A risk-averse scheduling method and system for a geographically distributed energy coalition

Abstract

The present application belongs to the field of renewable energy grid connection technology, and discloses a risk avoidance scheduling method and system of a geographically distributed energy alliance. The method constructs an energy alliance self-balancing scheduling deterministic model with the aim of maximizing internal income by obtaining equipment parameters, meteorological parameters, load parameters and economic parameters. The energy alliance self-balancing scheduling deterministic model can provide a deterministic solution under accurate prediction value parameters based on actual data, thereby effectively guiding energy scheduling. The risk scheduling model established in combination with the information gap decision theory can cope with the uncertainty problem of line transmission congestion in the power transmission network, and provides an optimal risk avoidance scheduling strategy for the energy alliance. The use of the scheduling method significantly enhances the economy and robustness of the energy alliance when facing transmission congestion risks, and provides a scientific and effective solution for the energy management of third-party entities.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of renewable energy grid connection, and particularly relates to a risk-avoiding scheduling method and system of a geographically distributed energy alliance. BACKGROUND

[0002] Wind and light new energy has the characteristics of intermittency, volatility and randomness, and the reliable and efficient operation of a power system containing a high proportion of new energy faces great challenges. In this context, it is of great significance to improve the flexibility of the power system to cope with the large-scale integration of renewable energy equipment.

[0003] With the development of communication and Internet of Things technology, using flexible load to provide regulation services and demand response for the power system is a very promising way. Through a medium and long-term agreement, geographically distributed new energy power generation systems, flexible loads based on distributed energy systems, and large power users can form an energy alliance. Under direct load control, the demand side flexible load plays its flexible regulation role with the help of the distributed energy system, and the supply side station tracks renewable energy generation, so as to realize self-balancing within the energy alliance. However, the scheduling of the geographically distributed energy alliance relies on the power transmission network for power transmission. When new energy power generation is large, the system faces the risk of transmission congestion, and line congestion will lead to serious "curtailment of wind" and "curtailment of light", which is not conducive to the efficient use of new energy. The existing congestion relief methods are implemented by power system operators, which are not suitable for energy alliances of third-party entities.

[0004] Therefore, the existing congestion relief measures cannot effectively solve the uncertainty problem of line transmission congestion in the power transmission network, which greatly affects the economy and robustness of the scheduling of the energy alliance under the risk of transmission congestion. SUMMARY

[0005] The application aims to provide a risk-avoiding scheduling method and system of a geographically distributed energy alliance to solve the technical problem that the existing congestion relief measures cannot effectively solve the uncertainty problem of line transmission congestion in the power transmission network, which greatly affects the economy and robustness of the scheduling of the energy alliance under the risk of transmission congestion.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the application is as follows:

[0007] In a first aspect, the application provides a risk-avoiding scheduling method of a geographically distributed energy alliance, comprising:

[0008] obtaining device parameters, meteorological parameters, load parameters and economic parameters of a geographically distributed energy alliance; wherein the geographically distributed energy alliance comprises a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user;

[0009] A self-balancing scheduling deterministic model of the energy alliance is constructed based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the aim of maximizing internal benefits of the geographically distributed energy alliance;

[0010] The self-balancing scheduling deterministic model of the energy alliance is solved to obtain a deterministic solution under the predicted value parameters;

[0011] Based on the self-balancing scheduling deterministic model of the energy alliance, a risk scheduling model is established in combination with the information gap decision theory;

[0012] Based on the deterministic solution under the predicted value parameters, the risk scheduling model based on the information gap decision theory is solved to obtain an optimal risk-averse scheduling result of the geographically distributed energy alliance.

[0013] Preferably, the flexible controllable load takes a distributed energy system as a carrier, and the distributed energy system includes a combined heat and power device, an electricity-to-gas device, a heat recovery device, an electric heating boiler, an absorption chiller, a compression chiller, a gas storage tank, a heat storage tank, a cold storage tank and a battery energy storage system; the battery energy storage system, the electric heating boiler, the electricity-to-gas device and the compression chiller are connected through the same bus for connecting internal power loads of the flexible controllable load; a gas output port of the electricity-to-gas device is connected to an input port of the gas storage tank; the electricity-to-gas device and the combined heat and power device are connected to the heat recovery device; output ports of the electric heating boiler and the heat recovery device are connected to an input port of the heat storage tank; an output port of the heat storage tank is connected to an input port of the absorption chiller; the absorption chiller and the compression chiller are connected to an input port of the cold storage tank; the gas storage tank is connected to a gas load demand side, the heat storage tank is connected to a heat load demand side, and the cold storage tank is connected to a cold load demand side, for providing corresponding types of energy.

[0014] Preferably, the equipment parameters include operation parameters of a wind power generation system, a photovoltaic power generation system and the flexible controllable load;

[0015] The meteorological parameters include historical fluctuation factors of wind resources and historical fluctuation factors of light resources;

[0016] The load parameters include day-ahead predicted power load of a large power user, self-used hydrogen, electricity, cold and heat load of the flexible load, and day-ahead predicted node injection power information of each node of an external power grid;

[0017] The economic parameters include penalty fees of new energy power generation systems, operation fees of each energy equipment, time-of-use power prices and power supply and distribution prices;

[0018] The self-balancing scheduling deterministic model of the energy alliance includes an objective function, flexible load operation constraints, new energy power generation system operation constraints, power balance constraints and line transmission constraints.

[0019] Preferably, the objective function of the energy alliance self-balancing dispatch deterministic model is expressed as:

[0020]

[0021]

[0022]

[0023]

[0024]

[0025] in, represents the revenue from selling electricity; Revenue from selling electricity and power generation costs , flexible load operating costs , electricity transmission costs difference; t is the index of the running time period, is the total number of running hours; Indexing large electricity users, A collection of large electricity users; For the period t Time-of-use electricity prices, For large electricity users In the period t The electricity load;

[0026] represents the cost of electricity generation; is the index of the wind power system, A collection of wind power generation systems. is the index of the photovoltaic power generation system, It is a collection of photovoltaic power generation systems; are the penalty factors for wind power and photovoltaic power respectively, Wind power / photovoltaic power generation system in the time period t The fluctuation factor reflects the abundance of wind and light resources; Wind power / photovoltaic power generation system in the time period t installed capacity; Wind power / photovoltaic power generation system in the time period t The actual transmitted active power;

[0027] Indicates operating cost; is the gas purchase price, These are the operating costs of power-to-gas equipment / cogeneration equipment / energy storage equipment; are the volumes of gas purchased from the energy market and generated in power-to-gas plants, respectively; The amount of gas consumed for cogeneration equipment; Energy storage devices e Time t 0-1 variable for charge / discharge status;

[0028] represents the transmission cost; The unit price of network access fee, For the period t The amount of electricity transmitted through the power grid.

[0029] Preferably, the flexible load operation constraints of the energy alliance self-balancing scheduling deterministic model include power-to-gas equipment operation constraints, cogeneration equipment operation constraints, electric boiler operation constraints, absorption chiller operation constraints, compression chiller operation constraints, energy storage equipment operation constraints, and flexible load internal energy balance constraints;

[0030] The operation constraints of the new energy power generation system are expressed as:

[0031]

[0032]

[0033] The power balance constraint is expressed as:

[0034]

[0035]

[0036] in, For large electricity users, Renewable energy power generation system period t To large electricity users The amount of electricity sold, i.e. the electricity demand of large electricity users; is the set of external grid nodes, For the period t External Node The predicted value of injection power;

[0037] The line transmission constraint is expressed as:

[0038]

[0039]

[0040] in, For the period t line The transmission power, Separate lines for a wind power generation system for a photovoltaic power generation system for a flexible load for a large power consumer for an external node a power transmission distribution factor, a line set of the entire power grid; a transmission capacity upper limit of a line .

[0041] Preferably, the specific steps of establishing a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model, combined with the information gap decision theory, include:

[0042] transforming the energy alliance self-balancing scheduling deterministic model into a compact matrix form;

[0043] based on the compact matrix form of the energy alliance self-balancing scheduling deterministic model, establishing a prediction error envelope model of the external grid node injection power;

[0044] combined with the information gap decision theory and the prediction error envelope model of the external grid node injection power, a risk scheduling model is constructed, which is used to maximize the robustness of the energy alliance self-balancing scheduling deterministic model under transmission congestion risk.

[0045] Preferably, the risk scheduling model is simplified, and the simplified risk scheduling model is solved based on the deterministic solution under the prediction value parameter, to obtain the optimal risk avoidance scheduling result of the geographically distributed energy alliance.

[0046] In a second aspect, the present application provides a risk avoidance scheduling system for a geographically distributed energy alliance, comprising:

[0047] a parameter acquisition module for acquiring device parameters, meteorological parameters, load parameters and economic parameters of a geographically distributed energy alliance; wherein the geographically distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power consumer;

[0048] a first model construction module for constructing an energy alliance self-balancing scheduling deterministic model based on the device parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal revenue of the geographically distributed energy alliance;

[0049] a first model calculation module for solving the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under a prediction value parameter;

[0050] a second model construction module for establishing a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model, combined with the information gap decision theory;

[0051] A second model calculation module is configured to solve a risk scheduling model based on information gap decision theory based on the deterministic solution under the predicted value parameter, and obtain an optimal risk avoidance scheduling result of the geographic distributed energy alliance.

[0052] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the risk avoidance scheduling method of the geographic distributed energy alliance when executing the computer program.

[0053] In a fourth aspect, the present application provides a computer readable storage medium comprising a computer program, wherein the computer program is executable by a processor to implement the steps of the risk avoidance scheduling method of the geographic distributed energy alliance.

[0054] Compared with the prior art, the present application has the following beneficial effects:

[0055] The present application provides a risk avoidance scheduling method of a geographic distributed energy alliance, which acquires device parameters, meteorological parameters, load parameters and economic parameters, and constructs an energy alliance self-balancing scheduling deterministic model with the goal of maximizing internal revenue; the energy alliance self-balancing scheduling deterministic model can provide accurate deterministic solutions under predicted value parameters based on actual data, thereby effectively guiding energy scheduling; a risk scheduling model established in combination with information gap decision theory can cope with the uncertainty problem of line transmission congestion in a power transmission network, and provides an optimal risk avoidance scheduling strategy for the energy alliance. The present scheduling method not only improves the efficient utilization rate of new energy and improves the flexibility of power system operation, but also significantly enhances the economic efficiency and robustness of the energy alliance when facing transmission congestion risks, and provides a scientific and effective solution for energy management of third-party entities.

[0056] Preferably, in the present application, the composition and connection mode of the flexible load based on the distributed energy system are provided, which helps to more accurately evaluate the adjustment capacity and potential of the flexible load, thereby optimizing the internal scheduling of the energy alliance and improving the overall energy efficiency.

[0057] Preferably, in the present application, the specific contents of the device parameters, meteorological parameters, load parameters and economic parameters, and the components of the energy alliance self-balancing scheduling deterministic model are provided; the present application provides detailed data support and theoretical basis for the construction of the model, which helps the model to more accurately reflect the actual situation and improve the accuracy and reliability of the scheduling.

[0058] Preferably, in the present application, the objective function of the energy alliance self-balancing scheduling deterministic model comprehensively considers factors such as electricity selling revenue, power generation cost, flexible load operation cost, and electricity transmission fee; this helps the energy alliance to balance various costs while pursuing maximum internal revenue, and to maximize economic benefits.

[0059] Preferably, in the present application, the constraint conditions of the energy alliance self-balancing scheduling deterministic model include flexible load operation constraints, new energy power generation system operation constraints, power balance constraints, and line transmission constraints. These constraint conditions ensure the feasibility and safety of scheduling, and avoid equipment damage or power grid accidents caused by improper scheduling.

[0060] Preferably, in the present application, the energy alliance self-balancing scheduling deterministic model is transformed into a compact matrix form, and a prediction error envelope model of external power grid node injection power is established, and a risk scheduling model is constructed in combination with information gap decision theory. This helps to improve the robustness and adaptability of the model when facing transmission congestion risks, and ensures the reliability of scheduling.

[0061] Preferably, in the present application, the optimal risk-averse scheduling result of the geographically distributed energy alliance is obtained by simplifying the risk scheduling model and solving based on the deterministic solution under the predicted value parameter; this helps to quickly and accurately develop the optimal scheduling strategy in practical applications, and improves the operation efficiency and economic benefits of the energy alliance. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 The energy alliance typical structure plane topological graph and the flexible load internal typical structure schematic diagram provided for the embodiments of the present application;

[0063] Figure 2 The flowchart of the risk-averse scheduling method of the geographically distributed energy alliance provided for the embodiments of the present application;

[0064] Figure 3 The wind power provided for the embodiments of the present application;

[0065] Figure 4 The photovoltaic power provided for the embodiments of the present application;

[0066] Figure 5 The flexible load internal electric load provided for the embodiments of the present application;

[0067] Figure 6 The flexible load internal hydrogen load provided for the embodiments of the present application;

[0068] Figure 7 The flexible load internal heat load provided for the embodiments of the present application;

[0069] Figure 8The flexible load internal cold load provided for the embodiment of the present application;

[0070] Figure 9 The certain electric power large user electric load provided for the embodiment of the present application;

[0071] Figure 10 The external power grid injected power prediction value provided for the embodiment of the present application;

[0072] Figure 11 The flow chart of the risk avoidance scheduling method of the geographic distributed energy alliance provided by the present application;

[0073] Figure 12 The structural schematic diagram of the risk avoidance scheduling system of the geographic distributed energy alliance provided by the present application. DETAILED DESCRIPTION

[0074] Embodiment 1

[0075] As described in the background, at present, the scheduling of the geographic distributed energy alliance relies on the power transmission network for power transmission, when the new energy power generation is large, the system faces the risk of transmission congestion, and the line blockage will cause the system to appear serious 'abandonment of wind' and 'abandonment of light', which is not conducive to the efficient use of new energy. The existing method for relieving congestion is implemented by the power system operator, which is not suitable for the energy alliance of third-party entities.

[0076] In order to solve the above problems, the present application provides a risk avoidance scheduling method of a geographic distributed energy alliance. The method combines the characteristics of wind, light and new energy, considers the new structure of the energy alliance with new energy generation system, flexible load and large power user, and proposes a risk avoidance scheduling method of the energy alliance for the uncertainty of line transmission blockage in the power transmission network, thereby improving the economy and robustness of the energy alliance facing the risk of transmission blockage.

[0077] It can be seen that in order to improve the flexibility of the system, the present embodiment studies the scheduling problem of the energy alliance composed of geographically distributed new energy generation system, flexible load and large power user, proposes a collaborative scheduling model integrating multiple distributed resource operations, and uses information gap decision theory to consider the risk of transmission blockage. A risk avoidance scheduling method is proposed to handle the uncertainty of node injected power in the power transmission network, which provides a scientific idea for large-scale orderly access of new energy to the power grid and promotes the construction of clean and low-carbon new power system.

[0078] The present embodiment will be further explained and described in combination with the accompanying drawings:

[0079] As Figure 1As shown, the embodiment provides a geographical distributed energy alliance composed of a wind power system, a photovoltaic power system, a flexible controllable load and a power large user. Among them: the flexible controllable load takes the distributed energy system as a carrier, has internal electricity, cold, heat and gas load (hydrogen load) demand, and is composed of a combined heat and power device, an electricity-to-gas device, a heat recovery device, an electric heating boiler, an absorption refrigeration machine, a compression refrigeration machine, a gas storage tank, a heat storage tank, a cold storage tank and a battery energy storage system. The battery energy storage system, the electric heating boiler, the electricity-to-gas device and the compression refrigeration machine are connected through the same bus to cooperate and connect the internal electricity load of the flexible controllable load. The gas output port of the electricity-to-gas device is connected to the input port of the gas storage tank; the electricity-to-gas device and the combined heat and power device are connected to the heat recovery device at the same time; the output ports of the electric heating boiler and the heat recovery device are connected to the input port of the heat storage tank; the output port of the heat storage tank is connected to the input port of the absorption refrigeration machine; the outputs of the absorption refrigeration machine and the compression refrigeration machine are connected to the input port of the cold storage tank. The gas storage tank, the heat storage tank and the cold storage tank are respectively connected to the gas load, the heat load and the cold load demand side, and provide corresponding type energy for the flexible controllable load.

[0080] 1) The specific structural features of the geographical distributed energy alliance are as follows:

[0081] (1) The wind power system is composed of a wind turbine group, an inverter, a collection line and other auxiliary equipment, and can convert wind energy into electric energy;

[0082] (2) The photovoltaic power system is composed of a photovoltaic array, an inverter, a collection line and other auxiliary equipment, and can convert solar energy into electric energy;

[0083] (3) The battery energy storage system is composed of a battery pack, a battery management system, a power conversion system, a collection line and other auxiliary equipment, and is used for storage, conversion and release of electric energy;

[0084] (4) The combined heat and power device simultaneously generates electric power and heat, generates electricity with gas as raw material, and recovers heat discharged during electricity generation to supply heat load;

[0085] (5) The electricity-to-gas device is composed of a tank body, an anode and a cathode, and can generate gas by chemical reaction;

[0086] (6) The heat recovery device is used to recover heat energy generated during the operation of the electricity-to-gas device and the combined heat and power device, and then the recovered heat energy is introduced into the heat storage tank for storage;

[0087] (7) The electric heating boiler is a heat device for converting electric energy into heat energy, including necessary safety accessories, heating pipes, controllers, water pumps and the like, and can generate heat at room temperature and introduce it into the heat storage tank for storage;

[0088] (8) Absorption refrigeration machine is a refrigeration equipment that converts heat energy into cold energy, which can produce refrigeration at room temperature by using heat energy, relying on the action of absorber and generator group;

[0089] (9) Compression refrigeration machine is a refrigeration equipment that converts electrical energy into cold energy, including necessary safety accessories, condenser, throttle valve, etc., which can produce refrigeration at room temperature by using electrical energy;

[0090] (10) Gas storage tank is a pressure vessel for storing gas, which stores gas by high-pressure storage and is equipped with a compressor, including necessary safety accessories, pressure detection and display instruments, etc., which can quickly charge and discharge gas at room temperature to supply gas load inside the flexible controllable load;

[0091] (11) Heat storage tank is a container for storing liquid hot water, including necessary safety accessories, temperature detection and display instruments, etc., which can quickly charge and discharge hot water at room temperature to supply heat load inside the flexible controllable load.

[0092] (12) Cold storage tank is a container for storing liquid cold water, including necessary safety accessories, temperature detection and display instruments, etc., which can quickly charge and discharge cold water at room temperature to supply heat load inside the flexible controllable load.

[0093] 2) The specific operation characteristics of the geographical distributed energy alliance are as follows:

[0094] (1) Wind energy and solar energy are converted into electrical energy by wind power generation system and photovoltaic power generation system, and through direct load control technology (DLC), flexible controllable load tracks new energy output to achieve balance within the energy alliance.

[0095] (2) The electricity generated by wind power generation system and photovoltaic power generation system is transmitted to flexible load and power large user end through power network.

[0096] (3) The electricity transmitted through the power grid, the battery energy storage system and the electricity generated by the combined heat and power equipment can be input into the electric-gas equipment, electric heating boiler and compression refrigeration machine, respectively, to convert electricity into gas, heat and cold, and then store the converted energy in the corresponding energy storage device.

[0097] (3) In the case of implementing industrial peak-valley electricity price and provincial electricity transmission price in the power grid, flexible load can be used as demand side flexible resource to interact with wind and light new energy. Energy alliance pays electricity transmission cost to the power grid to realize the supply of new energy power generation system transmission electricity to flexible load and large power users. New energy power generation can obtain electricity sales revenue. The dispatching cost of flexible load, "abandoned wind and light" of new energy power generation system and electricity transmission cost are regarded as the cost of energy alliance. If the power transmitted through the power grid is sufficient, flexible load can change the power external characteristics by flexibly adjusting and changing the internal multi-medium energy storage to realize the tracking of new energy output. If the electricity that can be transmitted by the energy alliance is limited due to the congestion of the power grid, a large amount of "abandoned wind and light" of new energy power generation system cannot be avoided, and the demand of large power users needs to be met to ensure the revenue. Flexible load can generate electricity by purchasing gas, and can dispatch multiple types of energy production equipment and energy storage devices to meet the demand of the load.

[0098] As shown in Figure 2 The embodiment provides a risk-avoiding self-balancing scheduling method of a geographically distributed energy alliance, which aims to improve the congestion risk response capability of the energy alliance, and to meet the safe operation of the power system and the demand supply of each load, to track the new energy output by optimizing and scheduling the internal combined heat and power equipment, electric-gas conversion equipment, heat recovery device, electric heating boiler, absorption chiller, compression chiller, gas tank, heat tank, cold tank and battery energy storage system of the flexible load, so that more new energy power generation can be transmitted, and the economic optimization of the energy alliance scheduling under the congestion risk is realized. (Note that in this embodiment, the compressor is an auxiliary equipment of the gas tank, and its cost is calculated together with the gas tank, and it is not scheduled and operated alone), and the scheduling method specifically comprises the following steps:

[0099] S1: Obtain the related information required by the risk-avoiding scheduling method of a geographically distributed energy alliance, which specifically comprises:

[0100] (1) Equipment parameters, such as the operation parameters of wind power generation system, photovoltaic power generation system, combined heat and power equipment, electric-gas conversion equipment, heat recovery device, electric heating boiler, absorption chiller, compression chiller, gas tank, heat tank, cold tank, battery energy storage system and the like;

[0101] (2) Meteorological parameters, such as the historical fluctuation factors of wind and light resources;

[0102] (3) Load parameters, such as the day-ahead predicted electricity load of large power users, self-use hydrogen, electricity, cold and heat load of flexible load, and day-ahead predicted node injection power information of each node of external power grid;

[0103] (4) Economic parameters, such as the "abandoned wind and light" penalty cost of the new energy power generation system, the operation cost of each energy device, the time-of-use electricity price of the power grid, and the electricity transmission and distribution price.

[0104] S2: Based on the historical wind, light resource fluctuation factor, load parameter, device parameter and economic parameter in step 1, an energy alliance self-balancing scheduling deterministic model is constructed:

[0105] 1) Objective function

[0106] (1)

[0107] (2)

[0108] (3)

[0109] (4)

[0110] (5)

[0111] (1) The electricity selling revenue (formula (2)) is the electricity quantity transaction revenue of the new energy power generation system and the power large user. Wherein, represents the electricity selling revenue is the difference between the generation cost , the flexible load operation cost , the electricity transmission cost ; t is the index of the operation period, is the total number of operation periods; is the index of the power large user, is the set of power large users; is the time-of-use electricity price of period t , and is the electricity load of the power large user in period t .

[0112] (2) The generation cost (formula (3)) is the operation cost of the new energy power generation system due to abandoned wind and light. Wherein, is the index of the wind power generation system, is the set of wind power generation systems, is the index of the photovoltaic power generation system, is the set of photovoltaic power generation systems. are respectively the penalty factors of wind power / photovoltaic, are respectively the fluctuation factors of the wind power / photovoltaic power generation system in period t , reflecting the richness of wind and light resources; are respectively the fluctuation factors of the wind power / photovoltaic power generation system in period tthe installed capacity of the new energy power generation system; respectively the actual transmission active power of the wind power / photovoltaic power generation system in the time period t The operation cost of the new energy power generation system is the sum of the penalty factors and the curtailment amount, and the curtailment amount is the difference between the wind and light power generation amount and the actual transmission active power.

[0113] (3) The operation cost (formula (4)) is the sum of the operation cost of each energy device in the flexible load and the gas purchase cost. Among them, is the gas purchase unit price, respectively the operation cost of the electric-gas device / combined heat and power device / energy storage device; and respectively the gas amount purchased from the energy market and generated by the electric-gas device; is the gas amount consumed by the combined heat and power device; is the energy storage device e time period t 0-1 variable of the charging / discharging state.

[0114] (4) The transmission cost (formula (5)) is the over-grid fee generated by the transmission of the new energy power generation system through the external power grid. Among them, is the over-grid fee unit price, is the electric quantity transmitted through the power grid in the time period t .

[0115] 2) Flexible load operation constraints

[0116] The operation of the flexible load needs to meet a series of constraint conditions:

[0117] (1) Electric-gas device operation constraint

[0118] The electric-gas device can convert electric energy into gas through chemical reaction, and in its working process, electric energy will also be converted into heat energy, which is realized by a heat recovery device (note that the heat recovery device of the present application is used to recover the heat generated in the working process of the electric-gas device, and the related constraints are given together with the related devices that generate waste heat, and the operation constraints thereof are not given separately). The electric-gas and electric-heat conversion equations are:

[0119] (6)

[0120] (7)

[0121] Among them, respectively the electric-gas / electric-heat conversion efficiency; respectively the electric-gas / electric-heat conversion performance coefficient of the electric-gas device; is the electric quantity used by the electric-gas device in the time period t ; is the electric quantity used by the electric-gas device in the time periodt Heat energy is generated during the operation of the electric-gas conversion equipment.

[0122] In addition, the operation of the electric-gas conversion equipment is also subject to the capacity constraint of the equipment:

[0123] (8)

[0124] wherein, is the time period of the electric-gas conversion equipment t is a 0-1 variable of the working state; is the time period of the electric-gas conversion equipment t is the upper / lower limit of the electricity consumption of the electric-gas conversion equipment.

[0125] In order to avoid the simultaneous operation of the electric-gas conversion equipment and the cogeneration equipment, and the operation of the gas storage equipment is related to the operation state of the gas generation / consumption equipment, the operation of the electric-gas conversion equipment is subject to the following constraint:

[0126] (9)

[0127] wherein, is the time period of the gas storage equipment t is a 0-1 variable of the charging state.

[0128] (2) Operation constraint of the cogeneration equipment

[0129] The cogeneration equipment can generate electricity using gas as raw material, and the heat energy generated during the conversion process can be recycled. The gas-electricity / gas-heat conversion equation is:

[0130] (10)

[0131] (11)

[0132] wherein, is the time period of the cogeneration equipment t is the electric energy generated by the cogeneration equipment; is the gas-electricity / gas-heat conversion efficiency of the cogeneration equipment, respectively; is the gas-electricity / gas-heat conversion performance coefficient, respectively; is the time period of the cogeneration equipment t is the gas consumed by the electric-gas conversion equipment; is the time period of the cogeneration equipment t Heat energy is generated during the operation of the cogeneration equipment.

[0133] In addition, the operation of the cogeneration equipment is also subject to the capacity constraint of the equipment:

[0134] (12)

[0135] wherein, is the time period of the cogeneration equipmentt 0-1 variable of the on-state; is the time period t upper / lower limit of the electricity generated by the cogeneration plant.

[0136] Similarly, the operating state of the cogeneration plant is subject to the following constraint:

[0137] (13)

[0138] where: is the time period t 0-1 variable of the on-state.

[0139] (3) Operating constraint of the electric boiler

[0140] The electric boiler converts electricity into heat by heating water, and its electricity-heat conversion equation is:

[0141] (14)

[0142] where, is the time period t heat produced by the electric boiler; is the electricity-heat conversion efficiency of the electric boiler; is the time period t electricity consumed by the electric boiler.

[0143] In addition, the operation of the electric boiler is also subject to the capacity constraint of the device:

[0144] (15)

[0145] where, is the time period t upper limit of the heat produced by the electric boiler.

[0146] (4) Operating constraint of the absorption chiller

[0147] The absorption chiller realizes refrigeration with heat as the driving energy, and its heat-cold conversion equation is:

[0148] (16)

[0149] where, is the time period t cold produced by the absorption chiller; is the conversion efficiency of the absorption chiller; is the heat-cold conversion coefficient of performance; is the time period t heat consumed by the absorption chiller.

[0150] In addition, the absorption chiller operation is also subject to the capacity constraint of the device:

[0151] (17)

[0152] where, is the time period t The upper limit of the heat energy generated by the absorption chiller.

[0153] (5) Compression chiller operation constraint

[0154] The compression chiller uses electrical energy to achieve the refrigeration effect by compressing and relaxing the chiller, and its electrical-to-cold conversion equation is:

[0155] (18)

[0156] where, is the time period t The refrigeration capacity of the compression chiller; is the conversion efficiency of the compression chiller; is the heat-to-cold conversion performance coefficient; is the time period t The power consumption of the compression chiller.

[0157] In addition, the operation of the compression chiller is also subject to the capacity constraint of the device:

[0158] (19)

[0159] where, is the time period t The upper limit of the refrigeration capacity of the compression chiller

[0160] (6) Energy storage device operation constraint

[0161] Energy storage devices include battery storage, gas storage tanks, heat storage tanks, and cold storage tanks, which are electrical energy, gas, heat energy, and cold energy storage devices. The operation constraints of energy storage devices are written as general expressions, and the set of energy storage devices is denoted as , and the set elements represent battery storage, gas storage tanks, heat storage tanks, and cold storage tanks, respectively.

[0162] The energy storage device cannot be charged and discharged, and is limited by a single charge and discharge state: as follows:

[0163] (20)

[0164] (21)

[0165] Secondly, the operation of the energy storage device is also subject to the power constraint of the device:

[0166] (22)

[0167] (23)

[0168] where, are the time periods t energy storage devices e charging / discharging amounts; are the energy storage devices e upper limits of charging / discharging amounts.

[0169] In addition, each energy storage device satisfies the material flow balance equation and the energy storage capacity constraint of the energy system:

[0170] (24)

[0171] (25)

[0172] where, are the time periods t energy storage devices e the capacity state of the energy storage device, are the energy storage devices e charging / discharging efficiencies, are the time periods t energy storage devices e upper / lower limits of capacity.

[0173] To ensure that the energy storage states at the beginning and end of scheduling are the same, the energy storage device should also satisfy the following beginning and end energy storage state constraints:

[0174] (26)

[0175] (7) Internal energy balance constraint of flexible load

[0176] The flexible load has multiple types of energy inside, and its external characteristics are electric characteristics, which are expressed as:

[0177] (27)

[0178] where, is the internal electric load of the flexible load.

[0179] In addition, the multiple types of energy inside the flexible load are converted to each other, and the gas, heat, and cold energy subsystems satisfy the following energy balances, respectively:

[0180] (28)

[0181] (29)

[0182] (30)

[0183] where, respectively, the gas / heat / cold demand of flexible internal load.

[0184] 3) Operation constraints of new energy generation system

[0185] The system output of wind power generation system and photovoltaic power generation system is mainly determined by installed capacity and natural resource conditions. Wind power generation system and photovoltaic power generation system need to meet the active power output constraints as follows:

[0186] (31)

[0187] (32)

[0188] 4) Power balance constraint

[0189] The power grid connected by the geographical distributed energy alliance is referred to as the external power grid, and the power supply system of the geographical distributed energy alliance and the external power grid need to meet the electric power balance equation respectively:

[0190] (33)

[0191] (34)

[0192] wherein, is the set of large power users, is the time period of new energy generation system t to the large power users the amount of electricity sold, that is, the power demand of the large power users; is the set of external power grid nodes, is the time period t the injection power prediction value of external node .

[0193] 5) Line transmission constraint

[0194] The power transmission in the power grid is subject to line transmission safety constraints, and the line transmission power expression based on the power transmission distribution factor and the transmission capacity constraint are as follows:

[0195] (35)

[0196] (36)

[0197] wherein, is the transmission power of line t in the time period , respectively, line about wind power generation system / photovoltaic power generation system / flexible load / large power users / external nodes power transfer distribution factor of, line set of the entire power grid; upper limit of transmission capacity of line .

[0198] S3: Solve the energy alliance self-balancing scheduling deterministic model in step 2 to obtain the deterministic solution under the predicted value parameter.

[0199] S4: On the basis of the energy alliance self-balancing scheduling deterministic model, establish a risk scheduling model based on information gap decision theory (IGDT).

[0200] S401: To avoid redundancy of subsequent content, give the compact matrix form of the deterministic model:

[0201] (37)

[0202] s.t. (38)

[0203] (39)

[0204] (40)

[0205] (41)

[0206] (42)

[0207] wherein, predicted value , the objective function (37) corresponds to formula (1)-(5), 0-1 variable and continuous variable, respectively; formula (38) is the relevant constraint of variable x , corresponding to constraints (9), (13) and (21); formula (39) is the coupling constraint of variable x and variable y , corresponding to constraints (8), (12) and (22)-(23); formula (39) is the relationship between variable y and predicted value , corresponding to constraints (34) and (35), and formula (42) represents the remaining constraints in the deterministic model.

[0208] S402: Establish a predicted error envelope model of the external grid node injection power:

[0209] (43)

[0210] where, is the uncertain risk boundary, determines the deviation degree of the node power prediction value and the actual value According to the linear relationship between the node power and the line power according to formula (35), for the constant , the size of the power transmission congestion risk is directly determined by , The larger the value is, the higher the possibility of congestion is.

[0211] S403: Further, based on the information gap decision theory, a risk-averse scheduling model is constructed, which can maximize the robustness of the energy alliance scheduling model under the transmission congestion risk:

[0212] (44)

[0213] (45)

[0214] (46)

[0215] (47)

[0216] (48)

[0217] (49)

[0218] (50)

[0219] (51)

[0220] where, is the expected economic benefit under uncertainty, taking the maximum benefit value of the deterministic solution under the prediction value parameter, is a deviation factor lower than the expected benefit of the energy alliance (indicating the acceptance limit of the scheduling decision maker for the benefit lower than the expectation), defining formula (45) as a "lower bound of benefit" constraint, ensuring that the total benefit of the energy alliance scheduling is higher than the lower bound of benefit . Note that the risk scheduling model is actually a double-layer optimization problem. The upper-layer optimization problem is to maximize the target of the uncertain risk boundary while meeting the constraint conditions (45)-(49); the lower-layer optimization problem (51) takes into account the uncertain set to affect the calculation of the economic benefit of the energy alliance in the worst case.

[0221] S404: Further, the risk-averse scheduling model is simplified. Obviously, when the external node injection power reaches the risk critical value (i.e. ), the lowest economic benefit will be obtained, therefore, formula (45) and (48) can be equivalently replaced by the following formula, and then the double-layer optimization problem can be converted into a single-layer optimization form which is easier to solve:

[0222] (52)

[0223] (53)

[0224] It can be seen that formula (44), (46)-(47), (49)-(50) and (52)-(53) constitute a single-layer mixed integer optimization form of the risk-averse scheduling model.

[0225] S5: solving the energy alliance risk-averse scheduling model of step S4 to obtain the optimal risk-averse scheduling result of the energy alliance.

[0226] The scheduling method provided in the embodiment is implemented in detail as follows.

[0227] Taking an IEEE30 node system as an example, there are 30 nodes and 41 lines, Figure 1 is a schematic diagram of the connection between the energy alliance and the external power grid, three wind power systems and four photovoltaic power systems are set, which are respectively at nodes 6, 22, 25, 4, 5, 9 and 27. Two power users are at nodes 11 and 13, and the flexible load is at node 28. In the embodiment, the gas in the flexible controllable load is hydrogen, the electric-to-gas equipment is an electrolytic tank, the combined heat and power equipment is a fuel cell, and the gas tank is a hydrogen storage tank. The related information required by the risk-averse scheduling method of a geographical distributed energy alliance is obtained, and table 1-table 2 respectively show the main economic parameters of the internal energy conversion equipment and the energy storage equipment of the flexible load, and table 3 shows the time-of-use electricity price data of the region where the energy alliance is located, and the remaining parameters required for risk scheduling are shown in table 4.

[0228] Table 1 Main parameters of internal energy conversion equipment of flexible load

[0229]

[0230] Table 2 Main parameters of energy storage system

[0231]

[0232] Table 3 Time-of-use electricity price data

[0233]

[0234] Table 4 Remaining required parameters of the embodiment

[0235]

[0236] In addition to the above parameters, the output of the new energy power generation system is shown in Figure 3 The demand of each type of load inside the flexible load is shown in Figures 4-8 The load demand of two large power users is shown in Figure 9 There are 20 external nodes in total, and only the node injection power prediction values of randomly selected nodes 8, 14 and 15 are shown due to space limitations. Figure 10

[0237] 1) Test setting

[0238] Case1: Deterministic scheduling

[0239] Case2: Risk-averse scheduling

[0240] Based on the above example parameters, the deterministic scheduling Case1 (solving equations (37)-(42)) and the risk scheduling Case2 (solving the risk scheduling model obtained in step 4) mentioned in the steps are tested. In order to better compare the effectiveness of the invention method, a comparison case Case1# is set based on the deterministic scheduling model: the upper limit of transmission power and the lower limit of hydrogen purchase in Case1# are set as the scheduling results of Case1, and the node injection power value is set as the solving result of Case2 , and then equations (37)-(42) are solved.

[0241] 2) Test results

[0242] The example is solved using the method of the invention,

[0243]

[0244] The deterministic scheduling uses the predicted value for optimization scheduling, and the total income is 135217.32 yuan, at this time the flexible load does not generate hydrogen purchase cost, indicating that the power generation of wind power and photovoltaic completely meets the demand of the load, and realizes the balance inside the energy alliance. Compared with the deterministic scheduling, the over-network fee of the risk scheduling is reduced by 3034.94 yuan, and the abandoned electricity cost is increased by 4134.8 yuan, at this time the flexible load needs to purchase hydrogen from the energy market to meet the energy demand, and the hydrogen purchase cost is 12860.91 yuan, and the risk-averse scheduling income after considering the congestion risk is 16226.08 yuan lower than the deterministic scheduling.

[0245] ​​Further analysis of the results of Case 1 shows that the risk-averse scheduling method has advantages. When the energy alliance faces the congestion risk in Case 2, the revenue of the deterministic model scheduling is lower than that of the risk scheduling Case 2. Therefore, the risk-averse scheduling method based on IGDT can effectively hedge the line transmission congestion risk and has certain economic efficiency.

[0246] In summary, the risk-averse scheduling method of the geographic distributed energy alliance provided in the embodiment has the following advantages compared with the existing scheduling method or congestion mitigation measures:

[0247] In the scheduling method, the structure of the geographic distributed energy alliance is introduced for the first time, that is, through the protocol cooperation of the new energy generation system, the flexible controllable load and the power large user, the energy alliance with geographic distribution is formed. Secondly, the energy alliance self-balancing scheduling can be based on the direct load control technology to schedule the internal devices of the flexible load to track the new energy fluctuation, realize the energy balance in the energy alliance, and thus absorb the new energy. Compared with the general energy alliance, the distributed energy system is the carrier of the flexible controllable load, has internal multi-energy conversion devices and multi-medium energy storage systems, and can improve the user-side adjustment flexibility, so as to play an equivalent role of the flexible load in the energy alliance. When the power transmitted by the power grid is too much, the energy alliance can use its multi-energy conversion advantage to store the electric energy in various energy forms; when the electric energy transmitted to the flexible load is less, the flexible load can purchase gas from the energy market and use the gas to generate electricity to meet the load demand. Finally, the risk-averse scheduling model considering the transmission congestion uncertainty can ensure the economic efficiency of the energy alliance scheduling when the power grid is congested. The scheduling method provides a risk scheduling scheme for the transmission congestion uncertainty, and the use of the method can effectively improve the robustness and economic efficiency of the energy alliance scheduling under the transmission congestion risk.

[0248] Embodiment 2

[0249] As shown in Figure 11 , the embodiment provides a risk-averse scheduling method of a geographic distributed energy alliance, including the following steps:

[0250] Obtaining device parameters, meteorological parameters, load parameters and economic parameters of the geographic distributed energy alliance; wherein the geographic distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a power large user;

[0251] Based on the device parameters, the meteorological parameters, the load parameters and the economic parameters, a deterministic model of energy alliance self-balancing scheduling is constructed to maximize the internal revenue of the geographic distributed energy alliance;

[0252] Solving the deterministic model of energy alliance self-balancing scheduling to obtain a deterministic solution under the predicted value parameters;

[0253] a risk scheduling model is established based on the self-balancing scheduling deterministic model of the energy alliance and the information gap decision theory;

[0254] The risk scheduling model based on the information gap decision theory is solved based on the deterministic solution under the predicted value parameter, and an optimal risk-avoiding scheduling result of the geographically distributed energy alliance is obtained.

[0255] As shown in Figure 12 The embodiment also provides a risk-avoiding scheduling system of a geographically distributed energy alliance, which comprises: a parameter acquisition module, which is used to acquire device parameters, meteorological parameters, load parameters and economic parameters of the geographically distributed energy alliance; wherein the geographically distributed energy alliance comprises a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user; a first model construction module, which is used to construct a self-balancing scheduling deterministic model of the energy alliance based on the device parameters, the meteorological parameters, the load parameters and the economic parameters, with the aim of maximizing the internal revenue of the geographically distributed energy alliance; a first model calculation module, which is used to solve the self-balancing scheduling deterministic model of the energy alliance, and obtain a deterministic solution under a predicted value parameter; a second model construction module, which is used to establish a risk scheduling model based on the self-balancing scheduling deterministic model of the energy alliance and the information gap decision theory; and a second model calculation module, which is used to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameter, and obtain an optimal risk-avoiding scheduling result of the geographically distributed energy alliance.

[0256] The embodiment also provides a device, which comprises: a memory, which is used to store a computer program; and a processor, which is used to realize the steps of the risk-avoiding scheduling method of the geographically distributed energy alliance when executing the computer program.

[0257] The processor realizes the steps of the risk-avoiding scheduling method of the geographically distributed energy alliance when executing the computer program, for example: acquiring device parameters, meteorological parameters, load parameters and economic parameters of the geographically distributed energy alliance; wherein the geographically distributed energy alliance comprises a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user; constructing a self-balancing scheduling deterministic model of the energy alliance based on the device parameters, the meteorological parameters, the load parameters and the economic parameters, with the aim of maximizing the internal revenue of the geographically distributed energy alliance; solving the self-balancing scheduling deterministic model of the energy alliance, and obtaining a deterministic solution under a predicted value parameter; establishing a risk scheduling model based on the self-balancing scheduling deterministic model of the energy alliance and the information gap decision theory; and solving the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameter, and obtaining an optimal risk-avoiding scheduling result of the geographically distributed energy alliance.

[0258] Alternatively, the processor implements the functions of the modules in the above system when executing the computer program, for example: a parameter acquisition module, configured to acquire device parameters, meteorological parameters, load parameters, and economic parameters of a geographic distributed energy alliance; wherein the geographic distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load, and a large power user; a first model construction module, configured to construct an energy alliance self-balancing scheduling deterministic model based on the device parameters, the meteorological parameters, the load parameters, and the economic parameters, with the goal of maximizing internal revenue of the geographic distributed energy alliance; a first model calculation module, configured to solve the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under a predicted value parameter; a second model construction module, configured to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model and in combination with an information gap decision theory; and a second model calculation module, configured to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameter, to obtain an optimal risk-avoiding scheduling result of the geographic distributed energy alliance.

[0259] Illustratively, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a preset function, which are used to describe the execution process of the computer program in the risk-avoiding scheduling device of the geographic distributed energy alliance. For example, the computer program can be divided into a parameter acquisition module, a first model construction module, a first model calculation module, a second model construction module, and a second model calculation module; the specific functions of the modules are as follows: the parameter acquisition module is configured to acquire device parameters, meteorological parameters, load parameters, and economic parameters of a geographic distributed energy alliance; wherein the geographic distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load, and a large power user; the first model construction module is configured to construct an energy alliance self-balancing scheduling deterministic model based on the device parameters, the meteorological parameters, the load parameters, and the economic parameters, with the goal of maximizing internal revenue of the geographic distributed energy alliance; the first model calculation module is configured to solve the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under a predicted value parameter; the second model construction module is configured to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model and in combination with an information gap decision theory; and the second model calculation module is configured to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameter, to obtain an optimal risk-avoiding scheduling result of the geographic distributed energy alliance.

[0260] The risk-averse scheduling device of the geographically distributed energy alliance can be a desktop computer, a notebook, a palm computer, a cloud server, and the like. The risk-averse scheduling device of the geographically distributed energy alliance can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above are examples of the risk-averse scheduling device of the geographically distributed energy alliance, and do not constitute a limitation on the risk-averse scheduling device of the geographically distributed energy alliance, and can include more components than the above, or combine certain components, or different components, for example, the risk-averse scheduling device of the geographically distributed energy alliance can also include an input / output device, a network access device, a bus, and the like.

[0261] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, and the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, and the like. The processor is a control center of the risk-averse scheduling of the geographically distributed energy alliance, and connects various parts of the risk-averse scheduling device of the geographically distributed energy alliance through various interfaces and lines.

[0262] The memory can be used to store the computer programs and / or modules, and the processor realizes various functions of the risk-averse scheduling device of the geographically distributed energy alliance by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory.

[0263] The memory can mainly include a program storage area and a data storage area. The program storage area can store an operating system, at least one application required by a function (such as a sound playing function, an image playing function, and the like), and the like. The data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, and the like), and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0264] The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the risk-avoiding scheduling method of the geographical distributed energy alliance.

[0265] The modules / units of the risk-avoiding scheduling system of the geographical distributed energy alliance are stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products.

[0266] Based on the understanding, all or part of the processes of the risk-avoiding scheduling method of the geographical distributed energy alliance can also be completed by a computer program instructing related hardware, the computer program can be stored in a computer readable storage medium, and the computer program can implement the steps of the risk-avoiding scheduling method of the geographical distributed energy alliance when executed by a processor. The computer program includes computer program codes, which can be in the form of source codes, object codes, executable files or preset intermediate forms.

[0267] The computer readable storage medium can include any entity or device, recording medium, U disk, 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, etc. that can carry the computer program codes.

[0268] It should be noted that the content included in the computer readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to the legislation and patent practice, the computer readable storage medium does not include electric carrier signals and telecommunication signals.

[0269] The above embodiment is only one of the implementation manners of the technical scheme of the application, and the scope of the application claimed by the application is not limited to the embodiment, but also includes any changes, substitutions and other implementation manners easily thought by those skilled in the art within the technical scope disclosed by the application.

Claims

1. A risk-averse scheduling method for a geographically distributed energy alliance, characterized in that: include: Obtaining equipment parameters, meteorological parameters, load parameters, and economic parameters of a geographically distributed energy alliance, wherein the geographically distributed energy alliance includes wind power generation systems, photovoltaic power generation systems, flexible controllable loads, and large electricity users; Based on equipment parameters, meteorological parameters, load parameters and economic parameters, a deterministic model of self-balancing dispatch of the energy alliance is constructed with the goal of maximizing the internal benefits of the geographically distributed energy alliance. Solve the energy alliance self-balancing dispatch deterministic model and obtain the deterministic solution under the predicted value parameters; Based on the energy alliance self-balancing dispatch deterministic model and combined with information gap decision theory, a risk dispatch model is established; Based on the deterministic solution under the predicted value parameters, the risk scheduling model based on information gap decision theory is solved to obtain the optimal risk-averse scheduling result of the geographical distributed energy alliance; The equipment parameters include operating parameters of the wind power generation system, photovoltaic power generation system and flexible controllable load; The meteorological parameters include historical fluctuation factors of wind resources and historical fluctuation factors of light resources; The load parameters include the day-ahead forecasted electricity load of large power users, the self-used hydrogen, electricity, cooling and heating loads of flexible loads, and the day-ahead forecasted node injection power information of each node in the external power grid; The economic parameters include penalty costs of the new energy power generation system, operating costs of various energy equipment, time-of-use electricity prices of the power grid, and electricity transmission and distribution prices; The energy alliance self-balancing dispatch deterministic model includes an objective function, flexible load operation constraints, new energy power generation system operation constraints, power balance constraints and line transmission constraints; The objective function of the energy alliance self-balancing dispatch deterministic model is expressed as: in, represents the revenue from selling electricity; Revenue from selling electricity and power generation costs , flexible load operating costs , electricity transmission costs difference; t is the index of the running time period, is the total number of running hours; Indexing large electricity users, A collection of large electricity users; For the period t Time-of-use electricity prices, For large electricity users In the period t The electricity load; represents the cost of electricity generation; is the index of the wind power system, A collection of wind power generation systems. is the index of the photovoltaic power generation system, It is a collection of photovoltaic power generation systems; are the penalty factors for wind power and photovoltaic power respectively, Wind power / photovoltaic power generation system in the time period t The fluctuation factor reflects the abundance of wind and light resources; Wind power / photovoltaic power generation system in the time period t installed capacity; Wind power / photovoltaic power generation system in the time period t The actual transmitted active power; Indicates operating cost; is the gas purchase price, These are the operating costs of power-to-gas equipment / cogeneration equipment / energy storage equipment; are the volumes of gas purchased from the energy market and generated in power-to-gas plants, respectively; The amount of gas consumed for cogeneration equipment; Energy storage devices e Time t 0-1 variable for charge / discharge status; represents the transmission cost; The unit price of network access fee, For the period t The amount of electricity transmitted through the grid; The flexible load operation constraints of the energy alliance self-balancing scheduling deterministic model include power-to-gas equipment operation constraints, cogeneration equipment operation constraints, electric boiler operation constraints, absorption chiller operation constraints, compression chiller operation constraints, energy storage equipment operation constraints and flexible load internal energy balance constraints; The operation constraints of the new energy power generation system are expressed as: The power balance constraint is expressed as: in, For large electricity users, Renewable energy power generation system period t To large electricity users The amount of electricity sold, i.e. the electricity demand of large electricity users; is the set of external grid nodes, For the period t External Node The predicted value of injection power; The line transmission constraint is expressed as: in, For the period t line The transmission power, Separate lines About Wind Power Generation Systems / Photovoltaic power generation system / Flexible load / Large electricity users / External Node The power transfer distribution factor, is the collection of lines for the entire power grid; For the line The upper limit of transmission capacity.

2. The risk-avoidance scheduling method for a geographically distributed energy alliance according to claim 1, characterized in that: The flexible controllable load is based on a distributed energy system, which includes a cogeneration device, a power-to-gas device, a heat recovery device, an electric boiler, an absorption refrigerator, a compression refrigerator, a gas storage tank, a heat storage tank, a cold storage tank, and a battery energy storage system. The battery energy storage system, the electric boiler, the power-to-gas device, and the compression refrigerator are connected to each other through the same busbar and are used to connect the internal electrical load of the flexible controllable load. The gas output port of the power-to-gas device is connected to the input port of the gas storage tank. The power-to-gas device and the cogeneration device are connected to the heat recovery device at the same time. The output ports of the electric boiler and the heat recovery device are connected to the input port of the heat storage tank. The output port of the heat storage tank is connected to the input port of the absorption refrigerator. The outputs of the absorption refrigerator and the compression refrigerator are connected to the input port of the cold storage tank. The gas storage tank is connected to the gas load demand side, the heat storage tank is connected to the heat load demand side, and the cold storage tank is connected to the cold load demand side, so as to provide corresponding types of energy.

3. The risk-avoidance scheduling method for a geographically distributed energy alliance according to claim 1, characterized in that: The specific steps of establishing the risk scheduling model based on the energy alliance self-balancing scheduling deterministic model and combining the information gap decision theory include: Transform the energy alliance self-balancing dispatch deterministic model into a compact matrix form; Based on the energy alliance self-balancing dispatch deterministic model in compact matrix form, a prediction error envelope model of the power injected into the external grid node is established; Combining the information gap decision theory with the prediction error envelope model of the injected power of external grid nodes, a risk scheduling model is constructed. The risk scheduling model is used to maximize the robustness of the energy alliance self-balancing scheduling deterministic model under the risk of transmission congestion.

4. The risk-avoidance scheduling method for a geographically distributed energy alliance according to claim 1, characterized in that: The risk scheduling model is simplified and solved based on the deterministic solution under the predicted value parameters to obtain the optimal risk aversion scheduling result of the geographical distributed energy alliance.

5. A risk-avoidance scheduling system for a geographically distributed energy alliance, used to implement the steps of the risk-avoidance scheduling method for a geographically distributed energy alliance according to any one of claims 1 to 4, characterized in that: include: a parameter acquisition module for acquiring equipment parameters, meteorological parameters, load parameters, and economic parameters of a geographically distributed energy alliance, wherein the geographically distributed energy alliance includes wind power generation systems, photovoltaic power generation systems, flexible controllable loads, and large electricity users; The first model building module is used to build a self-balancing dispatch deterministic model of the energy alliance based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal benefits of the geographically distributed energy alliance; The first model calculation module is used to solve the energy alliance self-balancing dispatch deterministic model and obtain a deterministic solution under the predicted value parameters; The second model building module is used to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model and combined with the information gap decision theory; The second model calculation module is used to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameters, and obtain the optimal risk avoidance scheduling result of the geographical distributed energy alliance.

6. A device, characterized in that include: Memory for storing computer programs; A processor is configured to implement the steps of the risk avoidance scheduling method for a geographically distributed energy alliance as described in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the steps of the risk-averse scheduling method for a geographically distributed energy alliance as described in any one of claims 1 to 4.

Images