CN111899125A - Optimized modeling operation method, device and medium for comprehensive energy system - Google Patents
Optimized modeling operation method, device and medium for comprehensive energy system Download PDFInfo
- Publication number
- CN111899125A CN111899125A CN202010758147.2A CN202010758147A CN111899125A CN 111899125 A CN111899125 A CN 111899125A CN 202010758147 A CN202010758147 A CN 202010758147A CN 111899125 A CN111899125 A CN 111899125A
- Authority
- CN
- China
- Prior art keywords
- power
- energy
- energy system
- flow
- heat
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 48
- 238000005457 optimization Methods 0.000 claims abstract description 53
- 238000004146 energy storage Methods 0.000 claims description 78
- 238000010248 power generation Methods 0.000 claims description 67
- 238000005338 heat storage Methods 0.000 claims description 56
- 230000005611 electricity Effects 0.000 claims description 52
- 230000006870 function Effects 0.000 claims description 39
- 238000004891 communication Methods 0.000 claims description 16
- 238000011217 control strategy Methods 0.000 claims description 16
- 238000003860 storage Methods 0.000 claims description 11
- 238000007599 discharging Methods 0.000 claims description 10
- 238000006243 chemical reaction Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 7
- 230000009194 climbing Effects 0.000 claims description 6
- 230000005855 radiation Effects 0.000 claims description 6
- 239000000126 substance Substances 0.000 claims description 6
- 230000020169 heat generation Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 abstract description 12
- 230000007246 mechanism Effects 0.000 abstract description 8
- 230000002452 interceptive effect Effects 0.000 abstract description 3
- 238000011161 development Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000004458 analytical method Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 6
- 230000003993 interaction Effects 0.000 description 4
- 238000007726 management method Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000010438 heat treatment Methods 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000010223 real-time analysis Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- 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
- 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
Abstract
The invention relates to an optimized modeling operation method, device and medium of an integrated energy system, which comprises the steps of obtaining a target information flow of the integrated energy system; respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set; and adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme. The invention can consider the connection relation and the interactive working mechanism between the information level and the physical level of the comprehensive energy system, and can carry out unified modeling and quantitative analysis on the information flow and the energy flow of the comprehensive energy system, thereby realizing optimal energy flow control, improving the energy utilization rate and realizing the economic and safe operation of the comprehensive energy system.
Description
Technical Field
The invention relates to the technical field of comprehensive energy, in particular to an optimized modeling operation method, device and medium of a comprehensive energy system.
Background
In order to relieve the energy crisis and realize the social sustainable development, China actively promotes the coordinated development of fossil energy and renewable new energy, a comprehensive energy system containing various resources such as electric energy, heat energy, natural gas energy, solar energy, biomass energy and the like is formed, various heterogeneous energy sources can be cooperatively scheduled, the energy utilization rate is improved, the energy conservation and emission reduction are promoted, and the green sustainable development is realized.
With the development of ubiquitous power internet of things and strong smart power grids, a typical information physical system is formed by the comprehensive energy system and the control system thereof, and functions of wide-area information measurement, information transmission and analysis, information decision and the like can be realized. The energy gateway of the comprehensive energy system deeply senses information of different devices to form information flow for analysis and decision, optimizes the energy flow of the comprehensive energy system and ensures the economic and safe operation of the comprehensive energy system. However, with the complication of the interaction of the integrated energy system information flow with the energy flow, it is necessary to model the coupling of the information flow and the energy flow of the integrated energy system and analyze the interworking mechanism thereof.
Currently, research results mainly relate to discrete information flow modeling (such as communication protocol modeling) or energy flow modeling (such as coordination control of a generator set and an energy storage device) of an integrated energy system, however, the prior art is less related to an interaction mechanism between information flow and energy flow of the integrated energy system, and the unified modeling and quantitative analysis of the information flow and the energy flow of the integrated energy system are lacked.
Therefore, a modeling operation method for information flow and energy flow of the integrated energy system is provided, and by considering the connection relation and the interaction mechanism between the information layer and the physical layer of the integrated energy system, unified modeling and quantitative analysis can be performed on the information flow and the energy flow of the integrated energy system, so that optimal energy flow control is realized, and the method is a problem to be solved urgently in current research on the integrated energy system.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an optimized modeling operation method, device and medium for an integrated energy system, which can consider the connection relationship and the interworking mechanism between the information level and the physical level of the integrated energy system, and can perform unified modeling and quantitative analysis on the information flow and the energy flow of the integrated energy system, thereby realizing optimal energy flow control.
The technical scheme for solving the technical problems is as follows:
an optimized modeling operation method of an integrated energy system comprises the following steps:
acquiring a target information flow of the comprehensive energy system;
respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme.
According to another aspect of the invention, the invention further provides an optimized modeling operation device of the integrated energy system, which is applied to the optimized modeling operation method of the integrated energy system, and comprises an information flow acquisition module, an energy flow modeling module and an optimized solving module;
the information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme.
According to another aspect of the present invention, there is provided an apparatus for optimizing modeling operation of an integrated energy system, comprising a processor, a memory, and a computer program stored in the memory and operable on the processor, wherein the computer program realizes the steps of the method for optimizing modeling operation of an integrated energy system according to the present invention when running.
In accordance with another aspect of the present invention, there is provided a computer storage medium comprising: at least one instruction which, when executed, performs a step in the method of optimized modeled operation of an integrated energy system of the present invention.
The method, the device and the medium for optimizing modeling operation of the comprehensive energy system have the advantages that: the method comprises the steps of obtaining a target information flow of the comprehensive energy system, obtaining a power model capable of describing the comprehensive energy system according to the target information flow, providing an energy flow constraint condition set in the process of optimizing an operation objective function to reach an optimal value, constructing an optimized operation objective function, obtaining an energy flow optimized operation model according to the optimized operation objective function, the power model and the provided energy flow constraint condition set, solving the energy flow optimized operation model, and obtaining an optimized operation scheme, wherein the optimized operation scheme not only realizes the optimal control of the energy flow in the comprehensive energy system, but also considers the connection relation and the interactive working mechanism between the information level and the physical level of the comprehensive energy system, and realizes the unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system;
the optimized modeling operation method, the device and the medium of the integrated energy system can collect the information of each energy device of the energy layer in the integrated energy system and form the information flow of the information layer, carry out unified modeling and quantitative analysis on the information flow and the energy flow of the integrated energy system, and can utilize the technology of the information layer to carry out optimized solution on the optimized operation model of the energy flow from the set optimized operation objective function and the energy flow constraint condition set to obtain the optimal optimized operation scheme, thereby realizing the joint analysis of the information layer and the physical layer of the integrated energy system, carrying out optimal control on the energy flow, improving the energy utilization rate, realizing the economic and safe operation of the integrated energy system and realizing the green sustainable development.
Drawings
Fig. 1 is a schematic flow chart of an optimization modeling operation method of an integrated energy system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating obtaining a target information stream according to a first embodiment of the present invention;
FIG. 3 is a schematic diagram of an energy flow according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a structure of an information flow according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating an integrated architecture of energy flow and information flow of an integrated energy system according to an embodiment of the present invention;
FIG. 6 is a graph of the total output power of the photovoltaic power generation apparatus, the power demanded by the user electrical load, and the power demanded by the user thermal load according to an embodiment of the present invention;
FIG. 7 is a schematic flow chart illustrating a process of obtaining an energy flow optimization operation model according to a first embodiment of the present invention;
FIG. 8 is a schematic flow chart illustrating an optimized operation scheme according to a first embodiment of the present invention;
fig. 9 is a graph of electricity price-electricity purchase quantity of the integrated energy system according to the first embodiment of the present invention;
fig. 10 is a graph illustrating a remaining capacity ratio of the electric/thermal energy storage SOC of the integrated energy system according to the first embodiment of the present invention;
FIG. 11 is a graph of the power curve of the heat pump/energy storage battery of the integrated energy system according to the first embodiment of the present invention;
fig. 12 is a schematic structural diagram of an optimization modeling operation apparatus of an integrated energy system according to a second embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
The present invention will be described with reference to the accompanying drawings.
In a first embodiment, as shown in fig. 1, a method for optimizing modeling operation of an integrated energy system includes the following steps:
s1: acquiring a target information flow of the comprehensive energy system;
s2: respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
s2: and adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme.
The method comprises the steps of obtaining a target information flow of the comprehensive energy system, obtaining a power model capable of describing the comprehensive energy system according to the target information flow, providing an energy flow constraint condition set in the process of optimizing an operation objective function to reach an optimal value, constructing an optimized operation objective function, obtaining an energy flow optimized operation model according to the optimized operation objective function, the power model and the provided energy flow constraint condition set, solving the energy flow optimized operation model, and obtaining an optimized operation scheme, wherein the optimized operation scheme not only realizes the optimal control of the energy flow in the comprehensive energy system, but also considers the connection relation and the interactive working mechanism between the information level and the physical level of the comprehensive energy system, and realizes the unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system;
the optimized modeling operation method of the integrated energy system of the embodiment can collect information of each energy device of an energy layer in the integrated energy system and form information flow of the information layer, unified modeling and quantitative analysis are carried out on the information flow and the energy flow of the integrated energy system, an optimized energy flow operation model can be optimized and solved from a set optimized operation objective function and an energy flow constraint condition set by utilizing the technology of the information layer, an optimal optimized operation scheme is obtained, joint analysis of the information layer and the physical layer of the integrated energy system is realized, optimal control is carried out on the energy flow, the energy utilization rate is improved, economic and safe operation of the integrated energy system is realized, and green sustainable development is realized.
Preferably, the comprehensive energy system comprises an intelligent energy gateway, a comprehensive energy supply and demand platform, a communication manager and a comprehensive energy device group;
as shown in fig. 2, S1 specifically includes the following steps:
s11: acquiring an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
s12: converting the equipment information set by using the communication manager to form an original information stream;
s13: performing logic processing on the original information flow by using the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user heat load;
the equipment information set comprises total output power of the distributed power generation device, active power and reactive power of the heat pump, power generation power and heat generation power of the cogeneration unit, energy storage capacity, charging power and discharging power of the energy storage device, user electrical load demand power and user thermal load demand power at each moment.
The intelligent energy gateway of the energy level acquires the equipment information of each energy device to obtain an equipment information set, so that a communication manager can be conveniently and subsequently utilized to obtain a target information stream according to the equipment information set and upload the target information stream to the comprehensive energy supply and demand platform of the information level, and the optimal optimized operation scheme of the whole comprehensive energy system can be obtained by utilizing the technology of the information level.
Specifically, in this embodiment, the communication manager forms the device information set into an original information stream through an OPC protocol, and then uniformly aggregates the original information stream through logical processing methods such as data accumulation, subtraction, multiplication, division, and integration to obtain a target information stream, and uploads the target information stream to the integrated energy supply and demand platform in a data frame format for real-time analysis; it should be noted that the target information stream after the logic processing includes all the information in the device information set.
Specifically, in this embodiment, the distributed power generation equipment is specifically a photovoltaic power generation device, and the energy storage device specifically includes an energy storage battery and a heat storage tank, so that the total output power of the distributed power generation device in the target information stream is specifically the total output power of the photovoltaic power generation device, and the energy storage capacity, the energy charging power and the energy discharging power of the energy storage device specifically include the rated energy storage amount, the rated electricity storage power and the rated electricity discharging power of the energy storage battery, and the maximum heat storage capacity, the maximum heat storage power and the maximum heat discharging power of the heat storage tank; a specific structure diagram of the energy flow in the integrated energy system of this embodiment is shown in fig. 3, a specific structure diagram of the information flow in the integrated energy system is shown in fig. 4, and an integrated structure diagram of the information flow-energy flow in the integrated energy system is shown in fig. 5.
Specifically, the total output power (i.e., photovoltaic output) of the photovoltaic power generation apparatus, the power required by the user electrical load, and the power required by the user thermal load collected in this embodiment are shown in fig. 6, the maximum heat storage capacity of the heat storage tank is 16MWh, the rated electricity storage capacity of the energy storage battery is 10MWh, the active power extreme value of the heat pump is 2.4MW, and the electric-to-heat conversion efficiency is 2.6; the maximum electricity storage power and the maximum electricity release power of the energy storage battery are respectively 2MW and 1.5 MW.
Preferably, the power model comprises a photovoltaic power generation power model and a cogeneration power model;
as shown in fig. 7, S2 specifically includes the following steps:
s21: constructing the photovoltaic power generation power model according to the total output power of the photovoltaic power generation device, and constructing the cogeneration power model according to the generated power and the generated heat power of the cogeneration unit;
s22: obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the electricity generating power and the heat generating power of the cogeneration unit, the active power and the reactive power of the heat pump, the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device, the user electricity load demand power and the user heat load demand power;
s23: acquiring the exchange electric quantity between the comprehensive energy system and a power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
minF is the optimized operation objective function, F is the daily operation cost of the comprehensive energy system, c (T) is the electricity exchange cost of the comprehensive energy system and the power grid at the moment T, T is the daily operation period duration, and P is the timeexc(t) the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P is presentexc(t)>When 0 hour represents that the integrated energy system is in the electricity selling state at the moment t, P isexc(t) selling electricity; when P is presentexc(t)<When 0 hour represents that the comprehensive energy system is in the electricity purchasing state at the moment t, P isexc(t) the purchase amount of electricity; c1(t) and C2(t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
s24: and constructing the energy flow optimization operation model according to the optimization operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set.
The method comprises the steps that a power relation between information flow and energy flow in the whole comprehensive energy system can be obtained based on a photoelectric power generation power model and a cogeneration power model, the working condition that the information flow and the energy flow in the comprehensive energy system can keep normal operation is limited by an energy flow constraint condition set, and then the minimum daily operation cost of the comprehensive energy system is taken as the target of optimized operation to obtain an optimized operation target function between the information flow and the energy flow in the whole comprehensive energy system; the energy flow optimization operation model is constructed based on the optimization operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set, the connection relation and the interaction mechanism between the information layer and the physical layer of the comprehensive energy system can be fully considered, the unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system are realized, the subsequent optimal optimization operation scheme can be conveniently obtained, the optimal control of the energy flow is realized, and the energy utilization rate is effectively improved.
Specifically, in this embodiment S21, the expression of the photovoltaic power generation model is specifically:
wherein, Ppv(T) is the total output power of the photovoltaic power generation device at the time T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the time T, and is the power temperature coefficient of the photovoltaic power generation device, Tw(T) is the operating temperature of the photovoltaic power generation device at time T, T0Is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein the content of the first and second substances,
and
respectively refers to the generated power and the generated power of the cogeneration unit at the moment t under the ith new energy prediction scene, K is the output running range of the cogeneration unit,
and
respectively is the kth electrode value point and the kth thermal electrode value point in the output running range of the cogeneration unit,
in the ith new energy prediction scene, the kth output coefficient of the cogeneration unit at the time t is determined, wherein the kth electrode value point and the kth thermal extreme value point correspond to the kth output coefficient.
The specific photovoltaic power generation power model and the cogeneration power model truly reflect the power relation between the information flow and the energy flow in the whole comprehensive energy system, and are convenient for obtaining a more accurate and reasonable energy flow optimization operation model subsequently.
Specifically, in this embodiment S22, the set of energy flow constraints includes a power supply balance constraint, a heat storage device constraint, and an energy storage battery constraint;
the specific formula of the power supply balance constraint condition is as follows:
wherein, PLi(t) is the stored power of the energy storage battery at the moment tOr discharging power; when P is presentLiWhen (t) is more than or equal to 0, the energy storage battery is in the electricity storage state at the time of t, and then PLi(t) is the stored power; when P is presentLi(t)<When 0 represents that the energy storage battery is in a power-off state at the moment t, P isLi(t) is the discharge power; pL(t) and Ploss(t) the power demand of the consumer's electrical load and the grid loss, P, of the power system at time tHP(t) and QHP(t) respectively the active and reactive power of the heat pump at time t, PHP(t-1) and QHP(t-1) respectively the active power and the reactive power of the heat pump at the moment t-1,
and SHP,maxRespectively, active power limit and apparent power limit, Δ P, of the heat pumpHPAnd Δ QHPThe active power climbing limit value and the reactive power climbing limit value of the heat pump are respectively set;
the specific formula of the heat supply balance constraint condition is as follows:
wherein the content of the first and second substances,
and
the heat storage power and the heat release power of the heat storage tank at the moment t are respectively satisfied
HCHP(t) and HDmd(t) the heat production power of the cogeneration unit and the user heat load demand power at the moment t are respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E isre(t) is the heat storage amount of the heat storage tank at time t, Ere(t-1) is the heat storage amount of the heat storage tank at the moment t-1, etaHPIn order to obtain the electric-to-heat conversion efficiency of the heat pump,
for the heat release of the heat storage tank at time t, Ere-maxThe maximum heat storage capacity of the heat storage tank, SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy SLimin≤SLi(t)≤SLimax
Wherein S isLi(t) and SLi(t-1) respectively representing the SOC residual capacity ratio of the energy storage battery at the time t and the SOC residual capacity ratio of the energy storage battery at the time t-1, SLimaxAnd SLiminRespectively an upper limit and a lower limit of the SOC residual capacity of the energy storage battery,
and SLi,NRespectively the self-discharge rate and the rated stored electricity quantity, gamma, of the energy storage batteryLicAnd gammaLidRespectively the charging efficiency and the discharging efficiency, deltat, of the energy storage battery1To take a 1 hour scheduling interval.
The four constraint conditions (including the power supply balance constraint condition, the heat storage equipment constraint condition and the energy storage battery constraint condition) more comprehensively and accurately limit the working conditions of the integrated energy system when the information flow and the energy flow can keep normal operation, so that the finally obtained optimized operation scheme is optimal, the operation efficiency and the optimization rate of the integrated energy system can be further improved on the basis of ensuring the normal operation of the integrated energy system, and the energy utilization rate is further effectively improved.
Specifically, in the constraint condition of power supply balance, the active power extreme value of the heat pump
At 2.4MW, apparent power limit SHP,maxIs 2.4MVA, active power ramp limit value delta PHPAnd reactive power ramp limit Δ QHP2.4MW and 1.6Mvar, respectively; maximum heat storage capacity E of the heat storage tank in the heat storage device constraintre-maxIs 16 MWh; self-discharge rate of energy storage battery in energy storage battery constraint condition
And rated stored energy SLi,N1.5%/month and 10MWh respectively, and the charging efficiency gamma of the energy storage batteryLicAnd discharge efficiency gammaLidAre all 0.95, and the upper limit S of the SOC residual capacity of the energy storage batteryLimaxAnd a lower limit SLiminRespectively 1 and 0.
Specifically, in the optimized operation objective function of the embodiment, the electricity purchase price C of the integrated energy system at the time t is1(t) 0.3 yuan/kWh, and the electricity purchase price C of the integrated energy system at the time t2(t) implementing a step tariff, specifically: 7: 00-22: the electricity price is 0.7 yuan/kWh in the 00 time period, and 0.3 yuan/kWh in the rest time period.
Preferably, the optimized operation scheme comprises an optimized energy flow control strategy and a power purchase and sale plan;
as shown in fig. 8, S3 specifically includes the following steps:
s31: respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
s32: based on the mixed integer linear programming method, under the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
s33: the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication management machine to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electricity load and the user heat load.
The method comprises the steps of respectively setting a first working mode of a photovoltaic power generation device and a second working mode of a cogeneration unit, determining the flow direction of generated power of the photovoltaic power generation device and the flow direction of heat generated by the cogeneration unit, further specifying an optimal operation control strategy of the energy flow of the integrated energy system under the flow direction of the generated power and the flow direction of the heat, simultaneously determining an optimal purchase and sale power plan of the integrated energy system under the optimal operation control strategy, and after obtaining the optimal operation control strategy, in order to ensure that the energy flow of the integrated energy system can operate according to the optimal energy flow control strategy, respectively issuing the optimal energy flow control strategy to the photovoltaic power generation device, an energy storage device, a heat pump, the cogeneration unit, a user power load and a user heat load by using an intelligent energy gateway and a communication management machine through an integrated energy supply and demand platform, the optimal control of the energy flow is really realized, the energy loss is effectively reduced, the energy utilization rate is improved, and the economic and safe operation of the comprehensive energy system is realized.
The mixed integer linear programming method is one of integer linear programming models, and mixed integer linear programming is adopted when only one part of decision variables in the model are required to be non-negative integers and the other part of decision variables can be non-negative real numbers; the specific operation steps of the mixed integer linear programming method are the prior art, and the details are not described herein.
Specifically, the integrated energy system is a grid-connected integrated energy system, and the first operating mode and the second operating mode both specifically adopt a self-generation self-use operating mode and a margin grid-connection operating mode.
When the heat pump also adopts a self-generation self-use and surplus internet-surfing working mode, the generated energy generated by the photovoltaic power generation device is preferentially supplied to a user electric load, and if surplus energy exists, the surplus energy is preferentially stored in an energy storage device such as an energy storage battery; when the cogeneration unit adopts a working mode of self-generation and self-use and surplus internet surfing, heat energy generated by the cogeneration unit is preferentially supplied to a heat load of a user, if redundant heat is preferentially stored in heat storage equipment such as a heat storage tank, and if the energy storage tank cannot absorb all energy, the redundant electric energy is sold to a power grid, and the redundant heat energy is discarded; in addition, when the heat pump also adopts a self-generation self-use and surplus internet-surfing working mode, heat energy generated by the heat pump is preferentially supplied to a user heat load, if surplus heat is preferentially stored in heat storage equipment such as a heat storage tank, and if the energy storage tank cannot absorb all energy, surplus electric energy is sold to a power grid, and surplus heat energy is discarded; on the basis of the energy flow direction, if the power generation/heating equipment generates power generation/heating quantity which cannot supply the electricity/heat load demand of a user, the comprehensive energy system directly meets the electricity load demand of the user by purchasing electricity from a power grid, and converts electric energy into heat energy to meet the heat load demand of the user through a heat pump.
Specifically, in the present embodiment, under the photovoltaic-load scenario shown in fig. 6, according to the steps from S1 to S3, an energy flow optimization control strategy and a power purchase and sale plan are obtained, an electricity price-electricity purchase curve (i.e., a power purchase and sale plan) of the integrated energy system is shown in fig. 9, and after the energy flow optimization control strategy is performed, an obtained electricity/thermal energy storage SOC remaining capacity ratio curve is shown in fig. 10, and a power curve of the heat pump/energy storage battery is shown in fig. 11; the obtained final daily operating cost of the integrated energy system and the power grid is 17872 yuan, according to the electricity/heat energy storage SOC remaining capacity ratio curve in fig. 10 and the electricity purchasing and selling plan diagram in fig. 9, the integrated energy system purchases 33.4MWh of electric energy in a large amount in the valley period, only purchases 11.2MWh of electric energy in the peak period, the integrated energy system meets the user electricity load demand and the user heat load demand by consuming the electric quantity of the energy storage battery and the heat of the heat storage tank in the peak period, and the SOC capacity of the energy storage device is recovered to the initial value until a small amount of electricity is purchased before the end of a one-day period, so that the operating cost of the integrated energy system is greatly reduced.
In the second embodiment, as shown in fig. 12, an optimized modeling operation device of an integrated energy system is applied to the optimized modeling operation method of the integrated energy system in the first embodiment, and includes an information flow acquisition module, an energy flow modeling module and an optimization solution module;
the information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme.
The optimized modeling operation device of the integrated energy system formed by the modules can collect information of each energy device of an energy layer in the integrated energy system and form information flow of the information layer, unified modeling and quantitative analysis are carried out on the information flow and the energy flow of the integrated energy system, an optimized operation model of the energy flow can be optimized and solved from a set optimized operation objective function and an energy flow constraint condition set by utilizing the technology of the information layer, an optimal optimized operation scheme is obtained, joint analysis of the information layer and the physical layer of the integrated energy system is realized, optimal control is carried out on the energy flow, the energy utilization rate is improved, economic and safe operation of the integrated energy system is realized, and sustainable development is realized.
Preferably, the comprehensive energy system comprises an intelligent energy gateway, a comprehensive energy supply and demand platform, a communication manager and a comprehensive energy device group;
the information flow obtaining module is specifically configured to:
acquiring an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
converting the equipment information set by using the communication manager to form an original information stream;
performing logic processing on the original information flow by using the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user heat load;
the equipment information set comprises total output power of the distributed power generation device, active power and reactive power of the heat pump, power generation power and heat generation power of the cogeneration unit, energy storage capacity, charging power and discharging power of the energy storage device, user electrical load demand power and user thermal load demand power at each moment.
Preferably, the distributed power generation equipment is specifically a photovoltaic power generation device; the power model comprises a photovoltaic power generation power model and a combined heat and power generation power model;
the energy flow modeling module is specifically configured to:
constructing a photovoltaic power generation power model according to the total output power of the photovoltaic power generation device, and constructing a cogeneration power model according to the generated power and the generated heat power of the cogeneration unit;
obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the electricity generating power and the heat generating power of the cogeneration unit, the active power and the reactive power of the heat pump, the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device, the user electricity load demand power and the user heat load demand power;
acquiring the exchange electric quantity between the comprehensive energy system and a power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
minF is the optimized operation objective function, F is the daily operation cost of the comprehensive energy system, c (T) is the electricity exchange cost of the comprehensive energy system and the power grid at the moment T, and T isDuration of daily operating cycle, Pexc(t) the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P is presentexc(t)>When 0 hour represents that the integrated energy system is in the electricity selling state at the moment t, P isexc(t) selling electricity; when P is presentexc(t)<When 0 hour represents that the comprehensive energy system is in the electricity purchasing state at the moment t, P isexc(t) the purchase amount of electricity; c1(t) and C2(t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
and constructing the energy flow optimization operation model according to the optimization operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set.
Preferably, the expression of the photovoltaic power generation power model is specifically:
wherein, Ppv(T) is the total output power of the photovoltaic power generation device at the time T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the time T, and is the power temperature coefficient of the photovoltaic power generation device, Tw(T) is the operating temperature of the photovoltaic power generation device at time T, T0Is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein the content of the first and second substances,
and
respectively representing the electricity generating power and the heat generating power of the cogeneration unit at the moment t under the ith new energy prediction scene, and K is the cogeneration unitThe operating range of the output of the group,
and
respectively is the kth electrode value point and the kth thermal electrode value point in the output running range of the cogeneration unit,
in the ith new energy prediction scene, the kth output coefficient of the cogeneration unit at the time t is determined, wherein the kth electrode value point and the kth thermal extreme value point correspond to the kth output coefficient.
Preferably, the energy storage device specifically comprises an energy storage battery and a heat storage tank; the energy flow constraint condition set comprises a power supply balance constraint condition, a heat storage device constraint condition and an energy storage battery constraint condition;
the specific formula of the power supply balance constraint condition is as follows:
wherein, PLi(t) is the stored power or the released power of the energy storage battery at the moment t; when P is presentLiWhen (t) is more than or equal to 0, the energy storage battery is in the electricity storage state at the time of t, and then PLi(t) is the stored power; when P is presentLi(t)<When 0 represents that the energy storage battery is in a power-off state at the moment t, P isLi(t) is the discharge power; pL(t) and Ploss(t) the power demand of the consumer's electrical load and the grid loss, P, of the power system at time tHP(t) and QHP(t) respectively the active and reactive power of the heat pump at time t, PHP(t-1) and QHP(t-1) respectively the active power and the reactive power of the heat pump at the moment t-1,
and SHP,maxRespectively, active power limit and apparent power limit, Δ P, of the heat pumpHPAnd Δ QHPThe active power climbing limit value and the reactive power climbing limit value of the heat pump are respectively set;
the specific formula of the heat supply balance constraint condition is as follows:
wherein the content of the first and second substances,
and
the heat storage power and the heat release power of the heat storage tank at the moment t are respectively satisfied
HCHP(t) and HDmd(t) the heat production power of the cogeneration unit and the user heat load demand power at the moment t are respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E isre(t) is the heat storage amount of the heat storage tank at time t, Ere(t-1) is the heat storage amount of the heat storage tank at the moment t-1, etaHPIn order to obtain the electric-to-heat conversion efficiency of the heat pump,
for the heat release of the heat storage tank at time t, Ere-maxThe maximum heat storage capacity of the heat storage tank, SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy SLimin≤SLi(t)≤SLimax
Wherein S isLi(t) and SLi(t-1) respectively representing the SOC residual capacity ratio of the energy storage battery at the time t and the SOC residual capacity ratio of the energy storage battery at the time t-1, SLimaxAnd SLiminRespectively an upper limit and a lower limit of the SOC residual capacity of the energy storage battery,
and SLi,NRespectively the self-discharge rate and the rated stored electricity quantity, gamma, of the energy storage batteryLicAnd gammaLidRespectively the charging efficiency and the discharging efficiency, deltat, of the energy storage battery1To take a 1 hour scheduling interval.
Preferably, the optimized operation scheme comprises an optimized energy flow control strategy and a power purchase and sale plan;
the optimization solution model is specifically configured to:
respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
based on the mixed integer linear programming method, under the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication management machine to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electricity load and the user heat load.
Preferably, the integrated energy system is a grid-connected integrated energy system, and the first operating mode and the second operating mode both specifically adopt a self-generation self-use operating mode and a margin grid-connection operating mode.
The third embodiment is based on the first embodiment and the second embodiment, and the present embodiment further discloses an optimization modeling operation device of an integrated energy system, which includes a processor, a memory, and a computer program stored in the memory and operable on the processor, and the computer program implements the specific steps from S1 to S3 when running.
The information of each energy device of the energy layer in the integrated energy system can be collected and information flow of the information layer can be formed by running the computer program stored on the memory on the processor, the information flow and the energy flow of the integrated energy system are subjected to unified modeling and quantitative analysis, the energy flow optimization operation model can be optimized and solved from a set optimization operation objective function and energy flow constraint condition set by utilizing the technology of the information layer, an optimal optimization operation scheme is obtained, the joint analysis of the information layer and the physical layer of the integrated energy system is realized, the optimal control is carried out on the energy flow, the energy utilization rate is improved, the economic and safe operation of the integrated energy system is realized, and the green sustainable development is realized.
The present embodiment also provides a computer storage medium having at least one instruction stored thereon, where the instruction when executed implements the specific steps of S1-S3.
The method comprises the steps of executing a computer storage medium containing at least one instruction, acquiring information of each energy device of an energy layer in the integrated energy system, forming an information flow of the information layer, performing unified modeling and quantitative analysis on the information flow and the energy flow of the integrated energy system, performing optimized solution on an energy flow optimized operation model from a set optimized operation objective function and an energy flow constraint condition set by using the technology of the information layer, obtaining an optimal optimized operation scheme, realizing joint analysis of the information layer and a physical layer of the integrated energy system, performing optimal control on the energy flow, improving the energy utilization rate, realizing economic and safe operation of the integrated energy system, and realizing green sustainable development.
Details of the embodiment are not described in detail in the first embodiment and the specific descriptions in fig. 1 to 11, which are not repeated herein.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. An optimized modeling operation method of an integrated energy system is characterized by comprising the following steps:
acquiring a target information flow of the comprehensive energy system;
respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme.
2. The method of claim 1, wherein the integrated energy system comprises a smart energy gateway, an integrated energy supply and demand platform, a communication manager, and an integrated energy device group;
the step of obtaining the target information stream specifically comprises the following steps:
acquiring an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
converting the equipment information set by using the communication manager to form an original information stream;
performing logic processing on the original information flow by using the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user heat load;
the equipment information set comprises total output power of the distributed power generation device, active power and reactive power of the heat pump, power generation power and heat generation power of the cogeneration unit, energy storage capacity, charging power and discharging power of the energy storage device, user electrical load demand power and user thermal load demand power at each moment.
3. The method for optimized modeling operation of an integrated energy system according to claim 2, wherein said distributed power generation equipment is specifically a photovoltaic power generation device; the power model comprises a photovoltaic power generation power model and a combined heat and power generation power model;
the method for constructing the energy flow optimization operation model of the comprehensive energy system specifically comprises the following steps:
constructing a photovoltaic power generation power model according to the total output power of the photovoltaic power generation device, and constructing a cogeneration power model according to the generated power and the generated heat power of the cogeneration unit;
obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the electricity generating power and the heat generating power of the cogeneration unit, the active power and the reactive power of the heat pump, the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device, the user electricity load demand power and the user heat load demand power;
acquiring the exchange electric quantity between the comprehensive energy system and a power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
minF is the optimized operation objective function, F is the daily operation cost of the comprehensive energy system, c (T) is the electricity exchange cost of the comprehensive energy system and the power grid at the moment T, T is the daily operation period duration, and P is the timeexc(t) is the integrated energy systemExchanging electric quantity with the power grid at the moment t; when P is presentexc(t)>When 0 hour represents that the integrated energy system is in the electricity selling state at the moment t, P isexc(t) selling electricity; when P is presentexc(t)<When 0 hour represents that the comprehensive energy system is in the electricity purchasing state at the moment t, P isexc(t) the purchase amount of electricity; c1(t) and C2(t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
and constructing the energy flow optimization operation model according to the optimization operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set.
4. The optimal modeling operation method of the integrated energy system according to claim 3, wherein the expression of the photovoltaic power generation power model is specifically:
wherein, Ppv(T) is the total output power of the photovoltaic power generation device at the time T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the time T, and is the power temperature coefficient of the photovoltaic power generation device, Tw(T) is the operating temperature of the photovoltaic power generation device at time T, T0Is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein the content of the first and second substances,
and
respectively predicting the ith new energyUnder the scene, the power generation power and the heat generation power of the cogeneration unit at the time t, K is the output operation range of the cogeneration unit,
and
respectively is the kth electrode value point and the kth thermal electrode value point in the output running range of the cogeneration unit,
in the ith new energy prediction scene, the kth output coefficient of the cogeneration unit at the time t is determined, wherein the kth electrode value point and the kth thermal extreme value point correspond to the kth output coefficient.
5. The optimized modeling operation method of the integrated energy system according to claim 4, wherein the energy storage device specifically comprises an energy storage battery and a heat storage tank; the energy flow constraint condition set comprises a power supply balance constraint condition, a heat storage device constraint condition and an energy storage battery constraint condition;
the specific formula of the power supply balance constraint condition is as follows:
wherein, PLi(t) is the stored power or the released power of the energy storage battery at the moment t; when P is presentLiWhen (t) is more than or equal to 0, the energy storage battery is in the electricity storage state at the time of t, and then PLi(t) is the stored power; when P is presentLi(t)<When 0 represents that the energy storage battery is in a power-off state at the moment t, P isLi(t) is the discharge power; pL(t) and Ploss(t) the power demand of the consumer's electrical load and the grid loss, P, of the power system at time tHP(t) and QHP(t) at time t of the heat pumpPower and reactive power, PHP(t-1) and QHP(t-1) respectively the active power and the reactive power of the heat pump at the moment t-1,
and SHP,maxRespectively, active power limit and apparent power limit, Δ P, of the heat pumpHPAnd Δ QHPThe active power climbing limit value and the reactive power climbing limit value of the heat pump are respectively set;
the specific formula of the heat supply balance constraint condition is as follows:
wherein the content of the first and second substances,
and
the heat storage power and the heat release power of the heat storage tank at the moment t are respectively satisfied
HCHP(t) and HDmd(t) the heat production power of the cogeneration unit and the user heat load demand power at the moment t are respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E isre(t) is the heat storage amount of the heat storage tank at time t, Ere(t-1) is the heat storage amount of the heat storage tank at the moment t-1, etaHPIn order to obtain the electric-to-heat conversion efficiency of the heat pump,
for the heat release of the heat storage tank at time t, Ere-maxThe maximum heat storage capacity of the heat storage tank, SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy SLimin≤SLi(t)≤SLimax
Wherein S isLi(t) and SLi(t-1) respectively representing the SOC residual capacity ratio of the energy storage battery at the time t and the SOC residual capacity ratio of the energy storage battery at the time t-1, SLimaxAnd SLiminRespectively an upper limit and a lower limit of the SOC residual capacity of the energy storage battery,
and SLi,NRespectively the self-discharge rate and the rated stored electricity quantity, gamma, of the energy storage batteryLicAnd gammaLidRespectively the charging efficiency and the discharging efficiency, deltat, of the energy storage battery1To take a 1 hour scheduling interval.
6. The method of operation of an integrated energy system according to claim 3 wherein the optimal operating scheme comprises an optimal energy flow control strategy and a power purchase and sale plan;
the obtaining of the optimized operation scheme specifically comprises the following steps:
respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
based on the mixed integer linear programming method, under the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication management machine to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electricity load and the user heat load.
7. The method according to claim 6, wherein the integrated energy system is a grid-connected integrated energy system, and the first operating mode and the second operating mode both use a self-powered operating mode and a margin grid-connected operating mode.
8. An optimized modeling operation device of an integrated energy system, which is applied to the optimized modeling operation method of the integrated energy system according to any one of claims 1 to 7, and comprises an information flow acquisition module, an energy flow modeling module and an optimized solution module;
the information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the integrated energy system, and constructing an energy flow optimized operation model of the integrated energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme.
9. An apparatus for optimized modeling operation of an integrated energy system, comprising a processor, a memory and a computer program stored in the memory and operable on the processor, the computer program when executed implementing the method steps of any of claims 1 to 7.
10. A computer storage medium, the computer storage medium comprising: at least one instruction which, when executed, implements the method steps of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010758147.2A CN111899125B (en) | 2020-07-31 | 2020-07-31 | Optimized modeling operation method, device and medium of comprehensive energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010758147.2A CN111899125B (en) | 2020-07-31 | 2020-07-31 | Optimized modeling operation method, device and medium of comprehensive energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111899125A true CN111899125A (en) | 2020-11-06 |
| CN111899125B CN111899125B (en) | 2024-02-27 |
Family
ID=73182947
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010758147.2A Active CN111899125B (en) | 2020-07-31 | 2020-07-31 | Optimized modeling operation method, device and medium of comprehensive energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111899125B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565244A (en) * | 2022-02-16 | 2022-05-31 | 石河子大学 | Optimized scheduling method and device of comprehensive energy system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109784569A (en) * | 2019-01-23 | 2019-05-21 | 华北电力大学 | A kind of regional complex energy resource system optimal control method |
| CN110417006A (en) * | 2019-07-24 | 2019-11-05 | 三峡大学 | Consider the integrated energy system Multiple Time Scales energy dispatching method of multipotency collaboration optimization |
| CN110889600A (en) * | 2019-11-13 | 2020-03-17 | 国家电网有限公司 | Regional comprehensive energy system optimization scheduling method considering flexible thermal load |
-
2020
- 2020-07-31 CN CN202010758147.2A patent/CN111899125B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109784569A (en) * | 2019-01-23 | 2019-05-21 | 华北电力大学 | A kind of regional complex energy resource system optimal control method |
| CN110417006A (en) * | 2019-07-24 | 2019-11-05 | 三峡大学 | Consider the integrated energy system Multiple Time Scales energy dispatching method of multipotency collaboration optimization |
| CN110889600A (en) * | 2019-11-13 | 2020-03-17 | 国家电网有限公司 | Regional comprehensive energy system optimization scheduling method considering flexible thermal load |
Non-Patent Citations (1)
| Title |
|---|
| 顾伟等: "多区域综合能源系统热网建模及系统运行优化", 中国电机工程学报, vol. 37, no. 5, pages 1305 - 1315 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565244A (en) * | 2022-02-16 | 2022-05-31 | 石河子大学 | Optimized scheduling method and device of comprehensive energy system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111899125B (en) | 2024-02-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110350523B (en) | Multi-energy complementary optimization scheduling method based on demand response | |
| CN103151803B (en) | Method for optimizing wind power system-contained unit and backup configuration | |
| CN109473976A (en) | A kind of supply of cooling, heating and electrical powers type microgrid energy dispatching method and system | |
| CN112583017A (en) | Hybrid micro-grid energy distribution method and system considering energy storage operation constraint | |
| CN113988444A (en) | Electricity charge optimization control system and method for light storage system | |
| CN113437752A (en) | Operation control method for comprehensive energy system containing hybrid energy storage | |
| CN114498639A (en) | Day-ahead scheduling method for multi-microgrid combined mutual aid considering demand response | |
| CN112836849A (en) | Virtual power plant scheduling method considering wind power uncertainty | |
| CN116957294A (en) | Scheduling method for virtual power plant to participate in electric power market transaction based on digital twin | |
| CN111899125B (en) | Optimized modeling operation method, device and medium of comprehensive energy system | |
| CN112418537B (en) | Optimized scheduling method for multi-energy cloud energy storage system | |
| CN110224397B (en) | User-side battery energy storage cost benefit analysis method under wind and light access background | |
| CN109376406B (en) | Energy supply system superstructure model, modeling method, computer device and storage medium | |
| CN108683211B (en) | Virtual power plant combination optimization method and model considering distributed power supply volatility | |
| CN110994698A (en) | Optimized operation method of solar photovoltaic-photothermal combined power generation system | |
| CN115693793A (en) | Energy optimization control method for regional micro-grid | |
| CN110766285A (en) | Day-ahead energy scheduling method based on virtual power plant | |
| Ran et al. | Economic dispatch of off-grid photovoltaic generation system with hybrid energy storage | |
| Han et al. | Analysis of economic operation model for virtual power plants considering the uncertainties of renewable energy power generation | |
| CN113128746A (en) | Multi-agent-based multi-main-body combined optimization operation method for comprehensive energy system | |
| CN110266059A (en) | A kind of new energy feed system Optimal Configuration Method based on triangle comprehensive assessment | |
| CN113256009B (en) | Two-stage multi-standby configuration method, system and device based on aerothermal inertia | |
| CN114862163B (en) | Optimized scheduling method of comprehensive energy system | |
| CN117574684A (en) | Sequential production simulation method and system for electric-hydrogen-carbon comprehensive energy system | |
| CN108063447B (en) | Improved power storage modulation method for load power valley filling in power grid valley period |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |