000009966 trimming Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/405—Establishing or using transaction specific rules
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Strategic Management (AREA)
- Finance (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- Computer Security & Cryptography (AREA)
- Primary Health Care (AREA)
- Human Resources & Organizations (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a flexible power distribution network end-to-end electric energy transaction method based on non-cooperative game, which comprises the following steps: the method comprises the steps of forming a cost function of a period t on transaction power through trend analysis by taking the lowest electric energy cost and the smallest node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, and obtaining the output active power limit of an intelligent soft switch port; based on non-cooperative game, carrying out distributed market clearing calculation among all the interconnected distribution network areas, and determining clearing price and transaction active power of end-to-end electric energy transaction of the lower layer of each period on the premise of realizing privacy protection; taking power loss of the converter into consideration, acquiring actual transmission power of the intelligent soft switch in each power distribution network area; and the power distribution network areas are settled according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid are settled according to the actual transmission power and the electric energy price. The transaction method can improve the voltage distribution of each region, promote the running cost reduction of each region and consider privacy protection.
Description
Technical Field
The invention relates to the technical field of urban power grid planning and evaluation, in particular to a flexible power distribution network end-to-end electric energy trading method and device based on non-cooperative game.
Background
The operation of the distribution network is required to meet the requirement of diversified and customized electricity consumption of a user side, and the traditional distribution network is gradually developed from a traditional radial structure to a flexible interconnection structure with high flexibility and controllability under the support of flexible distribution equipment such as a multi-terminal multi-voltage-level intelligent soft point (SOP). Each power distribution network area interconnected through the multi-terminal intelligent soft switch has a plurality of energy interaction paths, supports accurate and controllable power transmission, and lays a physical foundation for peer-to-peer (P2P) electric energy transaction of the multi-area flexible interconnection power distribution network.
In the face of the end-to-end electric energy transaction requirement of the multi-region flexible interconnection power distribution network, how to realize fair and effective electric energy transaction among multi-benefit bodies and consider the influence of system operation constraint on the transaction are problems to be solved.
The key problem of end-to-end power trading is how to design a trading mechanism with the characteristics of protecting data privacy, information symmetry and fairness competition. The distributed market clearing algorithm can be used for realizing privacy protection and symmetric information of flexible interconnection power distribution network end-to-end electric energy transaction. And the non-cooperative game competition rule can be used for realizing fair and reasonable profit competition among all areas.
At present, research on multi-region flexible interconnection distribution networks at home and abroad mainly focuses on operation optimization strategy formulation of multi-terminal intelligent soft switches, and how to realize end-to-end electric energy transaction based on the intelligent soft switches needs to be further researched. Therefore, an end-to-end electric energy transaction method for promoting the reduction of the running cost of each region and considering privacy protection is required to meet the electric energy transaction requirement of the multi-region flexible interconnection distribution network.
Disclosure of Invention
The invention aims to provide a method and a device for end-to-end electric energy transaction of a flexible distribution network based on non-cooperative game aiming at the problems of fairness of transaction rules, data privacy protection and the like in electric energy transaction of the flexible interconnection distribution network.
The invention provides a flexible power distribution network end-to-end electric energy transaction method based on non-cooperative game, which comprises the following steps:
The method comprises the steps of taking the lowest electric energy cost and the smallest node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, forming a cost function of a period t relative to transaction power through power flow analysis, and obtaining the output active power limit of an intelligent soft switch port according to power flow constraint and safe operation constraint;
according to the cost function and the tide constraint of each interconnection distribution network area and the safe operation constraint, carrying out distributed market clearing calculation among each interconnection distribution network area based on non-cooperative game, and determining the clearing price and the transaction active power of the end-to-end electric energy transaction of the lower layer of each period under the premise of realizing privacy protection;
The intelligent energy storage soft switch calculates and obtains the actual transmission power of the intelligent soft switch in each power distribution network area according to the obtained lower end-to-end electric energy transaction result and the cost function and by considering the power loss of the converter;
And the power distribution network areas are settled according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid are settled according to the actual transmission power and the electric energy price.
