CN114004646A - 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
- CN114004646A CN114004646A CN202111279600.2A CN202111279600A CN114004646A CN 114004646 A CN114004646 A CN 114004646A CN 202111279600 A CN202111279600 A CN 202111279600A CN 114004646 A CN114004646 A CN 114004646A
- Authority
- CN
- China
- Prior art keywords
- power
- electric energy
- distribution network
- transaction
- power distribution
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000005540 biological transmission Effects 0.000 claims abstract description 19
- 238000004364 calculation method Methods 0.000 claims abstract description 15
- 230000009467 reduction Effects 0.000 claims abstract description 8
- 238000005206 flow analysis Methods 0.000 claims abstract description 7
- 230000005611 electricity Effects 0.000 claims description 26
- 238000004146 energy storage Methods 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 11
- 150000001875 compounds Chemical class 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 239000004576 sand Substances 0.000 claims description 3
- 230000006870 function Effects 0.000 description 26
- 239000000243 solution Substances 0.000 description 5
- 238000004422 calculation algorithm Methods 0.000 description 2
- 208000001613 Gambling Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007246 mechanism Effects 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
- 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
Images
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)
- Development Economics (AREA)
- Finance (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Computer Security & Cryptography (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Primary Health Care (AREA)
- Tourism & Hospitality (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 a non-cooperative game, which comprises the following steps: the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of all interconnected power distribution network areas in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limit output by an intelligent soft switch port is obtained; distributed market clearing calculation among all interconnected distribution network areas is carried out based on a non-cooperative game, and under the premise of realizing privacy protection, clearing price and transaction active power of lower-layer end-to-end electric energy transaction at each time period are determined; the method comprises the steps that power loss of a converter is considered, and actual transmission power of an intelligent soft switch in each power distribution network area is obtained; and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price. The trading method can improve the voltage distribution of each region, promote the reduction of the operation cost 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
A large amount of accesses of new elements such as distributed power sources and electric vehicles provide higher requirements for operation of a power distribution network, and for meeting diversified and customized power utilization requirements of a user side, the traditional power distribution network is gradually developed into a highly flexible and controllable flexible interconnection structure from a traditional radial structure under the support of flexible power distribution equipment such as a multi-end multi-voltage-level intelligent soft Switch (SOP). All distribution network areas interconnected through the multi-terminal intelligent soft switch have multiple energy interaction ways, accurate and controllable power transmission is supported, and a physical foundation is laid for peer-to-peer (P2P) electric energy transaction of a multi-area flexible interconnected distribution network.
In the face of the end-to-end electric energy transaction requirement of a multi-region flexible interconnected power distribution network, how to realize fair and effective electric energy transaction among multi-benefit subjects and consider the influence of system operation constraint on the transaction become problems to be solved.
The key problem of end-to-end electric energy transaction is how to design a transaction mechanism with the characteristics of data privacy protection, information symmetry and fair competition. The distributed market clearing algorithm can be used for realizing end-to-end electric energy transaction of the flexible interconnected power distribution network with privacy protection and information symmetry. And the non-cooperative game competition rules can be used for realizing fair and reasonable profit competition among the areas.
At present, research on multi-region flexible interconnected power distribution networks at home and abroad mainly focuses on the establishment of operation optimization strategies 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, for the electric energy transaction requirement of a multi-region flexible interconnected power distribution network, an end-to-end electric energy transaction method which promotes the reduction of the operation cost of each region and considers privacy protection is needed.
Disclosure of Invention
The invention aims to solve the problems of fairness of transaction rules, protection of data privacy and the like in electric energy transaction of a flexible interconnected power distribution network, and provides a method and a device for flexible power distribution network end-to-end electric energy transaction based on a non-cooperative game.
The invention provides a flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game, which comprises the following steps:
the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network region in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limitation output by an intelligent soft switch port is obtained according to power flow constraint and safe operation constraint;
according to the cost function and the trend constraint and the safe operation constraint of each interconnected distribution network region, distributed market clearing calculation among the interconnected distribution network regions is carried out based on a non-cooperative game, and the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval are determined on 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 distribution network region 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;
and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price.
Further, the cost function of the time period t formed by each interconnected distribution network area with respect to the transaction power is as follows:
in the formula (f)k,tRepresenting a cost function, pi, of the region k over a period ttElectric energy transaction prices among all regions determined in the lower-layer end-to-end electric energy transaction;the electric energy price for electric energy transaction between each distribution network area and the superior power network;respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU,k,tK voltage offset cost function for time period t region; Δ t is the transaction period duration;load power for node i;ωUAn out-of-load cost reduction factor for voltage overshoot; vi,tIs the square of the voltage at node i;which is the square of the nominal voltage at node i.
Further, the power flow constraint is as follows:
Vi,t-Vj,t=2(RijPij,t+XijQij,t) (8)
in the formula (I), the compound is shown in the specification,branch and node sets of the region k respectively;a node set of an intelligent energy storage soft switch access area k is obtained; pji,t、Qji,tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik,t、Qik,tRespectively flowing on branch ik at time interval tPower and reactive power; pi,t、Qi,tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;active power output and reactive power output of the distributed power supply are respectively time period t node i;injecting active power into the intelligent energy storage soft switch at an access node;respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
Further, the system safe operation constraints are as follows:
in the formula, omegaTA set of trade periods for a trade day; i isij,tThe current value of the branch ij is squared;the upper limit of the square value of the current of the branch ij; V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
in the formula, betak,tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
Further, the distributed market clearing calculation method for the interconnected distribution network regions based on the non-cooperative game comprises the following steps:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing powerOr selling electric powerThe calculation method is as follows:
in the formula (f)s,tAs a cost function of the seller s, fb,tA cost function for buyer b;selling electricity and purchasing electric power for the seller s and the buyer b respectively;
c) the same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller sAnd transmitted to each buyer; each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
ΩB∪ΩS=ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,distributing the obtained electric energy demand of the buyer b for the seller s;
d) each seller calculates and updates electricity selling price according to the following formula:
in the formula, σs,tAdjusting the factor for the seller s's electricity price;
e) judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, if not, setting h to h +1, and repeating the steps b) to d), wherein the convergence condition is as follows:
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
A flexible power distribution network end-to-end electric energy transaction device based on a non-cooperative game comprises the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by 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 performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid 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 non-cooperative game based flexible distribution network end-to-end power trading method 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 non-cooperative gambling based flexible power distribution network end-to-end power trading method as described above.
The invention has the advantages and positive effects that:
the invention discloses an end-to-end electric energy transaction method for a flexible interconnected power distribution network, which is based on the realization of electric energy transaction of fair competition among areas in the flexible interconnected power distribution network, takes the power adjustment of an intelligent soft switch as a transaction main body, fully considers the voltage control requirement of each area, constructs a cost function of each area about transaction power with the minimum electric energy cost and voltage deviation as targets, performs end-to-end electric energy transaction based on non-cooperative game according to the cost function with the highest self transaction profit as the target, realizes data privacy protection and market clearing by adopting a distributed algorithm, and further considers the loss of an intelligent soft switch converter to perform transaction power fine adjustment so that a transaction result meets the system operation constraint.
Drawings
FIG. 1 is a flow chart of a flexible power distribution network end-to-end electric energy transaction method based on non-cooperative game of the invention;
FIG. 2 is a schematic diagram of a four-terminal intelligent soft-switch flexible interconnection power distribution network in an exemplary area of Tianjin North Chen;
FIG. 3 is a photovoltaic, fan and load operating curve;
FIG. 4 is a superior grid power price curve;
FIG. 5 is a voltage distribution of each distribution network region under two schemes;
FIG. 6 is a cost reduction for zones in an end-to-end power transaction;
FIG. 7 is an end-to-end electric energy transaction active power of each zone after transaction trimming;
fig. 8 is an end-to-end trade electricity price result.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present invention clearer, 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 only some, but not all embodiments of the invention. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention discloses a flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game, which comprises the following steps as shown in figure 1:
inputting system parameters and network topology connection relations of each power distribution network region according to the selected flexible interconnected power distribution system, inputting access positions and related parameters of the intelligent soft switch, and using the adjusting power of the intelligent soft switch as an electric energy transaction object; inputting load and distributed power supply access positions, capacities and parameters; inputting a load and a daily operation curve of the distributed power supply; setting a system operation voltage level and a branch current limit; selecting a reference voltage and a reference power value; inputting the electric energy transaction price of each distribution network area and the superior power network in each time period t(ii) a Setting the duration delta t of each transaction time interval in one operation day; inputting the unit cost of load loss under the extreme voltage excursion;
for the present embodiment, a distribution network including four-terminal intelligent soft switches in the Tianjin North-Chen demonstration area is shown in fig. 2, and the detailed parameters are shown in tables 1 and 2. The demonstration area takes a joint table 110kV transformer substation and a wind power park 110kV transformer substation as centers to form a double-loop network structure comprising four feeders, four distribution network areas are flexibly interconnected through four-end intelligent soft switches, the voltage grades are all set to be 10.5kV, and the total active power demand and the total reactive power demand of the load are 9.9880MW and 7.3350Mvar respectively.
To account for the access impact of the high permeability distributed power, the distributed power access case is shown in table 3. The distributed power supply power factors are all set to 1.0. The distributed power output and load demand curves are shown in fig. 3. The capacity of the current converter of each port of the four-end intelligent soft switch is set to be 3MVA, and the loss coefficient is set to be 0.01. The system reference power was set to 1 MVA. The safe voltage operation range of the active power distribution network is 0.90p.u. -1.10 p.u.
In one trading day, the duration Δ t of each trading session is set to 1 hour for a total of 24 trading sessions. The electric energy price curve of the superior electric network in each period is shown in fig. 4. Calculating a voltage offset cost coefficient omega according to the load loss costUSet to 0.011.
According to the provided system parameters, network topology, intelligent soft switch access positions, the capacities and daily operating curves of loads and distributed power supplies in each power distribution network region, and the electric energy price and the load loss unit cost parameters of a superior power grid, each interconnected power distribution network region k takes the lowest electric energy cost and the minimum node voltage deviation as targets, and a cost function f related to transaction power in a time period t is formed through load flow analysisk,tCalculating the output active power limit of the intelligent soft switch port according to the power flow constraint, the safe operation constraint and the like;
the cost function of the time period t formed by the interconnected power distribution network areas on the transaction power is as follows:
in the formula (f)k,tRepresenting a cost function, pi, of the region k over a period ttElectric energy trading price between regions determined in lower layer end-to-end electric energy trading;The electric energy price for electric energy transaction between each distribution network area and the superior power network;respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU,k,tK voltage offset cost function for time period t region; Δ t is the transaction period duration;is the load power of node i; omegaUAn out-of-load cost reduction factor for voltage overshoot; vi,tIs the square of the voltage at node i;which is the square of the nominal voltage at node i.
The power flow constraint is as follows:
Vi,t-Vj,t=2(RijPij,t+XijQij,t) (8)
in the formula (I), the compound is shown in the specification,branch and node sets of the region k respectively;a node set of an intelligent energy storage soft switch access area k is obtained; pji,t、Qji,tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik,t、Qik,tRespectively is the active power and the reactive power flowing through the branch ik at the time interval t; pi,t、Qi,tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;active power output and reactive power output of the distributed power supply are respectively time period t node i;injecting active power into the intelligent energy storage soft switch at an access node;respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
The system safe operation constraint is as follows:
in the formula, omegaTA set of trade periods for a trade day; i isij,tThe current value of the branch ij is squared;the upper limit of the square value of the current of the branch ij; V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
in the formula, betak,tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
According to the obtained cost function of each distribution network region, distributed market clearing calculation based on non-cooperative game among the regions is carried out, and the transaction price pi of end-to-end electric energy transaction is determined on the premise of realizing privacy protectiontAnd the bought power of each region k in the time period tOr selling power
The distributed market clearing calculation method based on the non-cooperative game can be described as follows:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing powerOr selling electric powerThe calculation method is as follows:
in the formula (f)s,tAs a cost function of the seller s, fb,tA cost function for buyer b;the seller s and the buyer b sell electricity and purchase electric power respectively.
c) The same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller sAnd passed to each buyer. Each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
ΩB∪ΩS=ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,the resulting demand for electricity by buyer b is distributed to seller s.
d) Each seller calculates and updates electricity selling price according to the following formula:
in the formula, σs,tThe factor is adjusted for the seller s's electricity price.
e) Judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, and if not, setting h to h +1 and repeating the steps b) -d), wherein the convergence condition is as follows:
in the formula, 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 distribution network region according to the obtained end-to-end electric energy transaction result and by 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 formula (I), the compound is shown in the specification,setting the actual active power of the intelligent soft switch to be determined in the transaction fine adjustment for the t-period region k;active trading power determined in end-to-end electric energy trading for a t period region k;the loss power of the intelligent soft switch at the port of the converter in the area k in the period t; a. theSOPThe loss coefficient of the intelligent soft switching converter is obtained.
And settling accounts among the regions according to the transaction power and the clearing price, and settling accounts between the regions and the superior power grid according to the actual transmission power and the electric energy price.
In order to verify the feasibility and the effectiveness of the transaction method of the present invention, in this embodiment, the following two scenarios are adopted for verification analysis:
scheme I: and each distribution network area does not participate in electric energy transaction, so that the operation level and the cost of the distribution network in the initial state are obtained.
Scheme II: each distribution network area carries out end-to-end electric energy transaction of a multi-area flexible interconnected distribution network through an intelligent soft switch, and active power transaction fine adjustment based on the intelligent soft switch is carried out after the transaction.
The daily operating costs for each zone in scenario I, II are shown in Table 4. In both schemes, the voltage distribution of each grid area is shown in fig. 5. The cost reduction of each area in the end-to-end electric energy transaction result of the scheme II is shown in fig. 6, and the active power transaction result of each area after fine adjustment in the end-to-end electric energy transaction is shown in fig. 7. In scenario II, the end-to-end electric energy trade power rates are shown in fig. 8.
The computer hardware environment for executing solving calculation is Intel (R) core (TM) i5-5200U CPU, the main frequency is 2.20GHz, and the memory is 4 GB; the software environment is a Windows 10 operating system.
Compared with a 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 operation cost of each region, improves voltage distribution of each region, 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 power distribution network based on the non-cooperative game can effectively improve the operating economy of the system and improve the voltage distribution of the system.
TABLE 1 arithmetic load access position and power for distribution network in Tianjin North Chen demonstration area
TABLE 2 calculation circuit parameters of distribution network in Tianjin North Chen demonstration area
TABLE 3 distributed Power Access location and Capacity
Region(s) | Photovoltaic Capacity/MVA | Fan Capacity/MVA |
Wind 33 | 1.0 | - |
|
1.0 | 2.0 |
Wedding 64 | - | 2.0 |
Wedding 51 | - | 2.0 |
TABLE 4 daily operating costs for each distribution network region
A flexible power distribution network end-to-end electric energy transaction device based on a non-cooperative game comprises the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by 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 performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid 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,
when the one or more programs are executed by the one or more processing units, the one or more processing units execute the non-cooperative game-based flexible power distribution network end-to-end electric energy transaction method; it is 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 computing device including the processing unit, the memory unit do not constitute a limitation of the computing device, may include more components, or combine certain components, or different components, for example, the computing device may also include input output devices, network access devices, buses, etc.
A computer readable storage medium having non-volatile program code executable by a processor, the computer program when executed by the processor implementing the steps of the above-mentioned non-cooperative game based flexible power distribution network end-to-end electric energy transaction method; it should be noted that the readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof; the program embodied on the 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 situations involving remote computing devices, the remote computing devices 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., through the internet using an internet service provider).
Finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Although the present 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game is characterized by comprising the following steps:
the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network region in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limitation output by an intelligent soft switch port is obtained according to power flow constraint and safe operation constraint;
according to the cost function and the trend constraint and the safe operation constraint of each interconnected distribution network region, distributed market clearing calculation among the interconnected distribution network regions is carried out based on a non-cooperative game, and the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval are determined on the premise of realizing privacy protection;
calculating and obtaining the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function by considering the power loss of the converter;
and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price.
2. The flexible power distribution network end-to-end electric energy transaction method based on the non-cooperative game as claimed in claim 1, wherein a cost function of a time period t formed by each interconnected power distribution network region with respect to transaction power is as follows:
in the formula (f)k,tRepresenting a cost function, pi, of the region k over a period ttElectric energy transaction prices among all regions determined in the lower-layer end-to-end electric energy transaction;the electric energy price for electric energy transaction between each distribution network area and the superior power network;respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU,k,tK voltage offset cost function for time period t region; Δ t is the transaction period duration;is the load power of node i; omegaUAn out-of-load cost reduction factor for voltage overshoot; vi,tIs the square of the voltage at node i;which is the square of the nominal voltage at node i.
3. The non-cooperative game-based flexible power distribution network end-to-end electric energy transaction method according to claim 2, wherein the trend constraint is as follows:
Vi,t-Vj,t=2(RijPij,t+XijQij,t) (8)
in the formula (I), the compound is shown in the specification,branch and node sets of the region k respectively;a node set of an intelligent energy storage soft switch access area k is obtained; pji,t、Qji,tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik,t、Qik,tRespectively is the active power and the reactive power flowing through the branch ik at the time interval t; pi,t、Qi,tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;active power output and reactive power output of the distributed power supply are respectively time period t node i;injecting active power into the intelligent energy storage soft switch at an access node;respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
4. The flexible power distribution network end-to-end electric energy transaction method based on the non-cooperative game as claimed in claim 3, wherein the system safety operation constraints are as follows:
in the formula, omegaTA set of trade periods for a trade day; i isij,tThe current value of the branch ij is squared;the upper limit of the square value of the current of the branch ij; V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
in the formula, betak,tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
5. The electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch as claimed in claim 1, wherein the distributed market clearing calculation method between the areas of the interconnected power distribution networks based on the non-cooperative game comprises the following steps:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing powerOr selling electric powerThe calculation method is as follows:
in the formula (f)s,tAs a cost function of the seller s, fb,tA cost function for buyer b;selling electricity and purchasing electric power for the seller s and the buyer b respectively;
c) the same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller sAnd transmitted to each buyer; each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
ΩB∪ΩS=ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,distributing the obtained electric energy demand of the buyer b for the seller s;
d) each seller calculates and updates electricity selling price according to the following formula:
in the formula, σs,tAdjusting the factor for the seller s's electricity price;
e) judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, if not, setting h to h +1, and repeating the steps b) to d), wherein the convergence condition is as follows:
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
6. Flexible distribution network end-to-end electric energy transaction device based on non-cooperative game is characterized by comprising the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by 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 performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid according to the actual transmission power and the electric energy price.
7. A computing device, characterized by: the method comprises 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 1-5.
8. A computer-readable storage medium with non-volatile program code executable by a processor, characterized in that the computer program realizes the steps of the method according to any one of claims 1 to 5 when executed by the processor.
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 true CN114004646A (en) | 2022-02-01 |
CN114004646B 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) |
Citations (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 |
CN102915472A (en) * | 2012-10-30 | 2013-02-06 | 南京软核科技有限公司 | Comprehensive power distribution network optimization planning method based on gene modified chaos genetic algorithm |
CN104578157A (en) * | 2015-01-04 | 2015-04-29 | 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 |
CN112150287A (en) * | 2020-09-29 | 2020-12-29 | 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
Patent Citations (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 |
CN102915472A (en) * | 2012-10-30 | 2013-02-06 | 南京软核科技有限公司 | Comprehensive power distribution network optimization planning method based on gene modified chaos genetic algorithm |
CN104578157A (en) * | 2015-01-04 | 2015-04-29 | 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 |
CN112150287A (en) * | 2020-09-29 | 2020-12-29 | 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 |
Also Published As
Publication number | Publication date |
---|---|
CN114004646B (en) | 2024-06-14 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Correa-Florez et al. | Optimal participation of residential aggregators in energy and local flexibility markets | |
Zhou et al. | Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework | |
Shamsi et al. | Economic dispatch for an agent-based community microgrid | |
Haggi et al. | Multi-round double auction-enabled peer-to-peer energy exchange in active distribution networks | |
Zhang et al. | Real-time procurement strategies of a proactive distribution company with aggregator-based demand response | |
Qiu et al. | Distributed generation and energy storage system planning for a distribution system operator | |
Cui et al. | Game-based peer-to-peer energy sharing management for a community of energy buildings | |
Jin et al. | Pricing and operation strategy for peer-to-peer energy trading using distribution system usage charge and game theoretic model | |
Ali et al. | A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme | |
Gnanadass et al. | Assessment of available transfer capability for practical power systems with combined economic emission dispatch | |
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 | |
Zou et al. | Resource allocation game under double-sided auction mechanism: Efficiency and convergence | |
Sarfi et al. | Optimal Volt/VAR control in distribution systems with prosumer DERs | |
Lin et al. | Blockchain-based intelligent charging station management system platform | |
Swain et al. | Population variant differential evolution–based multiobjective economic emission load dispatch | |
Sarwar et al. | Bid responsive generation rescheduling for congestion management in electricity market | |
Abdolahinia et al. | Decentralized transactive energy market framework under network constraints to deal with technical issues in a radial distribution network | |
Faria et al. | P2P market coordination methodologies with distribution grid management | |
CN114006371A (en) | Flexible power distribution network electric energy transaction method and device oriented to intelligent energy storage soft switch | |
Zhang et al. | Expanding the role of DSOs in establishing flexible local markets: A brokerage perspective | |
Liu et al. | Strategic bidding optimization of microgrids in electricity distribution market | |
Krishnan et al. | Evolutionary programming-based simulation of bilateral real power contracts by optimal placement of flexible AC transmission system devices using contingency analysis | |
CN114004646A (en) | Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game | |
CN111626569B (en) | Micro-grid group electric power energy trading method |
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 |