Situation awareness-based regional integrated energy system optimization scheduling method and device, terminal equipment and storage medium

Abstract

The invention discloses a situation awareness-based regional integrated energy system optimization scheduling method and apparatus, a terminal device and a storage medium. The method comprises the steps of constructing an energy hub model of a regional integrated energy system; acquiring operation parameters of a gas turbine, a photovoltaic cell, an absorption refrigerator, an electric refrigerator, a gas boiler, a waste heat boiler, a storage battery and heat energy storage equipment of the energy hub model; according to the operation parameters and the energy hub model, with the purpose of minimizing the comprehensive operation cost of the regional comprehensive energy system, constructing a regional comprehensive energy system optimization scheduling model; solving the optimal scheduling model of the regional integrated energy system to generate an optimal scheduling strategy of the regional integrated energy system; and the regional integrated energy system is scheduled according to the optimized scheduling strategy. By implementing the method, the comprehensiveness of feature information analysis of the main equipment of the regional integrated energy system can be improved, and the accuracy of output regulation and control of the main equipment of the regional integrated energy system is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy system optimization and scheduling, and in particular to a regional integrated energy system optimization and scheduling method, device, terminal equipment and storage medium based on situation awareness. Background Art

[0002] Due to the significant randomness, intermittency and volatility of the output of renewable energy units, when the penetration rate of renewable energy units reaches a high proportion, whether the output of renewable energy units can be accurately regulated will have a significant impact on the safe and stable operation of the energy system and the efficient management of the demand side. The existing technology lacks targeted analysis of the main equipment in the energy system when regulating the output of renewable energy units, resulting in incomplete analysis of the characteristic information of the main equipment, and then resulting in a lack of accuracy in the output regulation of each device in the energy system. In order to make up for the problem of inaccurate output regulation of equipment caused by incomplete information acquisition, it is urgent to conduct a comprehensive analysis of the main equipment in the energy system and optimize the scheduling of the energy system to improve the accuracy of regulation. Summary of the invention

[0003] The embodiments of the present invention provide a method, apparatus, terminal device and storage medium for optimizing and scheduling a regional integrated energy system based on situational awareness, which can improve the comprehensiveness of characteristic information analysis of major equipment in the regional integrated energy system, thereby improving the accuracy of output regulation of major equipment in the regional integrated energy system.

[0004] An embodiment of the present invention provides a method for optimizing and scheduling a regional integrated energy system based on situation awareness, comprising:

[0005] Constructing an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network;

[0006] Obtaining basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters;

[0007] According to the basic operating parameters and energy hub model, an optimal dispatching model of the regional integrated energy system is constructed with the goal of minimizing the comprehensive operating cost of the regional integrated energy system;

[0008] Solving the regional integrated energy system optimization scheduling model to generate an optimization scheduling strategy for the regional integrated energy system when the comprehensive operating cost of the regional integrated energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank, and heat storage state of the cold storage tank;

[0009] The regional integrated energy system is dispatched using the optimized dispatching strategy.

[0010] Further, the gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate;

[0011] The photovoltaic cell operating parameters include: solar radiation, solar incident angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency;

[0012] The absorption chiller operating parameters include: thermal coefficient, specific enthalpy of hot steam, specific enthalpy of condensed water, self-consumption rate of cold storage tank energy, heat storage efficiency of cold storage tank, heat storage power of cold storage tank, heat release efficiency of cold storage tank and heat release power of cold storage tank;

[0013] The operating parameters of the electric refrigerator include the cooling coefficient;

[0014] The gas boiler operating parameters include the efficiency of the gas boiler;

[0015] The waste heat boiler operating parameters include the waste heat boiler efficiency and the heat exchange efficiency of the heat exchange device;

[0016] The battery operating parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity;

[0017] The operating parameters of the thermal energy storage equipment include: the energy self-consumption rate of the heat storage tank, the heat storage efficiency of the heat storage tank, the heat storage power of the heat storage tank and the heat release power of the heat storage tank.

[0018] Furthermore, based on the basic operating parameters and the energy hub model, with the goal of minimizing the comprehensive operating cost of the regional integrated energy system, a regional integrated energy system optimization scheduling model is constructed, including:

[0019] According to the gas turbine operating parameters, photovoltaic cell operating parameters, absorption chiller operating parameters, electric chiller operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters, a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model are constructed;

[0020] Based on the gas turbine operation model, photovoltaic cell operation model, absorption chiller operation model, electric chiller operation model, gas boiler operation model, waste heat boiler operation model, heat exchange device operation model, battery operation model, heat storage tank operation model, cold storage tank operation model and energy hub model, a regional integrated energy system optimization scheduling model is constructed.

[0021] Furthermore, it also includes:

[0022] Obtaining the distribution terminal parameters of the area corresponding to the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminal to be installed, and the unit installation cost of each terminal type;

[0023] According to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost corresponding to the load supply network;

[0024] Solving the regional terminal configuration model to generate a terminal configuration plan for the corresponding area of ​​the load supply network when the terminal investment cost and the terminal operation and maintenance cost are comprehensively minimized;

[0025] The terminal configuration scheme is used to adjust the layout of distribution terminals in the corresponding area of ​​the load supply network.

[0026] Based on the above method embodiment, the present invention provides a corresponding device embodiment;

[0027] An embodiment of the present invention provides a regional integrated energy system optimization scheduling device based on situation awareness, including: an energy hub model construction module, a data acquisition module, an optimization scheduling model construction module, an optimization scheduling model solving module and a scheduling module;

[0028] The energy hub model construction module is used to construct an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network;

[0029] The data acquisition module is used to acquire basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters;

[0030] The optimization scheduling model construction module is used to construct an optimization scheduling model for the regional comprehensive energy system based on the basic operating parameters and the energy hub model with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system;

[0031] The optimization scheduling model solving module is used to solve the optimization scheduling model of the regional comprehensive energy system to generate an optimization scheduling strategy for the regional comprehensive energy system when the comprehensive operation cost of the regional comprehensive energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank and heat storage state of the cold storage tank;

[0032] The scheduling module is used to schedule the regional integrated energy system using the optimized scheduling strategy.

[0033] Further, the gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate;

[0034] The photovoltaic cell operating parameters include: solar radiation, solar incident angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency;

[0035] The absorption chiller operating parameters include: thermal coefficient, specific enthalpy of hot steam, specific enthalpy of condensed water, self-consumption rate of cold storage tank energy, heat storage efficiency of cold storage tank, heat storage power of cold storage tank, heat release efficiency of cold storage tank and heat release power of cold storage tank;

[0036] The operating parameters of the electric refrigerator include the cooling coefficient;

[0037] The gas boiler operating parameters include the efficiency of the gas boiler;

[0038] The waste heat boiler operating parameters include the waste heat boiler efficiency and the heat exchange efficiency of the heat exchange device;

[0039] The battery operating parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity;

[0040] The operating parameters of the thermal energy storage equipment include: the energy self-consumption rate of the heat storage tank, the heat storage efficiency of the heat storage tank, the heat storage power of the heat storage tank and the heat release power of the heat storage tank.

[0041] Furthermore, based on the basic operating parameters and the energy hub model, with the goal of minimizing the comprehensive operating cost of the regional integrated energy system, a regional integrated energy system optimization scheduling model is constructed, including:

[0042] According to the gas turbine operating parameters, photovoltaic cell operating parameters, absorption chiller operating parameters, electric chiller operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters, a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model are constructed;

[0043] Based on the gas turbine operation model, photovoltaic cell operation model, absorption chiller operation model, electric chiller operation model, gas boiler operation model, waste heat boiler operation model, heat exchange device operation model, battery operation model, heat storage tank operation model, cold storage tank operation model and energy hub model, a regional integrated energy system optimization scheduling model is constructed.

[0044] Furthermore, it also includes a terminal layout module;

[0045] The terminal layout module is used to obtain the distribution terminal parameters of the corresponding area of ​​the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminal to be installed, and the unit installation cost of each terminal type;

[0046] According to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost corresponding to the load supply network;

[0047] Solving the regional terminal configuration model to generate a terminal configuration plan for the corresponding area of ​​the load supply network when the terminal investment cost and the terminal operation and maintenance cost are comprehensively minimized;

[0048] The terminal configuration scheme is used to adjust the layout of distribution terminals in the corresponding area of ​​the load supply network.

[0049] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a regional integrated energy system optimization and scheduling method described in the above-mentioned embodiment of the invention.

[0050] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a regional integrated energy system optimization scheduling method described in the above-mentioned invention embodiment.

[0051] The following beneficial effects are achieved by implementing the present invention:

[0052] The present invention provides a method, device, terminal device and storage medium for optimizing and scheduling a regional comprehensive energy system based on situation awareness. By constructing an energy hub model of the regional comprehensive energy system, the energy supply network, energy exchange network and load supply network of the regional comprehensive energy system are determined. After obtaining basic operating parameters such as gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters based on the energy exchange network, based on these basic operating parameters and the energy hub model, the regional comprehensive energy system optimization and scheduling method is constructed with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system. The optimization scheduling model is constructed, and then the optimization scheduling model of the regional comprehensive energy system is solved to generate the optimization scheduling strategy of the regional comprehensive energy system when the comprehensive operation cost of the regional comprehensive energy system is minimized; wherein, the optimization scheduling strategy includes: the natural gas consumption per unit time of the gas turbine, the calorific value of natural gas, the power generation power of photovoltaic cells, the input hot steam flow of the absorption refrigerator, the input electric power of the electric refrigerator, the amount of fuel consumed by the gas boiler, the input thermal energy power of the waste heat boiler, the input thermal power of the heat exchange device, the battery storage state, the heat storage state of the heat storage tank and the heat storage state of the cold storage tank, and then the various parameters in the solved optimization scheduling strategy are comprehensively optimized for each device in the regional comprehensive energy system. By constructing the energy hub model of the regional comprehensive energy system and obtaining the basic operating parameters of the main equipment in the regional comprehensive energy system, the comprehensiveness of the characteristic information analysis of the main equipment of the regional comprehensive energy system is improved, thereby improving the accuracy of the output regulation of the main equipment of the regional comprehensive energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a method for optimizing and scheduling a regional integrated energy system based on situation awareness provided by one embodiment of the present invention.

[0054] Figure 2 It is a schematic diagram of an energy hub model provided by an embodiment of the present invention.

[0055] Figure 3 It is a structural schematic diagram of a regional integrated energy system optimization and scheduling device based on situation awareness provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] like Figure 1 As shown, a method for optimizing and scheduling a regional integrated energy system according to an embodiment of the present invention includes:

[0058] Step S1: constructing an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network;

[0059] Step S2: Obtaining basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters;

[0060] Step S3: Based on the basic operating parameters and the energy hub model, an optimization scheduling model of the regional integrated energy system is constructed with the goal of minimizing the comprehensive operating cost of the regional integrated energy system;

[0061] Step S4: solving the regional integrated energy system optimization scheduling model to generate an optimization scheduling strategy for the regional integrated energy system when the comprehensive operating cost of the regional integrated energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank, and heat storage state of the cold storage tank;

[0062] Step S5: Dispatching the regional integrated energy system using the optimized dispatching strategy.

[0063] For step S1, construct Figure 2The energy hub model of the regional integrated energy system shown in FIG. 1 mainly includes an energy supply network (corresponding to the input layer), an energy exchange network (corresponding to the conversion layer) and a load supply network (corresponding to the output layer). The construction of the energy hub model can abstractly describe the multi-energy system of the regional integrated energy system as a network model with multiple input ports and multiple output ports. In the energy hub model, cold, heat, electricity, gas and other energies are coordinated, distributed, stored and converted internally. The energy supply network mainly includes power grid, photovoltaic and natural gas. The energy supply network is connected to the energy grid to obtain the above energy supply and is used to provide energy sources to the energy exchange network. The energy exchange network is mainly transformed from the main equipment contained in the regional integrated energy system. The main equipment contained in the regional integrated energy system includes gas turbines, waste heat boilers, electric energy storage, electric refrigerators, absorption refrigerators and thermal energy storage. Therefore, the energy exchange network also includes gas turbines, waste heat boilers, electric energy storage, electric refrigerators, absorption refrigerators and thermal energy storage. The load supply network mainly includes electric loads, cold loads and thermal loads output by the energy exchange network. The electrical load, cooling load and heating load output from the load supply network are used to transmit to various users in the regional integrated energy system.

[0064] It should be added that the input and output expressions of the energy hub model can be expressed as:

[0065] L = CP;

[0066] Among them, L represents the energy output by the energy hub model; C represents the coupling coefficient; and P represents the energy input by the energy hub model.

[0067] Since the input and output of the energy hub model include various forms, they are converted into the following matrix representation:

[0068]

[0069] Among them, L m P represents the various forms of energy such as cold, heat, and electricity output by the coupling matrix, that is, the various forms of loads such as cold, heat, and electricity output; n Represents various forms of energy input into the coupling matrix, i.e. input cold, heat, electricity, gas and other energy; c mn Represents the coupling coefficient, which represents the ratio of the nth output energy to the mth input energy. Various forms of energy in the coupling matrix go from input to output mainly through two forms: energy distribution and energy conversion. Energy distribution means that the input energy is distributed to different energy conversion devices in a certain proportion, and energy conversion means that the input energy is converted into other forms of energy through energy conversion equipment, and there is a certain conversion efficiency. That is:

[0070] c nm =η nm v nm ;

[0071] Among them, η nm Indicates the conversion efficiency of the equipment, that is, the efficiency of converting the nth energy into the mth energy; v nm Indicates the coefficient of the nth energy source allocated to the conversion device corresponding to the mth energy source. nm The following constraints must be met:

[0072]

[0073] It should be noted that various forms of energy in the coupling matrix mainly go through two forms: energy distribution and energy conversion from input to output. Energy distribution means that the input energy is distributed to different energy conversion devices in a certain proportion, and energy conversion means that the input energy is converted by the energy conversion device. The distribution coefficient in the coupling matrix of other forms of energy can be set manually by changing the settings of the energy conversion device. At the same time, the conversion coefficient is not a constant, but a function of energy type, temperature, time, and equipment. Therefore, the matrix modeling of the energy hub is not a relatively easy set of linear equations. Different types of energy and the operating status of equipment may lead to more nonlinear elements in the coupling matrix. When considering factors such as energy storage equipment, user demand-side response, and electric vehicles, the modeling can also be extended by adding corresponding matrices containing energy storage, demand-side response coupling factors, and electric vehicle state selection functions to the matrix expression of the energy hub.

[0074] For step S2, the basic operating parameters of each major device in the energy exchange network are obtained. The basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption chiller operating parameters, electric chiller operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters.

[0075] In a preferred embodiment, the gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate; photovoltaic cell operating parameters include: solar radiation, solar incidence angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency; absorption refrigerator operating parameters include: thermal coefficient, hot steam specific enthalpy, condensed water specific enthalpy, cold storage tank energy self-consumption rate, cold storage tank heat storage efficiency, cold storage tank heat storage power, cold storage tank heat release efficiency and cold storage tank heat release power; electric refrigerator operating parameters include cooling coefficient; gas boiler operating parameters include gas boiler efficiency; waste heat boiler operating parameters include waste heat boiler efficiency and heat exchange efficiency of heat exchange device; battery operating parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity; thermal energy storage equipment operating parameters include: heat storage tank energy self-consumption rate, heat storage efficiency, heat storage tank heat storage power and heat storage tank heat release power.

[0076] For steps S3 and S4, in a preferred embodiment, the basic operating parameters and the energy hub model are used to construct an optimal scheduling model for the regional integrated energy system with the goal of minimizing the comprehensive operating cost of the regional integrated energy system, including: constructing a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model according to the gas turbine operating parameters, the photovoltaic cell operating parameters, the absorption chiller operating parameters, the electric chiller operating parameters, the gas boiler operating parameters, the waste heat boiler operating model, the heat exchange device operating model, the battery operating model, the heat storage tank operating model and the cold storage tank operating model; constructing a regional integrated energy system optimal scheduling model according to the gas turbine operating model, the photovoltaic cell operating model, the absorption chiller operating model, the electric chiller operating model, the gas boiler operating model, the waste heat boiler operating model, the heat exchange device operating model, the battery operating model, the heat storage tank operating model, the cold storage tank operating model and the energy hub model.

[0077] Specifically, when optimizing the dispatch of the regional integrated energy system, it is necessary to first analyze the operating characteristics of each device based on the energy hub model and the energy exchange network to determine the operating model of each device. The following is a specific description of the construction of the operating model of each device and the associated devices contained in each device.

[0078] The working principle of a gas turbine is to burn natural gas to generate high-temperature combustion gas, which expands and does work, thereby driving the impeller of the gas turbine to rotate, and then driving the generator set to generate electricity through the rapid rotation of the impeller. When constructing the operation model of the gas turbine, the present invention mainly studies the static characteristics between the fuel input to the gas turbine and the output power of the gas turbine. Therefore, the operation model of the gas turbine can be expressed as:

[0079] P gt =V gt ·H ng ·η gt ;

[0080] Q gt =V gt ·H ng ·(1-η gt -η loss );

[0081] Among them, P gt Indicates the gas turbine output power; Q gt Indicates the thermal power output of the gas turbine; H ng Indicates the calorific value of natural gas; V gtIndicates the natural gas consumption per unit time of the gas turbine, in m 3 ; η gt Represents the power generation efficiency of the gas turbine; η loss Indicates the gas turbine energy loss rate. In this operation model, V gt and H ng Parameters to be solved in the energy system optimization scheduling model.

[0082] Photovoltaic cells (i.e. Figure 2 The voltage that a photovoltaic (PV) monomer can generate is relatively small, and the smallest photovoltaic power generation unit is called a monomer, and the form of a photovoltaic cell composed of multiple solar cell monomers is called a module, and a photovoltaic cell composed of multiple modules is called an array. In this way, by arranging and packaging photovoltaic cells in series and parallel according to certain rules, a photovoltaic cell group with a certain voltage and power level is formed, and a photovoltaic panel is composed of a photovoltaic cell group. The photovoltaic cell used in the present invention is the photovoltaic cell panel described above. During operation, the photovoltaic cell is mainly affected by solar radiation, solar incident angle, panel area, the efficiency of the maximum power point tracking controller (MPPT controller) and the efficiency of the photovoltaic cell; wherein, the MPPT controller is the core component of the photovoltaic cell, which is used to control the current and voltage output of the photovoltaic cell to maximize the output power of the photovoltaic cell.

[0083] The operation model of a photovoltaic cell is as follows:

[0084] P PV =ξ×cosθ×η m ×A p ×η p ;

[0085] Among them, P PV represents the power generation of photovoltaic cells; ξ represents solar radiation, in W / ㎡; θ represents the solar incident angle; η m Indicates the efficiency of the MPPT controller; A p Represents the area of ​​the photovoltaic panel; η p represents the efficiency of the photovoltaic cell. In this operating model, P PV Parameters to be solved in the energy system optimization scheduling model.

[0086] The working principle of the absorption chiller requires that the heat input into the absorption chiller be used as power to drive the absorption chiller to operate, and the input heat is converted into cold energy for release. The operation model of the absorption chiller is as follows:

[0087]

[0088] Among them, Q AC It indicates the output cooling power of the absorption chiller when it is working, in kW; Indicates the thermal power required to drive the absorption chiller, in kW; COP AC It indicates the ratio between the input heat value and the output cooling value of the absorption chiller, generally known as the thermal coefficient; W s Indicates the input hot steam flow rate of the absorption chiller; h s1 represents the specific enthalpy of hot steam; h s2 represents the specific enthalpy of condensed water. In this operating model, W s Parameters to be solved in the energy system optimization scheduling model.

[0089] Electric refrigerators can be classified into piston compressors, screw compressors, centrifugal compressors, etc. according to their mechanical structures. The electric refrigerators of the present invention include screw refrigerators and centrifugal refrigerators. The operation model of the electric refrigerator is as follows:

[0090] Q EC =COP EC ·P EC ;

[0091] Among them, Q EC Indicates the output cooling power of the electric refrigerator, in kW; P EC Indicates the input power of the electric refrigerator in kW; COP EC The conversion coefficient between the input electrical energy and the output cooling energy of the electric refrigerator is called the cooling coefficient. EC Parameters to be solved in the energy system optimization scheduling model.

[0092] Gas boilers are often used as auxiliary equipment for balancing heat load supply and demand in integrated energy systems when the user's heat demand is higher than the amount that the combined energy equipment can provide, that is, higher than the amount that the gas turbine and waste heat boiler can provide, due to their clean raw materials, low emission pollution and high combustion efficiency. The output power of a gas boiler is mainly related to the load characteristics and output characteristics of the gas boiler. The operation model of a gas boiler is as follows:

[0093]

[0094] in, Indicates the output thermal power of the gas boiler, in kW; η GB Indicates the heating efficiency of the gas boiler; F GB Indicates the amount of fuel consumed by the gas boiler, in kW. In this operation model, F GB Parameters to be solved in the energy system optimization scheduling model.

[0095] Waste heat boilers can significantly improve the recovery and utilization rate of combustion heat and have a high energy saving rate. The operation mode of waste heat boilers can be summarized as a linear relationship between input heat and output heat. The operation model of waste heat boilers is as follows:

[0096] Q EB =Q EB,in ·η EB ;

[0097] Among them, Q EB Indicates the output thermal power of the waste heat boiler, in kW; Q EB,in Indicates the input heat power of the waste heat boiler, in kW; η EB Indicates the efficiency of the waste heat boiler. In this operation model, Q EB,in Parameters to be solved in the energy system optimization scheduling model.

[0098] The heat exchange device associated with the waste heat boiler transfers the steam heat generated by the integrated energy system into hot water, which is then provided to the load side. The operation model of the heat exchange device when it is working is as follows:

[0099] Q he =Q he,in ·η he ;

[0100] Among them, Q he Indicates the output thermal power of the heat exchange device, in kW; Q he,in Indicates the input thermal power of the heat exchange device, in kW; η he Indicates the heat transfer efficiency of the heat exchange device. In this operation model, Q he,in Parameters to be solved in the energy system optimization scheduling model.

[0101] When there is excess power generation from new energy equipment in the regional integrated energy system, the excess power can be stored in batteries. When there is a shortage of power on the load side, the batteries can supply the stored power to the load side. This can not only absorb the excess power output by new energy equipment, but also solve the problem of energy supply regulation to the load side, and also play a role in peak shaving and valley filling according to the characteristics of the load during the period. Figure 2 According to the classification of energy storage medium, it can be divided into mechanical energy storage, electrochemical energy storage, electrical energy storage and chemical energy storage. The operation model of the battery is as follows:

[0102]

[0103] Among them, SOC T+1 Indicates the battery storage state during the T+1 period; SOC T Indicates the battery storage state during the T period; μ eIndicates the energy self-consumption rate of the battery; Indicates battery charging efficiency; Indicates the battery charging power; Indicates the battery discharge efficiency; Indicates the battery discharge power; C b represents the battery capacity; ΔT represents the scheduling period, which is calculated based on T+1 and T. In this operation model, SOC T Parameters to be solved in the energy system optimization scheduling model.

[0104] When the heat load demand on the load side does not match the heat load provided by the heating equipment such as the gas turbine of the regional integrated energy system, that is, the load directly provided by the heating equipment such as the gas turbine, waste heat boiler, gas boiler, etc. cannot be directly provided to the load side for use, the heat storage tank ( Figure 2 The thermal energy storage in the heat storage tank can balance the heat load demand on the load side. The operation model of the heat storage tank is as follows:

[0105]

[0106] in, Indicates the heat storage status of the heat storage tank during the T+1 period; Indicates the heat storage state of the heat storage tank during period T; μ h Indicates the energy self-consumption rate of the heat storage tank; Indicates the thermal storage efficiency; Indicates thermal storage power; It indicates heat release efficiency; represents the heat release power; ΔT represents the scheduling period, which is calculated based on T+1 and T. In this operation model Parameters to be solved in the energy system optimization scheduling model.

[0107] The cold storage tank is associated with the absorption chiller, and the operation model of the cold storage tank is as follows:

[0108]

[0109] in, Indicates the heat storage status of the cold storage tank during the T+1 period; Indicates the heat storage state of the cold storage tank during period T; μ c Indicates the energy self-consumption rate of the cold storage tank; Indicates the heat storage efficiency of the cold storage tank; Indicates the heat storage power of the cold storage tank; Indicates the heat release efficiency of the cold storage tank; represents the heat release power of the cold storage tank; ΔT represents the scheduling period, which is calculated based on T+1 and T. In this operation model Parameters to be solved in the energy system optimization scheduling model.

[0110] Preferably, after determining the operation model of each major device based on the operation principle of each major device in the regional integrated energy system, it is necessary to further combine the energy hub model to construct the regional integrated energy system optimization scheduling model. When constructing the regional integrated energy system optimization scheduling model, it is necessary to consider the load characteristics of the area where the load supply network is located. The load characteristics are mainly determined by the regional type of the area and the electricity consumption type of each user in the area.

[0111] The load characteristics are considered because various functional building clusters constitute the main load usage of the regional energy system. Therefore, according to different building types, the usage characteristics of various types of loads such as cooling, heating, and electricity of various buildings can be studied separately. Then, according to the usage characteristics of various types of loads such as cooling, heating, and electricity of various buildings, the output of each major equipment in the regional comprehensive energy system can be adjusted.

[0112] It should be noted that the regional integrated energy system can be understood as a system composed of multiple integrated energy system sub-regions of different regional types, and the division of regional types is mainly based on the building type. The diversity of building functions is the main reason for the diversity of building types. It is precisely because different buildings have different functions and configurations that buildings are divided into various types. Therefore, the diversity of functions implemented by buildings is also the main reason affecting building loads. The present invention classifies buildings according to the following requirements: (1) First, the building load level is equivalent. The load level can be understood as the load usage, that is, the difference in usage of the same type of building load within the same time interval is required to be within the control range; (2) Secondly, the building load characteristics should be similar. The load characteristics can be understood as the load change trend, that is, the change characteristics of the same type of load over time, that is, the change curves of the loads of the same type of buildings are required to be basically similar in order to reflect the load characteristics of the same type of buildings; (3) Finally, the building load characteristic indicators are consistent. Considering general load characteristic indicators, general load characteristic indicators include daily maximum load, daily average load, daily load rate, daily minimum load rate, daily peak-to-valley difference, daily peak-to-valley difference rate and daily load curve; among them, daily maximum load is determined according to the maximum value of the daily hourly load; daily average load is determined according to the daily load divided by 24 hours; daily load rate is determined according to the ratio of daily average load to daily maximum load; daily minimum load rate is determined according to the ratio of daily minimum load to daily maximum load; daily peak-to-valley difference is determined according to the difference between daily maximum load and daily minimum load; daily peak-to-valley difference rate is determined according to the percentage value of daily peak-to-valley difference to daily maximum load; daily load curve is a load curve drawn in chronological order with hourly hourly load. According to the above classification basis and indicators, general buildings of regional energy systems can be divided into categories as shown in the following table:

[0113]

[0114] The power supply area is divided into six levels according to the different requirements for power reliability in the areas corresponding to different building types, namely: A+, A, B, C, D, and E. The A+ level area is generally an area with very high reliability requirements, the A level area has relatively low reliability requirements, and the E level has the lowest reliability requirements. Based on the division of power supply areas, it is extremely important to adjust the layout of distribution terminals in different power supply areas.

[0115] In a preferred embodiment, it also includes: obtaining the distribution terminal parameters of the area corresponding to the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminals to be installed and the unit installation cost of each terminal type; according to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost of the area corresponding to the load supply network; the regional terminal configuration model is solved to generate a terminal configuration plan for the area corresponding to the load supply network when the terminal investment cost and the terminal operation and maintenance cost are minimized; and the distribution terminal layout of the area corresponding to the load supply network is adjusted according to the terminal configuration plan.

[0116] Specifically, the regional type of the area corresponding to the load supply network of the energy hub model and the load characteristics of the corresponding area are obtained, and the existing distribution terminal parameters in the corresponding area are obtained. The distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminal to be installed, and the unit installation cost of each terminal type. According to the distribution terminal parameters, with the goal of minimizing the comprehensive investment cost of the terminal corresponding to the load supply network and the terminal operation and maintenance cost, a regional terminal configuration model is constructed. The regional terminal configuration model is as follows:

[0117] C ZD =C ZDtz +C ZDyw ;

[0118]

[0119] Among them, C ZD Represents the regional terminal configuration model; C ZDtz represents the regional terminal investment cost; C ZDyw represents the regional terminal operation and maintenance cost; n k represents the number of terminals in the planning area; r is the return on investment, which is 0.1; T ′ Plan the service life of the equipment; C ki It represents the investment cost required to install the i-th terminal type on a single switch in the region. The installation types in the present invention include no terminal, two remote controls and three remote controls. K is the three situations of installing terminals on the switch, namely, no terminal, two remote controls and three remote controls. β is the regional power distribution terminal operation and maintenance conversion rate.

[0120] It should be noted that the "two remotes" have the functions of telesignaling and telemetering, which can report fault information and measure voltage, current and other information, but they do not have the remote control function, that is, there is no need to install an electric device at the corresponding switch equipment. Most of them are composed of fault indicators and communication modules (generally using packet radio service technology GPRS), which can be mainly installed in the pole switches on overhead lines and the ring network cabinets of cables. After the fault occurs, the fault area can be quickly located, and the staff needs to go to the site in time to operate the corresponding switches to isolate the fault. The "three remotes" have the functions of telemetering, telesignaling and remote control. In addition to the functions of the two remotes, electric mechanisms and optical fiber communication channels are also installed at the switch positions to be connected, so that it has the ability of remote control. After the fault occurs, the "three remotes" terminal device can automatically control the switch to disconnect and quickly isolate the fault area. It is faster than the "two remotes" and has less impact, but the installation cost will increase accordingly. Generally, the "three remotes" function can be achieved by installing FTU on overhead lines and DTU on cable lines. An FTU can monitor a switch when used in conjunction with a set of corresponding equipment, while a DTU contains multiple terminal modules, each of which needs to be used in conjunction with a set of electric devices to monitor multiple switches.

[0121] The regional terminal configuration model is solved to generate a terminal configuration plan for the corresponding area of ​​the load supply network when the terminal investment cost and the terminal operation and maintenance cost are comprehensively minimized.

[0122] Preferably, it can be integrated into the regional integrated energy system optimization dispatching model. That is, based on the basic operating parameters, energy hub model and terminal configuration model, the regional integrated energy system optimization dispatching model is constructed with the goal of minimizing the comprehensive operating cost of the regional integrated energy system. At this time, the comprehensive operating cost of the constructed regional integrated energy system optimization dispatching model also includes terminal investment cost and terminal operation and maintenance cost. When the grid interaction cost and fuel consumption cost are further considered in the comprehensive operating cost, the regional integrated energy system optimization dispatching model shown below can be obtained:

[0123] minC=C inf +C grid +C f +C ZD ;

[0124]

[0125] Among them, minC represents the regional integrated energy system optimization scheduling model; C inf represents the initial investment cost of the system, that is, the cost when only the main equipment corresponding to the regional integrated energy system is considered; C grid represents the grid interaction cost; C frepresents the fuel consumption cost, including the fuel cost of the gas boiler, the user and the fuel cost of the gas turbine; C i P represents the initial investment cost per unit capacity of each major equipment; i Indicates the rated power of each major equipment; c b.t P represents the price of electricity purchased from the power grid during period t; b.t represents the power purchased from the power grid during period t; c s.t P represents the electricity price sold to the power grid during period t; s.t represents the power sold to the grid during period t; represents the fuel consumption rate of the i-th gas turbine during period t; represents the fuel consumption rate of the i-th gas boiler during period t; Indicates the user's fuel usage per unit time; represents the natural gas price during period t.

[0126] After constructing the above-mentioned regional integrated energy system optimization scheduling model, the above-mentioned regional integrated energy system optimization scheduling model is solved by the method of using particle swarm algorithm to improve K-Means clustering centroid extracted by the present invention, and the optimization scheduling strategy of the regional integrated energy system is obtained. The optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal energy power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank, heat storage state of the cold storage tank and regional terminal configuration scheme associated with the load side.

[0127] It should be noted that the K-Means algorithm is an unsupervised partition clustering method. The basic idea of ​​K-Means clustering is to analyze the various forms of energy input to the power grid and select the input energy data set D = {d1, d2, …, d m ,…,d M}, the energy data set in the present invention is an initial value set of each parameter in the optimization scheduling strategy; according to the clustering needs, k initial cluster centers are randomly set, the Euclidean distance between each data in the data set and the cluster center is calculated, and the data set is divided with the goal of minimizing the sum of squares of the Euclidean distances within each cluster, and the cluster center position is further iterated and updated according to the division result until the cluster center no longer changes. At this time, the clustering result of the data set obtained is the optimization scheduling strategy. The clustering method of this method is as follows:

[0128]

[0129] Among them, k is the number of clusters obtained after setting clustering; D jis the data set of the jth cluster; is the i-th data in the j-th cluster; cen j is the class center of the jth cluster.

[0130] However, this traditional K-Means clustering is highly dependent on the position of the initial cluster center and has poor global search performance. Therefore, when the initial cluster center is randomly generated, it is easy to be premature and fall into the local optimum. Based on this, the present invention proposes to improve the generation mechanism of the K-Means clustering cluster center by using particle swarm optimization (PSO) to enhance the global search capability in the clustering process, thereby improving the accuracy of the generated optimization scheduling strategy when solving the regional integrated energy system optimization scheduling model.

[0131] The core of the particle swarm algorithm is to generate particles of a certain scale, and iteratively update the speed and position of each particle according to the following two formulas based on the fitness, so as to obtain the particle position with the best fitness. The particle position with the best fitness is the optimal solution.

[0132]

[0133] X i (l+1)=X i (l)+V i (l+1);

[0134] Among them, V i is the velocity of particle i; X i is the position of particle i; l is the number of iterations; w is the inertia coefficient weight; c1 and c2 are the self-learning factor and the other-learning factor, which represent the learning weight of particle i from its own historical optimal trajectory in previous iterations and the historical optimal trajectory of all particles in the world; rand1 and rand2 are random numbers distributed between [0,1]; is the position of particle i with the best fitness in all iterations; P i g,best is the position of the best fitness of all particles in all iterations.

[0135] In order to minimize the difference between data points of the same type and maximize the difference between different clusters when using the clustering algorithm, the present invention proposes a fitness function in the particle swarm algorithm optimization process as follows:

[0136]

[0137] Among them, CD j is the number of data points in the jth cluster; ∑dis jis the sum of the distances from all data points in the jth cluster to the cluster center; maxG is the fitness function value; f(i) is the fitness function of the i-th particle.

[0138] In summary, the present invention uses a particle swarm algorithm combined with a K-Means clustering algorithm to solve the problem, and the execution process includes the following steps:

[0139] Step S101: input the cluster k, particle swarm size M, maximum number of iterations L, and convergence judgment threshold λ.

[0140] Step S201: randomly determine k data and use them as particles P m Initial position, calculate particle fitness G i , initialize particle velocity and record individual optimal position P m,best .

[0141] Step S301: Calculate and update the best particle position P in the jth generation j g,best And the corresponding optimal fitness function And update the speed and position of each particle.

[0142] Step S401: Determination

[0143] Step S501: Output the best particle position as the initial K-Means clustering center.

[0144] Step S601: Perform K-Means clustering with the initial cluster centers determined in step S501 until all cluster centers no longer change.

[0145] Step S701: Output each cluster center and data partition result to obtain an optimized scheduling strategy.

[0146] For step S5, the corresponding equipment of the regional integrated energy system is optimized and scheduled using the parameter values ​​in the optimized scheduling strategy.

[0147] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0148] like Figure 3 As shown, an embodiment of the present invention provides a regional integrated energy system optimization scheduling device based on situation awareness, including: an energy hub model construction module, a data acquisition module, an optimization scheduling model construction module, an optimization scheduling model solving module and a scheduling module;

[0149] The energy hub model construction module is used to construct an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network;

[0150] The data acquisition module is used to acquire basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters;

[0151] The optimization scheduling model construction module is used to construct an optimization scheduling model for the regional comprehensive energy system based on the basic operating parameters and the energy hub model with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system;

[0152] The optimization scheduling model solving module is used to solve the optimization scheduling model of the regional comprehensive energy system to generate an optimization scheduling strategy for the regional comprehensive energy system when the comprehensive operation cost of the regional comprehensive energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank and heat storage state of the cold storage tank;

[0153] The scheduling module is used to schedule the regional integrated energy system using the optimized scheduling strategy.

[0154] In a preferred embodiment, the gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate; the photovoltaic cell operating parameters include: solar radiation, solar incidence angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency; the absorption refrigeration machine operating parameters include: thermal coefficient, hot steam specific enthalpy, condensed water specific enthalpy, cold storage tank energy self-consumption rate, cold storage tank heat storage efficiency, cold storage tank heat storage power, cold storage tank heat release efficiency and cold storage tank heat release power; the electric refrigerator operating parameters include cooling coefficient; the gas boiler operating parameters include gas boiler efficiency; the waste heat boiler operating parameters include waste heat boiler efficiency and heat exchange efficiency of heat exchange device; the battery operating parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity; the thermal energy storage device operating parameters include: heat storage tank energy self-consumption rate, heat storage efficiency, heat storage tank heat storage power and heat storage tank heat release power.

[0155] In a preferred embodiment, the regional integrated energy system optimization scheduling model is constructed based on the basic operating parameters and the energy hub model with the goal of minimizing the comprehensive operating cost of the regional integrated energy system, including: constructing a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model based on the gas turbine operating parameters, the photovoltaic cell operating parameters, the absorption chiller operating parameters, the electric chiller operating parameters, the gas boiler operating parameters, the waste heat boiler operating model, the heat exchange device operating model, the battery operating model, the heat storage tank operating model and the cold storage tank operating model; constructing a regional integrated energy system optimization scheduling model based on the gas turbine operating model, the photovoltaic cell operating model, the absorption chiller operating model, the electric chiller operating model, the gas boiler operating model, the waste heat boiler operating model, the heat exchange device operating model, the battery operating model, the heat storage tank operating model, the cold storage tank operating model and the energy hub model.

[0156] In a preferred embodiment, it also includes a terminal layout module; the terminal layout module is used to obtain the distribution terminal parameters of the area corresponding to the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminals to be installed and the unit installation cost of each terminal type; according to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost of the area corresponding to the load supply network; the regional terminal configuration model is solved to generate a terminal configuration plan for the area corresponding to the load supply network when the terminal investment cost and the terminal operation and maintenance cost are minimized; the distribution terminal layout of the area corresponding to the load supply network is adjusted according to the terminal configuration plan.

[0157] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0158] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0159] Based on the above method item embodiments, the present invention provides corresponding terminal device item embodiments.

[0160] An embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a method for optimizing and scheduling a regional integrated energy system based on situational awareness as described in any one of the present invention.

[0161] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0162] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0163] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0164] Based on the above method item embodiments, the present invention provides a corresponding storage medium item embodiment.

[0165] An embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a regional integrated energy system optimization and scheduling method based on situational awareness as described in any one of the present inventions.

[0166] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0167] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A regional integrated energy system optimization scheduling method based on situation awareness, characterized in that: include: Constructing an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network; Obtaining basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters; According to the basic operating parameters and energy hub model, an optimal dispatching model of the regional integrated energy system is constructed with the goal of minimizing the comprehensive operating cost of the regional integrated energy system; Solving the regional integrated energy system optimization scheduling model to generate an optimization scheduling strategy for the regional integrated energy system when the comprehensive operating cost of the regional integrated energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank, and heat storage state of the cold storage tank; The regional integrated energy system is dispatched using the optimized dispatching strategy.

2. A method for optimizing and dispatching a regional integrated energy system based on situational awareness as claimed in claim 1, characterized in that: The gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate; The photovoltaic cell operating parameters include: solar radiation, solar incident angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency; The absorption chiller operating parameters include: thermal coefficient, specific enthalpy of hot steam, specific enthalpy of condensed water, self-consumption rate of cold storage tank energy, heat storage efficiency of cold storage tank, heat storage power of cold storage tank, heat release efficiency of cold storage tank and heat release power of cold storage tank; The operating parameters of the electric refrigerator include the cooling coefficient; The gas boiler operating parameters include the efficiency of the gas boiler; The waste heat boiler operating parameters include the waste heat boiler efficiency and the heat exchange efficiency of the heat exchange device; The battery operation parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity; The operating parameters of the thermal energy storage equipment include: the energy self-consumption rate of the heat storage tank, the heat storage efficiency of the heat storage tank, the heat storage power of the heat storage tank and the heat release power of the heat storage tank.

3. A method for optimizing and dispatching a regional integrated energy system based on situational awareness as claimed in claim 2, characterized in that: According to the basic operating parameters and the energy hub model, with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system, a regional comprehensive energy system optimization scheduling model is constructed, including: According to the gas turbine operating parameters, photovoltaic cell operating parameters, absorption chiller operating parameters, electric chiller operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters, a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model are constructed; Based on the gas turbine operation model, photovoltaic cell operation model, absorption chiller operation model, electric chiller operation model, gas boiler operation model, waste heat boiler operation model, heat exchange device operation model, battery operation model, heat storage tank operation model, cold storage tank operation model and energy hub model, a regional integrated energy system optimization scheduling model is constructed.

4. A method for optimizing and dispatching a regional integrated energy system based on situational awareness as claimed in claim 1, characterized in that: Also includes: Obtaining the distribution terminal parameters of the area corresponding to the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminal to be installed, and the unit installation cost of each terminal type; According to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost corresponding to the load supply network; Solving the regional terminal configuration model to generate a terminal configuration plan for the corresponding area of ​​the load supply network when the terminal investment cost and the terminal operation and maintenance cost are comprehensively minimized; The terminal configuration scheme is used to adjust the layout of distribution terminals in the corresponding area of ​​the load supply network.

5. A regional integrated energy system optimization and scheduling device based on situational awareness, characterized in that: include: Energy hub model building module, data acquisition module, optimization scheduling model building module, optimization scheduling model solving module and scheduling module; The energy hub model construction module is used to construct an energy hub model of a regional integrated energy system; wherein the energy hub model includes an energy supply network, an energy exchange network and a load supply network; The data acquisition module is used to acquire basic operating parameters of the energy exchange network; wherein the basic operating parameters include: gas turbine operating parameters, photovoltaic cell operating parameters, absorption refrigerator operating parameters, electric refrigerator operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters; The optimization scheduling model construction module is used to construct an optimization scheduling model for the regional comprehensive energy system based on the basic operating parameters and the energy hub model with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system; The optimization scheduling model solving module is used to solve the optimization scheduling model of the regional comprehensive energy system to generate an optimization scheduling strategy for the regional comprehensive energy system when the comprehensive operation cost of the regional comprehensive energy system is minimized; wherein the optimization scheduling strategy includes: natural gas consumption per unit time of the gas turbine, natural gas calorific value, photovoltaic cell power generation, input hot steam flow of the absorption refrigerator, input electric power of the electric refrigerator, fuel consumption of the gas boiler, input thermal power of the waste heat boiler, input thermal power of the heat exchange device, battery power storage state, heat storage state of the heat storage tank and heat storage state of the cold storage tank; The scheduling module is used to schedule the regional integrated energy system using the optimized scheduling strategy.

6. A regional integrated energy system optimization and scheduling device based on situational awareness as claimed in claim 5, characterized in that: The gas turbine operating parameters include: gas turbine power generation efficiency and gas turbine energy loss rate; The photovoltaic cell operating parameters include: solar radiation, solar incident angle, maximum power point tracking controller efficiency, photovoltaic panel area and photovoltaic cell efficiency; The absorption chiller operating parameters include: thermal coefficient, specific enthalpy of hot steam, specific enthalpy of condensed water, self-consumption rate of cold storage tank energy, heat storage efficiency of cold storage tank, heat storage power of cold storage tank, heat release efficiency of cold storage tank and heat release power of cold storage tank; The operating parameters of the electric refrigerator include the cooling coefficient; The gas boiler operating parameters include the efficiency of the gas boiler; The waste heat boiler operating parameters include the waste heat boiler efficiency and the heat exchange efficiency of the heat exchange device; The battery operation parameters include: battery energy self-consumption rate, battery charging efficiency, battery charging power, battery discharge efficiency, battery discharge power and battery capacity; The operating parameters of the thermal energy storage equipment include: the energy self-consumption rate of the heat storage tank, the heat storage efficiency of the heat storage tank, the heat storage power of the heat storage tank and the heat release power of the heat storage tank.

7. A regional integrated energy system optimization and scheduling device based on situational awareness as claimed in claim 6, characterized in that: According to the basic operating parameters and the energy hub model, with the goal of minimizing the comprehensive operating cost of the regional comprehensive energy system, a regional comprehensive energy system optimization scheduling model is constructed, including: According to the gas turbine operating parameters, photovoltaic cell operating parameters, absorption chiller operating parameters, electric chiller operating parameters, gas boiler operating parameters, waste heat boiler operating parameters, battery operating parameters and thermal energy storage device operating parameters, a gas turbine operating model, a photovoltaic cell operating model, an absorption chiller operating model, an electric chiller operating model, a gas boiler operating model, a waste heat boiler operating model, a heat exchange device operating model, a battery operating model, a heat storage tank operating model and a cold storage tank operating model are constructed; Based on the gas turbine operation model, photovoltaic cell operation model, absorption chiller operation model, electric chiller operation model, gas boiler operation model, waste heat boiler operation model, heat exchange device operation model, battery operation model, heat storage tank operation model, cold storage tank operation model and energy hub model, a regional integrated energy system optimization scheduling model is constructed.

8. A regional integrated energy system optimization and scheduling device based on situational awareness as claimed in claim 5, characterized in that: Also includes terminal layout module; The terminal layout module is used to obtain the distribution terminal parameters of the corresponding area of ​​the load supply network of the energy hub model; wherein the distribution terminal parameters include: the number of regional distribution terminals, the number of regional switches, the type of terminal to be installed, and the unit installation cost of each terminal type; According to the distribution terminal parameters, a regional terminal configuration model is constructed with the goal of minimizing the comprehensive terminal investment cost and terminal operation and maintenance cost corresponding to the load supply network; Solving the regional terminal configuration model to generate a terminal configuration plan for the corresponding area of ​​the load supply network when the terminal investment cost and the terminal operation and maintenance cost are comprehensively minimized; The terminal configuration scheme is used to adjust the layout of distribution terminals in the corresponding area of ​​the load supply network.

9. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a regional integrated energy system optimization and scheduling method based on situational awareness as described in any one of claims 1 to 4.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a regional integrated energy system optimization and scheduling method based on situational awareness as described in any one of claims 1 to 4.

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