Further, the cost function of the time period t formed by each interconnected power distribution network area with respect to the transaction power is as follows:
Where f k,t represents the cost function of the period t of region k, pi t is the determined price of the electric energy transaction between the regions in the underlying end-to-end electric energy transaction; The method comprises the steps of carrying out electric energy price of electric energy transaction for each power distribution network area and an upper power grid; /(I) Respectively buying and selling active power in end-to-end electric energy transaction in a time period t region k; /(I)Buying and selling active power to an upper power grid for a time period t region k respectively; f U,k,t is the time period t region k voltage offset cost function; Δt is the transaction period duration; /(I)Load power for node i; omega U is the loss-of-load cost conversion coefficient when the voltage is over-limit; v i,t is the square of the voltage at node i; /(I)The square of the rated voltage of node i.
Further, the tide constraint is as follows:
Vi,t-Vj,t＝2(RijPij,t+XijQij,t) (8)
In the method, in the process of the invention, Branch and node sets of the region k respectively; /(I)The node set of the access area k of the intelligent energy storage soft switch; p ji,t、Qji,t is the active power and the reactive power flowing through the branch ji in the period t respectively; p ik,t、Qik,t is the active power and the reactive power flowing through the branch ik in the period t respectively; p i,t、Qi,t is the net injected active power and reactive power of the time period t node i respectively; /(I)Active and reactive power output of the distributed power supply is respectively carried out at a time interval t and a node i; /(I)Active power is injected into the access node for the intelligent energy storage soft switch; /(I)Active and reactive loads of the time period t node i are respectively; r ij、Xij is the resistance and reactance of branch ij, respectively.
Further, the system safe operation constraint is as follows:
Wherein Ω T is a transaction period set of one transaction day; i ij,t is the square of the current value of the branch ij; The upper limit of the square value of the current of the branch ij; /(I) V i is the upper and lower limits of the square value of the voltage of the node i respectively;
wherein the active power balance constraint of each region k can be expressed as follows:
Each region only serves as a buyer or a seller to participate in the electric energy transaction in the end-to-end electric energy transaction market in the same time period, and corresponding constraint can be expressed as follows:
Wherein, beta k,t is a binary variable representing the market identity of the region k in the period t, and the region k is represented as a seller when 1 is taken; s SOP is the converter capacity of the intelligent energy storage soft switch.
Further, the distributed market clearing calculation method between the interconnected distribution network areas based on the non-cooperative game comprises the following steps:
a) Setting the iteration times h=1, and setting the initial end-to-end electric energy transaction market electricity selling price in each region k
B) Each area collects electricity selling prices of other areas, calculates whether the area is a buyer or a seller according to the highest electricity price, and best electricity purchasing powerOr electric power selling/>The calculation mode is as follows:
Where f s,t is the cost function of seller s and f b,t is the cost function of buyer b; The selling power and the purchasing power of the seller s and the buyer b are respectively;
c) For privacy protection requirements, the same auxiliary parameters M h are generated and shared among sellers, and each seller s generates auxiliary variables And transmitted to each buyer; each buyer b calculates its power demand amount assigned to each seller s according to the following formula:
ΩB∪ΩS＝ΩR (18)
Wherein Ω B is a buyer area set, Ω S is a seller area set, Ω R is a flexible interconnect power distribution network area set, Distributing the obtained electric energy requirement of the buyer b to the seller s;
d) Each seller calculates and updates the electricity selling price according to the following formula:
wherein sigma s,t is the electric energy price adjustment coefficient of the seller s;
e) Judging whether the electricity price of each seller meets the iteration convergence condition, terminating the iteration if the electricity price meets the iteration convergence condition, setting h=h+1 if the electricity price does not meet the iteration convergence condition, and repeating the steps b) -d), wherein the convergence condition is as follows:
wherein epsilon is the iterative convergence error of the selling price of the seller.
Flexible distribution network end-to-end electric energy transaction device based on non-cooperative game, the device includes as follows:
The system comprises a cost function, a power flow constraint and safe operation constraint acquisition module, a power flow analysis module and a power flow constraint and safe operation constraint acquisition module, wherein the cost function and the power flow constraint and safe operation constraint acquisition module are used for forming a cost function of a period t relative to transaction power through power flow analysis by taking the lowest electric energy cost and the minimum node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, and acquiring the output active power limit of an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for carrying out distributed market clearing calculation among the interconnected distribution network areas based on non-cooperative game according to the cost function, the trend constraint and the safe operation constraint of the interconnected distribution network areas, and determining the clearing price and the transaction active power of end-to-end electric energy transaction of the lower layer of each period on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for the intelligent energy storage soft switch to calculate and acquire the actual transmission power of the intelligent soft switch in each power distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function and by considering the power loss of the converter;
The electric energy settlement module is used for settling accounts among the power distribution network areas according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid settle accounts according to the actual transmission power and the electric energy price.
A computing device, comprising:
One or more processing units;
A storage unit for storing one or more programs,
Wherein the one or more programs, when executed by the one or more processing units, cause the one or more processing units to perform the flexible power distribution network end-to-end power trading method based on non-cooperative gaming as described above.
A computer readable storage medium having non-volatile program code executable by a processor, the computer program when executed by the processor implementing a flexible power distribution network end-to-end power trading method based on non-cooperative gaming as described above.
The invention has the advantages and positive effects that:
the end-to-end electric energy trading method of the flexible interconnection power distribution network is based on the realization of fair competition electric energy trading among areas in the flexible interconnection power distribution network, the power adjustment of the intelligent soft switch is taken as a trading subject, the voltage control requirement of each area is fully considered, the cost function of each area about trading power is built with the aim of minimum electric energy cost and voltage deviation, each area takes the highest trading profit per se as the aim, the end-to-end electric energy trading based on non-cooperative game is carried out according to the cost function, the data privacy protection and market clearing are realized by adopting a distributed algorithm, and the trading power fine adjustment is carried out by further considering the loss of the intelligent soft switch converter, so that the trading result meets the system operation constraint.
Drawings
FIG. 1 is a flow chart of a flexible power distribution network end-to-end power trading method based on non-cooperative gaming;
FIG. 2 is a schematic diagram of a flexible interconnection power distribution network of four-terminal intelligent soft switches in an exemplary area of Tianjin North Star;
FIG. 3 is a graph of photovoltaic, fan and load operation;
FIG. 4 is a top grid power price curve;
FIG. 5 is a voltage distribution of each distribution network area for two schemes;
FIG. 6 is a cost reduction for each zone in an end-to-end power transaction;
FIG. 7 is an end-to-end electrical energy trading active power for each zone after trading fine tuning;
Fig. 8 is an end-to-end trade price result.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention become more apparent, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of the invention. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention discloses a non-cooperative game-based flexible power distribution network end-to-end electric energy transaction method, which is shown in figure 1 and comprises the following steps:
According to the selected flexible interconnection power distribution system, system parameters and network topology connection relations of all power distribution network areas are input, intelligent soft switch access positions and relevant parameters are input, and the regulated power of the intelligent soft switch is used as an electric energy transaction object; inputting load and distributed power supply access position, capacity and parameters; inputting a daily operation curve of a load and a distributed power supply; setting a system operating voltage level and a branch current limit; selecting a reference voltage and a reference power value; electric energy transaction prices of all distribution network areas and upper power grid in all time periods t are input ; Setting the duration delta t of each transaction period in one operation day; load loss unit cost under input terminal voltage offset;
For this embodiment, the power distribution network including four-terminal intelligent soft switches in the Tianjin North Star exemplary area is shown in fig. 2, and the detailed parameters are shown in table 1 and table 2. The demonstration area forms a double-ring network structure comprising four feeder lines by taking a happy station 110kV transformer substation and a wind power park 110kV transformer substation as centers, four distribution network areas are flexibly interconnected through four-terminal intelligent soft switches, the voltage levels are all set to 10.5kV, and the total active power requirements and the total reactive power requirements of loads are 9.9880MW and 7.3350Mvar respectively.
To take into account the access impact of the high permeability distributed power supply, the distributed power supply access situation is shown in table 3. The distributed power supply power factor is set to 1.0. The distributed power output and load demand curves are shown in fig. 3. The capacity of each port converter of the four-terminal intelligent soft switch is set to be 3MVA, and the loss coefficient is set to be 0.01. The system reference power is set to 1MVA. The voltage safety operation range of the active power distribution network is 0.90p.u. to 1.10p.u..
In one trade day, the time duration Δt of each trade period is set to 1 hour, for a total of 24 trade periods. The electric energy price curve of the upper power grid in each period is shown in fig. 4. The voltage offset cost coefficient ω U calculated from the load loss cost is set to 0.011.
