CN113437752B

CN113437752B - Operation control method of comprehensive energy system containing hybrid energy storage

Info

Publication number: CN113437752B
Application number: CN202110694608.9A
Authority: CN
Inventors: 张鹏; 唐若愚; 周步祥; 臧天磊; 张越; 罗欢; 董申; 陈实
Original assignee: Sichuan University; Dongfang Electric Machinery Co Ltd DEC
Current assignee: Sichuan University; Dongfang Electric Machinery Co Ltd DEC
Priority date: 2021-06-22
Filing date: 2021-06-22
Publication date: 2023-04-25
Anticipated expiration: 2041-06-22
Also published as: CN113437752A

Abstract

The application provides a comprehensive energy system operation control method containing mixed energy storage, and relates to the technical field of energy scheduling. The method comprises the steps of starting from the actual running condition of an energy storage device, constructing a preset comprehensive energy system containing hybrid energy, comprising a distributed energy storage device, a distributed energy generation device and an energy conversion device, wherein the preset comprehensive energy system containing the hybrid energy can be a virtual power plant, performing detailed independent modeling on all equipment in the virtual power plant, comprehensively considering energy balance constraint, hybrid energy constraint, equipment running constraint and energy transmission network constraint aiming at the comprehensive energy virtual power plant containing the hybrid energy, and finally establishing an optimal scheduling model of the comprehensive energy virtual power plant containing the hybrid energy by taking the maximum profit and the minimum energy loss as objective functions to obtain the electric energy conversion quantity of all equipment in the distributed energy storage device so as to compensate the random fluctuation and the intermittence of the distributed energy through the electric energy conversion of the energy storage device.

Description

Operation control method of comprehensive energy system containing hybrid energy storage

Technical Field

The application relates to the technical field of energy scheduling, in particular to an operation control method of a comprehensive energy system containing hybrid energy storage.

Background

Energy is an important foundation for global social operation and development, and for a long time, human beings excessively depend on fossil energy with limited resources, so that the problem of environmental pollution is not ignored. Clean energy sources such as electricity, natural gas and new energy sources are increasingly being used from research to application in response to the problems of energy exhaustion and environmental pollution.

The new energy is unevenly distributed in different regions, for example, the regions with enough wind energy for generating electricity are mainly in open regions such as northern plain and grasslands; areas capable of photovoltaic power generation are concentrated on the plateau; the area capable of carrying out hydroelectric generation of river channels is mostly along the coast of yellow river and Yangtze river. Meanwhile, the electricity consumption, electricity consumption conditions and electricity consumption peaks of different regions are different, for example, the electricity consumption of high-voltage electricity in the daytime is larger in multiple factories in the bead triangle region; the large cities in various provinces are populated with a large number of people, and the peak value of the low-voltage electricity consumption occurs at night. Based on the current situation, the rationality and instantaneity of energy scheduling and distribution are particularly important.

In the prior art, power dispatching and distribution are generally regulated by paving a power transmission network, however, the circuit network has a longer setting period, and sudden power consumption peaks or other power consumption conditions cannot be dealt with.

Disclosure of Invention

The embodiment of the application provides a comprehensive energy system operation control method containing mixed energy storage, which can coordinate energy requirements among all areas by using charge quantity or discharge quantity of a distributed energy storage device so as to adjust electricity consumption peaks or other electricity consumption conditions among all areas.

The embodiment of the application provides a comprehensive energy system operation control method containing mixed energy storage, which comprises the following steps:

adding the distributed energy storage device into an electrothermal gas comprehensive energy system according to the consumption requirement of renewable energy sources to obtain a preset comprehensive energy system containing mixed energy storage; wherein, the electric heating gas comprehensive energy system comprises a distributed energy generating device;

according to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage; 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;

constructing an energy discarding model of the distributed energy generating device;

and taking the maximum gain as a first solving target of the optimal scheduling model, taking the minimum energy loss as a second solving target of the energy discarding model, and calculating to obtain the electric energy conversion quantity of the distributed energy storage device by utilizing a fuzzy membership function according to the first solving target and the second solving target so as to balance the energy difference of the preset comprehensive energy system containing hybrid energy storage by utilizing the electric energy conversion quantity.

Optionally, the distributed energy source generating device comprises a wind power device and a photovoltaic power generation device; adding the distributed energy storage device into an electrothermal gas comprehensive energy system according to the consumption requirement of renewable energy sources to obtain a preset comprehensive energy system containing mixed energy storage, wherein the comprehensive energy system comprises:

according to the electric power consumption required by the wind power device and the photovoltaic power generation device, adding a gas-electricity conversion device into an electric heating gas comprehensive energy system;

according to the energy conversion characteristics of the new energy automobile, adding the new energy automobile into an electric heating gas comprehensive energy system;

according to the characteristics of the hydrogen storage device for converting multiple energy sources and the long-term energy storage requirement, adding the hydrogen storage device into an electric heating gas comprehensive energy system;

and adding the storage battery and the heat storage tank into the preset comprehensive energy system containing the hybrid 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 steps of:

and adding an electric boiler into the preset comprehensive energy system containing hybrid energy storage according to the energy demand difference of the external power grid and the external heat supply network so as to regulate and optimally control the cogeneration demands 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 steps of:

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 network and the external air network so as to regulate and optimally control the energy co-supply requirements of different areas.

Optionally, the method further comprises:

acquiring the electric quantity requirement of the current time;

constructing a first energy model of the distributed energy storage device; the first energy model is used for representing the association relation between the first operation parameter and the electric energy conversion quantity generated by the distributed energy storage device;

according to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage, which comprises the following steps:

and determining the electric quantity requirement, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

Optionally, the method further comprises:

acquiring the electric quantity requirement of the current time;

constructing an electric energy balance constraint condition according to the electric quantity requirement and the real-time electric quantity generated by the distributed energy generating device;

constructing a second electric energy balance constraint condition according to the wind discarding loss of the wind power device and the light discarding 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 electric energy conversion quantity comprises the following components:

and under the first electric energy balance constraint condition and the second electric energy balance constraint condition, calculating to obtain 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 heat demand, heat energy supply, gas energy demand and gas energy supply of the current time;

constructing a thermal energy balance constraint condition according to the heat demand and the thermal energy supply quantity;

constructing a gas energy balance constraint condition according to the gas energy requirement and the gas energy supply quantity;

And under the heat energy balance constraint condition and the gas energy balance constraint condition, calculating to obtain 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.

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 association relation between the second operation parameter and the output force of the distributed energy generation device;

and determining the second energy model, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

Optionally, the preset integrated energy system containing hybrid energy storage comprises an energy conversion device; the method further comprises the steps of:

adding an energy conversion device into an electric heating integrated energy system according to the energy conversion requirements among any two of the external power grid, the external air grid and the external heat supply network to obtain a preset integrated energy system containing mixed energy storage and provided with the energy conversion device;

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 the discharge efficiency, the heat release efficiency or the gas energy consumption of the energy conversion device.

Optionally, the method further comprises:

constructing a third energy model of the energy conversion device; the third energy model is used for representing the association relation between the third operation parameter and the energy consumption of the energy conversion device;

and determining the third energy model, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

The embodiment of the application starts from the actual running condition of the energy storage device, constructs a preset comprehensive energy system containing hybrid energy storage, which comprises a distributed energy storage device, a distributed energy generation device and an energy conversion device, wherein the preset comprehensive energy system containing hybrid energy storage can be a virtual power plant, so that the distributed energy storage device is utilized to supplement the deficiency of electric power when the power consumption peaks and the distributed energy storage device is utilized to store electric energy when the power consumption peaks or convert the electric energy into gas energy, heat energy or chemical energy to supplement the instantaneous consumption of other energy in the process of coordinating the energy of each energy system through a communication technology and a software architecture; according to the method, a preset comprehensive energy system containing hybrid energy storage is respectively connected with an external power grid, an external air network and an external heat supply network, an optimal scheduling model with maximum benefit as a target is built, an energy discarding model with minimum energy discarding loss as a target is built, the real-time generated energy, the required energy of a real-time user for various energy sources, the loss of a maintenance distributed energy storage device, a distributed energy generation device and an energy conversion device are input into the optimal scheduling model and the energy discarding model, the electric energy conversion quantity capable of achieving the maximum benefit target and the minimum energy discarding loss target is solved, the electric energy conversion quantity is the charged quantity or the discharged quantity of the distributed energy storage device, and then the energy requirements among all areas are coordinated with the charged quantity or the discharged quantity of the distributed energy storage device, or the charged quantity or the discharged quantity of the distributed energy storage device supplements energy gaps 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 that are needed in the description of the embodiments of the present application will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of 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 diagram of a preset hybrid energy storage integrated energy system in an embodiment of the present application;

fig. 3 is a functional block diagram of an integrated energy system operation control device containing hybrid energy storage according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

Fig. 1 is a flowchart of steps of a method for controlling operation of an integrated energy system including hybrid energy storage according to an embodiment of the present application, as shown in fig. 1, where the method includes:

step S11: adding the distributed energy storage device into an electrothermal gas comprehensive energy system according to the consumption requirement of renewable energy sources to obtain a preset comprehensive energy system containing mixed energy storage; wherein, the electric heating gas comprehensive energy system comprises a distributed energy generating device.

According to the embodiment of the application, the distributed energy storage device is added into the electric and thermal gas comprehensive energy system, the defect that single energy storage is difficult to meet the requirements of both power and energy is overcome, and as the distributed energy storage device comprises a plurality of energy storage devices, the preset comprehensive energy system containing hybrid energy storage comprises hybrid energy storage, the hybrid energy storage is fully complementary from different time scales, and the uniformity of economy, high efficiency and stability of the system is realized.

Fig. 2 is a schematic structural diagram of a preset integrated energy system including hybrid energy storage in an embodiment of the present application, and as shown in fig. 2, a distributed energy generating device includes a wind power device and a photovoltaic power generation device; the substeps of step S11 include:

step S11-1: and adding a gas-electricity conversion device into an electric-thermal integrated 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 high, and Power balance and electric energy quality are difficult to maintain.

Step S11-2: and adding the new energy automobile into the electric heating gas comprehensive energy system according to the energy conversion characteristics of the new energy automobile and the absorption requirements of renewable energy.

The new energy automobile (EVS) has energy conversion characteristics 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 the new energy automobile has a large-scale convergence effect; the multiple new energy automobiles forming the local network can balance the energy difference value of the specific position.

The new energy automobile is connected with an external power grid.

Step S11-3: the hydrogen storage device is added into the electric heating gas comprehensive energy system according to the characteristics of the hydrogen storage device for converting various energy sources and the long-term energy storage requirement.

The characteristic that the hydrogen storage device has a function of converting various energy sources means that: 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 which is connected with an external power grid. The electrolytic cell can convert the electric energy into hydrogen, the hydrogen is stored in the hydrogen storage device, and the fuel cell can convert the hydrogen into electric energy and input the electric energy into an external power grid. The hydrogen can exist stably for a long time in a hydrogen storage device, which is a long-term energy storage device.

Step S11-4: and adding the storage battery and the heat storage tank into the preset comprehensive energy system containing the hybrid 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 the 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 running process of the system. The heat storage device may be a heat storage tank.

The embodiment of the application adopts the external power grid to connect the hydrogen storage device and P2G and other energy modes to realize the distributed conversion and storage of electric energy, and then promotes the utilization of renewable energy sources in the modes of improving regulation means and the like; renewable energy power generation is matched with a hydrogen storage device to become a schedulable, predictable and controllable power supply; meanwhile, the new energy automobile is utilized to realize the power supply and power consumption relation conversion of the terminal user, the energy buffering of the energy utilization equipment, the flexible interaction and the intelligent interaction.

In another embodiment of the present application, an energy conversion device may also be added to the electrothermal gas integrated energy system to achieve the interconversion of various energy sources (electrical energy, gas energy, and thermal energy). And adding the energy conversion device into an electric heating integrated energy system according to the energy conversion requirements among any two of the external power grid, the external air grid and the external heat supply network to obtain the preset integrated energy system containing hybrid energy storage and provided with the energy conversion device.

The energy conversion device comprises an electrolytic cell and a fuel cell which are provided by other embodiments of the application, 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 comprehensive energy system comprises the following steps:

According to the embodiment of the application, the gas boiler, the gas turbine, the waste heat recovery device and the electric boiler are utilized, so that energy conversion between an external power grid and an external heat supply network, energy conversion between the external power grid and an external air network and energy conversion between the external heat supply network and the external air network are realized, and a foundation is provided for full complementation of hybrid energy storage from different time scales.

Step S12: according to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage; 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.

In another embodiment of the present application, before an optimized scheduling model of a preset integrated energy system including hybrid energy storage is constructed according to the first operating parameter and the second operating parameter, the discharge efficiency, the heat release efficiency or the gas energy consumption of the energy conversion device is also obtained and used as a third operating parameter, and finally the optimized scheduling model is constructed according to the first operating parameter, the second operating parameter and the third operating parameter. The third operating parameter is the discharge efficiency, the heat release efficiency or the gas energy consumption of the energy conversion device.

In one embodiment of the present application, the first operating parameter includes: the novel energy vehicle comprises charging power of the novel energy vehicle, discharging power of the novel energy vehicle, power of the gas-electric conversion device for absorbing wind power generation, power of the gas-electric conversion device for absorbing photovoltaic power generation, charging efficiency of the hydrogen storage device, discharging efficiency of the hydrogen storage device, charging efficiency of the storage battery, discharging efficiency of the storage battery, heat release efficiency of the heat storage device and heat storage efficiency of the heat storage device.

The second operating parameters include: wind power discharge power, photovoltaic power generation power and interruptible load power.

The third operating parameters include: the gas turbine consumes an amount of natural gas.

Besides the first operation parameters including the second operation parameters and the third operation parameters, the optimal scheduling model is constructed, the electric energy consumption in the external power grid is required to be collected, the electric energy consumption in the external power grid can be the transaction amount of the electric power market, the electric quantity required by the electric network in a specific area is calculated according to the electric quantity required by a user in real time, the electric power generated by the distributed energy generating device and the real-time electric energy generated by the distributed energy generating device, then the target parameters which can simultaneously consider the targets with the maximum income and the minimum energy rejection are calculated according to the energy storage power of various hybrid energy storage devices contained by the distributed energy storing device, and the target parameters respectively correspond to the real-time energy storage values of various hybrid energy storage devices, so that the purposes of optimizing the open interconnection of various energy sources, flexible interconnection, adjustment and joint regulation of different energy networks with electricity as the center are achieved.

Another embodiment of the present application specifically describes the working principle of the constructed optimal scheduling model. Before an optimized scheduling model is built, the embodiment of the application respectively builds the parameter models of all energy storage equipment in the distributed energy storage device to obtain a first energy model of the distributed energy storage device.

Before a first energy model is built, acquiring the electric quantity requirement of the current time; the electric quantity requirement of the current time refers to the electric quantity consumed by a user at a specific time of a preset comprehensive energy system containing hybrid energy storage. The current time power demand may be the power consumption in the external power grid collected by other embodiments of the present application.

an example process of constructing a first energy model of a distributed energy storage device is as follows:

1. and constructing a new energy automobile charging and discharging and energy storage parameter model. For modeling feasibility, assume that the schedulable new energy automobile of each area is connected with the power grid through a centralized controller, and the centralized controller is equivalent to a new energy automobile to complete optimal scheduling, and the model is shown in the following formulas (1) and (2):

Wherein,,

representing the charging power of the new energy automobile in t time period, < >>

Representing the discharge power of the new energy automobile in the t period;

And->

The value of (2) is in the range of 0-1, and the new energy automobile is in the condition of charging,/-for the new energy automobile>

Is equal to 1 and is equal to 1,

equal to 0; in the case of a discharge of a new energy vehicle, < >>

Equal to 0, & gt>

Equal to 1;

Representing the battery capacity of the new energy automobile in the t+1 period,/->

Representing the charging efficiency of a new energy vehicle, +.>

Indicating the discharge efficiency of the new energy automobile.

2. Constructing a parameter model of a gas-electric conversion device (P2G), as shown in a formula (3):

wherein,,

represents the gas production power, eta of the period t ^P2G Indicating the efficiency of gas production, +.>

Representing the power consumption. Sources of electrical energy consumed by the gas-to-electricity 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 a long-term energy storage device, the hydrogen storage system has lower charge and discharge efficiency and lower 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 formula (4):

wherein E is _HST,t+1 Represents the capacity of the hydrogen storage device during the period t +1,

representing the real-time electrolytic power of the electrolytic cell,

Indicating the real-time released power of the fuel cell;

Indicating the electrolysis efficiency of the cell, < >>

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 charge and discharge efficiency and high power, and is mainly used for maintaining the real-time supply and demand balance. The model of the storage battery is shown in formula (5):

wherein E is _BES,t+1 For the real-time capacity of the battery,

for the charging power of the accumulator, ">

For the discharge power of the accumulator, < >>

For the charging efficiency of the accumulator>

Is 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 running process of the system. Assuming that the front and back states of charge of the energy storage system remain unchanged during an operation period, and meanwhile, the states of charge of the energy storage system meet the constraint shown in the formula (6) in the charging and discharging process:

wherein E is _TST,t+1 Representing the real-time capacity of the heat storage device,

indicating heat storage power, +.>

Indicating exothermic power, +.>

Indicating heat storage efficiency, +.>

Indicating the heat release efficiency.

According to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage, which comprises the following steps: and determining the electric quantity requirement, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

Before an optimal scheduling model is built, the embodiment of the application respectively builds parameter models of all power generation equipment in the distributed energy generation device to obtain a second energy model of the distributed energy generation device.

Constructing a second energy model of the distributed energy generation device; the second energy model is used for representing the association relation between the second operation parameter and the output force of the distributed energy generation device.

An example process of constructing a second energy model of a distributed energy generation apparatus is as follows:

1. and constructing a wind turbine output parameter model. The output of the wind turbine is directly related to the wind speed. At present, the wind speed is generally modeled by adopting Weibull distribution aiming at a wind turbine generator output model, and a wind speed probability density function based on the Weibull distribution is shown as a formula (7):

wherein v represents wind speed, f _w (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 method for calculating the shape parameter of the wind speed is shown as the formula (8):

the method for calculating the dimensional parameter of the wind speed is shown in the formula (9):

Where μ represents an expected value of the wind speed history data, σ represents a variance of the wind speed history data, Γ is a Gamma function. Based on the wind speed model, an output model of the wind turbine generator is established as shown in a formula (10):

wherein P is _W The output of the wind turbine generator can also be regarded as the power of the wind turbine generator; v is wind speed, v _i To cut in wind speed v _r Is rated wind speed v _o To cut out wind speed, P _Wo The 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 the Beta distribution, i.e. the power curve of the photovoltaic system follows the condition of formula (11):

wherein k and c are shape parameters of Beta distribution, θ is radiation intensity, and average value and standard deviation of irradiance are introduced for calculation.

According to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage, which comprises the following steps: and determining the second energy model, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

Before an optimized scheduling model is built, parameter models of all devices in the energy conversion device are built respectively, and a third energy model of the energy conversion device is obtained.

Constructing a third energy model of the energy conversion device; the third energy model is used for representing the association relation between the third operation parameter and the energy consumption of the energy conversion device.

An example process of constructing a third energy model of a distributed energy conversion device 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 is shown as the formula (12):

wherein,,

for the heat production power of the gas boiler in the t period, < >>

For heat production efficiency, +.>

The gas consumption power of the gas boiler in the period t is obtained.

2. Constructing a parameter model of the gas turbine, wherein the parameter model of the gas turbine is shown as a formula (13):

wherein,,

for t-period gas turbine electric power, +.>

Waste heat power of the gas turbine in the t period;

For the natural gas consumption of the gas turbine in the period t, eta ^MT For gas turbine efficiency, eta ^loss The 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 in the formula (14):

Wherein,,

heating power eta for the waste heat recovery device in the period t ^hrs The waste heat recovery device efficiency is achieved.

4. And constructing a parameter model of the electric boiler. An electric boiler is a more common electric-to-thermal conversion device, and a parameter model thereof is shown as a formula (15):

wherein,,

for the heat supply quantity of the electric boiler in the period t, eta ^EB For the electric-heat conversion efficiency of an electric boiler, < >>

The power consumption of the electric boiler in the period t is shown.

5. And constructing a parametric model of the electrolytic cell and the fuel cell. The parametric model of the electrolytic cell is shown as (16), and the parametric model of the fuel cell is shown as (17):

wherein,,

for the consumed electrical power of the electrolytic cell, +.>

The amount of hydrogen gas generated for the cell; v _EC For the conversion efficiency of the electrolytic cell, < > for>

Converting the electric energy into hydrogen with the same energy;

For the amount of hydrogen consumed by the fuel cell, +.>

For the electric power output by the fuel cell, v _FC Is the conversion efficiency of the fuel cell.

According to the first operation parameter and the second operation parameter, constructing an optimized scheduling model of the preset comprehensive energy system containing the hybrid energy storage, which comprises the following steps: and determining the third energy model, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model, and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

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 the distributed energy storage device into an optimized 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 an optimization scheduling model, wherein the optimization scheduling model can be used for determining the following variables in the known decision variables: the method comprises the steps of solving and obtaining energy storage energy of energy storage devices such as the new energy automobile, the gas-electric conversion device, the hydrogen storage device, the storage battery, the heat storage device and the heat storage device under the conditions that charging power of the new energy automobile, discharging power of the new energy automobile, power of the gas-electric conversion device for absorbing wind power generation, power of the gas-electric conversion device for absorbing photovoltaic power generation, charging efficiency of the hydrogen storage device, discharging efficiency of the hydrogen storage device, charging efficiency of the storage battery, discharging efficiency of the storage battery, heat storage device, heat storage efficiency of the heat storage device, wind power generation power of the storage battery, interruptable load power and natural gas consumption of the gas turbine, and converting surplus energy into heat energy or gas energy by the energy storage energy.

One example of the application adopts the maximum running net profit as a target to establish an optimal scheduling model. The optimal scheduling model is shown as (18):

f ₁ for the first solution target.

Wherein T is a period of 24 hours. I is the income of the preset comprehensive energy system containing the hybrid energy storage, and C is the cost of the preset comprehensive energy system containing the hybrid energy storage. The calculation of I is shown in formula (19):

the calculation of C is shown in the formula (20):

C＝C _pv 、 _W,t +C _P2G,t +C _EV,t +C _MT,t +C _main (20)；

wherein I is _L，t For t period load benefit, I _M，t Representing energy market benefit, I _EV，t Representing the charge benefits and the discharge benefits of the new energy automobile;

indicating the benefit of the battery->

Indicating hydrogen storage device benefit->

Indicating the benefit of the heat storage device. C (C) _pv Representing operation and maintenance cost of the wind turbine generator set in t period, C _W，t Representing the operation and maintenance cost of photovoltaic power generation, C _P2G，t Representing the conversion cost of P2G operation, C _MT，t Representing the operation and maintenance cost of the gas turbine, C _main Representing the maintenance costs of other devices than the above-mentioned devices.

the calculation method of the load gain in the t period is shown as the formula (21):

wherein P is _L，t Is the load of the t period of time,

is the k-th level interrupt load power, k is the number of interrupt classes. Lambda (lambda) _M，t Is market electricity price;

Is the k-th level interrupt load compensation price.

The energy market revenue includes electric power market revenue and heat grid revenue as shown in equation (22):

I _M，t ＝λ _su，t P _M，t μ _su，t -λ _sd，t P _M,t μ _sd，t +λ _α Q _t (22)；

Wherein P is _M，t Is t period preset comprehensive energy system containing hybrid energy storage and electric power market transaction amount, Q _t The method is characterized in that the market transaction amount of the comprehensive energy system containing the hybrid energy storage and the heat supply network is preset in a t period. Mu when electricity is sold in preset comprehensive energy system containing mixed energy storage _su,t The value is 1 mu _sd,t The value is 0, and mu is preset when the comprehensive energy system containing the hybrid energy storage is purchased _su,t Take the value of 0 mu _sd,t The value is 1. Lambda (lambda) _su,t Is to preset the contract electricity selling price lambda of the comprehensive energy system containing the hybrid energy storage and the electric power market _sd,t Is to preset contract electricity purchase price lambda of a comprehensive energy system containing hybrid energy storage and an electric power market _α The method is to preset the transaction price of the comprehensive energy system containing the hybrid energy storage and the heat supply network.

The profit calculation mode of the single new energy automobile is shown as the formula (23):

I _EV,t ＝λ _ch，t P _EV，t μ _ch，t +λ _dis，t P _EV，t μ _dis，t -λ _EV P _EV，t (23)；

P _EV，t when the value is positive, the charging quantity P of the new energy automobile in the period t is represented _EV，t And when the value is negative, the discharge capacity of the new energy automobile is represented in the period t. Mu in case of charging a new energy automobile _ch，t The value is 1 mu _dis，t The value is 0, and mu is in the case of discharging the new energy automobile _ch，t Take the value of 0 mu _dis，t The value is 1. Lambda (lambda) _ch，t Represents the charging price lambda of the new energy automobile _dis,t Represents the discharge price lambda of the new energy automobile _EV Indicating the charge and discharge of new energy automobiles Compensating coefficients.

The sales energy benefits of the storage battery are shown as (24):

wherein c _E，t Revenue representing discharge of storage battery->

Indicating the sales energy income of the hydrogen storage device, c _T,t Representing heat selling income of heat storage device, P _FC,t Indicating the sales capacity of the hydrogen storage device, < >>

Indicating the sales heat of the hydrogen storage device.

The hydrogen storage device benefit is shown in formula (25):

wherein,,

the heat storage device benefit is shown in formula (26):

wherein the method comprises the steps of

The operation and maintenance costs of the wind turbine generator and the photovoltaic power generation are shown in the formulas (27) and (28):

C _PV ＝λ ₁ P _PV,t +λ ₂ P _W,t (27)；

C _W,t ＝λ ₁ P _PV,t +λ ₂ P _W,t (28) The method comprises the steps of carrying out a first treatment on the surface of the Wherein P is _PV,t Is the photovoltaic power of the region t period, P _W,t Is the fan power of the i region t period, λ1 is the operation and maintenance cost of the fan electric group, and λ2 is the operation and maintenance cost of the photovoltaic.

The calculation mode of the operation conversion cost of the gas-electric conversion device is shown as the formula (29):

wherein lambda is _P2G Is the P2G operation conversion cost, < >>

Is the unit price of CO 2.

The operation and maintenance cost of the gas turbine is calculated as shown in the formula (30):

wherein lambda is _gas For the price of natural gas in the period t,

for the start-up costs of the gas turbine, < > for>

Is the stopping cost of the gas turbine;

And->

Is a boolean variable,/-when the gas turbine is started in period t>

The value is 1, & lt + & gt>

The value is 0; when the gas turbine is stopped in the t period, the valve is opened>

The value is 0, & lt + & gt>

The value is 1.

The maintenance cost of the other devices is calculated as shown in the formula (31):

(31) The method comprises the steps of carrying out a first treatment on the surface of the Wherein,,

indicating the equipment maintenance costs of the electrolytic cell during the scheduling period,/-, for example>

Representing the equipment maintenance costs of the fuel cell during the scheduling period,/->

Indicating equipment maintenance costs of the hydrogen storage device during the scheduling period,/->

Representing equipment maintenance costs of the heat storage device during the scheduling period,/->

Indicating the equipment maintenance costs of the battery during the dispatch period.

Step S13: and constructing an energy discarding model of the distributed energy generating device.

The way in which the energy abandoning model is constructed in an example is shown in the formula (32), and the energy abandoning rate is minimized as the ratio of the energy abandoning quantity of the virtual power plant to the actual available new energy:

f ₂ for the second solution target.

Wherein,,

for discarding wind volume->

For discarding light quantity +.>

For the total amount of actually available wind power, +.>

Is the total amount of practically usable photovoltaic.

Step S14: and taking the maximum gain as a first solving target of the optimal scheduling model, taking the minimum energy loss as a second solving target of the energy discarding model, and calculating to obtain the electric energy conversion quantity of the distributed energy generating device according to the first solving target and the second solving target by using a fuzzy membership function so as to balance the energy difference of the preset comprehensive energy system containing hybrid energy storage by using the electric energy conversion quantity.

The specific method for obtaining the electric energy conversion quantity of the distributed energy storage device by utilizing the fuzzy membership function to solve the optimal scheduling model and the energy discarding model according to the first solving target and the second solving target is as follows:

in order to consider the double-target problem of the maximum net benefit and the minimum energy rejection of the system, the final scheduling scheme is weighted and screened from the Pareto solution set by utilizing the fuzzy membership function, and the double-target problem of the maximum benefit and the minimum energy rejection is calculated according to the method shown in the formulas (33) and (34):

wherein x is _m Mu, the value of the objective function _m,i For m non-inferior solutions x _m Satisfaction with the ith objective; f (f) _i (x _m ) Is a non-inferior solution x _m Is set to be equal to the i-th target value of (c),

maximum value of the ith target, +.>

Minimum value of ith target, μ _m Is a non-inferior solution x _m The comprehensive satisfaction degree of all targets is that M is the number of non-inferior solutions; l is the target number, which in this application is 2.

The solving flow of the multi-objective optimization model of the comprehensive energy virtual power plant containing mixed energy storage, which is adopted in the method, is as follows:

(1) Setting basic conditions such as population scale, iteration times, and if the initial iteration times are k=1. The population in this application is the objective function mentioned herein.

(2) Initializing a population.

(3) And calculating an individual objective function value optimization scheduling model and an energy discarding model, and sorting by using a Pareto priority sorting method.

(4) And calculating two fitness values of the objective functions of the two particles, and further updating the individual optimal values.

(5) Assuming k is a multiple of 10, the selection, crossover and mutation operations are performed, individual optimum values are reinitialized, and the speed and position of the particles are updated.

(6) Judging whether iteration is finished, if the set maximum iteration number is reached, turning to (7), otherwise turning to (3), and carrying out the next iteration.

(7) And (3) selecting a final scheduling scheme by weighting from the Pareto solution set by referring to the fuzzy membership function, if t=t+1, if T is less than or equal to 1, and if T is less than T, turning to (2), until a solution with the minimum energy loss and the maximum benefit is obtained.

According to the method and the device, the balance constraint condition is set, so that the preset comprehensive energy system containing the hybrid energy storage can obtain the electric energy conversion quantity of each device in the distributed energy storage device under the condition of considering energy balance, and the random fluctuation and the intermittent supplement of the distributed energy are realized.

Acquiring the electric quantity requirement of the current time; constructing an electric energy balance constraint condition according to the electric quantity requirement and the real-time electric quantity generated by the distributed energy generating device; and constructing a second electric energy balance constraint condition according to the wind discarding loss of the wind power device and the light discarding loss of the photovoltaic power generation device.

The preset comprehensive energy system containing the hybrid energy storage adopts (35) constraint electric quantity and electric energy generation to keep instantaneous balance.

Wherein,,

representing photovoltaic power;

Representing fan power;

Indicating gas turbine power,/-, and>

representing the electric power output by the hydrogen storage device;

Representing fan power;

Indicating gas turbine power,/-, and>

represents the electric power output by the hydrogen storage device, P _M,t Representing the amount of power obtained from an external power grid; p (P) _EV,t Representing the charge or discharge of the new energy automobile;

Indicating the energy released by the cell; p (P) _L,t Representing the amount of charge;

Representing an interrupt load power;

Indicating the discharge capacity of the battery.

Wherein,,

wherein,,

representing photovoltaic power;

Indicating the amount of waste;

Indicating the total photovoltaic output.

In the middle of

Representing fan power;

Indicating the air discarding quantity;

Indicating the total output of the fan.

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 electric energy conversion quantity comprises the following components: and under the first electric energy balance constraint condition and the second electric energy balance constraint condition, calculating to obtain 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.

the integrated energy system comprising the hybrid energy storage is preset to maintain a transient balance between the amount of thermal energy used and the amount of thermal energy output using (38).

Wherein,,

indicating the heat supply quantity of the electric boiler;

Indicating the heat supply quantity of the gas boiler;

Representing the heat supply of the gas turbine;

Indicating the heat release amount of the heat storage device; q (Q) _t Representing heat obtained from an external heat supply network;

Indicating the amount of heat stored; l (L) _h，t Indicating the amount of heat actually used.

in addition to the external gas market, only the P2G energy conversion equipment is arranged in the preset comprehensive energy system containing the hybrid energy storage to supply gas energy, so that the preset comprehensive energy system containing the hybrid energy storage adopts (39) about heat energy to keep instantaneous balance.

Wherein,,

representing the P2G gas production power; q (Q) _gas Representing the amount of natural gas obtained from an external gas network;

Representing the power of the natural gas consumed by the gas boiler;

The natural gas amount consumed by the gas boiler is represented; l (L) _g,t Representing the gas load required for presetting the integrated energy system containing the hybrid energy storage.

The embodiment of the application also adopts the formulas (40) and (41) to carry out interrupt load constraint.

Is t period kth level interruptible load maximum power.

Other devices, such as wind turbine generator system constraint, and constraint conditions related to wind turbine generator system, photovoltaic turbine generator system and electric automobile can adopt constraint conditions of related technologies, and the embodiment of the application is not repeated.

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 electric energy conversion quantity comprises the following components: and under the heat energy balance constraint condition and the gas energy balance constraint condition, calculating to obtain 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.

Based on the same inventive concept, the embodiment of the application provides a comprehensive energy system operation control device containing hybrid energy storage. Referring to fig. 3, 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. The device comprises:

the first adding module 31 is configured to add the distributed energy storage device to the electrothermal gas integrated energy system according to the consumption requirement of the renewable energy source, so as to obtain a preset integrated energy system containing mixed energy storage; wherein, the electric heating gas comprehensive energy system comprises a distributed energy generating device;

A first construction module 32, configured to construct an optimized scheduling model of the preset hybrid energy storage-containing comprehensive energy system according to the first operation parameter and the second operation 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;

a second construction module 33, configured to construct an energy discarding model of the distributed energy generating apparatus;

the calculation module 34 is configured to calculate, according to the first solution target and the second solution target by using a fuzzy membership function, an electric energy conversion amount of the distributed energy storage device, so as to balance the energy difference of the preset hybrid energy storage-containing comprehensive energy system by using the electric energy conversion amount.

Optionally, the distributed energy source generating device comprises a wind power device and a photovoltaic power generation device; the first joining module includes:

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 sub-module is used for adding the new energy automobile into the electric heating gas comprehensive energy system according to the energy conversion characteristics of the new energy automobile;

the third adding sub-module is used for adding the hydrogen storage device into the electric heating gas comprehensive energy system according to the characteristics of the hydrogen storage device for converting various energy sources and long-term energy storage requirements;

and the fourth adding submodule is used for adding the storage battery and the heat storage tank into the preset comprehensive energy system containing the hybrid energy according to the real-time energy storage requirement.

Optionally, the preset integrated energy system containing hybrid energy storage is connected to an external power grid and an external heat supply network respectively, and the device further comprises:

and the second adding module is used for adding the electric boiler into the preset comprehensive energy system containing the hybrid energy storage according to the energy demand difference of the external power grid and the external heat supply network so as to regulate and optimally control the cogeneration demands of different areas.

Optionally, the preset comprehensive energy system containing hybrid energy storage is connected with an external air network; the apparatus further comprises:

and the third adding module is used for adding the gas boiler, the gas turbine and the waste heat recovery device into the preset comprehensive energy system containing the hybrid energy storage according to the energy demand difference of the external power grid and the external air grid and the energy demand difference of the external heat supply network and the external air network so as to regulate and optimally control the energy co-supply and the demand of different areas.

Optionally, the apparatus further comprises:

the first acquisition module is used for acquiring the electric quantity requirement of the current time;

a third building module for building a first energy model of the distributed energy storage device; the first energy model is used for representing the association relation between the first operation parameter and the electric energy conversion quantity generated by the distributed energy storage device;

the first building block includes:

the first construction submodule is used for determining the electric quantity requirement, the first operation parameter and the second operation parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model and constructing the optimized dispatching model of the preset comprehensive energy system containing the hybrid energy storage.

Optionally, the apparatus further comprises:

a fourth construction module, configured to construct an electric energy balance constraint condition according to the electric energy requirement and the real-time electric energy generated by the distributed energy generating device;

the fifth construction module is used for constructing a second electric energy balance constraint condition according to the waste wind loss of the wind power device and the waste light loss of the photovoltaic power generation device;

The first building block includes:

and the second construction submodule is used for 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 under the first electric energy balance constraint condition and the second electric energy balance constraint condition.

The apparatus 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 building module for building a thermal energy balance constraint according to the thermal demand and the thermal energy supply;

a sixth building module for building a gas energy balance constraint condition according to the gas energy requirement and the gas energy supply amount;

the computing module includes:

the first calculation sub-module is used for 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 under the heat energy balance constraint condition and the gas energy balance constraint condition.

Optionally, the apparatus further comprises: a seventh building module for building a second energy model of the distributed energy generation device; the second energy model is used for representing the association relation between the second operation parameter and the output force of the distributed energy generation device;

The first building block includes:

and the third construction submodule is used for determining the second energy model, the first operating parameter and the second operating parameter as input variables of the optimized dispatching model, determining the electric energy conversion quantity as output variables of the optimized dispatching model and constructing the optimized dispatching model of the preset comprehensive energy system containing hybrid energy storage.

Optionally, the preset integrated energy system containing hybrid energy storage comprises an energy conversion device; the apparatus further comprises:

the fourth adding module is used for adding the energy conversion device into the electric heating gas comprehensive energy system according to the energy conversion requirement among any two of the external power grid, the external air grid and the external heat supply network to obtain a preset comprehensive energy system containing hybrid energy storage and provided with the energy conversion device;

the first building block includes:

the fourth construction submodule is used for constructing the optimal scheduling model according to the first operation parameter, the second operation parameter and the third operation parameter; wherein the third operating parameter is the discharge efficiency, the heat release efficiency or the gas energy consumption of the energy conversion device.

The apparatus further comprises:

an eighth building module for building a third energy model of the energy conversion device; the third energy model is used for representing the association relation between the third operation parameter and the energy consumption of the energy conversion device;

the first building block includes:

and a fifth construction submodule, configured to determine the third energy model, the first operation parameter and the second operation parameter as input variables of the optimized scheduling model, determine the electric energy conversion quantity as output variables of the optimized scheduling model, and construct the optimized scheduling model of the preset integrated energy system containing hybrid energy storage.

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 in the integrated energy system operation control method including hybrid energy storage according to any of the embodiments of the present application.

Based on the same inventive concept, another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the steps in the method for controlling operation of the integrated energy system with hybrid energy storage described in any of the foregoing embodiments of the present application.

For the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.

In this specification, each embodiment is described in a progressive or illustrative manner, and each embodiment is mainly described by the differences from other embodiments, and identical and similar parts between the embodiments are mutually referred.

It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present embodiments 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 on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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 device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, 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 apparatus 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 apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus 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 embodiments have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the present application.

Finally, it is further noted that relational terms such as first and second, and the like are 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. Moreover, 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 one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.

The above description of the above embodiment is only used to help understand the method and core idea of the present application; meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Claims

1. An integrated energy system operation control method containing hybrid energy storage, which is characterized by comprising the following steps:

according to the consumption requirement of renewable energy sources, starting from the actual running condition of the energy storage device, adding the distributed energy storage device into an electrothermal gas comprehensive energy system to obtain a preset comprehensive energy system containing mixed energy storage; the electric heating gas comprehensive energy system comprises a distributed energy generation device, wherein the distributed energy generation device comprises a wind power device and a photovoltaic power generation device; adding the distributed energy storage device into an electrothermal gas comprehensive energy system according to the consumption requirement of renewable energy sources to obtain a preset comprehensive energy system containing mixed energy storage, wherein the comprehensive energy system comprises:

adding a storage battery and a heat storage tank into the preset comprehensive energy system containing hybrid energy storage according to the real-time energy storage requirement;

the first operating parameter includes: the method comprises the steps of charging power of a new energy automobile, discharging power of the new energy automobile, power consumed by a gas-electric conversion device for wind power generation, power consumed by the gas-electric conversion device for photovoltaic power generation, charging efficiency of a hydrogen storage device, discharging efficiency of the hydrogen storage device, charging efficiency of a storage battery, discharging efficiency of the storage battery, heat release efficiency of a heat storage device and heat storage efficiency of the heat storage device;

the second operating parameter includes: wind power discharge power, photovoltaic power generation power and interruptible load power;

taking the maximum gain as a first solving target of the optimal scheduling model, taking the minimum energy loss as a second solving target of the energy discarding model, and calculating to obtain the electric energy conversion quantity 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 of the preset comprehensive energy system containing hybrid energy storage by using the electric energy conversion quantity;

The preset comprehensive energy system containing the hybrid energy storage is respectively connected with an external power grid, an external heat supply network and an external air network;

adding an electric boiler into the preset comprehensive energy system containing hybrid energy storage according to the energy demand difference of the external power grid and the external heat supply network so as to regulate and optimally control the cogeneration demands of different areas;

2. The method according to claim 1, wherein the method further comprises:

acquiring the electric quantity requirement of the current time;

3. The method according to claim 1, wherein the method further comprises:

acquiring the electric quantity requirement of the current time;

constructing a first electric energy balance constraint condition according to the electric quantity requirement and the real-time electric quantity generated by the distributed energy generating device;

4. The method according to claim 1, wherein the method further comprises:

5. The method according to claim 2, wherein the method further comprises:

6. The method of claim 2, wherein the predetermined hybrid energy storage-containing integrated energy system comprises an energy conversion device; the method further comprises the steps of:

7. The method of claim 6, wherein the method further comprises: