CN115511168A - Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid - Google Patents

Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid Download PDF

Info

Publication number
CN115511168A
CN115511168A CN202211143962.3A CN202211143962A CN115511168A CN 115511168 A CN115511168 A CN 115511168A CN 202211143962 A CN202211143962 A CN 202211143962A CN 115511168 A CN115511168 A CN 115511168A
Authority
CN
China
Prior art keywords
heat
power
microgrid
energy
grid
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202211143962.3A
Other languages
Chinese (zh)
Inventor
王灿
张羽
张高瑞
凌凯
贺旭辉
张雪菲
甘友春
王帆
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Three Gorges University CTGU
Original Assignee
China Three Gorges University CTGU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Three Gorges University CTGU filed Critical China Three Gorges University CTGU
Priority to CN202211143962.3A priority Critical patent/CN115511168A/en
Publication of CN115511168A publication Critical patent/CN115511168A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • 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
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Mathematical Physics (AREA)
  • Strategic Management (AREA)
  • Data Mining & Analysis (AREA)
  • Power Engineering (AREA)
  • Mathematical Optimization (AREA)
  • Marketing (AREA)
  • Mathematical Analysis (AREA)
  • General Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Computational Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Software Systems (AREA)
  • Development Economics (AREA)
  • Quality & Reliability (AREA)
  • Health & Medical Sciences (AREA)
  • Game Theory and Decision Science (AREA)
  • Algebra (AREA)
  • Operations Research (AREA)
  • Primary Health Care (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Computing Systems (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

A multi-energy complementary three-layer optimized operation method suitable for a combined heat and power type microgrid is characterized in that a lower-layer optimized operation model with the aim of minimum operation cost of each microgrid is established, each combined heat and power type microgrid is independently optimized with the aim of minimum operation cost, and electric information, thermal information, residual amount and shortage amount information in the microgrid are transmitted to an intermediate-layer optimized operation model for next-step energy optimization; the intermediate layer optimization operation model aims at minimizing the loss of thermoelectric energy transmission paths, the Floyd-Warshall algorithm is adopted to optimize the barter transaction and the business transaction of the energy among the micro-grids, and the information of the surplus, shortage and increasable amount of the electric energy heat energy of each combined heat and power type micro-grid is transmitted to the upper layer optimization operation model. And the upper-layer optimization operation model is used for solving according to the total electric energy, heat energy surplus or shortage condition, and selecting a proper route to carry out transaction with the outside. The method has the advantages of good applicability, lower energy transmission process loss, stronger energy mutual aid capacity among the micro-grids and lower running cost of each micro-grid.

Description

Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid
Technical Field
The invention belongs to the technical field of optimization of a combined heat and power type microgrid, and particularly relates to a multi-energy complementary three-layer optimized operation method suitable for the combined heat and power type microgrid.
Background
With the gradual depletion of traditional energy sources, how to fully develop and utilize renewable energy sources and improve the energy utilization rate becomes an urgent problem. The combined heat and power supply type micro-grid integrates heat supply and power supply, the cascade utilization of energy is realized through the internal combined heat and power generation unit, and the energy utilization rate and the flexibility of system operation are improved. However, the coupling relationship between the energy structure and the equipment in the combined heat and power type microgrid is complex, the difficulty of system operation and management is increased, and the safe and reliable operation of the system is influenced by the intermittent defect of renewable energy. Therefore, an optimal operation method suitable for the cogeneration-type microgrid is needed to realize the coordinated and optimal operation of renewable energy sources, energy supply equipment and energy storage equipment in the system.
In the prior art documents: the method is characterized in that an optimal scheduling model of an electric-thermal hybrid energy storage system is established by aiming at the lowest comprehensive operation cost of CHP type micro-grids in the documents [1], [ community micro-grid energy storage capacity configuration for electric vehicles ], liu Yanjuan, pan Tinglong and Yang Chaohui ] and the community micro-grid energy storage capacity configuration for electric vehicles [ J ]. Solar energy bulletin, 2021,42 (12): 363-367 ]. The problem that traditional battery energy storage running cost is high and microgrid operating stability is poor has been solved to this model.
Document [2] the economical Optimization scheduling configuration and Demand Response (DOU C, ZHOU X, ZHANG T, et al. The economical Optimization scheduling of micro grid for the generating photovoltaic configuration and Demand Response [ J ]. Journal of model power systems and seal energy,2020,8 (3): 557-563.) A load Demand Response model for the time-share electricity price of the distribution grid is established, which greatly reduces the operating cost of the system.
A cooperative optimization strategy based on a cooperative game is provided in the document [3] cooperative optimization scheduling based on the cooperative game under the consideration of conditional risk value (Shuai Xuan, wang Xiuli, wu Xiong, and the like.) cooperative optimization scheduling based on the cooperative game under the consideration of the conditional risk value [ J ] power grid technology, 2022,46 (1): 130-137.), and the method realizes the optimal operation of the CHP type microgrid.
However, the optimal operation methods in the above documents do not take into account the comfort of power consumption and the operation cost of multiple micro-grids, and there is a problem that the energy loss during transmission is not considered.
Disclosure of Invention
In order to solve the technical problems, the invention provides a multi-energy complementary three-layer optimization operation method suitable for a Combined Heat and Power (CHP) type microgrid, which constructs a lower-layer optimization operation model taking the minimum operation cost of each microgrid as a target, an upper-layer optimization operation model taking the minimum interaction cost among bodies as a target, and an intermediate-layer optimization operation model taking the minimum energy transmission path loss as a target. The method comprises the steps that firstly, the microgrid is optimized with the aim of minimizing the operation cost, then the energy mutual aid capacity among the microgrids is improved through a mode of barter trading and buying and selling trading through an intermediate layer model, an optimal transmission path is searched for the energy trading among the microgrids on the basis of a Floyd-Warshall algorithm, and finally, an appropriate route is selected by an upper layer to conduct trading with the outside. Compared with other optimization strategies, the method has the advantages of lower energy transmission process loss, stronger energy mutual-aid capacity among the micro-grids and lower running cost of each micro-grid.
The technical scheme adopted by the invention is as follows:
a multi-energy complementary three-layer optimized operation method suitable for a combined heat and power microgrid comprises the following steps:
step 1: constructing a lower-layer optimized operation model with the minimum operation cost of each micro-grid as a target, independently optimizing each cogeneration type micro-grid with the minimum operation cost as a target, and transmitting the internal electrical information, thermal information, residual amount and shortage amount information of the micro-grid to an intermediate-layer optimized operation model for next energy optimization;
and 2, step: the intermediate layer optimization operation model aims at minimizing the loss of a thermoelectric energy transmission path, the Floyd-Warshall algorithm is adopted to optimize the barter transaction and the business transaction of the energy among the micro grids, and the surplus, shortage and increasable amount information of the electric energy and the heat energy of each cogeneration type micro-grid is transmitted to an upper-layer optimization operation model.
And 3, step 3: and the upper-layer optimization operation model is used for solving according to the total electric energy, heat energy surplus or shortage condition, and selecting a proper route to carry out transaction with the outside.
In the step 1, the lower-layer optimized operation model takes the lowest operation cost as an optimization target, and the specific expression is as follows:
Figure BDA0003854851010000021
in the formula: c fuel Fuel cost for CHP; c om The operation and maintenance cost of the interior of the heat and power cogeneration type micro-grid is saved;
Figure BDA0003854851010000022
the CHP start-stop cost.
CHP fuel costs are as follows:
Figure BDA0003854851010000023
in the formula: r ng Is the unit price of fuel; h ng Is the specific heating value of the fuel; p t CHP,E Electric power of CHP unit; eta CHP The generating efficiency of the CHP unit is obtained; t is the scheduled time period in the day ahead.
The operation and maintenance costs of the cogeneration-type microgrid are as follows:
Figure BDA0003854851010000031
in the formula:
Figure BDA0003854851010000032
maintenance costs for CHP;
Figure BDA0003854851010000033
maintenance costs for the photovoltaic;
Figure BDA0003854851010000034
maintenance costs for stored energy;
k CHP 、k PV CHP and photovoltaic operation maintenance cost coefficients are respectively;
Figure BDA00038548510100000326
a maintenance cost factor for electrical energy storage;
Figure BDA0003854851010000035
a maintenance cost factor for thermal energy storage;
Figure BDA0003854851010000036
charging and discharging efficiencies of the electric energy storage are respectively realized;
Figure BDA0003854851010000037
respectively the charging efficiency and the discharging efficiency of the heat energy storage.
P t PV The output power of the photovoltaic is;
Figure BDA0003854851010000038
a charging power to store energy for electricity;
Figure BDA0003854851010000039
discharge power for storing energy for electricity.
The CHP start-stop cost is as follows:
Figure BDA00038548510100000310
in the formula:
Figure BDA00038548510100000311
is the state variable of CHP in the t period;
Figure BDA00038548510100000312
starting and stopping cost coefficients of the CHP are respectively;
Figure BDA00038548510100000313
is the state variable of the CHP in the t-1 period.
Constraint conditions are as follows:
the constraint conditions mainly comprise CHP output power constraint, electric and thermal power balance constraint, energy storage constraint and the like.
The CHP output power constraint is:
Figure BDA00038548510100000314
Figure BDA00038548510100000315
in the formula:
Figure BDA00038548510100000316
the CHP minimum and maximum output electric power respectively,
Figure BDA00038548510100000317
the thermoelectric yield ratio of CHP;
Figure BDA00038548510100000318
thermal power output for CHP; p t CHP,E Electrical power output for CHP.
The electric and thermal load power balance constraint is as follows:
Figure BDA00038548510100000319
Figure BDA00038548510100000320
in the formula: p t E,sur 、P t E,short Surplus power and shortage power of the electric energy of the combined heat and power type micro-grid are respectively obtained;
Figure BDA00038548510100000321
surplus and shortage power of heat energy of the combined heat and power type micro-grid are respectively generated;
Figure BDA00038548510100000322
respectively is a combined heat and power supply type electricity and heat load power. P t BS,E Electrical power for storing energy; p t BS,H Thermal power for energy storage; p t CHP,E Is the electrical power of the CHP plant.
The energy storage constraint of the combined heat and power type microgrid is as follows:
Figure BDA00038548510100000323
Figure BDA00038548510100000324
Figure BDA00038548510100000325
Figure BDA0003854851010000041
Figure BDA0003854851010000042
Figure BDA0003854851010000043
in the formula:
Figure BDA0003854851010000044
the maximum charging power and the maximum discharging power of the combined heat and power type microgrid electric energy storage are respectively;
Figure BDA0003854851010000045
the heat storage energy of the combined heat and power type micro-grid is respectively the maximum charging power and the maximum discharging power;
Figure BDA0003854851010000046
the minimum and maximum values of the electric energy storage capacity of the combined heat and power type micro-grid are respectively;
Figure BDA0003854851010000047
the heat energy storage capacity of the heat and power combined supply type micro-grid is the minimum value and the maximum value respectively;
Figure BDA0003854851010000048
the energy storage capacities of the heat and power cogeneration type micro-grid at the t-period are respectively.
In the step 2, each cogeneration-type microgrid gives out electric energy and heat energy purchase/sale prices according to the energy condition thereof:
Figure BDA0003854851010000049
Figure BDA00038548510100000410
in the formula: f. of 1,t The operation cost of the heat and power combined supply type micro-grid is saved; p t PV +P t CHP,E -P t BS,E The net power generation quantity of the cogeneration-type microgrid is obtained; p t CHP,H -P t BS,H The heat is generated for the combined heat and power type micro-grid; when the combined heat and power type microgrid is in a power purchasing and heat purchasing state,
Figure BDA00038548510100000411
and
Figure BDA00038548510100000412
respectively the electricity purchase price and the heat purchase price; when the combined heat and power type microgrid is in a power selling and heat selling state,
Figure BDA00038548510100000415
and
Figure BDA00038548510100000413
the price of electricity and heat are respectively sold.
In the step 2, the line loss is calculated by adopting a direct current approximation method:
P loss,i ＝r i P i 2 /V i 2 ；
in the formula: p loss,i The line loss power of the ith transmission line among the heat and power cogeneration type micro grids is obtained; r is i The line resistance of the ith transmission line; p i Transmitting active power for the ith transmission line; v i Is the voltage level of the transmission line.
Calculating heat loss in the heat supply pipeline transmission process by adopting a node method:
the tail end temperature in the heat supply pipeline transmission process is as follows:
Figure BDA00038548510100000414
in the formula: c is the heat loss coefficient in the transmission process of the heat supply pipeline of the combined heat and power type micro-grid; tau is i The heat delay time in the heat supply pipeline transmission process is set; t is i in The temperature of the head end of the heat supply pipeline in the heat supply pipeline transmission process is measured; lambda is the heat supply pipeline loss coefficient in the heat supply pipeline transmission process; c. C i The specific heat capacity of a heat transfer medium of the heat supply pipeline of the heat-electricity cogeneration type micro-grid is provided; t is m Is ambient temperature; l i The length of the ith heat and power cogeneration type micro-grid heat supply pipeline is obtained; m is a unit of i The weight of the heat transfer medium for the heat supply pipeline of the heat and power cogeneration type micro-grid.
The delay time in the heat supply pipeline transmission process is as follows:
Figure BDA0003854851010000051
in the formula: delta tau is the transmission time error of the heat supply pipeline of the heat and power cogeneration type micro-grid; l. the i 、d i Respectively the length and the radius of the heat supply pipeline; rho w 、m i Density, mass of the heat conveyance medium, respectively.
Based on the electric energy line loss and the heat energy heat supply network characteristics, the electric heat gain function of the combined heat and power type micro-grid is as follows:
Figure BDA0003854851010000052
Figure BDA0003854851010000053
Figure BDA0003854851010000054
Figure BDA0003854851010000055
Figure BDA0003854851010000056
Figure BDA0003854851010000057
in the formula:
Figure BDA0003854851010000058
acquiring an electricity purchasing gain function for the combined heat and power type micro-grid;
Figure BDA0003854851010000059
a power selling income function for the combined heat and power type micro-grid;
Figure BDA00038548510100000510
purchasing a heat gain function for the combined heat and power type microgrid;
Figure BDA00038548510100000511
a heat gain function is sold for the combined heat and power type micro-grid;
Figure BDA00038548510100000512
the electric quantity and the heat purchasing quantity of the heat and power cogeneration type microgrid are respectively obtained;
Figure BDA00038548510100000513
the power and heat losses of the combined heat and power type micro-grid are respectively;
Figure BDA00038548510100000514
the quantity of electricity and heat sold by the heat and electricity cogeneration type micro-grid are respectively.
Figure BDA00038548510100000515
The electricity purchasing prices and electricity selling prices are respectively given for the two combined heat and power type micro-grids;
Figure BDA00038548510100000516
the heat purchasing prices and the heat selling prices are respectively given for the two combined heat and power type micro-grids;
Figure BDA00038548510100000517
for the trade price of the combined heat and power type microgrid electricity, the method comprises the following steps:
Figure BDA00038548510100000518
Figure BDA00038548510100000519
the heat exchange easy price of the heat and power cogeneration type micro-grid is as follows:
Figure BDA00038548510100000520
in the step 2, an optimization objective function of the cogeneration type microgrid intermediate layer optimization operation model is as follows:
Figure BDA00038548510100000521
in the formula: u and M are the total number of the electric and heat transactions of the combined heat and power type microgrid respectively; u is the number of the cogeneration type micro-grids for electric transaction; and m is the number of the heat and power cogeneration type micro-grids for heat transaction.
Figure BDA0003854851010000061
Purchasing a power income function for the combined heat and power type microgrid;
Figure BDA0003854851010000062
a power selling income function for the combined heat and power type micro-grid;
Figure BDA0003854851010000063
a heat purchasing gain function is carried out on the combined heat and power type micro-grid;
Figure BDA0003854851010000064
a heat gain function is sold for the combined heat and power type micro-grid;
constraint conditions of the combined heat and power type microgrid:
1) Purchasing/selling price constraints:
Figure BDA0003854851010000065
Figure BDA00038548510100000611
2) Purchase/sale volume constraints:
Figure BDA0003854851010000066
Figure BDA0003854851010000067
in the formula:
Figure BDA0003854851010000068
the maximum values of electricity purchase and electricity sale of the combined heat and power type microgrid are respectively;
Figure BDA0003854851010000069
the maximum values of the purchased heat and the sold heat of the combined heat and power type micro-grid are respectively; Δ t is the step size of the scheduling.
In the step 2, the intermediate layer optimization operation model improves the energy mutual aid capability among the combined heat and power type micro-grids in a barter trading mode, and when the micro-grid n has the surplus energy and lacks the heat energy and the micro-grid m has the surplus heat and lacks the energy, the micro-grid n and the micro-grid m are paired in barter trading. Redundant electric energy of the microgrid n is transmitted to the microgrid m, redundant heat energy of the microgrid m is transmitted to the microgrid n, and therefore energy complementation among the microgrids is achieved.
In the step 2, an optimal path is selected for energy transaction between the cogeneration-type micro-grids by adopting a Floyd-Warshall algorithm, and the method comprises the following steps:
step 2.1: setting N (V, A) as a cogeneration-type microgrid connection network, wherein V = {1,2,3, …, N } is a cogeneration-type microgrid node set, and | V | = N; and A = { (i, k) } is an edge set between the two cogeneration type microgrids. i represents the ith cogeneration type; k represents the kth cogeneration type.
Step 2.2: set up D j 、R j (j =0,1, …, n) is an n × n order matrix in the cogeneration-type microgrid connection network.
j is the order, n is the total number of network nodes, wherein D j As a path matrix, R j Is a precursor matrix.
Step 2.3: when j = 0:
at this time, D 0 ＝[d ik ]：
Figure BDA00038548510100000610
D 0 Represents a 0 th order path matrix; d ik And the path distance between the piconet i and the piconet k is shown.
At this time, R 0 ＝[r ik ]：
Figure BDA0003854851010000071
R 0 Representing a 0 th order precursor matrix; r is a radical of hydrogen ik And representing an intermediate point on the shortest path from the microgrid i to the microgrid k.
Step 2.4: when j = 1:
at this time, D 1 ＝[d ik ]
Figure BDA0003854851010000072
D 1 Representing a path matrix of order 1; d ij Represents the path distance between the microgrid i and the microgrid j, d jk And the path distance between the piconet j and the piconet k is shown.
At this time, R 1 ＝[r ik ]
Figure BDA0003854851010000073
R 1 Representing a precursor matrix of order 1; r is ik And representing an intermediate point on the shortest path from the microgrid i to the microgrid k.
Step 2.5: and repeating the step 2.5 until j = n, and at this time, obtaining an optimal transmission path between any two cogeneration type microgrids.
In step 3, the upper layer optimizes and runs the model objective function:
Figure BDA0003854851010000074
in the formula:
Figure BDA0003854851010000075
the cost is the electricity interaction cost between the combined heat and power microgrid and the power distribution network;
Figure BDA0003854851010000076
the heat exchange cost of the heat-electricity co-generation type micro-grid and an external heat supply network system is reduced;
Figure BDA0003854851010000077
in order to reduce the cost of the electrical losses,
Figure BDA0003854851010000078
which is a heat loss cost.
The total electric heat interaction cost of the combined heat and power type microgrid is shown as follows:
Figure BDA0003854851010000079
Figure BDA00038548510100000710
in the formula:
Figure BDA00038548510100000711
the power is respectively the electricity and the heat interaction power of a thermoelectric co-generation type microgrid;
Figure BDA00038548510100000712
purchasing/selling electricity prices for the distribution network; x is the number of pur,t 、x sel,t Respectively is a state variable of the combined heat and power supply type micro-network purchasing and selling electricity;
Figure BDA00038548510100000713
respectively purchasing and selling heat prices of the heat supply network system; y is pur,t 、y sel,t Respectively are heat and electricity cogeneration type micro-network purchasing and selling state variables.
The electric heating loss cost of the combined heat and power type microgrid is respectively shown as the following formula:
Figure BDA0003854851010000081
Figure BDA0003854851010000082
in the formula: r is the radius of the heat supply pipeline of the combined heat and power type micro-grid; t is in 、T out The temperatures of the head end and the tail end of the heat supply pipeline of the heat and power cogeneration type micro-grid are respectively measured; c is the specific heat capacity of a transmission medium in the heat supply pipeline of the combined heat and power type microgrid; and m is the quality of a transmission medium in the heat supply pipeline of the heat and power cogeneration type micro-grid.
Constraint conditions of the cogeneration-type microgrid:
Figure BDA0003854851010000083
Figure BDA0003854851010000084
in the formula:
Figure BDA0003854851010000085
the minimum value and the maximum value of the power of the cogeneration type microgrid and the power distribution network are respectively;
Figure BDA0003854851010000086
the minimum value and the maximum value of the interactive thermal power of the heat and power cogeneration type micro-grid and the heat supply network system are obtained;
Figure BDA0003854851010000087
the electric power is the interactive electric power of the heat supply network system and the combined heat and power type micro-grid;
Figure BDA0003854851010000088
the heat power is the interactive heat power of the heat and power cogeneration type micro-grid and the heat supply network system.
The invention discloses a multi-energy complementary three-layer optimized operation method suitable for a combined heat and power CHP type microgrid, which has the following technical effects:
1) According to the energy trading mode between the micro-grids, which is provided by the invention and combines the barter trading and the buying and selling trading, the energy mutual-aid capability between the micro-grids can be gradually improved, and the dependence of the micro-grids on an external power distribution network and a heat supply network system is reduced.
2) The invention optimizes the barter transaction and the buying and selling transaction of the energy between the micro grids by adopting the Floyd-Warshall algorithm, and the algorithm can find out the shortest distance between the two points without traversing all paths in the network diagram, thereby greatly reducing the calculation time of the algorithm.
3) Different from the optimization process of other cogeneration-type micro-grids, the invention considers the loss problems in the energy transaction process, including the line loss in the electric energy transmission process, and the heat delay and heat loss in the heat energy transmission process. The optimal operation of the combined heat and power microgrid can be better realized by considering the loss in the transmission process.
Drawings
FIG. 1 is a flow chart of the operation method of the present invention.
Fig. 2 is a schematic structural diagram of a cogeneration-type micro-computing system.
Fig. 3 (a) is a CHP electric power scheduling result diagram of each microgrid within 24 hours;
fig. 3 (b) is a graph of the thermal power scheduling result of each microgrid CHP within 24 hours.
Fig. 4 (a) is a schematic diagram of charging and discharging of each microgrid electric energy storage within 24 hours;
fig. 4 (b) is a schematic diagram of heat storage and charge-discharge of each microgrid within 24 hours;
fig. 5 is a diagram of a result of the electric heating interaction power scheduling of the microgrid group within 24 hours.
Fig. 6 is a graph of the operating cost of each microgrid according to the optimization method provided by the present invention.
Detailed Description
A multi-energy complementary three-layer optimization operation method suitable for a Combined Heat and Power (CHP) type microgrid. The method constructs a lower-layer optimized operation model taking the minimum operation cost of each microgrid as a target, an upper-layer optimized operation model taking the minimum interaction cost among main bodies as a target, and an intermediate-layer optimized operation model taking the minimum energy transmission path loss as a target. Firstly, optimization is carried out by taking the minimum operation cost of each cogeneration type microgrid as a target. And then, improving the energy mutual aid capability among the micro-grids in the middle layer model through the mode of barter transaction and buying and selling transaction, and searching an optimal transmission path for the energy transaction among the micro-grids on the basis of the Floyd-Warshall algorithm. And finally, selecting a proper route by the upper layer to carry out transaction with the outside. Compared with other optimization strategies, the method has the advantages of lower energy transmission process loss, stronger energy mutual-assistance capability among the micro-grids and lower running cost of each micro-grid.
Fig. 1 is a flowchart of a multi-energy complementary three-layer optimized operation method suitable for a cogeneration-type microgrid, as shown in fig. 1, the method flow is as follows:
(1) And each combined heat and power type microgrid is independently optimized by taking the minimum operation cost as a target, and the electricity/heat surplus/shortage information in the microgrid is transmitted to the middle layer for next energy optimization.
(2) The middle layer aims at minimizing the loss of a thermoelectric energy transmission path, the Floyd-Warshall algorithm is adopted to optimize the barter transaction and the business transaction of the energy among the micro-grids, and the surplus/shortage and increment information of the electric energy of each combined heat and power type micro-grid is transmitted to the upper layer.
(3) The upper layer solves the problem according to the total electric energy and heat energy surplus/shortage condition, and selects a proper route to carry out transaction with the outside. Fig. 2 is a schematic structural diagram of a cogeneration-type micro-computing system. As shown in fig. 2, the system of the present embodiment is composed of 6 cogeneration-type microgrids. The microgrid 1 can perform electric energy interaction with the microgrid 2, the microgrid 3 and the microgrid 6, and the microgrid 1 can perform heat energy interaction with the microgrid 2, the microgrid 3 and the microgrid 5; the microgrid 2 can perform electric energy interaction with the microgrid 1, the microgrid 3 and the microgrid 5, and the microgrid 2 can perform heat energy interaction with the microgrid 1, the microgrid 4 and the microgrid 5; the microgrid 3 can perform electric energy interaction with the microgrid 1, the microgrid 2, the microgrid 4 and the microgrid 6, and the microgrid 3 can perform heat energy interaction with the microgrid 1 and the microgrid 4; the microgrid 4 can perform electric energy interaction with the microgrid 3 and the microgrid 6, and the microgrid 4 can perform heat energy interaction with the microgrid 2, the microgrid 3 and the microgrid 6; the microgrid 5 can perform electric energy interaction with the microgrid 2 and the microgrid 6, and the microgrid 5 can perform heat energy interaction with the microgrid 1, the microgrid 2 and the microgrid 6; the microgrid 6 can be in electric energy interaction with the microgrid 1, the microgrid 3, the microgrid 4 and the microgrid 5, and the microgrid 6 can be in heat energy interaction with the microgrid 4 and the microgrid 5.
Fig. 3 (a), 3 (b), 4 (a), 4 (b) and 5 are the scheduling results of CHP electrothermal power, electrothermal energy storage charge and discharge, and electrothermal interaction power of the microgrid group in 24 hours, respectively. As shown in fig. 3 (a), 3 (b), 4 (a), 4 (b), and 5, in order to reduce the operating cost of each cogeneration-type microgrid, each CHP reduces the amount of power generated by itself, and the electric energy storage device is in a charged state to increase the amount of power stored; at the moment, the combined heat and power type micro-grid group increases the electricity purchasing quantity, and the electricity is purchased at a lower price to provide electricity for the electricity users and the electricity storage, so that the fuel cost of the system is reduced. In the period from 11. Each microgrid increases self generated energy through CHP, and the mode that the electricity stored energy discharges satisfies user's power consumption demand and reduces system power consumption cost, and the microgrid crowd reduces the electric energy of purchasing the distribution network, and meanwhile, there is unnecessary electric energy in 21 period microgrid system, sells the electric energy to the distribution network, and then reduces the whole running cost of microgrid crowd.
Fig. 6 shows the operating cost of each microgrid under the optimization method provided by the present invention. As can be seen from fig. 6, compared with the three-layer optimization strategy provided in the present invention, the total operation cost of each microgrid using the hierarchical autonomous optimization strategy and the collaborative optimization strategy is higher. Because the energy mutual aid between the micro-networks is not considered in the optimization process of the hierarchical autonomous optimization strategy, the energy can only be traded with the outside at a higher price. And the cooperative optimization strategy has more electric energy and heat energy loss because an optimal transmission path cannot be selected in the inter-microgrid energy transmission process. The three-layer optimization strategy provided by the invention considers the energy mutual aid among the micro-grids and the problem of transmission loss, so that the operation cost of the 6 cogeneration-type micro-grids is lower than that of the other two optimization strategies.
Table 1 11: trade result of barter between 00-time-interval combined heat and power type micro-grids
Figure BDA0003854851010000101
Table 2 11: 00-period combined heat and power supply type inter-microgrid energy trading result
Figure BDA0003854851010000102
Table 3 electric heat interaction costs of cogeneration type microgrid group, power distribution network and heat supply network system under three different optimization strategies
Figure BDA0003854851010000103
Figure BDA0003854851010000111
Table 1 and table 2 are 11: and 5, the result of barter transaction and energy buying and selling among the heat and power cogeneration type micro-grids at the 00 time period. As can be seen from tables 1 and 2, the multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type micro-grid firstly performs barter trading among the micro-grids, and each micro-grid respectively takes out electric heating energy with equal value according to an equivalent exchange principle to perform trading according to an agreed electric heating trading price. And the analysis is performed by taking the barter trading of the cogeneration-type microgrid 1 and the cogeneration-type microgrid 5 as representatives. The microgrid 1 is in excess of waste heat energy shortage, the microgrid 5 is in excess of heat energy shortage, and the electric heat transaction price is determined according to respective electric heat transaction quotations. The microgrid 1 transmits electric energy to the microgrid 5, and the microgrid 5 transmits heat energy to the microgrid 1, so that mutual energy compensation between the two microgrids is realized.
And updating the surplus/shortage quantity of each microgrid for energy buying and selling after bartering transaction. And analyzing by taking the heat energy transaction between the cogeneration-type microgrid 3 and the cogeneration-type microgrid 1 as a representative. At the moment, the microgrid 3 has redundant heat energy, the microgrid 1 lacks heat energy, the microgrid and the heat energy trade offer are agreed for trading price according to respective heat energy trade offers, then a trade path with the minimum electric heating loss is selected based on the Floyd-Warshall algorithm, energy buying and selling among the microgrids are completed, and the economic benefit of the microgrids is improved.
And table 3 shows the electric heating interaction cost of the microgrid group, the power distribution network and the heat supply network system under three different optimization strategies. As can be seen from table 3, in terms of the electricity transaction cost with the external power distribution network and the heat exchange cost of the external heat supply network system, the optimization strategy provided by the present invention considers the factors such as the energy mutual aid of the cogeneration-type microgrid and the minimum loss of the transmission path, so that both the transaction costs are less than the hierarchical autonomous optimization strategy and the collaborative optimization strategy. On the total transaction cost, the optimization strategy provided by the invention is reduced by 23.76% and 10.16% respectively compared with the hierarchical autonomous optimization strategy and the collaborative optimization strategy.

Claims (9)

1. A multi-energy complementary three-layer optimized operation method suitable for a combined heat and power microgrid is characterized by comprising the following steps of:
step 1: constructing a lower-layer optimized operation model with the minimum operation cost of each micro-grid as a target, independently optimizing each cogeneration type micro-grid with the minimum operation cost as a target, and transmitting the internal electrical information, thermal information, residual amount and shortage amount information of the micro-grid to an intermediate-layer optimized operation model for next energy optimization;
step 2: the intermediate layer optimization operation model aims at minimizing thermoelectric energy transmission path loss, a Floyd-Warshall algorithm is adopted to optimize barter trading and buying and selling trading of energy among the micro grids, and information of surplus, shortage and increasable amount of electric energy heat energy of each combined heat and power type micro grid is transmitted to the upper layer optimization operation model;
and step 3: and the upper-layer optimization operation model is used for solving according to the total electric energy, heat energy surplus or shortage condition, and selecting a proper route to carry out transaction with the outside.
2. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 1, characterized in that: in the step 1, the lower-layer optimized operation model takes the lowest operation cost as an optimization target, and the specific expression is as follows:
Figure FDA0003854847000000011
in the formula: c fuel Fuel cost for CHP; c om The operation and maintenance cost of the interior of the heat and power cogeneration type micro-grid is saved;
Figure FDA0003854847000000012
the starting and stopping cost of the CHP is shown;
CHP fuel costs are as follows:
Figure FDA0003854847000000013
in the formula: r ng Is the unit price of fuel; h ng Is the specific heating value of the fuel; p t CHP,E Electric power of CHP unit; eta CHP Is CHP, generating efficiency of the unit; t is the time period scheduled day before;
the operation and maintenance costs of the cogeneration-type microgrid are as follows:
Figure FDA0003854847000000014
in the formula:
Figure FDA0003854847000000015
maintenance costs for the CHP;
Figure FDA0003854847000000016
maintenance costs for the photovoltaic;
Figure FDA0003854847000000017
maintenance costs for stored energy;
k CHP 、k PV CHP and photovoltaic operation maintenance cost coefficients are respectively;
Figure FDA0003854847000000018
a maintenance cost factor for electrical energy storage;
Figure FDA0003854847000000019
maintenance cost factor for thermal energy storage;
Figure FDA00038548470000000110
charging and discharging efficiencies of the electric energy storage are respectively realized;
Figure FDA00038548470000000111
respectively the charging and discharging efficiency of the heat energy storage;
P t PV the output power of the photovoltaic is;
Figure FDA0003854847000000021
charging power for storing energy for electricity；
Figure FDA0003854847000000022
A discharge power to store energy for electricity;
the CHP start-stop cost is as follows:
Figure FDA0003854847000000023
in the formula: u shape t CHP Is the state variable of CHP in the t period;
Figure FDA0003854847000000024
starting and stopping cost coefficients of the CHP are respectively;
Figure FDA0003854847000000025
is the state variable of CHP in the t-1 period.
3. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 2, characterized in that: the lower-layer optimized operation model constraint conditions mainly comprise CHP output power constraint, electric and thermal power balance constraint, energy storage constraint and the like;
the CHP output power constraint is:
Figure FDA0003854847000000026
Figure FDA0003854847000000027
in the formula:
Figure FDA0003854847000000028
the CHP minimum and maximum output electric power respectively,
Figure FDA0003854847000000029
the thermoelectric yield ratio of CHP; p t CHP,H Thermal power output for CHP; p t CHP,E Electrical power output for CHP;
the electric and thermal load power balance constraint is as follows:
Figure FDA00038548470000000210
Figure FDA00038548470000000211
in the formula: p t E,sur 、P t E,short Surplus power and shortage power of the electric energy of the combined heat and power type microgrid are respectively obtained; p t H,sur 、P t H,short Surplus and shortage power of heat energy of the combined heat and power type micro-grid are respectively generated;
Figure FDA00038548470000000212
the power is the combined heat and power type electricity and the heat load power respectively; p is t BS,E Electrical power for storing energy; p t BS,H Thermal power for energy storage; p t CHP,E Electric power of CHP unit;
the energy storage constraint of the combined heat and power type microgrid is as follows:
Figure FDA00038548470000000213
Figure FDA00038548470000000214
Figure FDA00038548470000000215
Figure FDA00038548470000000216
Figure FDA00038548470000000217
Figure FDA00038548470000000218
in the formula:
Figure FDA00038548470000000219
the maximum charging power and the maximum discharging power of the combined heat and power type micro-grid electricity energy storage are respectively provided;
Figure FDA00038548470000000220
the heat storage energy of the combined heat and power type micro-grid is respectively the maximum charging power and the maximum discharging power;
Figure FDA0003854847000000031
the minimum and maximum values of the electric energy storage capacity of the combined heat and power type micro-grid are respectively;
Figure FDA0003854847000000032
the heat storage capacity of the heat and power combined supply type microgrid is the minimum value and the maximum value respectively;
E t BS,E 、E t BS,H the energy storage capacities of the heat and power cogeneration type micro-grid at the t-period are respectively.
4. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 1, characterized in that: in the step 2, each cogeneration-type microgrid gives out electric energy and heat energy purchase/sale prices according to the energy condition thereof:
Figure FDA0003854847000000033
Figure FDA0003854847000000034
in the formula: f. of 1,t The operation cost of the heat and power combined supply type micro-grid is saved; p t PV +P t CHP,E -P t BS,E The net power generation quantity of the cogeneration type microgrid is obtained; p t CHP,H -P t BS,H The heat is generated for the combined heat and power type micro-grid; when the combined heat and power type microgrid is in a power purchasing and heat purchasing state,
Figure FDA0003854847000000035
and
Figure FDA0003854847000000036
respectively the electricity purchase price and the heat purchase price; when the combined heat and power type microgrid is in a power selling and heat selling state, rho t E And rho t H The price of electricity and heat are respectively sold.
5. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration microgrid according to claim 1, characterized in that: in the step 2, the line loss is calculated by adopting a direct current approximation mode:
P loss,i ＝r i P i 2 /V i 2 ；
in the formula: p loss,i The power loss of the line of the ith transmission line among the cogeneration type microgrids is obtained; r is a radical of hydrogen i A line resistance of an ith transmission line; p i Transmitting active power for the ith transmission line; v i Is the voltage class of the transmission line;
calculating heat loss in the heat supply pipeline transmission process by adopting a node method:
the tail end temperature in the heat supply pipeline transmission process is as follows:
Figure FDA0003854847000000037
in the formula: c is the heat loss coefficient in the transmission process of the heat supply pipeline of the combined heat and power type micro-grid; tau. i The heat delay time in the heat supply pipeline transmission process is set; t is i in The temperature of the head end of the heat supply pipeline in the heat supply pipeline transmission process is measured; lambda is the heat supply pipeline loss coefficient in the heat supply pipeline transmission process; c. C i The specific heat capacity of a heat transfer medium of the heat supply pipeline of the heat-electricity cogeneration type micro-grid is provided; t is m Is ambient temperature; l i The length of the ith heat and power cogeneration type micro-grid heat supply pipeline is obtained; m is i The weight of a heat transfer medium for the heat supply pipeline of the heat and power cogeneration type micro-grid;
the delay time in the heat supply pipeline transmission process is as follows:
Figure FDA0003854847000000038
in the formula: delta tau is the transmission time error of the heat supply pipeline of the heat and power cogeneration type micro-grid; l i 、d i Respectively the length and the radius of the heat supply pipeline; rho w 、m i Density and mass of the heat transport medium, respectively;
based on the electric energy line loss and the heat energy heat supply network characteristics, the electric heat gain function of the combined heat and power type micro-grid is as follows:
Figure FDA0003854847000000041
Figure FDA0003854847000000042
Figure FDA0003854847000000043
Figure FDA0003854847000000044
Figure FDA0003854847000000045
Figure FDA0003854847000000046
in the formula:
Figure FDA0003854847000000047
acquiring an electricity purchasing gain function for the combined heat and power type micro-grid;
Figure FDA0003854847000000048
selling an electricity profit function for the combined heat and power type microgrid;
Figure FDA0003854847000000049
a heat purchasing gain function is carried out on the combined heat and power type micro-grid;
Figure FDA00038548470000000410
selling a heat gain function for the combined heat and power type microgrid;
Figure FDA00038548470000000411
the power and heat purchase amount of the heat and power cogeneration type microgrid are respectively;
Figure FDA00038548470000000412
the power and heat losses of the combined heat and power type micro-grid are respectively;
Figure FDA00038548470000000413
the electricity and heat sales volume of the combined heat and power type microgrid are respectively;
Figure FDA00038548470000000414
electricity purchasing prices and electricity selling prices are respectively given for the two combined heat and power type micro-grids;
Figure FDA00038548470000000415
the heat purchasing prices and the heat selling prices are respectively given for the two combined heat and power type micro-grids;
Figure FDA00038548470000000424
for the trade price of combined heat and power type microgrid electricity, the method comprises the following steps:
Figure FDA00038548470000000416
Figure FDA00038548470000000417
the heat exchange easy price of the heat and power cogeneration type micro-grid is as follows:
Figure FDA00038548470000000418
6. the multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 1, characterized in that: in the step 2, an optimization objective function of the cogeneration type microgrid intermediate layer optimization operation model is as follows:
Figure FDA00038548470000000419
in the formula: u and M are the total number of the electric and heat transactions of the combined heat and power type microgrid respectively; u is the number of the cogeneration type micro-grids for electric transaction; m is the number of the heat and power cogeneration type micro-grids for heat transaction;
Figure FDA00038548470000000420
acquiring an electricity purchasing gain function for the combined heat and power type micro-grid;
Figure FDA00038548470000000421
a power selling income function for the combined heat and power type micro-grid;
Figure FDA00038548470000000422
purchasing a heat gain function for the combined heat and power type microgrid;
Figure FDA00038548470000000423
a heat gain function is sold for the combined heat and power type micro-grid;
constraint conditions of the combined heat and power type microgrid:
1) Purchase/sale price constraints:
Figure FDA0003854847000000051
Figure FDA0003854847000000052
2) Purchase/sale quantity constraints:
Figure FDA0003854847000000053
Figure FDA0003854847000000054
in the formula:
Figure FDA0003854847000000055
the maximum values of electricity purchasing and electricity selling of the combined heat and power type micro-grid are respectively;
Figure FDA0003854847000000056
the maximum values of the purchased heat and the sold heat of the combined heat and power type micro-grid are respectively; Δ t is the step size of the scheduling.
7. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 1, characterized in that: in the step 2, the intermediate layer optimized operation model improves the energy mutual aid capability among the combined heat and power type micro-grids in a barter trading mode, and when the micro-grid n has the surplus energy and lacks the heat energy and the micro-grid m has the surplus heat and lacks the energy, the micro-grid n and the micro-grid m are subjected to barter trading pairing; redundant electric energy of the microgrid n is transmitted to the microgrid m, redundant heat energy of the microgrid m is transmitted to the microgrid n, and therefore energy complementation among the microgrids is achieved.
8. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration microgrid according to claim 1, characterized in that: in the step 2, an optimal path is selected for energy transaction between the cogeneration-type micro grids by adopting a Floyd-Warshall algorithm, and the method comprises the following steps:
step 2.1: setting N (V, A) as a cogeneration-type microgrid connection network, wherein V = {1,2,3, …, N } is a cogeneration-type microgrid node set, and | V | = N; a = { (i, k): i, k belongs to V, i ≠ k } is a side set between the two cogeneration-type microgrids; i represents the ith cogeneration type; k represents the kth cogeneration type;
step 2.2: set up D j 、R j (j =0,1, …, n) is an n × n order matrix in the cogeneration-type microgrid connection network;
j is the order, n is the total number of network nodes, wherein D j As a path matrix, R j Is a precursor matrix;
step 2.3: when j = 0:
at this time, D 0 ＝[d ik ]：
Figure FDA0003854847000000057
D 0 Represents a 0 th order path matrix; d is a radical of ik Representing the path distance between the microgrid i and the microgrid k;
at this time, R 0 ＝[r ik ]：
Figure FDA0003854847000000061
R 0 Representing a 0 th order precursor matrix; r is a radical of hydrogen ik Representing an intermediate point on the shortest path from the microgrid i to the microgrid k;
step 2.4: when j = 1:
at this time, D 1 ＝[d ik ]
Figure FDA0003854847000000062
D 1 Representing a path matrix of order 1; d ij Represents the path distance between the microgrid i and the microgrid j, d jk Representing the path distance between the microgrid j and the microgrid k;
at this time, R 1 ＝[r ik ]
Figure FDA0003854847000000063
R 1 Representing a 1 st order precursor matrix; r is ik Representing an intermediate point on the shortest path from the microgrid i to the microgrid k;
step 2.5: and repeating the step 2.5 until j = n, and at this time, obtaining an optimal transmission path between any two cogeneration type microgrids.
9. The multi-energy complementary three-layer optimized operation method suitable for the cogeneration-type microgrid according to claim 1, characterized in that: in step 3, the upper layer optimizes and runs the model objective function:
Figure FDA0003854847000000064
in the formula:
Figure FDA0003854847000000065
the electricity interaction cost between the combined heat and power microgrid and the power distribution network is represented;
Figure FDA0003854847000000066
the heat exchange cost of the heat-electricity co-generation type micro-grid and an external heat supply network system is reduced;
Figure FDA0003854847000000067
in order to be at the cost of electrical losses,
Figure FDA0003854847000000068
cost for heat loss;
the total electric heat interaction cost of the combined heat and power type microgrid is shown as follows:
Figure FDA0003854847000000069
Figure FDA00038548470000000610
in the formula:
Figure FDA00038548470000000611
the power is respectively the electricity and the heat interaction power of a thermoelectric co-generation type microgrid;
Figure FDA00038548470000000612
purchasing/selling electricity prices for the distribution network; x is the number of pur,t 、x sel,t Are respectively thermoelectricThe combined supply type micro-network electricity purchasing and selling state variable;
Figure FDA00038548470000000613
respectively the purchase and sale heat prices of the heat supply network system; y is pur,t 、y sel,t Respectively is a heat and electricity combined supply type micro-network purchasing and selling heat state variable;
the electric heating loss cost of the combined heat and power type microgrid is respectively shown as the following formula:
Figure FDA0003854847000000071
Figure FDA0003854847000000072
in the formula: r is the radius of the heat supply pipeline of the combined heat and power type micro-grid; t is a unit of in 、T out The temperatures of the head end and the tail end of the heat supply pipeline of the heat and power cogeneration type micro-grid are respectively measured; c is the specific heat capacity of a transmission medium in the heat supply pipeline of the combined heat and power type microgrid; m is the mass of a transmission medium in the heat supply pipeline of the combined heat and power type micro-grid;
constraint conditions of the combined heat and power type microgrid:
Figure FDA0003854847000000073
Figure FDA0003854847000000074
in the formula:
Figure FDA0003854847000000075
the minimum value and the maximum value of the interactive power of the heat and power combined supply type micro-grid and the power distribution network are respectively;
Figure FDA0003854847000000076
the minimum value and the maximum value of the interactive thermal power of the heat and power cogeneration type micro-grid and the heat supply network system are obtained;
Figure FDA0003854847000000077
the electric power is the interactive electric power of the heat supply network system and the heat cogeneration type micro-grid;
Figure FDA0003854847000000078
the heat power is the interactive heat power of the heat and power cogeneration type micro-grid and the heat supply network system.
CN202211143962.3A 2022-09-20 2022-09-20 Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid Pending CN115511168A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202211143962.3A CN115511168A (en) 2022-09-20 2022-09-20 Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211143962.3A CN115511168A (en) 2022-09-20 2022-09-20 Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid

Publications (1)

Publication Number Publication Date
CN115511168A true CN115511168A (en) 2022-12-23

Family

ID=84503658

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211143962.3A Pending CN115511168A (en) 2022-09-20 2022-09-20 Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid

Country Status (1)

Country Link
CN (1) CN115511168A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116911533A (en) * 2023-06-27 2023-10-20 西安理工大学 Multi-microgrid energy sharing method for regional comprehensive energy system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116911533A (en) * 2023-06-27 2023-10-20 西安理工大学 Multi-microgrid energy sharing method for regional comprehensive energy system
CN116911533B (en) * 2023-06-27 2024-05-14 西安理工大学 Multi-microgrid energy sharing method for regional comprehensive energy system

Similar Documents

Publication Publication Date Title
CN107958300B (en) Multi-microgrid interconnection operation coordination scheduling optimization method considering interactive response
CN109347149B (en) Micro-grid energy storage scheduling method and device based on deep Q-value network reinforcement learning
Li et al. Hierarchical optimal scheduling method for regional integrated energy systems considering electricity-hydrogen shared energy
CN116542370A (en) Park low-carbon economic operation method considering carbon capture and carbon transaction
CN111899054A (en) Shared energy storage control method and system for distributed renewable energy resource producers and consumers
CN114219195A (en) Regional comprehensive energy capacity optimization control method
CN111476423A (en) Energy interconnected distribution network fault recovery method
CN115829142A (en) Industrial enterprise comprehensive energy system optimization planning method
CN117236587A (en) Electric hydrogen-carbon cooperative scheduling optimization method for park comprehensive energy system
CN112883584A (en) Benefit interaction-considered multi-energy micro-grid group cooling, heating and power multi-energy coupling optimization method
CN115511168A (en) Multi-energy complementary three-layer optimized operation method suitable for combined heat and power type microgrid
CN115241923A (en) Micro-grid multi-objective optimization configuration method based on snake optimization algorithm
CN112085263A (en) User side distributed energy system hybrid energy storage optimal configuration method and system
CN114123260B (en) Renewable energy-oriented multi-energy micro-grid shared energy storage control method and system
Yousri et al. Managing the exchange of energy between microgrid elements based on multi-objective enhanced marine predators algorithm
Singh et al. Prosumer energy management for optimal utilization of bid fulfillment with EV uncertainty modeling
CN112883630B (en) Multi-microgrid system day-ahead optimization economic dispatching method for wind power consumption
CN117371669B (en) Park comprehensive energy system operation method considering carbon transaction risk cost
CN112668186B (en) ELM-based location and volume-fixing collaborative optimization method for integrated energy storage system
CN117811047A (en) Electric energy optimization method of multi-microgrid comprehensive energy system containing carbon capture and electric conversion gas
CN113258559A (en) Game optimization method for combined cooling heating and power supply micro-grid group system
CN117013552A (en) Cooperative operation strategy of electric power traffic coupling network
Cheng et al. Nash bargaining‐based cooperative game for distributed economic scheduling of microgrid with charging‐swapping‐storage integrated station
CN115085293A (en) Distributed energy interaction method for regional energy Internet and power distribution network
Zhou et al. Dynamic pricing of integrated energy service providers based on master-slave game

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination