CN111899125B - Optimized modeling operation method, device and medium of comprehensive energy system - Google Patents

Optimized modeling operation method, device and medium of comprehensive energy system Download PDF

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CN111899125B
CN111899125B CN202010758147.2A CN202010758147A CN111899125B CN 111899125 B CN111899125 B CN 111899125B CN 202010758147 A CN202010758147 A CN 202010758147A CN 111899125 B CN111899125 B CN 111899125B
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power
energy
heat
flow
energy system
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CN111899125A (en
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胡志豪
林湘宁
李正天
李雪松
戎子睿
张培夫
陶贵生
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Huazhong University of Science and Technology
State Grid Hubei Electric Power Co Ltd
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Huazhong University of Science and Technology
State Grid Hubei Electric Power Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/067—Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
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    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0206—Price or cost determination based on market factors

Abstract

The invention relates to an optimization modeling operation method, device and medium of a comprehensive energy system, which comprises the steps of obtaining a target information flow of the comprehensive energy system; respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set; and (3) adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme. The invention can consider the connection relation between the information layer and the physical layer of the comprehensive energy system and the interactive working mechanism, and can perform unified modeling and quantitative analysis on the information flow and the energy flow of the comprehensive energy system, thereby realizing optimal energy flow control, improving the energy utilization rate and realizing economic and safe operation of the comprehensive energy system.

Description

Optimized modeling operation method, device and medium of comprehensive energy system
Technical Field
The invention relates to the technical field of comprehensive energy, in particular to an optimization modeling operation method, device and medium of a comprehensive energy system.
Background
In order to relieve the energy crisis, realize the sustainable development of society, china actively promotes the coordinated development of fossil energy and renewable new energy, forms a comprehensive energy system containing various resources such as electric energy, heat energy, natural gas energy, solar energy, biomass energy and the like, can cooperatively schedule various different energy sources, improves the energy utilization rate, promotes energy conservation and emission reduction, and realizes green sustainable development.
With the development of ubiquitous power Internet of things and strong smart grids, the comprehensive energy system and the control system thereof form a typical information physical system, and the functions of wide-area information measurement, information transmission and analysis, information decision and the like can be realized. The energy gateway of the comprehensive energy system carries out deep perception on different equipment information to form an information flow for analysis decision, so that the energy flow of the comprehensive energy system is optimized, and the economic and safe operation of the comprehensive energy system is ensured. However, with the complexity of the integrated energy system information flow and energy flow interactions, it is necessary to model the integrated energy system information flow and energy flow coupling and analyze its interaction mechanisms.
At present, research results mainly relate to discrete information flow modeling (such as communication protocol modeling) or energy flow modeling (such as coordinated control of a generator set and energy storage equipment) of an integrated energy system, however, the prior art rarely relates to an interworking mechanism between information flow and energy flow of the integrated energy system, and unified modeling and quantitative analysis of the information flow and the energy flow of the integrated energy system are lacking.
Therefore, the modeling operation method of the information flow and the energy flow of the comprehensive energy system is provided, the connection relation and the interactive working mechanism of the information layer and the physical layer of the comprehensive energy system are considered, the information flow and the energy flow of the comprehensive energy system can be subjected to unified modeling and quantitative analysis, and the optimal energy flow control is realized, so that the method is a problem to be solved in the current comprehensive energy system research.
Disclosure of Invention
The invention aims to solve the technical problems of the prior art, and provides an optimization modeling operation method, device and medium of a comprehensive energy system, which can consider the connection relation between an information layer and a physical layer of the comprehensive energy system and an interactive working mechanism, and can perform unified modeling and quantitative analysis on the information flow and the energy flow of the comprehensive energy system so as to realize optimal energy flow control.
The technical scheme for solving the technical problems is as follows:
an optimized modeling operation method of a comprehensive energy system comprises the following steps:
acquiring a target information flow of a comprehensive energy system;
respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and (3) adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme.
According to another aspect of the invention, an optimizing modeling operation device of the comprehensive energy system is provided, and the optimizing modeling operation device is applied to the optimizing modeling operation method of the comprehensive energy system, and comprises an information flow acquisition module, an energy flow modeling module and an optimizing solving module;
the information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
And the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme.
According to another aspect of the present invention, there is provided an apparatus for optimizing modeling operation of an integrated energy system, comprising a processor, a memory, and a computer program stored in the memory and operable on the processor, the computer program when run implementing the steps in the method for optimizing modeling operation of an integrated energy system of the present invention.
According to another aspect of the present invention, there is provided a computer storage medium including: at least one instruction, when executed, implements the steps in the method of optimizing modeling operation of the integrated energy system of the present invention.
The method, the device and the medium for optimizing and modeling the comprehensive energy system have the beneficial effects that: the method comprises the steps of obtaining a target information flow of a comprehensive energy system, obtaining a power model capable of describing the comprehensive energy system according to the target information flow, providing an energy flow constraint condition set in the process that an optimal operation objective function reaches an optimal value, building the optimal operation objective function, obtaining an energy flow optimal operation model according to the optimal operation objective function, the power model and the energy flow constraint condition set, and solving the energy flow optimal operation model to obtain an optimal operation scheme, wherein the optimal control of the energy flow in the comprehensive energy system is realized, and the unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system are realized by considering the connection relation and the interactive working mechanism of the information layer and the physical layer of the comprehensive energy system;
The method, the device and the medium for optimizing modeling operation of the comprehensive energy system can collect information of each energy device in an energy layer in the comprehensive energy system and form information flow of the information layer, perform unified modeling and quantitative analysis on the information flow and the energy flow of the comprehensive energy system, and perform optimization solving on an energy flow optimizing operation model from a set of optimizing operation objective functions and energy flow constraint condition sets by utilizing the technology of the information layer to obtain an optimal optimizing operation scheme, so that joint analysis of the information layer and the physical layer of the comprehensive energy system is realized, energy utilization rate is improved, economic and safe operation of the comprehensive energy system is realized, and green sustainable development is realized.
Drawings
FIG. 1 is a schematic flow chart of an optimizing modeling operation method of a comprehensive energy system in a first embodiment of the invention;
FIG. 2 is a flow chart of a method for obtaining a target information stream according to a first embodiment of the present invention;
FIG. 3 is a schematic diagram of the energy flow structure in accordance with the first embodiment of the present invention;
FIG. 4 is a schematic diagram of the information flow structure in the first embodiment of the present invention;
FIG. 5 is a diagram showing an integrated architecture of energy flow and information flow of the integrated energy system according to the first embodiment of the present invention;
FIG. 6 is a graph showing the total output power of the photovoltaic power generation apparatus and the power required by the consumer electrical load and the power required by the consumer thermal load according to the first embodiment of the present invention;
FIG. 7 is a schematic flow chart of an energy flow optimizing operation model according to the first embodiment of the invention;
FIG. 8 is a schematic flow chart of an optimized operation scheme according to the first embodiment of the present invention;
FIG. 9 is a graph showing electricity price versus electricity purchase amount of the integrated energy system according to the first embodiment of the present invention;
FIG. 10 is a graph showing the residual capacity of the electric/thermal energy storage SOC of the integrated energy system according to the first embodiment of the present invention;
FIG. 11 is a graph showing the power of a heat pump/energy storage battery of the integrated energy system according to the first embodiment of the present invention;
fig. 12 is a schematic structural diagram of an optimizing modeling operation device of a comprehensive energy system in the second embodiment of the present invention.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
The present invention will be described below with reference to the accompanying drawings.
In a first embodiment, as shown in fig. 1, an optimization modeling operation method of an integrated energy system includes the following steps:
s1: acquiring a target information flow of a comprehensive energy system;
S2: respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
s2: and (3) adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme.
The method comprises the steps of obtaining a target information flow of a comprehensive energy system, obtaining a power model capable of describing the comprehensive energy system according to the target information flow, providing an energy flow constraint condition set in the process that an optimal operation objective function reaches an optimal value, building the optimal operation objective function, obtaining an energy flow optimal operation model according to the optimal operation objective function, the power model and the energy flow constraint condition set, and solving the energy flow optimal operation model to obtain an optimal operation scheme, wherein the optimal control of the energy flow in the comprehensive energy system is realized, and the unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system are realized by considering the connection relation and the interactive working mechanism of the information layer and the physical layer of the comprehensive energy system;
The optimization modeling operation method of the comprehensive energy system can collect information of each energy device of an energy level in the comprehensive energy system and form an information flow of the information level, perform unified modeling and quantitative analysis on the information flow and the energy flow of the comprehensive energy system, and perform optimization solving on an energy flow optimization operation model from a set of optimization operation objective functions and energy flow constraint condition sets by utilizing the technology of the information level to obtain an optimal optimization operation scheme, so that joint analysis of the information level and a physical level of the comprehensive energy system is realized, energy utilization rate is improved, economic and safe operation of the comprehensive energy system is realized, and green sustainable development is realized.
Preferably, the integrated energy system comprises an intelligent energy gateway, an integrated energy supply and demand platform, a communication manager and an integrated energy device group;
as shown in fig. 2, S1 specifically includes the following steps:
s11: collecting an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
s12: converting the device information set by the communication manager to form an original information stream;
s13: carrying out logic processing on the original information flow by utilizing the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
The comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user thermal load;
the equipment information set comprises the total output power of the distributed power generation device, the active power and the reactive power of the heat pump, the power generation power and the heat generation power of the cogeneration unit, the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device, the user electric load demand power and the user heat load demand power at each moment.
The intelligent energy gateway on the energy level collects the equipment information of each energy device to obtain an equipment information set, a communication manager is convenient to obtain a target information flow according to the equipment information set, and the target information flow is uploaded to the comprehensive energy supply and demand platform on the information level, so that the technology on the information level is convenient to obtain the optimal operation scheme of the whole comprehensive energy system.
Specifically, in this embodiment, the communication manager forms the device information set into an original information stream through an OPC protocol, and then unifies and sums the original information stream through logic processing methods such as data accumulation, subtraction, multiplication and division, integration, and the like, so as to obtain a target information stream, and uploads the target information stream to the comprehensive energy supply and demand platform in a format of a data frame for real-time analysis; the target information stream after the logic processing includes all information in the device information set.
Specifically, the distributed power generation device in this embodiment is a photovoltaic power generation device, and the energy storage device specifically includes an energy storage battery and a heat storage tank, so that the total output power of the distributed power generation device in the target information stream is specifically the total output power of the photovoltaic power generation device, and the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device specifically include the rated power storage capacity, the energy storage power and the energy releasing power of the energy storage battery, and the maximum heat storage capacity, the heat storage power and the heat releasing power of the heat storage tank; the specific structure diagram of the energy flow in the integrated energy system of this embodiment is shown in fig. 3, the specific structure diagram of the information flow in the integrated energy system is shown in fig. 4, and the integrated structure diagram of the information flow-energy flow in the integrated energy system is shown in fig. 5.
Specifically, the total output power (i.e., photovoltaic output) of the photovoltaic power generation device, the user electrical load demand power and the user thermal load demand power collected in the embodiment are shown in fig. 6, the maximum heat storage capacity of the heat storage tank is 16MWh, the rated power storage capacity of the energy storage battery is 10MWh, the active power extremum of the heat pump is 2.4MW, and the electrothermal conversion efficiency is 2.6; the maximum power of the energy storage battery and the maximum power of the energy release battery are respectively 2MW and 1.5MW.
Preferably, the power model comprises a photovoltaic power generation power model and a cogeneration power model;
as shown in fig. 7, S2 specifically includes the following steps:
s21: constructing a photovoltaic power generation power model according to the total output power of the photovoltaic power generation device, and constructing the cogeneration power model according to the generated power and the generated heat power of the cogeneration unit;
s22: obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the power generation and heat generation power of the cogeneration unit, the active power and reactive power of the heat pump, the energy storage capacity, the energy charging power and energy releasing power of the energy storage device, the user electric load demand power and the user thermal load demand power;
s23: acquiring the exchange electric quantity between the comprehensive energy system and the power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
wherein, minF is the optimized running objective function, F is the daily running cost of the comprehensive energy system, c (T) is the exchange electricity cost between the comprehensive energy system and the power grid at the moment T, T is the daily running period duration, and P exc (t) is the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P exc (t)>When 0 represents that the comprehensive energy system is in a power selling state at the time t, P is exc (t) is the sales power; when P exc (t)<When 0 represents that the comprehensive energy system is in a power purchasing state at the time t, P is exc (t) is electricity purchasing quantity; c (C) 1 (t) and C 2 (t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
s24: and constructing the energy flow optimizing operation model according to the optimizing operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set.
The power relation between the information flow and the energy flow in the whole comprehensive energy system can be obtained based on the photoelectric power generation power model and the cogeneration power model, the working conditions when the information flow and the energy flow in the comprehensive energy system can keep normal operation are limited by the energy flow constraint condition set, and then the daily operation cost of the comprehensive energy system reaches the minimum as the target of optimizing operation, so that the optimized operation objective function between the information flow and the energy flow in the whole comprehensive energy system is obtained; the energy flow optimizing operation model is constructed based on the optimizing operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set, the connection relation and the interactive working mechanism between the information layer and the physical layer of the comprehensive energy system can be fully considered, unified modeling and quantitative analysis of the information flow and the energy flow of the comprehensive energy system are realized, the follow-up obtaining of an optimal optimizing operation scheme is facilitated, the optimal control of the energy flow is realized, and the energy utilization rate is effectively improved.
Specifically, in the present embodiment S21, the expression of the photovoltaic power generation power model is specifically:
wherein P is pv (T) is the total output power of the photovoltaic power generation device at the moment T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the moment T, epsilon is the power temperature coefficient of the photovoltaic power generation device, and T w (T) is the working temperature of the photovoltaic power generation device at the moment T, T 0 The temperature is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein,and->Respectively generating electric power and heat generating power of the cogeneration unit at the time t under the ith new energy prediction scene, wherein K is the output running range of the cogeneration unit, and K is>And->Respectively being a kth electrode value point and a kth thermal extreme point in the output operation range of the cogeneration unit, < >>In order to realize the kth output coefficient of the cogeneration unit at the time t under the ith new energy prediction scene, the kth electrode value point and the kth heat extreme point are corresponding to the kth output coefficient.
The specific photovoltaic power generation power model and the cogeneration power model truly reflect the power relation between the information flow and the energy flow in the whole comprehensive energy system, and are convenient for obtaining a more accurate and reasonable energy flow optimizing operation model later.
Specifically, in this embodiment S22, the set of energy flow constraints includes a power supply balance constraint, a heat storage device constraint, and an energy storage battery constraint;
the specific formula of the power supply balance constraint condition is as follows:
wherein P is Li (t) is the stored or released power of the energy storage battery at the time t; when P Li When (t) is more than or equal to 0, representing that the energy storage battery is in a power storage state at the moment t, then P Li (t) is electric power storage; when P Li (t)<When 0 represents that the energy storage battery is in a discharging state at the time t, P is Li (t) is the release power; p (P) L (t) and P loss (t) the power demand of the consumer electric load and the network loss of the electric power system at the moment t respectively, P HP (t) and Q HP (t) is the active power and the reactive power of the heat pump at the moment t respectively, P HP (t-1) and Q HP (t-1) is the active power and the reactive power of the heat pump at the time t-1 respectively,and S is HP,max Respectively an active power extremum and an apparent power extremum, delta P of the heat pump HP And DeltaQ HP An active power ramp limit value and a reactive power ramp limit value of the heat pump respectively;
the specific formula of the heat supply balance constraint condition is as follows:
wherein,and->The heat storage power and the heat release power of the heat storage tank at the time t are respectively as follows H CHP (t) and H Dmd (t) the heat generation power of the cogeneration unit and the heat load demand power of the user at the time t respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E is re (t) is the heat storage amount of the heat storage tank at the time t, E re (t-1) is the heat storage capacity, eta of the heat storage tank at the time t-1 HP For the electrothermal conversion efficiency of the heat pump,for the heat release amount of the heat storage tank at the time t, E re-max The SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy S Limin ≤S Li (t)≤S Limax
Wherein S is Li (t) and S Li (t-1) is the SOC remaining power ratio of the energy storage battery at the time t and the SOC remaining power ratio at the time t-1 respectively, S Limax And S is Limin Respectively an upper limit and a lower limit of the SOC residual capacity ratio of the energy storage battery,and S is Li,N The self-discharge rate and rated electricity storage capacity of the energy storage battery are respectively gamma Lic And gamma Lid Respectively the charging efficiency and the discharging efficiency of the energy storage battery, delta t 1 To take a scheduling time interval of 1 hour.
The four large constraint conditions (including the power supply balance constraint condition, the heat storage equipment constraint condition and the energy storage battery constraint condition) more comprehensively and accurately limit the working conditions when the information flow and the energy flow in the comprehensive energy system can keep normal operation, so that the finally obtained optimized operation scheme is optimal, the operation efficiency and the optimization rate of the comprehensive energy system can be further improved on the basis of ensuring the normal operation of the comprehensive energy system, and the energy utilization rate is further effectively improved.
Specifically, in the power supply balance constraint condition, the active power extremum of the heat pump2.4MW, apparent power extremum S HP,max An active power ramp limit value DeltaP of 2.4MVA HP And reactive power ramp limit Δq HP 2.4MW and 1.6Mvar, respectively; in the heat storage device constraint condition, the maximum heat storage capacity E of the heat storage tank re-max 16MWh; in the constraint condition of the energy storage battery, the self-discharge rate of the energy storage battery is +.>And rated power storage S Li,N Respectively 1.5%/montath and 10MWh, and the charging efficiency gamma of the energy storage battery Lic And discharge efficiency gamma Lid Are all 0.95, and the upper limit S of the SOC residual electric quantity ratio of the energy storage battery Limax And a lower limit S Limin 1 and 0, respectively.
Specifically, in the optimized running objective function of the embodiment, the electricity purchase price C of the integrated energy system at the time t 1 (t) is 0.3 yuan/kWh, and the electricity purchasing price C of the comprehensive energy system at the time t 2 (t) implementing a step electricity price, specifically: 7:00-22: electricity price of 00 period is 0.7 yuan/kWh, and other period is 0.3 yuan/kWh.
Preferably, the optimized operation scheme comprises an optimized energy flow control strategy and an electricity purchasing plan;
as shown in fig. 8, S3 specifically includes the following steps:
s31: respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
S32: based on the mixed integer linear programming method, in the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
s33: the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication manager to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electric load and the user thermal load.
The flow direction of the generated energy generated by the photovoltaic power generation device and the flow direction of the heat generated by the cogeneration unit can be determined through setting the first working mode of the photovoltaic power generation device and the second working mode of the cogeneration unit respectively, the flow direction of the generated energy generated by the photovoltaic power generation device and the flow direction of the heat generated by the cogeneration unit are further designated, the optimal operation control strategy of the energy flow of the comprehensive energy system is further designated, the optimal electricity purchasing plan of the comprehensive energy system under the optimal operation control strategy is determined, and after the optimal operation control strategy is obtained, in order to ensure that the energy flow of the comprehensive energy system can operate according to the optimal energy flow control strategy, the optimal energy flow control strategy is respectively issued to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electric load and the user heat load through the comprehensive energy supply and demand platform, the optimal control of the energy flow is truly realized, the energy loss is effectively reduced, the energy utilization rate is improved, and the economic and safe operation of the comprehensive energy system is realized.
The mixed integer linear programming method is one of integer linear programming models, and when only one part of decision variables in the model require non-negative integers and the other part of decision variables can take non-negative real numbers, the mixed integer linear programming is realized; the specific operation steps of the mixed integer linear programming method are the prior art, and specific details are not described herein.
Specifically, the integrated energy system is specifically a grid-connected integrated energy system, and the first working mode and the second working mode both specifically adopt working modes of spontaneous use and residual surfing.
When the heat pump also adopts a working mode of self-power-consumption and surplus internet surfing, the generated energy generated by the photovoltaic power generation device is preferentially supplied to a user electric load, and if redundant energy exists, the redundant energy is preferentially stored in an electric storage device such as an energy storage battery; when the cogeneration unit adopts a working mode of spontaneous self-use and surplus internet surfing, heat energy generated by the cogeneration unit is preferentially supplied to a user heat load, if surplus heat is preferentially stored in heat storage equipment such as a heat storage tank, and if the energy storage tank cannot consume all the energy, the surplus energy is sold to a power grid, and the surplus heat energy is discarded; in addition, when the heat pump also adopts a working mode of self-use and surplus internet surfing, heat energy generated by the heat pump is preferentially supplied to a user thermal load, if surplus heat is preferentially stored in heat storage equipment such as a heat storage tank, and if the energy storage tank cannot consume all the energy, surplus electric energy is sold to a power grid, and the surplus heat energy is discarded; on the basis of the energy flow direction, if the power generation/heating equipment generates power and heat quantity which can not supply the electric/thermal load demands of users, the comprehensive energy system purchases power to the power grid, part of the comprehensive energy system directly meets the electric load demands of the users, and part of the comprehensive energy system converts the electric energy into heat energy through the heat pump to meet the thermal load demands of the users.
Specifically, in the photovoltaic-load scenario shown in fig. 6, according to steps S1 to S3, an energy flow optimization control strategy and a power purchase and selling plan are obtained, an electricity price-power purchase curve (i.e., power purchase and selling plan) of the integrated energy system is shown in fig. 9, and after the energy flow optimization control strategy is adopted, an obtained electricity/heat energy storage SOC remaining capacity ratio curve is shown in fig. 10, and a power curve of the heat pump/energy storage battery is shown in fig. 11; the daily operation cost of the final comprehensive energy system and the power grid is 17872 yuan, and according to the electricity/heat energy storage SOC residual capacity ratio curve in fig. 10 and the electricity purchasing plan in fig. 9, the comprehensive energy system can purchase 33.4MWh of electric energy in a large quantity in a valley period, the electricity purchasing in a peak period only purchases 11.2MWh of electric energy, the comprehensive energy system can meet the electricity load requirement and the heat load requirement of a user by consuming the electric quantity of an energy storage battery and the heat of a heat storage tank in the peak period, and the SOC capacity of the energy storage equipment can recover to an initial value by purchasing a small quantity until the period of one day is finished, so that the operation cost of the comprehensive energy system is greatly reduced.
In a second embodiment, as shown in fig. 12, an optimizing modeling operation device of a comprehensive energy system is applied to an optimizing modeling operation method of a comprehensive energy system in the first embodiment, and includes an information flow obtaining module, an energy flow modeling module and an optimizing solving module;
The information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
and the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme.
The optimization modeling operation device of the integrated energy system formed by the modules can collect information of each energy device of an energy level in the integrated energy system and form information flow of the information level, perform unified modeling and quantitative analysis on the information flow and the energy flow of the integrated energy system, perform optimization solving on an energy flow optimization operation model from a set of optimization operation objective functions and energy flow constraint condition sets by utilizing the technology of the information level to obtain an optimal optimization operation scheme, realize joint analysis of the information level and a physical level of the integrated energy system, perform optimal control on the energy flow, improve the energy utilization rate, realize economic and safe operation of the integrated energy system, and realize green sustainable development.
Preferably, the integrated energy system comprises an intelligent energy gateway, an integrated energy supply and demand platform, a communication manager and an integrated energy device group;
the information flow obtaining module is specifically configured to:
collecting an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
converting the device information set by the communication manager to form an original information stream;
carrying out logic processing on the original information flow by utilizing the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user thermal load;
the equipment information set comprises the total output power of the distributed power generation device, the active power and the reactive power of the heat pump, the power generation power and the heat generation power of the cogeneration unit, the energy storage capacity, the energy charging power and the energy releasing power of the energy storage device, the user electric load demand power and the user heat load demand power at each moment.
Preferably, the distributed power generation equipment is specifically a photovoltaic power generation device; the power model comprises a photovoltaic power generation power model and a cogeneration power model;
The energy flow modeling module is specifically configured to:
a photovoltaic power generation power model is built according to the total output power of the photovoltaic power generation device, and a cogeneration power model is built according to the generated power and the generated heat power of the cogeneration unit;
obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the power generation and heat generation power of the cogeneration unit, the active power and reactive power of the heat pump, the energy storage capacity, the energy charging power and energy releasing power of the energy storage device, the user electric load demand power and the user thermal load demand power;
acquiring the exchange electric quantity between the comprehensive energy system and the power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
wherein, minF is the optimized running objective function, F is the daily running cost of the comprehensive energy system, c (T) is the exchange electricity cost between the comprehensive energy system and the power grid at the moment T, T is the daily running period duration, and P exc (t) is the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P exc (t)>When 0 represents that the comprehensive energy system is in a power selling state at the time t, P is exc (t) is the sales power; when P exc (t)<When 0 represents that the comprehensive energy system is in a power purchasing state at the time t, P is exc (t) is electricity purchasing quantity; c (C) 1 (t) and C 2 (t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
and constructing the energy flow optimizing operation model according to the optimizing operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set.
Preferably, the expression of the photovoltaic power generation power model is specifically:
wherein P is pv (T) is the total output power of the photovoltaic power generation device at the moment T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the moment T, epsilon is the power temperature coefficient of the photovoltaic power generation device, and T w (T) is the working temperature of the photovoltaic power generation device at the moment T, T 0 The temperature is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein,and->Respectively generating electric power and heat generating power of the cogeneration unit at the time t under the ith new energy prediction scene, wherein K is the output running range of the cogeneration unit, and K is>And->Respectively being a kth electrode value point and a kth thermal extreme point in the output operation range of the cogeneration unit, < > >In order to realize the kth output coefficient of the cogeneration unit at the time t under the ith new energy prediction scene, the kth electrode value point and the kth heat extreme point are corresponding to the kth output coefficient.
Preferably, the energy storage device specifically comprises an energy storage battery and a heat storage tank; the energy flow constraint condition set comprises a power supply balance constraint condition, a heat storage equipment constraint condition and an energy storage battery constraint condition;
the specific formula of the power supply balance constraint condition is as follows:
wherein P is Li (t) is the stored or released power of the energy storage battery at the time t; when P Li When (t) is more than or equal to 0, representing that the energy storage battery is in a power storage state at the moment t, then P Li (t) is electric power storage; when P Li (t)<When 0 represents that the energy storage battery is in a discharging state at the time t, P is Li (t) is the release power; p (P) L (t) and P loss (t) the power demand of the consumer electric load and the network loss of the electric power system at the moment t respectively, P HP (t) and Q HP (t) is the active power and the reactive power of the heat pump at the moment t respectively, P HP (t-1) and Q HP (t-1) is the active power and the reactive power of the heat pump at the time t-1 respectively,and S is HP,max Respectively an active power extremum and an apparent power extremum, delta P of the heat pump HP And DeltaQ HP An active power ramp limit value and a reactive power ramp limit value of the heat pump respectively;
the specific formula of the heat supply balance constraint condition is as follows:
wherein the method comprises the steps of，And->The heat storage power and the heat release power of the heat storage tank at the time t are respectively as followsH CHP (t) and H Dmd (t) the heat generation power of the cogeneration unit and the heat load demand power of the user at the time t respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E is re (t) is the heat storage amount of the heat storage tank at the time t, E re (t-1) is the heat storage capacity, eta of the heat storage tank at the time t-1 HP For the electrothermal conversion efficiency of the heat pump,for the heat release amount of the heat storage tank at the time t, E re-max The SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy S Limin ≤S Li (t)≤S Limax
Wherein S is Li (t) and S Li (t-1) is the SOC remaining power ratio of the energy storage battery at the time t and the SOC remaining power ratio at the time t-1 respectively, S Limax And S is Limin Respectively is the instituteAn upper limit and a lower limit of the SOC remaining capacity of the energy storage battery,and S is Li,N The self-discharge rate and rated electricity storage capacity of the energy storage battery are respectively gamma Lic And gamma Lid Respectively the charging efficiency and the discharging efficiency of the energy storage battery, delta t 1 To take a scheduling time interval of 1 hour.
Preferably, the optimized operation scheme comprises an optimized energy flow control strategy and an electricity purchasing plan;
the optimization solution model is specifically used for:
respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
based on the mixed integer linear programming method, in the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication manager to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electric load and the user thermal load.
Preferably, the integrated energy system is specifically a grid-connected integrated energy system, and the first working mode and the second working mode are both specifically spontaneous and self-used and allowance internet working modes.
The third embodiment is based on the first embodiment and the second embodiment, and the present embodiment further discloses an optimizing modeling operation device of the integrated energy system, which includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the specific steps of S1 to S3 are implemented when the computer program runs.
The information of each energy device of the energy level in the comprehensive energy system can be acquired and the information flow of the information level can be formed through the computer program stored in the memory and running on the processor, unified modeling and quantitative analysis are carried out on the information flow and the energy flow of the comprehensive energy system, the energy flow optimization running model can be optimized and solved from a set of optimization running objective functions and energy flow constraint condition sets by utilizing the technology of the information level, the optimal optimization running scheme is obtained, the joint analysis of the information level and the physical level of the comprehensive energy system is realized, the energy utilization rate is improved, the economic and safe running of the comprehensive energy system is realized, and the green sustainable development is realized.
The present embodiment also provides a computer storage medium having at least one instruction stored thereon, which when executed, implements the specific steps of S1 to S3.
By executing a computer storage medium containing at least one instruction, the information of each energy device of the energy level in the comprehensive energy system can be acquired, the information flow of the information level is formed, the information flow and the energy flow of the comprehensive energy system are subjected to unified modeling and quantitative analysis, the energy flow optimization operation model can be optimally solved from a set of optimization operation objective functions and energy flow constraint condition sets by utilizing the technology of the information level, an optimal optimization operation scheme is obtained, the joint analysis of the information level and the physical level of the comprehensive energy system is realized, the energy flow is optimally controlled, the energy utilization rate is improved, the economic and safe operation of the comprehensive energy system is realized, and the green sustainable development is realized.
Details of the embodiment I and the detailed descriptions of FIGS. 1 to 11 are not repeated here.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.

Claims (6)

1. The optimized modeling operation method of the comprehensive energy system is characterized by comprising the following steps of:
Acquiring a target information flow of a comprehensive energy system;
respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
adopting a mixed integer linear programming method to carry out optimization solution on the energy flow optimization operation model to obtain an optimization operation scheme;
the comprehensive energy system comprises an intelligent energy gateway, a comprehensive energy supply and demand platform, a communication manager and a comprehensive energy device group;
the method for acquiring the target information stream specifically comprises the following steps:
collecting an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
converting the device information set by the communication manager to form an original information stream;
carrying out logic processing on the original information flow by utilizing the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user thermal load;
The equipment information set comprises total output power of the distributed power generation device, active power and reactive power of the heat pump, power generation power and heat generation power of the cogeneration unit, energy storage capacity, energy charging power and energy releasing power of the energy storage device, user electric load demand power and user heat load demand power at each moment;
the distributed power generation equipment is specifically a photovoltaic power generation device; the power model comprises a photovoltaic power generation power model and a cogeneration power model;
the energy flow optimization operation model of the comprehensive energy system is constructed by the following steps:
a photovoltaic power generation power model is built according to the total output power of the photovoltaic power generation device, and a cogeneration power model is built according to the generated power and the generated heat power of the cogeneration unit;
obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the power generation and heat generation power of the cogeneration unit, the active power and reactive power of the heat pump, the energy storage capacity, the energy charging power, the energy releasing power, the user electric load demand power and the user heat load demand power of the energy storage device;
Acquiring the exchange electric quantity between the comprehensive energy system and the power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
wherein, minF is the optimized running objective function, F is the daily running cost of the comprehensive energy system, c (T) is the exchange electricity cost between the comprehensive energy system and the power grid at the moment T, T is the daily running period duration, and P exc (t) is the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P exc (t)>When 0 represents that the comprehensive energy system is in a power selling state at the time t, P is exc (t) is the sales power; when P exc (t)<When 0 represents that the comprehensive energy system is in a power purchasing state at the time t, P is exc (t) is electricity purchasing quantity; c (C) 1 (t) and C 2 (t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
constructing the energy flow optimizing operation model according to the optimizing operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set;
the expression of the photovoltaic power generation power model is specifically as follows:
wherein P is pv (T) is the total output power of the photovoltaic power generation device at the moment T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the moment T, epsilon is the power temperature coefficient of the photovoltaic power generation device, and T w (T) is the working temperature of the photovoltaic power generation device at the moment T, T 0 The temperature is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein,and->Respectively generating electric power and heat generating power of the cogeneration unit at the time t under the ith new energy prediction scene, wherein K is the output running range of the cogeneration unit, and K is>And->Respectively being a kth electrode value point and a kth thermal extreme point in the output operation range of the cogeneration unit, < >>In order to realize the kth output system of the cogeneration unit at the time t under the ith new energy prediction sceneThe number of the electrodes is that the kth electrode value point and the kth thermal extreme point are corresponding to the kth output coefficient;
the energy storage device specifically comprises an energy storage battery and a heat storage tank; the energy flow constraint condition set comprises a power supply balance constraint condition, a heat storage equipment constraint condition and an energy storage battery constraint condition;
the specific formula of the power supply balance constraint condition is as follows:
wherein P is Li (t) is the stored or released power of the energy storage battery at the time t; when P Li When (t) is more than or equal to 0, representing that the energy storage battery is in a power storage state at the moment t, then P Li (t) is electric power storage; when P Li (t)<When 0 represents that the energy storage battery is in a discharging state at the time t, P is Li (t) is the release power; p (P) L (t) and P loss (t) the power demand of the consumer electric load and the network loss of the electric power system at the moment t respectively, P HP (t) and Q HP (t) is the active power and the reactive power of the heat pump at the moment t respectively, P HP (t-1) and Q HP (t-1) is the active power and the reactive power of the heat pump at the time t-1 respectively,and S is HP,max Respectively an active power extremum and an apparent power extremum, delta P of the heat pump HP And DeltaQ HP An active power ramp limit value and a reactive power ramp limit value of the heat pump respectively;
the specific formula of the heat supply balance constraint condition is as follows:
wherein,and->The heat storage power and the heat release power of the heat storage tank at the time t are respectively as followsH CHP (t) and H Dmd (t) the heat generation power of the cogeneration unit and the heat load demand power of the user at the time t respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E is re (t) is the heat storage amount of the heat storage tank at the time t, E re (t-1) is the heat storage capacity, eta of the heat storage tank at the time t-1 HP For the electrothermal conversion efficiency of the heat pump,for the heat release amount of the heat storage tank at the time t, E re-max The SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
The specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy S Limin ≤S Li (t)≤S Limax
Wherein S is Li (t) and S Li (t-1) is the SOC remaining power ratio of the energy storage battery at the time t and the SOC remaining power ratio at the time t-1 respectively, S Limax And S is Limin Respectively an upper limit and a lower limit of the SOC residual capacity ratio of the energy storage battery,and S is Li,N The self-discharge rate and rated electricity storage capacity of the energy storage battery are respectively gamma Lic And gamma Lid Respectively the charging efficiency and the discharging efficiency of the energy storage battery, delta t 1 To take a scheduling time interval of 1 hour.
2. The method for optimizing modeling operation of an integrated energy system of claim 1, wherein the optimized operation scheme comprises optimizing an energy flow control strategy and an electricity purchase and sales plan;
the method for obtaining the optimized operation scheme specifically comprises the following steps:
respectively setting a first working mode of the photovoltaic power generation device and a second working mode of the cogeneration unit;
based on the mixed integer linear programming method, in the first working mode and the second working mode, carrying out optimization solution on the energy flow optimization operation model to obtain the optimized energy flow control strategy and the electricity purchasing and selling plan;
the comprehensive energy supply and demand platform utilizes the intelligent energy gateway and the communication manager to respectively issue the optimized energy flow control strategy to the photovoltaic power generation device, the energy storage device, the heat pump, the cogeneration unit, the user electric load and the user thermal load.
3. The method for optimizing and modeling an integrated energy system according to claim 2, wherein the integrated energy system is a grid-connected integrated energy system, and the first working mode and the second working mode are both self-service and surplus internet working modes.
4. An optimizing modeling operation device of a comprehensive energy system is characterized by being applied to the optimizing modeling operation method of the comprehensive energy system according to any one of claims 1 to 3, and comprising an information flow acquisition module, an energy flow modeling module and an optimizing solving module;
the information flow acquisition module is used for acquiring a target information flow of the comprehensive energy system;
the energy flow modeling module is used for respectively obtaining a power model and an energy flow constraint condition set of the comprehensive energy system according to the target information flow; constructing an optimized operation objective function of the comprehensive energy system, and constructing an energy flow optimized operation model of the comprehensive energy system according to the optimized operation objective function, the power model and the energy flow constraint condition set;
the optimization solving module is used for carrying out optimization solving on the energy flow optimization operation model by adopting a mixed integer linear programming method to obtain an optimization operation scheme;
The comprehensive energy system comprises an intelligent energy gateway, a comprehensive energy supply and demand platform, a communication manager and a comprehensive energy device group;
the method for acquiring the target information stream specifically comprises the following steps:
collecting an equipment information set of the comprehensive energy device group by using the intelligent energy gateway;
converting the device information set by the communication manager to form an original information stream;
carrying out logic processing on the original information flow by utilizing the communication manager to obtain the target information flow and uploading the target information flow to the comprehensive energy supply and demand platform;
the comprehensive energy device group comprises a distributed power generation device, an energy storage device, a heat pump, a cogeneration unit, a user electric load and a user thermal load;
the equipment information set comprises total output power of the distributed power generation device, active power and reactive power of the heat pump, power generation power and heat generation power of the cogeneration unit, energy storage capacity, energy charging power and energy releasing power of the energy storage device, user electric load demand power and user heat load demand power at each moment;
the distributed power generation equipment is specifically a photovoltaic power generation device; the power model comprises a photovoltaic power generation power model and a cogeneration power model;
The energy flow optimization operation model of the comprehensive energy system is constructed by the following steps:
a photovoltaic power generation power model is built according to the total output power of the photovoltaic power generation device, and a cogeneration power model is built according to the generated power and the generated heat power of the cogeneration unit;
obtaining the energy flow constraint condition set according to the total output power of the photovoltaic power generation device, the power generation and heat generation power of the cogeneration unit, the active power and reactive power of the heat pump, the energy storage capacity, the energy charging power, the energy releasing power, the user electric load demand power and the user heat load demand power of the energy storage device;
acquiring the exchange electric quantity between the comprehensive energy system and the power grid, and constructing the optimized operation objective function according to the exchange electric quantity;
the specific formula of the optimized operation objective function is as follows:
wherein, minF is the optimized running objective function, F is the daily running cost of the comprehensive energy system, c (T) is the exchange electricity cost between the comprehensive energy system and the power grid at the moment T, T is the daily running period duration, and P exc (t) is the exchange electric quantity between the comprehensive energy system and the power grid at the moment t; when P exc (t)>When 0 represents that the comprehensive energy system is in a power selling state at the time t, P is exc (t) is the sales power; when P exc (t)<When 0 represents that the comprehensive energy system is in a power purchasing state at the time t, P is exc (t) is electricity purchasing quantity; c (C) 1 (t) and C 2 (t) the selling price and the purchasing price of the comprehensive energy system at the time t are respectively;
constructing the energy flow optimizing operation model according to the optimizing operation objective function, the photovoltaic power generation power model, the cogeneration power model and the energy flow constraint condition set;
the expression of the photovoltaic power generation power model is specifically as follows:
wherein P is pv (T) is the total output power of the photovoltaic power generation device at the moment T, eta is the solar radiation conversion efficiency of the photovoltaic power generation device, S (T) is the solar radiation intensity at the moment T, epsilon is the power temperature coefficient of the photovoltaic power generation device, and T w (T) is the working temperature of the photovoltaic power generation device at the moment T, T 0 The temperature is the standard working condition temperature;
the expression of the cogeneration power model is specifically as follows:
wherein,and->Respectively generating electric power and heat generating power of the cogeneration unit at the time t under the ith new energy prediction scene, wherein K is the output running range of the cogeneration unit, and K is >And->Respectively a kth electrode value point and a kth heat in the output operation range of the cogeneration unitExtreme point (S)>In the ith new energy prediction scene, the kth output coefficient of the cogeneration unit at the t moment, wherein the kth electrode value point and the kth heat extremum point are corresponding to the kth output coefficient;
the energy storage device specifically comprises an energy storage battery and a heat storage tank; the energy flow constraint condition set comprises a power supply balance constraint condition, a heat storage equipment constraint condition and an energy storage battery constraint condition;
the specific formula of the power supply balance constraint condition is as follows:
wherein P is Li (t) is the stored or released power of the energy storage battery at the time t; when P Li When (t) is more than or equal to 0, representing that the energy storage battery is in a power storage state at the moment t, then P Li (t) is electric power storage; when P Li (t)<When 0 represents that the energy storage battery is in a discharging state at the time t, P is Li (t) is the release power; p (P) L (t) and P loss (t) the power demand of the consumer electric load and the network loss of the electric power system at the moment t respectively, P HP (t) and Q HP (t) is the active power and the reactive power of the heat pump at the moment t respectively, P HP (t-1) and Q HP (t-1) is the active power and the reactive power of the heat pump at the time t-1 respectively, And S is HP,max Respectively an active power extremum and an apparent power extremum, delta P of the heat pump HP And DeltaQ HP An active power ramp limit value and a reactive power ramp limit value of the heat pump respectively;
the specific formula of the heat supply balance constraint condition is as follows:
wherein,and->The heat storage power and the heat release power of the heat storage tank at the time t are respectively as followsH CHP (t) and H Dmd (t) the heat generation power of the cogeneration unit and the heat load demand power of the user at the time t respectively;
the specific formula of the constraint condition of the heat storage equipment is as follows:
wherein E is re (t) is the heat storage amount of the heat storage tank at the time t, E re (t-1) is the heat storage capacity, eta of the heat storage tank at the time t-1 HP For the electrothermal conversion efficiency of the heat pump,for the heat release amount of the heat storage tank at the time t, E re-max The SOC (t) is the percentage of the residual heat of the heat storage tank at the time t to the maximum heat storage capacity;
the specific formula of the constraint condition of the energy storage battery is as follows:
and satisfy S Limin ≤S Li (t)≤S Limax
Wherein S is Li (t) and S Li (t-1) is the SOC remaining power ratio of the energy storage battery at the time t and the SOC remaining power ratio at the time t-1 respectively, S Limax And S is Limin Respectively an upper limit and a lower limit of the SOC residual capacity ratio of the energy storage battery, And S is Li,N The self-discharge rate and rated electricity storage capacity of the energy storage battery are respectively gamma Lic And gamma Lid Respectively the charging efficiency and the discharging efficiency of the energy storage battery, delta t 1 To take a scheduling time interval of 1 hour.
5. An optimised modelling operating device for an integrated energy system, comprising a processor, a memory and a computer program stored in the memory and operable on the processor, the computer program when run to carry out the method steps of any of claims 1 to 3.
6. A computer storage medium, the computer storage medium comprising: at least one instruction which, when executed, implements the method steps of any one of claims 1 to 3.
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