CN114006371A - Flexible power distribution network electric energy transaction method and device oriented to intelligent energy storage soft switch - Google Patents

Flexible power distribution network electric energy transaction method and device oriented to intelligent energy storage soft switch Download PDF

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CN114006371A
CN114006371A CN202111279876.0A CN202111279876A CN114006371A CN 114006371 A CN114006371 A CN 114006371A CN 202111279876 A CN202111279876 A CN 202111279876A CN 114006371 A CN114006371 A CN 114006371A
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energy storage
power
transaction
soft switch
distribution network
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CN114006371B (en
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李娟�
徐晶
张梁
张章
崔荣靖
迟福建
李桂鑫
李鹏
田振
冀浩然
宋关羽
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State Grid Corp of China SGCC
State Grid Tianjin Electric Power Co Ltd
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State Grid Tianjin Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/50—Controlling the sharing of the out-of-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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Abstract

The invention provides an intelligent energy storage soft switch-oriented flexible power distribution network electric energy transaction method, which comprises the following steps: 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 minimum node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring power flow constraint and safe operation constraint; distributed market clearing calculation among all interconnected distribution network regions is carried out based on a non-cooperative game, and clearing price and transaction active power of lower-layer end-to-end electric energy transaction at each time interval are determined; performing upper-layer active power transaction adjustment and solving of internal energy storage link output strategies to obtain an intelligent energy storage soft switch active power scheduling result; obtaining the optimal reactive power output of the intelligent energy storage soft switch in each interconnected power distribution network region according to the cost function; and the distribution network area performs actual purchase and sale electricity quantity settlement with the superior power network according to the final transaction result. The invention can promote the reduction of the operation cost of each area and improve the operation profit of the intelligent energy storage soft switch.

Description

Flexible power distribution network electric energy transaction method and device oriented to intelligent energy storage soft switch
Technical Field
The invention relates to the technical field of urban power grid planning evaluation, in particular to a flexible power distribution network electric energy trading method oriented to an intelligent energy storage soft switch.
Background
The large access of new elements such as distributed power sources and electric vehicles puts higher requirements on the operation of the power distribution network. In order to meet the diversified and customized electricity 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-terminal multi-voltage-level intelligent soft Switch (SOP) and the like. Each distribution network region interconnected through the multi-terminal intelligent soft switch has a plurality of energy interaction ways, supports accurate and controllable power transmission, and lays a physical foundation for electric energy transaction of a multi-region flexible interconnected distribution network. The energy storage device is additionally arranged in the direct current link of the intelligent soft switch to form the intelligent energy storage soft switch, so that the time sequence trend adjusting capability of the intelligent soft switch can be further improved. The reactive power regulation ability of the intelligent energy storage soft switch can optimize the voltage distribution of each area, improves the operation benefit of each area, and provides conditions for the reactive power auxiliary service of a multi-area flexible interconnected power distribution network.
In the face of the electric energy transaction requirements of a multi-region flexible interconnected power distribution network, how to realize fair and effective electric energy transaction among multi-benefit main bodies and promote the recovery of the investment cost of flexible interconnection devices such as intelligent energy storage soft switches and the like is the problem to be solved.
The key problem of electric energy transaction is how to design a transaction mechanism with the characteristics of protecting data privacy, information symmetry and fair competition. The distributed market clearing algorithm can be used for realizing privacy protection and information symmetry flexible interconnection power distribution network electric energy transaction. And the non-cooperative game competition rules can be used for realizing fair and reasonable profit competition among the areas.
At present, the research on multi-region flexible interconnected power distribution networks at home and abroad mainly focuses on the operation optimization strategy formulation of a multi-terminal intelligent energy storage soft switch, and how to realize the improvement of the operation profit of the intelligent energy storage soft switch in electric energy transaction needs to be further researched. Therefore, an electric energy transaction method for promoting the reduction of the operation cost of each region and improving the operation profit of the intelligent energy storage soft switch is needed to be researched for the electric energy transaction requirement of the multi-region flexible interconnected power distribution network.
Disclosure of Invention
The invention aims to design an electric energy trading method for promoting the reduction of the operation cost of each region and improving the operation profit of an intelligent energy storage soft switch.
The invention provides an intelligent energy storage soft switch-oriented flexible power distribution network electric energy transaction method, which comprises the following steps:
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 minimum node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring 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;
according to the obtained lower-layer end-to-end electric energy trading result and the cost function, the intelligent energy storage soft switch carries out upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each interconnected power distribution network region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
based on the active power of the intelligent energy storage soft switch and the energy storage link scheduling result, the optimal reactive power output of the intelligent energy storage soft switch is obtained in each interconnected power distribution network region according to a cost function;
and (4) settlement is carried out between the distribution network areas according to end-to-end transaction results, the intelligent soft switch and the two-time profit of settlement of each area are divided into the difference with the adjustment and compensation of active transaction, and the actual purchase and sale electric quantity settlement is carried out between the distribution network areas and the superior power grid according to the final transaction results.
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:
Figure BDA0003326335960000021
Figure BDA0003326335960000022
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;
Figure BDA0003326335960000023
the electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure BDA0003326335960000024
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure BDA0003326335960000025
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;
Figure BDA0003326335960000026
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;
Figure BDA0003326335960000027
which is the square of the nominal voltage at node i.
Further, the power flow constraint is as follows:
Figure BDA0003326335960000031
Figure BDA0003326335960000032
Figure BDA0003326335960000033
Figure BDA0003326335960000034
Figure BDA0003326335960000035
Vi,t-Vj,t＝2(RijPij,t+XijQij,t) (8)
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000036
branch and node sets of the region k respectively;
Figure BDA0003326335960000037
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;
Figure BDA0003326335960000038
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure BDA0003326335960000039
injecting active power into the intelligent energy storage soft switch at an access node;
Figure BDA00033263359600000310
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:
Figure BDA00033263359600000311
Figure BDA00033263359600000312
in the formula, omegaTA set of trade periods for a trade day; i isij,tThe current value of the branch ij is squared;
Figure BDA00033263359600000313
the upper limit of the square value of the current of the branch ij;
Figure BDA00033263359600000314
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:
Figure BDA00033263359600000315
Figure BDA00033263359600000316
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:
Figure BDA00033263359600000317
Figure BDA00033263359600000318
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 intelligent energy storage soft switch performs upper active power trading adjustment and internal energy storage link output strategy solving according to the obtained lower layer end-to-end electric energy trading result and the cost function by aiming at minimizing the sum of cost change compensation in trading adjustment of each interconnected power distribution network area, and the method for obtaining the intelligent energy storage soft switch active power scheduling result comprises the following steps:
the objective function of the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch can be expressed as follows:
Figure BDA0003326335960000041
Figure BDA0003326335960000042
Figure BDA0003326335960000043
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000044
setting the actual active power of the intelligent energy storage soft switch to be determined in the transaction adjustment for a time period t region k;
Figure BDA0003326335960000045
active trading power determined for a region k in a lower layer end-to-end electric energy trading in a time period t;
Figure BDA0003326335960000046
is an active power adjustment;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the equality relationship between the end-to-end electric energy transaction adjustment quantity of each area and the balance power bought or sold to the superior power grid can be expressed as follows:
Figure BDA0003326335960000047
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000048
respectively is the balance power purchased and sold by the superior power grid in the time period t region k due to the end-to-end electric energy transaction adjustment;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the operation constraint of the intelligent energy storage soft switch can be expressed as:
Figure BDA0003326335960000049
Figure BDA00033263359600000410
Figure BDA00033263359600000411
Figure BDA00033263359600000412
Figure BDA00033263359600000413
Figure BDA00033263359600000414
Figure BDA00033263359600000415
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000051
the loss power of the converter port of the intelligent energy storage soft switch in the region k time period t is measured;
Figure BDA0003326335960000052
the charging and discharging power of an internal energy storage link of the intelligent energy storage soft switch is provided; a. theSOPLoss coefficient of the intelligent energy storage soft switching converter;
Figure BDA0003326335960000053
the reactive power of the intelligent energy storage soft switch at the port of the converter in the area k is set for a time t; sSOPCapacity of the intelligent energy storage soft switching converter; emax、EminRespectively an upper limit and a lower limit of the energy storage charge state; eOStoring an initial state of charge for a transaction day; pES,maxIs an energy storage charging and discharging power limit value;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the transaction adjustment constraint is expressed as:
Figure BDA0003326335960000054
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000055
the upper limit and the lower limit of the active output of the intelligent energy storage soft switch at the port of the converter are obtained by solving according to the regional operation constraint.
Further, based on the active power of the intelligent energy storage soft switch and the scheduling result of the energy storage link, the method for obtaining the optimal reactive power of the intelligent energy storage soft switch by each interconnected power distribution network region according to the cost function comprises the following steps:
in the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the objective function of each region can be expressed as:
Figure BDA0003326335960000056
Figure BDA0003326335960000057
Figure BDA0003326335960000058
in the formula, ζi,kIs a regionA set of branches from node i to the source node in domain k; zetaSOP,kA branch set from an intelligent energy storage soft switch access node to a source node in a region k is formed;
Figure BDA0003326335960000059
adjusting the result for the upper layer active power transaction; rij、XijThe resistance and reactance of branch ij are respectively;
Figure BDA00033263359600000510
cost of voltage offset by linear current analysis
Figure BDA00033263359600000511
The analytical expression of (1);
Figure BDA00033263359600000512
the square value of the initial voltage of the node i before transaction;
in the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the reactive power scheduling constraint can be expressed as:
Figure BDA00033263359600000513
Figure BDA0003326335960000061
Figure BDA0003326335960000062
Figure BDA0003326335960000063
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000064
is a node set in the region k;
Figure BDA0003326335960000065
is a branch set in the region k;
Figure BDA0003326335960000066
V ithe upper limit and the lower limit of the voltage square value of the node i are respectively;
Figure BDA0003326335960000067
the upper limit of the square of the current for branch ij.
Further, the settlement is carried out between the distribution network areas according to end-to-end transaction results, the two profits of settlement of the intelligent soft switch and each area are divided into the difference with the adjustment and compensation of active transaction, and the method for carrying out actual purchase and sale electric quantity settlement on the distribution network areas and the superior power grid according to the final transaction results comprises the following steps:
settlement is carried out among all interconnected power distribution network areas according to the trading power and clearing price, and trading income is proportionally distributed to the intelligent energy storage soft switch to serve as profit in all the interconnected power distribution network areas; according to the active power transaction adjustment result, the intelligent energy storage soft switch and each area perform compensation settlement of transaction adjustment cost change; according to the reactive power scheduling result, each interconnected power distribution network region distributes the cost reduction amount brought by the reactive power scheduling to the intelligent energy storage soft switch in proportion to be used as profit; and (4) settling the interconnected power distribution network areas and the superior power network according to the actual transmission power and the electric energy price.
Towards flexible distribution network electric energy transaction device of soft switch of intelligent energy storage, the device includes as follows:
the cost function establishing module is used for forming a cost function of the transaction power in the time period t 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 power flow constraint and 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 energy storage soft switch active power scheduling result obtaining module is used for the intelligent energy storage soft switch to obtain a lower-layer end-to-end electric energy trading result and a cost function according to the obtained lower-layer end-to-end electric energy trading result, and to perform upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each interconnected power distribution network region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
the optimal reactive power output acquisition module of the intelligent energy storage soft switch is used for acquiring the optimal reactive power output of the intelligent energy storage soft switch according to a cost function in each interconnected power distribution network region based on the active power of the intelligent energy storage soft switch and an energy storage link scheduling result;
and the transaction settlement module is used for settling between the power distribution network areas according to end-to-end transaction results, dividing the two profits of settlement of the intelligent soft switch and each area into a difference with the adjustment and compensation of active transaction, and settling the actual purchase and sale electric quantity of the power distribution network areas according to the final transaction results and the superior power grid.
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 are enabled to execute the flexible power distribution network electric energy transaction method facing the intelligent energy storage soft switch.
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 power trading method oriented to intelligent energy storage soft switches as described above.
The invention has the advantages and positive effects that:
the electric energy transaction method of the flexible interconnected power distribution network facing the intelligent energy storage soft switch is based on realizing the electric energy transaction of fair competition among areas in the flexible interconnected power distribution network and improving the transaction profit of the flexible interconnected device, the power adjustment of the intelligent energy storage soft switch is taken as a trading subject, the voltage control requirements of each region and the adjusting capability of the intelligent energy storage soft switch are fully considered, constructing a cost function of each area about transaction power by taking the minimum electric energy cost and the minimum voltage deviation as targets, taking the highest self transaction profit as the target of each area, carrying out lower-layer end-to-end electric energy transaction based on a non-cooperative game according to the cost function, and data privacy protection and market clearing are realized by adopting a distributed algorithm, and the intelligent energy storage soft switch further realizes the improvement of the operation benefits of the interconnection area and the intelligent energy storage soft switch through upper-layer active power transaction adjustment, energy storage link scheduling and reactive scheduling.
Drawings
FIG. 1 is a flow chart of an electric energy transaction method of a flexible interconnected power distribution network facing an intelligent energy storage soft switch, disclosed by the invention;
FIG. 2 is a schematic diagram of an improved four-terminal intelligent energy storage 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 three schemes;
FIG. 6 is a cost reduction for zones in a lower level end-to-end power transaction;
FIG. 7 is active power traded by zones in a lower level end-to-end power trade;
FIG. 8 shows the adjustment result of the active power transaction of the upper layer intelligent energy storage soft switch;
FIG. 9 shows the result of the upper-layer intelligent energy storage soft switch reactive scheduling;
fig. 10 shows the internal energy storage scheduling of the upper intelligent energy storage soft switch and the end-to-end trading power price result of the lower intelligent energy storage soft switch.
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.
The retail package pricing method considering price type demand response constructs a demand response model, analyzes the cost-income function of the electricity selling company containing electricity selling income, electricity purchasing expenditure, response income and the like, constructs the retail package pricing model, and provides decision support for the retailer from the perspective of optimized pricing.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention discloses an intelligent energy storage soft switch-oriented flexible power distribution network electric energy transaction method, which comprises the following steps as shown in figure 1:
1) according to the selected flexible interconnected power distribution system, system parameters and network topology connection relations of all power distribution network regions are obtained, access positions of intelligent energy storage soft switches, current transformer capacity, internal energy storage link capacity and charging and discharging power limits are obtained, and the current transformer regulating power of the intelligent energy storage soft switches is used as an electric energy trading object; obtaining the access position, capacity and parameters of the load and the distributed power supply; obtaining the load and the daily operation curve prediction result 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; obtaining the electric energy transaction price of each distribution network area and the superior power network in each time period t in one operation day
Figure BDA0003326335960000091
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, an improved distribution network with four-terminal intelligent energy storage 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 energy storage soft switches, the voltage grades are all set to be 10.5kV, and the load total active power requirements and the load total reactive power requirements 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 at each port of the four-end intelligent energy storage soft switch is set to be 3MVA, and the loss coefficient is set to be 0.01. The capacity of an internal energy storage link of the intelligent energy storage soft switch is set to be 3MWh, the charge state range is 10% -90%, and the charge and discharge power is limited to be 0.5 MW. 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.
2) According to the system parameters, the network topology, the intelligent soft switch access position, the load and the position, the capacity and the daily operation curve prediction of the distributed power supply of each power distribution network region provided in the step 1), and the unit cost parameters of the electric energy price and the load loss of the superior power grid, each interconnected power distribution network region k takes the lowest electric energy cost and the minimum node voltage deviation as the target, and a cost function f of the transaction power in the time period t is formed through load flow analysisk,tCalculating the output active power limit of the port of the intelligent energy storage soft switch according to the power flow constraint, the safe operation constraint and the like;
(1) the regions form a cost function f related to active transaction powerk,tIt can be expressed as:
Figure BDA0003326335960000092
Figure BDA0003326335960000093
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;
Figure BDA0003326335960000094
the electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure BDA0003326335960000095
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure BDA0003326335960000096
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;
Figure BDA0003326335960000097
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;
Figure BDA0003326335960000101
which is the square of the nominal voltage at node i.
(2) And the flow constraint of each region k is as follows:
Figure BDA0003326335960000102
Figure BDA0003326335960000103
Figure BDA0003326335960000104
Figure BDA0003326335960000105
Figure BDA0003326335960000106
Vi,t-Vj,t＝2(RijPij,t+XijQij,t) (8)
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000107
branch and node sets of the region k respectively;
Figure BDA0003326335960000108
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;
Figure BDA0003326335960000109
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure BDA00033263359600001010
injecting active power into the intelligent energy storage soft switch at an access node;
Figure BDA00033263359600001011
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.
(3) The system safe operation constraint is as follows:
Figure BDA00033263359600001012
Figure BDA00033263359600001013
in the formula, omegaTA set of trade periods for a trade day; i isij,tThe current value of the branch ij is squared;
Figure BDA00033263359600001014
the upper limit of the square value of the current of the branch ij;
Figure BDA00033263359600001015
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:
Figure BDA00033263359600001016
Figure BDA00033263359600001017
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:
Figure BDA00033263359600001018
Figure BDA00033263359600001019
in the formula, betak,tBinary for representing the identity of the market for region k over time period tThe variable represents that the area k is a seller when 1 is taken; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
3) According to the cost function of each distribution network region obtained in the step 2), distributed market clearing calculation based on non-cooperative game among the regions is carried out, and the transaction price pi of the lower-layer end-to-end electric energy transaction in each time period is determined on the premise of realizing privacy protectiontAnd the bought power of each region k in time period t
Figure BDA0003326335960000111
Or selling power
Figure BDA0003326335960000112
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
Figure BDA0003326335960000113
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 power
Figure BDA0003326335960000114
Or selling electric power
Figure BDA0003326335960000115
The solving formula is as follows:
Figure BDA0003326335960000116
Figure BDA0003326335960000117
in the formula (f)s,tAs a cost function of the seller s, fb,tCost function for buyer b；
Figure BDA0003326335960000118
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 s
Figure BDA0003326335960000119
And transmitting the electric energy to each buyer, wherein each buyer b calculates the electric energy demand distributed to each seller s according to the following formula:
Figure BDA00033263359600001110
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,
Figure BDA00033263359600001111
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:
Figure BDA00033263359600001112
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:
Figure BDA00033263359600001113
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
4) According to the lower-layer end-to-end electric energy trading result and each region cost function obtained in the step 3), carrying out upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
(1) the objective function of the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch can be expressed as follows:
Figure BDA0003326335960000121
Figure BDA0003326335960000122
Figure BDA0003326335960000123
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000124
setting the actual active power of the intelligent energy storage soft switch to be determined in the transaction adjustment for a time period t region k;
Figure BDA0003326335960000125
the active trading power determined by the area k in the lower-layer end-to-end electric energy trading at the time period t in the step 3);
Figure BDA0003326335960000126
is the active power adjustment.
(2) In the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the equation relationship between the end-to-end electric energy transaction adjustment amount of each area and the balance power bought or sold to the superior power grid can be expressed as follows:
Figure BDA0003326335960000127
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000128
respectively, the time period t is the balance power purchased and sold to the upper-level power grid in the region k due to the end-to-end electric energy transaction adjustment.
(3) In the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the operation constraint of the intelligent energy storage soft switch can be expressed as:
Figure BDA0003326335960000129
Figure BDA00033263359600001210
Figure BDA00033263359600001211
Figure BDA00033263359600001212
Figure BDA00033263359600001213
Figure BDA00033263359600001214
Figure BDA0003326335960000131
in the formula，
Figure BDA0003326335960000132
The loss power of the converter port of the intelligent energy storage soft switch in the region k time period t is measured;
Figure BDA0003326335960000133
the charging and discharging power of the internal energy storage link of the intelligent energy storage soft switch is positive; a. theSOPLoss coefficient of the intelligent energy storage soft switching converter;
Figure BDA0003326335960000134
the reactive power of the intelligent energy storage soft switch at the port of the converter in the area k is set for a time t; sSOPCapacity of the intelligent energy storage soft switching converter; emax、EminRespectively an upper limit and a lower limit of the energy storage charge state; e0Storing an initial state of charge for a transaction day; pES,maxIs the limit value of the energy storage charging and discharging power.
(4) In the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the transaction adjustment constraint can be expressed as:
Figure BDA0003326335960000135
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000136
and respectively solving the upper and lower active output limits of the intelligent energy storage soft switch at the port of the converter according to the regional operation constraint.
5) Based on the active power of the intelligent energy storage soft switch in the step 4) and the scheduling result of the energy storage link, calculating the optimal reactive output of the intelligent energy storage soft switch according to the cost function in each area;
(1) in the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the objective function of each region can be expressed as:
Figure BDA0003326335960000137
Figure BDA0003326335960000138
Figure BDA0003326335960000139
in the formula, ζi,kA branch set from a node i to a source node in a region k; zetaSOP,kA branch set from an intelligent energy storage soft switch access node to a source node in a region k is formed;
Figure BDA00033263359600001310
adjusting the result for the upper layer active power transaction; rij、XijThe resistance and reactance of branch ij are respectively;
Figure BDA00033263359600001311
cost of voltage offset by linear current analysis
Figure BDA00033263359600001312
The analytical expression of (1);
Figure BDA00033263359600001313
the square value of the initial voltage of the node i before the transaction.
(2) In the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the reactive power scheduling constraint can be expressed as:
Figure BDA00033263359600001314
Figure BDA0003326335960000141
Figure BDA0003326335960000142
in the formula (I), the compound is shown in the specification,
Figure BDA0003326335960000143
is a node set in the region k;
Figure BDA0003326335960000144
is a branch set in the region k;
Figure BDA0003326335960000145
V irespectively representing the upper limit and the lower limit of a voltage square value of a node i;
Figure BDA0003326335960000146
the upper limit of the square of the current for branch ij.
6) The settlement is carried out between the regions according to the trading power and clearing price, and the regions receive the trading income according to alpha1% of the proportion is distributed to the intelligent energy storage soft switch as profit; according to the active power transaction adjustment result, the intelligent energy storage soft switch and each area perform compensation settlement of transaction adjustment cost change; according to the result of reactive scheduling, each region reduces the cost brought by reactive scheduling by alpha2% of the proportion is distributed to the intelligent energy storage soft switch as profit; and (4) settling accounts between each district and the superior power grid according to the actual transmission power and the electric energy price.
For the present embodiment, α is chosen1＝30、α2＝30。
The invention establishes an active power transaction adjustment and internal energy storage scheduling model and a reactive scheduling model of a flexible interconnected power distribution network based on an intelligent energy storage soft switch. The models are proved to be convex planning models, and an interior point method can be adopted for solving to obtain active regulation, energy storage scheduling and reactive scheduling schemes of the intelligent energy storage soft switch.
In order to verify the feasibility and the effectiveness of the electric energy transaction method of the flexible interconnected power distribution network facing the intelligent energy storage soft switch, in the embodiment, the following three scenes are adopted for verification and analysis:
scheme I: each distribution network area does not participate in electric energy transaction, and 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 energy storage soft switch, and active power transaction adjustment and internal energy storage scheduling based on the intelligent energy storage soft switch are carried out after the transaction;
scheme III: and each distribution network area carries out end-to-end electric energy transaction of a multi-area flexible interconnected distribution network through the intelligent energy storage soft switch, and active power transaction adjustment and internal energy storage scheduling based on the intelligent energy storage soft switch are carried out after the transaction. Based on the active power adjustment result, further performing reactive power scheduling based on the intelligent energy storage soft switch;
the daily operation cost of each region from the scheme I to the scheme III is shown in a table 4, and the daily operation profit of the intelligent energy storage soft switch in the schemes II and III is shown in a table 5. The voltage distribution for each grid area of the three schemes is shown in fig. 5. In schemes II and III, the cost reduction of each region in the lower layer end-to-end electric energy transaction is shown in fig. 6, and the active power transaction result of each region in the lower layer end-to-end electric energy transaction is shown in fig. 7. In the scheme II, an active power transaction adjustment scheme based on the intelligent energy storage soft switch is shown in fig. 8. In the scheme III, the reactive scheduling scheme based on the intelligent energy storage soft switch is shown in fig. 9. In schemes II and III, the scheduling result of the intelligent energy storage soft switch energy storage link and the lower end-to-end electric energy trading power price are shown in fig. 10.
The computer hardware environment for executing the optimization 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 trading, the schemes II and III realize effective reduction of operation cost of each region and improve voltage distribution of each region for flexible interconnection power distribution network electric energy trading of the intelligent energy storage soft switch. Compared with the scheme II, the scheme III further improves the operation profit of the intelligent energy storage soft switch, optimizes the voltage distribution of each region and further reduces the operation cost of the power distribution network region.
Compared with the three schemes, the electric energy transaction method for the flexible interconnected power distribution network facing the intelligent energy storage soft switch can effectively improve the operation economy of the system, improve the operation benefit of the intelligent energy storage soft switch and improve the voltage distribution of the system.
The following are the attached tables:
TABLE 1 improvement of arithmetic load access position and power of distribution network in Tianjin North Chen demonstration area
Figure BDA0003326335960000151
Figure BDA0003326335960000161
TABLE 2 improved arithmetic circuit parameters of distribution network in Tianjin North Chen demonstration area
Figure BDA0003326335960000162
TABLE 3 distributed Power Access location and Capacity
Figure BDA0003326335960000163
Figure BDA0003326335960000171
TABLE 4 daily operating costs for each distribution network region
Figure BDA0003326335960000172
TABLE 5 Intelligent energy storage Soft-on-off daily operating profit
Figure BDA0003326335960000173
Towards flexible interconnection distribution network electric energy transaction device of soft switch of intelligent energy storage, the device includes as follows:
the cost function establishing module is used for forming a cost function of the transaction power in the time period t 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 power flow constraint and 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 energy storage soft switch active power scheduling result obtaining module is used for the intelligent energy storage soft switch to obtain a lower-layer end-to-end electric energy trading result and a cost function according to the obtained lower-layer end-to-end electric energy trading result, and to perform upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each interconnected power distribution network region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
the optimal reactive power output acquisition module of the intelligent energy storage soft switch is used for acquiring the optimal reactive power output of the intelligent energy storage soft switch according to a cost function in each interconnected power distribution network region based on the active power of the intelligent energy storage soft switch and an energy storage link scheduling result;
and the transaction settlement module is used for settling between the power distribution network areas according to end-to-end transaction results, dividing the two profits of settlement of the intelligent soft switch and each area into a difference with the adjustment and compensation of active transaction, and settling the actual purchase and sale electric quantity of the power distribution network areas according to the final transaction results and the superior power grid.
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 above electric energy transaction method for the flexible interconnected power distribution network facing the intelligent energy storage soft switch; 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, wherein the computer program when executed by the processor implements the steps of the above method for trading electric energy in a flexible interconnected power distribution network facing a smart energy storage soft switch; 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 (10)

1. The flexible power distribution network electric energy transaction method oriented to the intelligent energy storage soft switch is characterized by comprising the following steps:
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 minimum node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring 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;
according to the obtained lower-layer end-to-end electric energy trading result and the cost function, the intelligent energy storage soft switch carries out upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each interconnected power distribution network region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
based on the active power of the intelligent energy storage soft switch and the energy storage link scheduling result, the optimal reactive power output of the intelligent energy storage soft switch is obtained in each interconnected power distribution network region according to a cost function;
and (4) settlement is carried out between the distribution network areas according to end-to-end transaction results, the intelligent soft switch and the two-time profit of settlement of each area are divided into the difference with the adjustment and compensation of active transaction, and the actual purchase and sale electric quantity settlement is carried out between the distribution network areas and the superior power grid according to the final transaction results.
2. The electric energy transaction method for the flexible power distribution network oriented to the intelligent energy storage soft switch 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:
Figure FDA0003326335950000011
Figure FDA0003326335950000012
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;
Figure FDA0003326335950000013
the electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure FDA0003326335950000014
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure FDA0003326335950000015
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;
Figure FDA0003326335950000016
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;
Figure FDA00033263359500000217
which is the square of the nominal voltage at node i.
3. The electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch as claimed in claim 2, wherein the power flow constraint is as follows:
Figure FDA0003326335950000021
Figure FDA0003326335950000022
Figure FDA0003326335950000023
Figure FDA0003326335950000024
Figure FDA0003326335950000025
Vi，t-Vj，t＝2(RijPij，t+XijQij，t) (8)
in the formula (I), the compound is shown in the specification,
Figure FDA0003326335950000026
branch and node sets of the region k respectively;
Figure FDA0003326335950000027
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, a time period tActive and reactive power flowing through the branch ik; pi，t、Qi，tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;
Figure FDA0003326335950000028
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure FDA0003326335950000029
injecting active power into the intelligent energy storage soft switch at an access node;
Figure FDA00033263359500000210
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 electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch as claimed in claim 3, wherein the system safe operation constraints are as follows:
Figure FDA00033263359500000211
Figure FDA00033263359500000212
in the formula, omegaTA set of trade periods for a trade day; i isij，tThe current value of the branch ij is squared;
Figure FDA00033263359500000213
the upper limit of the square value of the current of the branch ij;
Figure FDA00033263359500000214
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:
Figure FDA00033263359500000215
Figure FDA00033263359500000216
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:
Figure FDA0003326335950000031
Figure FDA0003326335950000032
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 intelligent energy storage soft switch performs upper active power transaction adjustment and internal energy storage link output strategy solving with the goal of minimizing the sum of cost change compensation in transaction adjustment of each interconnected power distribution network region according to the obtained lower end-to-end electric energy transaction result and the cost function, and the method for obtaining the intelligent energy storage soft switch active power scheduling result comprises the following steps:
the objective function of the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch can be expressed as follows:
Figure FDA0003326335950000033
Figure FDA0003326335950000034
Figure FDA0003326335950000035
in the formula (I), the compound is shown in the specification,
Figure FDA0003326335950000036
setting the actual active power of the intelligent energy storage soft switch to be determined in the transaction adjustment for a time period t region k;
Figure FDA0003326335950000037
active trading power determined for a region k in a lower layer end-to-end electric energy trading in a time period t;
Figure FDA0003326335950000038
is an active power adjustment;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the equality relationship between the end-to-end electric energy transaction adjustment quantity of each area and the balance power bought or sold to the superior power grid can be expressed as follows:
Figure FDA0003326335950000039
in the formula (I), the compound is shown in the specification,
Figure FDA00033263359500000310
respectively is the balance power purchased and sold by the superior power grid in the time period t region k due to the end-to-end electric energy transaction adjustment;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the operation constraint of the intelligent energy storage soft switch can be expressed as:
Figure FDA00033263359500000311
Figure FDA00033263359500000312
Figure FDA0003326335950000041
Figure FDA0003326335950000042
Figure FDA0003326335950000043
Figure FDA0003326335950000044
Figure FDA0003326335950000045
in the formula (I), the compound is shown in the specification,
Figure FDA0003326335950000046
the loss power of the converter port of the intelligent energy storage soft switch in the region k time period t is measured;
Figure FDA0003326335950000047
the charging and discharging power of an internal energy storage link of the intelligent energy storage soft switch is provided; a. theSOPLoss coefficient of the intelligent energy storage soft switching converter;
Figure FDA0003326335950000048
the reactive power of the intelligent energy storage soft switch at the port of the converter in the area k is set for a time t; sSOPCapacity of the intelligent energy storage soft switching converter; emax、EminRespectively an upper limit and a lower limit of the energy storage charge state; eOStoring an initial state of charge for a transaction day; pES，maxIs an energy storage charging and discharging power limit value;
in the active power transaction adjustment and internal energy storage link scheduling method based on the intelligent energy storage soft switch, the transaction adjustment constraint is expressed as:
Figure FDA0003326335950000049
in the formula (I), the compound is shown in the specification,
Figure FDA00033263359500000410
the upper limit and the lower limit of the active output of the intelligent energy storage soft switch at the port of the converter are obtained by solving according to the regional operation constraint.
6. The electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch as claimed in claim 1, wherein based on the active power of the intelligent energy storage soft switch and the scheduling result of the energy storage link, the method for obtaining the optimal reactive power of the intelligent energy storage soft switch by each interconnected power distribution network region according to the cost function is as follows:
in the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the objective function of each region can be expressed as:
Figure FDA00033263359500000411
Figure FDA00033263359500000412
Figure FDA00033263359500000413
in the formula, ζi，kA branch set from a node i to a source node in a region k; zetaSOP，kA branch set from an intelligent energy storage soft switch access node to a source node in a region k is formed;
Figure FDA0003326335950000051
adjusting the result for the upper layer active power transaction; rij、XijThe resistance and reactance of branch ij are respectively;
Figure FDA0003326335950000052
cost of voltage offset by linear current analysis
Figure FDA0003326335950000053
The analytical expression of (1);
Figure FDA0003326335950000054
the square value of the initial voltage of the node i before transaction;
in the reactive power optimization scheduling method based on the intelligent energy storage soft switch, the reactive power scheduling constraint can be expressed as:
Figure FDA0003326335950000055
Figure FDA0003326335950000056
Figure FDA0003326335950000057
in the formula (I), the compound is shown in the specification,
Figure FDA0003326335950000058
is a node set in the region k;
Figure FDA0003326335950000059
is a branch set in the region k;
Figure FDA00033263359500000510
V ithe upper limit and the lower limit of the voltage square value of the node i are respectively;
Figure FDA00033263359500000511
the upper limit of the square of the current for branch ij.
7. 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 electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch is characterized in that the electric energy transaction between the power distribution network areas is settled according to end-to-end transaction results, the intelligent soft switch and each area are settled to obtain two profits which are divided into a difference with the adjustment and compensation of active transaction, and the method for the power distribution network areas to settle the actual purchase and sale electric quantity with the superior power network according to the final transaction results is as follows:
settlement is carried out among all interconnected power distribution network areas according to the trading power and clearing price, and trading income is proportionally distributed to the intelligent energy storage soft switch to serve as profit in all the interconnected power distribution network areas; according to the active power transaction adjustment result, the intelligent energy storage soft switch and each area perform compensation settlement of transaction adjustment cost change; according to the reactive power scheduling result, each interconnected power distribution network region distributes the cost reduction amount brought by the reactive power scheduling to the intelligent energy storage soft switch in proportion to be used as profit; and (4) settling the interconnected power distribution network areas and the superior power network according to the actual transmission power and the electric energy price.
8. Flexible distribution network electric energy transaction device towards soft switch of intelligent energy storage, its characterized in that, the device includes as follows:
the cost function establishing module is used for forming a cost function of the transaction power in the time period t 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 power flow constraint and 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 energy storage soft switch active power scheduling result obtaining module is used for the intelligent energy storage soft switch to obtain a lower-layer end-to-end electric energy trading result and a cost function according to the obtained lower-layer end-to-end electric energy trading result, and to perform upper-layer active power trading adjustment and internal energy storage link output strategy solving by taking the minimum sum of cost change compensation in trading adjustment of each interconnected power distribution network region as a target to obtain an intelligent energy storage soft switch active power scheduling result;
the optimal reactive power output acquisition module of the intelligent energy storage soft switch is used for acquiring the optimal reactive power output of the intelligent energy storage soft switch according to a cost function in each interconnected power distribution network region based on the active power of the intelligent energy storage soft switch and an energy storage link scheduling result;
and the transaction settlement module is used for settling between the power distribution network areas according to end-to-end transaction results, dividing the two profits of settlement of the intelligent soft switch and each area into a difference with the adjustment and compensation of active transaction, and settling the actual purchase and sale electric quantity of the power distribution network areas according to the final transaction results and the superior power grid.
9. 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 1-7.
10. 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 7 when executed by the processor.
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