According to the provided system parameters, network topology, intelligent soft switch access positions, capacity, daily operation curves of loads and distributed power supplies of all power distribution network areas, and electric energy price and loss load unit cost parameters of an upper-level power grid, all interconnected power distribution network areas k take the lowest electric energy cost and the lowest node voltage offset as targets, a cost function f k,t of t time intervals relative to transaction power is formed through power flow analysis, and the output active power limit of an intelligent soft switch port is calculated according to power flow constraint, safe operation constraint and the like;
the cost function of the time period t formed by each interconnected power distribution network area with respect to the transaction power is:
Where f k,t represents the cost function of the period t of region k, pi t is the determined price of the electric energy transaction between the regions in the underlying end-to-end electric energy transaction; The method comprises the steps of carrying out electric energy price of electric energy transaction for each power distribution network area and an upper power grid; /(I) Respectively buying and selling active power in end-to-end electric energy transaction in a time period t region k; /(I)Buying and selling active power to an upper power grid for a time period t region k respectively; f U,k,t is the time period t region k voltage offset cost function; Δt is the transaction period duration; /(I)Load power for node i; omega U is the loss-of-load cost conversion coefficient when the voltage is over-limit; v i,t is the square of the voltage at node i; /(I)The square of the rated voltage of node i.
The tide constraint is as follows:
Vi,t-Vj,t＝2(RijPij,t+XijQij,t) (8)
In the method, in the process of the invention, Branch and node sets of the region k respectively; /(I)The node set of the access area k of the intelligent energy storage soft switch; p ji,t、Qji,t is the active power and the reactive power flowing through the branch ji in the period t respectively; p ik,t、Qik,t is the active power and the reactive power flowing through the branch ik in the period t respectively; p i,t、Qi,t is the net injected active power and reactive power of the time period t node i respectively; /(I)Active and reactive power output of the distributed power supply is respectively carried out at a time interval t and a node i; /(I)Active power is injected into the access node for the intelligent energy storage soft switch; /(I)Active and reactive loads of the time period t node i are respectively; r ij、Xij is the resistance and reactance of branch ij, respectively.
The system safe operation constraint is as follows:
Wherein Ω T is a transaction period set of one transaction day; i ij,t is the square of the current value of the branch ij; The upper limit of the square value of the current of the branch ij; /(I) V i is the upper and lower limits of the square value of the voltage of the node i respectively;
wherein the active power balance constraint of each region k can be expressed as follows:
Each region only serves as a buyer or a seller to participate in the electric energy transaction in the end-to-end electric energy transaction market in the same time period, and corresponding constraint can be expressed as follows:
Wherein, beta k,t is a binary variable representing the market identity of the region k in the period t, and the region k is represented as a seller when 1 is taken; s SOP is the converter capacity of the intelligent energy storage soft switch.
According to the obtained cost function of each distribution network area, carrying out distributed market clearing calculation based on non-cooperative game among areas, and determining the transaction price pi t of end-to-end electric energy transaction and the buying power of each area k in the period t on the premise of realizing privacy protectionOr sell power/>
The distributed market clearing calculation method based on the non-cooperative game can be described as follows:
a) Setting the iteration times h=1, and setting the initial end-to-end electric energy transaction market electricity selling price in each region k
B) Each area collects electricity selling prices of other areas, calculates whether the area is a buyer or a seller according to the highest electricity price, and best electricity purchasing powerOr electric power selling/>The calculation mode is as follows:
Where f s,t is the cost function of seller s and f b,t is the cost function of buyer b; the selling power and the purchasing power of the seller s and the buyer b are respectively.
C) For privacy protection requirements, the same auxiliary parameters M h are generated and shared among sellers, and each seller s generates auxiliary variablesAnd transmitted to each buyer. Each buyer b calculates its power demand amount assigned to each seller s according to the following formula:
ΩB∪ΩS＝ΩR (18)
Wherein Ω B is a buyer area set, Ω S is a seller area set, Ω R is a flexible interconnect power distribution network area set, The resulting power demand for buyer b is allocated to seller s.
D) Each seller calculates and updates the electricity selling price according to the following formula:
Wherein σ s,t is the power price adjustment coefficient of seller s.
E) Judging whether the electricity prices of all sellers meet iteration convergence conditions, terminating iteration if the electricity prices meet the iteration convergence conditions, setting h=h+1 if the electricity prices do not meet the iteration convergence conditions, and repeating the steps b) -d), wherein the convergence conditions are as follows:
wherein epsilon is the iterative convergence error of the selling price of the seller.
The intelligent soft switch calculates the actual transmission power of the intelligent soft switch in each power distribution network area according to the end-to-end electric energy transaction result and considering the power loss of the converter;
(1) The method for calculating the actual transmission power of the intelligent soft switch can be expressed as follows:
In the method, in the process of the invention, The method comprises the steps that an intelligent soft switch actual active power set value to be determined in transaction fine adjustment is set for a t-period region k; /(I)Active transaction power determined in an end-to-end electrical energy transaction for t-period region k; /(I)The power loss of the intelligent soft switch in the region k converter port is t time periods; a SOP is the loss coefficient of the intelligent soft switching converter.
And each zone is settled according to the transaction power and the clearing price, and each zone and the upper power grid are settled according to the actual transmission power and the electric energy price.
In order to verify the feasibility and effectiveness of the transaction method in the invention, in the embodiment, the following two scenarios are adopted for verification analysis:
scheme I: and each power distribution network area does not participate in electric energy transaction, so that the operation level and the cost of the power distribution network in the initial state are obtained.
Scheme II: each power distribution network region carries out end-to-end electric energy transaction of the multi-region flexible interconnection power distribution network through the intelligent soft switch, and active power transaction fine adjustment based on the intelligent soft switch is carried out after the transaction.
In scheme I, II, the daily operating costs for each zone are shown in Table 4. In both schemes, the voltage distribution of each distribution network area is shown in fig. 5. The cost reduction for each zone in the end-to-end power trade result for scenario II is shown in fig. 6, and the active power trade result for each zone after trimming in the end-to-end power trade is shown in fig. 7. In scenario II, the end-to-end power trade price is shown in fig. 8.
The computer hardware environment for executing the solving calculation is Intel (R) Core (TM) i5-5200U CPU, the main frequency is 2.20GHz, and the memory is 4GB; the software environment is the Windows 10 operating system.
Compared with the scheme I which does not participate in market transaction, the flexible interconnection power distribution network end-to-end electric energy transaction based on the non-cooperative game in the scheme II realizes effective reduction of running cost of each zone, improves voltage distribution of each zone, and guarantees cost privacy of market participants.
Compared with the two schemes, the end-to-end electric energy transaction method for the multi-region flexible interconnected distribution network based on the non-cooperative game can effectively improve the running economy of the system and improve the voltage distribution of the system.
Table 1 Tianjin North Star exemplary district distribution network calculation load access position and power
Table 2 Tianjin North Star exemplary regional power distribution network example line parameters
Table 3 distributed power access location and capacity
| Region(s) | Photovoltaic Capacity/MVA | Blower capacity/MVA |
| Wind 33 | 1.0 | - |
| Lang 17 | 1.0 | 2.0 |
| Wedding 64 | - | 2.0 |
| Wedding 51 | - | 2.0 |
Table 4 daily operating costs for each distribution network area
Flexible distribution network end-to-end electric energy transaction device based on non-cooperative game, the device includes as follows:
The system comprises a cost function, a power flow constraint and safe operation constraint acquisition module, a power flow analysis module and a power flow constraint and safe operation constraint acquisition module, wherein the cost function and the power flow constraint and safe operation constraint acquisition module are used for forming a cost function of a period t relative to transaction power through power flow analysis by taking the lowest electric energy cost and the minimum node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, and acquiring the output active power limit of an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for carrying out distributed market clearing calculation among the interconnected distribution network areas based on non-cooperative game according to the cost function, the trend constraint and the safe operation constraint of the interconnected distribution network areas, and determining the clearing price and the transaction active power of end-to-end electric energy transaction of the lower layer of each period on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for the intelligent energy storage soft switch to calculate and acquire the actual transmission power of the intelligent soft switch in each power distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function and by considering the power loss of the converter;
The electric energy settlement module is used for settling accounts among the power distribution network areas according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid settle accounts according to the actual transmission power and the electric energy price.
A computing device, comprising:
One or more processing units;
A storage unit for storing one or more programs,
Wherein, when the one or more programs are executed by the one or more processing units, the one or more processing units execute the flexible power distribution network end-to-end power trading method based on the non-cooperative game; it should be noted that the computing device may include, but is not limited to, a processing unit, a storage unit; those skilled in the art will appreciate that the inclusion of a processing unit, a storage unit, and a computing device is not limiting of computing devices, and may include additional components, or may combine certain components, or different components, e.g., a computing device may also include an input-output device, a network access device, a bus, etc.
A computer readable storage medium having non-volatile program code executable by a processor, the computer program when executed by the processor performing the steps of the flexible power distribution network end-to-end power trading method described above based on non-cooperative gaming; the readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing; the program embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. For example, program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, or entirely on a remote computing device or server. In the context of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., connected over the Internet using an Internet service provider).
Finally, it should be pointed out that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting. Although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. The flexible power distribution network end-to-end electric energy transaction method based on the non-cooperative game is characterized by comprising the following steps of:
The method comprises the steps of taking the lowest electric energy cost and the smallest node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, forming a cost function of a period t relative to transaction power through power flow analysis, and obtaining the output active power limit of an intelligent soft switch port according to power flow constraint and safe operation constraint;
according to the cost function and the tide constraint of each interconnection distribution network area and the safe operation constraint, carrying out distributed market clearing calculation among each interconnection distribution network area based on non-cooperative game, and determining the clearing price and the transaction active power of the end-to-end electric energy transaction of the lower layer of each period under the premise of realizing privacy protection;
according to the obtained end-to-end electric energy transaction result of the lower layer and the cost function, the power loss of the converter is considered, and the actual transmission power of the intelligent soft switch in each power distribution network area is calculated and obtained;
The power distribution network areas are settled according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid are settled according to the actual transmission power and the electric energy price;
the cost function of the time period t formed by each interconnected power distribution network area with respect to the transaction power is:
Where f k,t represents the cost function of the period t of region k, pi t is the determined price of the electric energy transaction between the regions in the underlying end-to-end electric energy transaction; The method comprises the steps of carrying out electric energy price of electric energy transaction for each power distribution network area and an upper power grid; /(I) Respectively buying and selling active power in end-to-end electric energy transaction in a time period t region k; /(I)Buying and selling active power to an upper power grid for a time period t region k respectively; f U,k,t is the time period t region k voltage offset cost function; Δt is the transaction period duration; /(I)Load power for node i; omega U is the loss-of-load cost conversion coefficient when the voltage is over-limit; v i,t is the square of the voltage at node i; /(I)Square the rated voltage of the node i;
The distributed market clearing calculation method for each interconnection distribution network area based on the non-cooperative game comprises the following steps:
a) Setting the iteration times h=1, and setting the initial end-to-end electric energy transaction market electricity selling price in each region k
B) Each area collects electricity selling prices of other areas, calculates whether the area is a buyer or a seller according to the highest electricity price, and best electricity purchasing powerOr electric power selling/>The calculation mode is as follows:
Where f s,t is the cost function of seller s and f b,t is the cost function of buyer b; The selling power and the purchasing power of the seller s and the buyer b are respectively;
c) For privacy protection requirements, the same auxiliary parameters M h are generated and shared among sellers, and each seller s generates auxiliary variables And transmitted to each buyer; each buyer b calculates its power demand amount assigned to each seller s according to the following formula:
ΩBUΩs＝ΩR (18)
Wherein Ω B is a buyer area set, Ω S is a seller area set, Ω R is a flexible interconnect power distribution network area set, Distributing the obtained electric energy requirement of the buyer b to the seller s;
d) Each seller calculates and updates the electricity selling price according to the following formula:
wherein sigma s,t is the electric energy price adjustment coefficient of the seller s;
e) Judging whether the electricity price of each seller meets the iteration convergence condition, terminating the iteration if the electricity price meets the iteration convergence condition, setting h=h+1 if the electricity price does not meet the iteration convergence condition, and repeating the steps b) -d), wherein the convergence condition is as follows:
wherein epsilon is the iterative convergence error of the selling price of the seller.
2. The non-cooperative game-based end-to-end electric energy transaction method for the flexible power distribution network according to claim 1, wherein the tide constraint is as follows:
Vi,t-Vj,t＝2(RijPij,t+XijQij,t) (8)
In the method, in the process of the invention, Branch and node sets of the region k respectively; /(I)The node set of the access area k of the intelligent energy storage soft switch; p ji,t、Qji,t is the active power and the reactive power flowing through the branch ji in the period t respectively; p ik,t、Qik,t is the active power and the reactive power flowing through the branch ik in the period t respectively; p i,t、Qi,t is the net injected active power and reactive power of the time period t node i respectively; active and reactive power output of the distributed power supply is respectively carried out at a time interval t and a node i; /(I) Active power is injected into the access node for the intelligent energy storage soft switch; /(I)Active and reactive loads of the time period t node i are respectively; r ij、Xij is the resistance and reactance of branch ij, respectively.
3. The end-to-end electric energy transaction method of the flexible power distribution network based on the non-cooperative game according to claim 2, wherein the system safe operation constraint is as follows:
Wherein Ω T is a transaction period set of one transaction day; i ij,t is the square of the current value of the branch ij; The upper limit of the square value of the current of the branch ij; /(I) V i is the upper and lower limits of the square value of the voltage of the node i respectively;
wherein the active power balance constraint of each region k can be expressed as follows:
Each region only serves as a buyer or a seller to participate in the electric energy transaction in the end-to-end electric energy transaction market in the same period, and corresponding constraint is expressed as:
Wherein, beta k,t is a binary variable representing the market identity of the region k in the period t, and the region k is represented as a seller when 1 is taken; s SOP is the converter capacity of the intelligent energy storage soft switch.
4. Flexible distribution network end-to-end electric energy transaction device based on non-cooperative game, which is characterized by comprising the following steps:
The system comprises a cost function, a power flow constraint and safe operation constraint acquisition module, a power flow analysis module and a power flow constraint and safe operation constraint acquisition module, wherein the cost function and the power flow constraint and safe operation constraint acquisition module are used for forming a cost function of a period t relative to transaction power through power flow analysis by taking the lowest electric energy cost and the minimum node voltage offset of each interconnected power distribution network area in a flexible interconnected power distribution system as targets, and acquiring the output active power limit of an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for carrying out distributed market clearing calculation among the interconnected distribution network areas based on non-cooperative game according to the cost function, the trend constraint and the safe operation constraint of the interconnected distribution network areas, and determining the clearing price and the transaction active power of end-to-end electric energy transaction of the lower layer of each period on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for the intelligent energy storage soft switch to calculate and acquire the actual transmission power of the intelligent soft switch in each power distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function and by considering the power loss of the converter;
The electric energy settlement module is used for settling accounts among the power distribution network areas according to the transaction power and the clearing price, and each area of the power distribution network and the upper power grid settle accounts according to the actual transmission power and the electric energy price;
the cost function of the time period t formed by each interconnected power distribution network area with respect to the transaction power is:
Where f k,t represents the cost function of the period t of region k, pi t is the determined price of the electric energy transaction between the regions in the underlying end-to-end electric energy transaction; The method comprises the steps of carrying out electric energy price of electric energy transaction for each power distribution network area and an upper power grid; /(I) Respectively buying and selling active power in end-to-end electric energy transaction in a time period t region k; /(I)Buying and selling active power to an upper power grid for a time period t region k respectively; f U,k,t is the time period t region k voltage offset cost function; Δt is the transaction period duration; /(I)Load power for node i; omega U is the loss-of-load cost conversion coefficient when the voltage is over-limit; v i,t is the square of the voltage at node i; /(I)Square the rated voltage of the node i;
The distributed market clearing calculation method for each interconnection distribution network area based on the non-cooperative game comprises the following steps:
a) Setting the iteration times h=1, and setting the initial end-to-end electric energy transaction market electricity selling price in each region k
B) Each area collects electricity selling prices of other areas, calculates whether the area is a buyer or a seller according to the highest electricity price, and best electricity purchasing powerOr electric power selling/>The calculation mode is as follows:
Where f s,t is the cost function of seller s and f b,t is the cost function of buyer b; The selling power and the purchasing power of the seller s and the buyer b are respectively;
c) For privacy protection requirements, the same auxiliary parameters M h are generated and shared among sellers, and each seller s generates auxiliary variables And transmitted to each buyer; each buyer b calculates its power demand amount assigned to each seller s according to the following formula:
ΩB∪ΩS＝ΩR (18)
Wherein Ω B is a buyer area set, Ω S is a seller area set, Ω R is a flexible interconnect power distribution network area set, Distributing the obtained electric energy requirement of the buyer b to the seller s;
d) Each seller calculates and updates the electricity selling price according to the following formula:
wherein sigma s,t is the electric energy price adjustment coefficient of the seller s;
e) Judging whether the electricity price of each seller meets the iteration convergence condition, terminating the iteration if the electricity price meets the iteration convergence condition, setting h=h+1 if the electricity price does not meet the iteration convergence condition, and repeating the steps b) -d), wherein the convergence condition is as follows:
wherein epsilon is the iterative convergence error of the selling price of the seller.
5. A computing device, characterized by: comprising the following steps:
One or more processing units;
A storage unit for storing one or more programs,
Wherein the one or more programs, when executed by the one or more processing units, cause the one or more processing units to perform the method of any of claims 1-3.
6. A computer readable storage medium having a processor executable non-volatile program code, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111279600.2A CN114004646B (en) | 2021-10-28 | 2021-10-28 | Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111279600.2A CN114004646B (en) | 2021-10-28 | 2021-10-28 | Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114004646A CN114004646A (en) | 2022-02-01 |
| CN114004646B true CN114004646B (en) | 2024-06-14 |
Family
ID=79925914
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111279600.2A Active CN114004646B (en) | 2021-10-28 | 2021-10-28 | Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114004646B (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008146105A (en) * | 2006-12-05 | 2008-06-26 | Toshiba Corp | System, method and program for evaluating power transaction |
| CN102915472B (en) * | 2012-10-30 | 2016-06-01 | 南京软核科技有限公司 | Based on the power distribution network synthesis optimization planning method of gene repair Chaos Genetic Algorithm |
| CN104578157B (en) * | 2015-01-04 | 2017-05-10 | 云南电网有限责任公司电力科学研究院 | Load flow calculation method of distributed power supply connection power grid |
| CN112150287B (en) * | 2020-09-29 | 2022-08-16 | 天津大学 | End-to-end electric energy transaction method for multi-region flexible interconnected power distribution network |
| CN112581309A (en) * | 2020-11-30 | 2021-03-30 | 江苏电力交易中心有限公司 | Block chain-based distributed energy transaction method and system for power distribution network |
-
2021
- 2021-10-28 CN CN202111279600.2A patent/CN114004646B/en active Active
Non-Patent Citations (2)
| Title |
|---|
| 芮涛.基于博弈论的配电侧多微电网***优化运行方法研究.全文. * |
| 黄顺杰.基于博弈论的智能配电网需求响应研究.全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114004646A (en) | 2022-02-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Asrari et al. | A market framework for decentralized congestion management in smart distribution grids considering collaboration among electric vehicle aggregators | |
| Zhang et al. | Bidding strategy analysis of virtual power plant considering demand response and uncertainty of renewable energy | |
| Astero et al. | Multi‐agent transactive energy management system considering high levels of renewable energy source and electric vehicles | |
| Qiu et al. | Distributed generation and energy storage system planning for a distribution system operator | |
| Moeini-Aghtaie et al. | Incorporating large-scale distant wind farms in probabilistic transmission expansion planning—Part I: Theory and algorithm | |
| Sahraei-Ardakani et al. | Transfer capability improvement through market-based operation of series FACTS devices | |
| Yi et al. | Coordinated operation strategy for a virtual power plant with multiple DER aggregators | |
| Ali et al. | A peer-to-peer energy trading for a clustered microgrid–Game theoretical approach | |
| Pantoš | Market-based congestion management in electric power systems with exploitation of aggregators | |
| Ali et al. | A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme | |
| Bedoya et al. | Bilateral electricity market in a distribution system environment | |
| Elmitwally et al. | Long‐term economic model for allocation of FACTS devices in restructured power systems integrating wind generation | |
| CN111864742B (en) | Active power distribution system extension planning method and device and terminal equipment | |
| JPH0833207A (en) | Reactive power planning method for power system | |
| Lin et al. | Blockchain-based intelligent charging station management system platform | |
| Su et al. | Reactive power compensation using electric vehicles considering drivers’ reasons | |
| Xu et al. | Deep reinforcement learning and blockchain for peer-to-peer energy trading among microgrids | |
| CN114006371B (en) | Flexible power distribution network electric energy transaction method and device for intelligent energy storage soft switch | |
| Yu et al. | Continuous group-wise double auction for prosumers in distribution-level markets | |
| Rajasekhar et al. | Heuristic approach for transactive energy management in active distribution systems | |
| CN114004646B (en) | Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game | |
| Liu et al. | Strategic bidding optimization of microgrids in electricity distribution market | |
| Yi et al. | Self‐adaptive hybrid algorithm based bi‐level approach for virtual power plant bidding in multiple retail markets | |
| Homaee et al. | Retail market policy for distribution systems in presence of DERs and microgrids: comparison of sequential and simultaneous settlement of energy and reactive power markets | |
| Liao et al. | Bi‐level optimization of multi‐regional power system considering low‐carbon oriented synergy of both source and load sides |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |