CN112381421B - Source network load multi-main-body game planning method considering full dimensionality of power market - Google Patents

Source network load multi-main-body game planning method considering full dimensionality of power market Download PDF

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CN112381421B
CN112381421B CN202011287828.1A CN202011287828A CN112381421B CN 112381421 B CN112381421 B CN 112381421B CN 202011287828 A CN202011287828 A CN 202011287828A CN 112381421 B CN112381421 B CN 112381421B
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CN112381421A (en
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杨楠
丁力
刘钊
黄悦华
邾玢鑫
李振华
刘颂凯
张涛
张磊
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China Three Gorges University CTGU
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    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/067—Enterprise or organisation modelling
    • 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
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    • 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
    • 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • 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
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    • 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

Abstract

A source network load multi-subject game planning method considering the full dimensionality of a power market comprises the following specific steps: based on the overall angle of the power market operation, an independent system operator is brought into a game planning system, a power transmission utility calculation method considering power transmission control characteristics is introduced, and a source-network-load multi-main-body planning game model from power generation to a power utilization complete power market operation mechanism is constructed; then, considering the game relation among the main bodies, and constructing a full-dimensional game decision framework from power generation to power utilization power market; and finally, solving the model by adopting an iterative search method to obtain a final planning scheme.

Description

Source network load multi-main-body game planning method considering full dimensionality of power market
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a source network load multi-main-body game planning method considering the full dimensionality of a power market.
Background
The continuous push of market reformation of electric power in the global scope brings a series of opportunities and challenges for the development of the electric power industry. On one hand, the traditional power transmission planning does not flexibly adjust the power price strategy in time according to the user requirements when calculating the power transmission utility; on the other hand, the resource allocation capacity of the power system can be fully improved based on the overall angle of the power market when the planning model is constructed. Therefore, the research of the traditional planning method focuses on solving the problems of new energy consumption, demand side response and the like in the system planning process. Although the method can improve the efficiency of system investment planning to a certain extent, the method does not fully simulate the full-dimensional game decision process including ISO and source network load planning main bodies, and lacks the vitality of resource allocation. Thus, there are also the following problems:
1) since in the mature power market the utility of different bodies of the source grid charge (especially for the transmission companies) depends not only on the node price, it is also influenced by the market operating regime (ISO decision, transmission organisation, blocking situation, etc). Therefore, the method directly taking the node marginal price result as the decision information of each main body is often only used for planning the decision of the main body for a single or part in the planning, so the considered ISO decision is only related to the information interaction with the part of the market main body (other market information is generally fixed). In fact, in a mature electric power market, a source, a network, a load and an ISO form a complete information interaction and game interaction relationship, decision information provided by the ISO not only has node electricity price, but also comprises unit output and unit utility rate parameters of a power transmission company, and the change of ISO decision boundary conditions can be caused by the updating of a planning scheme of any one investment subject of the source, the network and the load in a game process, so that the accurate simulation of an electric power market planning decision can be realized only by establishing a full-dimensional decision framework including the ISO;
2) the traditional planning method is simple to calculate the utility of the power transmission company (the investment operation rate or the utility is simply calculated), and the planning utility and the rate of the power transmission company are basically not calculated from the perspective of the actual power market. In the mature electricity market, the utility of different sources, grids, and loads (especially for transmission companies) is not only dependent on node electricity prices, but is also influenced by uncertainty factors (ISO decisions, transmission organizations, congestion conditions, and other factors). Only when all market elements are completely considered in a planning model of a power transmission company, the planning result can be guaranteed to effectively relieve congestion and reduce the marginal price of electricity of the nodes, so that the planning investment efficiency of the whole power system is further improved.
Therefore, under the background, research on dynamic game behaviors capable of comprehensively analyzing source-network-load and ISO complete market elements has important theoretical and practical significance for realizing accurate simulation of power market planning decisions and improving planning investment efficiency of the whole power system.
Disclosure of Invention
The invention aims to provide a source network load multi-main-body game planning method which can realize more accurate simulation on power market planning decisions.
The purpose of the invention is realized by adopting the following technical scheme:
a source network load multi-subject game planning method considering the full dimensionality of a power market comprises the following processes:
step 1: introducing a power transmission utility calculation method considering power transmission control characteristics, and constructing a power transmission company planning model considering monopoly control and market operation;
step 2: establishing a source network load planning model considering a multi-market main body by taking power supply new establishment and distributed power supply operation as decision variables;
and step 3: providing a source-network-load planning game decision framework considering the operation of the power market;
and 4, step 4: and solving Nash equilibrium to obtain a planning scheme of the final model.
In the step 1, when a power transmission utility calculation method considering power transmission control characteristics is introduced and a power transmission company planning model is constructed, an objective function of the power transmission utility calculation method is composed of power transmission service income and reliability cost, and a line operation rate is calculated by dividing lines based on power price and power flow data, so that reasonable guidance of a power transmission line planning market is ensured.
The objective function is specifically shown in formula (1):
Figure RE-GDA0002884122460000021
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000022
vector set for planning transmission line project, wherein
Figure RE-GDA0002884122460000023
mT∈ΩmTAll variables are 0-1 variables, and represent whether a project for planning the power transmission line is newly built or not;
Figure RE-GDA0002884122460000024
a set of planned capacity expansions representing a power transmission company line;
Figure RE-GDA0002884122460000025
mT∈ΩmTthe capacity expansion capacity of each planned line is represented; omegamTRepresenting a set of planned transmission line projects;
Figure RE-GDA0002884122460000026
the transmission rate of the first line; u shapeTraIs the total utility of the transmission company;
Figure RE-GDA0002884122460000027
revenue for transmission services of the transmission company;
Figure RE-GDA0002884122460000031
a maintenance utility for operation;
Figure RE-GDA0002884122460000032
to the operational utility;
Figure RE-GDA0002884122460000033
utility for other services such as communications;
Figure RE-GDA0002884122460000034
reliability utility of line l in year t; psiesLoss in power failure is unit; EENSl,tThe expected value of the power shortage of the circuit l in the t year; omegalIs a line set;
wherein the utility of operation and maintenance in transmission service revenue for a transmission company
Figure RE-GDA0002884122460000035
Operational utility
Figure RE-GDA0002884122460000036
Other service utilities of communication
Figure RE-GDA0002884122460000037
Is expressed by equation (2):
Figure RE-GDA0002884122460000038
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000039
maximum power value flowing through line l for year t; pl capIs the capacity of line l; pl lenIs the length of line l;
Figure RE-GDA00028841224600000310
modeling and analyzing the rate for the unit capacity of the power transmission company;
Figure RE-GDA00028841224600000311
operating rates for unit active power of the transmission company; sigmamOperating rates for the transmission lines per unit capacity; sigmacOther service rates such as unit length transmission line communication; relevant parameters involved in specific utility calculations, e.g.
Figure RE-GDA00028841224600000312
σmAnd σcAll are obtained by ISO in the decision stage;
the constraint conditions comprise newly-built line investment constraint, branch power flow constraint and safety constraint;
(1) newly-built line quantity constraint
Figure RE-GDA00028841224600000313
(2) Branch current flow restraint
Figure RE-GDA00028841224600000314
In the formula: pi.tAnd Qi.tActive power and reactive power of a node i at the moment t respectivelyRate; u shapei.tAnd Uj.tThe voltage amplitudes of the node i and the node j at the moment t are respectively; gijAnd BijConductance and susceptance of branch ij, respectively; thetaijIs the phase angle difference between the voltages of the node i and the node j;
(3) safety restraint
Figure RE-GDA0002884122460000041
In the formula: u shapei.minAnd Ui.maxRespectively is the lower limit and the upper limit of the voltage amplitude of the node i at any typical time t; pij.tAnd Pij.maxRespectively the transmission power of branch ij at any typical time t and its upper limit value.
In step 2, the power generation company carries out location and volume fixing on the newly added unit in the power system planning, the objective function of the planning model of the power generation company is composed of the electricity selling utility and the operation rate of the existing unit, and the decision variables are the position and the capacity of the newly added unit.
In step 2, the objective function is shown in equation (6);
Figure RE-GDA0002884122460000042
in the formula of UGenRepresents the total utility of the power generation company;
Figure RE-GDA0002884122460000043
for planning vector sets of generator set projects, wherein
Figure RE-GDA0002884122460000044
mG∈ΩmGAll the variables are 0-1 variable, and represent whether the generator set project is newly built or not, and omegamGA set of project for planning a power generation group;
Figure RE-GDA0002884122460000045
representing a set of unit planning capacities of a power generation company, wherein
Figure RE-GDA0002884122460000046
mG∈ΩmGRepresenting the planned capacity of each generator set project;
Figure RE-GDA0002884122460000047
quoting information for power generation; lambda [ alpha ]pnRepresenting the marginal price of the node at the node n;
Figure RE-GDA0002884122460000048
the utility of selling electricity for the generator set of the power generation company;
Figure RE-GDA0002884122460000049
the operating cost of the generating company unit; r is the discount rate; t is the year of engineering operation;
Figure RE-GDA00028841224600000410
the power selling quantity at the time of the n nodes t is; omegatIs the set of peak load typical time T in the T year; omegaTIs a planning cycle set; omegaNIs a node set;
Figure RE-GDA00028841224600000411
the unit operation rate of the generator set;
the constraint conditions comprise the quantity constraint of the newly built generating set and the output upper and lower limit constraints of the newly built generating set:
(1) newly-built unit quantity restraint of can generating electricity
Figure RE-GDA00028841224600000412
(2) Newly-built generator set output upper and lower limit restraint
Figure RE-GDA0002884122460000051
In the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000052
respectively output for newly built generator
Figure RE-GDA0002884122460000053
Upper and lower limits of.
If the planning model is constructed for the large power user company, the objective function is shown as (9):
Figure RE-GDA0002884122460000054
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000055
to plan a vector set of DG projects, wherein
Figure RE-GDA0002884122460000056
mU∈ΩmUAll variables are 0-1 variables, which indicate whether a DG project is planned to be newly built or not;
Figure RE-GDA0002884122460000057
a vector set representing the number of planned distributed power supply units of the large power users;
Figure RE-GDA0002884122460000058
representing the total distributed power supply construction capacity of each planning scheme; mU is belonged to omegamURepresenting a set for planning a newly built DG project;
Figure RE-GDA0002884122460000059
the electricity purchasing quantity from the main network is provided for the user; u shapeUseThe utility of the electricity cost of the user;
Figure RE-GDA00028841224600000510
the utility of the electricity purchasing cost of the user;
Figure RE-GDA00028841224600000511
purchasing electricity cost and utility for the main network of the user;
Figure RE-GDA00028841224600000512
generating revenue for the distributed power;
Figure RE-GDA00028841224600000513
cost effectiveness for equipment operation and maintenance;
Figure RE-GDA00028841224600000514
the output of the distributed power supply c at the n node at the time t; omegacA set of distributed power sources c at n nodes;
Figure RE-GDA00028841224600000515
operating maintenance rate for unit DG output;
wherein, the electricity purchasing cost utility of the large power users
Figure RE-GDA00028841224600000516
The calculation formula of the main grid electricity purchasing cost and the distributed power generation income is shown as the formula (10):
Figure RE-GDA00028841224600000517
in the formula (f)n,tThe peak load of the node n at the time t in the planning period is obtained;
the constraint conditions of the planning model of the large power user mainly comprise DG (distributed generation) candidate node access number limitation, DG permeability constraint and DG output constraint;
(1) DG candidate node access number limitation
Figure RE-GDA00028841224600000518
In the formula: n is a radical ofi.minAnd Ni.maxRespectively is a lower limit value and an upper limit value of the DG number accessed to the node i to be selected;
(2) node power balance constraints
Figure RE-GDA0002884122460000061
In the formula: q. q.sn,tThe method comprises the steps of (1) purchasing electric quantity of a node n at the time t for peak load in a planning period;
Figure RE-GDA0002884122460000062
generating capacity of a distributed power supply at a node n at the moment t;
Figure RE-GDA0002884122460000063
the total load of the n nodes at the time t is obtained;
(3) DG output constraint
Figure RE-GDA0002884122460000064
In the formula:
Figure RE-GDA0002884122460000065
and
Figure RE-GDA0002884122460000066
respectively the lower limit and the upper limit of DG output;
(4) the newly built DG capacity of the large power users has the following relationship constrained by the equation:
Figure RE-GDA0002884122460000067
in step 4, for the proposed dynamic game model, nash equilibrium is solved by an iterative search method, and the specific solving steps are as follows:
1) input raw data and parameters: initializing data required by establishing a game model, wherein the data comprises load information, parameters of a set to be newly built, parameters of a line to be newly built, parameters of a distributed power source to be newly built, quotations of each set of a power generation company, original network topology parameters of related parameters of power market operation and the like;
2) generating a game participant strategy set: power generation maleGenerating a planning strategy set of a power generation company according to a set to be selected of the newly-built unit
Figure RE-GDA0002884122460000068
Generating a power grid planning strategy set by a power transmission company according to the candidate set of the power transmission line
Figure RE-GDA0002884122460000069
A user generates a distributed power supply construction strategy set according to the distributed power supply candidate set
Figure RE-GDA00028841224600000610
mG, mT and mU are the total number of elements in a power generation company, a power transmission company and a power large user strategy set in sequence;
3) randomly extracting a group of planning strategy schemes from the three participant strategy sets as initial values of the planning schemes;
4) setting an iteration initial value delta to be 2;
5) and (3) carrying out scheme optimization by the participants: each participant carries out decision making, checking and calculation on the planning scheme of the participant according to the information of other participants in the previous round, and the final effect of the three parties in the game round is obtained after load flow calculation and electricity price calculation;
6) judging whether the balance state is achieved: if the effectiveness of the two continuous game rounds is the same, the balance state is considered to be achieved, and the step 4.7 is entered; if not, making k equal to k +1, and returning to the step 4.5;
4.7) output model equalization solution
Figure RE-GDA0002884122460000071
And the ultimate utility of the parties.
A construction method of a source-network-load planning game decision architecture comprises the following steps:
step 1) a power generation company provides a power supply location and capacity scheme (X) according to a grid structure scheme obtained by a power transmission company through decision and a power generation output plan obtained through ISO calculationGen,NGen) And power generation quotation information
Figure RE-GDA0002884122460000072
Step 2) the power generation company transmits the position and capacity information of the power supply to a power transmission company and transmits power generation quotation information to ISO; the utility calculation parameters of unit rates transmitted by a power transmission company according to the ISO in the day are combined with the power position and capacity information provided by a power generation company and the electricity purchasing amount information of the large-power users
Figure RE-GDA0002884122460000073
Making a circuit upgrading scheme by decision making to form a new grid structure;
step 3) determining the transmission rate of the transmission company at the same time
Figure RE-GDA0002884122460000074
And combines the grid structure information (X)Tra,NTra) Transmitting to power generation company, transmitting power transmission rate information to large electric power user, and transmitting power transmission network parameter (line length P)l lenLine capacity Pl capTransmission current constraint) to ISO;
step 4) the large power user combines the ISO calculated node marginal power price SP according to the determined power transmission rate of the power transmission companypiInvestment plan for making order electricity and DG (X)Use,NUse) And feeding back the purchased electric quantity information to the transmission company and ISO;
step 5) ISO carries out decision making by collecting information of source-network-load three parties, establishes unit rate utility calculation parameters according to power transmission network parameters of a power transmission company and transmits the unit rate utility calculation parameters to the power transmission company, and makes an output plan P of the power generation companygMeanwhile, the node marginal electricity price is calculated, and finally, the node marginal electricity price information is transmitted to a power generation company and a power consumer.
The objective function of the power consumer planning model is shown as (15):
Figure RE-GDA0002884122460000075
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000076
to plan a vector set of DG projects, wherein
Figure RE-GDA0002884122460000077
mU∈ΩmUAll variables are 0-1 variables, which indicate whether a DG project is planned to be newly built or not;
Figure RE-GDA0002884122460000081
a vector set representing the number of planned distributed power supply units of the large power users;
Figure RE-GDA0002884122460000082
representing the total distributed power supply construction capacity of each planning scheme; mU is belonged to omegamURepresenting a set for planning a newly built DG project;
Figure RE-GDA0002884122460000083
the electricity purchasing quantity from the main network is provided for the user; u shapeUseThe utility of the electricity cost of the user;
Figure RE-GDA0002884122460000084
the utility of the electricity purchasing cost of the user;
Figure RE-GDA0002884122460000085
purchasing electricity cost and utility for the main network of the user;
Figure RE-GDA0002884122460000086
generating revenue for the distributed power;
Figure RE-GDA0002884122460000087
cost effectiveness for equipment operation and maintenance;
Figure RE-GDA0002884122460000088
the output of the distributed power supply c at the n node at the time t; omegacA set of distributed power sources c at n nodes;
Figure RE-GDA0002884122460000089
operating maintenance rate for unit DG output;
wherein, the electricity purchasing cost utility of the large power users
Figure RE-GDA00028841224600000810
The calculation formula of the main grid electricity purchasing cost and the distributed power generation income is shown as the formula (16):
Figure RE-GDA00028841224600000811
in the formula (f)n,tThe peak load of the node n at the time t in the planning period is obtained;
the constraint conditions of the planning model of the large power user mainly comprise DG (distributed generation) candidate node access number limitation, DG permeability constraint and DG output constraint;
(1) DG (distributed generation) candidate node access number limitation
Figure RE-GDA00028841224600000812
In the formula: n is a radical ofi.minAnd Ni.maxRespectively is a lower limit value and an upper limit value of the DG number accessed to the node i to be selected;
(2) node power balance constraints
Figure RE-GDA00028841224600000813
In the formula: q. q.sntThe method comprises the steps of (1) purchasing electric quantity of a node n at the time t for peak load in a planning period;
Figure RE-GDA00028841224600000814
generating capacity of a distributed power supply at a node n at a time t;
Figure RE-GDA00028841224600000815
for total load of n nodes at time t；
(3) DG output constraint
Figure RE-GDA00028841224600000816
In the formula:
Figure RE-GDA00028841224600000817
and
Figure RE-GDA00028841224600000818
respectively the lower limit and the upper limit of DG output;
(4) the newly built DG capacity of the large power users has the following relationship constrained by the equation:
Figure RE-GDA0002884122460000091
in the formula, omegawIs a set of generator sets w; pgwIs the output of the generator set w; pg＝[Pg1,Pg2,…,Pgw]The vector set of the output of each generator set; f. ofpw(. cndot.) is a scheduling function.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1) the invention can realize more accurate simulation on the planning decision of the power market;
2) the invention can technically improve the planning investment efficiency of the whole power system.
Drawings
FIG. 1 is a diagram of the body transfer relationships;
FIG. 2 is a diagram of the analysis of the dynamic gaming behavior of subjects;
FIG. 3 is a schematic diagram of planning results;
fig. 4 is a graph of the incoming power at peak load for each line for both methods.
Detailed Description
A source network load multi-subject game planning method considering the full dimensionality of a power market mainly comprises the following steps:
1) based on the overall angle of the electric power market operation, an independent system operator ISO is brought into a game planning system, a power transmission utility calculation method considering the power transmission control characteristics is introduced, and a power transmission company planning model considering monopoly control and market operation is constructed;
2) establishing a source network load planning model considering a multi-market main body by taking power supply new establishment and distributed power supply operation as decision variables;
3) considering the game relation among the main bodies, providing a source-network-load planning game decision framework considering the operation of the power market;
4) and solving Nash equilibrium by adopting an iterative search method to obtain a planning scheme of a final model.
Further, in the step 1), the transmission company plans the transmission network in the power system planning, the goal is to maximize its utility, and the decision variable is a scheme for expanding the newly-built line. According to the invention, a power transmission utility calculation method considering power transmission control characteristics is introduced, a planning model of a power transmission company is constructed, an objective function of the power transmission company is composed of power transmission service income and reliability cost, wherein in order to play resource configuration advantages and improve planning efficiency while supervising the power transmission company, a utility calculation project is specifically subdivided into three utility calculation modes of operation maintenance, operation management and service income by referring to the power transmission utility calculation method of the American mature power market by the utility of the power transmission company, and planning and profitability of the power transmission company are ensured on the basis of the three utility calculation modes. Meanwhile, the line operation rate is obtained by branch line accounting based on the electricity price and tidal current data, and the unit utility rate calculation parameters involved in the calculation of the utility are obtained by the ISO in the market clearing stage, so that the reasonable guidance of the power transmission line planning market is ensured. The objective function is specifically shown in formula (1).
The objective function is specifically shown in formula (1).
Figure RE-GDA0002884122460000101
In the formula (I), the compound is shown in the specification,
Figure RE-GDA0002884122460000102
vector set for planning transmission line project, wherein
Figure RE-GDA0002884122460000103
mT∈ΩmTAll variables are 0-1 variables, and represent whether a project for planning the power transmission line is newly built or not;
Figure RE-GDA0002884122460000104
a set of planned capacity expansions representing a power transmission company line;
Figure RE-GDA0002884122460000105
mT∈ΩmTthe capacity expansion capacity of each planned line is represented; omegamTRepresenting a set of planned transmission line projects;
Figure RE-GDA0002884122460000106
the transmission rate of the first line; u shapeTraIs the total utility of the transmission company;
Figure RE-GDA0002884122460000107
revenue for transmission services of the transmission company;
Figure RE-GDA0002884122460000108
a maintenance utility for operation;
Figure RE-GDA0002884122460000109
to the operational utility;
Figure RE-GDA00028841224600001010
utility for other services such as communications;
Figure RE-GDA00028841224600001011
reliability utility of line l in year t; psiesLoss in power failure is unit; EENSl,tThe expected value of the power shortage of the circuit l in the t year; omegalIs a set of lines.
Wherein the transmission company transmitsOperational maintenance utility in electricity service revenue
Figure RE-GDA00028841224600001012
Operational utility
Figure RE-GDA00028841224600001013
Other service utilities of communication
Figure RE-GDA00028841224600001014
The solving formula of (2) is shown as the formula:
Figure RE-GDA00028841224600001015
in the formula (I), the compound is shown in the specification,
Figure RE-GDA00028841224600001016
maximum power value flowing through line l for year t; pl capIs the capacity of line l; pl lenIs the length of line l;
Figure RE-GDA00028841224600001017
modeling and analyzing the rate for the unit capacity of the power transmission company;
Figure RE-GDA00028841224600001018
operating rates for unit active power of the transmission company; sigmamOperating rates for the transmission lines per unit capacity; sigmacOther service rates such as unit length transmission line communication; relevant parameters involved in specific utility calculations, e.g.
Figure RE-GDA0002884122460000111
σmAnd σcAll derived from ISO in the decision phase.
The constraint conditions comprise newly-built line investment constraint, branch power flow constraint and safety constraint.
(1) Newly-built line quantity constraint
Figure RE-GDA0002884122460000112
(2) Branch current flow restraint
Figure RE-GDA0002884122460000113
In the formula: pi.tAnd Qi.tRespectively the active power and the reactive power of a node i at the moment t; u shapei.tAnd Uj.tThe voltage amplitudes of the node i and the node j at the moment t are respectively; gijAnd BijConductance and susceptance of branch ij, respectively; thetaijIs the phase angle difference between the voltages at node i and node j.
(3) Safety restraint
Figure RE-GDA0002884122460000114
In the formula: u shapei.minAnd Ui.maxRespectively is the lower limit and the upper limit of the voltage amplitude of the node i at any typical time t; pij.tAnd Pij.maxRespectively the transmission power of branch ij at any typical time t and its upper limit value.
And in the step 2), the power generation company mainly carries out site selection and volume determination on the newly added unit in the power system planning. The objective function of the planning model is composed of the electricity selling utility and the operation rate of the existing unit, and the decision variables are the position and the capacity of the newly added unit.
The specific objective function is shown in equation (6).
Figure RE-GDA0002884122460000115
In the formula of UGenRepresents the total utility of the power generation company;
Figure RE-GDA0002884122460000116
for planning vector sets of generator set projects, wherein
Figure RE-GDA0002884122460000117
mG∈ΩmGAll the variables are 0-1 variable, and represent whether the generator set project is newly built or not, and omegamGA set of project for planning a power generation group;
Figure RE-GDA0002884122460000121
representing a set of unit planning capacities of a power generation company, wherein
Figure RE-GDA0002884122460000122
mG∈ΩmGRepresenting the planned capacity of each generator set project;
Figure RE-GDA0002884122460000123
quoting information for power generation; lambda [ alpha ]pnRepresenting the marginal price of the node at the node n;
Figure RE-GDA0002884122460000124
the utility of selling electricity for the generator set of the power generation company;
Figure RE-GDA0002884122460000125
the operating cost of the generating company unit; r is the discount rate; t is the year of engineering operation;
Figure RE-GDA0002884122460000126
the power selling quantity at the time of the n nodes t is; omegatIs the set of peak load typical time T in the T year; omegaTIs a planning cycle set; omegaNIs a node set;
Figure RE-GDA0002884122460000127
the unit operation rate of the generator set.
The constraint conditions comprise the quantity constraint of the newly built generating set and the output upper and lower limit constraints of the newly built generating set:
(1) newly-built unit quantity restraint of can generating electricity
Figure RE-GDA0002884122460000128
(2) Newly-built generator set output upper and lower limit restraint
Figure RE-GDA0002884122460000129
In the formula (I), the compound is shown in the specification,
Figure RE-GDA00028841224600001210
respectively output for newly built generator
Figure RE-GDA00028841224600001211
Upper and lower limits of.
The power consumers with large power in the step 2) meet the power loads of the consumers in two ways: 1) purchasing electricity from a power generator, and transmitting the electricity through a power transmission network, wherein the electric energy settlement mode is the node marginal price of the node, and the power transmission rate is charged by the power transmitter according to a certain rate according to the peak load of the node; 2) the dependence on power generation companies and power transmission companies is reduced by building the distributed power supply, and the investment operation rate of the distributed power supply is borne by power users. The large power users mainly plan their own power consumption plans in the power system planning, the goal is to minimize their own power consumption rate, and the decision variable is the distributed power supply construction scheme. The objective function of the planning model of the large power user company constructed by the invention is composed of the electricity purchasing cost of the user and the DG operation and maintenance cost. The specific calculation formula is shown as (9):
Figure RE-GDA00028841224600001212
in the formula (I), the compound is shown in the specification,
Figure RE-GDA00028841224600001213
to plan a vector set of DG projects, wherein
Figure RE-GDA0002884122460000131
mU∈ΩmUAll variables are 0-1 variables, which indicate whether a DG project is planned to be newly built or not;
Figure RE-GDA0002884122460000132
a vector set representing the number of planned distributed power supply units of the large power users;
Figure RE-GDA0002884122460000133
representing the total distributed power supply construction capacity of each planning scheme; mU is belonged to omegamURepresenting a set for planning a newly built DG project;
Figure RE-GDA0002884122460000134
the electricity purchasing quantity from the main network is provided for the user; u shapeUseThe utility of the electricity cost of the user;
Figure RE-GDA0002884122460000135
the utility of the electricity purchasing cost of the user;
Figure RE-GDA0002884122460000136
purchasing electricity cost and utility for the main network of the user;
Figure RE-GDA0002884122460000137
generating revenue for the distributed power;
Figure RE-GDA0002884122460000138
cost effectiveness for equipment operation and maintenance;
Figure RE-GDA0002884122460000139
the output of the distributed power supply c at the n node at the time t; omegacA set of distributed power sources c at n nodes;
Figure RE-GDA00028841224600001310
the operating maintenance rate is the unit DG force.
Wherein, the electricity purchasing cost utility of the large power users
Figure RE-GDA00028841224600001311
The calculation formula of the main grid electricity purchasing cost and the distributed power generation income is shown as the formula (10):
Figure RE-GDA00028841224600001312
in the formula (f)n,tThe peak load of the node n at the time t in the planning period is shown.
The constraint conditions of the planning model of the large power user mainly comprise DG (distributed generation) candidate node access number limitation, DG permeability constraint and DG output constraint.
(1) DG candidate node access number limitation
Figure RE-GDA00028841224600001313
In the formula: n is a radical ofi.minAnd Ni.maxRespectively a lower limit value and an upper limit value of the DG number accessed to the node i to be selected.
(2) Node power balance constraints
Figure RE-GDA00028841224600001314
In the formula: q. q.sn,tThe method comprises the steps of (1) purchasing electric quantity of a node n at the time t for peak load in a planning period;
Figure RE-GDA00028841224600001315
generating capacity of a distributed power supply at a node n at the moment t;
Figure RE-GDA00028841224600001316
is the total load of the n nodes at time t.
(3) DG output constraint
Figure RE-GDA00028841224600001317
In the formula:
Figure RE-GDA00028841224600001318
and
Figure RE-GDA00028841224600001319
respectively, the lower limit and the upper limit of the DG output.
(4) The newly built DG capacity of the large power users has the following relationship constrained by the equation:
Figure RE-GDA0002884122460000141
the decision model of the ISO generated output plan in the step 2) is an optimal economic dispatching model, and the specific formula is as follows:
Figure RE-GDA0002884122460000142
in the formula, omegawIs a set of generator sets w; pgwIs the output of the generator set w; pg＝[Pg1,Pg2,…,Pgw]The vector set of the output of each generator set; f. ofpw(. cndot.) is a scheduling rate function.
The ISO scheduling cost calculation formula is as follows:
Figure RE-GDA0002884122460000143
in the formula, NGThe total number of the accessed generators; c. Cpw、bpw、apwIs the quoted price parameter of the generator set w.
The constraint conditions of the ISO power generation plan decision model are as follows:
(1) the equation is constrained to:
Figure RE-GDA0002884122460000144
in the formula, Pgw,QgwEach being a generator wActive and reactive power generation capacity; pdw,QdwRespectively the active and reactive loads of the generator w; u shapei,UjThe voltage amplitudes of nodes i and j, respectively; thetai,θjThe voltage phase angles of nodes i and j, respectively; y isijAdmittance matrix elements for the nodes; deltaijIs the admittance phase angle.
(2) Constraint of inequality
Figure RE-GDA0002884122460000145
In the formula, Pgwmax,PgwminRespectively as the active power P of the generator wgwThe upper and lower limits of (2) are constrained; qgwmax,QgwminRespectively as w reactive output Q of the generatorgwThe upper and lower limits of (2) are constrained; u shapeimax,UiminRespectively, node i voltage amplitude UiThe upper and lower limits of (2) are constrained; plIs the active power flowing through line l; plmaxAn upper limit constraint for the active power of the line l;
Figure RE-GDA0002884122460000151
indicating that power supply node n distributes the amount of power delivered by line i.
According to a marginal rate pricing theory, the marginal electricity price of the node is a micro-increment rate of system rate to injected power of each node, and on the basis of formulas (15) to (18), a Lagrangian function introducing a power flow equation is constructed by introducing a relaxation variable and a barrier function as follows:
Figure RE-GDA0002884122460000152
in the formula, lambda, beta and omega are Lagrange multiplier vectors; o, u are relaxation variables, wherein o, u are both greater than 0; p is the vector dimension of o and u; h (x) is an equality constraint in equation (17); g (x) g (P)gw,Qgw,Ui,Pl) Is an inequality constraint in equation (18); mu is a barrier factor and is greater than 0.
Wherein, a barrier function term is introduced to obtain an extended objective function as:
Figure RE-GDA0002884122460000153
the equality constraint for introducing relaxation quantization in the lagrange function is:
Figure RE-GDA0002884122460000154
the node marginal price of the active node n is obtained as follows:
Figure RE-GDA0002884122460000155
in the formula, denotes an optimal solution.
The transfer relationship of each main body involved in the full-dimensional source network load planning game decision model in the step 3) during planning decision is shown in fig. 1.
In the decision process, the power generation company provides a power supply location and capacity scheme (X) according to a grid structure scheme obtained by the decision of the power transmission company and a power generation output plan obtained by ISO calculationGen,NGen) And power generation quotation information
Figure RE-GDA0002884122460000156
Transmitting the position and capacity information of the power supply to a power transmission company, and transmitting power generation quotation information to an ISO (International organization for standardization); the utility calculation parameters of unit rates transmitted by a power transmission company according to the ISO in the day are combined with the power position and capacity information provided by a power generation company and the electricity purchasing amount information of the large-power users
Figure RE-GDA0002884122460000157
Making a circuit upgrading scheme by decision making to form a new grid structure;
simultaneous determination of transmission rates
Figure RE-GDA0002884122460000161
And combines the grid structure information (X)Tra,NTra) Transmitting to power generation company, transmitting power transmission rate information to large electric power user, and transmitting power transmission network parameter (line length P)l lenLine capacity Pl capTransmission current constraint) to ISO;
the large power users combine the ISO calculated node marginal price SP according to the determined power transmission rate of the power transmission companypiInvestment plan for making order electricity and DG (X)Use,NUse) And feeding back the purchased electric quantity information to the transmission company and ISO; ISO is an independent operation decision mechanism for the electricity market;
the method carries out decision by collecting information of a source-network-load party, makes unit rate utility calculation parameters according to power transmission network parameters of a power transmission company, transmits the unit rate utility calculation parameters to the power transmission company, and makes a power generation company output plan PgMeanwhile, the node marginal electricity price is calculated, and finally, the node marginal electricity price information is transmitted to a power generation company and a power consumer.
In the three market main bodies, for a power generation company and a power transmission company, because the decision needs to be checked through security check, and the security check is realized from the overall perspective of a power network by collecting information of each link of the source network load of the system, the decision of the power generation company and the power transmission company can be directly influenced and restricted by decision behaviors of other main bodies from the source network load by taking the security check as a core node, so that a game relationship is formed. For the user side, the decision is influenced both directly from the transmission company and indirectly from the generation company. Specifically, before a power transmission company makes a power transmission rate, the power transmission company firstly performs security verification of a power transmission network according to information such as a planned grid structure, and the like, so that a plurality of strategies with insufficient security performance are prevented from being transmitted to a power generation side and a user side, and further, the verified power transmission rate is transmitted to power users to influence the power utilization rate and decision thereof. The power generation company firstly reports the power generation rate to the ISO for decision, and then the ISO calculates the node marginal electricity price through independent operation optimization decision to influence the power consumption rate and decision of the power consumer. In general, the decisions of the three market subjects are independent and restricted, and the decision information is completely shared, so that a complete information game relationship is formed.
Because the planning and construction of the power system need to be completed together on the premise of independent decision, the power generation company, the power transmission company and the large power user mutually master all strategy information of each other in the planning process, the actions of the three have a sequence in the game process, and the game behavior schematic diagram is shown in fig. 2.
In a game round shown in fig. 2, ISO is taken as a special subject independent of source network load, is merged into a game planning system, plays a role in information transmission before a power generation company and a large power user, and gives a node marginal electricity price and a scheduling plan after receiving unit quotation information of the power generation company and a power utilization plan of the large power user. After receiving the electricity price information and the power transmission rate information, the large power user determines a power purchase plan and a construction plan of the distributed power supply by taking the minimum power consumption rate as a target, and feeds back the power purchase plan and the construction plan to ISO and power transmission companies. According to the electricity purchasing plan of the previous round of large power users and the power supply construction plan of the power generation company, the total utility of the power transmission network is maximized by adjusting the line construction scheme, and meanwhile, according to the newly-built line decision-making scheme of the previous round of power transmission company and the power utilization plan of the large power users, the power generation company adjusts the site selection and volume fixing scheme of the newly-built power generation unit to maximize the electricity selling utility of the power generation company. And entering the next game round after updating the location determination capacity, the network topology and the electricity purchasing plan of the newly-built unit.
In the game process, when any one of the power generation company, the power transmission company and the large power user changes the strategy and cannot obtain more utilities, the game reaches a balanced state, and the specific description is as follows:
Figure RE-GDA0002884122460000171
in the formula:
Figure RE-GDA0002884122460000172
all the strategies are own optimal strategies under the optimal strategy selected by the opposite side, and the power generation company, the power transmission company and the large power user can achieve the maximum effectiveness under the balanced meaning under the combination of the strategies; argmax (·) is the set of variables that maximizes the value of the objective function.
For the proposed dynamic game model in the step 4), Nash equilibrium is solved through an iterative search method, and the specific solving steps are as follows:
4.1) inputting raw data and parameters. Initializing data required by establishing a game model, wherein the data comprises load information, parameters of a set to be newly built, parameters of a line to be newly built, parameters of a distributed power source to be newly built, quotations of each set of a power generation company, original network topology parameters of related parameters of power market operation and the like;
4.2) generating a game participant strategy set. Generating a planning strategy set of the power generation company according to the set to be selected of the newly-built unit by the power generation company
Figure RE-GDA0002884122460000173
Generating a power grid planning strategy set by a power transmission company according to the candidate set of the power transmission line
Figure RE-GDA0002884122460000174
A user generates a distributed power supply construction strategy set according to the distributed power supply candidate set
Figure RE-GDA0002884122460000175
mG, mT, and mU are, in turn, the total number of elements in the power generation company, the transmission company, and the large electricity consumer policy set.
4.3) randomly extracting a group of planning strategy schemes from the three participant strategy sets as initial values of the planning schemes;
4.4) setting an iteration initial value delta to be 2;
4.5) participants to optimize the scheme. And each participant carries out decision making, checking and calculation on the own planning scheme again according to the information of other participants in the previous round, and the final effects of the three parties in the game round are obtained after load flow calculation and electricity price calculation. The method is based on an ISO scheduling model, and a node marginal electricity price of the system is calculated by adopting a primal-dual interior point method;
4.6) judging whether the equilibrium state is reached. If the effectiveness of the two continuous game rounds is the same, the balance state is considered to be achieved, and the step 4.7 is entered; if not, making k equal to k +1, and returning to the step 4.5;
4.7) output model equalization solution
Figure RE-GDA0002884122460000181
And the ultimate utility of the parties.
Example (b):
1. parameter setting
The invention selects a modified IEEE30 node system as a simulation example. The market pricing mechanism in the embodiment of the invention is the node marginal electricity price, the decision mechanism is the unit combination considering the safety constraint, and the planning period is 20 years. Assuming that a power generation company needs to newly build a power supply at nodes 1-6 as the load increases, relevant parameters of the newly-built power supply are shown in table 1. The fluctuation ratios mentioned in table 1 and below are effective fluctuation ratios.
TABLE 1 Power supply parameter table for power generation company
Figure RE-GDA0002884122460000182
According to load change in a power grid and development requirements of a power transmission company, a power transmission expansion plan is made, a line set to be upgraded and modified in a planning period is {2,6,16,28,35,32}, the utility fluctuation rate is {0.4,0.41,0.38,0.23,0.29,0.32}, and technical parameters of an expandable newly-built line are shown in a table 2.
TABLE 2 Capacity-expandable line parameter table for transmission company
Figure RE-GDA0002884122460000183
Relevant parameters of the distributed power supply which can be newly built by the large-power users are shown in the table 3.
Table 3 electric power big user newly-built distributed power supply parameter table
Figure RE-GDA0002884122460000184
Meanwhile, in order to verify the correctness and the effectiveness of the method, two different methods are added to solve the calculation example of the invention, and the result is compared and analyzed with the method of the invention, and the methods are as follows.
The method comprises the following steps: conventional planning methods in full dimensions are not considered. Namely, a planning model without considering the dynamic influence of ISO decision and the utility of a power transmission company;
the method 2 comprises the following steps: a full-dimensional planning method is considered. I.e. a planning model that takes into account the dynamic impact of ISO decisions and utility of the transmission company.
2. Simulation result
The results of the planning decision schemes of the market subjects obtained by performing simulation calculation in the above examples by using two methods are shown in table 4.
TABLE 4 planning scenarios and Total utilities for different market entities for each method
Figure RE-GDA0002884122460000191
As can be seen from Table 4, the planning scheme of the power generation company of the present invention is to newly build 10MW power supplies at nodes 1, 3 and 5; the planning scheme of the power transmission company is to upgrade and transform the line 6, the line 2, the line 16 and the line 35, and adopt 2 types of lines; the planning scheme for large power users is to newly build a 5MW distributed power supply at nodes 8, 19, 21 and 30. A schematic diagram of the planning results is shown in fig. 4.
3. Comparative analysis
1) Company of electric Power Transmission
First, the reliability cost, total income and total utility of the power transmission company of the schemes obtained by the methods 1 and 2 are compared, and the calculation results are shown in table 5.
TABLE 5 comparison of results calculated by two methods of the Power Transmission company (Wanyuan)
Figure RE-GDA0002884122460000192
As can be seen from table 5, the total revenue of method 2 is increased by 295.37 ten thousand yuan compared with method 1, the reliability cost is reduced by 300 ten thousand yuan compared with method 1, and thus the final total utility is increased by 595.37 ten thousand yuan compared with method 1. The main reasons are as follows: compared with the method 1, the method 2 does not simply take the marginal electricity price difference of the nodes and the cost utility as optimization targets, but carries out planning decision from the perspective of optimizing operation of the whole power market, so that one more line is expanded compared with the method 1. The circuit strengthens the structure of the power transmission grid structure on the whole. On one hand, the power flow of the power grid is optimized, and the power loss of a power transmission company is reduced, so that the reliability cost of the power transmission company is reduced; on the other hand, the utility of the power transmission company is increased by reducing the electricity consumption cost of the users and increasing the electricity selling amount from the whole power market perspective.
Therefore, compared with the method 1, the method 2 constructs a planning and planning model considering the market characteristics of the power transmission network, so that a power transmission company is prompted to make planning decisions from the macroscopic perspective of the utility of the whole market. The overall income of the project is guaranteed, meanwhile, the overall grid structure of the power transmission company is effectively strengthened, the overall electricity selling income is increased, and meanwhile, the operation cost is reduced, so that the overall utility of the power transmission company can be effectively improved.
2) Electric Power Generation Co Ltd
Comparing the total operation cost, total income and total utility of the power generation company of the schemes obtained by the method 1 and the method 2, the calculation result is shown in table 6.
TABLE 6 comparison of results calculated by two methods of Power Generation Co (Wanyuan)
Figure RE-GDA0002884122460000201
As can be seen from table 6, in terms of the total operating costs and the total revenue of all the units of the power generation company, in method 2, 34500 ten thousand yuan and 329000 ten thousand yuan are respectively increased compared to method 1, so that the total utility of the power generation company is increased by 363500 ten thousand yuan compared to method 1. The reason is that: on one hand, the method 2 optimizes the power transmission network structure from the overall perspective, and provides conditions for accepting more generator sets in the whole power market; on the other hand, the method 2 incorporates the ISO decision into a planning game system, ensures accounting of a power generation company and dynamic reflection of a power market in the planning decision process, and can improve the electricity selling amount by reducing the node marginal price of the system according to the dynamic game of the power market, thereby improving the total utility of the power generation company on the whole.
Therefore, in the method 2, besides using the node marginal electricity price information to guide different main body planning, the ISO is also taken as an independent main body to be incorporated into a planning system, so that a power generation company can fully consider the resource configuration optimization problem in the decision making process, the decision is made from the aspect of optimizing the electricity consumption of the whole electric power market while ensuring the utility of the project, and the maximum total utility is obtained by enhancing the market competitiveness of the power generation company.
3) Large power consumer
Comparing the project investment operating cost and income of the new project of the power consumers obtained by the method 1 and the method 2, and the total operating cost, the total income and the utility of the power consumers except the new project, the calculation result is shown in table 7, wherein the electricity consumption cost of the power consumers consists of the total income and the electricity purchasing cost, and the node marginal electricity price at the peak load of part of the nodes is shown in table 8.
TABLE 7 comparison of results calculated by two methods for big electric power users (Wanyuan)
Figure RE-GDA0002884122460000211
TABLE 8 marginal electricity price (Yuan) of node at peak load of partial node
Figure RE-GDA0002884122460000212
From table 7, the total operating cost and the total revenue of the electricity consumers are both 0. The main reasons are as follows: before the new project is built, the user does not have to stock distributed power supplies. The electricity purchasing cost and the total electricity consumption cost of the large-power users of the method 2 are reduced by 66521.63 ten thousand yuan compared with the method 1. The main reasons are as follows: the method 2 starts from the full dimension of the power market in the planning decision process, introduces the influence of ISO decision, and feeds back the newly-built information of the distributed power supply of the user to other market main bodies dynamically, thereby forming the market game. The grid structure of the power grid is strengthened from the overall perspective of the power market for the power transmission company, and meanwhile, the power generation company can adjust the planning decision scheme of the power generation company according to the dynamic response of the power market, so that the marginal price of the node is effectively reduced. Therefore, the power users can adjust the investment plans of the distributed power supplies according to the node power rates, and the total power consumption cost of the users is further reduced from the aspect of visitation.
Therefore, the method 2 introduces the ISO into the planning system, and can dynamically feed the planning information of the power generation company and the power transmission company back to the power consumers in each game round in the form of node marginal electricity price, so that the power consumers can realize the dynamic optimal balance between power purchase and the newly-built distributed power supply in the decision process according to the changed market information, and feed the relevant information back to the market in real time through the ISO, so that the decision of other main bodies is guided in the planning process, and the planning benefit of each main body is effectively improved.
Compared with the method 1, the method 2 has the advantages that the transmission power of the line 1, the line 7, the line 10 and the like is increased, so that the equipment utilization rate of the transmission line is improved, and the overall utility of a transmission company is increased. The main reasons are as follows: method 1 chooses to build the extension of lines No. 2 and No. 35, but does not build the 16 lines with higher marginal price of electricity of the nearby nodes. This is because the method 1 adopts the node marginal electricity price difference as a utility calculation model for power transmission network planning directly, and dynamic market feedback of ISO and other market bodies is not considered in the planning process. The planning method is used for planning decisions from the short-term project utility perspective of the power transmission network, and the construction cost of the 16 line is higher, so that the 16 line cannot be included in a planning scheme. This also results in the electricity price of part of the nodes being higher than that of method 2, directly increasing the electricity purchasing cost of the user and further resulting in the user selecting to enlarge the newly-built scale of the distributed power supply, thereby reducing the transmission power of part of the lines and reducing the utilization rate of the transmission equipment. Different from the method 1, the method 2 incorporates the ISO decision into a multi-subject game framework, and on the basis, a power transmission utility calculation method considering the power transmission control characteristics is further introduced to prompt a power transmission company to optimize a grid from the overall perspective of the power market, so that a 16-number line with higher cost is expanded besides the 2-number line and the 35-number line. The network capacity and the utility of a power generation company are increased while the congestion is relieved, meanwhile, the marginal price of the nodes is effectively reduced due to the extension of the lines and the increase of the units, and the electric quantity purchased by a user is increased, so that the transmission power of part of the lines is further increased, the utilization rate of power transmission equipment is improved, and the comprehensive utility of the power transmission company is further improved on the whole.
In conclusion, the idea of fully considering the full dimension in the planning process provided by the invention can effectively improve the planning benefit of each main body, and is accurate and effective.

Claims (2)

1. A source network load multi-subject game planning method considering the full dimensionality of a power market is characterized by comprising the following processes:
step 1: introducing a power transmission utility calculation method considering power transmission control characteristics, and constructing a power transmission company planning model considering monopoly control and market operation;
step 2: establishing a source network load planning model considering a multi-market main body by taking power supply new establishment and distributed power supply operation as decision variables;
and step 3: providing a source-network-load planning game decision framework considering the operation of the power market;
and 4, step 4: solving Nash equilibrium to obtain a planning scheme of a final model;
in the step 1, when a power transmission utility calculation method considering power transmission control characteristics is introduced and a power transmission company planning model is constructed, a target function of the power transmission utility calculation method is composed of power transmission service income and reliability cost, and a line operation rate is calculated by dividing lines based on power price and power flow data, so that reasonable guidance of a power transmission line planning market is ensured; the objective function of the power transmission company planning model is specifically shown in formula (1):
Figure FDA0003556558400000011
in the formula (I), the compound is shown in the specification,
Figure FDA0003556558400000012
vector set for planning transmission line project, wherein
Figure FDA0003556558400000013
All variables are 0-1 variables, and represent whether a project for planning the power transmission line is newly built or not;
Figure FDA0003556558400000014
a set of planned capacity expansions representing a power transmission company line;
Figure FDA0003556558400000015
the capacity expansion capacity of each planned line is represented; omegamTRepresenting a set of planned transmission line projects;
Figure FDA0003556558400000016
the transmission rate of the first line; u shapeTraIs the total utility of the transmission company;
Figure FDA0003556558400000017
revenue for transmission services of the transmission company;
Figure FDA0003556558400000018
a maintenance utility for operation;
Figure FDA0003556558400000019
to the operational utility;
Figure FDA00035565584000000110
is the utility of the communication;
Figure FDA00035565584000000111
reliability utility of line l in year t; psiesLoss in power failure is unit; EENSl,tThe expected value of the power shortage of the circuit l in the t year; omegalIs a line set;
wherein the utility of operation and maintenance in transmission service revenue for a transmission company
Figure FDA00035565584000000112
Operational utility
Figure FDA00035565584000000113
Utility of communication
Figure FDA00035565584000000114
Is expressed by equation (2):
Figure FDA0003556558400000021
in the formula (I), the compound is shown in the specification,
Figure FDA0003556558400000022
maximum power value flowing through line l for year t; pl capIs the capacity of line l; pl lenIs the length of line l;
Figure FDA0003556558400000023
modeling and analyzing the rate for the unit capacity of the power transmission company;
Figure FDA0003556558400000024
operating rates for unit active power of the transmission company; sigmamOperating rates for the transmission lines per unit capacity; sigmacCommunication rate for transmission line of unit length(ii) a Relevant parameters involved in specific utility calculations, e.g.
Figure FDA0003556558400000025
σmAnd σcAll are obtained by ISO in the decision stage;
the constraint conditions comprise newly-built line investment constraint, branch power flow constraint and safety constraint;
(1) newly-built line quantity constraint
Figure FDA0003556558400000026
(2) Branch current flow restraint
Figure FDA0003556558400000027
In the formula: pi.tAnd Qi.tRespectively the active power and the reactive power of a node i at the moment t; u shapei.tAnd Uj.tThe voltage amplitudes of the node i and the node j at the moment t are respectively; gijAnd BijConductance and susceptance of branch ij, respectively; thetaijIs the phase angle difference between the voltages of the node i and the node j;
(3) safety restraint
Figure FDA0003556558400000028
In the formula: u shapei.minAnd Ui.maxRespectively is the lower limit and the upper limit of the voltage amplitude of the node i at any typical time t; pij.tAnd Pij.maxThe transmission power and the upper limit value of the branch ij at any typical time t are respectively;
the power generation company carries out site selection and volume fixing on the newly added unit in the power system planning, the objective function of a planning model of the power generation company is composed of the electricity selling utility and the running rate of the existing unit, and the decision variables are the position and the capacity of the newly added unit; the objective function of the power generation company is shown in formula (6);
Figure FDA0003556558400000031
in the formula of UGenRepresents the total utility of the power generation company;
Figure FDA0003556558400000032
for planning vector sets of generator set projects, wherein
Figure FDA0003556558400000033
All the variables are 0-1 variables, and indicate whether the generating set project is newly built or not, and omegamGA set of project for planning a power generation group;
Figure FDA0003556558400000034
representing a set of unit planning capacities of a power generation company, wherein
Figure FDA0003556558400000035
Representing the planned capacity of each generator set project;
Figure FDA0003556558400000036
quoting information for power generation; lambda [ alpha ]pnRepresenting the marginal price of the node at the node n;
Figure FDA0003556558400000037
the utility of selling electricity for the generator set of the power generation company;
Figure FDA0003556558400000038
the operating cost of the generating company unit; r is the discount rate; t is the year of engineering operation;
Figure FDA0003556558400000039
the power selling quantity at the time of the n nodes t is; omegatIs the set of peak load typical time T in the T year; omegaTCompassesA cycle set is drawn; omegaNIs a node set;
Figure FDA00035565584000000310
the unit operation rate of the generator set;
the constraint conditions comprise the quantity constraint of the newly built generating set and the output upper and lower limit constraints of the newly built generating set:
(1) newly-built unit quantity restraint of can generating electricity
Figure FDA00035565584000000311
(2) Newly-built generator set output upper and lower limit restraint
Figure FDA00035565584000000312
In the formula (I), the compound is shown in the specification,
Figure FDA00035565584000000313
respectively output for newly built generators
Figure FDA00035565584000000314
Upper and lower limit constraints of (d);
the objective function of the power large user company planning model is shown as (9):
Figure FDA0003556558400000041
in the formula (I), the compound is shown in the specification,
Figure FDA0003556558400000042
to plan a vector set of DG projects, wherein
Figure FDA0003556558400000043
All variables are 0-1 variables, which indicate whether a DG project is planned to be newly built or not;
Figure FDA0003556558400000044
a vector set representing the number of planned distributed power supply units of the large power users;
Figure FDA0003556558400000045
representing the total distributed power supply construction capacity of each planning scheme; mU is belonged to omegamURepresenting a set for planning a newly built DG project;
Figure FDA0003556558400000046
the electricity purchasing quantity from the main network is provided for the user; u shapeUseThe utility of the electricity cost of the user;
Figure FDA0003556558400000047
the utility of the electricity purchasing cost of the user;
Figure FDA0003556558400000048
purchasing electricity cost and utility for the main network of the user;
Figure FDA0003556558400000049
generating revenue for the distributed power;
Figure FDA00035565584000000410
cost effectiveness is maintained for equipment operation;
Figure FDA00035565584000000411
the output of the distributed power supply c at the n node at the time t; omegacA set of distributed power sources c at n nodes;
Figure FDA00035565584000000412
operating maintenance rate for unit DG output;
wherein, the electricity purchasing cost utility of the large power users
Figure FDA00035565584000000413
The calculation formula of the main network electricity purchasing cost and the distributed power generation income in the system is shown as the formula (10):
Figure FDA00035565584000000414
in the formula (f)n,tThe peak load of the node n at the time t in the planning period is obtained;
the constraint conditions of the planning model of the large power user mainly comprise DG (distributed generation) candidate node access number limitation, DG permeability constraint and DG output constraint;
(1) DG candidate node access number limitation
Figure FDA00035565584000000415
In the formula: n is a radical ofi.minAnd Ni.maxRespectively is a lower limit value and an upper limit value of the DG number accessed to the node i to be selected;
(2) node power balance constraints
Figure FDA00035565584000000416
In the formula: q. q ofn,tThe method comprises the steps of (1) purchasing electric quantity of a node n at the time t for peak load in a planning period;
Figure FDA00035565584000000417
generating capacity of a distributed power supply at a node n at the moment t;
Figure FDA0003556558400000051
the total load of the n nodes at the time t is obtained;
(3) DG output constraint
Figure FDA0003556558400000052
In the formula:
Figure FDA0003556558400000053
and
Figure FDA0003556558400000054
respectively the lower limit and the upper limit of DG output;
(4) the newly built DG capacity of the large power users has the following relationship constrained by the equation:
Figure FDA0003556558400000055
Figure FDA0003556558400000056
the information of the purchased electric quantity of the large-power user.
2. The source network load multi-subject game planning method considering the full dimension of the power market is characterized in that in step 4, for the proposed dynamic game model, nash equilibrium is solved by an iterative search method, and the specific solving steps are as follows:
1) input raw data and parameters: initializing data required for establishing a game model, wherein the data comprises load information, parameters of a set to be newly built, parameters of a line to be newly built, parameters of a distributed power source to be newly built, quotations of each set of a power generation company, and original network topology parameters of related parameters of power market operation;
2) generating a game participant strategy set: generating a planning strategy set of the power generation company according to the set to be selected of the newly-built unit by the power generation company
Figure FDA0003556558400000057
Generating a power grid planning strategy set by a power transmission company according to the candidate set of the power transmission line
Figure FDA0003556558400000058
A user generates a distributed power supply construction strategy set according to the distributed power supply candidate set
Figure FDA0003556558400000059
mG, mT and mU are the total number of elements in a power generation company, a power transmission company and a power large user strategy set in sequence;
3) randomly extracting a group of planning strategy schemes from the three participant strategy sets as initial values of the planning schemes;
4) setting an iteration initial value delta;
5) and (3) carrying out scheme optimization by the participants: each participant carries out decision making, checking and calculation on the planning scheme of the participant according to the information of other participants in the previous round, and the final effect of the three parties in the game round is obtained after load flow calculation and electricity price calculation;
6) judging whether an equilibrium state is reached: if the effectiveness of two continuous game rounds is the same, determining that the equilibrium state is reached, and entering the step 7); if not, making k equal to k +1, and returning to the step 5);
7) output model equalization solution
Figure FDA00035565584000000510
And the ultimate utility of the parties.
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