CN113437752A - Operation control method for comprehensive energy system containing hybrid energy storage - Google Patents

Operation control method for comprehensive energy system containing hybrid energy storage Download PDF

Info

Publication number
CN113437752A
CN113437752A CN202110694608.9A CN202110694608A CN113437752A CN 113437752 A CN113437752 A CN 113437752A CN 202110694608 A CN202110694608 A CN 202110694608A CN 113437752 A CN113437752 A CN 113437752A
Authority
CN
China
Prior art keywords
energy
electric
energy storage
gas
operating parameter
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
Application number
CN202110694608.9A
Other languages
Chinese (zh)
Other versions
CN113437752B (en
Inventor
张鹏
唐若愚
周步祥
臧天磊
张越
罗欢
董申
陈实
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.)
Sichuan University
Dongfang Electric Machinery Co Ltd DEC
Original Assignee
Sichuan University
Dongfang Electric Machinery Co Ltd DEC
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 Sichuan University, Dongfang Electric Machinery Co Ltd DEC filed Critical Sichuan University
Priority to CN202110694608.9A priority Critical patent/CN113437752B/en
Publication of CN113437752A publication Critical patent/CN113437752A/en
Application granted granted Critical
Publication of CN113437752B publication Critical patent/CN113437752B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • 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
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

Abstract

The application provides a comprehensive energy system operation control method containing hybrid energy storage, and relates to the technical field of energy scheduling. Starting from the actual operation condition of the energy storage device, a preset hybrid energy storage-containing comprehensive energy system comprising the distributed energy storage device, the distributed energy generation device and the energy conversion device is constructed, the preset hybrid energy storage-containing comprehensive energy system can be a virtual power plant, each device in the virtual power plant is independently modeled in detail, energy balance constraint, hybrid energy storage constraint, device operation constraint and energy transmission network constraint are comprehensively considered for the hybrid energy storage-containing comprehensive energy virtual power plant, and finally an optimized scheduling model of the hybrid energy storage-containing comprehensive energy virtual power plant is established by taking the maximum income and the minimum energy loss as objective functions, so that the electric energy conversion amount of each device in the distributed energy storage device is obtained, and the random fluctuation and the intermittence of the distributed energy are compensated through the electric energy conversion of the energy storage device.

Description

Operation control method for comprehensive energy system containing hybrid energy storage
Technical Field
The application relates to the technical field of energy scheduling, in particular to a comprehensive energy system operation control method with hybrid energy storage.
Background
Energy is an important foundation for the operation and development of the global society, and the problem of non-negligible environmental pollution is caused for a long time because human beings depend on fossil energy with limited resources excessively. In response to the problems of exhaustion of energy and environmental pollution, clean energy such as electricity, natural gas, and new energy are gradually being developed from research into applications.
The new energy in different regions is distributed unevenly, for example, the regions with enough wind energy for generating electricity are mainly in open regions such as northern plains, grasslands and the like; areas capable of photovoltaic power generation are concentrated on plateaus; the areas capable of carrying out river hydroelectric generation are mostly along the coasts of yellow river and Yangtze river. Meanwhile, the power consumption condition and the power consumption peak value are different in different regions, for example, the power consumption of high voltage is larger in daytime in a plurality of factories in the pearl triangle area; the provinces and the cities have large urban population, and the peak value of low-voltage electricity utilization is usually generated at night. Based on the above situation, the rationality and immediacy of energy scheduling and allocation are particularly important.
In the prior art, the dispatching and distribution of electric power are generally adjusted by laying a power transmission network, however, the circuit network has a long setting period and cannot cope with sudden power utilization peaks or other power utilization conditions.
Disclosure of Invention
The embodiment of the application provides a method for controlling the operation of a comprehensive energy system with hybrid energy storage, which can coordinate energy requirements among areas according to the charging amount or the discharging amount of a distributed energy storage device, and further adjust the power utilization peak value or other power utilization conditions among the areas.
The embodiment of the application provides a method for controlling the operation of an integrated energy system containing hybrid energy storage, which comprises the following steps:
adding the distributed energy storage device into the electric-heating-gas comprehensive energy system according to the consumption demand of renewable energy to obtain a preset comprehensive energy system containing mixed energy storage; the electric-thermal gas integrated energy system comprises a distributed energy generation device;
constructing an optimized dispatching model of the preset hybrid energy storage-containing comprehensive energy system according to the first operating parameter and the second operating parameter; wherein the first operating parameter is stored energy power of the distributed energy storage device and the second operating parameter is power of the distributed energy generation device;
constructing an energy abandoning model of the distributed energy generation device;
and calculating the electric energy conversion amount of the distributed energy storage device by using a fuzzy membership function according to the first solving target and the second solving target so as to balance the energy difference amount of the preset comprehensive energy system containing mixed energy storage by using the electric energy conversion amount.
Optionally, the distributed energy generation device comprises a wind power device and a photovoltaic power generation device; according to renewable energy's consumption demand, add electric heat gas comprehensive energy system with distributed energy storage device, obtain predetermineeing the comprehensive energy system who contains mixed energy storage, include:
adding a gas-electricity conversion device into an electric heating-gas comprehensive energy system according to the electric power consumption required by the wind power device and the photovoltaic power generation device;
adding the new energy automobile into an electric heating and gas comprehensive energy system according to the energy conversion characteristics of the new energy automobile;
adding the hydrogen storage device into an electric heating gas comprehensive energy system according to the characteristic that the hydrogen storage device is converted with various energy sources and the long-term energy storage requirement;
and adding a storage battery and a heat storage tank into the preset comprehensive energy system containing mixed energy storage according to the real-time energy storage requirement.
Optionally, the preset comprehensive energy system containing hybrid energy storage is respectively connected with an external power grid and an external heat supply network; the method further comprises the following steps:
and adding an electric boiler into the preset comprehensive energy system containing the mixed energy storage according to the energy demand difference between the external power grid and the external heat grid so as to adjust, optimize and control the combined heat and power demand of different areas.
Optionally, the preset comprehensive energy system containing hybrid energy storage is connected with an external air network; the method further comprises the following steps:
and adding a gas boiler, a gas turbine and a waste heat recovery device into the preset comprehensive energy system containing hybrid energy storage according to the energy demand difference between the external power grid and the external air grid and the energy demand difference between the external heat supply grid and the external air grid so as to adjust and optimally control the energy co-supply requirements of different areas.
Optionally, the method further comprises:
acquiring the electric quantity demand of the current time;
constructing a first energy model of the distributed energy storage device; the first energy model is used for representing the correlation relationship between the first operating parameter and the electric energy conversion amount generated by the distributed energy storage device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the electric quantity demand, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Optionally, the method further comprises:
acquiring the electric quantity demand of the current time;
constructing an electric energy balance constraint condition according to the electric quantity demand and the real-time electric quantity generated by the distributed energy generation device;
constructing a second electric energy balance constraint condition according to the abandoned wind loss of the wind power device and the abandoned light loss of the photovoltaic power generation device;
calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps:
and under the first electric energy balance constraint condition and the second electric energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
Optionally, the method further comprises:
acquiring the heat demand, the heat energy supply quantity, the gas energy demand and the gas energy supply quantity at the current time;
constructing a heat energy balance constraint condition according to the heat demand and the heat energy supply quantity;
constructing a gas energy balance constraint condition according to the gas energy demand and the gas energy supply quantity;
calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps:
and under the heat energy balance constraint condition and the gas energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
Optionally, the method further comprises:
constructing a second energy model of the distributed energy generation device; the second energy model is used for representing the correlation between the second operation parameter and the output of the distributed energy generation device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the second energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Optionally, the preset hybrid energy storage-containing comprehensive energy system comprises an energy conversion device; the method further comprises the following steps:
adding an energy conversion device into the electric-heating-gas comprehensive energy system according to the energy conversion requirement between any two of the external power grid, the external gas grid and the external heat supply network to obtain a preset comprehensive energy system with energy conversion device and hybrid energy storage;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
constructing the optimized scheduling model according to the first operating parameter, the second operating parameter and the third operating parameter; wherein the third operating parameter is a discharge efficiency, a heat release efficiency, or a gas energy consumption of the energy conversion device.
Optionally, the method further comprises:
constructing a third energy model of the energy conversion device; wherein the third energy model is used for characterizing the correlation of the third operating parameter and the energy consumption of the energy conversion device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the third energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Starting from the actual operation condition of the energy storage device, a preset hybrid energy storage-containing comprehensive energy system comprising the distributed energy storage device, the distributed energy generation device and the energy conversion device is constructed, and the preset hybrid energy storage-containing comprehensive energy system can be a virtual power plant, so that in the process of coordinating the energy of each energy system through a communication technology and a software architecture, the distributed energy storage device is utilized to supplement the shortage of electric power at the peak power utilization value, and the distributed energy storage device is utilized to store electric energy at the bottom of a power utilization valley, or the electric energy is converted into gas energy, heat energy or chemical energy to supplement the instantaneous consumption of other energy; the embodiment of the application respectively connects the preset comprehensive energy system containing the hybrid energy storage with the external power grid, the external air grid and the external heat supply network, constructs an optimized dispatching model taking the maximum benefit as the target, meanwhile, an energy abandoning model taking minimum energy abandoning loss as a target is constructed, the real-time generated energy, the demand of real-time users for various energy sources and the loss input optimization scheduling model and the energy abandoning model for maintaining the distributed energy storage devices, the distributed energy generation devices and the energy conversion devices are solved to obtain the electric energy conversion quantity which can take the maximum profit target and the minimum energy abandoning loss target into consideration, the electric energy conversion quantity is the charging quantity or the discharging quantity of the distributed energy storage devices, further coordinating the energy demand between the zones with the charge or discharge of the distributed energy storage devices, or the charging amount or the discharging amount of the distributed energy storage device supplements the energy gap of the distributed energy generation device caused by random fluctuation and intermittence.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart illustrating steps of a method for controlling operation of an integrated energy system including hybrid energy storage according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of an integrated energy system with hybrid energy storage preset in the embodiment of the present application;
fig. 3 is a functional block diagram of an integrated energy system operation control device including hybrid energy storage according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Starting from the actual operation condition of the energy storage device, a preset hybrid energy storage-containing comprehensive energy system comprising the distributed energy storage device, the distributed energy generation device and the energy conversion device is constructed, and the preset hybrid energy storage-containing comprehensive energy system can be a virtual power plant, so that in the process of coordinating the energy of each energy system through a communication technology and a software architecture, the distributed energy storage device is utilized to supplement the shortage of electric power at the peak power utilization value, and the distributed energy storage device is utilized to store electric energy at the bottom of a power utilization valley, or the electric energy is converted into gas energy, heat energy or chemical energy to supplement the instantaneous consumption of other energy; the embodiment of the application respectively connects the preset comprehensive energy system containing the hybrid energy storage with the external power grid, the external air grid and the external heat supply network, constructs an optimized dispatching model taking the maximum benefit as the target, meanwhile, an energy abandoning model taking minimum energy abandoning loss as a target is constructed, the real-time generated energy, the demand of real-time users for various energy sources and the loss input optimization scheduling model and the energy abandoning model for maintaining the distributed energy storage devices, the distributed energy generation devices and the energy conversion devices are solved to obtain the electric energy conversion quantity which can take the maximum profit target and the minimum energy abandoning loss target into consideration, the electric energy conversion quantity is the charging quantity or the discharging quantity of the distributed energy storage devices, further coordinating the energy demand between the zones with the charge or discharge of the distributed energy storage devices, or the charging amount or the discharging amount of the distributed energy storage device supplements the energy gap of the distributed energy generation device caused by random fluctuation and intermittence.
Fig. 1 is a flowchart illustrating steps of a method for controlling operation of an integrated energy system with hybrid energy storage according to an embodiment of the present application, where the method includes:
step S11: adding the distributed energy storage device into the electric-heating-gas comprehensive energy system according to the consumption demand of renewable energy to obtain a preset comprehensive energy system containing mixed energy storage; wherein, the electric-thermal gas integrated energy system comprises a distributed energy generation device.
The embodiment of the application adds the distributed energy storage device into the electric heating and gas heating integrated energy system, overcomes the defect that single energy storage is difficult to simultaneously satisfy two aspects of power and energy, and because the distributed energy storage device comprises various energy storage equipment, the preset integrated energy system containing mixed energy storage comprises mixed energy storage, and the mixed energy storage is fully complementary from different time scales, so that the unification of system economy, high efficiency and stability is realized.
Fig. 2 is a schematic structural diagram of an integrated energy system with preset hybrid energy storage in an embodiment of the application, and as shown in fig. 2, the distributed energy generation device includes a wind power device and a photovoltaic power generation device; the sub-step of step S11 includes:
step S11-1: and adding the gas-electricity conversion device into an electric heating-gas comprehensive energy system according to the electric power consumption required by the wind power device and the photovoltaic power generation device.
Because wind energy and light energy are influenced by natural factors, the Power randomness of the wind Power device and the photovoltaic Power generation device is large, and the Power balance and the Power quality are difficult to maintain.
Step S11-2: according to the energy conversion characteristics of the new energy automobile and the consumption demand of renewable energy, the new energy automobile is added into an electric heating gas comprehensive energy system.
The energy conversion characteristic of a new energy automobile (EVS) means that the position of the new energy automobile can be changed, and along with the wide application of the new energy automobile, a plurality of new energy automobiles positioned at specific positions can form a power supply network or a network for storing surplus electric quantity, so that a large-scale convergence effect is achieved; the energy difference values of the specific positions of the new energy automobiles can be balanced by the new energy automobiles forming the local network.
The new energy automobile is connected with an external power grid.
Step S11-3: and adding the hydrogen storage device into an electric heating gas comprehensive energy system according to the characteristic that the hydrogen storage device is converted with various energy sources and the long-term energy storage requirement.
The characteristic that the hydrogen storage device can convert with various energy sources is as follows: the hydrogen storage device is connected with an electrolytic cell, and the electrolytic cell is connected with an external power grid; the hydrogen storage device is simultaneously connected with a fuel cell, and the fuel cell is connected with an external power grid. The electrolytic cell can convert the electric energy into hydrogen to be stored in the hydrogen storage device, and the fuel cell can convert the hydrogen into the electric energy to be input into an external power grid. Hydrogen can be stably present in a hydrogen storage device for a long period of time, which is a long-term energy storage device.
Step S11-4: and adding a storage battery and a heat storage tank into the preset comprehensive energy system containing mixed energy storage according to the real-time energy storage requirement.
The storage battery is short-term energy storage equipment, and the lithium storage battery has high charging and discharging efficiency and high power and is mainly used for maintaining real-time supply and demand balance. The heat storage device is connected with an external heat supply network, and plays a good role in peak clipping and valley filling in the system operation process. The heat storage device may be a heat storage tank.
In the embodiment of the application, the distributed conversion and storage of the electric energy are realized by adopting a mode that an external power grid is connected with a hydrogen storage device energy, P2G and other various energy sources, and the utilization of renewable energy sources is promoted by improving regulation and control means and other modes; the renewable energy power generation is matched with the hydrogen storage device to form a power supply which can be scheduled, predicted and controlled; meanwhile, the new energy automobile is utilized to realize the conversion of the power supply and utilization relation of a terminal user, the energy buffering of energy utilization equipment, flexible interaction and intelligent interaction.
In another embodiment of the present application, an energy conversion device may be added to the electric-heat-gas comprehensive energy system to realize interconversion of various energy sources (electric energy, gas energy, and heat energy). And adding an energy conversion device into the electric-heating-gas comprehensive energy system according to the energy conversion requirements between any two of the external power grid, the external gas grid and the external heat supply network to obtain the preset comprehensive energy system with the energy conversion device and mixed energy storage.
The energy conversion device comprises the electrolytic cell and the fuel cell, and further comprises a gas boiler, a gas turbine, a waste heat recovery device and an electric boiler. The specific process of adding the energy conversion device to the hot gas integrated energy system comprises the following steps:
and adding an electric boiler into the preset comprehensive energy system containing the mixed energy storage according to the energy demand difference between the external power grid and the external heat grid so as to adjust, optimize and control the combined heat and power demand of different areas.
And adding a gas boiler, a gas turbine and a waste heat recovery device into the preset comprehensive energy system containing hybrid energy storage according to the energy demand difference between the external power grid and the external air grid and the energy demand difference between the external heat supply grid and the external air grid so as to adjust and optimally control the energy co-supply requirements of different areas.
The embodiment of the application utilizes gas boiler, gas turbine, waste heat recovery device, electric boiler, has realized the energy conversion of outside electric wire netting and outside heat supply network, the energy conversion of outside electric wire netting and outside gas network to and the energy conversion of outside heat supply network and outside gas network, provide the basis for mixing the abundant complementation of energy storage from different time scales.
Step S12: constructing an optimized dispatching model of the preset hybrid energy storage-containing comprehensive energy system according to the first operating parameter and the second operating parameter; wherein the first operating parameter is the stored energy power of the distributed energy storage device and the second operating parameter is the power of the distributed energy generation device.
According to another embodiment of the application, before an optimized scheduling model of a preset hybrid energy storage-containing comprehensive energy system is built according to a first operation parameter and a second operation parameter, the discharging efficiency, the heat release efficiency or the gas energy consumption of an energy conversion device can be obtained and used as a third operation parameter, and finally, the optimized scheduling model is built according to the first operation parameter, the second operation parameter and the third operation parameter. The third operating parameter is a discharge efficiency, a heat release efficiency, or a gas energy consumption amount of the energy conversion device.
In one embodiment of the present application, the first operating parameter includes: the charging power of the new energy automobile, the discharging power of the new energy automobile, the power of the gas-electricity conversion device for absorbing wind power generation, the power of the gas-electricity conversion device for absorbing photovoltaic power generation, the charging efficiency of the hydrogen storage device, the discharging efficiency of the hydrogen storage device, the charging efficiency of the storage battery, the discharging efficiency of the storage battery, the heat release efficiency of the heat storage device and the heat storage efficiency of the heat storage device.
The second operating parameter includes: wind power discharge power, photovoltaic power generation power, interruptible load power.
The third operating parameter includes: gas turbines consume an amount of natural gas.
Besides the first operating parameter, the second operating parameter and the third operating parameter, constructing the optimal scheduling model also requires collecting the electric energy consumption in the external power grid, which may also be the trading volume of the electric power market, calculating the electric quantity required by the power network in a specific area in real time according to the electric quantity required by a user in real time, the power of the electric energy generated by the distributed energy generation device and the real-time electric energy generated by the distributed energy generation device, calculating target parameters capable of simultaneously considering the target of maximum profit and minimum energy loss according to the energy storage power of various hybrid energy storage devices contained in the distributed energy storage device, wherein the target parameters respectively correspond to the real-time energy storage values of the various hybrid energy storage devices, therefore, the purposes of optimizing the open interconnection of various energy sources, flexibly interconnecting different energy source networks by taking electricity as a center, adjusting and jointly regulating are achieved.
The other embodiment of the application specifically illustrates the working principle of the constructed optimized scheduling model. Before an optimized scheduling model is constructed, a parameter model of each energy storage device in the distributed energy storage device is constructed respectively in the embodiment of the application, and a first energy model of the distributed energy storage device is obtained.
Before a first energy model is constructed, acquiring the electric quantity demand of the current time; the electric quantity demand at the current time refers to the electric quantity consumed by a user at a specific time by a preset comprehensive energy system containing hybrid energy storage. The electric quantity demand at the current time may be the electric energy consumption in the external power grid collected in other embodiments of the present application.
Constructing a first energy model of the distributed energy storage device; the first energy model is used for representing the correlation relationship between the first operating parameter and the electric energy conversion amount generated by the distributed energy storage device;
an example of a process for constructing a first energy model of a distributed energy storage device of the present application is as follows:
1. and constructing a new energy automobile charging and discharging and energy storage parameter model. For modeling feasibility, assuming that the schedulable new energy automobile in each region is connected with a power grid through an integrated controller, the integrated controller completes optimized scheduling for equivalently one new energy automobile, and the model is shown as the following formulas (1) and (2):
Figure BDA0003127611860000101
Figure BDA0003127611860000102
wherein the content of the first and second substances,
Figure BDA0003127611860000103
represents the charging power of the new energy automobile in the period t,
Figure BDA0003127611860000104
representing the discharge power of the new energy automobile in the t period;
Figure BDA0003127611860000105
and
Figure BDA0003127611860000106
the value of (b) is in the range of 0-1, and under the condition of charging of the new energy automobile,
Figure BDA0003127611860000107
equal to 1, and is,
Figure BDA0003127611860000108
equal to 0; under the condition of discharging of the new energy automobile,
Figure BDA0003127611860000109
is equal to 0 and is equal to 0,
Figure BDA00031276118600001010
equal to 1;
Figure BDA00031276118600001011
represents the battery capacity of the new energy automobile in the t +1 time period,
Figure BDA00031276118600001012
represents the charging efficiency of the new energy automobile,
Figure BDA00031276118600001013
and the discharge efficiency of the new energy automobile is shown.
2. Constructing a parameter model of the gas-electric conversion device (P2G), as shown in formula (3):
Figure BDA00031276118600001014
wherein the content of the first and second substances,
Figure BDA00031276118600001015
gas generation power, eta, representing the t periodP2GThe gas production efficiency is shown,
Figure BDA00031276118600001016
representing the consumed power. Sources of electrical energy consumed by the gas-to-electric conversion device include: electric energy generated by photovoltaic power generation and electric energy generated by wind power generation.
3. And constructing a parameter model of the hydrogen storage device. As long-term energy storage equipment, the hydrogen storage system has low charge-discharge efficiency and low peak power, but can store energy for a long time through electrolysis and is mainly used for balancing energy imbalance among seasons. The model of the hydrogen storage device is shown in equation (4):
Figure BDA00031276118600001017
wherein E isHST,t+1Representing the capacity of the hydrogen storage device during the period t +1,
Figure BDA00031276118600001018
representing the real-time electrolysis power of the electrolytic cell,
Figure BDA00031276118600001019
representing the real-time released power of the fuel cell;
Figure BDA00031276118600001020
the efficiency of the electrolysis of the electrolytic cell is shown,
Figure BDA00031276118600001021
indicating the discharge efficiency of the fuel cell.
4. And constructing a parameter model of the storage battery. As short-term energy storage equipment, the lithium storage battery has high charging and discharging efficiency and high power and is mainly used for maintaining real-time supply and demand balance. The model of the storage battery is shown in formula (5):
Figure BDA0003127611860000111
wherein E isBES,t+1Is the real-time capacity of the storage battery,
Figure BDA0003127611860000112
for the charging power of the storage battery,
Figure BDA0003127611860000113
is the discharge power of the storage battery,
Figure BDA0003127611860000114
in order to achieve the charging efficiency of the secondary battery,
Figure BDA0003127611860000115
the discharge efficiency of the battery.
5. Constructing a parameter model of the heat storage device; the heat storage device plays a good role in peak clipping and valley filling in the system operation process. Assuming that the front and back charge states of the energy storage system are kept unchanged in one operation period, and meanwhile, the charge state of the energy storage system meets the constraint shown in the formula (6) in the charging and discharging process:
Figure BDA0003127611860000116
wherein E isTST,t+1Indicating the real-time capacity of the heat storage device,
Figure BDA0003127611860000117
the power of the stored heat is shown,
Figure BDA0003127611860000118
the heat-release power is expressed as,
Figure BDA0003127611860000119
the efficiency of the heat storage is shown,
Figure BDA00031276118600001110
indicating the exothermic efficiency.
According to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps: and determining the electric quantity demand, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Before the optimal scheduling model is constructed, the embodiment of the application constructs parameter models of all power generation equipment in the distributed energy generation device respectively to obtain a second energy model of the distributed energy generation device.
Constructing a second energy model of the distributed energy generation device; and the second energy model is used for representing the correlation between the second operation parameter and the output of the distributed energy generation device.
An example of a process for constructing a second energy model of a distributed energy generation apparatus of the present application is as follows:
1. and constructing a wind turbine generator output parameter model. The output of the wind turbine generator is directly related to the wind speed. At present, a wind turbine generator output model is generally modeled by Weibull distribution, and a wind speed probability density function based on Weibull distribution is shown as a formula (7):
Figure BDA00031276118600001111
wherein v represents the wind speed, fw(v) Is a wind speed probability density function; alpha is the shape parameter of the wind speed, beta is the size parameter of the wind speed, the shape parameter of the wind speed and the size parameter of the wind speed are obtained by statistical analysis of historical data of the wind speed, and the wind speed is calculatedThe method of the shape parameter is shown as the formula (8):
Figure BDA0003127611860000121
the method for calculating the size parameter of the wind speed is shown as the formula (9):
Figure BDA0003127611860000122
wherein, mu represents the expected value of the wind speed historical data, sigma represents the variance of the wind speed historical data, and Gamma is a Gamma function. Based on the wind speed model, the output model of the wind turbine generator is established as shown in the formula (10):
Figure BDA0003127611860000123
wherein, PWThe output of the wind turbine can also be regarded as the power of the wind turbine; v is wind speed, viFor cutting into wind speed, vrRated wind speed, voFor cutting out the wind speed, PWoThe rated power of the wind turbine generator is obtained.
2. And constructing a photovoltaic output parameter model. The power curve of the photovoltaic system follows Beta distribution, namely the power curve of the photovoltaic system follows the condition of the formula (11):
Figure BDA0003127611860000124
and k and c are shape parameters of Beta distribution, theta is radiation intensity, and the mean value and the standard deviation of irradiance are introduced for calculation.
According to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps: and determining the second energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Before the optimal scheduling model is constructed, the embodiment of the application constructs parameter models of all devices in the energy conversion device respectively to obtain a third energy model of the energy conversion device.
Constructing a third energy model of the energy conversion device; wherein the third energy model is used for characterizing the correlation of the third operating parameter and the energy consumption of the energy conversion device.
An example of a process for constructing the third energy model of the distributed energy conversion apparatus of the present application is as follows:
1. and constructing a parameter model of the gas boiler. The gas boiler is a common gas-heat cooperative device, and the parameter model of the gas boiler is shown as the formula (12):
Figure BDA0003127611860000131
wherein the content of the first and second substances,
Figure BDA0003127611860000132
for the heat generating power of the gas boiler during the period t,
Figure BDA0003127611860000133
in order to produce the heat with high efficiency,
Figure BDA0003127611860000134
the gas consumption power of the gas boiler in the time period t is obtained.
2. Constructing a parameter model of the gas turbine, wherein the parameter model of the gas turbine is shown as the formula (13):
Figure BDA0003127611860000135
wherein the content of the first and second substances,
Figure BDA0003127611860000136
for the time period t the gas turbine is electrically powered,
Figure BDA0003127611860000137
the residual heat power of the gas turbine is t time period;
Figure BDA0003127611860000138
for the natural gas consumption of the gas turbine during the period t, etaMTFor gas turbine efficiency, ηlossThe heat dissipation loss rate of the gas turbine.
3. And constructing a parameter model of the waste heat recovery device. The parameter model of the waste heat recovery device is shown as the formula (14):
Figure BDA0003127611860000139
wherein the content of the first and second substances,
Figure BDA00031276118600001310
for t period waste heat recovery device heating power, etahrsThe efficiency of the waste heat recovery device.
4. And constructing a parameter model of the electric boiler. An electric boiler is a common electric-heat conversion device, and a parametric model thereof is shown as formula (15):
Figure BDA00031276118600001311
wherein the content of the first and second substances,
Figure BDA00031276118600001312
is the heat supply of the electric boiler in the time period t, etaEBTo the electricity-to-heat conversion efficiency of the electric boiler,
Figure BDA00031276118600001313
the power consumption of the electric boiler in the time period t.
5. Parametric models of the electrolyzer and the fuel cell were constructed. The parameter model of the electrolytic cell is shown in the formula (16), and the parameter model of the fuel cell is shown in the formula (17):
Figure BDA00031276118600001314
Figure BDA00031276118600001315
wherein the content of the first and second substances,
Figure BDA00031276118600001316
for the electrical power consumed by the electrolytic cell,
Figure BDA00031276118600001317
the amount of hydrogen generated for the electrolytic cell; v. ofECIn order to achieve the conversion efficiency of the electrolytic cell,
Figure BDA00031276118600001318
converting the electric energy into a unit conversion coefficient of hydrogen with the same energy;
Figure BDA00031276118600001319
the amount of hydrogen gas consumed by the fuel cell,
Figure BDA00031276118600001320
electric power output for fuel cell, vFCThe conversion efficiency of the fuel cell.
According to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps: and determining the third energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Inputting a new energy automobile parameter model, a gas-electricity conversion device parameter model, a hydrogen storage device parameter model, a storage battery parameter model, a heat storage device parameter model and a heat storage device parameter model in a distributed energy storage device into an optimization scheduling model; simultaneously inputting a wind turbine generator output parameter model and a photovoltaic output parameter model in the distributed energy generation device into an optimized scheduling model; and then inputting a gas boiler parameter model, a gas turbine parameter model, a waste heat recovery device parameter model and an electric boiler parameter model in the energy conversion device into the optimization scheduling model, wherein the optimization scheduling model can be obtained by the following steps: the method comprises the steps of solving energy storage energy stored by energy storage devices such as a new energy automobile, a gas-electricity conversion device, a hydrogen storage device, a storage battery, a heat storage device and the like under the conditions that the charging power of the new energy automobile, the discharging power of the new energy automobile, the wind-electricity conversion device, the discharging efficiency of the hydrogen storage device, the charging efficiency of the storage battery, the discharging efficiency of the storage battery, the heat release efficiency of the heat storage device, the heat storage efficiency of the heat storage device, the wind discharging power of the wind-electricity conversion device, the photovoltaic power generation power, the interruptible load power and the natural gas consumption amount of a gas turbine are all consumed, and performing energy conversion by using the energy storage energy, wherein surplus electric energy is converted into heat energy or gas energy, surplus gas energy is converted into electric energy or heat energy, and surplus heat energy is converted into electric energy or gas energy, so that the random fluctuation, wind power generation power of distributed energy is achieved, And (4) intermittent supplement.
One example of the present application establishes an optimal scheduling model using a net profit maximum of operation as a goal. The optimization scheduling model is shown as equation (18):
Figure BDA0003127611860000141
f1the objective is solved for the first.
Wherein T is 24 hours in one period. I is the profit of the comprehensive energy system containing the preset mixed energy storage, and C is the cost of the comprehensive energy system containing the preset mixed energy storage. I is calculated as shown in equation (19):
Figure BDA0003127611860000142
c is calculated as shown in equation (20):
C＝Cpv、W,t+CP2G,t+CEV,t+CMT,t+Cmain (20)；
wherein, IL，tFor the load gain of t time period, IM，tRepresenting energy market revenue, IEV，tRepresenting the charging income and the discharging income of the new energy automobile;
Figure BDA0003127611860000151
the benefit of the storage battery is shown,
Figure BDA0003127611860000152
the benefit of the hydrogen storage device is expressed,
Figure BDA0003127611860000153
representing the heat storage device revenue. CpvRepresenting the operation and maintenance cost of the wind turbine generator in the time period of t, CW，tRepresents the operation and maintenance cost of photovoltaic power generation, CP2G，tRepresents the operating conversion cost of P2G, CMT，tRepresenting gas turbine maintenance costs, CmainIndicating the maintenance cost of other equipment than the above.
the calculation method of the load gain in the period t is shown as the formula (21):
Figure BDA0003127611860000154
wherein, PL，tIs the load for the period of t,
Figure BDA0003127611860000155
is the kth level interrupt load power, k is the number of interrupt levels. Lambda [ alpha ]M，tIs the market price of electricity;
Figure BDA0003127611860000156
is the kth interrupt load compensation price.
The gains of the energy market include the electric power market gains and the heat supply network gains as shown in equation (22):
IM，t＝λsu，tPM，tμsu，t-λsd，tPM,tμsd，t+λαQt (22)；
wherein, PM，tIs the t-time period preset comprehensive energy system containing hybrid energy storage and the trading volume, Q, of the electric power markettThe trading volume of the comprehensive energy system containing the hybrid energy storage and the heat supply network market is preset in the t period. When the preset comprehensive energy system containing mixed energy storage is soldsu,tValue of 1, musd,tThe value is 0, when the preset comprehensive energy system containing the mixed energy storage is used for purchasing electricity, the mu value issu,tValue of 0, musd,tThe value is 1. Lambda [ alpha ]su,tPresetting a contract electricity selling price, lambda, of a comprehensive energy system containing hybrid energy storage and an electricity marketsd,tIs to preset the contract electricity purchase price, lambda, of the comprehensive energy system containing the mixed energy storage and the electric power marketαThe trade price of the comprehensive energy system containing the hybrid energy storage and the heat supply network is preset.
The income calculation mode of a single new energy automobile is shown as the formula (23):
IEV,t＝λch，tPEV，tμch，t+λdis，tPEV，tμdis，t-λEVPEV，t (23)；
PEV，twhen the value is positive, the charging quantity P of the new energy automobile in the t period is representedEV，tAnd when the value is negative, the discharge capacity of the new energy automobile in the t period is represented. In the case of charging a new energy vehicle, much，tValue of 1, mudis，tThe value is 0, and mu is measured under the condition of discharging of the new energy automobilech，tValue of 0, mudis，tThe value is 1. Lambda [ alpha ]ch，tIndicates the charging price of the new energy automobile, lambdadis,tRepresents the discharge price, lambda, of the new energy automobileEVAnd representing the charge and discharge compensation coefficient of the new energy automobile.
The battery energy sales yield is expressed by the formula (24):
Figure BDA0003127611860000157
wherein, cE，tShows the charge of the battery,
Figure BDA0003127611860000158
Indicating sales income of hydrogen storage device, cT,tIndicating heat sales revenue, P, of the heat storage deviceFC,tThe sales electricity quantity of the hydrogen storage device is shown,
Figure BDA0003127611860000161
indicating the sales heat of the hydrogen storage device.
The hydrogen storage device yield is shown in the formula (25):
Figure BDA0003127611860000162
wherein the content of the first and second substances,
the heat storage device gains are shown as the formula (26):
Figure BDA0003127611860000163
wherein
The operation and maintenance costs of the wind turbine generator and the photovoltaic power generation are shown as formulas (27) and (28):
CPV＝λ1PPV,t+λ2PW,t (27)；
CW,t＝λ1PPV,t+λ2PW,t(28) (ii) a Wherein, PPV,tIs the photovoltaic power in the i region t period, PW,tThe fan power in the t period of the i area, the lambda 1 is the operation and maintenance cost of the fan electric group, and the lambda 2 is the operation and maintenance cost of the photovoltaic.
The operation conversion cost of the gas-electric conversion device is calculated as shown in the formula (29):
Figure BDA0003127611860000164
wherein λ isP2GIs the operating conversion cost of P2G,
Figure BDA0003127611860000165
is CO2Is monovalent.
The operation and maintenance cost of the gas turbine is calculated as shown in the formula (30):
Figure BDA0003127611860000166
wherein λ isgasFor the price of the natural gas in the period t,
Figure BDA0003127611860000167
in order to account for the start-up costs of the gas turbine,
Figure BDA0003127611860000168
as a shutdown cost of the gas turbine;
Figure BDA0003127611860000169
and
Figure BDA00031276118600001610
is a boolean variable, and during the time period t, when the gas turbine is started,
Figure BDA00031276118600001611
the value is 1, and the value is,
Figure BDA00031276118600001612
the value is 0; when the gas turbine is stopped for a period of t,
Figure BDA00031276118600001613
the value of the oxygen is 0, and the oxygen concentration is less than or equal to zero,
Figure BDA00031276118600001614
the value is 1.
The maintenance cost of the remaining devices is calculated in the manner shown in equation (31):
Figure BDA00031276118600001615
(31) (ii) a Wherein the content of the first and second substances,
Figure BDA00031276118600001616
represents the equipment maintenance cost of the electrolytic cell in the scheduling period,
Figure BDA00031276118600001617
represents the equipment maintenance cost of the fuel cell during the scheduling period,
Figure BDA00031276118600001618
represents the equipment maintenance cost of the hydrogen storage device in the scheduling period,
Figure BDA00031276118600001619
represents the equipment maintenance cost of the heat storage facility during the scheduling period,
Figure BDA00031276118600001620
representing the equipment maintenance cost of the battery during the scheduling period.
Step S13: and constructing an energy abandonment model of the distributed energy generation device.
An example of the method for constructing the energy curtailment model is shown as a formula (32), and the wind curtailment rate is minimized to be a ratio of the light curtailment amount of the wind curtailment of the virtual power plant to the actual available new energy amount:
Figure BDA0003127611860000171
f2the objective is solved for a second time.
Wherein the content of the first and second substances,
Figure BDA0003127611860000172
in order to discard the air volume,
Figure BDA0003127611860000173
in order to reject the amount of light,
Figure BDA0003127611860000174
in order to actually use the total amount of the available wind power,
Figure BDA0003127611860000175
for practical use of the photovoltaicTotal amount of the components.
Step S14: and calculating the electric energy conversion amount of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target so as to balance the energy difference amount of the preset hybrid energy storage-containing comprehensive energy system by using the electric energy conversion amount.
The specific method for solving the optimal scheduling model and the energy abandoning model according to the first solving objective and the second solving objective by using the fuzzy membership function to obtain the electric energy conversion quantity of the distributed energy storage device comprises the following steps:
in order to consider the dual-objective problem of the maximum net gain and the minimum energy loss of the system, a final scheduling scheme is screened out from the Pareto solution set through a fuzzy membership function, and the dual-objective problem of the maximum net gain and the minimum energy loss can be calculated according to methods shown in formulas (33) and (34):
Figure BDA0003127611860000176
Figure BDA0003127611860000177
wherein xmIs the value of the objective function, mum,iFor m non-inferior solutions xmSatisfaction with the ith target; f. ofi(xm) Is a non-inferior solution xmThe (i) th target value of (a),
Figure BDA0003127611860000178
is the maximum value of the i-th target,
Figure BDA0003127611860000179
is the minimum value of the ith target, μmIs a non-inferior solution xmFor the comprehensive satisfaction of all targets, M is the number of non-inferior solutions; l is the target number, which in this application is 2.
The solving process of the hybrid energy storage-containing comprehensive energy virtual power plant multi-target optimization model adopted by the method is as follows:
(1) and setting the population scale, the iteration times, and the like if the initial iteration time k is 1. The population in this application is the objective function referred to herein.
(2) And initializing the population.
(3) And calculating an individual objective function value optimization scheduling model and an energy abandoning model, and sequencing by using a Pareto priority sequencing method.
(4) And calculating two target function fitness values of the two particles, and further updating the individual optimal value.
(5) Assuming k is a multiple of 10, the selection, crossover and mutation operations are performed, the individual optima are reinitialized, and the velocity and position of the particles are updated.
(6) And (4) judging whether the iteration is finished, if the iteration reaches the set maximum iteration number, turning to the step (7), and if not, turning to the step (3) to carry out the next iteration.
(7) And (3) weighing and screening a final scheduling scheme from a Pareto solution set by introducing a fuzzy membership function, if T is T +1, if T is less than or equal to 1, and if T is less than T, turning to (2) until a solution giving consideration to minimum energy loss and maximum income is obtained.
In another embodiment of the present application, a balance constraint condition is further set, so that a preset hybrid energy storage-containing comprehensive energy system can obtain the electric energy conversion amount of each device in the distributed energy storage device under the condition of considering energy balance, thereby realizing random fluctuation and intermittent supplement of the distributed energy.
Acquiring the electric quantity demand of the current time; constructing an electric energy balance constraint condition according to the electric quantity demand and the real-time electric quantity generated by the distributed energy generation device; and constructing a second electric energy balance constraint condition according to the abandoned wind loss of the wind power device and the abandoned light loss of the photovoltaic power generation device.
A (35) type constraint electric quantity and generated energy are adopted by a preset comprehensive energy system containing hybrid energy storage to keep instantaneous balance.
Figure BDA0003127611860000181
Wherein the content of the first and second substances,
Figure BDA0003127611860000182
represents photovoltaic power;
Figure BDA0003127611860000183
representing the fan power;
Figure BDA0003127611860000184
the power of the gas turbine is shown,
Figure BDA0003127611860000185
representing the electrical power output by the hydrogen storage device;
Figure BDA0003127611860000186
representing the fan power;
Figure BDA0003127611860000187
the power of the gas turbine is shown,
Figure BDA0003127611860000188
representing the electrical power output of the hydrogen storage means, PM,tRepresenting the amount of power obtained from an external power grid; pEV,tRepresenting the charge quantity or the discharge quantity of the new energy automobile;
Figure BDA0003127611860000189
representing the energy released by the cell; pL,tRepresenting an electrical load;
Figure BDA00031276118600001810
representing the interrupt load power;
Figure BDA00031276118600001811
indicating the amount of battery discharge.
Wherein the content of the first and second substances,
Figure BDA00031276118600001812
wherein the content of the first and second substances,
Figure BDA00031276118600001813
represents photovoltaic power;
Figure BDA00031276118600001814
indicating the light rejection amount;
Figure BDA00031276118600001815
representing the total photovoltaic output.
Figure BDA0003127611860000191
In the formula
Figure BDA0003127611860000192
Representing the fan power;
Figure BDA0003127611860000193
representing the air abandoning amount;
Figure BDA0003127611860000194
indicating the total fan output.
Calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps: and under the first electric energy balance constraint condition and the second electric energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
Acquiring the heat demand, the heat energy supply quantity, the gas energy demand and the gas energy supply quantity at the current time;
constructing a heat energy balance constraint condition according to the heat demand and the heat energy supply quantity;
the preset comprehensive energy system containing mixed energy storage adopts a formula (38) to ensure that the heat energy usage and the heat energy output keep instantaneous balance.
Figure BDA0003127611860000195
Wherein the content of the first and second substances,
Figure BDA0003127611860000196
representing the heat supply amount of the electric boiler;
Figure BDA0003127611860000197
representing the heat supply amount of the gas boiler;
Figure BDA0003127611860000198
representing the heat supply of the gas turbine;
Figure BDA0003127611860000199
indicating the heat release of the heat storage device; qtRepresenting the amount of heat obtained from an external heat net;
Figure BDA00031276118600001910
represents the amount of stored heat; l ish，tRepresenting the amount of heat actually used.
Constructing a gas energy balance constraint condition according to the gas energy demand and the gas energy supply quantity;
except for an external gas market, only P2G energy conversion equipment is arranged in the preset comprehensive energy system containing mixed energy storage for supplying gas energy, so that the preset comprehensive energy system containing mixed energy storage adopts (39) type heat energy-saving energy to keep instantaneous balance.
Figure BDA00031276118600001911
Wherein the content of the first and second substances,
Figure BDA00031276118600001912
represents P2G gas production power; qgasRepresenting the amount of natural gas obtained from an external gas grid;
Figure BDA00031276118600001913
power representing natural gas consumed by the gas boiler;
Figure BDA00031276118600001914
representing the amount of natural gas consumed by the gas boiler; l isg,tAnd the gas load required by the comprehensive energy system containing the mixed stored energy is preset.
The embodiment of the present application also performs interrupt load restraint by using equations (40) and (41).
Figure BDA00031276118600001915
Figure BDA00031276118600001916
Figure BDA00031276118600001917
Is the k-th level interruptible load maximum power for the t period.
Other devices, such as wind turbine generator constraint, and constraint conditions relating to wind turbines, photovoltaic turbines and electric vehicles, may adopt constraint conditions of related technologies, and are not described in detail in the embodiments of the present application.
Calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps: and under the heat energy balance constraint condition and the gas energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
Based on the same invention concept, the embodiment of the application provides a comprehensive energy system operation control device with hybrid energy storage. Referring to fig. 3, fig. 3 is a functional block diagram of an integrated energy system operation control device with hybrid energy storage according to an embodiment of the present application. The device includes:
the first adding module 31 is used for adding the distributed energy storage device into the electric-heating-gas comprehensive energy system according to the consumption demand of the renewable energy to obtain a preset comprehensive energy system containing mixed energy storage; the electric-thermal gas integrated energy system comprises a distributed energy generation device;
the first construction module 32 is configured to construct an optimized scheduling model of the preset hybrid energy storage-containing integrated energy system according to the first operating parameter and the second operating parameter; wherein the first operating parameter is stored energy power of the distributed energy storage device and the second operating parameter is power of the distributed energy generation device;
a second construction module 33, configured to construct an energy curtailment model of the distributed energy generation apparatus;
the calculation module 34 is configured to use the maximum profit as a first solving objective of the optimized scheduling model, use the minimum energy loss as a second solving objective of the energy curtailment model, and calculate the electric energy conversion amount of the distributed energy storage device according to the first solving objective and the second solving objective by using a fuzzy membership function, so as to balance the energy difference amount of the preset hybrid energy storage-containing integrated energy system by using the electric energy conversion amount.
Optionally, the distributed energy generation device comprises a wind power device and a photovoltaic power generation device; the first joining module comprises:
the first adding submodule is used for adding the gas-electricity conversion device into the electric heating-gas comprehensive energy system according to the electric power consumption required by the wind power device and the photovoltaic power generation device;
the second adding submodule is used for adding the new energy automobile into an electric heating and gas comprehensive energy system according to the energy conversion characteristics of the new energy automobile;
the third adding submodule is used for adding the hydrogen storage device into an electric heating gas comprehensive energy system according to the characteristic that the hydrogen storage device has conversion with various energy sources and the long-term energy storage requirement;
and the fourth adding submodule is used for adding a storage battery and a heat storage tank into the preset comprehensive energy system containing mixed energy storage according to the real-time energy storage requirement.
Optionally, the preset hybrid energy storage-containing comprehensive energy system is respectively connected to an external power grid and an external heat supply network, and the device further includes:
and the second adding module is used for adding the electric boiler into the preset comprehensive energy system containing the mixed energy storage according to the energy demand difference between the external power grid and the external heat grid so as to adjust, optimize and control the combined heat and power demands of different areas.
Optionally, the preset comprehensive energy system containing hybrid energy storage is connected with an external air network; the device further comprises:
and the third adding module is used for adding a gas boiler, a gas turbine and a waste heat recovery device into the preset comprehensive energy system containing the mixed energy storage according to the energy demand difference between the external power grid and the external air grid and the energy demand difference between the external heat grid and the external air grid so as to adjust and optimize the energy co-generation requirements of different areas.
Optionally, the apparatus further comprises:
the first acquisition module is used for acquiring the electric quantity demand of the current time;
the third construction module is used for constructing a first energy model of the distributed energy storage device; the first energy model is used for representing the correlation relationship between the first operating parameter and the electric energy conversion amount generated by the distributed energy storage device;
the first building block comprises:
the first construction submodule is used for determining the electric quantity demand, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Optionally, the apparatus further comprises:
the first acquisition module is used for acquiring the electric quantity demand of the current time;
the fourth construction module is used for constructing an electric energy balance constraint condition according to the electric quantity demand and the real-time electric quantity generated by the distributed energy generation device;
the fifth construction module is used for constructing a second electric energy balance constraint condition according to the abandoned wind loss of the wind power device and the abandoned light loss of the photovoltaic power generation device;
the first building block comprises:
and the second construction submodule is used for calculating the electric energy conversion quantity of the distributed energy generation device by utilizing a fuzzy membership function according to the first solving target and the second solving target under the first electric energy balance constraint condition and the second electric energy balance constraint condition.
The device further comprises:
the third acquisition module is used for acquiring the heat demand, the heat energy supply quantity, the gas energy demand and the gas energy supply quantity at the current time;
a fifth construction module, configured to construct a thermal energy balance constraint condition according to the thermal demand and the thermal energy supply amount;
the sixth construction module is used for constructing a gas energy balance constraint condition according to the gas energy demand and the gas energy supply quantity;
the calculation module comprises:
and the first calculation submodule is used for calculating the electric energy conversion quantity of the distributed energy generation device by utilizing a fuzzy membership function according to the first solving target and the second solving target under the heat energy balance constraint condition and the gas energy balance constraint condition.
Optionally, the apparatus further comprises: the seventh construction module is used for constructing a second energy model of the distributed energy generation device; the second energy model is used for representing the correlation between the second operation parameter and the output of the distributed energy generation device;
the first building block comprises:
and the third construction submodule is used for determining the second energy model, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Optionally, the preset hybrid energy storage-containing comprehensive energy system comprises an energy conversion device; the device further comprises:
the fourth adding module is used for adding an energy conversion device into the electric-heating-gas comprehensive energy system according to the energy conversion requirements between any two of the external power grid, the external gas grid and the external heat grid to obtain a preset comprehensive energy system with energy conversion devices and mixed energy storage;
the first building block comprises:
the fourth construction submodule is used for constructing the optimized scheduling model according to the first operation parameter, the second operation parameter and the third operation parameter; wherein the third operating parameter is a discharge efficiency, a heat release efficiency, or a gas energy consumption of the energy conversion device.
The device further comprises:
an eighth construction module, configured to construct a third energy model of the energy conversion apparatus; wherein the third energy model is used for characterizing the correlation of the third operating parameter and the energy consumption of the energy conversion device;
the first building block comprises:
and the fifth construction submodule is used for determining the third energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
Based on the same inventive concept, another embodiment of the present application provides a readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the hybrid energy storage-based operation control method according to any of the above embodiments of the present application.
Based on the same inventive concept, another embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method for controlling the operation of the hybrid energy storage-containing integrated energy system according to any of the above embodiments of the present application is implemented.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are described in a progressive or descriptive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The operation control method of the hybrid energy storage-containing comprehensive energy system provided by the application is introduced in detail, and the description of the embodiment is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. An operation control method of an integrated energy system containing hybrid energy storage is characterized by comprising the following steps:
adding the distributed energy storage device into the electric-heating-gas comprehensive energy system according to the consumption demand of renewable energy to obtain a preset comprehensive energy system containing mixed energy storage; the electric-thermal gas integrated energy system comprises a distributed energy generation device;
constructing an optimized dispatching model of the preset hybrid energy storage-containing comprehensive energy system according to the first operating parameter and the second operating parameter; wherein the first operating parameter is stored energy power of the distributed energy storage device and the second operating parameter is power of the distributed energy generation device;
constructing an energy abandoning model of the distributed energy generation device;
and calculating the electric energy conversion amount of the distributed energy storage device by using a fuzzy membership function according to the first solving target and the second solving target so as to balance the energy difference amount of the preset comprehensive energy system containing mixed energy storage by using the electric energy conversion amount.
2. The method of claim 1, wherein the distributed energy generation facility comprises a wind power plant and a photovoltaic power plant; according to renewable energy's consumption demand, add electric heat gas comprehensive energy system with distributed energy storage device, obtain predetermineeing the comprehensive energy system who contains mixed energy storage, include:
adding a gas-electricity conversion device into an electric heating-gas comprehensive energy system according to the electric power consumption required by the wind power device and the photovoltaic power generation device;
adding the new energy automobile into an electric heating and gas comprehensive energy system according to the energy conversion characteristics of the new energy automobile;
adding the hydrogen storage device into an electric heating gas comprehensive energy system according to the characteristic that the hydrogen storage device is converted with various energy sources and the long-term energy storage requirement;
and adding a storage battery and a heat storage tank into the preset comprehensive energy system containing mixed energy storage according to the real-time energy storage requirement.
3. The method according to claim 1, wherein the preset hybrid energy storage-containing integrated energy system is respectively connected with an external power grid and an external heat supply network; the method further comprises the following steps:
and adding an electric boiler into the preset comprehensive energy system containing the mixed energy storage according to the energy demand difference between the external power grid and the external heat grid so as to adjust, optimize and control the combined heat and power demand of different areas.
4. The method of claim 3, wherein the predetermined hybrid energy storage-containing integrated energy system is connected to an external gas grid; the method further comprises the following steps:
and adding a gas boiler, a gas turbine and a waste heat recovery device into the preset comprehensive energy system containing hybrid energy storage according to the energy demand difference between the external power grid and the external air grid and the energy demand difference between the external heat supply grid and the external air grid so as to adjust and optimally control the energy co-supply requirements of different areas.
5. The method of claim 1, further comprising:
acquiring the electric quantity demand of the current time;
constructing a first energy model of the distributed energy storage device; the first energy model is used for representing the correlation relationship between the first operating parameter and the electric energy conversion amount generated by the distributed energy storage device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the electric quantity demand, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
6. The method of claim 2, further comprising:
acquiring the electric quantity demand of the current time;
constructing an electric energy balance constraint condition according to the electric quantity demand and the real-time electric quantity generated by the distributed energy generation device;
constructing a second electric energy balance constraint condition according to the abandoned wind loss of the wind power device and the abandoned light loss of the photovoltaic power generation device;
calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps:
and under the first electric energy balance constraint condition and the second electric energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
7. The method of claim 1, further comprising:
acquiring the heat demand, the heat energy supply quantity, the gas energy demand and the gas energy supply quantity at the current time;
constructing a heat energy balance constraint condition according to the heat demand and the heat energy supply quantity;
constructing a gas energy balance constraint condition according to the gas energy demand and the gas energy supply quantity;
calculating the electric energy conversion quantity of the distributed energy generation device according to the first solving target and the second solving target by using a fuzzy membership function, wherein the calculation comprises the following steps:
and under the heat energy balance constraint condition and the gas energy balance constraint condition, calculating the electric energy conversion quantity of the distributed energy generation device by using a fuzzy membership function according to the first solving target and the second solving target.
8. The method of claim 5, further comprising:
constructing a second energy model of the distributed energy generation device; the second energy model is used for representing the correlation between the second operation parameter and the output of the distributed energy generation device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the second energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
9. The method of claim 4, wherein the predetermined hybrid energy storage-containing integrated energy system comprises an energy conversion device; the method further comprises the following steps:
adding an energy conversion device into the electric-heating-gas comprehensive energy system according to the energy conversion requirement between any two of the external power grid, the external gas grid and the external heat supply network to obtain a preset comprehensive energy system with energy conversion device and hybrid energy storage;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
constructing the optimized scheduling model according to the first operating parameter, the second operating parameter and the third operating parameter; wherein the third operating parameter is a discharge efficiency, a heat release efficiency, or a gas energy consumption of the energy conversion device.
10. The method of claim 5, further comprising:
constructing a third energy model of the energy conversion device; wherein the third energy model is used for characterizing the correlation of the third operating parameter and the energy consumption of the energy conversion device;
according to the first operating parameter and the second operating parameter, an optimal scheduling model of the preset hybrid energy storage-containing comprehensive energy system is constructed, and the optimal scheduling model comprises the following steps:
and determining the third energy model, the first operating parameter and the second operating parameter as input variables of the optimized scheduling model, determining the electric energy conversion quantity as output variables of the optimized scheduling model, and constructing the optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system.
CN202110694608.9A 2021-06-22 2021-06-22 Operation control method of comprehensive energy system containing hybrid energy storage Active CN113437752B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110694608.9A CN113437752B (en) 2021-06-22 2021-06-22 Operation control method of comprehensive energy system containing hybrid energy storage

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110694608.9A CN113437752B (en) 2021-06-22 2021-06-22 Operation control method of comprehensive energy system containing hybrid energy storage

Publications (2)

Publication Number Publication Date
CN113437752A true CN113437752A (en) 2021-09-24
CN113437752B CN113437752B (en) 2023-04-25

Family

ID=77757232

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110694608.9A Active CN113437752B (en) 2021-06-22 2021-06-22 Operation control method of comprehensive energy system containing hybrid energy storage

Country Status (1)

Country Link
CN (1) CN113437752B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113887946A (en) * 2021-09-30 2022-01-04 煤炭科学研究总院 Emergency material transportation scheduling method and device for hydrogen energy driven non-stop transmission and storage medium
CN114396644A (en) * 2021-12-10 2022-04-26 中国华能集团清洁能源技术研究院有限公司 Multistage heating system based on hydrogen energy
CN116643526A (en) * 2023-06-12 2023-08-25 上海启斯云计算有限公司 Power supply energy-saving control method and system
CN116681270A (en) * 2023-08-04 2023-09-01 山东理工大学 Optimal scheduling method of virtual power plant under flexible carbon emission mechanism
CN116643526B (en) * 2023-06-12 2024-04-23 上海启斯云计算有限公司 Power supply energy-saving control method and system

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109146117A (en) * 2018-06-15 2019-01-04 中国电建集团福建省电力勘测设计院有限公司 A kind of region multi-energy system running optimizatin method considering Demand-side resource
CN110417015A (en) * 2019-06-18 2019-11-05 湖北追日电气股份有限公司 Micro-capacitance sensor Multiobjective Optimal Operation method and system based on Model Predictive Control
CN110807560A (en) * 2019-11-12 2020-02-18 国网重庆市电力公司电力科学研究院 Method and device for scheduling hydrogen-mixed natural gas energy system and readable storage medium
CN111144668A (en) * 2020-01-19 2020-05-12 河海大学 Method for establishing comprehensive energy system random optimization model considering scene simulation
CN111242806A (en) * 2020-02-19 2020-06-05 武汉理工大学 Planning method of electric-thermal-hydrogen multi-energy system considering uncertainty
CN111340274A (en) * 2020-02-17 2020-06-26 国网冀北电力有限公司 Virtual power plant participation-based comprehensive energy system optimization method and system
CN111355230A (en) * 2018-12-24 2020-06-30 中国电力科学研究院有限公司 Optimized scheduling method and system for comprehensive energy system
CN112365034A (en) * 2020-10-27 2021-02-12 燕山大学 Electric heating comprehensive energy system scheduling method and system
CN112465200A (en) * 2020-11-18 2021-03-09 国网江苏省电力有限公司盐城供电分公司 Energy optimization scheduling method for virtual power plant

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109146117A (en) * 2018-06-15 2019-01-04 中国电建集团福建省电力勘测设计院有限公司 A kind of region multi-energy system running optimizatin method considering Demand-side resource
CN111355230A (en) * 2018-12-24 2020-06-30 中国电力科学研究院有限公司 Optimized scheduling method and system for comprehensive energy system
CN110417015A (en) * 2019-06-18 2019-11-05 湖北追日电气股份有限公司 Micro-capacitance sensor Multiobjective Optimal Operation method and system based on Model Predictive Control
CN110807560A (en) * 2019-11-12 2020-02-18 国网重庆市电力公司电力科学研究院 Method and device for scheduling hydrogen-mixed natural gas energy system and readable storage medium
CN111144668A (en) * 2020-01-19 2020-05-12 河海大学 Method for establishing comprehensive energy system random optimization model considering scene simulation
CN111340274A (en) * 2020-02-17 2020-06-26 国网冀北电力有限公司 Virtual power plant participation-based comprehensive energy system optimization method and system
CN111242806A (en) * 2020-02-19 2020-06-05 武汉理工大学 Planning method of electric-thermal-hydrogen multi-energy system considering uncertainty
CN112365034A (en) * 2020-10-27 2021-02-12 燕山大学 Electric heating comprehensive energy system scheduling method and system
CN112465200A (en) * 2020-11-18 2021-03-09 国网江苏省电力有限公司盐城供电分公司 Energy optimization scheduling method for virtual power plant

Non-Patent Citations (10)

* Cited by examiner, † Cited by third party
Title
刘小敏等: "电力市场环境下计及V2G和多类型需求响应的综合能源系统多目标优化模型", 《数学的实践与认识》 *
刘小敏等: "电力市场环境下计及V2G和多类型需求响应的综合能源系统多目标优化模型", 《数学的实践与认识》, vol. 51, no. 3, 28 February 2021 (2021-02-28), pages 98 - 109 *
刘敦楠等: "考虑多类型能源转换与存储的综合能源微网优化运行研究", 《南方电网技术》 *
刘敦楠等: "考虑多类型能源转换与存储的综合能源微网优化运行研究", 《南方电网技术》, no. 03, 20 March 2018 (2018-03-20), pages 111 - 121 *
吴静等: "计及P2G 与CCHP 技术的综合能源系统多目标协同优化模型", 《电测与仪表》 *
吴静等: "计及P2G 与CCHP 技术的综合能源系统多目标协同优化模型", 《电测与仪表》, vol. 58, no. 5, 15 May 2021 (2021-05-15), pages 20 - 30 *
张军六等: "计及需求响应的气电互联虚拟电厂多目标调度优化模型", 《电力建设》 *
张军六等: "计及需求响应的气电互联虚拟电厂多目标调度优化模型", 《电力建设》, no. 02, 1 February 2020 (2020-02-01), pages 5 - 14 *
裘昕月等: "考虑风电出力不确定性的综合能源系统鲁棒优化", 《智慧电力》 *
裘昕月等: "考虑风电出力不确定性的综合能源系统鲁棒优化", 《智慧电力》, no. 05, 20 May 2020 (2020-05-20), pages 7 - 12 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113887946A (en) * 2021-09-30 2022-01-04 煤炭科学研究总院 Emergency material transportation scheduling method and device for hydrogen energy driven non-stop transmission and storage medium
CN113887946B (en) * 2021-09-30 2022-07-26 煤炭科学研究总院有限公司 Emergency material transportation scheduling method and device driven by hydrogen energy and transmitted without stopping
CN114396644A (en) * 2021-12-10 2022-04-26 中国华能集团清洁能源技术研究院有限公司 Multistage heating system based on hydrogen energy
CN116643526A (en) * 2023-06-12 2023-08-25 上海启斯云计算有限公司 Power supply energy-saving control method and system
CN116643526B (en) * 2023-06-12 2024-04-23 上海启斯云计算有限公司 Power supply energy-saving control method and system
CN116681270A (en) * 2023-08-04 2023-09-01 山东理工大学 Optimal scheduling method of virtual power plant under flexible carbon emission mechanism

Also Published As

Publication number Publication date
CN113437752B (en) 2023-04-25

Similar Documents

Publication Publication Date Title
Roslan et al. Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction
CN105591406B (en) A kind of optimized algorithm of the microgrid energy management system based on non-cooperative game
CN113437752B (en) Operation control method of comprehensive energy system containing hybrid energy storage
CN106410861B (en) A kind of micro-capacitance sensor optimization operation real-time control method based on schedulable ability
Hannan et al. Binary particle swarm optimization for scheduling MG integrated virtual power plant toward energy saving
CN112583017A (en) Hybrid micro-grid energy distribution method and system considering energy storage operation constraint
CN112800658A (en) Active power distribution network scheduling method considering source storage load interaction
CN115173453A (en) Energy storage auxiliary power grid peak regulation optimal configuration method
CN112508325A (en) Multi-time-scale electric energy scheduling method for household micro-grid
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
CN116384039A (en) Intelligent power grid energy optimization efficient management method based on model prediction
CN115293457A (en) Seasonal hydrogen storage optimization configuration method of comprehensive energy system based on distributed collaborative optimization strategy
Mao et al. Microgrid group control method based on deep learning under cloud edge collaboration
CN112510690B (en) Optimal scheduling method and system considering wind-fire-storage combination and demand response reward and punishment
Liu et al. Day-ahead economic dispatch of renewable energy system considering wind and photovoltaic predicted output
CN117081041A (en) Harbor district multi-energy fusion coordination optimization control method and system
CN115693793A (en) Energy optimization control method for regional micro-grid
CN116742812A (en) Energy storage capacity coordination optimization configuration method and system for multi-energy complementary power generation system
CN111899125B (en) Optimized modeling operation method, device and medium of comprehensive energy system
CN115660371A (en) Virtual power plant day-ahead and day-internal two-stage cooperative regulation and control method and device
CN114498769A (en) High-proportion wind-solar island micro-grid group energy scheduling method and system
Liu et al. Hierarchical optimal dispatching strategy for microgrid system considering user-side resources
CN111967646A (en) Renewable energy source optimal configuration method for virtual power plant
CN112801813A (en) Method and system for determining virtual power plant system source-load collaborative optimization model

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